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      Ofsted ILACS Summary

      Disclaimer: This summary is built from scraped data direct from https://reports.ofsted.gov.uk/ published PDF inspection report files. As a result of the nuances|variance within the inspection report content or pdf encoding, we're noting some problematic data extraction for a small number of LAs*.
      *LA extraction issues: southend-on-sea, [overall, help_and_protection_grade,care_leavers_grade], nottingham,[inspection_framework, inspection_date], redcar and cleveland,[inspection_framework, inspection_date], knowsley,[inspector_name], stoke-on-trent,[inspector_name]
      Feedback on specific problems|inaccuracies|suggestions welcomed.*

      -

      Summary data last updated: 15 07 2024 11:49

      -

      LA inspections last updated: ['2733698_westmorland and furness - 12 july 2024', '80471_halton - 12 july 2024', '80483_leicestershire - 12 july 2024', '80493_ealing - 12 july 2024', '80532_northumberland - 12 july 2024', '80534_nottinghamshire - 12 july 2024', '80535_oldham - 12 july 2024', '80540_reading - 12 july 2024', '80547_rutland - 12 july 2024', '80570_telford & wrekin - 12 july 2024']

      +

      Summary data last updated: 25 07 2024 13:46

      +

      LA inspections last updated: ['80472_hampshire - 23 july 2024', '80487_barnet - 23 july 2024', '80495_greenwich - 16 july 2024', '80512_redbridge - 23 july 2024', '80556_south gloucestershire - 23 july 2024']

      @@ -679,15 +679,15 @@

      Ofsted ILACS Summary

      - + - - + + - + @@ -935,15 +935,15 @@

      Ofsted ILACS Summary

      - + - - - + + + + - @@ -1063,15 +1063,15 @@

      Ofsted ILACS Summary

      - - + + - - - - + + + - + + @@ -1271,15 +1271,15 @@

      Ofsted ILACS Summary

      - + - - + + + + - - @@ -1991,15 +1991,15 @@

      Ofsted ILACS Summary

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a/output.log b/output.log index 77a0dff..49c3053 100644 --- a/output.log +++ b/output.log @@ -1,4109 +1,4109 @@ -2024-07-15 10:42:31,439 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:42:31,441 - built Dictionary<1216 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2696 corpus positions) -2024-07-15 10:42:31,444 - Dictionary lifecycle event {'msg': "built Dictionary<1216 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2696 corpus positions)", 'datetime': '2024-07-15T10:42:31.441802', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:31,446 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:42:31,446 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:42:31,446 - using serial LDA version on this node -2024-07-15 10:42:31,447 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:42:31,447 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:42:31,451 - -8.102 per-word bound, 274.8 perplexity estimate based on a held-out corpus of 1 documents with 2696 words -2024-07-15 10:42:31,451 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:42:31,452 - topic #0 (0.333): 0.013*"’" + 0.007*"leaders" + 0.005*"Barnsley" + 0.005*"practice" + 0.005*"within" + 0.004*"needs" + 0.004*"plans" + 0.004*"response" + 0.004*"15" + 0.004*"experiences" -2024-07-15 10:42:31,452 - topic #1 (0.333): 0.023*"’" + 0.011*"needs" + 0.008*"leaders" + 0.007*"within" + 0.006*"Barnsley" + 0.006*"practice" + 0.005*"plans" + 0.004*"senior" + 0.004*"response" + 0.004*"family" -2024-07-15 10:42:31,453 - topic #2 (0.333): 0.016*"’" + 0.007*"leaders" + 0.006*"needs" + 0.006*"practice" + 0.005*"within" + 0.005*"Barnsley" + 0.004*"11" + 0.004*"2023" + 0.004*"senior" + 0.004*"response" -2024-07-15 10:42:31,453 - topic diff=0.812192, rho=1.000000 -2024-07-15 10:42:31,453 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:42:31.453438', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:31,455 - Failed to import jpype dependencies. Fallback to subprocess. -2024-07-15 10:42:31,455 - No module named 'jpype' -2024-07-15 10:42:32,368 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:42:32,368 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:32,368 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:42:32,368 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:32,369 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:42:32,369 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:32,369 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:42:32,369 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:32,369 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:42:32,369 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:32,370 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:42:32,370 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:33,746 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:42:33,749 - built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2085 corpus positions) -2024-07-15 10:42:33,749 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2085 corpus positions)", 'datetime': '2024-07-15T10:42:33.749170', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:33,750 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:42:33,750 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:42:33,750 - using serial LDA version on this node -2024-07-15 10:42:33,750 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:42:33,751 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:42:33,754 - -8.026 per-word bound, 260.6 perplexity estimate based on a held-out corpus of 1 documents with 2085 words -2024-07-15 10:42:33,754 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:42:33,755 - topic #0 (0.333): 0.019*"’" + 0.009*"well" + 0.007*"practice" + 0.006*"needs" + 0.005*"leaders" + 0.005*"impact" + 0.005*"effective" + 0.005*"receive" + 0.004*"2022" + 0.004*"East" -2024-07-15 10:42:33,756 - topic #1 (0.333): 0.014*"’" + 0.007*"well" + 0.007*"needs" + 0.006*"leaders" + 0.005*"plans" + 0.004*"clear" + 0.004*"North" + 0.004*"‘" + 0.004*"Somerset" + 0.004*"28" -2024-07-15 10:42:33,756 - topic #2 (0.333): 0.020*"’" + 0.010*"well" + 0.006*"plans" + 0.005*"needs" + 0.005*"practice" + 0.005*"Bath" + 0.005*"East" + 0.005*"4" + 0.005*"effective" + 0.005*"March" -2024-07-15 10:42:33,756 - topic diff=0.745017, rho=1.000000 -2024-07-15 10:42:33,756 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:42:33.756639', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:34,653 - Inspection date 2022-02-28 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:42:34,653 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:34,654 - Inspection date 2022-02-28 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:42:34,654 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:34,654 - Inspection date 2022-02-28 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:42:34,654 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:34,654 - Inspection date 2022-02-28 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:42:34,654 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:34,655 - Inspection date 2022-02-28 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:42:34,655 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:34,655 - Inspection date 2022-02-28 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:42:34,655 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:36,303 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:42:36,308 - built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2585 corpus positions) -2024-07-15 10:42:36,308 - Dictionary lifecycle event {'msg': "built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2585 corpus positions)", 'datetime': '2024-07-15T10:42:36.308327', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:36,310 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:42:36,310 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:42:36,310 - using serial LDA version on this node -2024-07-15 10:42:36,311 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:42:36,311 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:42:36,321 - -8.113 per-word bound, 276.9 perplexity estimate based on a held-out corpus of 1 documents with 2585 words -2024-07-15 10:42:36,322 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:42:36,324 - topic #0 (0.333): 0.023*"’" + 0.007*"ensure" + 0.006*"plans" + 0.006*"needs" + 0.005*"Bedford" + 0.005*"well" + 0.005*"education" + 0.005*"supported" + 0.004*"progress" + 0.004*"2021" -2024-07-15 10:42:36,324 - topic #1 (0.333): 0.015*"’" + 0.006*"needs" + 0.006*"well" + 0.005*"family" + 0.005*"ensure" + 0.004*"supported" + 0.004*"Bedford" + 0.004*"good" + 0.004*"plans" + 0.004*"education" -2024-07-15 10:42:36,325 - topic #2 (0.333): 0.017*"’" + 0.008*"needs" + 0.007*"ensure" + 0.006*"well" + 0.006*"good" + 0.006*"progress" + 0.005*"Bedford" + 0.005*"supported" + 0.005*"Borough" + 0.005*"plans" -2024-07-15 10:42:36,325 - topic diff=0.789570, rho=1.000000 -2024-07-15 10:42:36,325 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:42:36.325606', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:37,460 - Inspection date 2021-11-15 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:42:37,460 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:37,461 - Inspection date 2021-11-15 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:42:37,461 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:37,461 - Inspection date 2021-11-15 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:42:37,461 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:37,462 - Inspection date 2021-11-15 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:42:37,462 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:37,462 - Inspection date 2021-11-15 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:42:37,462 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:37,463 - Inspection date 2021-11-15 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:42:37,463 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:39,031 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:42:39,033 - built Dictionary<1065 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2378 corpus positions) -2024-07-15 10:42:39,033 - Dictionary lifecycle event {'msg': "built Dictionary<1065 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2378 corpus positions)", 'datetime': '2024-07-15T10:42:39.033817', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:39,034 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:42:39,035 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:42:39,035 - using serial LDA version on this node -2024-07-15 10:42:39,035 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:42:39,035 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:42:39,039 - -7.963 per-word bound, 249.5 perplexity estimate based on a held-out corpus of 1 documents with 2378 words -2024-07-15 10:42:39,039 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:42:39,040 - topic #0 (0.333): 0.019*"’" + 0.011*"needs" + 0.007*"effective" + 0.007*"well" + 0.007*"progress" + 0.006*"plans" + 0.006*"Birmingham" + 0.006*"trust" + 0.006*"3" + 0.005*"leaders" -2024-07-15 10:42:39,041 - topic #1 (0.333): 0.009*"’" + 0.007*"needs" + 0.004*"Birmingham" + 0.004*"well" + 0.003*"February" + 0.003*"protection" + 0.003*"plans" + 0.003*"effective" + 0.003*"trust" + 0.003*"ensure" -2024-07-15 10:42:39,041 - topic #2 (0.333): 0.013*"’" + 0.008*"needs" + 0.007*"effective" + 0.007*"well" + 0.007*"plans" + 0.005*"trust" + 0.005*"risk" + 0.005*"appropriate" + 0.005*"Birmingham" + 0.005*"progress" -2024-07-15 10:42:39,041 - topic diff=0.827233, rho=1.000000 -2024-07-15 10:42:39,041 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:42:39.041595', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:40,046 - Inspection date 2023-02-20 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:42:40,046 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:40,046 - Inspection date 2023-02-20 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:42:40,047 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:40,047 - Inspection date 2023-02-20 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:42:40,047 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:40,047 - Inspection date 2023-02-20 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:42:40,047 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:40,047 - Inspection date 2023-02-20 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:42:40,048 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:40,048 - Inspection date 2023-02-20 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:42:40,048 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:41,496 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:42:41,498 - built Dictionary<1055 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2353 corpus positions) -2024-07-15 10:42:41,499 - Dictionary lifecycle event {'msg': "built Dictionary<1055 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2353 corpus positions)", 'datetime': '2024-07-15T10:42:41.499130', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:41,500 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:42:41,500 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:42:41,500 - using serial LDA version on this node -2024-07-15 10:42:41,501 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:42:41,501 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:42:41,505 - -7.965 per-word bound, 249.9 perplexity estimate based on a held-out corpus of 1 documents with 2353 words -2024-07-15 10:42:41,505 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:42:41,506 - topic #0 (0.333): 0.012*"’" + 0.010*"practice" + 0.009*"needs" + 0.007*"impact" + 0.007*"Darwen" + 0.007*"well" + 0.006*"Blackburn" + 0.005*"quality" + 0.005*"4" + 0.005*"planning" -2024-07-15 10:42:41,506 - topic #1 (0.333): 0.012*"’" + 0.006*"Blackburn" + 0.006*"quality" + 0.005*"effective" + 0.005*"Darwen" + 0.005*"needs" + 0.005*"practice" + 0.005*"impact" + 0.005*"plans" + 0.005*"well" -2024-07-15 10:42:41,507 - topic #2 (0.333): 0.017*"’" + 0.009*"quality" + 0.008*"needs" + 0.007*"Blackburn" + 0.006*"Darwen" + 0.006*"well" + 0.005*"impact" + 0.005*"practice" + 0.005*"result" + 0.005*"planning" -2024-07-15 10:42:41,507 - topic diff=0.819021, rho=1.000000 -2024-07-15 10:42:41,507 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:42:41.507372', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:42,514 - Inspection date 2022-01-24 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:42:42,514 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:42,515 - Inspection date 2022-01-24 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:42:42,515 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:42,515 - Inspection date 2022-01-24 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:42:42,515 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:42,515 - Inspection date 2022-01-24 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:42:42,516 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:42,516 - Inspection date 2022-01-24 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:42:42,516 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:42,516 - Inspection date 2022-01-24 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:42:42,516 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:44,171 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:42:44,173 - built Dictionary<1037 unique tokens: ['0', '0161', '030', '0300', '1']...> from 1 documents (total 2392 corpus positions) -2024-07-15 10:42:44,173 - Dictionary lifecycle event {'msg': "built Dictionary<1037 unique tokens: ['0', '0161', '030', '0300', '1']...> from 1 documents (total 2392 corpus positions)", 'datetime': '2024-07-15T10:42:44.173599', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:44,175 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:42:44,175 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:42:44,175 - using serial LDA version on this node -2024-07-15 10:42:44,175 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:42:44,175 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:42:44,179 - -7.923 per-word bound, 242.7 perplexity estimate based on a held-out corpus of 1 documents with 2392 words -2024-07-15 10:42:44,179 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:42:44,180 - topic #0 (0.333): 0.020*"’" + 0.011*"needs" + 0.009*"well" + 0.008*"Blackpool" + 0.006*"practice" + 0.005*"progress" + 0.005*"16" + 0.005*"plans" + 0.005*"supported" + 0.005*"experiences" -2024-07-15 10:42:44,181 - topic #1 (0.333): 0.017*"’" + 0.010*"needs" + 0.008*"Blackpool" + 0.007*"well" + 0.006*"effective" + 0.005*"team" + 0.005*"quality" + 0.005*"carers" + 0.004*"supported" + 0.004*"understand" -2024-07-15 10:42:44,181 - topic #2 (0.333): 0.013*"’" + 0.010*"well" + 0.010*"needs" + 0.006*"Blackpool" + 0.006*"effective" + 0.006*"plans" + 0.005*"practice" + 0.005*"16" + 0.005*"quality" + 0.005*"supported" -2024-07-15 10:42:44,181 - topic diff=0.828279, rho=1.000000 -2024-07-15 10:42:44,181 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:42:44.181528', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:45,187 - Inspection date 2022-12-05 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:42:45,187 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:45,187 - Inspection date 2022-12-05 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:42:45,187 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:45,187 - Inspection date 2022-12-05 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:42:45,187 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:45,188 - Inspection date 2022-12-05 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:42:45,188 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:45,188 - Inspection date 2022-12-05 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:42:45,188 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:45,188 - Inspection date 2022-12-05 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:42:45,188 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:47,103 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:42:47,105 - built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2055 corpus positions) -2024-07-15 10:42:47,105 - Dictionary lifecycle event {'msg': "built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2055 corpus positions)", 'datetime': '2024-07-15T10:42:47.105220', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:47,106 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:42:47,106 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:42:47,106 - using serial LDA version on this node -2024-07-15 10:42:47,106 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:42:47,107 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:42:47,110 - -7.912 per-word bound, 240.8 perplexity estimate based on a held-out corpus of 1 documents with 2055 words -2024-07-15 10:42:47,110 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:42:47,111 - topic #0 (0.333): 0.015*"’" + 0.008*"plans" + 0.007*"Bolton" + 0.007*"needs" + 0.007*"well" + 0.005*"supported" + 0.005*"experiences" + 0.005*"need" + 0.005*"strong" + 0.004*"planning" -2024-07-15 10:42:47,112 - topic #1 (0.333): 0.022*"’" + 0.011*"needs" + 0.010*"Bolton" + 0.010*"well" + 0.007*"plans" + 0.006*"effective" + 0.006*"supported" + 0.005*"need" + 0.005*"planning" + 0.005*"timely" -2024-07-15 10:42:47,112 - topic #2 (0.333): 0.018*"’" + 0.008*"needs" + 0.007*"plans" + 0.006*"well" + 0.005*"11" + 0.005*"Bolton" + 0.005*"planning" + 0.004*"supported" + 0.004*"15" + 0.004*"need" -2024-07-15 10:42:47,112 - topic diff=0.791425, rho=1.000000 -2024-07-15 10:42:47,112 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:42:47.112468', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:48,340 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:42:48,340 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:48,340 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:42:48,340 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:48,341 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:42:48,341 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:48,341 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:42:48,341 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:48,341 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:42:48,341 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:48,342 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:42:48,342 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:49,620 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:42:49,622 - built Dictionary<1035 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2004 corpus positions) -2024-07-15 10:42:49,622 - Dictionary lifecycle event {'msg': "built Dictionary<1035 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2004 corpus positions)", 'datetime': '2024-07-15T10:42:49.622695', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:49,623 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:42:49,623 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:42:49,624 - using serial LDA version on this node -2024-07-15 10:42:49,624 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:42:49,624 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:42:49,628 - -8.031 per-word bound, 261.5 perplexity estimate based on a held-out corpus of 1 documents with 2004 words -2024-07-15 10:42:49,628 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:42:49,629 - topic #0 (0.333): 0.013*"’" + 0.006*"practice" + 0.005*"progress" + 0.005*"Bournemouth" + 0.005*"time" + 0.005*"6" + 0.005*"quality" + 0.005*"Poole" + 0.005*"However" + 0.004*"risk" -2024-07-15 10:42:49,629 - topic #1 (0.333): 0.023*"’" + 0.007*"quality" + 0.006*"practice" + 0.006*"progress" + 0.005*"17" + 0.005*"well" + 0.005*"time" + 0.005*"risk" + 0.005*"impact" + 0.004*"Poole" -2024-07-15 10:42:49,629 - topic #2 (0.333): 0.014*"’" + 0.005*"quality" + 0.005*"Christchurch" + 0.005*"Bournemouth" + 0.004*"6" + 0.004*"However" + 0.004*"practice" + 0.004*"December" + 0.004*"impact" + 0.004*"well" -2024-07-15 10:42:49,629 - topic diff=0.757402, rho=1.000000 -2024-07-15 10:42:49,630 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:42:49.630059', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:51,299 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:42:51,299 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:51,299 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:42:51,299 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:51,299 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:42:51,300 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:51,300 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:42:51,300 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:51,300 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:42:51,300 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:51,300 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:42:51,301 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:52,532 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:42:52,534 - built Dictionary<900 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1846 corpus positions) -2024-07-15 10:42:52,535 - Dictionary lifecycle event {'msg': "built Dictionary<900 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1846 corpus positions)", 'datetime': '2024-07-15T10:42:52.535192', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:52,536 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:42:52,536 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:42:52,537 - using serial LDA version on this node -2024-07-15 10:42:52,537 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:42:52,537 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:42:52,541 - -7.855 per-word bound, 231.6 perplexity estimate based on a held-out corpus of 1 documents with 1846 words -2024-07-15 10:42:52,541 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:42:52,542 - topic #0 (0.333): 0.022*"’" + 0.008*"Bracknell" + 0.007*"needs" + 0.007*"good" + 0.006*"well" + 0.006*"Forest" + 0.006*"positive" + 0.006*"effective" + 0.006*"quality" + 0.005*"need" -2024-07-15 10:42:52,542 - topic #1 (0.333): 0.009*"’" + 0.007*"quality" + 0.007*"risk" + 0.006*"needs" + 0.005*"Forest" + 0.005*"Bracknell" + 0.005*"good" + 0.005*"provided" + 0.005*"carers" + 0.005*"plans" -2024-07-15 10:42:52,543 - topic #2 (0.333): 0.016*"’" + 0.008*"Forest" + 0.008*"risk" + 0.006*"needs" + 0.006*"Bracknell" + 0.006*"effective" + 0.006*"progress" + 0.006*"good" + 0.006*"plans" + 0.005*"provided" -2024-07-15 10:42:52,543 - topic diff=0.765162, rho=1.000000 -2024-07-15 10:42:52,543 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:42:52.543397', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:53,445 - Inspection date 2022-06-13 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:42:53,445 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:53,445 - Inspection date 2022-06-13 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:42:53,446 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:53,446 - Inspection date 2022-06-13 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:42:53,446 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:53,446 - Inspection date 2022-06-13 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:42:53,446 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:53,447 - Inspection date 2022-06-13 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:42:53,447 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:53,447 - Inspection date 2022-06-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:42:53,447 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:54,962 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:42:54,964 - built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2249 corpus positions) -2024-07-15 10:42:54,964 - Dictionary lifecycle event {'msg': "built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2249 corpus positions)", 'datetime': '2024-07-15T10:42:54.964775', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:54,965 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:42:54,965 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:42:54,966 - using serial LDA version on this node -2024-07-15 10:42:54,966 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:42:54,966 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:42:54,970 - -8.089 per-word bound, 272.4 perplexity estimate based on a held-out corpus of 1 documents with 2249 words -2024-07-15 10:42:54,970 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:42:54,971 - topic #0 (0.333): 0.013*"’" + 0.006*"Hove" + 0.006*"Brighton" + 0.006*"practice" + 0.006*"needs" + 0.005*"well" + 0.005*"relationships" + 0.005*"receive" + 0.005*"experiences" + 0.005*"range" -2024-07-15 10:42:54,972 - topic #1 (0.333): 0.019*"’" + 0.009*"well" + 0.008*"Hove" + 0.007*"Brighton" + 0.007*"needs" + 0.006*"progress" + 0.006*"practice" + 0.006*"relationships" + 0.005*"experiences" + 0.005*"family" -2024-07-15 10:42:54,972 - topic #2 (0.333): 0.016*"’" + 0.007*"well" + 0.007*"needs" + 0.006*"practice" + 0.005*"Brighton" + 0.005*"experiences" + 0.005*"Hove" + 0.005*"progress" + 0.005*"11" + 0.004*"PAs" -2024-07-15 10:42:54,972 - topic diff=0.742882, rho=1.000000 -2024-07-15 10:42:54,972 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:42:54.972538', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:55,919 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:42:55,919 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:55,919 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:42:55,920 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:55,920 - Inspection date None / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:42:55,920 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:55,920 - Inspection date None / Column 'in_care' not found in the DataFrame. -2024-07-15 10:42:55,920 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:55,920 - Inspection date None / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:42:55,920 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:55,921 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:42:55,921 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:57,182 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:42:57,184 - built Dictionary<1151 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2647 corpus positions) -2024-07-15 10:42:57,185 - Dictionary lifecycle event {'msg': "built Dictionary<1151 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2647 corpus positions)", 'datetime': '2024-07-15T10:42:57.185022', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:57,186 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:42:57,186 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:42:57,186 - using serial LDA version on this node -2024-07-15 10:42:57,186 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:42:57,187 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:42:57,190 - -8.034 per-word bound, 262.1 perplexity estimate based on a held-out corpus of 1 documents with 2647 words -2024-07-15 10:42:57,191 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:42:57,192 - topic #0 (0.333): 0.023*"’" + 0.009*"well" + 0.008*"needs" + 0.008*"good" + 0.006*"Bristol" + 0.006*"health" + 0.005*"always" + 0.005*"27" + 0.005*"leaders" + 0.005*"receive" -2024-07-15 10:42:57,192 - topic #1 (0.333): 0.019*"’" + 0.010*"well" + 0.009*"Bristol" + 0.008*"good" + 0.007*"needs" + 0.007*"progress" + 0.005*"16" + 0.005*"need" + 0.005*"plans" + 0.005*"arrangements" -2024-07-15 10:42:57,192 - topic #2 (0.333): 0.014*"’" + 0.007*"well" + 0.006*"Bristol" + 0.006*"needs" + 0.006*"good" + 0.005*"health" + 0.005*"leaders" + 0.005*"progress" + 0.004*"timely" + 0.004*"plans" -2024-07-15 10:42:57,193 - topic diff=0.826858, rho=1.000000 -2024-07-15 10:42:57,193 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:42:57.193189', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:58,033 - Inspection date 2023-01-16 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:42:58,034 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:58,034 - Inspection date 2023-01-16 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:42:58,034 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:58,034 - Inspection date 2023-01-16 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:42:58,034 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:58,034 - Inspection date 2023-01-16 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:42:58,035 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:58,035 - Inspection date 2023-01-16 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:42:58,035 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:58,035 - Inspection date 2023-01-16 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:42:58,035 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:42:59,586 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:42:59,589 - built Dictionary<1263 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2404 corpus positions) -2024-07-15 10:42:59,589 - Dictionary lifecycle event {'msg': "built Dictionary<1263 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2404 corpus positions)", 'datetime': '2024-07-15T10:42:59.589452', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:42:59,590 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:42:59,590 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:42:59,591 - using serial LDA version on this node -2024-07-15 10:42:59,591 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:42:59,591 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:42:59,595 - -8.236 per-word bound, 301.5 perplexity estimate based on a held-out corpus of 1 documents with 2404 words -2024-07-15 10:42:59,595 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:42:59,598 - topic #0 (0.333): 0.015*"’" + 0.005*"17" + 0.005*"Buckinghamshire" + 0.004*"practice" + 0.004*"number" + 0.004*"plans" + 0.004*"December" + 0.004*"protection" + 0.004*"6" + 0.004*"needs" -2024-07-15 10:42:59,599 - topic #1 (0.333): 0.010*"’" + 0.005*"number" + 0.005*"plans" + 0.005*"Buckinghamshire" + 0.004*"many" + 0.004*"protection" + 0.004*"6" + 0.004*"needs" + 0.004*"small" + 0.004*"2021" -2024-07-15 10:42:59,599 - topic #2 (0.333): 0.014*"’" + 0.006*"plans" + 0.005*"17" + 0.005*"number" + 0.004*"2021" + 0.004*"many" + 0.004*"6" + 0.004*"December" + 0.004*"well" + 0.004*"Buckinghamshire" -2024-07-15 10:42:59,599 - topic diff=0.720616, rho=1.000000 -2024-07-15 10:42:59,599 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:42:59.599670', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:00,687 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:00,688 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:00,688 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:00,688 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:00,688 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:00,688 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:00,688 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:00,689 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:00,689 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:00,689 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:00,689 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:00,689 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:02,235 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:02,238 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2427 corpus positions) -2024-07-15 10:43:02,238 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2427 corpus positions)", 'datetime': '2024-07-15T10:43:02.238515', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:02,239 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:02,239 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:02,239 - using serial LDA version on this node -2024-07-15 10:43:02,240 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:02,240 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:02,244 - -7.973 per-word bound, 251.3 perplexity estimate based on a held-out corpus of 1 documents with 2427 words -2024-07-15 10:43:02,244 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:02,245 - topic #0 (0.333): 0.010*"’" + 0.007*"2021" + 0.006*"protection" + 0.005*"needs" + 0.005*"practice" + 0.004*"quality" + 0.004*"risk" + 0.004*"always" + 0.004*"October" + 0.004*"Bury" -2024-07-15 10:43:02,245 - topic #1 (0.333): 0.012*"’" + 0.007*"2021" + 0.006*"protection" + 0.006*"impact" + 0.005*"practice" + 0.005*"5" + 0.005*"need" + 0.005*"delay" + 0.005*"risk" + 0.004*"needs" -2024-07-15 10:43:02,245 - topic #2 (0.333): 0.012*"’" + 0.009*"needs" + 0.008*"team" + 0.007*"protection" + 0.006*"practice" + 0.006*"need" + 0.006*"Bury" + 0.005*"2021" + 0.005*"quality" + 0.005*"impact" -2024-07-15 10:43:02,245 - topic diff=0.805574, rho=1.000000 -2024-07-15 10:43:02,246 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:02.246035', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:03,080 - Inspection date 2021-10-25 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:03,080 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:03,080 - Inspection date 2021-10-25 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:03,081 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:03,081 - Inspection date 2021-10-25 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:03,081 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:03,081 - Inspection date 2021-10-25 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:03,081 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:03,081 - Inspection date 2021-10-25 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:03,082 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:03,082 - Inspection date 2021-10-25 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:03,082 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:04,595 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:04,597 - built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2389 corpus positions) -2024-07-15 10:43:04,597 - Dictionary lifecycle event {'msg': "built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2389 corpus positions)", 'datetime': '2024-07-15T10:43:04.597568', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:04,598 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:04,598 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:04,599 - using serial LDA version on this node -2024-07-15 10:43:04,599 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:04,599 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:04,603 - -8.033 per-word bound, 262.0 perplexity estimate based on a held-out corpus of 1 documents with 2389 words -2024-07-15 10:43:04,603 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:04,604 - topic #0 (0.333): 0.022*"’" + 0.009*"Calderdale" + 0.008*"needs" + 0.006*"ensure" + 0.005*"experiences" + 0.005*"well" + 0.005*"progress" + 0.005*"plans" + 0.005*"risk" + 0.005*"parents" -2024-07-15 10:43:04,604 - topic #1 (0.333): 0.021*"’" + 0.011*"needs" + 0.009*"Calderdale" + 0.007*"well" + 0.006*"plans" + 0.006*"ensure" + 0.006*"progress" + 0.006*"risk" + 0.005*"need" + 0.005*"parents" -2024-07-15 10:43:04,605 - topic #2 (0.333): 0.016*"’" + 0.009*"needs" + 0.007*"plans" + 0.006*"Calderdale" + 0.005*"well" + 0.005*"progress" + 0.004*"parents" + 0.004*"PAs" + 0.004*"23" + 0.004*"risk" -2024-07-15 10:43:04,605 - topic diff=0.792896, rho=1.000000 -2024-07-15 10:43:04,605 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:04.605412', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:05,542 - Inspection date 2024-02-19 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:05,543 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:05,543 - Inspection date 2024-02-19 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:05,543 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:05,543 - Inspection date 2024-02-19 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:05,543 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:05,543 - Inspection date 2024-02-19 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:05,543 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:05,544 - Inspection date 2024-02-19 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:05,544 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:05,544 - Inspection date 2024-02-19 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:05,544 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:07,196 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:07,199 - built Dictionary<1082 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2339 corpus positions) -2024-07-15 10:43:07,199 - Dictionary lifecycle event {'msg': "built Dictionary<1082 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2339 corpus positions)", 'datetime': '2024-07-15T10:43:07.199236', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:07,200 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:07,200 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:07,200 - using serial LDA version on this node -2024-07-15 10:43:07,201 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:07,201 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:07,204 - -8.009 per-word bound, 257.7 perplexity estimate based on a held-out corpus of 1 documents with 2339 words -2024-07-15 10:43:07,204 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:07,206 - topic #0 (0.333): 0.019*"’" + 0.007*"leaders" + 0.007*"Cambridgeshire" + 0.006*"needs" + 0.005*"effective" + 0.005*"good" + 0.005*"15" + 0.005*"well" + 0.005*"However" + 0.005*"quality" -2024-07-15 10:43:07,206 - topic #1 (0.333): 0.016*"’" + 0.007*"leaders" + 0.007*"needs" + 0.006*"Cambridgeshire" + 0.006*"good" + 0.005*"quality" + 0.005*"4" + 0.005*"practice" + 0.004*"March" + 0.004*"well" -2024-07-15 10:43:07,206 - topic #2 (0.333): 0.015*"’" + 0.007*"needs" + 0.006*"Cambridgeshire" + 0.005*"well" + 0.005*"leaders" + 0.005*"effective" + 0.004*"good" + 0.004*"2024" + 0.004*"access" + 0.004*"leadership" -2024-07-15 10:43:07,206 - topic diff=0.786488, rho=1.000000 -2024-07-15 10:43:07,206 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:07.206890', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:08,225 - Inspection date 2024-03-04 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:08,225 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:08,225 - Inspection date 2024-03-04 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:08,225 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:08,226 - Inspection date 2024-03-04 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:08,226 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:08,226 - Inspection date 2024-03-04 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:08,226 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:08,226 - Inspection date 2024-03-04 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:08,226 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:08,227 - Inspection date 2024-03-04 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:08,227 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:09,640 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:09,642 - built Dictionary<1030 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions) -2024-07-15 10:43:09,643 - Dictionary lifecycle event {'msg': "built Dictionary<1030 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)", 'datetime': '2024-07-15T10:43:09.642975', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:09,643 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:09,644 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:09,644 - using serial LDA version on this node -2024-07-15 10:43:09,644 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:09,644 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:09,648 - -7.964 per-word bound, 249.8 perplexity estimate based on a held-out corpus of 1 documents with 2199 words -2024-07-15 10:43:09,648 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:09,649 - topic #0 (0.333): 0.017*"’" + 0.009*"well" + 0.008*"need" + 0.006*"carers" + 0.006*"progress" + 0.005*"plans" + 0.005*"Bedfordshire" + 0.005*"good" + 0.005*"needs" + 0.005*"practice" -2024-07-15 10:43:09,650 - topic #1 (0.333): 0.014*"’" + 0.010*"well" + 0.008*"needs" + 0.007*"carers" + 0.007*"good" + 0.006*"need" + 0.006*"progress" + 0.006*"plans" + 0.005*"Central" + 0.005*"number" -2024-07-15 10:43:09,650 - topic #2 (0.333): 0.017*"’" + 0.008*"well" + 0.008*"needs" + 0.006*"good" + 0.006*"plans" + 0.005*"Bedfordshire" + 0.005*"carers" + 0.005*"effective" + 0.005*"need" + 0.004*"information" -2024-07-15 10:43:09,650 - topic diff=0.781522, rho=1.000000 -2024-07-15 10:43:09,650 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:09.650574', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:10,573 - Inspection date 2022-01-17 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:10,573 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:10,574 - Inspection date 2022-01-17 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:10,574 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:10,574 - Inspection date 2022-01-17 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:10,574 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:10,574 - Inspection date 2022-01-17 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:10,574 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:10,575 - Inspection date 2022-01-17 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:10,575 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:10,575 - Inspection date 2022-01-17 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:10,575 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:12,008 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:12,010 - built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2272 corpus positions) -2024-07-15 10:43:12,010 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2272 corpus positions)", 'datetime': '2024-07-15T10:43:12.010749', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:12,011 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:12,011 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:12,012 - using serial LDA version on this node -2024-07-15 10:43:12,012 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:12,012 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:12,016 - -7.978 per-word bound, 252.2 perplexity estimate based on a held-out corpus of 1 documents with 2272 words -2024-07-15 10:43:12,016 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:12,017 - topic #0 (0.333): 0.010*"’" + 0.008*"2024" + 0.007*"needs" + 0.007*"well" + 0.006*"practice" + 0.006*"Cheshire" + 0.005*"East" + 0.005*"effective" + 0.005*"quality" + 0.005*"plans" -2024-07-15 10:43:12,017 - topic #1 (0.333): 0.015*"’" + 0.008*"plans" + 0.008*"needs" + 0.007*"2024" + 0.007*"quality" + 0.006*"need" + 0.006*"East" + 0.006*"well" + 0.005*"leaders" + 0.005*"practice" -2024-07-15 10:43:12,018 - topic #2 (0.333): 0.012*"’" + 0.008*"practice" + 0.008*"2024" + 0.007*"needs" + 0.007*"well" + 0.006*"plans" + 0.006*"Cheshire" + 0.005*"quality" + 0.005*"leaders" + 0.005*"always" -2024-07-15 10:43:12,018 - topic diff=0.780229, rho=1.000000 -2024-07-15 10:43:12,018 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:12.018252', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:12,999 - Inspection date 2024-02-26 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:13,000 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:13,000 - Inspection date 2024-02-26 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:13,000 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:13,000 - Inspection date 2024-02-26 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:13,000 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:13,000 - Inspection date 2024-02-26 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:13,001 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:13,001 - Inspection date 2024-02-26 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:13,001 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:13,001 - Inspection date 2024-02-26 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:13,001 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:14,545 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:14,548 - built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2186 corpus positions) -2024-07-15 10:43:14,548 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2186 corpus positions)", 'datetime': '2024-07-15T10:43:14.548282', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:14,549 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:14,549 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:14,549 - using serial LDA version on this node -2024-07-15 10:43:14,550 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:14,550 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:14,554 - -7.999 per-word bound, 255.9 perplexity estimate based on a held-out corpus of 1 documents with 2186 words -2024-07-15 10:43:14,554 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:14,555 - topic #0 (0.333): 0.025*"’" + 0.007*"well" + 0.006*"needs" + 0.005*"plans" + 0.005*"impact" + 0.005*"effective" + 0.005*"practice" + 0.004*"effectively" + 0.004*"always" + 0.004*"receive" -2024-07-15 10:43:14,556 - topic #1 (0.333): 0.014*"’" + 0.007*"needs" + 0.006*"well" + 0.004*"However" + 0.004*"order" + 0.004*"always" + 0.004*"timely" + 0.004*"effectively" + 0.004*"abuse" + 0.004*"early" -2024-07-15 10:43:14,556 - topic #2 (0.333): 0.022*"’" + 0.008*"well" + 0.008*"needs" + 0.006*"practice" + 0.005*"learning" + 0.004*"always" + 0.004*"order" + 0.004*"early" + 0.004*"effective" + 0.004*"effectively" -2024-07-15 10:43:14,556 - topic diff=0.767361, rho=1.000000 -2024-07-15 10:43:14,556 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:14.556633', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:15,510 - Inspection date 2019-03-18 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:15,510 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:15,510 - Inspection date 2019-03-18 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:15,510 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:15,510 - Inspection date 2019-03-18 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:15,511 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:15,511 - Inspection date 2019-03-18 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:15,511 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:15,511 - Inspection date 2019-03-18 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:15,511 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:15,512 - Inspection date 2019-03-18 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:15,512 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:17,179 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:17,181 - built Dictionary<1164 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2639 corpus positions) -2024-07-15 10:43:17,181 - Dictionary lifecycle event {'msg': "built Dictionary<1164 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2639 corpus positions)", 'datetime': '2024-07-15T10:43:17.181767', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:17,182 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:17,183 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:17,183 - using serial LDA version on this node -2024-07-15 10:43:17,183 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:17,183 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:17,189 - -8.054 per-word bound, 265.8 perplexity estimate based on a held-out corpus of 1 documents with 2639 words -2024-07-15 10:43:17,190 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:17,192 - topic #0 (0.333): 0.023*"’" + 0.007*"plans" + 0.005*"2" + 0.005*"needs" + 0.005*"Bradford" + 0.005*"21" + 0.005*"practice" + 0.005*"impact" + 0.005*"Council" + 0.004*"◼" -2024-07-15 10:43:17,192 - topic #1 (0.333): 0.019*"’" + 0.007*"plans" + 0.005*"needs" + 0.005*"risk" + 0.005*"quality" + 0.005*"need" + 0.005*"Bradford" + 0.004*"senior" + 0.004*"Metropolitan" + 0.004*"2022" -2024-07-15 10:43:17,192 - topic #2 (0.333): 0.019*"’" + 0.006*"plans" + 0.005*"need" + 0.004*"Bradford" + 0.004*"November" + 0.004*"2" + 0.004*"quality" + 0.004*"City" + 0.004*"experiences" + 0.004*"lack" -2024-07-15 10:43:17,192 - topic diff=0.811068, rho=1.000000 -2024-07-15 10:43:17,193 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:17.193171', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:18,207 - Inspection date 2022-11-21 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:18,207 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:18,207 - Inspection date 2022-11-21 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:18,207 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:18,208 - Inspection date 2022-11-21 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:18,208 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:18,208 - Inspection date 2022-11-21 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:18,208 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:18,208 - Inspection date 2022-11-21 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:18,208 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:18,209 - Inspection date 2022-11-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:18,209 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:19,575 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:19,578 - built Dictionary<876 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1767 corpus positions) -2024-07-15 10:43:19,578 - Dictionary lifecycle event {'msg': "built Dictionary<876 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1767 corpus positions)", 'datetime': '2024-07-15T10:43:19.578264', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:19,579 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:19,579 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:19,579 - using serial LDA version on this node -2024-07-15 10:43:19,579 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:19,580 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:19,583 - -7.833 per-word bound, 228.0 perplexity estimate based on a held-out corpus of 1 documents with 1767 words -2024-07-15 10:43:19,583 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:19,584 - topic #0 (0.333): 0.012*"’" + 0.010*"needs" + 0.010*"well" + 0.007*"ensure" + 0.007*"progress" + 0.007*"effective" + 0.006*"plans" + 0.006*"clear" + 0.005*"good" + 0.005*"understanding" -2024-07-15 10:43:19,585 - topic #1 (0.333): 0.012*"needs" + 0.011*"’" + 0.010*"well" + 0.008*"ensure" + 0.006*"effective" + 0.006*"individual" + 0.005*"good" + 0.005*"clear" + 0.005*"practice" + 0.004*"clearly" -2024-07-15 10:43:19,585 - topic #2 (0.333): 0.012*"’" + 0.012*"needs" + 0.010*"well" + 0.009*"ensure" + 0.007*"clear" + 0.007*"progress" + 0.006*"effective" + 0.006*"plans" + 0.006*"within" + 0.005*"good" -2024-07-15 10:43:19,585 - topic diff=0.745380, rho=1.000000 -2024-07-15 10:43:19,585 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:19.585642', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:20,724 - Inspection date 2020-03-02 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:20,724 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:20,724 - Inspection date 2020-03-02 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:20,724 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:20,724 - Inspection date 2020-03-02 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:20,724 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:20,725 - Inspection date 2020-03-02 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:20,725 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:20,725 - Inspection date 2020-03-02 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:20,725 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:20,725 - Inspection date 2020-03-02 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:20,725 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:22,117 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:22,121 - built Dictionary<1007 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2281 corpus positions) -2024-07-15 10:43:22,121 - Dictionary lifecycle event {'msg': "built Dictionary<1007 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2281 corpus positions)", 'datetime': '2024-07-15T10:43:22.121204', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:22,122 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:22,123 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:22,123 - using serial LDA version on this node -2024-07-15 10:43:22,123 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:22,123 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:22,129 - -7.912 per-word bound, 240.8 perplexity estimate based on a held-out corpus of 1 documents with 2281 words -2024-07-15 10:43:22,130 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:22,132 - topic #0 (0.333): 0.017*"’" + 0.008*"well" + 0.008*"Wakefield" + 0.007*"quality" + 0.006*"leaders" + 0.006*"receive" + 0.006*"November" + 0.005*"plans" + 0.005*"timely" + 0.005*"good" -2024-07-15 10:43:22,132 - topic #1 (0.333): 0.017*"’" + 0.009*"November" + 0.009*"leaders" + 0.008*"Wakefield" + 0.008*"quality" + 0.008*"effective" + 0.008*"good" + 0.008*"well" + 0.006*"plans" + 0.006*"progress" -2024-07-15 10:43:22,132 - topic #2 (0.333): 0.014*"’" + 0.007*"quality" + 0.007*"effective" + 0.006*"good" + 0.006*"Wakefield" + 0.006*"well" + 0.005*"plans" + 0.005*"leaders" + 0.005*"receive" + 0.004*"November" -2024-07-15 10:43:22,132 - topic diff=0.812514, rho=1.000000 -2024-07-15 10:43:22,132 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:22.132967', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:23,192 - Inspection date 2021-11-08 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:23,192 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:23,193 - Inspection date 2021-11-08 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:23,193 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:23,193 - Inspection date 2021-11-08 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:23,193 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:23,193 - Inspection date 2021-11-08 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:23,193 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:23,194 - Inspection date 2021-11-08 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:23,194 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:23,194 - Inspection date 2021-11-08 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:23,194 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:24,605 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:24,608 - built Dictionary<909 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1855 corpus positions) -2024-07-15 10:43:24,608 - Dictionary lifecycle event {'msg': "built Dictionary<909 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1855 corpus positions)", 'datetime': '2024-07-15T10:43:24.608688', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:24,609 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:24,609 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:24,609 - using serial LDA version on this node -2024-07-15 10:43:24,610 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:24,610 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:24,613 - -7.864 per-word bound, 232.9 perplexity estimate based on a held-out corpus of 1 documents with 1855 words -2024-07-15 10:43:24,613 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:24,615 - topic #0 (0.333): 0.018*"’" + 0.009*"needs" + 0.007*"March" + 0.007*"quality" + 0.006*"effective" + 0.006*"York" + 0.006*"plans" + 0.006*"ensure" + 0.006*"However" + 0.006*"need" -2024-07-15 10:43:24,615 - topic #1 (0.333): 0.013*"’" + 0.007*"needs" + 0.007*"quality" + 0.006*"March" + 0.006*"effective" + 0.005*"However" + 0.005*"well" + 0.005*"education" + 0.005*"18" + 0.004*"experiences" -2024-07-15 10:43:24,615 - topic #2 (0.333): 0.010*"’" + 0.008*"March" + 0.006*"quality" + 0.005*"effective" + 0.004*"practice" + 0.004*"needs" + 0.004*"appropriate" + 0.004*"ensure" + 0.004*"small" + 0.004*"7" -2024-07-15 10:43:24,615 - topic diff=0.782295, rho=1.000000 -2024-07-15 10:43:24,615 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:24.615934', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:25,595 - Inspection date 2022-03-07 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:25,595 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:25,596 - Inspection date 2022-03-07 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:25,596 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:25,596 - Inspection date 2022-03-07 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:25,596 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:25,596 - Inspection date 2022-03-07 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:25,596 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:25,596 - Inspection date 2022-03-07 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:25,597 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:25,597 - Inspection date 2022-03-07 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:25,597 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:26,814 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:26,817 - built Dictionary<1014 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2157 corpus positions) -2024-07-15 10:43:26,817 - Dictionary lifecycle event {'msg': "built Dictionary<1014 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2157 corpus positions)", 'datetime': '2024-07-15T10:43:26.817168', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:26,818 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:26,818 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:26,818 - using serial LDA version on this node -2024-07-15 10:43:26,818 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:26,818 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:26,822 - -7.952 per-word bound, 247.6 perplexity estimate based on a held-out corpus of 1 documents with 2157 words -2024-07-15 10:43:26,822 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:26,823 - topic #0 (0.333): 0.017*"well" + 0.014*"’" + 0.011*"quality" + 0.010*"effective" + 0.010*"leaders" + 0.007*"plans" + 0.006*"timely" + 0.006*"good" + 0.006*"arrangements" + 0.006*"Senior" -2024-07-15 10:43:26,824 - topic #1 (0.333): 0.011*"well" + 0.011*"’" + 0.009*"quality" + 0.007*"leaders" + 0.006*"effective" + 0.005*"good" + 0.005*"highly" + 0.005*"arrangements" + 0.004*"timely" + 0.004*"high" -2024-07-15 10:43:26,824 - topic #2 (0.333): 0.013*"well" + 0.011*"’" + 0.008*"effective" + 0.008*"leaders" + 0.007*"quality" + 0.006*"plans" + 0.005*"good" + 0.005*"arrangements" + 0.005*"ensure" + 0.004*"timely" -2024-07-15 10:43:26,824 - topic diff=0.788395, rho=1.000000 -2024-07-15 10:43:26,824 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:26.824664', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:28,130 - Inspection date 2019-10-14 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:28,131 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:28,131 - Inspection date 2019-10-14 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:28,131 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:28,131 - Inspection date 2019-10-14 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:28,131 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:28,132 - Inspection date 2019-10-14 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:28,132 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:28,132 - Inspection date 2019-10-14 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:28,132 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:28,132 - Inspection date 2019-10-14 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:28,132 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:28,982 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:28,984 - built Dictionary<754 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1521 corpus positions) -2024-07-15 10:43:28,984 - Dictionary lifecycle event {'msg': "built Dictionary<754 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1521 corpus positions)", 'datetime': '2024-07-15T10:43:28.984682', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:28,985 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:28,985 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:28,985 - using serial LDA version on this node -2024-07-15 10:43:28,986 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:28,986 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:28,988 - -7.687 per-word bound, 206.1 perplexity estimate based on a held-out corpus of 1 documents with 1521 words -2024-07-15 10:43:28,989 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:28,990 - topic #0 (0.333): 0.012*"’" + 0.010*"Scilly" + 0.009*"Isles" + 0.009*"need" + 0.007*"practice" + 0.007*"information" + 0.006*"quality" + 0.005*"needs" + 0.005*"protection" + 0.005*"2023" -2024-07-15 10:43:28,990 - topic #1 (0.333): 0.013*"’" + 0.011*"Isles" + 0.009*"Scilly" + 0.009*"need" + 0.007*"needs" + 0.007*"information" + 0.006*"practice" + 0.006*"place" + 0.006*"protection" + 0.006*"quality" -2024-07-15 10:43:28,990 - topic #2 (0.333): 0.029*"’" + 0.014*"Scilly" + 0.014*"Isles" + 0.011*"information" + 0.010*"practice" + 0.008*"protection" + 0.007*"need" + 0.007*"needs" + 0.007*"place" + 0.006*"11" -2024-07-15 10:43:28,990 - topic diff=0.779804, rho=1.000000 -2024-07-15 10:43:28,990 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.00s', 'datetime': '2024-07-15T10:43:28.990778', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:29,859 - Inspection date 2023-07-11 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:29,860 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:29,860 - Inspection date 2023-07-11 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:29,861 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:29,861 - Inspection date 2023-07-11 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:29,861 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:29,861 - Inspection date 2023-07-11 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:29,862 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:29,862 - Inspection date 2023-07-11 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:29,862 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:29,862 - Inspection date 2023-07-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:29,862 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:31,160 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:31,162 - built Dictionary<938 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2074 corpus positions) -2024-07-15 10:43:31,162 - Dictionary lifecycle event {'msg': "built Dictionary<938 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2074 corpus positions)", 'datetime': '2024-07-15T10:43:31.162563', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:31,163 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:31,163 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:31,163 - using serial LDA version on this node -2024-07-15 10:43:31,164 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:31,164 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:31,167 - -7.847 per-word bound, 230.3 perplexity estimate based on a held-out corpus of 1 documents with 2074 words -2024-07-15 10:43:31,167 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:31,168 - topic #0 (0.333): 0.017*"’" + 0.010*"well" + 0.008*"Coventry" + 0.007*"needs" + 0.006*"plans" + 0.006*"supported" + 0.005*"need" + 0.005*"strong" + 0.004*"20" + 0.004*"understand" -2024-07-15 10:43:31,169 - topic #1 (0.333): 0.021*"’" + 0.008*"Coventry" + 0.007*"family" + 0.007*"plans" + 0.007*"supported" + 0.007*"strong" + 0.006*"needs" + 0.005*"need" + 0.005*"well" + 0.005*"20" -2024-07-15 10:43:31,169 - topic #2 (0.333): 0.020*"’" + 0.009*"well" + 0.009*"needs" + 0.008*"Coventry" + 0.007*"supported" + 0.006*"family" + 0.005*"plans" + 0.005*"1" + 0.005*"PAs" + 0.004*"need" -2024-07-15 10:43:31,169 - topic diff=0.796283, rho=1.000000 -2024-07-15 10:43:31,169 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:31.169472', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:32,119 - Inspection date 2022-06-20 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:32,120 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:32,120 - Inspection date 2022-06-20 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:32,120 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:32,120 - Inspection date 2022-06-20 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:32,120 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:32,121 - Inspection date 2022-06-20 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:32,121 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:32,121 - Inspection date 2022-06-20 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:32,121 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:32,121 - Inspection date 2022-06-20 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:32,121 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:34,016 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:34,020 - built Dictionary<1195 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2653 corpus positions) -2024-07-15 10:43:34,020 - Dictionary lifecycle event {'msg': "built Dictionary<1195 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2653 corpus positions)", 'datetime': '2024-07-15T10:43:34.020918', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:34,022 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:34,023 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:34,023 - using serial LDA version on this node -2024-07-15 10:43:34,024 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:34,024 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:34,031 - -8.088 per-word bound, 272.2 perplexity estimate based on a held-out corpus of 1 documents with 2653 words -2024-07-15 10:43:34,031 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:34,033 - topic #0 (0.333): 0.017*"’" + 0.008*"well" + 0.008*"October" + 0.007*"needs" + 0.007*"leaders" + 0.006*"Darlington" + 0.006*"practice" + 0.005*"quality" + 0.005*"effective" + 0.005*"supported" -2024-07-15 10:43:34,034 - topic #1 (0.333): 0.021*"’" + 0.009*"well" + 0.007*"practice" + 0.007*"needs" + 0.006*"October" + 0.006*"leaders" + 0.006*"Darlington" + 0.005*"effective" + 0.005*"family" + 0.005*"supported" -2024-07-15 10:43:34,034 - topic #2 (0.333): 0.018*"’" + 0.006*"leaders" + 0.006*"well" + 0.006*"Darlington" + 0.005*"needs" + 0.005*"October" + 0.005*"quality" + 0.005*"appropriate" + 0.004*"practice" + 0.004*"education" -2024-07-15 10:43:34,034 - topic diff=0.798382, rho=1.000000 -2024-07-15 10:43:34,034 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:34.034829', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:35,052 - Inspection date 2022-10-10 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:35,052 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:35,053 - Inspection date 2022-10-10 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:35,053 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:35,053 - Inspection date 2022-10-10 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:35,053 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:35,053 - Inspection date 2022-10-10 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:35,054 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:35,054 - Inspection date 2022-10-10 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:35,054 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:35,054 - Inspection date 2022-10-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:35,054 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:36,639 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:36,642 - built Dictionary<1121 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2396 corpus positions) -2024-07-15 10:43:36,642 - Dictionary lifecycle event {'msg': "built Dictionary<1121 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2396 corpus positions)", 'datetime': '2024-07-15T10:43:36.642260', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:36,643 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:36,643 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:36,643 - using serial LDA version on this node -2024-07-15 10:43:36,644 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:36,644 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:36,647 - -8.048 per-word bound, 264.6 perplexity estimate based on a held-out corpus of 1 documents with 2396 words -2024-07-15 10:43:36,648 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:36,649 - topic #0 (0.333): 0.018*"’" + 0.009*"needs" + 0.006*"quality" + 0.006*"Derby" + 0.005*"receive" + 0.005*"progress" + 0.005*"appropriate" + 0.005*"need" + 0.005*"views" + 0.004*"plans" -2024-07-15 10:43:36,649 - topic #1 (0.333): 0.023*"’" + 0.010*"needs" + 0.007*"quality" + 0.007*"Derby" + 0.007*"good" + 0.006*"plans" + 0.006*"progress" + 0.006*"need" + 0.005*"well" + 0.005*"receive" -2024-07-15 10:43:36,649 - topic #2 (0.333): 0.021*"’" + 0.010*"needs" + 0.008*"Derby" + 0.007*"receive" + 0.006*"well" + 0.006*"leaders" + 0.005*"plans" + 0.005*"appropriate" + 0.005*"progress" + 0.005*"quality" -2024-07-15 10:43:36,650 - topic diff=0.777717, rho=1.000000 -2024-07-15 10:43:36,650 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:36.650257', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:37,601 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:37,601 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:37,602 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:37,602 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:37,602 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:37,602 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:37,602 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:37,602 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:37,603 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:37,603 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:37,603 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:37,603 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:38,738 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:38,740 - built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2035 corpus positions) -2024-07-15 10:43:38,740 - Dictionary lifecycle event {'msg': "built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2035 corpus positions)", 'datetime': '2024-07-15T10:43:38.740703', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:38,741 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:38,741 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:38,742 - using serial LDA version on this node -2024-07-15 10:43:38,742 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:38,742 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:38,746 - -8.040 per-word bound, 263.2 perplexity estimate based on a held-out corpus of 1 documents with 2035 words -2024-07-15 10:43:38,746 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:38,747 - topic #0 (0.333): 0.016*"’" + 0.008*"well" + 0.006*"Derbyshire" + 0.005*"plans" + 0.005*"10" + 0.005*"education" + 0.005*"needs" + 0.005*"positive" + 0.005*"practice" + 0.004*"number" -2024-07-15 10:43:38,747 - topic #1 (0.333): 0.013*"’" + 0.006*"well" + 0.005*"Derbyshire" + 0.005*"effective" + 0.005*"plans" + 0.004*"positive" + 0.004*"leaders" + 0.004*"need" + 0.004*"30" + 0.004*"good" -2024-07-15 10:43:38,747 - topic #2 (0.333): 0.013*"’" + 0.009*"well" + 0.007*"Derbyshire" + 0.005*"needs" + 0.005*"leaders" + 0.005*"plans" + 0.005*"positive" + 0.005*"health" + 0.004*"education" + 0.004*"number" -2024-07-15 10:43:38,748 - topic diff=0.743747, rho=1.000000 -2024-07-15 10:43:38,748 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:38.748139', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:39,793 - Inspection date 2023-10-30 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:39,794 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:39,794 - Inspection date 2023-10-30 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:39,794 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:39,794 - Inspection date 2023-10-30 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:39,794 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:39,795 - Inspection date 2023-10-30 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:39,795 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:39,795 - Inspection date 2023-10-30 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:39,795 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:39,795 - Inspection date 2023-10-30 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:39,795 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:41,142 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:41,144 - built Dictionary<1175 unique tokens: ['0161', '0300', '1', '1,000', '10']...> from 1 documents (total 2313 corpus positions) -2024-07-15 10:43:41,145 - Dictionary lifecycle event {'msg': "built Dictionary<1175 unique tokens: ['0161', '0300', '1', '1,000', '10']...> from 1 documents (total 2313 corpus positions)", 'datetime': '2024-07-15T10:43:41.144997', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:41,146 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:41,146 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:41,146 - using serial LDA version on this node -2024-07-15 10:43:41,146 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:41,146 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:41,150 - -8.146 per-word bound, 283.4 perplexity estimate based on a held-out corpus of 1 documents with 2313 words -2024-07-15 10:43:41,150 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:41,152 - topic #0 (0.333): 0.011*"’" + 0.006*"well" + 0.005*"leaders" + 0.004*"progress" + 0.004*"risk" + 0.004*"health" + 0.004*"quality" + 0.004*"case" + 0.004*"protection" + 0.003*"need" -2024-07-15 10:43:41,152 - topic #1 (0.333): 0.009*"’" + 0.006*"well" + 0.005*"leaders" + 0.004*"Devon" + 0.004*"health" + 0.004*"risk" + 0.004*"need" + 0.004*"progress" + 0.004*"areas" + 0.004*"living" -2024-07-15 10:43:41,152 - topic #2 (0.333): 0.009*"’" + 0.006*"well" + 0.006*"health" + 0.005*"risk" + 0.005*"progress" + 0.004*"case" + 0.004*"quality" + 0.004*"leaders" + 0.004*"protection" + 0.004*"Devon" -2024-07-15 10:43:41,152 - topic diff=0.732306, rho=1.000000 -2024-07-15 10:43:41,153 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:41.152994', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:42,205 - Inspection date 2020-01-20 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:42,205 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:42,205 - Inspection date 2020-01-20 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:42,205 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:42,206 - Inspection date 2020-01-20 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:42,206 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:42,206 - Inspection date 2020-01-20 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:42,206 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:42,206 - Inspection date 2020-01-20 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:42,206 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:42,207 - Inspection date 2020-01-20 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:42,207 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:43,594 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:43,597 - built Dictionary<1175 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2429 corpus positions) -2024-07-15 10:43:43,597 - Dictionary lifecycle event {'msg': "built Dictionary<1175 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2429 corpus positions)", 'datetime': '2024-07-15T10:43:43.597531', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:43,598 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:43,599 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:43,599 - using serial LDA version on this node -2024-07-15 10:43:43,599 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:43,600 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:43,604 - -8.109 per-word bound, 276.0 perplexity estimate based on a held-out corpus of 1 documents with 2429 words -2024-07-15 10:43:43,604 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:43,605 - topic #0 (0.333): 0.020*"’" + 0.007*"well" + 0.006*"Doncaster" + 0.005*"14" + 0.005*"quality" + 0.005*"records" + 0.005*"receive" + 0.005*"information" + 0.005*"many" + 0.004*"progress" -2024-07-15 10:43:43,606 - topic #1 (0.333): 0.019*"’" + 0.006*"well" + 0.006*"leaders" + 0.005*"plans" + 0.005*"Doncaster" + 0.005*"records" + 0.005*"many" + 0.005*"arrangements" + 0.005*"quality" + 0.005*"25" -2024-07-15 10:43:43,606 - topic #2 (0.333): 0.020*"’" + 0.006*"well" + 0.006*"Doncaster" + 0.006*"progress" + 0.005*"protection" + 0.005*"many" + 0.004*"leaders" + 0.004*"plans" + 0.004*"Trust" + 0.004*"information" -2024-07-15 10:43:43,606 - topic diff=0.766250, rho=1.000000 -2024-07-15 10:43:43,606 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:43.606606', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:45,721 - Inspection date 2022-02-14 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:45,721 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:45,722 - Inspection date 2022-02-14 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:45,722 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:45,722 - Inspection date 2022-02-14 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:45,722 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:45,722 - Inspection date 2022-02-14 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:45,722 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:45,722 - Inspection date 2022-02-14 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:45,723 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:45,723 - Inspection date 2022-02-14 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:45,723 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:46,985 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:46,986 - built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1942 corpus positions) -2024-07-15 10:43:46,987 - Dictionary lifecycle event {'msg': "built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1942 corpus positions)", 'datetime': '2024-07-15T10:43:46.987150', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:46,988 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:46,988 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:46,988 - using serial LDA version on this node -2024-07-15 10:43:46,988 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:46,989 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:46,992 - -8.103 per-word bound, 275.0 perplexity estimate based on a held-out corpus of 1 documents with 1942 words -2024-07-15 10:43:46,992 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:46,994 - topic #0 (0.333): 0.012*"’" + 0.006*"Dorset" + 0.005*"well" + 0.005*"good" + 0.004*"impact" + 0.004*"October" + 0.004*"arrangements" + 0.004*"Senior" + 0.004*"leaders" + 0.004*"change" -2024-07-15 10:43:46,994 - topic #1 (0.333): 0.008*"’" + 0.006*"Dorset" + 0.005*"good" + 0.004*"needs" + 0.004*"arrangements" + 0.004*"impact" + 0.004*"well" + 0.004*"8" + 0.003*"27" + 0.003*"need" -2024-07-15 10:43:46,994 - topic #2 (0.333): 0.017*"’" + 0.009*"Dorset" + 0.007*"good" + 0.007*"well" + 0.005*"needs" + 0.005*"8" + 0.005*"including" + 0.005*"arrangements" + 0.004*"quality" + 0.004*"leaders" -2024-07-15 10:43:46,994 - topic diff=0.750451, rho=1.000000 -2024-07-15 10:43:46,994 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:46.994861', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:47,883 - Inspection date 2021-09-27 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:47,883 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:47,883 - Inspection date 2021-09-27 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:47,883 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:47,884 - Inspection date 2021-09-27 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:47,884 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:47,884 - Inspection date 2021-09-27 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:47,884 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:47,884 - Inspection date 2021-09-27 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:47,884 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:47,884 - Inspection date 2021-09-27 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:47,884 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:49,215 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:49,217 - built Dictionary<1050 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2138 corpus positions) -2024-07-15 10:43:49,218 - Dictionary lifecycle event {'msg': "built Dictionary<1050 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2138 corpus positions)", 'datetime': '2024-07-15T10:43:49.218059', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:49,219 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:49,219 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:49,219 - using serial LDA version on this node -2024-07-15 10:43:49,219 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:49,219 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:49,223 - -8.010 per-word bound, 257.9 perplexity estimate based on a held-out corpus of 1 documents with 2138 words -2024-07-15 10:43:49,223 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:49,224 - topic #0 (0.333): 0.014*"’" + 0.010*"needs" + 0.009*"Dudley" + 0.006*"well" + 0.005*"plans" + 0.005*"arrangements" + 0.004*"quality" + 0.004*"ensure" + 0.004*"11" + 0.004*"experiences" -2024-07-15 10:43:49,225 - topic #1 (0.333): 0.016*"’" + 0.013*"needs" + 0.008*"Dudley" + 0.006*"always" + 0.006*"well" + 0.005*"arrangements" + 0.005*"plans" + 0.005*"oversight" + 0.005*"management" + 0.005*"quality" -2024-07-15 10:43:49,225 - topic #2 (0.333): 0.015*"’" + 0.009*"needs" + 0.006*"Dudley" + 0.005*"always" + 0.005*"arrangements" + 0.005*"plans" + 0.005*"well" + 0.004*"oversight" + 0.004*"ensure" + 0.004*"However" -2024-07-15 10:43:49,225 - topic diff=0.764642, rho=1.000000 -2024-07-15 10:43:49,225 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:49.225532', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:50,283 - Inspection date 2022-10-31 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:50,283 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:50,284 - Inspection date 2022-10-31 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:50,284 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:50,284 - Inspection date 2022-10-31 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:50,284 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:50,284 - Inspection date 2022-10-31 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:50,284 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:50,285 - Inspection date 2022-10-31 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:50,285 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:50,285 - Inspection date 2022-10-31 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:50,285 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:51,815 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:51,818 - built Dictionary<1051 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2278 corpus positions) -2024-07-15 10:43:51,818 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2278 corpus positions)", 'datetime': '2024-07-15T10:43:51.818129', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:51,819 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:51,819 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:51,819 - using serial LDA version on this node -2024-07-15 10:43:51,819 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:51,819 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:51,823 - -7.975 per-word bound, 251.5 perplexity estimate based on a held-out corpus of 1 documents with 2278 words -2024-07-15 10:43:51,823 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:51,824 - topic #0 (0.333): 0.017*"’" + 0.012*"needs" + 0.007*"well" + 0.007*"ensure" + 0.007*"Durham" + 0.006*"May" + 0.006*"plans" + 0.005*"practice" + 0.005*"family" + 0.005*"number" -2024-07-15 10:43:51,825 - topic #1 (0.333): 0.011*"’" + 0.009*"needs" + 0.008*"May" + 0.007*"Durham" + 0.007*"plans" + 0.007*"well" + 0.006*"ensure" + 0.005*"practice" + 0.004*"2022" + 0.004*"10" -2024-07-15 10:43:51,825 - topic #2 (0.333): 0.015*"’" + 0.010*"needs" + 0.007*"May" + 0.007*"Durham" + 0.007*"plans" + 0.007*"well" + 0.005*"supported" + 0.005*"practice" + 0.005*"progress" + 0.004*"protection" -2024-07-15 10:43:51,825 - topic diff=0.775139, rho=1.000000 -2024-07-15 10:43:51,825 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:51.825447', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:52,743 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:52,744 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:52,744 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:52,744 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:52,744 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:52,744 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:52,745 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:52,745 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:52,745 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:52,745 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:52,745 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:52,745 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:54,103 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:54,105 - built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2014 corpus positions) -2024-07-15 10:43:54,105 - Dictionary lifecycle event {'msg': "built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2014 corpus positions)", 'datetime': '2024-07-15T10:43:54.105866', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:54,106 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:54,106 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:54,107 - using serial LDA version on this node -2024-07-15 10:43:54,107 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:54,107 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:54,110 - -7.921 per-word bound, 242.4 perplexity estimate based on a held-out corpus of 1 documents with 2014 words -2024-07-15 10:43:54,110 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:54,112 - topic #0 (0.333): 0.020*"’" + 0.009*"needs" + 0.008*"plans" + 0.008*"well" + 0.007*"Riding" + 0.006*"progress" + 0.006*"East" + 0.005*"2023" + 0.005*"10" + 0.005*"education" -2024-07-15 10:43:54,112 - topic #1 (0.333): 0.010*"’" + 0.008*"needs" + 0.007*"well" + 0.006*"plans" + 0.006*"progress" + 0.005*"Riding" + 0.005*"10" + 0.005*"East" + 0.004*"education" + 0.004*"place" -2024-07-15 10:43:54,112 - topic #2 (0.333): 0.017*"’" + 0.010*"needs" + 0.010*"plans" + 0.009*"well" + 0.007*"progress" + 0.007*"East" + 0.006*"Riding" + 0.005*"partners" + 0.005*"30" + 0.005*"good" -2024-07-15 10:43:54,112 - topic diff=0.779870, rho=1.000000 -2024-07-15 10:43:54,112 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:54.112872', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:55,147 - Inspection date 2023-01-30 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:55,147 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:55,147 - Inspection date 2023-01-30 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:55,147 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:55,148 - Inspection date 2023-01-30 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:55,148 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:55,148 - Inspection date 2023-01-30 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:55,148 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:55,148 - Inspection date 2023-01-30 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:55,148 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:55,148 - Inspection date 2023-01-30 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:55,149 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:56,613 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:56,616 - built Dictionary<1111 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2220 corpus positions) -2024-07-15 10:43:56,616 - Dictionary lifecycle event {'msg': "built Dictionary<1111 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2220 corpus positions)", 'datetime': '2024-07-15T10:43:56.616173', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:56,617 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:56,617 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:56,617 - using serial LDA version on this node -2024-07-15 10:43:56,618 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:56,618 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:56,621 - -8.074 per-word bound, 269.5 perplexity estimate based on a held-out corpus of 1 documents with 2220 words -2024-07-15 10:43:56,621 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:56,623 - topic #0 (0.333): 0.012*"’" + 0.008*"well" + 0.008*"needs" + 0.007*"plans" + 0.005*"progress" + 0.005*"East" + 0.005*"Sussex" + 0.005*"impact" + 0.005*"experiences" + 0.004*"including" -2024-07-15 10:43:56,623 - topic #1 (0.333): 0.014*"’" + 0.008*"needs" + 0.008*"well" + 0.006*"Sussex" + 0.006*"progress" + 0.006*"plans" + 0.005*"East" + 0.005*"including" + 0.004*"relationships" + 0.004*"impact" -2024-07-15 10:43:56,623 - topic #2 (0.333): 0.020*"’" + 0.011*"well" + 0.009*"plans" + 0.008*"East" + 0.007*"needs" + 0.007*"including" + 0.006*"Sussex" + 0.006*"progress" + 0.006*"provide" + 0.006*"11" -2024-07-15 10:43:56,623 - topic diff=0.770718, rho=1.000000 -2024-07-15 10:43:56,623 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:56.623949', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:57,644 - Inspection date 2023-12-11 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:43:57,644 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:57,644 - Inspection date 2023-12-11 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:43:57,644 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:57,645 - Inspection date 2023-12-11 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:43:57,645 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:57,645 - Inspection date 2023-12-11 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:43:57,645 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:57,645 - Inspection date 2023-12-11 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:43:57,645 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:57,646 - Inspection date 2023-12-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:43:57,646 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:43:59,063 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:43:59,067 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2686 corpus positions) -2024-07-15 10:43:59,067 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2686 corpus positions)", 'datetime': '2024-07-15T10:43:59.067879', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:43:59,069 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:43:59,070 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:43:59,070 - using serial LDA version on this node -2024-07-15 10:43:59,071 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:43:59,071 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:43:59,077 - -8.011 per-word bound, 258.0 perplexity estimate based on a held-out corpus of 1 documents with 2686 words -2024-07-15 10:43:59,077 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:43:59,079 - topic #0 (0.333): 0.015*"’" + 0.007*"needs" + 0.007*"plans" + 0.007*"family" + 0.007*"well" + 0.006*"progress" + 0.005*"Essex" + 0.005*"leaders" + 0.005*"understand" + 0.005*"parents" -2024-07-15 10:43:59,080 - topic #1 (0.333): 0.018*"’" + 0.007*"well" + 0.007*"progress" + 0.006*"needs" + 0.005*"experiences" + 0.005*"helped" + 0.005*"advisers" + 0.005*"‘" + 0.005*"Essex" + 0.005*"plans" -2024-07-15 10:43:59,080 - topic #2 (0.333): 0.020*"’" + 0.007*"well" + 0.006*"progress" + 0.006*"plans" + 0.005*"needs" + 0.005*"practice" + 0.005*"risk" + 0.005*"new" + 0.005*"need" + 0.005*"understand" -2024-07-15 10:43:59,080 - topic diff=0.807055, rho=1.000000 -2024-07-15 10:43:59,080 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:43:59.080945', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:00,126 - Inspection date 2023-06-26 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:00,127 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:00,127 - Inspection date 2023-06-26 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:00,127 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:00,128 - Inspection date 2023-06-26 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:00,128 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:00,128 - Inspection date 2023-06-26 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:00,128 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:00,129 - Inspection date 2023-06-26 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:00,129 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:00,129 - Inspection date 2023-06-26 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:00,129 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:01,602 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:01,604 - built Dictionary<1112 unique tokens: ['0161', '0300', '0–19', '1', '10']...> from 1 documents (total 2356 corpus positions) -2024-07-15 10:44:01,604 - Dictionary lifecycle event {'msg': "built Dictionary<1112 unique tokens: ['0161', '0300', '0–19', '1', '10']...> from 1 documents (total 2356 corpus positions)", 'datetime': '2024-07-15T10:44:01.604764', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:01,605 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:01,605 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:01,606 - using serial LDA version on this node -2024-07-15 10:44:01,606 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:01,606 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:01,610 - -8.041 per-word bound, 263.3 perplexity estimate based on a held-out corpus of 1 documents with 2356 words -2024-07-15 10:44:01,610 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:01,611 - topic #0 (0.333): 0.012*"’" + 0.009*"effective" + 0.007*"practice" + 0.006*"good" + 0.006*"needs" + 0.005*"quality" + 0.005*"early" + 0.005*"well" + 0.004*"home" + 0.004*"focus" -2024-07-15 10:44:01,612 - topic #1 (0.333): 0.015*"’" + 0.008*"quality" + 0.008*"effective" + 0.007*"good" + 0.007*"needs" + 0.006*"well" + 0.006*"timely" + 0.005*"practice" + 0.005*"plans" + 0.005*"improve" -2024-07-15 10:44:01,612 - topic #2 (0.333): 0.014*"’" + 0.009*"effective" + 0.007*"practice" + 0.006*"well" + 0.006*"good" + 0.006*"timely" + 0.005*"quality" + 0.005*"improve" + 0.005*"need" + 0.005*"early" -2024-07-15 10:44:01,612 - topic diff=0.764437, rho=1.000000 -2024-07-15 10:44:01,612 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:01.612590', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:02,522 - Inspection date 2019-04-29 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:02,522 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:02,523 - Inspection date 2019-04-29 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:02,523 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:02,523 - Inspection date 2019-04-29 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:02,523 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:02,523 - Inspection date 2019-04-29 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:02,524 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:02,524 - Inspection date 2019-04-29 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:02,524 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:02,524 - Inspection date 2019-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:02,524 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:03,753 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:03,756 - built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2579 corpus positions) -2024-07-15 10:44:03,756 - Dictionary lifecycle event {'msg': "built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2579 corpus positions)", 'datetime': '2024-07-15T10:44:03.756207', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:03,757 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:03,757 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:03,757 - using serial LDA version on this node -2024-07-15 10:44:03,758 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:03,758 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:03,762 - -8.065 per-word bound, 267.7 perplexity estimate based on a held-out corpus of 1 documents with 2579 words -2024-07-15 10:44:03,762 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:03,763 - topic #0 (0.333): 0.018*"’" + 0.009*"needs" + 0.007*"February" + 0.007*"plans" + 0.006*"2022" + 0.006*"progress" + 0.006*"well" + 0.005*"experienced" + 0.005*"good" + 0.004*"18" -2024-07-15 10:44:03,763 - topic #1 (0.333): 0.016*"’" + 0.010*"needs" + 0.007*"February" + 0.007*"2022" + 0.007*"Gloucestershire" + 0.006*"plans" + 0.006*"appropriate" + 0.005*"well" + 0.005*"leaders" + 0.005*"protection" -2024-07-15 10:44:03,764 - topic #2 (0.333): 0.017*"’" + 0.007*"2022" + 0.006*"needs" + 0.006*"plans" + 0.005*"February" + 0.005*"experienced" + 0.005*"timely" + 0.005*"7" + 0.005*"well" + 0.005*"18" -2024-07-15 10:44:03,764 - topic diff=0.823474, rho=1.000000 -2024-07-15 10:44:03,764 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:03.764331', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:04,873 - Inspection date 2022-02-07 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:04,873 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:04,873 - Inspection date 2022-02-07 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:04,873 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:04,874 - Inspection date 2022-02-07 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:04,874 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:04,874 - Inspection date 2022-02-07 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:04,874 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:04,874 - Inspection date 2022-02-07 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:04,874 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:04,875 - Inspection date 2022-02-07 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:04,875 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:06,698 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:06,701 - built Dictionary<1172 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2652 corpus positions) -2024-07-15 10:44:06,701 - Dictionary lifecycle event {'msg': "built Dictionary<1172 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2652 corpus positions)", 'datetime': '2024-07-15T10:44:06.701211', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:06,702 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:06,702 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:06,702 - using serial LDA version on this node -2024-07-15 10:44:06,703 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:06,703 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:06,707 - -8.060 per-word bound, 266.9 perplexity estimate based on a held-out corpus of 1 documents with 2652 words -2024-07-15 10:44:06,707 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:06,708 - topic #0 (0.333): 0.017*"’" + 0.007*"Halton" + 0.007*"quality" + 0.007*"needs" + 0.007*"many" + 0.006*"plans" + 0.005*"protection" + 0.005*"including" + 0.005*"13" + 0.005*"experiences" -2024-07-15 10:44:06,708 - topic #1 (0.333): 0.012*"’" + 0.007*"many" + 0.006*"needs" + 0.005*"including" + 0.005*"Halton" + 0.005*"quality" + 0.005*"lack" + 0.005*"recently" + 0.004*"Leaders" + 0.004*"need" -2024-07-15 10:44:06,708 - topic #2 (0.333): 0.016*"’" + 0.008*"needs" + 0.007*"need" + 0.006*"Halton" + 0.006*"including" + 0.005*"quality" + 0.005*"Leaders" + 0.004*"protection" + 0.004*"always" + 0.004*"2024" -2024-07-15 10:44:06,709 - topic diff=0.808243, rho=1.000000 -2024-07-15 10:44:06,709 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:06.709224', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:07,667 - Inspection date 2024-05-13 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:07,667 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:07,667 - Inspection date 2024-05-13 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:07,668 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:07,668 - Inspection date 2024-05-13 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:07,668 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:07,668 - Inspection date 2024-05-13 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:07,668 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:07,668 - Inspection date 2024-05-13 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:07,669 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:07,669 - Inspection date 2024-05-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:07,669 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:08,972 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:08,975 - built Dictionary<1182 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2382 corpus positions) -2024-07-15 10:44:08,975 - Dictionary lifecycle event {'msg': "built Dictionary<1182 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2382 corpus positions)", 'datetime': '2024-07-15T10:44:08.975891', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:08,977 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:08,977 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:08,977 - using serial LDA version on this node -2024-07-15 10:44:08,977 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:08,977 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:08,981 - -8.139 per-word bound, 281.8 perplexity estimate based on a held-out corpus of 1 documents with 2382 words -2024-07-15 10:44:08,981 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:08,983 - topic #0 (0.333): 0.020*"’" + 0.008*"needs" + 0.007*"plans" + 0.006*"quality" + 0.005*"well" + 0.004*"Hampshire" + 0.004*"leaders" + 0.004*"carers" + 0.004*"progress" + 0.004*"health" -2024-07-15 10:44:08,983 - topic #1 (0.333): 0.015*"’" + 0.006*"needs" + 0.005*"well" + 0.005*"strong" + 0.004*"leaders" + 0.004*"need" + 0.004*"plans" + 0.004*"highly" + 0.004*"improve" + 0.004*"home" -2024-07-15 10:44:08,983 - topic #2 (0.333): 0.020*"’" + 0.008*"needs" + 0.006*"well" + 0.006*"plans" + 0.005*"strong" + 0.005*"home" + 0.005*"leaders" + 0.004*"quality" + 0.004*"highly" + 0.004*"improve" -2024-07-15 10:44:08,983 - topic diff=0.747878, rho=1.000000 -2024-07-15 10:44:08,983 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:08.983957', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:10,099 - Inspection date 2019-04-29 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:10,099 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:10,099 - Inspection date 2019-04-29 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:10,099 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:10,100 - Inspection date 2019-04-29 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:10,100 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:10,100 - Inspection date 2019-04-29 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:10,100 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:10,100 - Inspection date 2019-04-29 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:10,100 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:10,101 - Inspection date 2019-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:10,101 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:11,671 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:11,674 - built Dictionary<1171 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2584 corpus positions) -2024-07-15 10:44:11,674 - Dictionary lifecycle event {'msg': "built Dictionary<1171 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2584 corpus positions)", 'datetime': '2024-07-15T10:44:11.674433', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:11,675 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:11,675 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:11,676 - using serial LDA version on this node -2024-07-15 10:44:11,676 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:11,676 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:11,680 - -8.070 per-word bound, 268.7 perplexity estimate based on a held-out corpus of 1 documents with 2584 words -2024-07-15 10:44:11,680 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:11,681 - topic #0 (0.333): 0.016*"’" + 0.007*"March" + 0.007*"Hartlepool" + 0.006*"well" + 0.005*"needs" + 0.004*"clear" + 0.004*"strong" + 0.004*"leaders" + 0.004*"practice" + 0.004*"18" -2024-07-15 10:44:11,682 - topic #1 (0.333): 0.019*"’" + 0.008*"March" + 0.007*"needs" + 0.007*"Hartlepool" + 0.006*"well" + 0.005*"effective" + 0.005*"good" + 0.005*"leaders" + 0.005*"practice" + 0.004*"strong" -2024-07-15 10:44:11,682 - topic #2 (0.333): 0.023*"’" + 0.008*"needs" + 0.007*"Hartlepool" + 0.007*"March" + 0.007*"leaders" + 0.006*"supported" + 0.006*"plans" + 0.006*"well" + 0.006*"18" + 0.005*"ensure" -2024-07-15 10:44:11,682 - topic diff=0.794003, rho=1.000000 -2024-07-15 10:44:11,682 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:11.682581', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:12,695 - Inspection date 2024-03-18 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:12,695 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:12,695 - Inspection date 2024-03-18 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:12,695 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:12,696 - Inspection date 2024-03-18 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:12,696 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:12,696 - Inspection date 2024-03-18 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:12,696 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:12,696 - Inspection date 2024-03-18 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:12,696 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:12,696 - Inspection date 2024-03-18 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:12,697 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:14,184 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:14,186 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions) -2024-07-15 10:44:14,186 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)", 'datetime': '2024-07-15T10:44:14.186388', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:14,187 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:14,187 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:14,187 - using serial LDA version on this node -2024-07-15 10:44:14,188 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:14,188 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:14,192 - -8.037 per-word bound, 262.7 perplexity estimate based on a held-out corpus of 1 documents with 2531 words -2024-07-15 10:44:14,192 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:14,193 - topic #0 (0.333): 0.020*"’" + 0.006*"practice" + 0.005*"needs" + 0.005*"lack" + 0.005*"quality" + 0.004*"impact" + 0.004*"carers" + 0.004*"plans" + 0.004*"Herefordshire" + 0.004*"oversight" -2024-07-15 10:44:14,193 - topic #1 (0.333): 0.015*"’" + 0.006*"Herefordshire" + 0.005*"impact" + 0.004*"plans" + 0.004*"many" + 0.004*"needs" + 0.004*"practice" + 0.004*"July" + 0.004*"18" + 0.004*"carers" -2024-07-15 10:44:14,194 - topic #2 (0.333): 0.016*"’" + 0.006*"practice" + 0.006*"lack" + 0.006*"Herefordshire" + 0.005*"impact" + 0.005*"many" + 0.004*"progress" + 0.004*"18" + 0.004*"management" + 0.004*"needs" -2024-07-15 10:44:14,194 - topic diff=0.787751, rho=1.000000 -2024-07-15 10:44:14,194 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:14.194416', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:15,298 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:15,298 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:15,299 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:15,299 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:15,299 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:15,299 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:15,300 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:15,300 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:15,300 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:15,300 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:15,300 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:15,300 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:16,663 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:16,665 - built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '100']...> from 1 documents (total 2456 corpus positions) -2024-07-15 10:44:16,665 - Dictionary lifecycle event {'msg': "built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '100']...> from 1 documents (total 2456 corpus positions)", 'datetime': '2024-07-15T10:44:16.665931', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:16,667 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:16,667 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:16,667 - using serial LDA version on this node -2024-07-15 10:44:16,667 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:16,667 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:16,671 - -8.136 per-word bound, 281.3 perplexity estimate based on a held-out corpus of 1 documents with 2456 words -2024-07-15 10:44:16,671 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:16,673 - topic #0 (0.333): 0.024*"’" + 0.007*"well" + 0.006*"Hertfordshire" + 0.006*"needs" + 0.006*"receive" + 0.005*"2023" + 0.004*"risk" + 0.004*"plans" + 0.004*"23" + 0.004*"positive" -2024-07-15 10:44:16,673 - topic #1 (0.333): 0.018*"’" + 0.006*"needs" + 0.006*"well" + 0.005*"receive" + 0.005*"Hertfordshire" + 0.004*"plans" + 0.004*"effective" + 0.004*"positive" + 0.004*"need" + 0.004*"risk" -2024-07-15 10:44:16,673 - topic #2 (0.333): 0.025*"’" + 0.008*"Hertfordshire" + 0.006*"well" + 0.006*"needs" + 0.005*"‘" + 0.005*"27" + 0.004*"leaders" + 0.004*"plans" + 0.004*"receive" + 0.004*"Leaders" -2024-07-15 10:44:16,673 - topic diff=0.789150, rho=1.000000 -2024-07-15 10:44:16,674 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:16.673982', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:18,497 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:18,497 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:18,497 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:18,497 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:18,498 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:18,498 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:18,498 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:18,498 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:18,498 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:18,498 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:18,499 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:18,499 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:19,771 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:19,773 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '10-year']...> from 1 documents (total 1934 corpus positions) -2024-07-15 10:44:19,773 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '10-year']...> from 1 documents (total 1934 corpus positions)", 'datetime': '2024-07-15T10:44:19.773450', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:19,774 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:19,775 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:19,775 - using serial LDA version on this node -2024-07-15 10:44:19,775 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:19,775 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:19,779 - -7.951 per-word bound, 247.4 perplexity estimate based on a held-out corpus of 1 documents with 1934 words -2024-07-15 10:44:19,779 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:19,780 - topic #0 (0.333): 0.016*"’" + 0.009*"leaders" + 0.007*"well" + 0.006*"practice" + 0.006*"plans" + 0.006*"Isle" + 0.006*"Wight" + 0.005*"progress" + 0.005*"supported" + 0.005*"improve" -2024-07-15 10:44:19,780 - topic #1 (0.333): 0.014*"’" + 0.007*"leaders" + 0.005*"needs" + 0.005*"3" + 0.004*"Senior" + 0.004*"effective" + 0.004*"Isle" + 0.004*"PAs" + 0.004*"supported" + 0.004*"Wight" -2024-07-15 10:44:19,780 - topic #2 (0.333): 0.022*"’" + 0.008*"leaders" + 0.007*"needs" + 0.005*"good" + 0.005*"3" + 0.005*"well" + 0.005*"30" + 0.005*"time" + 0.005*"protection" + 0.005*"Senior" -2024-07-15 10:44:19,780 - topic diff=0.785739, rho=1.000000 -2024-07-15 10:44:19,781 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:19.781046', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:20,907 - Inspection date 2023-10-30 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:20,908 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:20,908 - Inspection date 2023-10-30 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:20,908 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:20,908 - Inspection date 2023-10-30 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:20,908 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:20,908 - Inspection date 2023-10-30 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:20,909 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:20,909 - Inspection date 2023-10-30 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:20,909 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:20,909 - Inspection date 2023-10-30 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:20,909 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:23,102 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:23,105 - built Dictionary<1298 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2888 corpus positions) -2024-07-15 10:44:23,105 - Dictionary lifecycle event {'msg': "built Dictionary<1298 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2888 corpus positions)", 'datetime': '2024-07-15T10:44:23.105417', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:23,106 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:23,106 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:23,107 - using serial LDA version on this node -2024-07-15 10:44:23,107 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:23,107 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:23,111 - -8.174 per-word bound, 288.7 perplexity estimate based on a held-out corpus of 1 documents with 2888 words -2024-07-15 10:44:23,111 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:23,113 - topic #0 (0.333): 0.015*"’" + 0.008*"Kent" + 0.006*"needs" + 0.006*"supported" + 0.005*"County" + 0.005*"Council" + 0.005*"progress" + 0.005*"well" + 0.004*"practice" + 0.004*"impact" -2024-07-15 10:44:23,113 - topic #1 (0.333): 0.023*"’" + 0.010*"Kent" + 0.007*"needs" + 0.006*"well" + 0.006*"progress" + 0.005*"supported" + 0.005*"Council" + 0.005*"County" + 0.004*"including" + 0.004*"practice" -2024-07-15 10:44:23,113 - topic #2 (0.333): 0.015*"’" + 0.011*"Kent" + 0.009*"needs" + 0.008*"Council" + 0.006*"well" + 0.006*"supported" + 0.005*"leaders" + 0.005*"County" + 0.004*"practice" + 0.004*"including" -2024-07-15 10:44:23,113 - topic diff=0.802634, rho=1.000000 -2024-07-15 10:44:23,114 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:23.114048', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:24,062 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:24,062 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:24,063 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:24,063 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:24,063 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:24,063 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:24,063 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:24,064 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:24,064 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:24,064 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:24,064 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:24,064 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:25,244 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:25,247 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1970 corpus positions) -2024-07-15 10:44:25,248 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1970 corpus positions)", 'datetime': '2024-07-15T10:44:25.248194', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:25,249 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:25,250 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:25,250 - using serial LDA version on this node -2024-07-15 10:44:25,251 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:25,251 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:25,257 - -7.944 per-word bound, 246.3 perplexity estimate based on a held-out corpus of 1 documents with 1970 words -2024-07-15 10:44:25,257 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:25,259 - topic #0 (0.333): 0.017*"’" + 0.007*"protection" + 0.007*"number" + 0.006*"practice" + 0.006*"management" + 0.005*"planning" + 0.005*"Hull" + 0.005*"impact" + 0.005*"teams" + 0.005*"well" -2024-07-15 10:44:25,260 - topic #1 (0.333): 0.018*"’" + 0.007*"planning" + 0.007*"need" + 0.006*"number" + 0.006*"Hull" + 0.006*"practice" + 0.006*"25" + 0.005*"progress" + 0.005*"well" + 0.005*"oversight" -2024-07-15 10:44:25,260 - topic #2 (0.333): 0.012*"’" + 0.008*"number" + 0.007*"well" + 0.007*"planning" + 0.006*"protection" + 0.006*"risks" + 0.005*"need" + 0.005*"practice" + 0.005*"agency" + 0.005*"small" -2024-07-15 10:44:25,260 - topic diff=0.752620, rho=1.000000 -2024-07-15 10:44:25,261 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:25.261017', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:26,469 - Inspection date 2022-11-14 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:26,469 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:26,469 - Inspection date 2022-11-14 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:26,470 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:26,470 - Inspection date 2022-11-14 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:26,470 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:26,470 - Inspection date 2022-11-14 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:26,470 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:26,470 - Inspection date 2022-11-14 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:26,471 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:26,471 - Inspection date 2022-11-14 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:26,471 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:28,044 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:28,046 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2489 corpus positions) -2024-07-15 10:44:28,047 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2489 corpus positions)", 'datetime': '2024-07-15T10:44:28.047160', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:28,048 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:28,048 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:28,048 - using serial LDA version on this node -2024-07-15 10:44:28,049 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:28,049 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:28,053 - -8.052 per-word bound, 265.4 perplexity estimate based on a held-out corpus of 1 documents with 2489 words -2024-07-15 10:44:28,053 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:28,054 - topic #0 (0.333): 0.012*"’" + 0.006*"practice" + 0.006*"good" + 0.006*"senior" + 0.006*"permanence" + 0.005*"Senior" + 0.005*"plans" + 0.005*"quality" + 0.005*"protection" + 0.004*"training" -2024-07-15 10:44:28,054 - topic #1 (0.333): 0.013*"’" + 0.008*"quality" + 0.006*"practice" + 0.005*"plans" + 0.005*"training" + 0.004*"protection" + 0.004*"needs" + 0.004*"response" + 0.004*"well" + 0.004*"good" -2024-07-15 10:44:28,055 - topic #2 (0.333): 0.011*"’" + 0.007*"good" + 0.007*"quality" + 0.006*"practice" + 0.006*"well" + 0.006*"needs" + 0.005*"plans" + 0.005*"Senior" + 0.005*"permanence" + 0.005*"protection" -2024-07-15 10:44:28,055 - topic diff=0.788828, rho=1.000000 -2024-07-15 10:44:28,055 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:28.055514', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:29,046 - Inspection date 2019-06-10 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:29,047 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:29,047 - Inspection date 2019-06-10 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:29,047 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:29,047 - Inspection date 2019-06-10 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:29,047 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:29,048 - Inspection date 2019-06-10 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:29,048 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:29,048 - Inspection date 2019-06-10 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:29,048 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:29,048 - Inspection date 2019-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:29,048 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:30,195 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:30,197 - built Dictionary<886 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1837 corpus positions) -2024-07-15 10:44:30,197 - Dictionary lifecycle event {'msg': "built Dictionary<886 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1837 corpus positions)", 'datetime': '2024-07-15T10:44:30.197419', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:30,198 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:30,198 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:30,198 - using serial LDA version on this node -2024-07-15 10:44:30,199 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:30,199 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:30,202 - -7.830 per-word bound, 227.6 perplexity estimate based on a held-out corpus of 1 documents with 1837 words -2024-07-15 10:44:30,202 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:30,203 - topic #0 (0.333): 0.017*"’" + 0.009*"progress" + 0.008*"quality" + 0.008*"needs" + 0.007*"plans" + 0.007*"Knowsley" + 0.006*"2021" + 0.005*"need" + 0.005*"experiences" + 0.005*"good" -2024-07-15 10:44:30,203 - topic #1 (0.333): 0.011*"’" + 0.008*"progress" + 0.008*"plans" + 0.007*"needs" + 0.006*"Knowsley" + 0.006*"2021" + 0.005*"abuse" + 0.005*"experiences" + 0.005*"good" + 0.005*"22" -2024-07-15 10:44:30,203 - topic #2 (0.333): 0.013*"’" + 0.008*"quality" + 0.007*"progress" + 0.007*"needs" + 0.006*"plans" + 0.005*"Knowsley" + 0.005*"impact" + 0.005*"22" + 0.005*"2021" + 0.005*"education" -2024-07-15 10:44:30,204 - topic diff=0.745663, rho=1.000000 -2024-07-15 10:44:30,204 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:30.204198', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:31,287 - Inspection date 2021-10-11 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:31,288 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:31,288 - Inspection date 2021-10-11 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:31,288 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:31,288 - Inspection date 2021-10-11 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:31,289 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:31,289 - Inspection date 2021-10-11 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:31,289 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:31,289 - Inspection date 2021-10-11 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:31,289 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:31,290 - Inspection date 2021-10-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:31,290 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:32,521 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:32,523 - built Dictionary<1048 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2263 corpus positions) -2024-07-15 10:44:32,523 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2263 corpus positions)", 'datetime': '2024-07-15T10:44:32.523509', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:32,524 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:32,524 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:32,524 - using serial LDA version on this node -2024-07-15 10:44:32,525 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:32,525 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:32,529 - -7.972 per-word bound, 251.0 perplexity estimate based on a held-out corpus of 1 documents with 2263 words -2024-07-15 10:44:32,529 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:32,530 - topic #0 (0.333): 0.010*"’" + 0.006*"well" + 0.005*"supported" + 0.005*"need" + 0.005*"needs" + 0.004*"live" + 0.004*"Lancashire" + 0.004*"plans" + 0.004*"positive" + 0.004*"practice" -2024-07-15 10:44:32,530 - topic #1 (0.333): 0.021*"’" + 0.010*"well" + 0.008*"need" + 0.008*"needs" + 0.007*"Lancashire" + 0.006*"plans" + 0.005*"progress" + 0.005*"health" + 0.005*"live" + 0.005*"practice" -2024-07-15 10:44:32,530 - topic #2 (0.333): 0.015*"’" + 0.009*"well" + 0.008*"needs" + 0.006*"need" + 0.006*"Lancashire" + 0.006*"positive" + 0.006*"supported" + 0.005*"homes" + 0.005*"practice" + 0.005*"9" -2024-07-15 10:44:32,530 - topic diff=0.795958, rho=1.000000 -2024-07-15 10:44:32,531 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:32.531145', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:33,529 - Inspection date 2022-11-28 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:33,529 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:33,529 - Inspection date 2022-11-28 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:33,529 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:33,529 - Inspection date 2022-11-28 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:33,530 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:33,530 - Inspection date 2022-11-28 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:33,530 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:33,530 - Inspection date 2022-11-28 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:33,530 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:33,530 - Inspection date 2022-11-28 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:33,530 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:34,780 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:34,782 - built Dictionary<1071 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2261 corpus positions) -2024-07-15 10:44:34,782 - Dictionary lifecycle event {'msg': "built Dictionary<1071 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2261 corpus positions)", 'datetime': '2024-07-15T10:44:34.782971', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:34,784 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:34,784 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:34,784 - using serial LDA version on this node -2024-07-15 10:44:34,784 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:34,784 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:34,788 - -8.007 per-word bound, 257.3 perplexity estimate based on a held-out corpus of 1 documents with 2261 words -2024-07-15 10:44:34,788 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:34,789 - topic #0 (0.333): 0.015*"’" + 0.008*"needs" + 0.007*"Leeds" + 0.005*"well" + 0.005*"plans" + 0.005*"ensure" + 0.005*"risk" + 0.004*"practice" + 0.004*"4" + 0.004*"protection" -2024-07-15 10:44:34,790 - topic #1 (0.333): 0.015*"’" + 0.007*"needs" + 0.007*"well" + 0.006*"Leeds" + 0.005*"2022" + 0.005*"practice" + 0.004*"risk" + 0.004*"protection" + 0.004*"ensure" + 0.004*"21" -2024-07-15 10:44:34,790 - topic #2 (0.333): 0.017*"’" + 0.008*"Leeds" + 0.006*"needs" + 0.006*"risk" + 0.006*"well" + 0.005*"supported" + 0.004*"information" + 0.004*"4" + 0.004*"protection" + 0.004*"plans" -2024-07-15 10:44:34,790 - topic diff=0.775132, rho=1.000000 -2024-07-15 10:44:34,790 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:34.790554', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:35,718 - Inspection date 2022-02-21 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:35,718 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:35,718 - Inspection date 2022-02-21 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:35,718 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:35,719 - Inspection date 2022-02-21 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:35,719 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:35,719 - Inspection date 2022-02-21 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:35,719 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:35,719 - Inspection date 2022-02-21 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:35,719 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:35,720 - Inspection date 2022-02-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:35,720 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:37,060 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:37,062 - built Dictionary<932 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1950 corpus positions) -2024-07-15 10:44:37,062 - Dictionary lifecycle event {'msg': "built Dictionary<932 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1950 corpus positions)", 'datetime': '2024-07-15T10:44:37.062306', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:37,063 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:37,063 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:37,063 - using serial LDA version on this node -2024-07-15 10:44:37,064 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:37,064 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:37,067 - -7.875 per-word bound, 234.7 perplexity estimate based on a held-out corpus of 1 documents with 1950 words -2024-07-15 10:44:37,067 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:37,068 - topic #0 (0.333): 0.022*"’" + 0.011*"well" + 0.009*"2021" + 0.009*"Leicester" + 0.008*"needs" + 0.006*"ensure" + 0.006*"good" + 0.006*"1" + 0.005*"number" + 0.005*"Council" -2024-07-15 10:44:37,069 - topic #1 (0.333): 0.016*"’" + 0.007*"well" + 0.006*"Leicester" + 0.006*"2021" + 0.006*"ensure" + 0.005*"good" + 0.005*"number" + 0.005*"20" + 0.005*"including" + 0.005*"1" -2024-07-15 10:44:37,069 - topic #2 (0.333): 0.020*"’" + 0.009*"2021" + 0.008*"well" + 0.007*"Leicester" + 0.006*"good" + 0.006*"needs" + 0.005*"number" + 0.005*"20" + 0.005*"October" + 0.005*"including" -2024-07-15 10:44:37,069 - topic diff=0.784057, rho=1.000000 -2024-07-15 10:44:37,069 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:37.069466', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:38,214 - Inspection date 2021-09-20 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:38,214 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:38,214 - Inspection date 2021-09-20 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:38,214 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:38,215 - Inspection date 2021-09-20 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:38,215 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:38,215 - Inspection date 2021-09-20 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:38,215 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:38,215 - Inspection date 2021-09-20 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:38,215 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:38,216 - Inspection date 2021-09-20 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:38,216 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:39,734 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:39,737 - built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2745 corpus positions) -2024-07-15 10:44:39,737 - Dictionary lifecycle event {'msg': "built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2745 corpus positions)", 'datetime': '2024-07-15T10:44:39.737331', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:39,738 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:39,738 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:39,738 - using serial LDA version on this node -2024-07-15 10:44:39,739 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:39,739 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:39,743 - -8.111 per-word bound, 276.4 perplexity estimate based on a held-out corpus of 1 documents with 2745 words -2024-07-15 10:44:39,743 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:39,745 - topic #0 (0.333): 0.019*"’" + 0.009*"well" + 0.007*"Leicestershire" + 0.006*"need" + 0.006*"experiences" + 0.006*"family" + 0.006*"understand" + 0.006*"plans" + 0.005*"needs" + 0.005*"ensure" -2024-07-15 10:44:39,745 - topic #1 (0.333): 0.018*"’" + 0.009*"well" + 0.006*"Leicestershire" + 0.006*"needs" + 0.005*"risk" + 0.005*"progress" + 0.004*"3" + 0.004*"family" + 0.004*"plans" + 0.004*"understand" -2024-07-15 10:44:39,745 - topic #2 (0.333): 0.017*"’" + 0.008*"well" + 0.006*"Leicestershire" + 0.006*"family" + 0.005*"need" + 0.005*"needs" + 0.005*"PAs" + 0.004*"experiences" + 0.004*"plans" + 0.004*"understand" -2024-07-15 10:44:39,745 - topic diff=0.818913, rho=1.000000 -2024-07-15 10:44:39,745 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:39.745855', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:40,716 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:40,716 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:40,716 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:40,716 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:40,716 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:40,716 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:40,717 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:40,717 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:40,717 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:40,717 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:40,717 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:40,717 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:42,297 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:42,300 - built Dictionary<1323 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2927 corpus positions) -2024-07-15 10:44:42,300 - Dictionary lifecycle event {'msg': "built Dictionary<1323 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2927 corpus positions)", 'datetime': '2024-07-15T10:44:42.300815', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:42,302 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:42,302 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:42,302 - using serial LDA version on this node -2024-07-15 10:44:42,302 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:42,303 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:42,307 - -8.191 per-word bound, 292.3 perplexity estimate based on a held-out corpus of 1 documents with 2927 words -2024-07-15 10:44:42,307 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:42,308 - topic #0 (0.333): 0.020*"’" + 0.006*"needs" + 0.006*"Lincolnshire" + 0.006*"family" + 0.005*"well" + 0.005*"progress" + 0.004*"plans" + 0.004*"need" + 0.004*"24" + 0.004*"number" -2024-07-15 10:44:42,309 - topic #1 (0.333): 0.018*"’" + 0.008*"Lincolnshire" + 0.006*"needs" + 0.005*"plans" + 0.005*"well" + 0.004*"education" + 0.004*"family" + 0.004*"24" + 0.004*"progress" + 0.004*"April" -2024-07-15 10:44:42,309 - topic #2 (0.333): 0.025*"’" + 0.008*"Lincolnshire" + 0.007*"needs" + 0.007*"well" + 0.005*"28" + 0.005*"progress" + 0.004*"plans" + 0.004*"working" + 0.004*"24" + 0.004*"2023" -2024-07-15 10:44:42,309 - topic diff=0.789936, rho=1.000000 -2024-07-15 10:44:42,309 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:42.309508', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:43,241 - Inspection date 2023-04-24 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:43,242 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:43,242 - Inspection date 2023-04-24 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:43,242 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:43,242 - Inspection date 2023-04-24 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:43,242 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:43,243 - Inspection date 2023-04-24 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:43,243 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:43,243 - Inspection date 2023-04-24 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:43,243 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:43,243 - Inspection date 2023-04-24 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:43,243 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:44,884 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:44,886 - built Dictionary<1134 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions) -2024-07-15 10:44:44,887 - Dictionary lifecycle event {'msg': "built Dictionary<1134 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)", 'datetime': '2024-07-15T10:44:44.887083', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:44,888 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:44,888 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:44,888 - using serial LDA version on this node -2024-07-15 10:44:44,889 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:44,889 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:44,892 - -7.992 per-word bound, 254.6 perplexity estimate based on a held-out corpus of 1 documents with 2720 words -2024-07-15 10:44:44,892 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:44,894 - topic #0 (0.333): 0.017*"’" + 0.009*"needs" + 0.006*"quality" + 0.005*"need" + 0.004*"practice" + 0.004*"24" + 0.004*"PAs" + 0.004*"Liverpool" + 0.004*"timely" + 0.004*"protection" -2024-07-15 10:44:44,894 - topic #1 (0.333): 0.022*"’" + 0.008*"practice" + 0.007*"always" + 0.007*"need" + 0.007*"needs" + 0.006*"Liverpool" + 0.006*"quality" + 0.005*"13" + 0.005*"harm" + 0.005*"protection" -2024-07-15 10:44:44,894 - topic #2 (0.333): 0.017*"’" + 0.007*"always" + 0.006*"need" + 0.006*"Liverpool" + 0.006*"practice" + 0.006*"needs" + 0.005*"protection" + 0.005*"24" + 0.005*"quality" + 0.004*"timely" -2024-07-15 10:44:44,894 - topic diff=0.841859, rho=1.000000 -2024-07-15 10:44:44,894 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:44.894929', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:45,844 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:45,844 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:45,844 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:45,844 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:45,844 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:45,845 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:45,845 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:45,845 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:45,845 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:45,845 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:45,845 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:45,845 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:47,658 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:47,660 - built Dictionary<1193 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2610 corpus positions) -2024-07-15 10:44:47,660 - Dictionary lifecycle event {'msg': "built Dictionary<1193 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2610 corpus positions)", 'datetime': '2024-07-15T10:44:47.660908', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:47,662 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:47,662 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:47,662 - using serial LDA version on this node -2024-07-15 10:44:47,662 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:47,662 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:47,666 - -8.095 per-word bound, 273.4 perplexity estimate based on a held-out corpus of 1 documents with 2610 words -2024-07-15 10:44:47,666 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:47,668 - topic #0 (0.333): 0.022*"’" + 0.009*"needs" + 0.006*"plans" + 0.005*"carers" + 0.005*"good" + 0.005*"London" + 0.005*"planning" + 0.005*"Barking" + 0.005*"leaders" + 0.005*"practice" -2024-07-15 10:44:47,668 - topic #1 (0.333): 0.029*"’" + 0.009*"needs" + 0.007*"well" + 0.007*"good" + 0.006*"plans" + 0.006*"progress" + 0.006*"practice" + 0.005*"carers" + 0.005*"information" + 0.005*"e" -2024-07-15 10:44:47,668 - topic #2 (0.333): 0.008*"’" + 0.004*"Barking" + 0.004*"good" + 0.004*"information" + 0.004*"well" + 0.004*"needs" + 0.004*"plans" + 0.004*"Dagenham" + 0.004*"planning" + 0.004*"ensure" -2024-07-15 10:44:47,668 - topic diff=0.824433, rho=1.000000 -2024-07-15 10:44:47,669 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:47.669067', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:48,727 - Inspection date 2023-07-10 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:48,727 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:48,727 - Inspection date 2023-07-10 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:48,727 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:48,728 - Inspection date 2023-07-10 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:48,728 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:48,728 - Inspection date 2023-07-10 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:48,728 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:48,728 - Inspection date 2023-07-10 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:48,728 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:48,728 - Inspection date 2023-07-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:48,728 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:51,000 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:51,002 - built Dictionary<978 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1956 corpus positions) -2024-07-15 10:44:51,002 - Dictionary lifecycle event {'msg': "built Dictionary<978 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1956 corpus positions)", 'datetime': '2024-07-15T10:44:51.002713', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:51,003 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:51,003 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:51,004 - using serial LDA version on this node -2024-07-15 10:44:51,004 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:51,004 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:51,007 - -7.954 per-word bound, 247.9 perplexity estimate based on a held-out corpus of 1 documents with 1956 words -2024-07-15 10:44:51,007 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:51,009 - topic #0 (0.333): 0.013*"’" + 0.010*"good" + 0.010*"needs" + 0.008*"need" + 0.006*"well" + 0.006*"plans" + 0.006*"ensure" + 0.006*"clear" + 0.006*"carers" + 0.005*"progress" -2024-07-15 10:44:51,009 - topic #1 (0.333): 0.014*"’" + 0.010*"well" + 0.009*"good" + 0.008*"needs" + 0.008*"need" + 0.007*"progress" + 0.006*"receive" + 0.006*"ensure" + 0.005*"plans" + 0.005*"clear" -2024-07-15 10:44:51,009 - topic #2 (0.333): 0.015*"’" + 0.010*"needs" + 0.009*"well" + 0.008*"good" + 0.007*"progress" + 0.006*"need" + 0.006*"quality" + 0.006*"appropriate" + 0.006*"plans" + 0.005*"clear" -2024-07-15 10:44:51,009 - topic diff=0.767555, rho=1.000000 -2024-07-15 10:44:51,009 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:51.009673', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:51,978 - Inspection date 2019-05-13 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:51,978 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:51,979 - Inspection date 2019-05-13 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:51,979 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:51,979 - Inspection date 2019-05-13 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:51,979 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:51,979 - Inspection date 2019-05-13 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:51,980 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:51,980 - Inspection date 2019-05-13 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:51,980 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:51,980 - Inspection date 2019-05-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:51,980 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:53,580 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:53,583 - built Dictionary<1190 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2563 corpus positions) -2024-07-15 10:44:53,583 - Dictionary lifecycle event {'msg': "built Dictionary<1190 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2563 corpus positions)", 'datetime': '2024-07-15T10:44:53.583502', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:53,584 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:53,584 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:53,585 - using serial LDA version on this node -2024-07-15 10:44:53,585 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:53,585 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:53,589 - -8.104 per-word bound, 275.2 perplexity estimate based on a held-out corpus of 1 documents with 2563 words -2024-07-15 10:44:53,589 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:53,590 - topic #0 (0.333): 0.025*"’" + 0.008*"well" + 0.007*"need" + 0.006*"plans" + 0.006*"needs" + 0.006*"effective" + 0.006*"Bexley" + 0.005*"6" + 0.004*"clear" + 0.004*"10" -2024-07-15 10:44:53,591 - topic #1 (0.333): 0.016*"’" + 0.007*"needs" + 0.006*"plans" + 0.005*"effective" + 0.005*"well" + 0.005*"10" + 0.004*"Bexley" + 0.004*"need" + 0.004*"practice" + 0.004*"level" -2024-07-15 10:44:53,591 - topic #2 (0.333): 0.015*"’" + 0.006*"needs" + 0.005*"effective" + 0.005*"well" + 0.005*"Bexley" + 0.004*"practice" + 0.004*"including" + 0.004*"need" + 0.004*"oversight" + 0.004*"10" -2024-07-15 10:44:53,591 - topic diff=0.785100, rho=1.000000 -2024-07-15 10:44:53,591 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:53.591458', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:54,567 - Inspection date 2023-02-06 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:54,567 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:54,567 - Inspection date 2023-02-06 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:54,567 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:54,568 - Inspection date 2023-02-06 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:54,568 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:54,568 - Inspection date 2023-02-06 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:54,568 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:54,568 - Inspection date 2023-02-06 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:54,568 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:54,569 - Inspection date 2023-02-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:54,569 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:56,005 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:56,007 - built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2371 corpus positions) -2024-07-15 10:44:56,007 - Dictionary lifecycle event {'msg': "built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2371 corpus positions)", 'datetime': '2024-07-15T10:44:56.007360', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:56,008 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:56,008 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:56,008 - using serial LDA version on this node -2024-07-15 10:44:56,009 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:56,009 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:56,012 - -7.930 per-word bound, 243.8 perplexity estimate based on a held-out corpus of 1 documents with 2371 words -2024-07-15 10:44:56,012 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:56,014 - topic #0 (0.333): 0.020*"’" + 0.009*"well" + 0.008*"progress" + 0.007*"leaders" + 0.006*"good" + 0.006*"number" + 0.006*"Brent" + 0.005*"timely" + 0.005*"plans" + 0.005*"information" -2024-07-15 10:44:56,014 - topic #1 (0.333): 0.018*"’" + 0.009*"plans" + 0.009*"well" + 0.007*"leaders" + 0.006*"quality" + 0.006*"senior" + 0.006*"practice" + 0.005*"progress" + 0.005*"number" + 0.005*"good" -2024-07-15 10:44:56,014 - topic #2 (0.333): 0.011*"’" + 0.007*"leaders" + 0.007*"well" + 0.005*"Brent" + 0.005*"good" + 0.005*"senior" + 0.004*"progress" + 0.004*"small" + 0.004*"number" + 0.004*"plans" -2024-07-15 10:44:56,014 - topic diff=0.830040, rho=1.000000 -2024-07-15 10:44:56,014 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:56.014727', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:57,086 - Inspection date 2023-02-20 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:44:57,086 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:57,087 - Inspection date 2023-02-20 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:44:57,087 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:57,087 - Inspection date 2023-02-20 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:44:57,087 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:57,087 - Inspection date 2023-02-20 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:44:57,088 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:57,088 - Inspection date 2023-02-20 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:44:57,088 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:57,088 - Inspection date 2023-02-20 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:44:57,088 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:44:59,021 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:44:59,023 - built Dictionary<1266 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2640 corpus positions) -2024-07-15 10:44:59,024 - Dictionary lifecycle event {'msg': "built Dictionary<1266 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2640 corpus positions)", 'datetime': '2024-07-15T10:44:59.024203', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:44:59,025 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:44:59,025 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:44:59,025 - using serial LDA version on this node -2024-07-15 10:44:59,026 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:44:59,026 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:44:59,030 - -8.183 per-word bound, 290.7 perplexity estimate based on a held-out corpus of 1 documents with 2640 words -2024-07-15 10:44:59,030 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:44:59,032 - topic #0 (0.333): 0.018*"’" + 0.011*"Bromley" + 0.008*"needs" + 0.007*"well" + 0.005*"plans" + 0.005*"leaders" + 0.005*"education" + 0.005*"experiences" + 0.005*"health" + 0.005*"practice" -2024-07-15 10:44:59,032 - topic #1 (0.333): 0.018*"’" + 0.007*"well" + 0.007*"Bromley" + 0.005*"needs" + 0.005*"leaders" + 0.005*"practice" + 0.004*"health" + 0.004*"education" + 0.004*"plans" + 0.004*"YPAs" -2024-07-15 10:44:59,032 - topic #2 (0.333): 0.023*"’" + 0.008*"Bromley" + 0.006*"plans" + 0.006*"needs" + 0.006*"well" + 0.005*"leaders" + 0.005*"practice" + 0.005*"progress" + 0.004*"17" + 0.004*"strong" -2024-07-15 10:44:59,032 - topic diff=0.770029, rho=1.000000 -2024-07-15 10:44:59,032 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:44:59.032942', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:00,037 - Inspection date 2023-11-13 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:00,038 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:00,038 - Inspection date 2023-11-13 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:00,038 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:00,038 - Inspection date 2023-11-13 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:00,039 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:00,039 - Inspection date 2023-11-13 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:00,039 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:00,039 - Inspection date 2023-11-13 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:00,039 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:00,040 - Inspection date 2023-11-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:00,040 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:01,324 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:01,326 - built Dictionary<993 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1735 corpus positions) -2024-07-15 10:45:01,327 - Dictionary lifecycle event {'msg': "built Dictionary<993 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1735 corpus positions)", 'datetime': '2024-07-15T10:45:01.327003', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:01,327 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:01,328 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:01,328 - using serial LDA version on this node -2024-07-15 10:45:01,328 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:01,328 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:01,332 - -8.064 per-word bound, 267.6 perplexity estimate based on a held-out corpus of 1 documents with 1735 words -2024-07-15 10:45:01,332 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:01,333 - topic #0 (0.333): 0.010*"’" + 0.008*"Camden" + 0.006*"leaders" + 0.006*"needs" + 0.006*"protection" + 0.005*"well" + 0.005*"practice" + 0.005*"25" + 0.005*"appropriate" + 0.004*"29" -2024-07-15 10:45:01,333 - topic #1 (0.333): 0.009*"’" + 0.006*"leaders" + 0.006*"practice" + 0.006*"Camden" + 0.005*"protection" + 0.005*"well" + 0.005*"response" + 0.004*"needs" + 0.004*"appropriate" + 0.004*"29" -2024-07-15 10:45:01,334 - topic #2 (0.333): 0.012*"’" + 0.007*"Camden" + 0.007*"leaders" + 0.007*"practice" + 0.005*"well" + 0.005*"response" + 0.004*"2022" + 0.004*"April" + 0.004*"needs" + 0.004*"progress" -2024-07-15 10:45:01,334 - topic diff=0.700340, rho=1.000000 -2024-07-15 10:45:01,334 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:01.334325', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:02,331 - Inspection date 2022-04-25 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:02,331 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:02,331 - Inspection date 2022-04-25 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:02,331 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:02,332 - Inspection date 2022-04-25 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:02,332 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:02,332 - Inspection date 2022-04-25 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:02,332 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:02,332 - Inspection date 2022-04-25 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:02,332 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:02,333 - Inspection date 2022-04-25 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:02,333 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:03,809 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:03,811 - built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2209 corpus positions) -2024-07-15 10:45:03,811 - Dictionary lifecycle event {'msg': "built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2209 corpus positions)", 'datetime': '2024-07-15T10:45:03.811693', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:03,814 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:03,814 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:03,814 - using serial LDA version on this node -2024-07-15 10:45:03,815 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:03,815 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:03,821 - -7.988 per-word bound, 253.9 perplexity estimate based on a held-out corpus of 1 documents with 2209 words -2024-07-15 10:45:03,821 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:03,823 - topic #0 (0.333): 0.013*"’" + 0.008*"well" + 0.007*"Croydon" + 0.007*"needs" + 0.006*"quality" + 0.006*"Senior" + 0.005*"good" + 0.005*"effective" + 0.005*"ensure" + 0.005*"need" -2024-07-15 10:45:03,824 - topic #1 (0.333): 0.012*"’" + 0.007*"needs" + 0.007*"well" + 0.006*"improved" + 0.005*"good" + 0.005*"plans" + 0.005*"health" + 0.005*"Senior" + 0.005*"need" + 0.005*"Croydon" -2024-07-15 10:45:03,824 - topic #2 (0.333): 0.010*"’" + 0.007*"needs" + 0.006*"well" + 0.006*"need" + 0.006*"ensure" + 0.005*"quality" + 0.005*"Senior" + 0.004*"improved" + 0.004*"experiences" + 0.004*"health" -2024-07-15 10:45:03,824 - topic diff=0.771058, rho=1.000000 -2024-07-15 10:45:03,824 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:03.824832', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:04,895 - Inspection date 2020-02-03 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:04,896 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:04,896 - Inspection date 2020-02-03 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:04,896 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:04,896 - Inspection date 2020-02-03 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:04,896 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:04,896 - Inspection date 2020-02-03 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:04,897 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:04,897 - Inspection date 2020-02-03 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:04,897 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:04,897 - Inspection date 2020-02-03 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:04,897 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:06,550 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:06,559 - built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2365 corpus positions) -2024-07-15 10:45:06,560 - Dictionary lifecycle event {'msg': "built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2365 corpus positions)", 'datetime': '2024-07-15T10:45:06.560634', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:06,562 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:06,562 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:06,563 - using serial LDA version on this node -2024-07-15 10:45:06,563 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:06,564 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:06,568 - -8.054 per-word bound, 265.7 perplexity estimate based on a held-out corpus of 1 documents with 2365 words -2024-07-15 10:45:06,568 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:06,570 - topic #0 (0.333): 0.016*"’" + 0.007*"Ealing" + 0.006*"plans" + 0.006*"well" + 0.005*"needs" + 0.005*"progress" + 0.004*"need" + 0.004*"3" + 0.004*"London" + 0.004*"improve" -2024-07-15 10:45:06,570 - topic #1 (0.333): 0.015*"’" + 0.007*"Ealing" + 0.006*"needs" + 0.006*"progress" + 0.006*"plans" + 0.006*"well" + 0.005*"22" + 0.005*"effective" + 0.004*"London" + 0.004*"health" -2024-07-15 10:45:06,570 - topic #2 (0.333): 0.020*"’" + 0.010*"well" + 0.009*"Ealing" + 0.006*"progress" + 0.006*"needs" + 0.006*"need" + 0.006*"effective" + 0.005*"3" + 0.005*"including" + 0.005*"plans" -2024-07-15 10:45:06,570 - topic diff=0.791770, rho=1.000000 -2024-07-15 10:45:06,570 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:06.570741', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:07,613 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:07,614 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:07,614 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:07,614 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:07,614 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:07,614 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:07,615 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:07,615 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:07,615 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:07,615 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:07,615 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:07,615 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:09,159 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:09,161 - built Dictionary<999 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2104 corpus positions) -2024-07-15 10:45:09,161 - Dictionary lifecycle event {'msg': "built Dictionary<999 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2104 corpus positions)", 'datetime': '2024-07-15T10:45:09.161452', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:09,162 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:09,162 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:09,162 - using serial LDA version on this node -2024-07-15 10:45:09,163 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:09,163 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:09,166 - -7.939 per-word bound, 245.4 perplexity estimate based on a held-out corpus of 1 documents with 2104 words -2024-07-15 10:45:09,166 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:09,168 - topic #0 (0.333): 0.011*"’" + 0.009*"needs" + 0.008*"good" + 0.008*"ensure" + 0.007*"practice" + 0.007*"leaders" + 0.006*"range" + 0.006*"effective" + 0.006*"clear" + 0.006*"Enfield" -2024-07-15 10:45:09,168 - topic #1 (0.333): 0.016*"’" + 0.009*"needs" + 0.009*"practice" + 0.008*"ensure" + 0.007*"effective" + 0.007*"Enfield" + 0.007*"good" + 0.006*"clear" + 0.006*"timely" + 0.006*"improve" -2024-07-15 10:45:09,168 - topic #2 (0.333): 0.014*"’" + 0.007*"quality" + 0.006*"good" + 0.006*"needs" + 0.006*"effective" + 0.006*"clear" + 0.006*"ensure" + 0.006*"Enfield" + 0.006*"practice" + 0.005*"need" -2024-07-15 10:45:09,168 - topic diff=0.778021, rho=1.000000 -2024-07-15 10:45:09,168 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:09.168885', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:10,090 - Inspection date 2019-03-04 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:10,090 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:10,090 - Inspection date 2019-03-04 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:10,090 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:10,091 - Inspection date 2019-03-04 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:10,091 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:10,091 - Inspection date 2019-03-04 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:10,091 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:10,091 - Inspection date 2019-03-04 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:10,091 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:10,092 - Inspection date 2019-03-04 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:10,092 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:11,472 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:11,474 - built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1898 corpus positions) -2024-07-15 10:45:11,474 - Dictionary lifecycle event {'msg': "built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1898 corpus positions)", 'datetime': '2024-07-15T10:45:11.474473', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:11,475 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:11,475 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:11,475 - using serial LDA version on this node -2024-07-15 10:45:11,476 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:11,476 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:11,479 - -7.913 per-word bound, 240.9 perplexity estimate based on a held-out corpus of 1 documents with 1898 words -2024-07-15 10:45:11,479 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:11,480 - topic #0 (0.333): 0.013*"’" + 0.009*"well" + 0.009*"plans" + 0.009*"good" + 0.008*"need" + 0.007*"needs" + 0.006*"ensure" + 0.006*"range" + 0.006*"progress" + 0.005*"risk" -2024-07-15 10:45:11,481 - topic #1 (0.333): 0.010*"’" + 0.007*"needs" + 0.007*"well" + 0.007*"good" + 0.005*"plans" + 0.005*"range" + 0.004*"information" + 0.004*"progress" + 0.004*"ensure" + 0.004*"quality" -2024-07-15 10:45:11,481 - topic #2 (0.333): 0.012*"well" + 0.011*"’" + 0.009*"needs" + 0.007*"good" + 0.007*"plans" + 0.006*"range" + 0.006*"need" + 0.005*"quality" + 0.005*"progress" + 0.004*"risk" -2024-07-15 10:45:11,481 - topic diff=0.766231, rho=1.000000 -2024-07-15 10:45:11,481 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:11.481592', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:12,696 - Inspection date 2019-12-09 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:12,696 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:12,696 - Inspection date 2019-12-09 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:12,696 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:12,696 - Inspection date 2019-12-09 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:12,696 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:12,697 - Inspection date 2019-12-09 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:12,697 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:12,697 - Inspection date 2019-12-09 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:12,697 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:12,697 - Inspection date 2019-12-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:12,697 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:14,334 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:14,336 - built Dictionary<1122 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2603 corpus positions) -2024-07-15 10:45:14,336 - Dictionary lifecycle event {'msg': "built Dictionary<1122 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2603 corpus positions)", 'datetime': '2024-07-15T10:45:14.336794', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:14,337 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:14,338 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:14,338 - using serial LDA version on this node -2024-07-15 10:45:14,338 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:14,338 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:14,342 - -8.001 per-word bound, 256.1 perplexity estimate based on a held-out corpus of 1 documents with 2603 words -2024-07-15 10:45:14,342 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:14,344 - topic #0 (0.333): 0.012*"’" + 0.009*"practice" + 0.007*"number" + 0.007*"needs" + 0.006*"planning" + 0.006*"effective" + 0.006*"plans" + 0.005*"making" + 0.005*"leaders" + 0.005*"within" -2024-07-15 10:45:14,344 - topic #1 (0.333): 0.014*"’" + 0.012*"practice" + 0.006*"number" + 0.006*"planning" + 0.006*"including" + 0.006*"needs" + 0.005*"quality" + 0.005*"However" + 0.005*"within" + 0.005*"effective" -2024-07-15 10:45:14,344 - topic #2 (0.333): 0.014*"’" + 0.008*"practice" + 0.006*"need" + 0.006*"plans" + 0.006*"planning" + 0.005*"within" + 0.005*"effective" + 0.005*"protection" + 0.005*"oversight" + 0.005*"number" -2024-07-15 10:45:14,344 - topic diff=0.837222, rho=1.000000 -2024-07-15 10:45:14,344 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:14.344784', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:15,532 - Inspection date 2019-11-11 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:15,532 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:15,532 - Inspection date 2019-11-11 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:15,532 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:15,532 - Inspection date 2019-11-11 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:15,533 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:15,533 - Inspection date 2019-11-11 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:15,533 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:15,533 - Inspection date 2019-11-11 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:15,533 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:15,534 - Inspection date 2019-11-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:15,534 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:17,337 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:17,340 - built Dictionary<1330 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions) -2024-07-15 10:45:17,340 - Dictionary lifecycle event {'msg': "built Dictionary<1330 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)", 'datetime': '2024-07-15T10:45:17.340441', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:17,341 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:17,341 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:17,342 - using serial LDA version on this node -2024-07-15 10:45:17,342 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:17,342 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:17,347 - -8.202 per-word bound, 294.5 perplexity estimate based on a held-out corpus of 1 documents with 2905 words -2024-07-15 10:45:17,347 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:17,348 - topic #0 (0.333): 0.015*"’" + 0.008*"well" + 0.007*"receive" + 0.005*"needs" + 0.005*"plans" + 0.004*"effective" + 0.004*"Fulham" + 0.004*"11" + 0.004*"Hammersmith" + 0.004*"leaders" -2024-07-15 10:45:17,348 - topic #1 (0.333): 0.016*"’" + 0.008*"well" + 0.006*"needs" + 0.005*"receive" + 0.005*"Hammersmith" + 0.004*"Fulham" + 0.004*"Leaders" + 0.004*"supported" + 0.004*"11" + 0.004*"leaders" -2024-07-15 10:45:17,349 - topic #2 (0.333): 0.014*"’" + 0.006*"well" + 0.005*"2024" + 0.005*"needs" + 0.004*"effective" + 0.004*"receive" + 0.004*"Fulham" + 0.004*"supported" + 0.004*"plans" + 0.004*"Hammersmith" -2024-07-15 10:45:17,349 - topic diff=0.797315, rho=1.000000 -2024-07-15 10:45:17,349 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:17.349442', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:18,272 - Inspection date 2024-03-11 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:18,273 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:18,273 - Inspection date 2024-03-11 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:18,273 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:18,273 - Inspection date 2024-03-11 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:18,274 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:18,274 - Inspection date 2024-03-11 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:18,274 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:18,274 - Inspection date 2024-03-11 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:18,274 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:18,275 - Inspection date 2024-03-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:18,275 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:20,120 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:20,123 - built Dictionary<1252 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2620 corpus positions) -2024-07-15 10:45:20,123 - Dictionary lifecycle event {'msg': "built Dictionary<1252 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2620 corpus positions)", 'datetime': '2024-07-15T10:45:20.123428', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:20,124 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:20,124 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:20,125 - using serial LDA version on this node -2024-07-15 10:45:20,125 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:20,125 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:20,129 - -8.168 per-word bound, 287.6 perplexity estimate based on a held-out corpus of 1 documents with 2620 words -2024-07-15 10:45:20,129 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:20,131 - topic #0 (0.333): 0.021*"’" + 0.011*"needs" + 0.010*"Haringey" + 0.006*"well" + 0.006*"plans" + 0.006*"good" + 0.005*"progress" + 0.005*"need" + 0.005*"risk" + 0.005*"24" -2024-07-15 10:45:20,131 - topic #1 (0.333): 0.011*"’" + 0.008*"plans" + 0.007*"Haringey" + 0.006*"need" + 0.005*"needs" + 0.005*"good" + 0.005*"well" + 0.004*"progress" + 0.004*"training" + 0.004*"impact" -2024-07-15 10:45:20,131 - topic #2 (0.333): 0.012*"’" + 0.007*"plans" + 0.006*"well" + 0.006*"Haringey" + 0.005*"needs" + 0.004*"progress" + 0.004*"education" + 0.004*"need" + 0.004*"good" + 0.004*"carers" -2024-07-15 10:45:20,131 - topic diff=0.783756, rho=1.000000 -2024-07-15 10:45:20,132 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:20.132044', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:21,095 - Inspection date 2023-02-13 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:21,095 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:21,095 - Inspection date 2023-02-13 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:21,096 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:21,096 - Inspection date 2023-02-13 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:21,096 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:21,096 - Inspection date 2023-02-13 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:21,096 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:21,096 - Inspection date 2023-02-13 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:21,096 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:21,097 - Inspection date 2023-02-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:21,097 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:22,380 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:22,383 - built Dictionary<942 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1732 corpus positions) -2024-07-15 10:45:22,383 - Dictionary lifecycle event {'msg': "built Dictionary<942 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1732 corpus positions)", 'datetime': '2024-07-15T10:45:22.383689', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:22,385 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:22,385 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:22,385 - using serial LDA version on this node -2024-07-15 10:45:22,386 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:22,386 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:22,392 - -7.970 per-word bound, 250.8 perplexity estimate based on a held-out corpus of 1 documents with 1732 words -2024-07-15 10:45:22,392 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:22,394 - topic #0 (0.333): 0.013*"’" + 0.009*"good" + 0.008*"well" + 0.007*"needs" + 0.005*"impact" + 0.005*"experiences" + 0.005*"protection" + 0.005*"school" + 0.004*"early" + 0.004*"plans" -2024-07-15 10:45:22,395 - topic #1 (0.333): 0.013*"good" + 0.011*"’" + 0.009*"well" + 0.008*"needs" + 0.006*"plans" + 0.006*"practice" + 0.005*"need" + 0.005*"impact" + 0.005*"experiences" + 0.004*"protection" -2024-07-15 10:45:22,395 - topic #2 (0.333): 0.011*"’" + 0.009*"needs" + 0.009*"good" + 0.008*"well" + 0.006*"impact" + 0.006*"need" + 0.005*"protection" + 0.005*"early" + 0.005*"plans" + 0.005*"practice" -2024-07-15 10:45:22,395 - topic diff=0.687537, rho=1.000000 -2024-07-15 10:45:22,395 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:22.395755', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:24,203 - Inspection date 2020-02-10 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:24,203 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:24,204 - Inspection date 2020-02-10 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:24,204 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:24,204 - Inspection date 2020-02-10 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:24,204 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:24,204 - Inspection date 2020-02-10 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:24,204 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:24,205 - Inspection date 2020-02-10 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:24,205 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:24,205 - Inspection date 2020-02-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:24,205 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:25,717 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:25,719 - built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2243 corpus positions) -2024-07-15 10:45:25,719 - Dictionary lifecycle event {'msg': "built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2243 corpus positions)", 'datetime': '2024-07-15T10:45:25.719805', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:25,720 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:25,720 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:25,721 - using serial LDA version on this node -2024-07-15 10:45:25,721 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:25,721 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:25,725 - -8.010 per-word bound, 257.7 perplexity estimate based on a held-out corpus of 1 documents with 2243 words -2024-07-15 10:45:25,725 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:25,726 - topic #0 (0.333): 0.017*"’" + 0.012*"Havering" + 0.008*"quality" + 0.005*"plans" + 0.005*"needs" + 0.005*"oversight" + 0.004*"11" + 0.004*"22" + 0.004*"well" + 0.004*"experiences" -2024-07-15 10:45:25,726 - topic #1 (0.333): 0.010*"’" + 0.006*"plans" + 0.005*"Havering" + 0.004*"quality" + 0.004*"oversight" + 0.003*"22" + 0.003*"effective" + 0.003*"December" + 0.003*"practice" + 0.003*"needs" -2024-07-15 10:45:25,727 - topic #2 (0.333): 0.021*"’" + 0.013*"Havering" + 0.011*"quality" + 0.009*"plans" + 0.007*"effective" + 0.006*"oversight" + 0.005*"11" + 0.005*"needs" + 0.005*"practice" + 0.004*"many" -2024-07-15 10:45:25,727 - topic diff=0.794945, rho=1.000000 -2024-07-15 10:45:25,727 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:25.727363', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:26,694 - Inspection date 2023-12-11 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:26,694 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:26,695 - Inspection date 2023-12-11 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:26,695 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:26,695 - Inspection date 2023-12-11 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:26,695 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:26,695 - Inspection date 2023-12-11 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:26,695 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:26,695 - Inspection date 2023-12-11 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:26,696 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:26,696 - Inspection date 2023-12-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:26,696 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:28,426 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:28,429 - built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2511 corpus positions) -2024-07-15 10:45:28,429 - Dictionary lifecycle event {'msg': "built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2511 corpus positions)", 'datetime': '2024-07-15T10:45:28.429392', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:28,430 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:28,430 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:28,430 - using serial LDA version on this node -2024-07-15 10:45:28,431 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:28,431 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:28,435 - -8.079 per-word bound, 270.5 perplexity estimate based on a held-out corpus of 1 documents with 2511 words -2024-07-15 10:45:28,435 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:28,436 - topic #0 (0.333): 0.014*"’" + 0.009*"needs" + 0.008*"plans" + 0.007*"Hillingdon" + 0.007*"well" + 0.005*"need" + 0.004*"2" + 0.004*"leaders" + 0.003*"supported" + 0.003*"October" -2024-07-15 10:45:28,436 - topic #1 (0.333): 0.020*"’" + 0.009*"needs" + 0.008*"well" + 0.008*"plans" + 0.006*"Hillingdon" + 0.006*"team" + 0.005*"6" + 0.004*"2" + 0.004*"need" + 0.004*"leaders" -2024-07-15 10:45:28,437 - topic #2 (0.333): 0.018*"’" + 0.009*"Hillingdon" + 0.009*"needs" + 0.007*"plans" + 0.007*"well" + 0.005*"family" + 0.004*"team" + 0.004*"6" + 0.004*"2" + 0.004*"2023" -2024-07-15 10:45:28,437 - topic diff=0.796563, rho=1.000000 -2024-07-15 10:45:28,437 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:28.437285', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:29,509 - Inspection date 2023-10-02 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:29,509 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:29,510 - Inspection date 2023-10-02 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:29,510 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:29,510 - Inspection date 2023-10-02 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:29,510 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:29,511 - Inspection date 2023-10-02 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:29,511 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:29,511 - Inspection date 2023-10-02 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:29,511 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:29,512 - Inspection date 2023-10-02 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:29,512 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:31,066 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:31,068 - built Dictionary<1070 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2271 corpus positions) -2024-07-15 10:45:31,068 - Dictionary lifecycle event {'msg': "built Dictionary<1070 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2271 corpus positions)", 'datetime': '2024-07-15T10:45:31.068901', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:31,069 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:31,070 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:31,070 - using serial LDA version on this node -2024-07-15 10:45:31,070 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:31,070 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:31,074 - -8.007 per-word bound, 257.2 perplexity estimate based on a held-out corpus of 1 documents with 2271 words -2024-07-15 10:45:31,074 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:31,076 - topic #0 (0.333): 0.024*"’" + 0.011*"needs" + 0.010*"well" + 0.008*"effective" + 0.007*"Hounslow" + 0.006*"timely" + 0.006*"plans" + 0.005*"training" + 0.005*"16" + 0.005*"progress" -2024-07-15 10:45:31,076 - topic #1 (0.333): 0.018*"’" + 0.010*"needs" + 0.009*"well" + 0.006*"Hounslow" + 0.006*"timely" + 0.005*"effective" + 0.005*"oversight" + 0.004*"experiences" + 0.004*"strong" + 0.004*"16" -2024-07-15 10:45:31,076 - topic #2 (0.333): 0.017*"’" + 0.012*"needs" + 0.010*"well" + 0.007*"effective" + 0.007*"Hounslow" + 0.007*"plans" + 0.006*"timely" + 0.005*"strong" + 0.004*"experiences" + 0.004*"progress" -2024-07-15 10:45:31,076 - topic diff=0.783850, rho=1.000000 -2024-07-15 10:45:31,076 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:31.076727', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:32,069 - Inspection date 2023-10-16 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:32,069 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:32,069 - Inspection date 2023-10-16 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:32,070 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:32,070 - Inspection date 2023-10-16 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:32,070 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:32,070 - Inspection date 2023-10-16 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:32,070 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:32,071 - Inspection date 2023-10-16 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:32,071 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:32,071 - Inspection date 2023-10-16 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:32,071 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:33,292 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:33,294 - built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1982 corpus positions) -2024-07-15 10:45:33,294 - Dictionary lifecycle event {'msg': "built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1982 corpus positions)", 'datetime': '2024-07-15T10:45:33.294885', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:33,295 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:33,296 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:33,296 - using serial LDA version on this node -2024-07-15 10:45:33,296 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:33,296 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:33,300 - -7.925 per-word bound, 243.1 perplexity estimate based on a held-out corpus of 1 documents with 1982 words -2024-07-15 10:45:33,300 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:33,301 - topic #0 (0.333): 0.010*"’" + 0.009*"needs" + 0.009*"well" + 0.006*"good" + 0.006*"quality" + 0.006*"plans" + 0.005*"effective" + 0.004*"risk" + 0.004*"highly" + 0.004*"Islington" -2024-07-15 10:45:33,301 - topic #1 (0.333): 0.012*"’" + 0.011*"needs" + 0.008*"well" + 0.007*"highly" + 0.007*"plans" + 0.005*"effective" + 0.005*"quality" + 0.005*"good" + 0.004*"practice" + 0.004*"early" -2024-07-15 10:45:33,301 - topic #2 (0.333): 0.014*"’" + 0.012*"well" + 0.012*"needs" + 0.007*"leaders" + 0.007*"plans" + 0.006*"good" + 0.006*"highly" + 0.006*"Islington" + 0.006*"risk" + 0.005*"quality" -2024-07-15 10:45:33,301 - topic diff=0.748627, rho=1.000000 -2024-07-15 10:45:33,302 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:33.302074', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:35,134 - Inspection date 2020-03-09 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:35,134 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:35,134 - Inspection date 2020-03-09 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:35,134 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:35,135 - Inspection date 2020-03-09 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:35,135 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:35,135 - Inspection date 2020-03-09 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:35,135 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:35,135 - Inspection date 2020-03-09 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:35,135 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:35,136 - Inspection date 2020-03-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:35,136 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:36,459 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:36,461 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2090 corpus positions) -2024-07-15 10:45:36,462 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2090 corpus positions)", 'datetime': '2024-07-15T10:45:36.462017', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:36,462 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:36,463 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:36,463 - using serial LDA version on this node -2024-07-15 10:45:36,463 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:36,463 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:36,467 - -7.913 per-word bound, 241.0 perplexity estimate based on a held-out corpus of 1 documents with 2090 words -2024-07-15 10:45:36,467 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:36,468 - topic #0 (0.333): 0.013*"’" + 0.008*"good" + 0.008*"needs" + 0.008*"well" + 0.007*"plans" + 0.006*"progress" + 0.006*"leaders" + 0.005*"4" + 0.005*"Lambeth" + 0.005*"Leaders" -2024-07-15 10:45:36,468 - topic #1 (0.333): 0.016*"’" + 0.009*"needs" + 0.008*"well" + 0.007*"Lambeth" + 0.007*"need" + 0.006*"good" + 0.006*"plans" + 0.006*"impact" + 0.005*"progress" + 0.005*"4" -2024-07-15 10:45:36,469 - topic #2 (0.333): 0.016*"’" + 0.009*"needs" + 0.009*"well" + 0.008*"plans" + 0.006*"Lambeth" + 0.006*"need" + 0.005*"progress" + 0.005*"good" + 0.005*"number" + 0.005*"impact" -2024-07-15 10:45:36,469 - topic diff=0.800881, rho=1.000000 -2024-07-15 10:45:36,469 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:36.469393', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:37,628 - Inspection date 2022-10-24 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:37,628 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:37,628 - Inspection date 2022-10-24 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:37,628 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:37,629 - Inspection date 2022-10-24 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:37,629 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:37,629 - Inspection date 2022-10-24 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:37,629 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:37,629 - Inspection date 2022-10-24 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:37,629 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:37,629 - Inspection date 2022-10-24 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:37,629 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:38,842 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:38,844 - built Dictionary<1115 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2352 corpus positions) -2024-07-15 10:45:38,844 - Dictionary lifecycle event {'msg': "built Dictionary<1115 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2352 corpus positions)", 'datetime': '2024-07-15T10:45:38.844600', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:38,845 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:38,845 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:38,846 - using serial LDA version on this node -2024-07-15 10:45:38,846 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:38,846 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:38,850 - -8.049 per-word bound, 264.8 perplexity estimate based on a held-out corpus of 1 documents with 2352 words -2024-07-15 10:45:38,850 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:38,851 - topic #0 (0.333): 0.016*"’" + 0.008*"well" + 0.006*"effective" + 0.005*"needs" + 0.005*"plans" + 0.005*"4" + 0.005*"good" + 0.004*"progress" + 0.004*"15" + 0.004*"Lewisham" -2024-07-15 10:45:38,851 - topic #1 (0.333): 0.019*"’" + 0.009*"needs" + 0.009*"plans" + 0.008*"well" + 0.006*"Lewisham" + 0.006*"effective" + 0.005*"progress" + 0.005*"leaders" + 0.005*"4" + 0.005*"arrangements" -2024-07-15 10:45:38,852 - topic #2 (0.333): 0.016*"’" + 0.007*"well" + 0.007*"Lewisham" + 0.006*"effective" + 0.006*"needs" + 0.005*"plans" + 0.005*"good" + 0.005*"progress" + 0.004*"need" + 0.004*"2023" -2024-07-15 10:45:38,852 - topic diff=0.774604, rho=1.000000 -2024-07-15 10:45:38,852 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:38.852221', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:40,045 - Inspection date 2023-12-04 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:40,046 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:40,046 - Inspection date 2023-12-04 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:40,046 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:40,046 - Inspection date 2023-12-04 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:40,047 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:40,047 - Inspection date 2023-12-04 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:40,047 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:40,047 - Inspection date 2023-12-04 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:40,047 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:40,047 - Inspection date 2023-12-04 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:40,048 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:41,401 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:41,403 - built Dictionary<1015 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2032 corpus positions) -2024-07-15 10:45:41,403 - Dictionary lifecycle event {'msg': "built Dictionary<1015 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2032 corpus positions)", 'datetime': '2024-07-15T10:45:41.403821', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:41,404 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:41,404 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:41,405 - using serial LDA version on this node -2024-07-15 10:45:41,405 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:41,405 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:41,409 - -7.986 per-word bound, 253.5 perplexity estimate based on a held-out corpus of 1 documents with 2032 words -2024-07-15 10:45:41,409 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:41,411 - topic #0 (0.333): 0.011*"’" + 0.008*"well" + 0.007*"Merton" + 0.006*"needs" + 0.005*"family" + 0.004*"leaders" + 0.004*"progress" + 0.004*"risk" + 0.004*"March" + 0.004*"2022" -2024-07-15 10:45:41,411 - topic #1 (0.333): 0.012*"’" + 0.008*"well" + 0.006*"needs" + 0.005*"plans" + 0.005*"Merton" + 0.005*"progress" + 0.004*"ensure" + 0.004*"4" + 0.004*"good" + 0.004*"family" -2024-07-15 10:45:41,411 - topic #2 (0.333): 0.021*"’" + 0.007*"well" + 0.007*"Merton" + 0.005*"needs" + 0.005*"plans" + 0.005*"education" + 0.005*"good" + 0.004*"access" + 0.004*"helping" + 0.004*"4" -2024-07-15 10:45:41,411 - topic diff=0.752959, rho=1.000000 -2024-07-15 10:45:41,411 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:41.411733', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:42,357 - Inspection date 2022-02-28 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:42,357 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:42,358 - Inspection date 2022-02-28 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:42,358 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:42,358 - Inspection date 2022-02-28 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:42,358 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:42,358 - Inspection date 2022-02-28 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:42,359 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:42,359 - Inspection date 2022-02-28 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:42,359 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:42,359 - Inspection date 2022-02-28 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:42,359 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:43,974 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:43,977 - built Dictionary<1153 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2540 corpus positions) -2024-07-15 10:45:43,977 - Dictionary lifecycle event {'msg': "built Dictionary<1153 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2540 corpus positions)", 'datetime': '2024-07-15T10:45:43.977495', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:43,978 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:43,978 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:43,978 - using serial LDA version on this node -2024-07-15 10:45:43,979 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:43,979 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:43,983 - -8.055 per-word bound, 265.9 perplexity estimate based on a held-out corpus of 1 documents with 2540 words -2024-07-15 10:45:43,983 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:43,984 - topic #0 (0.333): 0.022*"’" + 0.008*"needs" + 0.008*"Newham" + 0.007*"progress" + 0.007*"practice" + 0.007*"effective" + 0.006*"plans" + 0.006*"need" + 0.005*"18" + 0.005*"good" -2024-07-15 10:45:43,984 - topic #1 (0.333): 0.017*"’" + 0.008*"needs" + 0.006*"Newham" + 0.006*"practice" + 0.005*"need" + 0.005*"plans" + 0.005*"progress" + 0.005*"effective" + 0.004*"good" + 0.004*"Leaders" -2024-07-15 10:45:43,985 - topic #2 (0.333): 0.017*"’" + 0.007*"needs" + 0.006*"Newham" + 0.006*"plans" + 0.006*"need" + 0.006*"good" + 0.005*"effective" + 0.005*"progress" + 0.005*"practice" + 0.005*"Leaders" -2024-07-15 10:45:43,985 - topic diff=0.777674, rho=1.000000 -2024-07-15 10:45:43,985 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:43.985315', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:44,986 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:44,986 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:44,987 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:44,987 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:44,987 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:44,987 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:44,987 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:44,988 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:44,988 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:44,988 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:44,988 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:44,988 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:46,636 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:46,638 - built Dictionary<1149 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2458 corpus positions) -2024-07-15 10:45:46,639 - Dictionary lifecycle event {'msg': "built Dictionary<1149 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2458 corpus positions)", 'datetime': '2024-07-15T10:45:46.639021', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:46,640 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:46,640 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:46,640 - using serial LDA version on this node -2024-07-15 10:45:46,641 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:46,641 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:46,644 - -8.072 per-word bound, 269.1 perplexity estimate based on a held-out corpus of 1 documents with 2458 words -2024-07-15 10:45:46,645 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:46,646 - topic #0 (0.333): 0.010*"’" + 0.007*"well" + 0.007*"practice" + 0.007*"needs" + 0.007*"need" + 0.006*"strong" + 0.005*"team" + 0.005*"risk" + 0.005*"Redbridge" + 0.005*"effective" -2024-07-15 10:45:46,646 - topic #1 (0.333): 0.007*"practice" + 0.006*"’" + 0.005*"including" + 0.005*"Redbridge" + 0.005*"well" + 0.004*"strong" + 0.004*"need" + 0.004*"needs" + 0.004*"effective" + 0.004*"risk" -2024-07-15 10:45:46,646 - topic #2 (0.333): 0.006*"needs" + 0.006*"effective" + 0.006*"practice" + 0.005*"progress" + 0.005*"well" + 0.005*"need" + 0.005*"’" + 0.005*"risk" + 0.005*"Redbridge" + 0.005*"including" -2024-07-15 10:45:46,646 - topic diff=0.775892, rho=1.000000 -2024-07-15 10:45:46,647 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:46.647066', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:47,798 - Inspection date 2019-04-29 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:47,799 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:47,799 - Inspection date 2019-04-29 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:47,799 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:47,799 - Inspection date 2019-04-29 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:47,799 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:47,800 - Inspection date 2019-04-29 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:47,800 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:47,800 - Inspection date 2019-04-29 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:47,800 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:47,800 - Inspection date 2019-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:47,800 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:48,911 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:48,913 - built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1818 corpus positions) -2024-07-15 10:45:48,913 - Dictionary lifecycle event {'msg': "built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1818 corpus positions)", 'datetime': '2024-07-15T10:45:48.913817', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:48,914 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:48,914 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:48,915 - using serial LDA version on this node -2024-07-15 10:45:48,915 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:48,915 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:48,918 - -7.982 per-word bound, 252.9 perplexity estimate based on a held-out corpus of 1 documents with 1818 words -2024-07-15 10:45:48,919 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:48,920 - topic #0 (0.333): 0.017*"’" + 0.013*"well" + 0.008*"Richmond" + 0.008*"needs" + 0.007*"good" + 0.006*"supported" + 0.006*"need" + 0.006*"additional" + 0.005*"4" + 0.005*"ensure" -2024-07-15 10:45:48,920 - topic #1 (0.333): 0.016*"’" + 0.011*"well" + 0.008*"Richmond" + 0.007*"team" + 0.007*"needs" + 0.007*"supported" + 0.005*"good" + 0.005*"upon" + 0.005*"need" + 0.005*"Thames" -2024-07-15 10:45:48,920 - topic #2 (0.333): 0.013*"’" + 0.008*"well" + 0.006*"Richmond" + 0.006*"needs" + 0.006*"need" + 0.004*"supported" + 0.004*"strong" + 0.004*"ensure" + 0.004*"team" + 0.004*"January" -2024-07-15 10:45:48,920 - topic diff=0.733415, rho=1.000000 -2024-07-15 10:45:48,921 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:48.921003', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:49,792 - Inspection date 2022-01-31 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:49,793 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:49,793 - Inspection date 2022-01-31 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:49,793 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:49,793 - Inspection date 2022-01-31 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:49,793 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:49,794 - Inspection date 2022-01-31 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:49,794 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:49,794 - Inspection date 2022-01-31 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:49,794 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:49,794 - Inspection date 2022-01-31 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:49,794 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:51,040 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:51,042 - built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions) -2024-07-15 10:45:51,042 - Dictionary lifecycle event {'msg': "built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions)", 'datetime': '2024-07-15T10:45:51.042292', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:51,043 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:51,043 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:51,043 - using serial LDA version on this node -2024-07-15 10:45:51,043 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:51,044 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:51,047 - -7.921 per-word bound, 242.4 perplexity estimate based on a held-out corpus of 1 documents with 1878 words -2024-07-15 10:45:51,047 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:51,048 - topic #0 (0.333): 0.011*"’" + 0.008*"Southwark" + 0.008*"good" + 0.006*"well" + 0.006*"needs" + 0.005*"progress" + 0.005*"Leaders" + 0.005*"strong" + 0.005*"quality" + 0.004*"plans" -2024-07-15 10:45:51,048 - topic #1 (0.333): 0.024*"’" + 0.010*"well" + 0.008*"Southwark" + 0.008*"good" + 0.007*"needs" + 0.006*"effective" + 0.006*"progress" + 0.005*"need" + 0.005*"Leaders" + 0.005*"plans" -2024-07-15 10:45:51,049 - topic #2 (0.333): 0.017*"’" + 0.011*"Southwark" + 0.008*"needs" + 0.008*"good" + 0.006*"need" + 0.006*"plans" + 0.006*"leaders" + 0.006*"progress" + 0.006*"well" + 0.005*"effective" -2024-07-15 10:45:51,049 - topic diff=0.741624, rho=1.000000 -2024-07-15 10:45:51,049 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:51.049411', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:52,153 - Inspection date 2022-09-26 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:52,154 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:52,154 - Inspection date 2022-09-26 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:52,154 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:52,155 - Inspection date 2022-09-26 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:52,155 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:52,155 - Inspection date 2022-09-26 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:52,155 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:52,156 - Inspection date 2022-09-26 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:52,156 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:52,156 - Inspection date 2022-09-26 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:52,156 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:53,446 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:53,448 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1847 corpus positions) -2024-07-15 10:45:53,448 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1847 corpus positions)", 'datetime': '2024-07-15T10:45:53.448231', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:53,449 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:53,449 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:53,449 - using serial LDA version on this node -2024-07-15 10:45:53,449 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:53,450 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:53,453 - -7.982 per-word bound, 252.7 perplexity estimate based on a held-out corpus of 1 documents with 1847 words -2024-07-15 10:45:53,453 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:53,454 - topic #0 (0.333): 0.013*"’" + 0.006*"needs" + 0.006*"well" + 0.005*"Sutton" + 0.004*"progress" + 0.004*"effective" + 0.004*"receive" + 0.004*"good" + 0.004*"leaders" + 0.004*"positive" -2024-07-15 10:45:53,454 - topic #1 (0.333): 0.020*"’" + 0.007*"well" + 0.007*"Sutton" + 0.006*"progress" + 0.006*"needs" + 0.005*"receive" + 0.005*"6" + 0.005*"good" + 0.005*"effective" + 0.005*"leaders" -2024-07-15 10:45:53,455 - topic #2 (0.333): 0.015*"’" + 0.007*"well" + 0.006*"needs" + 0.005*"Sutton" + 0.005*"good" + 0.005*"effective" + 0.004*"receive" + 0.004*"progress" + 0.004*"‘" + 0.004*"10" -2024-07-15 10:45:53,455 - topic diff=0.746989, rho=1.000000 -2024-07-15 10:45:53,455 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:53.455378', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:55,141 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:55,142 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:55,142 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:55,142 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:55,142 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:55,142 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:55,142 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:55,143 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:55,143 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:55,143 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:55,143 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:55,143 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:56,851 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:56,854 - built Dictionary<1194 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions) -2024-07-15 10:45:56,854 - Dictionary lifecycle event {'msg': "built Dictionary<1194 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions)", 'datetime': '2024-07-15T10:45:56.854762', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:56,855 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:56,856 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:56,856 - using serial LDA version on this node -2024-07-15 10:45:56,856 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:56,856 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:56,860 - -8.130 per-word bound, 280.2 perplexity estimate based on a held-out corpus of 1 documents with 2465 words -2024-07-15 10:45:56,860 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:56,862 - topic #0 (0.333): 0.014*"’" + 0.007*"effective" + 0.007*"good" + 0.006*"well" + 0.006*"practice" + 0.005*"plans" + 0.005*"need" + 0.005*"carers" + 0.005*"including" + 0.005*"‘" -2024-07-15 10:45:56,862 - topic #1 (0.333): 0.014*"’" + 0.006*"plans" + 0.005*"practice" + 0.005*"effective" + 0.005*"well" + 0.004*"progress" + 0.004*"good" + 0.004*"‘" + 0.004*"risk" + 0.004*"including" -2024-07-15 10:45:56,862 - topic #2 (0.333): 0.016*"’" + 0.008*"good" + 0.007*"plans" + 0.007*"‘" + 0.006*"effective" + 0.005*"need" + 0.005*"early" + 0.005*"well" + 0.005*"progress" + 0.004*"needs" -2024-07-15 10:45:56,862 - topic diff=0.770770, rho=1.000000 -2024-07-15 10:45:56,862 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:56.862691', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:58,238 - Inspection date 2019-06-10 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:45:58,238 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:58,238 - Inspection date 2019-06-10 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:45:58,239 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:58,239 - Inspection date 2019-06-10 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:45:58,239 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:58,239 - Inspection date 2019-06-10 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:45:58,239 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:58,239 - Inspection date 2019-06-10 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:45:58,240 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:58,240 - Inspection date 2019-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:45:58,240 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:45:59,483 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:45:59,486 - built Dictionary<1036 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions) -2024-07-15 10:45:59,486 - Dictionary lifecycle event {'msg': "built Dictionary<1036 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)", 'datetime': '2024-07-15T10:45:59.486190', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:45:59,487 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:45:59,487 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:45:59,487 - using serial LDA version on this node -2024-07-15 10:45:59,488 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:45:59,488 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:45:59,491 - -7.973 per-word bound, 251.3 perplexity estimate based on a held-out corpus of 1 documents with 2199 words -2024-07-15 10:45:59,491 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:45:59,493 - topic #0 (0.333): 0.014*"well" + 0.014*"’" + 0.009*"needs" + 0.008*"good" + 0.007*"effective" + 0.006*"need" + 0.005*"plans" + 0.005*"timely" + 0.005*"protection" + 0.005*"risk" -2024-07-15 10:45:59,493 - topic #1 (0.333): 0.012*"well" + 0.011*"’" + 0.009*"good" + 0.008*"needs" + 0.006*"effective" + 0.005*"need" + 0.005*"plans" + 0.005*"timely" + 0.004*"progress" + 0.004*"risk" -2024-07-15 10:45:59,493 - topic #2 (0.333): 0.018*"’" + 0.009*"needs" + 0.009*"well" + 0.007*"effective" + 0.007*"good" + 0.006*"need" + 0.005*"plans" + 0.005*"risk" + 0.005*"timely" + 0.004*"education" -2024-07-15 10:45:59,493 - topic diff=0.783248, rho=1.000000 -2024-07-15 10:45:59,493 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:45:59.493706', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:00,441 - Inspection date 2019-01-28 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:00,441 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:00,442 - Inspection date 2019-01-28 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:00,442 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:00,442 - Inspection date 2019-01-28 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:00,442 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:00,442 - Inspection date 2019-01-28 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:00,442 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:00,443 - Inspection date 2019-01-28 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:00,443 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:00,443 - Inspection date 2019-01-28 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:00,443 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:01,731 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:01,733 - built Dictionary<884 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1772 corpus positions) -2024-07-15 10:46:01,733 - Dictionary lifecycle event {'msg': "built Dictionary<884 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1772 corpus positions)", 'datetime': '2024-07-15T10:46:01.733732', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:01,734 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:01,734 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:01,734 - using serial LDA version on this node -2024-07-15 10:46:01,735 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:01,735 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:01,738 - -7.853 per-word bound, 231.2 perplexity estimate based on a held-out corpus of 1 documents with 1772 words -2024-07-15 10:46:01,738 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:01,739 - topic #0 (0.333): 0.011*"’" + 0.007*"well" + 0.006*"needs" + 0.006*"Wandsworth" + 0.005*"ensure" + 0.005*"Senior" + 0.005*"7" + 0.005*"protection" + 0.005*"progress" + 0.005*"good" -2024-07-15 10:46:01,740 - topic #1 (0.333): 0.010*"’" + 0.007*"well" + 0.006*"Senior" + 0.006*"protection" + 0.006*"needs" + 0.005*"practice" + 0.005*"supported" + 0.005*"team" + 0.005*"progress" + 0.004*"2022" -2024-07-15 10:46:01,740 - topic #2 (0.333): 0.014*"’" + 0.006*"progress" + 0.006*"well" + 0.005*"practice" + 0.005*"Wandsworth" + 0.005*"7" + 0.005*"team" + 0.005*"ensure" + 0.005*"effective" + 0.004*"quality" -2024-07-15 10:46:01,740 - topic diff=0.746228, rho=1.000000 -2024-07-15 10:46:01,740 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:01.740432', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:02,652 - Inspection date 2022-11-07 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:02,652 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:02,652 - Inspection date 2022-11-07 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:02,653 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:02,653 - Inspection date 2022-11-07 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:02,653 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:02,653 - Inspection date 2022-11-07 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:02,653 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:02,653 - Inspection date 2022-11-07 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:02,653 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:02,654 - Inspection date 2022-11-07 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:02,654 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:04,297 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:04,301 - built Dictionary<1136 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2101 corpus positions) -2024-07-15 10:46:04,301 - Dictionary lifecycle event {'msg': "built Dictionary<1136 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2101 corpus positions)", 'datetime': '2024-07-15T10:46:04.301385', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:04,303 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:04,303 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:04,303 - using serial LDA version on this node -2024-07-15 10:46:04,304 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:04,304 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:04,309 - -8.155 per-word bound, 285.0 perplexity estimate based on a held-out corpus of 1 documents with 2101 words -2024-07-15 10:46:04,309 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:04,310 - topic #0 (0.333): 0.011*"’" + 0.005*"practice" + 0.005*"highly" + 0.005*"well" + 0.005*"needs" + 0.004*"many" + 0.004*"plans" + 0.003*"high" + 0.003*"across" + 0.003*"direct" -2024-07-15 10:46:04,310 - topic #1 (0.333): 0.013*"’" + 0.007*"practice" + 0.006*"highly" + 0.005*"needs" + 0.005*"well" + 0.004*"across" + 0.004*"family" + 0.004*"many" + 0.003*"Westminster" + 0.003*"supported" -2024-07-15 10:46:04,310 - topic #2 (0.333): 0.014*"’" + 0.007*"needs" + 0.007*"practice" + 0.005*"well" + 0.005*"highly" + 0.004*"across" + 0.004*"shared" + 0.004*"many" + 0.003*"family" + 0.003*"high" -2024-07-15 10:46:04,311 - topic diff=0.692602, rho=1.000000 -2024-07-15 10:46:04,311 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:04.311145', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:05,475 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:05,475 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:05,476 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:05,476 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:05,476 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:05,476 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:05,476 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:05,476 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:05,476 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:05,477 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:05,477 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:05,477 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:07,177 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:07,179 - built Dictionary<1199 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2593 corpus positions) -2024-07-15 10:46:07,179 - Dictionary lifecycle event {'msg': "built Dictionary<1199 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2593 corpus positions)", 'datetime': '2024-07-15T10:46:07.179494', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:07,180 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:07,180 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:07,181 - using serial LDA version on this node -2024-07-15 10:46:07,181 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:07,181 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:07,185 - -8.104 per-word bound, 275.2 perplexity estimate based on a held-out corpus of 1 documents with 2593 words -2024-07-15 10:46:07,185 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:07,186 - topic #0 (0.333): 0.011*"’" + 0.007*"needs" + 0.006*"need" + 0.005*"Luton" + 0.005*"plans" + 0.005*"effective" + 0.005*"including" + 0.005*"good" + 0.004*"progress" + 0.004*"impact" -2024-07-15 10:46:07,187 - topic #1 (0.333): 0.018*"’" + 0.006*"need" + 0.005*"Luton" + 0.005*"plans" + 0.005*"effective" + 0.005*"quality" + 0.005*"needs" + 0.005*"progress" + 0.004*"good" + 0.004*"receive" -2024-07-15 10:46:07,187 - topic #2 (0.333): 0.020*"’" + 0.007*"plans" + 0.007*"needs" + 0.007*"need" + 0.006*"effective" + 0.006*"Luton" + 0.006*"good" + 0.005*"impact" + 0.005*"ensure" + 0.005*"quality" -2024-07-15 10:46:07,187 - topic diff=0.797225, rho=1.000000 -2024-07-15 10:46:07,187 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:07.187420', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:08,188 - Inspection date 2022-07-11 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:08,188 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:08,189 - Inspection date 2022-07-11 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:08,189 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:08,189 - Inspection date 2022-07-11 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:08,189 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:08,189 - Inspection date 2022-07-11 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:08,189 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:08,189 - Inspection date 2022-07-11 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:08,190 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:08,190 - Inspection date 2022-07-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:08,190 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:09,552 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:09,554 - built Dictionary<871 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1938 corpus positions) -2024-07-15 10:46:09,554 - Dictionary lifecycle event {'msg': "built Dictionary<871 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1938 corpus positions)", 'datetime': '2024-07-15T10:46:09.554518', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:09,555 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:09,555 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:09,555 - using serial LDA version on this node -2024-07-15 10:46:09,556 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:09,556 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:09,559 - -7.773 per-word bound, 218.7 perplexity estimate based on a held-out corpus of 1 documents with 1938 words -2024-07-15 10:46:09,559 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:09,560 - topic #0 (0.333): 0.019*"’" + 0.011*"Manchester" + 0.010*"needs" + 0.007*"well" + 0.007*"always" + 0.006*"supported" + 0.005*"education" + 0.005*"progress" + 0.005*"family" + 0.005*"21" -2024-07-15 10:46:09,560 - topic #1 (0.333): 0.024*"’" + 0.012*"Manchester" + 0.010*"needs" + 0.008*"well" + 0.007*"always" + 0.006*"protection" + 0.006*"supported" + 0.006*"education" + 0.006*"plans" + 0.005*"effective" -2024-07-15 10:46:09,560 - topic #2 (0.333): 0.018*"’" + 0.007*"Manchester" + 0.007*"supported" + 0.006*"needs" + 0.006*"plans" + 0.005*"well" + 0.005*"always" + 0.005*"21" + 0.004*"effective" + 0.004*"quality" -2024-07-15 10:46:09,561 - topic diff=0.815506, rho=1.000000 -2024-07-15 10:46:09,561 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.00s', 'datetime': '2024-07-15T10:46:09.561140', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:10,451 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:10,451 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:10,451 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:10,451 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:10,451 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:10,452 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:10,452 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:10,452 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:10,452 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:10,452 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:10,452 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:10,453 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:11,860 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:11,864 - built Dictionary<922 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1857 corpus positions) -2024-07-15 10:46:11,866 - Dictionary lifecycle event {'msg': "built Dictionary<922 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1857 corpus positions)", 'datetime': '2024-07-15T10:46:11.866591', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:11,868 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:11,868 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:11,868 - using serial LDA version on this node -2024-07-15 10:46:11,868 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:11,868 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:11,874 - -7.893 per-word bound, 237.8 perplexity estimate based on a held-out corpus of 1 documents with 1857 words -2024-07-15 10:46:11,874 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:11,876 - topic #0 (0.333): 0.014*"’" + 0.011*"Medway" + 0.008*"quality" + 0.008*"practice" + 0.007*"well" + 0.006*"needs" + 0.006*"oversight" + 0.005*"progress" + 0.005*"clear" + 0.005*"risk" -2024-07-15 10:46:11,877 - topic #1 (0.333): 0.018*"’" + 0.009*"Medway" + 0.009*"practice" + 0.009*"well" + 0.008*"quality" + 0.007*"leaders" + 0.007*"needs" + 0.007*"impact" + 0.006*"oversight" + 0.005*"clear" -2024-07-15 10:46:11,877 - topic #2 (0.333): 0.015*"’" + 0.007*"leaders" + 0.006*"quality" + 0.006*"well" + 0.006*"practice" + 0.006*"Medway" + 0.006*"17" + 0.006*"oversight" + 0.005*"experiences" + 0.005*"progress" -2024-07-15 10:46:11,877 - topic diff=0.766710, rho=1.000000 -2024-07-15 10:46:11,877 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:11.877569', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:12,937 - Inspection date 2023-07-17 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:12,937 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:12,938 - Inspection date 2023-07-17 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:12,938 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:12,938 - Inspection date 2023-07-17 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:12,938 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:12,938 - Inspection date 2023-07-17 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:12,938 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:12,938 - Inspection date 2023-07-17 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:12,939 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:12,939 - Inspection date 2023-07-17 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:12,939 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:14,826 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:14,828 - built Dictionary<1068 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2278 corpus positions) -2024-07-15 10:46:14,828 - Dictionary lifecycle event {'msg': "built Dictionary<1068 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2278 corpus positions)", 'datetime': '2024-07-15T10:46:14.828451', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:14,829 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:14,829 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:14,829 - using serial LDA version on this node -2024-07-15 10:46:14,830 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:14,830 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:14,833 - -8.003 per-word bound, 256.6 perplexity estimate based on a held-out corpus of 1 documents with 2278 words -2024-07-15 10:46:14,833 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:14,835 - topic #0 (0.333): 0.014*"’" + 0.008*"Middlesbrough" + 0.007*"needs" + 0.006*"plans" + 0.006*"effective" + 0.006*"practice" + 0.005*"progress" + 0.005*"well" + 0.005*"24" + 0.005*"risk" -2024-07-15 10:46:14,835 - topic #1 (0.333): 0.015*"’" + 0.008*"well" + 0.007*"effective" + 0.007*"plans" + 0.007*"Middlesbrough" + 0.006*"needs" + 0.006*"place" + 0.006*"progress" + 0.005*"13" + 0.005*"practice" -2024-07-15 10:46:14,835 - topic #2 (0.333): 0.010*"’" + 0.007*"plans" + 0.007*"effective" + 0.006*"well" + 0.005*"practice" + 0.005*"needs" + 0.005*"impact" + 0.004*"Middlesbrough" + 0.004*"progress" + 0.004*"24" -2024-07-15 10:46:14,835 - topic diff=0.783066, rho=1.000000 -2024-07-15 10:46:14,835 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:14.835831', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:15,704 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:15,705 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:15,705 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:15,705 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:15,705 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:15,705 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:15,706 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:15,706 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:15,706 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:15,706 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:15,706 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:15,706 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:17,134 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:17,136 - built Dictionary<1101 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2328 corpus positions) -2024-07-15 10:46:17,136 - Dictionary lifecycle event {'msg': "built Dictionary<1101 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2328 corpus positions)", 'datetime': '2024-07-15T10:46:17.136638', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:17,137 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:17,137 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:17,138 - using serial LDA version on this node -2024-07-15 10:46:17,138 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:17,138 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:17,142 - -8.042 per-word bound, 263.5 perplexity estimate based on a held-out corpus of 1 documents with 2328 words -2024-07-15 10:46:17,142 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:17,143 - topic #0 (0.333): 0.015*"’" + 0.006*"Keynes" + 0.005*"need" + 0.005*"practice" + 0.005*"Milton" + 0.005*"well" + 0.004*"plans" + 0.004*"impact" + 0.004*"25" + 0.004*"good" -2024-07-15 10:46:17,143 - topic #1 (0.333): 0.013*"’" + 0.005*"Keynes" + 0.005*"Milton" + 0.004*"well" + 0.004*"25" + 0.004*"practice" + 0.004*"need" + 0.004*"good" + 0.004*"leaders" + 0.004*"plans" -2024-07-15 10:46:17,144 - topic #2 (0.333): 0.016*"’" + 0.007*"Milton" + 0.006*"well" + 0.006*"need" + 0.006*"Keynes" + 0.005*"leaders" + 0.005*"2021" + 0.005*"good" + 0.005*"plans" + 0.005*"needs" -2024-07-15 10:46:17,144 - topic diff=0.794252, rho=1.000000 -2024-07-15 10:46:17,144 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:17.144236', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:18,182 - Inspection date 2021-10-25 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:18,182 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:18,182 - Inspection date 2021-10-25 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:18,182 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:18,182 - Inspection date 2021-10-25 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:18,182 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:18,183 - Inspection date 2021-10-25 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:18,183 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:18,183 - Inspection date 2021-10-25 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:18,183 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:18,183 - Inspection date 2021-10-25 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:18,183 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:19,675 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:19,677 - built Dictionary<956 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2076 corpus positions) -2024-07-15 10:46:19,677 - Dictionary lifecycle event {'msg': "built Dictionary<956 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2076 corpus positions)", 'datetime': '2024-07-15T10:46:19.677255', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:19,678 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:19,678 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:19,678 - using serial LDA version on this node -2024-07-15 10:46:19,679 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:19,679 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:19,682 - -7.880 per-word bound, 235.6 perplexity estimate based on a held-out corpus of 1 documents with 2076 words -2024-07-15 10:46:19,682 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:19,683 - topic #0 (0.333): 0.017*"’" + 0.009*"plans" + 0.008*"needs" + 0.008*"Newcastle" + 0.007*"well" + 0.007*"good" + 0.007*"protection" + 0.006*"progress" + 0.006*"2021" + 0.005*"ensure" -2024-07-15 10:46:19,684 - topic #1 (0.333): 0.016*"’" + 0.008*"plans" + 0.007*"needs" + 0.007*"Newcastle" + 0.007*"protection" + 0.006*"good" + 0.005*"need" + 0.005*"progress" + 0.005*"well" + 0.005*"response" -2024-07-15 10:46:19,684 - topic #2 (0.333): 0.014*"’" + 0.013*"plans" + 0.008*"needs" + 0.006*"good" + 0.006*"Newcastle" + 0.006*"protection" + 0.006*"planning" + 0.006*"well" + 0.006*"making" + 0.006*"ensure" -2024-07-15 10:46:19,684 - topic diff=0.786535, rho=1.000000 -2024-07-15 10:46:19,684 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:19.684467', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:20,641 - Inspection date 2021-11-29 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:20,641 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:20,642 - Inspection date 2021-11-29 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:20,642 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:20,642 - Inspection date 2021-11-29 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:20,642 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:20,642 - Inspection date 2021-11-29 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:20,643 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:20,643 - Inspection date 2021-11-29 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:20,643 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:20,643 - Inspection date 2021-11-29 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:20,643 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:22,430 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:22,432 - built Dictionary<1221 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2655 corpus positions) -2024-07-15 10:46:22,433 - Dictionary lifecycle event {'msg': "built Dictionary<1221 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2655 corpus positions)", 'datetime': '2024-07-15T10:46:22.433048', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:22,434 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:22,434 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:22,434 - using serial LDA version on this node -2024-07-15 10:46:22,435 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:22,435 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:22,439 - -8.129 per-word bound, 280.0 perplexity estimate based on a held-out corpus of 1 documents with 2655 words -2024-07-15 10:46:22,439 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:22,440 - topic #0 (0.333): 0.019*"’" + 0.007*"Norfolk" + 0.007*"carers" + 0.006*"well" + 0.006*"supported" + 0.006*"needs" + 0.006*"practice" + 0.005*"including" + 0.005*"information" + 0.005*"range" -2024-07-15 10:46:22,440 - topic #1 (0.333): 0.019*"’" + 0.009*"well" + 0.008*"Norfolk" + 0.006*"carers" + 0.006*"practice" + 0.006*"needs" + 0.005*"supported" + 0.005*"plans" + 0.004*"leaders" + 0.004*"7" -2024-07-15 10:46:22,441 - topic #2 (0.333): 0.010*"’" + 0.008*"Norfolk" + 0.008*"well" + 0.005*"needs" + 0.004*"carers" + 0.004*"18" + 0.004*"practice" + 0.004*"experiences" + 0.004*"supported" + 0.004*"plans" -2024-07-15 10:46:22,441 - topic diff=0.790226, rho=1.000000 -2024-07-15 10:46:22,441 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:22.441300', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:23,428 - Inspection date 2022-11-07 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:23,428 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:23,428 - Inspection date 2022-11-07 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:23,428 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:23,428 - Inspection date 2022-11-07 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:23,429 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:23,429 - Inspection date 2022-11-07 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:23,429 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:23,429 - Inspection date 2022-11-07 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:23,429 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:23,429 - Inspection date 2022-11-07 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:23,429 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:24,944 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:24,948 - built Dictionary<958 unique tokens: ['0161', '021', '0300', '1', '10']...> from 1 documents (total 2045 corpus positions) -2024-07-15 10:46:24,948 - Dictionary lifecycle event {'msg': "built Dictionary<958 unique tokens: ['0161', '021', '0300', '1', '10']...> from 1 documents (total 2045 corpus positions)", 'datetime': '2024-07-15T10:46:24.948803', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:24,950 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:24,950 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:24,951 - using serial LDA version on this node -2024-07-15 10:46:24,951 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:24,951 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:24,957 - -7.891 per-word bound, 237.3 perplexity estimate based on a held-out corpus of 1 documents with 2045 words -2024-07-15 10:46:24,957 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:24,959 - topic #0 (0.333): 0.015*"’" + 0.007*"practice" + 0.007*"leaders" + 0.007*"planning" + 0.006*"needs" + 0.006*"risk" + 0.006*"need" + 0.005*"October" + 0.005*"North" + 0.005*"oversight" -2024-07-15 10:46:24,959 - topic #1 (0.333): 0.016*"’" + 0.009*"risk" + 0.008*"practice" + 0.006*"needs" + 0.006*"planning" + 0.006*"senior" + 0.006*"leaders" + 0.005*"many" + 0.005*"East" + 0.005*"North" -2024-07-15 10:46:24,959 - topic #2 (0.333): 0.011*"’" + 0.007*"practice" + 0.006*"leaders" + 0.006*"needs" + 0.005*"planning" + 0.005*"Lincolnshire" + 0.005*"Council" + 0.005*"need" + 0.005*"2021" + 0.005*"risk" -2024-07-15 10:46:24,960 - topic diff=0.767127, rho=1.000000 -2024-07-15 10:46:24,960 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:24.960795', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:25,893 - Inspection date 2021-10-04 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:25,893 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:25,894 - Inspection date 2021-10-04 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:25,894 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:25,894 - Inspection date 2021-10-04 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:25,894 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:25,894 - Inspection date 2021-10-04 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:25,895 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:25,895 - Inspection date 2021-10-04 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:25,895 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:25,895 - Inspection date 2021-10-04 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:25,895 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:27,236 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:27,238 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2174 corpus positions) -2024-07-15 10:46:27,238 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2174 corpus positions)", 'datetime': '2024-07-15T10:46:27.238853', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:27,239 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:27,240 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:27,240 - using serial LDA version on this node -2024-07-15 10:46:27,240 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:27,240 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:27,244 - -8.064 per-word bound, 267.6 perplexity estimate based on a held-out corpus of 1 documents with 2174 words -2024-07-15 10:46:27,244 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:27,246 - topic #0 (0.333): 0.016*"’" + 0.006*"‘" + 0.006*"approach" + 0.006*"Lincolnshire" + 0.005*"North" + 0.005*"family" + 0.005*"leaders" + 0.005*"protection" + 0.004*"well" + 0.004*"14" -2024-07-15 10:46:27,246 - topic #1 (0.333): 0.023*"’" + 0.008*"‘" + 0.006*"family" + 0.005*"Lincolnshire" + 0.005*"well" + 0.005*"leaders" + 0.005*"North" + 0.005*"need" + 0.004*"14" + 0.004*"2022" -2024-07-15 10:46:27,246 - topic #2 (0.333): 0.021*"’" + 0.007*"family" + 0.006*"‘" + 0.006*"10" + 0.005*"North" + 0.005*"need" + 0.005*"well" + 0.005*"approach" + 0.005*"leaders" + 0.005*"council" -2024-07-15 10:46:27,246 - topic diff=0.747481, rho=1.000000 -2024-07-15 10:46:27,246 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:27.246758', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:28,218 - Inspection date 2022-10-10 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:28,218 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:28,218 - Inspection date 2022-10-10 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:28,218 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:28,219 - Inspection date 2022-10-10 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:28,219 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:28,219 - Inspection date 2022-10-10 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:28,219 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:28,219 - Inspection date 2022-10-10 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:28,219 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:28,220 - Inspection date 2022-10-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:28,220 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:29,488 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:29,490 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2204 corpus positions) -2024-07-15 10:46:29,490 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2204 corpus positions)", 'datetime': '2024-07-15T10:46:29.490932', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:29,492 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:29,492 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:29,492 - using serial LDA version on this node -2024-07-15 10:46:29,492 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:29,492 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:29,496 - -8.030 per-word bound, 261.3 perplexity estimate based on a held-out corpus of 1 documents with 2204 words -2024-07-15 10:46:29,496 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:29,497 - topic #0 (0.333): 0.019*"’" + 0.007*"Northamptonshire" + 0.007*"North" + 0.005*"Leaders" + 0.005*"well" + 0.005*"e" + 0.005*"quality" + 0.005*"plans" + 0.005*"3" + 0.005*"NCT" -2024-07-15 10:46:29,498 - topic #1 (0.333): 0.017*"’" + 0.008*"Northamptonshire" + 0.007*"well" + 0.007*"North" + 0.006*"quality" + 0.006*"practice" + 0.006*"impact" + 0.005*"need" + 0.005*"needs" + 0.005*"Leaders" -2024-07-15 10:46:29,498 - topic #2 (0.333): 0.013*"’" + 0.009*"Northamptonshire" + 0.006*"North" + 0.006*"well" + 0.005*"experiences" + 0.005*"quality" + 0.004*"needs" + 0.004*"NCT" + 0.004*"practice" + 0.004*"2022" -2024-07-15 10:46:29,498 - topic diff=0.750025, rho=1.000000 -2024-07-15 10:46:29,498 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:29.498595', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:30,624 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:30,624 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:30,625 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:30,625 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:30,625 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:30,625 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:30,625 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:30,626 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:30,626 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:30,626 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:30,626 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:30,627 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:32,136 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:32,139 - built Dictionary<1219 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2902 corpus positions) -2024-07-15 10:46:32,140 - Dictionary lifecycle event {'msg': "built Dictionary<1219 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2902 corpus positions)", 'datetime': '2024-07-15T10:46:32.140030', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:32,141 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:32,141 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:32,141 - using serial LDA version on this node -2024-07-15 10:46:32,142 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:32,142 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:32,146 - -8.070 per-word bound, 268.7 perplexity estimate based on a held-out corpus of 1 documents with 2902 words -2024-07-15 10:46:32,146 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:32,147 - topic #0 (0.333): 0.017*"’" + 0.007*"needs" + 0.006*"North" + 0.006*"Somerset" + 0.006*"always" + 0.005*"experienced" + 0.005*"number" + 0.005*"practice" + 0.005*"need" + 0.005*"progress" -2024-07-15 10:46:32,148 - topic #1 (0.333): 0.018*"’" + 0.008*"quality" + 0.007*"always" + 0.007*"practice" + 0.006*"needs" + 0.006*"number" + 0.006*"risk" + 0.006*"Somerset" + 0.005*"North" + 0.005*"need" -2024-07-15 10:46:32,148 - topic #2 (0.333): 0.014*"’" + 0.009*"quality" + 0.007*"needs" + 0.006*"progress" + 0.005*"well" + 0.005*"Somerset" + 0.005*"experienced" + 0.005*"North" + 0.005*"number" + 0.005*"always" -2024-07-15 10:46:32,148 - topic diff=0.832443, rho=1.000000 -2024-07-15 10:46:32,148 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:32.148621', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:34,104 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:34,105 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:34,105 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:34,105 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:34,105 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:34,105 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:34,106 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:34,106 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:34,106 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:34,106 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:34,106 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:34,106 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:35,567 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:35,569 - built Dictionary<1273 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2518 corpus positions) -2024-07-15 10:46:35,569 - Dictionary lifecycle event {'msg': "built Dictionary<1273 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2518 corpus positions)", 'datetime': '2024-07-15T10:46:35.569863', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:35,571 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:35,571 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:35,571 - using serial LDA version on this node -2024-07-15 10:46:35,571 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:35,571 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:35,576 - -8.220 per-word bound, 298.1 perplexity estimate based on a held-out corpus of 1 documents with 2518 words -2024-07-15 10:46:35,576 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:35,578 - topic #0 (0.333): 0.014*"’" + 0.006*"well" + 0.005*"make" + 0.005*"leaders" + 0.004*"need" + 0.004*"quality" + 0.004*"clear" + 0.004*"impact" + 0.004*"progress" + 0.003*"understand" -2024-07-15 10:46:35,578 - topic #1 (0.333): 0.019*"’" + 0.006*"well" + 0.006*"leaders" + 0.006*"need" + 0.005*"needs" + 0.005*"quality" + 0.005*"early" + 0.005*"make" + 0.004*"impact" + 0.004*"foster" -2024-07-15 10:46:35,578 - topic #2 (0.333): 0.014*"’" + 0.006*"well" + 0.005*"need" + 0.004*"quality" + 0.004*"leaders" + 0.004*"needs" + 0.004*"impact" + 0.003*"make" + 0.003*"understand" + 0.003*"protection" -2024-07-15 10:46:35,578 - topic diff=0.733480, rho=1.000000 -2024-07-15 10:46:35,578 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:35.578865', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:36,819 - Inspection date 2020-03-09 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:36,819 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:36,820 - Inspection date 2020-03-09 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:36,820 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:36,820 - Inspection date 2020-03-09 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:36,820 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:36,820 - Inspection date 2020-03-09 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:36,820 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:36,821 - Inspection date 2020-03-09 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:36,821 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:36,821 - Inspection date 2020-03-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:36,821 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:38,262 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:38,264 - built Dictionary<1259 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2759 corpus positions) -2024-07-15 10:46:38,265 - Dictionary lifecycle event {'msg': "built Dictionary<1259 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2759 corpus positions)", 'datetime': '2024-07-15T10:46:38.265079', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:38,266 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:38,266 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:38,266 - using serial LDA version on this node -2024-07-15 10:46:38,267 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:38,267 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:38,271 - -8.145 per-word bound, 283.1 perplexity estimate based on a held-out corpus of 1 documents with 2759 words -2024-07-15 10:46:38,271 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:38,272 - topic #0 (0.333): 0.012*"’" + 0.008*"well" + 0.006*"family" + 0.006*"Yorkshire" + 0.005*"needs" + 0.005*"North" + 0.004*"‘" + 0.004*"practice" + 0.004*"supported" + 0.004*"7" -2024-07-15 10:46:38,273 - topic #1 (0.333): 0.022*"’" + 0.009*"well" + 0.006*"North" + 0.006*"practice" + 0.006*"Yorkshire" + 0.006*"family" + 0.005*"needs" + 0.005*"‘" + 0.004*"3" + 0.004*"7" -2024-07-15 10:46:38,273 - topic #2 (0.333): 0.024*"’" + 0.008*"well" + 0.007*"North" + 0.007*"practice" + 0.006*"Yorkshire" + 0.006*"needs" + 0.005*"family" + 0.005*"‘" + 0.005*"3" + 0.005*"supported" -2024-07-15 10:46:38,273 - topic diff=0.807619, rho=1.000000 -2024-07-15 10:46:38,273 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:38.273562', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:39,444 - Inspection date 2023-07-03 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:39,444 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:39,445 - Inspection date 2023-07-03 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:39,445 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:39,445 - Inspection date 2023-07-03 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:39,445 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:39,445 - Inspection date 2023-07-03 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:39,446 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:39,446 - Inspection date 2023-07-03 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:39,446 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:39,446 - Inspection date 2023-07-03 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:39,446 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:40,980 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:40,982 - built Dictionary<1218 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2884 corpus positions) -2024-07-15 10:46:40,982 - Dictionary lifecycle event {'msg': "built Dictionary<1218 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2884 corpus positions)", 'datetime': '2024-07-15T10:46:40.982896', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:40,984 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:40,984 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:40,984 - using serial LDA version on this node -2024-07-15 10:46:40,984 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:40,984 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:40,988 - -8.072 per-word bound, 269.2 perplexity estimate based on a held-out corpus of 1 documents with 2884 words -2024-07-15 10:46:40,988 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:40,990 - topic #0 (0.333): 0.016*"’" + 0.006*"needs" + 0.006*"family" + 0.005*"strong" + 0.005*"provide" + 0.005*"leaders" + 0.005*"well" + 0.005*"experiences" + 0.005*"Northumberland" + 0.005*"plans" -2024-07-15 10:46:40,990 - topic #1 (0.333): 0.017*"’" + 0.009*"family" + 0.008*"leaders" + 0.007*"needs" + 0.007*"experiences" + 0.006*"well" + 0.006*"Northumberland" + 0.005*"within" + 0.005*"strong" + 0.005*"plans" -2024-07-15 10:46:40,990 - topic #2 (0.333): 0.022*"’" + 0.007*"strong" + 0.007*"family" + 0.006*"experiences" + 0.006*"leaders" + 0.006*"needs" + 0.005*"effective" + 0.005*"well" + 0.005*"Northumberland" + 0.005*"practice" -2024-07-15 10:46:40,990 - topic diff=0.837580, rho=1.000000 -2024-07-15 10:46:40,990 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:40.990962', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:42,298 - Inspection date 2024-05-20 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:42,298 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:42,299 - Inspection date 2024-05-20 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:42,299 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:42,299 - Inspection date 2024-05-20 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:42,299 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:42,300 - Inspection date 2024-05-20 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:42,300 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:42,300 - Inspection date 2024-05-20 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:42,300 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:42,300 - Inspection date 2024-05-20 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:42,301 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:43,961 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:43,963 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions) -2024-07-15 10:46:43,964 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)", 'datetime': '2024-07-15T10:46:43.964141', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:43,965 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:43,965 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:43,965 - using serial LDA version on this node -2024-07-15 10:46:43,966 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:43,966 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:43,969 - -8.027 per-word bound, 260.8 perplexity estimate based on a held-out corpus of 1 documents with 2316 words -2024-07-15 10:46:43,969 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:43,971 - topic #0 (0.333): 0.014*"’" + 0.008*"needs" + 0.005*"effective" + 0.005*"Nottingham" + 0.005*"July" + 0.005*"oversight" + 0.005*"impact" + 0.005*"11" + 0.004*"2022" + 0.004*"risk" -2024-07-15 10:46:43,971 - topic #1 (0.333): 0.013*"’" + 0.009*"needs" + 0.007*"effective" + 0.007*"plans" + 0.006*"Nottingham" + 0.005*"impact" + 0.005*"However" + 0.005*"11" + 0.005*"risk" + 0.004*"City" -2024-07-15 10:46:43,971 - topic #2 (0.333): 0.015*"’" + 0.006*"needs" + 0.006*"Nottingham" + 0.005*"City" + 0.005*"oversight" + 0.005*"plans" + 0.004*"practice" + 0.004*"impact" + 0.004*"11" + 0.004*"July" -2024-07-15 10:46:43,971 - topic diff=0.768551, rho=1.000000 -2024-07-15 10:46:43,972 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:43.971996', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:44,927 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:44,928 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:44,928 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:44,928 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:44,928 - Inspection date None / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:44,929 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:44,929 - Inspection date None / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:44,929 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:44,929 - Inspection date None / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:44,930 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:44,930 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:44,930 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:46,132 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:46,134 - built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2129 corpus positions) -2024-07-15 10:46:46,134 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2129 corpus positions)", 'datetime': '2024-07-15T10:46:46.134921', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:46,135 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:46,136 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:46,136 - using serial LDA version on this node -2024-07-15 10:46:46,136 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:46,136 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:46,140 - -8.014 per-word bound, 258.5 perplexity estimate based on a held-out corpus of 1 documents with 2129 words -2024-07-15 10:46:46,140 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:46,141 - topic #0 (0.333): 0.014*"’" + 0.010*"well" + 0.009*"needs" + 0.007*"Nottinghamshire" + 0.006*"plans" + 0.005*"20" + 0.005*"benefit" + 0.005*"2024" + 0.004*"education" + 0.004*"Leaders" -2024-07-15 10:46:46,141 - topic #1 (0.333): 0.011*"’" + 0.007*"needs" + 0.007*"well" + 0.006*"Nottinghamshire" + 0.005*"plans" + 0.005*"24" + 0.004*"Leaders" + 0.004*"benefit" + 0.004*"May" + 0.004*"County" -2024-07-15 10:46:46,141 - topic #2 (0.333): 0.025*"’" + 0.009*"well" + 0.009*"needs" + 0.006*"plans" + 0.006*"Nottinghamshire" + 0.006*"effective" + 0.005*"leaders" + 0.005*"practice" + 0.005*"Leaders" + 0.005*"ensure" -2024-07-15 10:46:46,142 - topic diff=0.765884, rho=1.000000 -2024-07-15 10:46:46,142 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:46.142125', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:47,098 - Inspection date 2024-05-20 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:47,098 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:47,098 - Inspection date 2024-05-20 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:47,099 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:47,099 - Inspection date 2024-05-20 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:47,099 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:47,099 - Inspection date 2024-05-20 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:47,100 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:47,100 - Inspection date 2024-05-20 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:47,100 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:47,100 - Inspection date 2024-05-20 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:47,101 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:48,447 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:48,449 - built Dictionary<1152 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2441 corpus positions) -2024-07-15 10:46:48,449 - Dictionary lifecycle event {'msg': "built Dictionary<1152 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2441 corpus positions)", 'datetime': '2024-07-15T10:46:48.449886', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:48,450 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:48,451 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:48,451 - using serial LDA version on this node -2024-07-15 10:46:48,451 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:48,451 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:48,455 - -8.083 per-word bound, 271.1 perplexity estimate based on a held-out corpus of 1 documents with 2441 words -2024-07-15 10:46:48,455 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:48,456 - topic #0 (0.333): 0.011*"’" + 0.009*"well" + 0.007*"plans" + 0.006*"needs" + 0.006*"Oldham" + 0.005*"practice" + 0.005*"PAs" + 0.005*"effective" + 0.005*"need" + 0.005*"progress" -2024-07-15 10:46:48,457 - topic #1 (0.333): 0.010*"’" + 0.009*"plans" + 0.007*"well" + 0.006*"practice" + 0.005*"Oldham" + 0.005*"supported" + 0.005*"leaders" + 0.005*"quality" + 0.005*"needs" + 0.004*"PAs" -2024-07-15 10:46:48,457 - topic #2 (0.333): 0.016*"’" + 0.009*"plans" + 0.008*"well" + 0.007*"needs" + 0.007*"PAs" + 0.006*"leaders" + 0.006*"Oldham" + 0.006*"practice" + 0.005*"progress" + 0.005*"risk" -2024-07-15 10:46:48,457 - topic diff=0.792929, rho=1.000000 -2024-07-15 10:46:48,457 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:48.457566', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:49,489 - Inspection date 2024-05-13 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:49,489 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:49,489 - Inspection date 2024-05-13 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:49,489 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:49,489 - Inspection date 2024-05-13 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:49,489 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:49,490 - Inspection date 2024-05-13 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:49,490 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:49,490 - Inspection date 2024-05-13 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:49,490 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:49,490 - Inspection date 2024-05-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:49,490 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:50,817 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:50,819 - built Dictionary<1066 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2294 corpus positions) -2024-07-15 10:46:50,819 - Dictionary lifecycle event {'msg': "built Dictionary<1066 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2294 corpus positions)", 'datetime': '2024-07-15T10:46:50.819813', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:50,820 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:50,820 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:50,821 - using serial LDA version on this node -2024-07-15 10:46:50,821 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:50,821 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:50,825 - -7.992 per-word bound, 254.5 perplexity estimate based on a held-out corpus of 1 documents with 2294 words -2024-07-15 10:46:50,825 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:50,826 - topic #0 (0.333): 0.019*"’" + 0.010*"needs" + 0.007*"Oxfordshire" + 0.006*"well" + 0.006*"12" + 0.006*"risk" + 0.005*"receive" + 0.005*"supported" + 0.005*"progress" + 0.004*"arrangements" -2024-07-15 10:46:50,827 - topic #1 (0.333): 0.019*"’" + 0.010*"needs" + 0.007*"Oxfordshire" + 0.007*"good" + 0.006*"well" + 0.006*"risk" + 0.005*"education" + 0.005*"12" + 0.005*"supported" + 0.005*"progress" -2024-07-15 10:46:50,827 - topic #2 (0.333): 0.020*"’" + 0.009*"needs" + 0.007*"well" + 0.007*"supported" + 0.006*"Oxfordshire" + 0.006*"quality" + 0.005*"good" + 0.005*"risk" + 0.005*"practice" + 0.004*"progress" -2024-07-15 10:46:50,827 - topic diff=0.773917, rho=1.000000 -2024-07-15 10:46:50,827 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:50.827467', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:51,783 - Inspection date 2024-02-12 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:51,783 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:51,784 - Inspection date 2024-02-12 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:51,784 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:51,784 - Inspection date 2024-02-12 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:51,784 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:51,784 - Inspection date 2024-02-12 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:51,785 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:51,785 - Inspection date 2024-02-12 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:51,785 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:51,785 - Inspection date 2024-02-12 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:51,785 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:53,512 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:53,514 - built Dictionary<893 unique tokens: ['0-25', '0161', '0300', '1', '10']...> from 1 documents (total 1737 corpus positions) -2024-07-15 10:46:53,514 - Dictionary lifecycle event {'msg': "built Dictionary<893 unique tokens: ['0-25', '0161', '0300', '1', '10']...> from 1 documents (total 1737 corpus positions)", 'datetime': '2024-07-15T10:46:53.514923', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:53,515 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:53,515 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:53,516 - using serial LDA version on this node -2024-07-15 10:46:53,516 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:53,516 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:53,519 - -7.883 per-word bound, 236.1 perplexity estimate based on a held-out corpus of 1 documents with 1737 words -2024-07-15 10:46:53,519 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:53,521 - topic #0 (0.333): 0.012*"’" + 0.010*"needs" + 0.007*"well" + 0.006*"need" + 0.006*"Peterborough" + 0.006*"2023" + 0.005*"good" + 0.005*"progress" + 0.005*"8" + 0.004*"supported" -2024-07-15 10:46:53,521 - topic #1 (0.333): 0.016*"’" + 0.015*"needs" + 0.008*"need" + 0.008*"Peterborough" + 0.007*"2023" + 0.006*"progress" + 0.006*"plans" + 0.005*"8" + 0.005*"well" + 0.005*"supported" -2024-07-15 10:46:53,521 - topic #2 (0.333): 0.015*"’" + 0.014*"needs" + 0.006*"Peterborough" + 0.006*"well" + 0.006*"need" + 0.005*"good" + 0.005*"progress" + 0.005*"supported" + 0.005*"education" + 0.005*"receive" -2024-07-15 10:46:53,521 - topic diff=0.732124, rho=1.000000 -2024-07-15 10:46:53,521 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:53.521569', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:54,485 - Inspection date 2023-11-27 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:54,485 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:54,485 - Inspection date 2023-11-27 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:54,485 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:54,486 - Inspection date 2023-11-27 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:54,486 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:54,486 - Inspection date 2023-11-27 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:54,486 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:54,486 - Inspection date 2023-11-27 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:54,486 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:54,486 - Inspection date 2023-11-27 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:54,487 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:56,106 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:56,109 - built Dictionary<1232 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions) -2024-07-15 10:46:56,109 - Dictionary lifecycle event {'msg': "built Dictionary<1232 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)", 'datetime': '2024-07-15T10:46:56.109235', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:56,110 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:56,110 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:56,110 - using serial LDA version on this node -2024-07-15 10:46:56,111 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:56,111 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:56,115 - -8.088 per-word bound, 272.0 perplexity estimate based on a held-out corpus of 1 documents with 2905 words -2024-07-15 10:46:56,115 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:56,117 - topic #0 (0.333): 0.011*"’" + 0.009*"needs" + 0.007*"well" + 0.007*"Plymouth" + 0.006*"practice" + 0.005*"appropriate" + 0.005*"February" + 0.005*"plans" + 0.005*"2" + 0.005*"Council" -2024-07-15 10:46:56,117 - topic #1 (0.333): 0.012*"’" + 0.006*"well" + 0.006*"needs" + 0.006*"Plymouth" + 0.005*"practice" + 0.004*"January" + 0.004*"2024" + 0.004*"plans" + 0.004*"benefit" + 0.004*"appropriate" -2024-07-15 10:46:56,117 - topic #2 (0.333): 0.016*"’" + 0.009*"needs" + 0.007*"well" + 0.007*"Plymouth" + 0.006*"education" + 0.005*"good" + 0.005*"2" + 0.005*"risks" + 0.004*"plans" + 0.004*"practice" -2024-07-15 10:46:56,117 - topic diff=0.839530, rho=1.000000 -2024-07-15 10:46:56,117 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:56.117580', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:57,034 - Inspection date 2024-01-22 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:57,034 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:57,035 - Inspection date 2024-01-22 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:57,035 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:57,035 - Inspection date 2024-01-22 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:57,036 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:57,036 - Inspection date 2024-01-22 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:57,036 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:57,036 - Inspection date 2024-01-22 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:57,036 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:57,036 - Inspection date 2024-01-22 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:57,036 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:58,752 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:46:58,755 - built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2738 corpus positions) -2024-07-15 10:46:58,755 - Dictionary lifecycle event {'msg': "built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2738 corpus positions)", 'datetime': '2024-07-15T10:46:58.755350', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:58,756 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:46:58,756 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:46:58,756 - using serial LDA version on this node -2024-07-15 10:46:58,757 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:46:58,757 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:46:58,762 - -8.113 per-word bound, 276.8 perplexity estimate based on a held-out corpus of 1 documents with 2738 words -2024-07-15 10:46:58,762 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:46:58,764 - topic #0 (0.333): 0.018*"’" + 0.008*"well" + 0.008*"care-experienced" + 0.007*"needs" + 0.006*"plans" + 0.005*"Portsmouth" + 0.005*"health" + 0.005*"practice" + 0.005*"19" + 0.004*"good" -2024-07-15 10:46:58,764 - topic #1 (0.333): 0.015*"’" + 0.008*"care-experienced" + 0.007*"Portsmouth" + 0.006*"needs" + 0.006*"family" + 0.005*"need" + 0.005*"practice" + 0.005*"2023" + 0.004*"plans" + 0.004*"well" -2024-07-15 10:46:58,764 - topic #2 (0.333): 0.018*"’" + 0.009*"well" + 0.008*"care-experienced" + 0.008*"Portsmouth" + 0.006*"needs" + 0.006*"family" + 0.006*"health" + 0.005*"plans" + 0.004*"progress" + 0.004*"leaders" -2024-07-15 10:46:58,764 - topic diff=0.793634, rho=1.000000 -2024-07-15 10:46:58,764 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:46:58.764972', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:46:59,876 - Inspection date 2023-05-15 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:46:59,876 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:59,877 - Inspection date 2023-05-15 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:46:59,877 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:59,877 - Inspection date 2023-05-15 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:46:59,877 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:59,877 - Inspection date 2023-05-15 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:46:59,878 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:59,878 - Inspection date 2023-05-15 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:46:59,878 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:46:59,878 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:46:59,878 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:01,168 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:01,170 - built Dictionary<1231 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2562 corpus positions) -2024-07-15 10:47:01,171 - Dictionary lifecycle event {'msg': "built Dictionary<1231 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2562 corpus positions)", 'datetime': '2024-07-15T10:47:01.171107', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:01,172 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:01,172 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:01,172 - using serial LDA version on this node -2024-07-15 10:47:01,173 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:01,173 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:01,177 - -8.158 per-word bound, 285.7 perplexity estimate based on a held-out corpus of 1 documents with 2562 words -2024-07-15 10:47:01,177 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:01,179 - topic #0 (0.333): 0.011*"’" + 0.005*"needs" + 0.005*"well" + 0.005*"plans" + 0.005*"Reading" + 0.005*"progress" + 0.004*"PAs" + 0.004*"2024" + 0.003*"practice" + 0.003*"3" -2024-07-15 10:47:01,179 - topic #1 (0.333): 0.014*"’" + 0.008*"needs" + 0.005*"PAs" + 0.005*"Reading" + 0.005*"progress" + 0.005*"22" + 0.005*"clear" + 0.005*"well" + 0.004*"3" + 0.004*"plans" -2024-07-15 10:47:01,179 - topic #2 (0.333): 0.017*"’" + 0.006*"PAs" + 0.006*"needs" + 0.005*"plans" + 0.005*"well" + 0.005*"progress" + 0.005*"arrangements" + 0.004*"effective" + 0.004*"2024" + 0.004*"risk" -2024-07-15 10:47:01,179 - topic diff=0.764295, rho=1.000000 -2024-07-15 10:47:01,179 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:01.179905', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:02,177 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:02,177 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:02,177 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:02,177 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:02,178 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:02,178 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:02,178 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:02,178 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:02,178 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:02,178 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:02,178 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:02,178 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:04,261 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:04,265 - built Dictionary<1112 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2515 corpus positions) -2024-07-15 10:47:04,265 - Dictionary lifecycle event {'msg': "built Dictionary<1112 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2515 corpus positions)", 'datetime': '2024-07-15T10:47:04.265481', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:04,267 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:04,267 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:04,268 - using serial LDA version on this node -2024-07-15 10:47:04,268 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:04,268 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:04,275 - -8.007 per-word bound, 257.2 perplexity estimate based on a held-out corpus of 1 documents with 2515 words -2024-07-15 10:47:04,275 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:04,277 - topic #0 (0.333): 0.016*"’" + 0.007*"leaders" + 0.006*"However" + 0.006*"practice" + 0.006*"needs" + 0.006*"consistently" + 0.005*"plans" + 0.005*"Cleveland" + 0.005*"2022" + 0.005*"July" -2024-07-15 10:47:04,277 - topic #1 (0.333): 0.015*"’" + 0.006*"needs" + 0.005*"leaders" + 0.005*"However" + 0.005*"Cleveland" + 0.005*"risk" + 0.005*"consistently" + 0.005*"Redcar" + 0.004*"plans" + 0.004*"practice" -2024-07-15 10:47:04,277 - topic #2 (0.333): 0.021*"’" + 0.007*"plans" + 0.006*"leaders" + 0.006*"20" + 0.005*"2022" + 0.005*"However" + 0.005*"consistently" + 0.005*"needs" + 0.005*"carers" + 0.004*"risk" -2024-07-15 10:47:04,278 - topic diff=0.798595, rho=1.000000 -2024-07-15 10:47:04,278 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:04.278416', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:05,248 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:05,248 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:05,248 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:05,248 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:05,249 - Inspection date None / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:05,249 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:05,249 - Inspection date None / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:05,249 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:05,249 - Inspection date None / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:05,249 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:05,250 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:05,250 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:06,646 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:06,648 - built Dictionary<1150 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2656 corpus positions) -2024-07-15 10:47:06,648 - Dictionary lifecycle event {'msg': "built Dictionary<1150 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2656 corpus positions)", 'datetime': '2024-07-15T10:47:06.648751', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:06,649 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:06,650 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:06,650 - using serial LDA version on this node -2024-07-15 10:47:06,650 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:06,650 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:06,654 - -8.026 per-word bound, 260.7 perplexity estimate based on a held-out corpus of 1 documents with 2656 words -2024-07-15 10:47:06,654 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:06,656 - topic #0 (0.333): 0.019*"’" + 0.008*"experienced" + 0.007*"practice" + 0.006*"response" + 0.006*"needs" + 0.006*"plans" + 0.005*"good" + 0.005*"quality" + 0.005*"consistently" + 0.004*"need" -2024-07-15 10:47:06,656 - topic #1 (0.333): 0.017*"’" + 0.009*"experienced" + 0.008*"needs" + 0.007*"practice" + 0.006*"consistently" + 0.006*"plans" + 0.006*"response" + 0.005*"Rochdale" + 0.005*"quality" + 0.005*"well" -2024-07-15 10:47:06,656 - topic #2 (0.333): 0.024*"’" + 0.011*"experienced" + 0.009*"needs" + 0.009*"practice" + 0.006*"response" + 0.006*"plans" + 0.005*"consistently" + 0.005*"good" + 0.005*"quality" + 0.005*"Rochdale" -2024-07-15 10:47:06,656 - topic diff=0.820674, rho=1.000000 -2024-07-15 10:47:06,656 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:06.656912', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:07,638 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:07,638 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:07,639 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:07,639 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:07,639 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:07,639 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:07,639 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:07,639 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:07,640 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:07,640 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:07,640 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:07,640 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:08,966 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:08,969 - built Dictionary<1127 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2366 corpus positions) -2024-07-15 10:47:08,969 - Dictionary lifecycle event {'msg': "built Dictionary<1127 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2366 corpus positions)", 'datetime': '2024-07-15T10:47:08.969219', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:08,970 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:08,970 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:08,970 - using serial LDA version on this node -2024-07-15 10:47:08,971 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:08,971 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:08,975 - -8.063 per-word bound, 267.5 perplexity estimate based on a held-out corpus of 1 documents with 2366 words -2024-07-15 10:47:08,975 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:08,977 - topic #0 (0.333): 0.013*"’" + 0.007*"needs" + 0.007*"Rotherham" + 0.005*"well" + 0.005*"plans" + 0.004*"good" + 0.004*"Council" + 0.004*"clear" + 0.004*"ensure" + 0.004*"protection" -2024-07-15 10:47:08,977 - topic #1 (0.333): 0.018*"’" + 0.010*"Rotherham" + 0.006*"needs" + 0.005*"However" + 0.005*"good" + 0.005*"Council" + 0.005*"well" + 0.005*"1" + 0.005*"ensure" + 0.004*"27" -2024-07-15 10:47:08,977 - topic #2 (0.333): 0.014*"’" + 0.009*"Rotherham" + 0.005*"needs" + 0.005*"well" + 0.005*"ensure" + 0.005*"good" + 0.004*"Council" + 0.004*"However" + 0.004*"2022" + 0.004*"clear" -2024-07-15 10:47:08,977 - topic diff=0.769773, rho=1.000000 -2024-07-15 10:47:08,977 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:08.977682', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:10,287 - Inspection date 2022-06-27 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:10,287 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:10,287 - Inspection date 2022-06-27 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:10,288 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:10,288 - Inspection date 2022-06-27 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:10,288 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:10,288 - Inspection date 2022-06-27 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:10,288 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:10,288 - Inspection date 2022-06-27 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:10,288 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:10,289 - Inspection date 2022-06-27 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:10,289 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:11,571 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:11,574 - built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2380 corpus positions) -2024-07-15 10:47:11,574 - Dictionary lifecycle event {'msg': "built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2380 corpus positions)", 'datetime': '2024-07-15T10:47:11.574909', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:11,576 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:11,576 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:11,576 - using serial LDA version on this node -2024-07-15 10:47:11,576 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:11,576 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:11,580 - -8.047 per-word bound, 264.5 perplexity estimate based on a held-out corpus of 1 documents with 2380 words -2024-07-15 10:47:11,580 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:11,582 - topic #0 (0.333): 0.012*"’" + 0.010*"well" + 0.007*"practice" + 0.006*"highly" + 0.005*"strong" + 0.005*"effective" + 0.004*"needs" + 0.004*"leaders" + 0.004*"high" + 0.004*"professionals" -2024-07-15 10:47:11,582 - topic #1 (0.333): 0.012*"well" + 0.011*"’" + 0.008*"practice" + 0.006*"highly" + 0.005*"effective" + 0.004*"strong" + 0.004*"needs" + 0.004*"improve" + 0.004*"need" + 0.004*"leaders" -2024-07-15 10:47:11,582 - topic #2 (0.333): 0.016*"well" + 0.014*"practice" + 0.012*"’" + 0.008*"highly" + 0.008*"strong" + 0.007*"needs" + 0.006*"leaders" + 0.005*"effective" + 0.005*"professionals" + 0.005*"high" -2024-07-15 10:47:11,582 - topic diff=0.780428, rho=1.000000 -2024-07-15 10:47:11,582 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:11.582842', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:12,712 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:12,712 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:12,713 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:12,713 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:12,713 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:12,713 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:12,713 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:12,713 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:12,713 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:12,713 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:12,714 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:12,714 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:14,522 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:14,524 - built Dictionary<1107 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2257 corpus positions) -2024-07-15 10:47:14,525 - Dictionary lifecycle event {'msg': "built Dictionary<1107 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2257 corpus positions)", 'datetime': '2024-07-15T10:47:14.525055', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:14,526 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:14,526 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:14,526 - using serial LDA version on this node -2024-07-15 10:47:14,526 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:14,526 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:14,530 - -8.068 per-word bound, 268.4 perplexity estimate based on a held-out corpus of 1 documents with 2257 words -2024-07-15 10:47:14,530 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:14,532 - topic #0 (0.333): 0.013*"’" + 0.009*"well" + 0.007*"plans" + 0.006*"needs" + 0.005*"practice" + 0.005*"effective" + 0.005*"supported" + 0.005*"progress" + 0.004*"clear" + 0.004*"good" -2024-07-15 10:47:14,532 - topic #1 (0.333): 0.016*"’" + 0.010*"well" + 0.009*"plans" + 0.008*"needs" + 0.005*"good" + 0.005*"need" + 0.004*"risk" + 0.004*"clear" + 0.004*"practice" + 0.004*"range" -2024-07-15 10:47:14,532 - topic #2 (0.333): 0.012*"’" + 0.008*"plans" + 0.008*"needs" + 0.007*"well" + 0.006*"good" + 0.005*"effective" + 0.005*"parents" + 0.004*"need" + 0.004*"range" + 0.004*"appropriate" -2024-07-15 10:47:14,532 - topic diff=0.752665, rho=1.000000 -2024-07-15 10:47:14,532 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:14.532645', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:15,792 - Inspection date 2019-10-21 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:15,792 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:15,793 - Inspection date 2019-10-21 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:15,793 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:15,793 - Inspection date 2019-10-21 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:15,793 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:15,794 - Inspection date 2019-10-21 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:15,794 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:15,794 - Inspection date 2019-10-21 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:15,794 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:15,795 - Inspection date 2019-10-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:15,795 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:17,154 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:17,157 - built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2088 corpus positions) -2024-07-15 10:47:17,157 - Dictionary lifecycle event {'msg': "built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2088 corpus positions)", 'datetime': '2024-07-15T10:47:17.157204', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:17,159 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:17,159 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:17,160 - using serial LDA version on this node -2024-07-15 10:47:17,160 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:17,160 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:17,167 - -8.116 per-word bound, 277.4 perplexity estimate based on a held-out corpus of 1 documents with 2088 words -2024-07-15 10:47:17,167 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:17,169 - topic #0 (0.333): 0.013*"’" + 0.005*"plans" + 0.004*"benefit" + 0.004*"quality" + 0.004*"needs" + 0.004*"well" + 0.004*"actions" + 0.004*"information" + 0.004*"However" + 0.004*"health" -2024-07-15 10:47:17,169 - topic #1 (0.333): 0.011*"’" + 0.006*"well" + 0.005*"quality" + 0.005*"needs" + 0.005*"plans" + 0.004*"always" + 0.004*"information" + 0.004*"benefit" + 0.004*"effective" + 0.004*"need" -2024-07-15 10:47:17,169 - topic #2 (0.333): 0.011*"’" + 0.006*"well" + 0.005*"needs" + 0.005*"quality" + 0.004*"use" + 0.004*"effective" + 0.004*"plans" + 0.004*"However" + 0.004*"informed" + 0.003*"information" -2024-07-15 10:47:17,169 - topic diff=0.714410, rho=1.000000 -2024-07-15 10:47:17,169 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:17.169889', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:18,427 - Inspection date 2020-01-13 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:18,427 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:18,427 - Inspection date 2020-01-13 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:18,427 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:18,428 - Inspection date 2020-01-13 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:18,428 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:18,428 - Inspection date 2020-01-13 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:18,428 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:18,428 - Inspection date 2020-01-13 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:18,428 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:18,429 - Inspection date 2020-01-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:18,429 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:20,028 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:20,032 - built Dictionary<1089 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2211 corpus positions) -2024-07-15 10:47:20,032 - Dictionary lifecycle event {'msg': "built Dictionary<1089 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2211 corpus positions)", 'datetime': '2024-07-15T10:47:20.032264', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:20,033 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:20,033 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:20,033 - using serial LDA version on this node -2024-07-15 10:47:20,034 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:20,034 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:20,038 - -8.053 per-word bound, 265.5 perplexity estimate based on a held-out corpus of 1 documents with 2211 words -2024-07-15 10:47:20,038 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:20,039 - topic #0 (0.333): 0.018*"’" + 0.010*"Rutland" + 0.007*"needs" + 0.006*"positive" + 0.006*"impact" + 0.005*"need" + 0.005*"family" + 0.005*"plans" + 0.004*"understand" + 0.004*"effective" -2024-07-15 10:47:20,040 - topic #1 (0.333): 0.018*"’" + 0.007*"Rutland" + 0.007*"needs" + 0.006*"plans" + 0.006*"need" + 0.005*"positive" + 0.005*"effective" + 0.004*"good" + 0.004*"experiences" + 0.004*"impact" -2024-07-15 10:47:20,040 - topic #2 (0.333): 0.019*"’" + 0.009*"effective" + 0.009*"Rutland" + 0.008*"needs" + 0.007*"impact" + 0.005*"practice" + 0.005*"plans" + 0.005*"2024" + 0.005*"positive" + 0.005*"good" -2024-07-15 10:47:20,040 - topic diff=0.765814, rho=1.000000 -2024-07-15 10:47:20,040 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:20.040966', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:21,092 - Inspection date 2024-04-15 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:21,092 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:21,092 - Inspection date 2024-04-15 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:21,093 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:21,093 - Inspection date 2024-04-15 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:21,093 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:21,093 - Inspection date 2024-04-15 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:21,093 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:21,094 - Inspection date 2024-04-15 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:21,094 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:21,094 - Inspection date 2024-04-15 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:21,094 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:22,237 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:22,240 - built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2253 corpus positions) -2024-07-15 10:47:22,240 - Dictionary lifecycle event {'msg': "built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2253 corpus positions)", 'datetime': '2024-07-15T10:47:22.240300', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:22,241 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:22,241 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:22,241 - using serial LDA version on this node -2024-07-15 10:47:22,242 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:22,242 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:22,245 - -8.012 per-word bound, 258.1 perplexity estimate based on a held-out corpus of 1 documents with 2253 words -2024-07-15 10:47:22,245 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:22,247 - topic #0 (0.333): 0.012*"’" + 0.008*"plans" + 0.006*"well" + 0.005*"Salford" + 0.005*"needs" + 0.005*"effective" + 0.005*"leaders" + 0.004*"practice" + 0.004*"planning" + 0.004*"progress" -2024-07-15 10:47:22,247 - topic #1 (0.333): 0.017*"’" + 0.009*"needs" + 0.008*"plans" + 0.007*"well" + 0.007*"effective" + 0.007*"Salford" + 0.005*"planning" + 0.005*"practice" + 0.005*"progress" + 0.005*"quality" -2024-07-15 10:47:22,247 - topic #2 (0.333): 0.011*"’" + 0.008*"well" + 0.007*"needs" + 0.007*"plans" + 0.007*"effective" + 0.005*"practice" + 0.005*"10" + 0.005*"planning" + 0.005*"Salford" + 0.005*"Council" -2024-07-15 10:47:22,247 - topic diff=0.792773, rho=1.000000 -2024-07-15 10:47:22,247 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:22.247909', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:23,149 - Inspection date 2023-11-06 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:23,149 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:23,149 - Inspection date 2023-11-06 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:23,149 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:23,150 - Inspection date 2023-11-06 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:23,150 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:23,150 - Inspection date 2023-11-06 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:23,150 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:23,150 - Inspection date 2023-11-06 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:23,150 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:23,151 - Inspection date 2023-11-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:23,151 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:25,063 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:25,066 - built Dictionary<995 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2066 corpus positions) -2024-07-15 10:47:25,066 - Dictionary lifecycle event {'msg': "built Dictionary<995 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2066 corpus positions)", 'datetime': '2024-07-15T10:47:25.066203', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:25,067 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:25,067 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:25,067 - using serial LDA version on this node -2024-07-15 10:47:25,067 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:25,068 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:25,071 - -7.946 per-word bound, 246.6 perplexity estimate based on a held-out corpus of 1 documents with 2066 words -2024-07-15 10:47:25,071 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:25,072 - topic #0 (0.333): 0.013*"’" + 0.009*"needs" + 0.007*"Sandwell" + 0.006*"well" + 0.006*"plans" + 0.005*"quality" + 0.005*"effective" + 0.005*"20" + 0.005*"good" + 0.005*"many" -2024-07-15 10:47:25,073 - topic #1 (0.333): 0.014*"’" + 0.008*"plans" + 0.008*"Sandwell" + 0.008*"well" + 0.007*"needs" + 0.006*"quality" + 0.005*"Trust" + 0.005*"9" + 0.005*"education" + 0.005*"number" -2024-07-15 10:47:25,073 - topic #2 (0.333): 0.015*"’" + 0.007*"needs" + 0.006*"plans" + 0.006*"quality" + 0.005*"Sandwell" + 0.005*"well" + 0.004*"number" + 0.004*"20" + 0.004*"education" + 0.004*"Trust" -2024-07-15 10:47:25,073 - topic diff=0.766446, rho=1.000000 -2024-07-15 10:47:25,073 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:25.073500', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:25,961 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:25,961 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:25,962 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:25,962 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:25,962 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:25,962 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:25,962 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:25,963 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:25,963 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:25,963 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:25,963 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:25,963 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:27,710 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:27,712 - built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2300 corpus positions) -2024-07-15 10:47:27,713 - Dictionary lifecycle event {'msg': "built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2300 corpus positions)", 'datetime': '2024-07-15T10:47:27.712995', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:27,714 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:27,714 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:27,714 - using serial LDA version on this node -2024-07-15 10:47:27,714 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:27,714 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:27,718 - -7.928 per-word bound, 243.5 perplexity estimate based on a held-out corpus of 1 documents with 2300 words -2024-07-15 10:47:27,718 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:27,719 - topic #0 (0.333): 0.015*"’" + 0.007*"needs" + 0.006*"practice" + 0.005*"March" + 0.005*"lack" + 0.005*"21" + 0.005*"including" + 0.005*"protection" + 0.004*"l" + 0.004*"Sefton" -2024-07-15 10:47:27,720 - topic #1 (0.333): 0.016*"’" + 0.012*"needs" + 0.006*"oversight" + 0.006*"practice" + 0.006*"including" + 0.005*"protection" + 0.005*"plans" + 0.005*"lack" + 0.005*"many" + 0.004*"Sefton" -2024-07-15 10:47:27,720 - topic #2 (0.333): 0.017*"’" + 0.009*"needs" + 0.006*"practice" + 0.006*"oversight" + 0.006*"◼" + 0.005*"management" + 0.005*"always" + 0.005*"planning" + 0.005*"4" + 0.005*"many" -2024-07-15 10:47:27,720 - topic diff=0.787522, rho=1.000000 -2024-07-15 10:47:27,720 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:27.720398', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:28,708 - Inspection date 2022-02-21 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:28,708 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:28,708 - Inspection date 2022-02-21 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:28,709 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:28,709 - Inspection date 2022-02-21 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:28,709 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:28,709 - Inspection date 2022-02-21 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:28,709 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:28,709 - Inspection date 2022-02-21 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:28,709 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:28,710 - Inspection date 2022-02-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:28,710 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:30,127 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:30,129 - built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2327 corpus positions) -2024-07-15 10:47:30,130 - Dictionary lifecycle event {'msg': "built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2327 corpus positions)", 'datetime': '2024-07-15T10:47:30.130011', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:30,131 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:30,131 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:30,131 - using serial LDA version on this node -2024-07-15 10:47:30,131 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:30,131 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:30,135 - -8.068 per-word bound, 268.3 perplexity estimate based on a held-out corpus of 1 documents with 2327 words -2024-07-15 10:47:30,136 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:30,137 - topic #0 (0.333): 0.020*"’" + 0.010*"Sheffield" + 0.007*"needs" + 0.005*"quality" + 0.005*"well" + 0.005*"good" + 0.005*"health" + 0.004*"11" + 0.004*"leaders" + 0.004*"receive" -2024-07-15 10:47:30,137 - topic #1 (0.333): 0.023*"’" + 0.011*"Sheffield" + 0.009*"well" + 0.008*"needs" + 0.007*"practice" + 0.006*"leaders" + 0.005*"health" + 0.004*"quality" + 0.004*"experiences" + 0.004*"11" -2024-07-15 10:47:30,137 - topic #2 (0.333): 0.018*"’" + 0.012*"Sheffield" + 0.010*"needs" + 0.006*"leaders" + 0.006*"practice" + 0.006*"health" + 0.006*"well" + 0.005*"mental" + 0.004*"plans" + 0.004*"right" -2024-07-15 10:47:30,137 - topic diff=0.766788, rho=1.000000 -2024-07-15 10:47:30,138 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:30.138051', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:31,185 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:31,185 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:31,185 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:31,185 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:31,185 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:31,186 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:31,186 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:31,186 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:31,186 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:31,186 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:31,186 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:31,187 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:32,435 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:32,438 - built Dictionary<939 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1749 corpus positions) -2024-07-15 10:47:32,439 - Dictionary lifecycle event {'msg': "built Dictionary<939 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1749 corpus positions)", 'datetime': '2024-07-15T10:47:32.439072', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:32,440 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:32,440 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:32,441 - using serial LDA version on this node -2024-07-15 10:47:32,441 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:32,442 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:32,447 - -7.956 per-word bound, 248.3 perplexity estimate based on a held-out corpus of 1 documents with 1749 words -2024-07-15 10:47:32,447 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:32,449 - topic #0 (0.333): 0.022*"’" + 0.009*"needs" + 0.008*"well" + 0.007*"progress" + 0.006*"Shropshire" + 0.006*"plans" + 0.005*"making" + 0.005*"2022" + 0.005*"effectively" + 0.005*"leaders" -2024-07-15 10:47:32,450 - topic #1 (0.333): 0.014*"’" + 0.007*"Shropshire" + 0.006*"needs" + 0.006*"well" + 0.005*"training" + 0.005*"progress" + 0.005*"making" + 0.005*"2022" + 0.005*"7" + 0.005*"11" -2024-07-15 10:47:32,450 - topic #2 (0.333): 0.012*"’" + 0.009*"needs" + 0.007*"Shropshire" + 0.006*"well" + 0.006*"plans" + 0.004*"2022" + 0.004*"practice" + 0.004*"progress" + 0.004*"need" + 0.004*"health" -2024-07-15 10:47:32,450 - topic diff=0.728475, rho=1.000000 -2024-07-15 10:47:32,450 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:32.450715', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:33,422 - Inspection date 2022-02-07 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:33,422 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:33,422 - Inspection date 2022-02-07 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:33,422 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:33,422 - Inspection date 2022-02-07 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:33,422 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:33,423 - Inspection date 2022-02-07 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:33,423 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:33,423 - Inspection date 2022-02-07 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:33,424 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:33,424 - Inspection date 2022-02-07 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:33,424 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:35,001 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:35,005 - built Dictionary<1113 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2352 corpus positions) -2024-07-15 10:47:35,005 - Dictionary lifecycle event {'msg': "built Dictionary<1113 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2352 corpus positions)", 'datetime': '2024-07-15T10:47:35.005624', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:35,007 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:35,007 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:35,008 - using serial LDA version on this node -2024-07-15 10:47:35,008 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:35,008 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:35,014 - -8.048 per-word bound, 264.6 perplexity estimate based on a held-out corpus of 1 documents with 2352 words -2024-07-15 10:47:35,014 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:35,017 - topic #0 (0.333): 0.014*"’" + 0.007*"Slough" + 0.007*"plans" + 0.006*"quality" + 0.006*"needs" + 0.005*"3" + 0.005*"impact" + 0.005*"However" + 0.004*"supported" + 0.004*"leaders" -2024-07-15 10:47:35,017 - topic #1 (0.333): 0.016*"’" + 0.009*"Slough" + 0.007*"practice" + 0.006*"quality" + 0.006*"needs" + 0.005*"plans" + 0.005*"leaders" + 0.005*"3" + 0.005*"23" + 0.004*"2023" -2024-07-15 10:47:35,017 - topic #2 (0.333): 0.017*"’" + 0.007*"Slough" + 0.007*"needs" + 0.006*"plans" + 0.005*"quality" + 0.005*"practice" + 0.005*"progress" + 0.005*"planning" + 0.005*"impact" + 0.005*"need" -2024-07-15 10:47:35,017 - topic diff=0.780968, rho=1.000000 -2024-07-15 10:47:35,018 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:35.018013', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:36,094 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:36,094 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:36,094 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:36,094 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:36,095 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:36,095 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:36,095 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:36,095 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:36,095 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:36,095 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:36,096 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:36,096 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:37,553 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:37,556 - built Dictionary<996 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2163 corpus positions) -2024-07-15 10:47:37,556 - Dictionary lifecycle event {'msg': "built Dictionary<996 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2163 corpus positions)", 'datetime': '2024-07-15T10:47:37.556632', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:37,557 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:37,557 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:37,558 - using serial LDA version on this node -2024-07-15 10:47:37,558 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:37,558 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:37,562 - -7.918 per-word bound, 241.9 perplexity estimate based on a held-out corpus of 1 documents with 2163 words -2024-07-15 10:47:37,562 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:37,564 - topic #0 (0.333): 0.018*"’" + 0.012*"lack" + 0.008*"2022" + 0.006*"quality" + 0.006*"experiences" + 0.006*"need" + 0.006*"risk" + 0.006*"effective" + 0.006*"Solihull" + 0.005*"practice" -2024-07-15 10:47:37,564 - topic #1 (0.333): 0.013*"’" + 0.009*"lack" + 0.009*"2022" + 0.006*"significant" + 0.006*"risk" + 0.005*"quality" + 0.005*"Solihull" + 0.005*"need" + 0.005*"practice" + 0.005*"experiences" -2024-07-15 10:47:37,564 - topic #2 (0.333): 0.014*"’" + 0.009*"lack" + 0.008*"2022" + 0.007*"Solihull" + 0.007*"need" + 0.005*"risk" + 0.005*"practice" + 0.004*"delay" + 0.004*"quality" + 0.004*"significant" -2024-07-15 10:47:37,564 - topic diff=0.791564, rho=1.000000 -2024-07-15 10:47:37,564 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:37.564879', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:38,763 - Inspection date 2022-10-31 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:38,763 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:38,764 - Inspection date 2022-10-31 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:38,764 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:38,764 - Inspection date 2022-10-31 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:38,764 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:38,764 - Inspection date 2022-10-31 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:38,764 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:38,765 - Inspection date 2022-10-31 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:38,765 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:38,765 - Inspection date 2022-10-31 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:38,765 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:40,460 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:40,463 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2181 corpus positions) -2024-07-15 10:47:40,464 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2181 corpus positions)", 'datetime': '2024-07-15T10:47:40.464017', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:40,465 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:40,465 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:40,466 - using serial LDA version on this node -2024-07-15 10:47:40,466 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:40,466 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:40,472 - -7.922 per-word bound, 242.5 perplexity estimate based on a held-out corpus of 1 documents with 2181 words -2024-07-15 10:47:40,473 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:40,475 - topic #0 (0.333): 0.019*"’" + 0.009*"well" + 0.008*"needs" + 0.007*"plans" + 0.007*"Somerset" + 0.006*"including" + 0.006*"progress" + 0.006*"need" + 0.006*"supported" + 0.005*"good" -2024-07-15 10:47:40,475 - topic #1 (0.333): 0.016*"’" + 0.010*"well" + 0.010*"needs" + 0.007*"Somerset" + 0.006*"plans" + 0.006*"good" + 0.006*"leaders" + 0.006*"number" + 0.005*"supported" + 0.005*"practice" -2024-07-15 10:47:40,475 - topic #2 (0.333): 0.016*"’" + 0.007*"well" + 0.006*"needs" + 0.006*"good" + 0.005*"Somerset" + 0.005*"need" + 0.004*"18" + 0.004*"leaders" + 0.004*"number" + 0.004*"practice" -2024-07-15 10:47:40,475 - topic diff=0.812514, rho=1.000000 -2024-07-15 10:47:40,476 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:40.476015', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:41,416 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:41,416 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:41,416 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:41,416 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:41,416 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:41,416 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:41,417 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:41,417 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:41,417 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:41,417 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:41,417 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:41,417 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:42,749 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:42,752 - built Dictionary<1052 unique tokens: ['0', '016', '0161', '0300', '0–25']...> from 1 documents (total 2383 corpus positions) -2024-07-15 10:47:42,752 - Dictionary lifecycle event {'msg': "built Dictionary<1052 unique tokens: ['0', '016', '0161', '0300', '0–25']...> from 1 documents (total 2383 corpus positions)", 'datetime': '2024-07-15T10:47:42.752926', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:42,754 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:42,754 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:42,754 - using serial LDA version on this node -2024-07-15 10:47:42,754 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:42,754 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:42,758 - -7.952 per-word bound, 247.7 perplexity estimate based on a held-out corpus of 1 documents with 2383 words -2024-07-15 10:47:42,758 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:42,760 - topic #0 (0.333): 0.011*"quality" + 0.010*"’" + 0.009*"plans" + 0.009*"well" + 0.008*"leaders" + 0.008*"good" + 0.006*"timely" + 0.006*"needs" + 0.005*"progress" + 0.005*"impact" -2024-07-15 10:47:42,760 - topic #1 (0.333): 0.011*"well" + 0.010*"quality" + 0.009*"leaders" + 0.007*"’" + 0.005*"needs" + 0.005*"plans" + 0.005*"progress" + 0.005*"always" + 0.005*"good" + 0.004*"including" -2024-07-15 10:47:42,760 - topic #2 (0.333): 0.013*"well" + 0.009*"quality" + 0.008*"’" + 0.008*"leaders" + 0.008*"plans" + 0.007*"good" + 0.007*"timely" + 0.006*"progress" + 0.005*"Senior" + 0.005*"needs" -2024-07-15 10:47:42,760 - topic diff=0.799489, rho=1.000000 -2024-07-15 10:47:42,760 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:42.760977', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:43,911 - Inspection date 2019-03-04 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:43,912 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:43,912 - Inspection date 2019-03-04 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:43,912 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:43,912 - Inspection date 2019-03-04 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:43,912 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:43,913 - Inspection date 2019-03-04 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:43,913 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:43,913 - Inspection date 2019-03-04 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:43,913 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:43,913 - Inspection date 2019-03-04 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:43,914 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:45,451 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:45,454 - built Dictionary<981 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2189 corpus positions) -2024-07-15 10:47:45,454 - Dictionary lifecycle event {'msg': 'built Dictionary<981 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2189 corpus positions)', 'datetime': '2024-07-15T10:47:45.454756', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:45,456 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:45,456 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:45,456 - using serial LDA version on this node -2024-07-15 10:47:45,457 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:45,457 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:45,463 - -7.886 per-word bound, 236.6 perplexity estimate based on a held-out corpus of 1 documents with 2189 words -2024-07-15 10:47:45,463 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:45,466 - topic #0 (0.333): 0.017*"’" + 0.008*"Tyneside" + 0.007*"South" + 0.007*"needs" + 0.005*"practice" + 0.005*"management" + 0.004*"2022" + 0.004*"15" + 0.004*"living" + 0.004*"oversight" -2024-07-15 10:47:45,466 - topic #1 (0.333): 0.030*"’" + 0.009*"needs" + 0.008*"Tyneside" + 0.008*"South" + 0.006*"effective" + 0.006*"carers" + 0.006*"oversight" + 0.006*"However" + 0.005*"management" + 0.005*"December" -2024-07-15 10:47:45,466 - topic #2 (0.333): 0.021*"’" + 0.010*"needs" + 0.007*"South" + 0.006*"Tyneside" + 0.005*"5" + 0.005*"oversight" + 0.005*"practice" + 0.005*"well" + 0.005*"2023" + 0.005*"14" -2024-07-15 10:47:45,466 - topic diff=0.807384, rho=1.000000 -2024-07-15 10:47:45,466 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:45.466961', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:46,573 - Inspection date 2022-12-05 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:46,573 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:46,573 - Inspection date 2022-12-05 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:46,574 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:46,574 - Inspection date 2022-12-05 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:46,574 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:46,574 - Inspection date 2022-12-05 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:46,574 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:46,575 - Inspection date 2022-12-05 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:46,575 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:46,575 - Inspection date 2022-12-05 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:46,575 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:48,043 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:48,046 - built Dictionary<1178 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2318 corpus positions) -2024-07-15 10:47:48,046 - Dictionary lifecycle event {'msg': "built Dictionary<1178 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2318 corpus positions)", 'datetime': '2024-07-15T10:47:48.046459', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:48,047 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:48,047 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:48,047 - using serial LDA version on this node -2024-07-15 10:47:48,048 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:48,048 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:48,052 - -8.149 per-word bound, 283.8 perplexity estimate based on a held-out corpus of 1 documents with 2318 words -2024-07-15 10:47:48,053 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:48,054 - topic #0 (0.333): 0.015*"’" + 0.005*"plans" + 0.004*"progress" + 0.004*"including" + 0.004*"2023" + 0.004*"Southampton" + 0.004*"5" + 0.004*"improve" + 0.004*"June" + 0.004*"timely" -2024-07-15 10:47:48,054 - topic #1 (0.333): 0.016*"’" + 0.006*"Southampton" + 0.006*"plans" + 0.005*"including" + 0.005*"5" + 0.005*"improve" + 0.004*"experiences" + 0.004*"needs" + 0.004*"provide" + 0.004*"June" -2024-07-15 10:47:48,054 - topic #2 (0.333): 0.017*"’" + 0.006*"Southampton" + 0.006*"plans" + 0.005*"progress" + 0.005*"improve" + 0.005*"good" + 0.005*"needs" + 0.005*"16" + 0.004*"5" + 0.004*"timely" -2024-07-15 10:47:48,055 - topic diff=0.743886, rho=1.000000 -2024-07-15 10:47:48,055 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:48.055143', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:48,949 - Inspection date 2023-06-05 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:48,949 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:48,950 - Inspection date 2023-06-05 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:48,950 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:48,950 - Inspection date 2023-06-05 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:48,950 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:48,950 - Inspection date 2023-06-05 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:48,951 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:48,951 - Inspection date 2023-06-05 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:48,951 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:48,951 - Inspection date 2023-06-05 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:48,951 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:50,526 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:50,528 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2086 corpus positions) -2024-07-15 10:47:50,528 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2086 corpus positions)", 'datetime': '2024-07-15T10:47:50.528539', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:50,529 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:50,529 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:50,529 - using serial LDA version on this node -2024-07-15 10:47:50,530 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:50,530 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:50,533 - -7.951 per-word bound, 247.5 perplexity estimate based on a held-out corpus of 1 documents with 2086 words -2024-07-15 10:47:50,533 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:50,534 - topic #0 (0.333): 0.014*"’" + 0.007*"planning" + 0.005*"leaders" + 0.005*"practice" + 0.005*"risk" + 0.005*"number" + 0.005*"protection" + 0.004*"good" + 0.004*"within" + 0.004*"always" -2024-07-15 10:47:50,535 - topic #1 (0.333): 0.016*"’" + 0.009*"planning" + 0.009*"quality" + 0.008*"practice" + 0.006*"plans" + 0.006*"leaders" + 0.005*"effective" + 0.005*"good" + 0.005*"need" + 0.005*"Southend" -2024-07-15 10:47:50,535 - topic #2 (0.333): 0.009*"’" + 0.007*"protection" + 0.007*"leaders" + 0.006*"practice" + 0.006*"planning" + 0.006*"number" + 0.005*"quality" + 0.005*"always" + 0.005*"within" + 0.005*"However" -2024-07-15 10:47:50,535 - topic diff=0.778099, rho=1.000000 -2024-07-15 10:47:50,535 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:50.535555', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:52,484 - Inspection date 2019-07-15 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:52,484 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:52,485 - Inspection date 2019-07-15 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:52,485 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:52,485 - Inspection date 2019-07-15 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:52,485 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:52,485 - Inspection date 2019-07-15 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:52,485 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:52,486 - Inspection date 2019-07-15 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:52,486 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:52,486 - Inspection date 2019-07-15 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:52,486 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:53,721 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:53,723 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2218 corpus positions) -2024-07-15 10:47:53,723 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2218 corpus positions)", 'datetime': '2024-07-15T10:47:53.723434', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:53,724 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:53,724 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:53,724 - using serial LDA version on this node -2024-07-15 10:47:53,725 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:53,725 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:53,729 - -8.050 per-word bound, 265.1 perplexity estimate based on a held-out corpus of 1 documents with 2218 words -2024-07-15 10:47:53,729 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:53,730 - topic #0 (0.333): 0.017*"’" + 0.009*"Helens" + 0.008*"St" + 0.008*"well" + 0.007*"needs" + 0.007*"progress" + 0.005*"10" + 0.005*"receive" + 0.005*"risk" + 0.005*"need" -2024-07-15 10:47:53,730 - topic #1 (0.333): 0.010*"’" + 0.008*"St" + 0.006*"Helens" + 0.005*"21" + 0.005*"needs" + 0.005*"good" + 0.004*"risk" + 0.004*"10" + 0.004*"need" + 0.004*"2023" -2024-07-15 10:47:53,730 - topic #2 (0.333): 0.018*"’" + 0.008*"needs" + 0.007*"well" + 0.007*"Helens" + 0.006*"receive" + 0.006*"St" + 0.006*"need" + 0.006*"progress" + 0.006*"good" + 0.006*"21" -2024-07-15 10:47:53,730 - topic diff=0.777023, rho=1.000000 -2024-07-15 10:47:53,731 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:53.731103', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:54,804 - Inspection date 2023-07-10 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:54,804 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:54,804 - Inspection date 2023-07-10 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:54,805 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:54,805 - Inspection date 2023-07-10 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:54,805 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:54,805 - Inspection date 2023-07-10 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:54,805 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:54,806 - Inspection date 2023-07-10 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:54,806 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:54,806 - Inspection date 2023-07-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:54,806 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:56,486 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:56,490 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2334 corpus positions) -2024-07-15 10:47:56,490 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2334 corpus positions)", 'datetime': '2024-07-15T10:47:56.490885', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:56,492 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:56,492 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:56,493 - using serial LDA version on this node -2024-07-15 10:47:56,493 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:56,494 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:56,500 - -7.993 per-word bound, 254.8 perplexity estimate based on a held-out corpus of 1 documents with 2334 words -2024-07-15 10:47:56,500 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:56,502 - topic #0 (0.333): 0.011*"’" + 0.006*"needs" + 0.005*"practice" + 0.004*"progress" + 0.004*"Staffordshire" + 0.004*"ensure" + 0.004*"plans" + 0.004*"quality" + 0.004*"good" + 0.004*"oversight" -2024-07-15 10:47:56,502 - topic #1 (0.333): 0.019*"’" + 0.012*"needs" + 0.006*"oversight" + 0.006*"practice" + 0.006*"quality" + 0.005*"plans" + 0.005*"progress" + 0.005*"Staffordshire" + 0.005*"impact" + 0.005*"ensure" -2024-07-15 10:47:56,502 - topic #2 (0.333): 0.018*"’" + 0.013*"needs" + 0.007*"health" + 0.007*"quality" + 0.006*"progress" + 0.006*"ensure" + 0.006*"Staffordshire" + 0.006*"oversight" + 0.005*"practice" + 0.005*"6" -2024-07-15 10:47:56,503 - topic diff=0.825196, rho=1.000000 -2024-07-15 10:47:56,503 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:56.503278', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:57,429 - Inspection date 2023-11-06 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:57,429 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:57,429 - Inspection date 2023-11-06 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:57,429 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:57,430 - Inspection date 2023-11-06 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:57,430 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:57,430 - Inspection date 2023-11-06 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:57,430 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:57,430 - Inspection date 2023-11-06 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:57,430 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:57,430 - Inspection date 2023-11-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:57,430 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:58,676 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:47:58,678 - built Dictionary<1060 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions) -2024-07-15 10:47:58,679 - Dictionary lifecycle event {'msg': "built Dictionary<1060 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)", 'datetime': '2024-07-15T10:47:58.679132', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:58,680 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:47:58,680 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:47:58,680 - using serial LDA version on this node -2024-07-15 10:47:58,680 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:47:58,681 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:47:58,685 - -7.980 per-word bound, 252.5 perplexity estimate based on a held-out corpus of 1 documents with 2316 words -2024-07-15 10:47:58,685 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:47:58,686 - topic #0 (0.333): 0.012*"’" + 0.007*"well" + 0.007*"practice" + 0.007*"Stockport" + 0.007*"needs" + 0.006*"plans" + 0.005*"strong" + 0.005*"risk" + 0.004*"ensure" + 0.004*"need" -2024-07-15 10:47:58,686 - topic #1 (0.333): 0.009*"’" + 0.007*"Stockport" + 0.007*"needs" + 0.006*"well" + 0.006*"practice" + 0.006*"strong" + 0.005*"risk" + 0.005*"leaders" + 0.004*"range" + 0.004*"ensure" -2024-07-15 10:47:58,686 - topic #2 (0.333): 0.011*"’" + 0.010*"well" + 0.008*"practice" + 0.006*"strong" + 0.005*"Stockport" + 0.005*"plans" + 0.005*"quality" + 0.005*"ensure" + 0.005*"1" + 0.005*"needs" -2024-07-15 10:47:58,687 - topic diff=0.792979, rho=1.000000 -2024-07-15 10:47:58,687 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:47:58.687229', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:47:59,649 - Inspection date 2022-03-28 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:47:59,649 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:59,649 - Inspection date 2022-03-28 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:47:59,649 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:59,649 - Inspection date 2022-03-28 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:47:59,650 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:59,650 - Inspection date 2022-03-28 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:47:59,650 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:59,650 - Inspection date 2022-03-28 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:47:59,650 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:47:59,650 - Inspection date 2022-03-28 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:47:59,650 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:01,421 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:01,424 - built Dictionary<1044 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2269 corpus positions) -2024-07-15 10:48:01,424 - Dictionary lifecycle event {'msg': "built Dictionary<1044 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2269 corpus positions)", 'datetime': '2024-07-15T10:48:01.424215', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:01,425 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:01,425 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:01,425 - using serial LDA version on this node -2024-07-15 10:48:01,425 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:01,426 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:01,429 - -7.967 per-word bound, 250.1 perplexity estimate based on a held-out corpus of 1 documents with 2269 words -2024-07-15 10:48:01,429 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:01,431 - topic #0 (0.333): 0.019*"’" + 0.010*"leaders" + 0.007*"needs" + 0.006*"good" + 0.006*"plans" + 0.006*"on-Tees" + 0.005*"quality" + 0.005*"well" + 0.005*"17" + 0.005*"senior" -2024-07-15 10:48:01,431 - topic #1 (0.333): 0.014*"’" + 0.008*"plans" + 0.007*"well" + 0.007*"leaders" + 0.006*"on-Tees" + 0.006*"Stockton" + 0.005*"good" + 0.005*"quality" + 0.004*"needs" + 0.004*"17" -2024-07-15 10:48:01,431 - topic #2 (0.333): 0.023*"’" + 0.010*"plans" + 0.008*"leaders" + 0.007*"needs" + 0.007*"well" + 0.007*"Stockton" + 0.006*"quality" + 0.006*"senior" + 0.006*"on-Tees" + 0.005*"good" -2024-07-15 10:48:01,431 - topic diff=0.776190, rho=1.000000 -2024-07-15 10:48:01,432 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:01.432099', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:02,393 - Inspection date 2023-03-06 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:02,393 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:02,394 - Inspection date 2023-03-06 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:02,394 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:02,394 - Inspection date 2023-03-06 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:02,394 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:02,394 - Inspection date 2023-03-06 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:02,394 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:02,395 - Inspection date 2023-03-06 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:02,395 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:02,395 - Inspection date 2023-03-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:02,395 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:03,669 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:03,671 - built Dictionary<986 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2165 corpus positions) -2024-07-15 10:48:03,671 - Dictionary lifecycle event {'msg': "built Dictionary<986 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2165 corpus positions)", 'datetime': '2024-07-15T10:48:03.671780', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:03,672 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:03,672 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:03,673 - using serial LDA version on this node -2024-07-15 10:48:03,673 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:03,673 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:03,676 - -7.903 per-word bound, 239.3 perplexity estimate based on a held-out corpus of 1 documents with 2165 words -2024-07-15 10:48:03,676 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:03,678 - topic #0 (0.333): 0.017*"’" + 0.009*"needs" + 0.008*"well" + 0.008*"Stoke" + 0.008*"However" + 0.006*"protection" + 0.006*"plans" + 0.006*"on-Trent" + 0.006*"ensure" + 0.005*"practice" -2024-07-15 10:48:03,678 - topic #1 (0.333): 0.017*"’" + 0.007*"on-Trent" + 0.007*"needs" + 0.007*"Stoke" + 0.007*"plans" + 0.006*"progress" + 0.006*"well" + 0.006*"protection" + 0.005*"However" + 0.005*"ensure" -2024-07-15 10:48:03,678 - topic #2 (0.333): 0.017*"’" + 0.009*"needs" + 0.007*"on-Trent" + 0.006*"plans" + 0.006*"well" + 0.005*"However" + 0.005*"quality" + 0.005*"ensure" + 0.004*"Stoke" + 0.004*"progress" -2024-07-15 10:48:03,678 - topic diff=0.780153, rho=1.000000 -2024-07-15 10:48:03,678 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:03.678819', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:04,546 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:04,546 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:04,547 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:04,547 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:04,547 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:04,547 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:04,547 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:04,547 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:04,547 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:04,548 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:04,548 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:04,548 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:06,170 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:06,174 - built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2286 corpus positions) -2024-07-15 10:48:06,174 - Dictionary lifecycle event {'msg': "built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2286 corpus positions)", 'datetime': '2024-07-15T10:48:06.174507', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:06,176 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:06,176 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:06,177 - using serial LDA version on this node -2024-07-15 10:48:06,177 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:06,177 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:06,184 - -8.180 per-word bound, 290.0 perplexity estimate based on a held-out corpus of 1 documents with 2286 words -2024-07-15 10:48:06,184 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:06,186 - topic #0 (0.333): 0.012*"’" + 0.006*"progress" + 0.005*"well" + 0.005*"effective" + 0.004*"good" + 0.004*"leaders" + 0.004*"practice" + 0.003*"ensure" + 0.003*"Senior" + 0.003*"Suffolk" -2024-07-15 10:48:06,186 - topic #1 (0.333): 0.014*"’" + 0.006*"well" + 0.006*"progress" + 0.005*"leaders" + 0.005*"good" + 0.005*"ensure" + 0.004*"needs" + 0.004*"effective" + 0.004*"high" + 0.004*"practice" -2024-07-15 10:48:06,187 - topic #2 (0.333): 0.013*"’" + 0.007*"well" + 0.006*"progress" + 0.006*"effective" + 0.005*"practice" + 0.005*"ensure" + 0.005*"good" + 0.004*"leaders" + 0.004*"need" + 0.004*"carers" -2024-07-15 10:48:06,187 - topic diff=0.726721, rho=1.000000 -2024-07-15 10:48:06,187 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:06.187717', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:07,594 - Got stderr: Jul 15, 2024 10:48:07 AM org.apache.pdfbox.pdmodel.font.PDTrueTypeFont +2024-07-25 12:38:42,561 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:38:42,565 - built Dictionary<1216 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2696 corpus positions) +2024-07-25 12:38:42,574 - Dictionary lifecycle event {'msg': "built Dictionary<1216 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2696 corpus positions)", 'datetime': '2024-07-25T12:38:42.567634', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:38:42,576 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:38:42,577 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:38:42,577 - using serial LDA version on this node +2024-07-25 12:38:42,577 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:38:42,578 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:38:42,585 - -8.107 per-word bound, 275.7 perplexity estimate based on a held-out corpus of 1 documents with 2696 words +2024-07-25 12:38:42,585 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:38:42,587 - topic #0 (0.333): 0.017*"’" + 0.007*"needs" + 0.006*"within" + 0.006*"Barnsley" + 0.005*"practice" + 0.005*"leaders" + 0.004*"understand" + 0.004*"family" + 0.004*"plans" + 0.004*"15" +2024-07-25 12:38:42,588 - topic #1 (0.333): 0.020*"’" + 0.009*"needs" + 0.008*"leaders" + 0.006*"within" + 0.006*"Barnsley" + 0.005*"practice" + 0.005*"11" + 0.004*"response" + 0.004*"senior" + 0.004*"plans" +2024-07-25 12:38:42,588 - topic #2 (0.333): 0.019*"’" + 0.008*"leaders" + 0.008*"needs" + 0.007*"practice" + 0.006*"within" + 0.005*"Barnsley" + 0.005*"plans" + 0.005*"senior" + 0.005*"response" + 0.004*"quality" +2024-07-25 12:38:42,588 - topic diff=0.798849, rho=1.000000 +2024-07-25 12:38:42,589 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:38:42.588999', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:38:42,592 - Failed to import jpype dependencies. Fallback to subprocess. +2024-07-25 12:38:42,592 - No module named 'jpype' +2024-07-25 12:38:45,348 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:38:45,349 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:45,349 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:38:45,350 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:45,350 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:38:45,350 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:45,351 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:38:45,351 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:45,351 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:38:45,351 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:45,352 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:38:45,352 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:46,901 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:38:46,904 - built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2085 corpus positions) +2024-07-25 12:38:46,904 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2085 corpus positions)", 'datetime': '2024-07-25T12:38:46.904881', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:38:46,905 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:38:46,906 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:38:46,906 - using serial LDA version on this node +2024-07-25 12:38:46,906 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:38:46,906 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:38:46,910 - -8.024 per-word bound, 260.2 perplexity estimate based on a held-out corpus of 1 documents with 2085 words +2024-07-25 12:38:46,910 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:38:46,911 - topic #0 (0.333): 0.019*"’" + 0.008*"well" + 0.006*"needs" + 0.006*"leaders" + 0.006*"effective" + 0.006*"clear" + 0.005*"practice" + 0.005*"Somerset" + 0.005*"protection" + 0.005*"plans" +2024-07-25 12:38:46,911 - topic #1 (0.333): 0.015*"’" + 0.009*"well" + 0.006*"plans" + 0.006*"needs" + 0.006*"practice" + 0.005*"effective" + 0.005*"4" + 0.004*"East" + 0.004*"North" + 0.004*"28" +2024-07-25 12:38:46,911 - topic #2 (0.333): 0.018*"’" + 0.010*"well" + 0.006*"needs" + 0.006*"practice" + 0.005*"plans" + 0.005*"Bath" + 0.005*"East" + 0.004*"impact" + 0.004*"leaders" + 0.004*"Somerset" +2024-07-25 12:38:46,912 - topic diff=0.747845, rho=1.000000 +2024-07-25 12:38:46,912 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:38:46.912210', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:38:48,149 - Inspection date 2022-02-28 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:38:48,149 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:48,150 - Inspection date 2022-02-28 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:38:48,150 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:48,150 - Inspection date 2022-02-28 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:38:48,150 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:48,151 - Inspection date 2022-02-28 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:38:48,151 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:48,152 - Inspection date 2022-02-28 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:38:48,152 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:48,152 - Inspection date 2022-02-28 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:38:48,152 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:49,970 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:38:49,973 - built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2585 corpus positions) +2024-07-25 12:38:49,973 - Dictionary lifecycle event {'msg': "built Dictionary<1202 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2585 corpus positions)", 'datetime': '2024-07-25T12:38:49.973375', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:38:49,974 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:38:49,974 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:38:49,974 - using serial LDA version on this node +2024-07-25 12:38:49,975 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:38:49,975 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:38:49,979 - -8.114 per-word bound, 277.0 perplexity estimate based on a held-out corpus of 1 documents with 2585 words +2024-07-25 12:38:49,979 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:38:49,980 - topic #0 (0.333): 0.016*"’" + 0.008*"needs" + 0.007*"ensure" + 0.005*"plans" + 0.005*"supported" + 0.005*"family" + 0.005*"good" + 0.005*"well" + 0.004*"Bedford" + 0.004*"progress" +2024-07-25 12:38:49,981 - topic #1 (0.333): 0.018*"’" + 0.005*"Bedford" + 0.005*"well" + 0.005*"ensure" + 0.004*"needs" + 0.004*"Borough" + 0.004*"family" + 0.004*"relationships" + 0.004*"supported" + 0.004*"plans" +2024-07-25 12:38:49,981 - topic #2 (0.333): 0.021*"’" + 0.008*"needs" + 0.007*"well" + 0.006*"ensure" + 0.006*"good" + 0.006*"plans" + 0.005*"education" + 0.005*"Bedford" + 0.005*"progress" + 0.005*"supported" +2024-07-25 12:38:49,981 - topic diff=0.789142, rho=1.000000 +2024-07-25 12:38:49,981 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:38:49.981639', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:38:51,036 - Inspection date 2021-11-15 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:38:51,037 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:51,037 - Inspection date 2021-11-15 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:38:51,037 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:51,037 - Inspection date 2021-11-15 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:38:51,037 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:51,038 - Inspection date 2021-11-15 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:38:51,038 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:51,038 - Inspection date 2021-11-15 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:38:51,038 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:51,038 - Inspection date 2021-11-15 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:38:51,038 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:52,609 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:38:52,613 - built Dictionary<1065 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2378 corpus positions) +2024-07-25 12:38:52,613 - Dictionary lifecycle event {'msg': "built Dictionary<1065 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2378 corpus positions)", 'datetime': '2024-07-25T12:38:52.613479', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:38:52,615 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:38:52,615 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:38:52,615 - using serial LDA version on this node +2024-07-25 12:38:52,616 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:38:52,616 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:38:52,622 - -7.970 per-word bound, 250.8 perplexity estimate based on a held-out corpus of 1 documents with 2378 words +2024-07-25 12:38:52,622 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:38:52,624 - topic #0 (0.333): 0.013*"’" + 0.009*"needs" + 0.006*"effective" + 0.006*"well" + 0.005*"plans" + 0.005*"trust" + 0.005*"timely" + 0.004*"progress" + 0.004*"risk" + 0.004*"Birmingham" +2024-07-25 12:38:52,624 - topic #1 (0.333): 0.018*"’" + 0.011*"needs" + 0.007*"plans" + 0.007*"effective" + 0.007*"well" + 0.007*"Birmingham" + 0.006*"trust" + 0.006*"appropriate" + 0.006*"progress" + 0.005*"risk" +2024-07-25 12:38:52,625 - topic #2 (0.333): 0.013*"’" + 0.009*"needs" + 0.006*"well" + 0.006*"3" + 0.006*"progress" + 0.006*"effective" + 0.005*"Birmingham" + 0.005*"appropriate" + 0.005*"trust" + 0.005*"20" +2024-07-25 12:38:52,625 - topic diff=0.797099, rho=1.000000 +2024-07-25 12:38:52,625 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:38:52.625313', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:38:53,678 - Inspection date 2023-02-20 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:38:53,679 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:53,679 - Inspection date 2023-02-20 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:38:53,679 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:53,679 - Inspection date 2023-02-20 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:38:53,679 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:53,680 - Inspection date 2023-02-20 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:38:53,680 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:53,680 - Inspection date 2023-02-20 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:38:53,680 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:53,680 - Inspection date 2023-02-20 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:38:53,680 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:55,769 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:38:55,771 - built Dictionary<1055 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2353 corpus positions) +2024-07-25 12:38:55,771 - Dictionary lifecycle event {'msg': "built Dictionary<1055 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2353 corpus positions)", 'datetime': '2024-07-25T12:38:55.771924', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:38:55,772 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:38:55,773 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:38:55,773 - using serial LDA version on this node +2024-07-25 12:38:55,773 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:38:55,773 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:38:55,777 - -7.962 per-word bound, 249.3 perplexity estimate based on a held-out corpus of 1 documents with 2353 words +2024-07-25 12:38:55,777 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:38:55,779 - topic #0 (0.333): 0.010*"’" + 0.007*"needs" + 0.006*"Darwen" + 0.006*"practice" + 0.006*"quality" + 0.006*"impact" + 0.005*"Blackburn" + 0.005*"planning" + 0.005*"well" + 0.005*"plans" +2024-07-25 12:38:55,779 - topic #1 (0.333): 0.013*"’" + 0.007*"quality" + 0.006*"impact" + 0.006*"well" + 0.006*"Blackburn" + 0.006*"needs" + 0.006*"practice" + 0.006*"Darwen" + 0.005*"result" + 0.005*"need" +2024-07-25 12:38:55,779 - topic #2 (0.333): 0.017*"’" + 0.009*"needs" + 0.009*"practice" + 0.008*"Blackburn" + 0.007*"quality" + 0.007*"Darwen" + 0.006*"well" + 0.006*"impact" + 0.005*"February" + 0.005*"plans" +2024-07-25 12:38:55,779 - topic diff=0.817257, rho=1.000000 +2024-07-25 12:38:55,779 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:38:55.779759', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:38:56,641 - Inspection date 2022-01-24 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:38:56,642 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:56,642 - Inspection date 2022-01-24 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:38:56,642 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:56,642 - Inspection date 2022-01-24 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:38:56,642 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:56,643 - Inspection date 2022-01-24 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:38:56,643 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:56,643 - Inspection date 2022-01-24 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:38:56,643 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:56,643 - Inspection date 2022-01-24 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:38:56,643 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:58,443 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:38:58,445 - built Dictionary<1037 unique tokens: ['0', '0161', '030', '0300', '1']...> from 1 documents (total 2392 corpus positions) +2024-07-25 12:38:58,445 - Dictionary lifecycle event {'msg': "built Dictionary<1037 unique tokens: ['0', '0161', '030', '0300', '1']...> from 1 documents (total 2392 corpus positions)", 'datetime': '2024-07-25T12:38:58.445759', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:38:58,446 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:38:58,446 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:38:58,447 - using serial LDA version on this node +2024-07-25 12:38:58,447 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:38:58,447 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:38:58,451 - -7.928 per-word bound, 243.6 perplexity estimate based on a held-out corpus of 1 documents with 2392 words +2024-07-25 12:38:58,451 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:38:58,452 - topic #0 (0.333): 0.015*"’" + 0.011*"needs" + 0.009*"well" + 0.009*"Blackpool" + 0.006*"effective" + 0.006*"16" + 0.005*"experiences" + 0.005*"supported" + 0.005*"understand" + 0.005*"plans" +2024-07-25 12:38:58,452 - topic #1 (0.333): 0.015*"’" + 0.009*"needs" + 0.009*"well" + 0.007*"Blackpool" + 0.005*"effective" + 0.005*"practice" + 0.004*"experiences" + 0.004*"2022" + 0.004*"plans" + 0.004*"carers" +2024-07-25 12:38:58,453 - topic #2 (0.333): 0.020*"’" + 0.010*"needs" + 0.009*"well" + 0.006*"Blackpool" + 0.006*"effective" + 0.005*"plans" + 0.005*"practice" + 0.005*"response" + 0.005*"supported" + 0.005*"quality" +2024-07-25 12:38:58,453 - topic diff=0.831384, rho=1.000000 +2024-07-25 12:38:58,453 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:38:58.453340', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:38:59,345 - Inspection date 2022-12-05 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:38:59,346 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:59,346 - Inspection date 2022-12-05 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:38:59,346 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:59,346 - Inspection date 2022-12-05 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:38:59,346 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:59,347 - Inspection date 2022-12-05 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:38:59,347 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:59,347 - Inspection date 2022-12-05 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:38:59,347 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:38:59,347 - Inspection date 2022-12-05 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:38:59,347 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:01,041 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:01,043 - built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2055 corpus positions) +2024-07-25 12:39:01,043 - Dictionary lifecycle event {'msg': "built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2055 corpus positions)", 'datetime': '2024-07-25T12:39:01.043454', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:01,044 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:01,044 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:01,044 - using serial LDA version on this node +2024-07-25 12:39:01,045 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:01,045 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:01,048 - -7.912 per-word bound, 240.8 perplexity estimate based on a held-out corpus of 1 documents with 2055 words +2024-07-25 12:39:01,048 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:01,050 - topic #0 (0.333): 0.016*"’" + 0.008*"needs" + 0.007*"plans" + 0.007*"well" + 0.006*"Bolton" + 0.005*"supported" + 0.005*"11" + 0.005*"strong" + 0.005*"effective" + 0.005*"planning" +2024-07-25 12:39:01,050 - topic #1 (0.333): 0.018*"’" + 0.010*"needs" + 0.010*"Bolton" + 0.008*"well" + 0.008*"plans" + 0.006*"supported" + 0.005*"effective" + 0.005*"planning" + 0.005*"progress" + 0.005*"need" +2024-07-25 12:39:01,050 - topic #2 (0.333): 0.022*"’" + 0.009*"needs" + 0.008*"well" + 0.007*"Bolton" + 0.007*"plans" + 0.006*"need" + 0.006*"planning" + 0.005*"response" + 0.005*"15" + 0.005*"11" +2024-07-25 12:39:01,050 - topic diff=0.774730, rho=1.000000 +2024-07-25 12:39:01,050 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:01.050691', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:02,064 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:02,065 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:02,065 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:02,065 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:02,065 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:02,066 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:02,066 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:02,066 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:02,066 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:02,066 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:02,067 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:02,067 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:03,571 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:03,573 - built Dictionary<1035 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2004 corpus positions) +2024-07-25 12:39:03,573 - Dictionary lifecycle event {'msg': "built Dictionary<1035 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2004 corpus positions)", 'datetime': '2024-07-25T12:39:03.573647', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:03,574 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:03,574 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:03,575 - using serial LDA version on this node +2024-07-25 12:39:03,575 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:03,575 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:03,579 - -8.028 per-word bound, 261.0 perplexity estimate based on a held-out corpus of 1 documents with 2004 words +2024-07-25 12:39:03,579 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:03,580 - topic #0 (0.333): 0.020*"’" + 0.007*"practice" + 0.007*"quality" + 0.005*"6" + 0.005*"Poole" + 0.005*"progress" + 0.005*"Bournemouth" + 0.005*"risk" + 0.004*"time" + 0.004*"2021" +2024-07-25 12:39:03,580 - topic #1 (0.333): 0.016*"’" + 0.006*"quality" + 0.005*"progress" + 0.005*"Christchurch" + 0.005*"risk" + 0.005*"17" + 0.005*"time" + 0.005*"impact" + 0.004*"practice" + 0.004*"right" +2024-07-25 12:39:03,580 - topic #2 (0.333): 0.016*"’" + 0.005*"practice" + 0.005*"quality" + 0.005*"Christchurch" + 0.005*"17" + 0.004*"progress" + 0.004*"Poole" + 0.004*"impact" + 0.004*"However" + 0.004*"many" +2024-07-25 12:39:03,581 - topic diff=0.751182, rho=1.000000 +2024-07-25 12:39:03,581 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:03.581186', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:07,152 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:07,153 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:07,153 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:07,153 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:07,153 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:07,153 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:07,154 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:07,154 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:07,154 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:07,154 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:07,154 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:07,154 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:08,574 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:08,576 - built Dictionary<900 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1846 corpus positions) +2024-07-25 12:39:08,576 - Dictionary lifecycle event {'msg': "built Dictionary<900 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1846 corpus positions)", 'datetime': '2024-07-25T12:39:08.576955', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:08,577 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:08,577 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:08,578 - using serial LDA version on this node +2024-07-25 12:39:08,578 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:08,578 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:08,581 - -7.857 per-word bound, 231.8 perplexity estimate based on a held-out corpus of 1 documents with 1846 words +2024-07-25 12:39:08,581 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:08,583 - topic #0 (0.333): 0.013*"’" + 0.006*"Bracknell" + 0.005*"quality" + 0.005*"progress" + 0.005*"carers" + 0.005*"needs" + 0.005*"Forest" + 0.005*"plans" + 0.005*"risk" + 0.004*"good" +2024-07-25 12:39:08,583 - topic #1 (0.333): 0.020*"’" + 0.009*"Forest" + 0.008*"risk" + 0.007*"needs" + 0.007*"good" + 0.007*"Bracknell" + 0.006*"well" + 0.006*"effective" + 0.006*"quality" + 0.006*"progress" +2024-07-25 12:39:08,583 - topic #2 (0.333): 0.015*"’" + 0.007*"needs" + 0.007*"Bracknell" + 0.006*"quality" + 0.006*"effective" + 0.006*"good" + 0.006*"provided" + 0.005*"carers" + 0.005*"need" + 0.005*"risk" +2024-07-25 12:39:08,583 - topic diff=0.769756, rho=1.000000 +2024-07-25 12:39:08,583 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:08.583662', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:09,696 - Inspection date 2022-06-13 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:09,696 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:09,696 - Inspection date 2022-06-13 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:09,696 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:09,696 - Inspection date 2022-06-13 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:09,696 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:09,697 - Inspection date 2022-06-13 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:09,697 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:09,697 - Inspection date 2022-06-13 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:09,697 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:09,697 - Inspection date 2022-06-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:09,697 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:11,235 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:11,237 - built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2249 corpus positions) +2024-07-25 12:39:11,238 - Dictionary lifecycle event {'msg': "built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2249 corpus positions)", 'datetime': '2024-07-25T12:39:11.238134', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:11,239 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:11,239 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:11,239 - using serial LDA version on this node +2024-07-25 12:39:11,240 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:11,240 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:11,243 - -8.093 per-word bound, 273.0 perplexity estimate based on a held-out corpus of 1 documents with 2249 words +2024-07-25 12:39:11,244 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:11,245 - topic #0 (0.333): 0.019*"’" + 0.007*"well" + 0.007*"practice" + 0.006*"Hove" + 0.006*"needs" + 0.006*"Brighton" + 0.005*"experiences" + 0.005*"15" + 0.005*"receive" + 0.005*"progress" +2024-07-25 12:39:11,245 - topic #1 (0.333): 0.013*"’" + 0.007*"Hove" + 0.006*"relationships" + 0.005*"well" + 0.005*"needs" + 0.005*"practice" + 0.004*"experiences" + 0.004*"progress" + 0.004*"need" + 0.004*"family" +2024-07-25 12:39:11,245 - topic #2 (0.333): 0.016*"’" + 0.009*"well" + 0.008*"needs" + 0.008*"Brighton" + 0.007*"Hove" + 0.006*"practice" + 0.006*"progress" + 0.005*"experiences" + 0.005*"relationships" + 0.005*"family" +2024-07-25 12:39:11,245 - topic diff=0.746763, rho=1.000000 +2024-07-25 12:39:11,246 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:11.246104', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:12,514 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:12,516 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:12,516 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:12,516 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:12,517 - Inspection date None / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:12,517 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:12,517 - Inspection date None / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:12,517 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:12,517 - Inspection date None / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:12,518 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:12,518 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:12,518 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:14,241 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:14,245 - built Dictionary<1151 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2647 corpus positions) +2024-07-25 12:39:14,245 - Dictionary lifecycle event {'msg': "built Dictionary<1151 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2647 corpus positions)", 'datetime': '2024-07-25T12:39:14.245596', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:14,247 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:14,247 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:14,248 - using serial LDA version on this node +2024-07-25 12:39:14,248 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:14,248 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:14,255 - -8.030 per-word bound, 261.4 perplexity estimate based on a held-out corpus of 1 documents with 2647 words +2024-07-25 12:39:14,255 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:14,258 - topic #0 (0.333): 0.016*"’" + 0.008*"good" + 0.008*"Bristol" + 0.007*"well" + 0.006*"needs" + 0.006*"health" + 0.005*"progress" + 0.005*"receive" + 0.004*"leaders" + 0.004*"plans" +2024-07-25 12:39:14,258 - topic #1 (0.333): 0.023*"’" + 0.010*"well" + 0.009*"needs" + 0.008*"Bristol" + 0.007*"good" + 0.005*"health" + 0.005*"leaders" + 0.005*"need" + 0.005*"risk" + 0.005*"16" +2024-07-25 12:39:14,258 - topic #2 (0.333): 0.017*"’" + 0.008*"well" + 0.008*"good" + 0.007*"Bristol" + 0.007*"needs" + 0.005*"progress" + 0.005*"plans" + 0.005*"27" + 0.004*"need" + 0.004*"16" +2024-07-25 12:39:14,259 - topic diff=0.820781, rho=1.000000 +2024-07-25 12:39:14,259 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:14.259357', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:15,262 - Inspection date 2023-01-16 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:15,262 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:15,262 - Inspection date 2023-01-16 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:15,262 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:15,263 - Inspection date 2023-01-16 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:15,263 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:15,263 - Inspection date 2023-01-16 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:15,263 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:15,263 - Inspection date 2023-01-16 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:15,263 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:15,264 - Inspection date 2023-01-16 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:15,264 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:17,464 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:17,466 - built Dictionary<1263 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2404 corpus positions) +2024-07-25 12:39:17,466 - Dictionary lifecycle event {'msg': "built Dictionary<1263 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2404 corpus positions)", 'datetime': '2024-07-25T12:39:17.466858', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:17,468 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:17,468 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:17,468 - using serial LDA version on this node +2024-07-25 12:39:17,468 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:17,469 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:17,473 - -8.238 per-word bound, 302.0 perplexity estimate based on a held-out corpus of 1 documents with 2404 words +2024-07-25 12:39:17,473 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:17,474 - topic #0 (0.333): 0.015*"’" + 0.005*"number" + 0.005*"6" + 0.004*"teams" + 0.004*"17" + 0.004*"needs" + 0.004*"practice" + 0.004*"Buckinghamshire" + 0.004*"plans" + 0.004*"protection" +2024-07-25 12:39:17,474 - topic #1 (0.333): 0.012*"’" + 0.005*"number" + 0.004*"plans" + 0.004*"17" + 0.004*"Buckinghamshire" + 0.004*"many" + 0.004*"well" + 0.004*"2021" + 0.003*"December" + 0.003*"needs" +2024-07-25 12:39:17,475 - topic #2 (0.333): 0.014*"’" + 0.006*"plans" + 0.005*"Buckinghamshire" + 0.005*"protection" + 0.005*"17" + 0.005*"many" + 0.004*"December" + 0.004*"number" + 0.004*"6" + 0.004*"2021" +2024-07-25 12:39:17,475 - topic diff=0.721681, rho=1.000000 +2024-07-25 12:39:17,475 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:17.475286', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:18,947 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:18,951 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:18,951 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:18,951 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:18,952 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:18,952 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:18,952 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:18,952 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:18,953 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:18,953 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:18,953 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:18,953 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:20,660 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:20,662 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2427 corpus positions) +2024-07-25 12:39:20,662 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2427 corpus positions)", 'datetime': '2024-07-25T12:39:20.662915', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:20,664 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:20,664 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:20,664 - using serial LDA version on this node +2024-07-25 12:39:20,664 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:20,664 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:20,668 - -7.974 per-word bound, 251.4 perplexity estimate based on a held-out corpus of 1 documents with 2427 words +2024-07-25 12:39:20,668 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:20,669 - topic #0 (0.333): 0.011*"’" + 0.007*"2021" + 0.006*"protection" + 0.006*"impact" + 0.006*"needs" + 0.006*"need" + 0.005*"team" + 0.005*"practice" + 0.005*"always" + 0.005*"risk" +2024-07-25 12:39:20,670 - topic #1 (0.333): 0.012*"’" + 0.007*"2021" + 0.007*"needs" + 0.007*"protection" + 0.006*"practice" + 0.006*"team" + 0.006*"quality" + 0.005*"Bury" + 0.005*"need" + 0.005*"risk" +2024-07-25 12:39:20,670 - topic #2 (0.333): 0.011*"’" + 0.006*"protection" + 0.006*"needs" + 0.005*"team" + 0.005*"practice" + 0.004*"2021" + 0.004*"impact" + 0.004*"delay" + 0.004*"new" + 0.004*"need" +2024-07-25 12:39:20,670 - topic diff=0.805995, rho=1.000000 +2024-07-25 12:39:20,670 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:20.670418', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:21,716 - Inspection date 2021-10-25 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:21,717 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:21,717 - Inspection date 2021-10-25 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:21,717 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:21,717 - Inspection date 2021-10-25 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:21,718 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:21,718 - Inspection date 2021-10-25 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:21,718 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:21,718 - Inspection date 2021-10-25 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:21,718 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:21,718 - Inspection date 2021-10-25 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:21,719 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:23,073 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:23,076 - built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2389 corpus positions) +2024-07-25 12:39:23,076 - Dictionary lifecycle event {'msg': "built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2389 corpus positions)", 'datetime': '2024-07-25T12:39:23.076183', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:23,077 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:23,077 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:23,077 - using serial LDA version on this node +2024-07-25 12:39:23,078 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:23,078 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:23,081 - -8.027 per-word bound, 260.8 perplexity estimate based on a held-out corpus of 1 documents with 2389 words +2024-07-25 12:39:23,081 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:23,083 - topic #0 (0.333): 0.019*"’" + 0.008*"Calderdale" + 0.008*"needs" + 0.006*"plans" + 0.006*"ensure" + 0.005*"parents" + 0.005*"well" + 0.005*"information" + 0.005*"need" + 0.004*"progress" +2024-07-25 12:39:23,083 - topic #1 (0.333): 0.020*"’" + 0.010*"Calderdale" + 0.010*"needs" + 0.007*"well" + 0.006*"plans" + 0.006*"progress" + 0.005*"risk" + 0.005*"experiences" + 0.005*"ensure" + 0.004*"23" +2024-07-25 12:39:23,083 - topic #2 (0.333): 0.021*"’" + 0.011*"needs" + 0.006*"Calderdale" + 0.006*"well" + 0.006*"progress" + 0.006*"ensure" + 0.005*"plans" + 0.005*"risk" + 0.005*"19" + 0.004*"parents" +2024-07-25 12:39:23,083 - topic diff=0.779186, rho=1.000000 +2024-07-25 12:39:23,084 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:23.084043', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:24,381 - Inspection date 2024-02-19 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:24,381 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:24,381 - Inspection date 2024-02-19 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:24,382 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:24,382 - Inspection date 2024-02-19 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:24,382 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:24,382 - Inspection date 2024-02-19 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:24,383 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:24,383 - Inspection date 2024-02-19 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:24,383 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:24,383 - Inspection date 2024-02-19 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:24,384 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:26,220 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:26,222 - built Dictionary<1082 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2339 corpus positions) +2024-07-25 12:39:26,222 - Dictionary lifecycle event {'msg': "built Dictionary<1082 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2339 corpus positions)", 'datetime': '2024-07-25T12:39:26.222549', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:26,223 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:26,224 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:26,224 - using serial LDA version on this node +2024-07-25 12:39:26,224 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:26,224 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:26,228 - -8.004 per-word bound, 256.6 perplexity estimate based on a held-out corpus of 1 documents with 2339 words +2024-07-25 12:39:26,228 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:26,230 - topic #0 (0.333): 0.022*"’" + 0.008*"needs" + 0.007*"Cambridgeshire" + 0.007*"leaders" + 0.006*"good" + 0.006*"practice" + 0.005*"well" + 0.005*"4" + 0.005*"However" + 0.005*"effective" +2024-07-25 12:39:26,230 - topic #1 (0.333): 0.012*"’" + 0.006*"needs" + 0.005*"Cambridgeshire" + 0.005*"4" + 0.004*"leaders" + 0.004*"good" + 0.004*"well" + 0.004*"leadership" + 0.004*"2024" + 0.004*"timely" +2024-07-25 12:39:26,230 - topic #2 (0.333): 0.013*"’" + 0.007*"leaders" + 0.006*"Cambridgeshire" + 0.005*"needs" + 0.005*"effective" + 0.005*"good" + 0.005*"leadership" + 0.004*"well" + 0.004*"2024" + 0.004*"15" +2024-07-25 12:39:26,230 - topic diff=0.800708, rho=1.000000 +2024-07-25 12:39:26,230 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:26.230879', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:27,414 - Inspection date 2024-03-04 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:27,414 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:27,415 - Inspection date 2024-03-04 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:27,415 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:27,415 - Inspection date 2024-03-04 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:27,415 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:27,416 - Inspection date 2024-03-04 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:27,416 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:27,416 - Inspection date 2024-03-04 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:27,416 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:27,417 - Inspection date 2024-03-04 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:27,417 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:29,106 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:29,110 - built Dictionary<1030 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions) +2024-07-25 12:39:29,110 - Dictionary lifecycle event {'msg': "built Dictionary<1030 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)", 'datetime': '2024-07-25T12:39:29.110644', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:29,111 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:29,112 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:29,112 - using serial LDA version on this node +2024-07-25 12:39:29,112 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:29,112 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:29,116 - -7.964 per-word bound, 249.6 perplexity estimate based on a held-out corpus of 1 documents with 2199 words +2024-07-25 12:39:29,116 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:29,118 - topic #0 (0.333): 0.015*"’" + 0.008*"well" + 0.007*"needs" + 0.007*"need" + 0.006*"carers" + 0.005*"plans" + 0.005*"Bedfordshire" + 0.005*"progress" + 0.005*"good" + 0.004*"effective" +2024-07-25 12:39:29,118 - topic #1 (0.333): 0.018*"’" + 0.011*"well" + 0.007*"needs" + 0.007*"good" + 0.006*"progress" + 0.006*"plans" + 0.006*"need" + 0.006*"carers" + 0.006*"information" + 0.005*"Leaders" +2024-07-25 12:39:29,118 - topic #2 (0.333): 0.015*"’" + 0.007*"well" + 0.007*"needs" + 0.006*"good" + 0.006*"carers" + 0.005*"need" + 0.005*"Central" + 0.005*"effective" + 0.005*"plans" + 0.004*"supported" +2024-07-25 12:39:29,118 - topic diff=0.786066, rho=1.000000 +2024-07-25 12:39:29,119 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:29.119080', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:30,152 - Inspection date 2022-01-17 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:30,152 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:30,152 - Inspection date 2022-01-17 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:30,152 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:30,153 - Inspection date 2022-01-17 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:30,153 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:30,153 - Inspection date 2022-01-17 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:30,153 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:30,153 - Inspection date 2022-01-17 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:30,153 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:30,154 - Inspection date 2022-01-17 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:30,154 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:31,684 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:31,686 - built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2272 corpus positions) +2024-07-25 12:39:31,687 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2272 corpus positions)", 'datetime': '2024-07-25T12:39:31.687017', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:31,688 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:31,688 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:31,688 - using serial LDA version on this node +2024-07-25 12:39:31,688 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:31,688 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:31,692 - -7.974 per-word bound, 251.4 perplexity estimate based on a held-out corpus of 1 documents with 2272 words +2024-07-25 12:39:31,692 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:31,693 - topic #0 (0.333): 0.014*"’" + 0.007*"needs" + 0.007*"2024" + 0.007*"plans" + 0.006*"well" + 0.006*"practice" + 0.005*"quality" + 0.005*"East" + 0.005*"Cheshire" + 0.005*"effective" +2024-07-25 12:39:31,694 - topic #1 (0.333): 0.014*"’" + 0.009*"2024" + 0.008*"needs" + 0.007*"well" + 0.007*"practice" + 0.006*"plans" + 0.006*"leaders" + 0.006*"Cheshire" + 0.005*"East" + 0.005*"effective" +2024-07-25 12:39:31,694 - topic #2 (0.333): 0.010*"’" + 0.007*"quality" + 0.007*"plans" + 0.007*"practice" + 0.006*"2024" + 0.006*"needs" + 0.006*"well" + 0.006*"means" + 0.006*"East" + 0.005*"access" +2024-07-25 12:39:31,694 - topic diff=0.774677, rho=1.000000 +2024-07-25 12:39:31,694 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:31.694570', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:32,625 - Inspection date 2024-02-26 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:32,625 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:32,626 - Inspection date 2024-02-26 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:32,626 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:32,626 - Inspection date 2024-02-26 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:32,626 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:32,626 - Inspection date 2024-02-26 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:32,626 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:32,626 - Inspection date 2024-02-26 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:32,626 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:32,627 - Inspection date 2024-02-26 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:32,627 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:33,958 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:33,960 - built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2186 corpus positions) +2024-07-25 12:39:33,961 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2186 corpus positions)", 'datetime': '2024-07-25T12:39:33.961061', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:33,962 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:33,962 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:33,962 - using serial LDA version on this node +2024-07-25 12:39:33,962 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:33,962 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:33,966 - -8.004 per-word bound, 256.7 perplexity estimate based on a held-out corpus of 1 documents with 2186 words +2024-07-25 12:39:33,966 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:33,967 - topic #0 (0.333): 0.021*"’" + 0.007*"well" + 0.007*"needs" + 0.005*"always" + 0.004*"effectively" + 0.004*"leaders" + 0.004*"impact" + 0.004*"timely" + 0.004*"order" + 0.004*"improve" +2024-07-25 12:39:33,968 - topic #1 (0.333): 0.018*"’" + 0.007*"well" + 0.007*"needs" + 0.005*"practice" + 0.004*"impact" + 0.004*"always" + 0.004*"good" + 0.004*"effective" + 0.004*"use" + 0.004*"receive" +2024-07-25 12:39:33,968 - topic #2 (0.333): 0.025*"’" + 0.007*"needs" + 0.007*"well" + 0.005*"plans" + 0.005*"practice" + 0.005*"effective" + 0.004*"order" + 0.004*"including" + 0.004*"effectively" + 0.004*"timely" +2024-07-25 12:39:33,968 - topic diff=0.764324, rho=1.000000 +2024-07-25 12:39:33,968 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:33.968575', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:34,923 - Inspection date 2019-03-18 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:34,923 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:34,923 - Inspection date 2019-03-18 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:34,924 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:34,924 - Inspection date 2019-03-18 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:34,924 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:34,924 - Inspection date 2019-03-18 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:34,924 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:34,924 - Inspection date 2019-03-18 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:34,925 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:34,925 - Inspection date 2019-03-18 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:34,925 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:36,964 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:36,966 - built Dictionary<1164 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2639 corpus positions) +2024-07-25 12:39:36,967 - Dictionary lifecycle event {'msg': "built Dictionary<1164 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2639 corpus positions)", 'datetime': '2024-07-25T12:39:36.967025', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:36,968 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:36,968 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:36,968 - using serial LDA version on this node +2024-07-25 12:39:36,969 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:36,969 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:36,973 - -8.050 per-word bound, 265.0 perplexity estimate based on a held-out corpus of 1 documents with 2639 words +2024-07-25 12:39:36,973 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:36,974 - topic #0 (0.333): 0.019*"’" + 0.007*"plans" + 0.005*"Bradford" + 0.005*"2" + 0.005*"needs" + 0.004*"quality" + 0.004*"Council" + 0.004*"practice" + 0.004*"Borough" + 0.004*"City" +2024-07-25 12:39:36,974 - topic #1 (0.333): 0.020*"’" + 0.006*"plans" + 0.005*"impact" + 0.005*"2" + 0.004*"◼" + 0.004*"quality" + 0.004*"Council" + 0.004*"Bradford" + 0.004*"need" + 0.004*"risk" +2024-07-25 12:39:36,975 - topic #2 (0.333): 0.023*"’" + 0.007*"plans" + 0.005*"needs" + 0.005*"progress" + 0.005*"Bradford" + 0.005*"risk" + 0.004*"21" + 0.004*"need" + 0.004*"lack" + 0.004*"November" +2024-07-25 12:39:36,975 - topic diff=0.807590, rho=1.000000 +2024-07-25 12:39:36,975 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:36.975380', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:38,218 - Inspection date 2022-11-21 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:38,219 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:38,219 - Inspection date 2022-11-21 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:38,219 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:38,220 - Inspection date 2022-11-21 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:38,220 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:38,220 - Inspection date 2022-11-21 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:38,220 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:38,221 - Inspection date 2022-11-21 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:38,221 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:38,221 - Inspection date 2022-11-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:38,221 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:39,592 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:39,594 - built Dictionary<876 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1767 corpus positions) +2024-07-25 12:39:39,594 - Dictionary lifecycle event {'msg': "built Dictionary<876 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1767 corpus positions)", 'datetime': '2024-07-25T12:39:39.594791', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:39,595 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:39,595 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:39,596 - using serial LDA version on this node +2024-07-25 12:39:39,596 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:39,596 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:39,599 - -7.838 per-word bound, 228.9 perplexity estimate based on a held-out corpus of 1 documents with 1767 words +2024-07-25 12:39:39,599 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:39,600 - topic #0 (0.333): 0.012*"’" + 0.009*"needs" + 0.008*"well" + 0.007*"ensure" + 0.007*"clear" + 0.007*"effective" + 0.006*"progress" + 0.005*"good" + 0.005*"plans" + 0.005*"individual" +2024-07-25 12:39:39,601 - topic #1 (0.333): 0.012*"needs" + 0.011*"well" + 0.009*"’" + 0.008*"ensure" + 0.007*"clear" + 0.006*"progress" + 0.006*"effective" + 0.005*"practice" + 0.005*"plans" + 0.005*"within" +2024-07-25 12:39:39,601 - topic #2 (0.333): 0.013*"’" + 0.012*"needs" + 0.010*"well" + 0.009*"ensure" + 0.007*"effective" + 0.006*"good" + 0.005*"progress" + 0.005*"plans" + 0.005*"supported" + 0.005*"individual" +2024-07-25 12:39:39,601 - topic diff=0.742921, rho=1.000000 +2024-07-25 12:39:39,601 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:39.601719', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:40,744 - Inspection date 2020-03-02 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:40,745 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:40,745 - Inspection date 2020-03-02 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:40,745 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:40,745 - Inspection date 2020-03-02 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:40,745 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:40,746 - Inspection date 2020-03-02 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:40,746 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:40,746 - Inspection date 2020-03-02 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:40,746 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:40,746 - Inspection date 2020-03-02 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:40,746 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:42,464 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:42,466 - built Dictionary<1007 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2281 corpus positions) +2024-07-25 12:39:42,466 - Dictionary lifecycle event {'msg': "built Dictionary<1007 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2281 corpus positions)", 'datetime': '2024-07-25T12:39:42.466384', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:42,467 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:42,467 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:42,467 - using serial LDA version on this node +2024-07-25 12:39:42,468 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:42,468 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:42,471 - -7.904 per-word bound, 239.5 perplexity estimate based on a held-out corpus of 1 documents with 2281 words +2024-07-25 12:39:42,471 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:42,473 - topic #0 (0.333): 0.016*"’" + 0.008*"quality" + 0.008*"well" + 0.008*"November" + 0.008*"plans" + 0.007*"Wakefield" + 0.006*"good" + 0.006*"leaders" + 0.005*"receive" + 0.005*"strong" +2024-07-25 12:39:42,473 - topic #1 (0.333): 0.019*"’" + 0.009*"Wakefield" + 0.009*"effective" + 0.008*"leaders" + 0.008*"well" + 0.007*"quality" + 0.007*"good" + 0.007*"November" + 0.006*"practice" + 0.006*"progress" +2024-07-25 12:39:42,473 - topic #2 (0.333): 0.014*"’" + 0.007*"leaders" + 0.007*"November" + 0.006*"quality" + 0.006*"Wakefield" + 0.006*"well" + 0.006*"good" + 0.005*"receive" + 0.005*"effective" + 0.005*"19" +2024-07-25 12:39:42,473 - topic diff=0.805261, rho=1.000000 +2024-07-25 12:39:42,473 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:42.473795', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:43,386 - Inspection date 2021-11-08 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:43,387 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:43,387 - Inspection date 2021-11-08 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:43,387 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:43,387 - Inspection date 2021-11-08 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:43,387 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:43,388 - Inspection date 2021-11-08 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:43,388 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:43,388 - Inspection date 2021-11-08 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:43,388 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:43,388 - Inspection date 2021-11-08 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:43,388 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:44,875 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:44,878 - built Dictionary<909 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1855 corpus positions) +2024-07-25 12:39:44,878 - Dictionary lifecycle event {'msg': "built Dictionary<909 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1855 corpus positions)", 'datetime': '2024-07-25T12:39:44.878825', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:44,879 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:44,879 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:44,880 - using serial LDA version on this node +2024-07-25 12:39:44,880 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:44,880 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:44,885 - -7.862 per-word bound, 232.7 perplexity estimate based on a held-out corpus of 1 documents with 1855 words +2024-07-25 12:39:44,885 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:44,886 - topic #0 (0.333): 0.015*"’" + 0.008*"needs" + 0.007*"March" + 0.007*"effective" + 0.006*"York" + 0.006*"quality" + 0.006*"ensure" + 0.006*"However" + 0.005*"7" + 0.005*"practice" +2024-07-25 12:39:44,887 - topic #1 (0.333): 0.016*"’" + 0.007*"quality" + 0.007*"needs" + 0.007*"March" + 0.005*"However" + 0.005*"plans" + 0.005*"ensure" + 0.005*"supported" + 0.005*"appropriate" + 0.005*"good" +2024-07-25 12:39:44,887 - topic #2 (0.333): 0.013*"’" + 0.007*"March" + 0.007*"needs" + 0.006*"quality" + 0.006*"effective" + 0.005*"training" + 0.004*"York" + 0.004*"well" + 0.004*"education" + 0.004*"However" +2024-07-25 12:39:44,887 - topic diff=0.770689, rho=1.000000 +2024-07-25 12:39:44,887 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:44.887722', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:45,870 - Inspection date 2022-03-07 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:45,870 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:45,871 - Inspection date 2022-03-07 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:45,871 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:45,871 - Inspection date 2022-03-07 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:45,871 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:45,871 - Inspection date 2022-03-07 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:45,872 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:45,872 - Inspection date 2022-03-07 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:45,872 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:45,872 - Inspection date 2022-03-07 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:45,872 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:47,288 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:47,292 - built Dictionary<1014 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2157 corpus positions) +2024-07-25 12:39:47,292 - Dictionary lifecycle event {'msg': "built Dictionary<1014 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2157 corpus positions)", 'datetime': '2024-07-25T12:39:47.292510', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:47,294 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:47,294 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:47,295 - using serial LDA version on this node +2024-07-25 12:39:47,295 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:47,296 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:47,301 - -7.950 per-word bound, 247.2 perplexity estimate based on a held-out corpus of 1 documents with 2157 words +2024-07-25 12:39:47,301 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:47,303 - topic #0 (0.333): 0.011*"well" + 0.010*"’" + 0.008*"effective" + 0.007*"leaders" + 0.006*"arrangements" + 0.006*"quality" + 0.005*"plans" + 0.005*"timely" + 0.004*"good" + 0.004*"highly" +2024-07-25 12:39:47,304 - topic #1 (0.333): 0.017*"well" + 0.012*"quality" + 0.011*"’" + 0.009*"effective" + 0.009*"leaders" + 0.007*"good" + 0.006*"plans" + 0.005*"timely" + 0.005*"ensure" + 0.005*"needs" +2024-07-25 12:39:47,304 - topic #2 (0.333): 0.015*"well" + 0.014*"’" + 0.009*"quality" + 0.009*"leaders" + 0.008*"effective" + 0.006*"arrangements" + 0.006*"highly" + 0.006*"timely" + 0.005*"plans" + 0.005*"good" +2024-07-25 12:39:47,304 - topic diff=0.784478, rho=1.000000 +2024-07-25 12:39:47,305 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:47.305014', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:49,060 - Inspection date 2019-10-14 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:49,060 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:49,061 - Inspection date 2019-10-14 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:49,061 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:49,061 - Inspection date 2019-10-14 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:49,062 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:49,062 - Inspection date 2019-10-14 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:49,063 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:49,064 - Inspection date 2019-10-14 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:49,064 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:49,065 - Inspection date 2019-10-14 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:49,065 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:50,099 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:50,102 - built Dictionary<754 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1521 corpus positions) +2024-07-25 12:39:50,102 - Dictionary lifecycle event {'msg': "built Dictionary<754 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1521 corpus positions)", 'datetime': '2024-07-25T12:39:50.102186', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:50,103 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:50,103 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:50,103 - using serial LDA version on this node +2024-07-25 12:39:50,103 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:50,103 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:50,106 - -7.679 per-word bound, 205.0 perplexity estimate based on a held-out corpus of 1 documents with 1521 words +2024-07-25 12:39:50,107 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:50,108 - topic #0 (0.333): 0.014*"’" + 0.011*"Scilly" + 0.009*"Isles" + 0.008*"practice" + 0.007*"information" + 0.006*"protection" + 0.006*"need" + 0.005*"needs" + 0.005*"place" + 0.005*"risks" +2024-07-25 12:39:50,108 - topic #1 (0.333): 0.024*"’" + 0.013*"Scilly" + 0.012*"Isles" + 0.010*"information" + 0.010*"need" + 0.009*"practice" + 0.007*"needs" + 0.007*"place" + 0.006*"quality" + 0.006*"risks" +2024-07-25 12:39:50,108 - topic #2 (0.333): 0.022*"’" + 0.013*"Isles" + 0.011*"Scilly" + 0.009*"information" + 0.009*"practice" + 0.008*"protection" + 0.008*"need" + 0.007*"needs" + 0.006*"quality" + 0.006*"11" +2024-07-25 12:39:50,108 - topic diff=0.753083, rho=1.000000 +2024-07-25 12:39:50,109 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:50.109022', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:51,016 - Inspection date 2023-07-11 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:51,016 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:51,017 - Inspection date 2023-07-11 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:51,017 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:51,017 - Inspection date 2023-07-11 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:51,017 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:51,017 - Inspection date 2023-07-11 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:51,017 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:51,017 - Inspection date 2023-07-11 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:51,018 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:51,018 - Inspection date 2023-07-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:51,018 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:52,542 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:52,544 - built Dictionary<938 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2074 corpus positions) +2024-07-25 12:39:52,544 - Dictionary lifecycle event {'msg': "built Dictionary<938 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2074 corpus positions)", 'datetime': '2024-07-25T12:39:52.544820', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:52,545 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:52,545 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:52,546 - using serial LDA version on this node +2024-07-25 12:39:52,546 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:52,546 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:52,549 - -7.847 per-word bound, 230.3 perplexity estimate based on a held-out corpus of 1 documents with 2074 words +2024-07-25 12:39:52,550 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:52,551 - topic #0 (0.333): 0.015*"’" + 0.009*"supported" + 0.008*"needs" + 0.008*"Coventry" + 0.007*"well" + 0.007*"plans" + 0.006*"family" + 0.006*"need" + 0.005*"strong" + 0.005*"training" +2024-07-25 12:39:52,551 - topic #1 (0.333): 0.019*"’" + 0.009*"Coventry" + 0.008*"well" + 0.008*"needs" + 0.006*"supported" + 0.006*"plans" + 0.005*"family" + 0.005*"strong" + 0.004*"2022" + 0.004*"need" +2024-07-25 12:39:52,551 - topic #2 (0.333): 0.024*"’" + 0.008*"well" + 0.007*"Coventry" + 0.006*"needs" + 0.006*"family" + 0.005*"strong" + 0.005*"plans" + 0.005*"need" + 0.005*"supported" + 0.005*"PAs" +2024-07-25 12:39:52,551 - topic diff=0.796455, rho=1.000000 +2024-07-25 12:39:52,551 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:52.551947', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:53,491 - Inspection date 2022-06-20 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:53,491 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:53,491 - Inspection date 2022-06-20 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:53,491 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:53,492 - Inspection date 2022-06-20 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:53,492 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:53,492 - Inspection date 2022-06-20 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:53,492 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:53,492 - Inspection date 2022-06-20 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:53,492 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:53,493 - Inspection date 2022-06-20 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:53,493 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:56,259 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:56,262 - built Dictionary<1195 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2653 corpus positions) +2024-07-25 12:39:56,262 - Dictionary lifecycle event {'msg': "built Dictionary<1195 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2653 corpus positions)", 'datetime': '2024-07-25T12:39:56.262452', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:56,263 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:56,263 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:56,264 - using serial LDA version on this node +2024-07-25 12:39:56,264 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:56,264 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:56,268 - -8.087 per-word bound, 272.0 perplexity estimate based on a held-out corpus of 1 documents with 2653 words +2024-07-25 12:39:56,268 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:56,270 - topic #0 (0.333): 0.013*"’" + 0.009*"well" + 0.008*"October" + 0.006*"leaders" + 0.006*"needs" + 0.005*"practice" + 0.005*"Darlington" + 0.004*"range" + 0.004*"family" + 0.004*"quality" +2024-07-25 12:39:56,270 - topic #1 (0.333): 0.024*"’" + 0.008*"leaders" + 0.008*"well" + 0.007*"Darlington" + 0.006*"practice" + 0.006*"needs" + 0.006*"October" + 0.006*"quality" + 0.005*"education" + 0.005*"supported" +2024-07-25 12:39:56,270 - topic #2 (0.333): 0.015*"’" + 0.007*"needs" + 0.006*"well" + 0.006*"practice" + 0.006*"October" + 0.005*"effective" + 0.005*"leaders" + 0.004*"Darlington" + 0.004*"supported" + 0.004*"access" +2024-07-25 12:39:56,270 - topic diff=0.803476, rho=1.000000 +2024-07-25 12:39:56,270 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:56.270860', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:57,228 - Inspection date 2022-10-10 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:39:57,228 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:57,228 - Inspection date 2022-10-10 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:39:57,229 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:57,229 - Inspection date 2022-10-10 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:39:57,229 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:57,229 - Inspection date 2022-10-10 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:39:57,229 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:57,229 - Inspection date 2022-10-10 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:39:57,229 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:57,230 - Inspection date 2022-10-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:39:57,230 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:39:59,073 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:39:59,075 - built Dictionary<1121 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2396 corpus positions) +2024-07-25 12:39:59,075 - Dictionary lifecycle event {'msg': "built Dictionary<1121 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2396 corpus positions)", 'datetime': '2024-07-25T12:39:59.075511', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:39:59,076 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:39:59,076 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:39:59,077 - using serial LDA version on this node +2024-07-25 12:39:59,077 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:39:59,077 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:39:59,081 - -8.043 per-word bound, 263.7 perplexity estimate based on a held-out corpus of 1 documents with 2396 words +2024-07-25 12:39:59,081 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:39:59,082 - topic #0 (0.333): 0.019*"’" + 0.008*"needs" + 0.007*"receive" + 0.007*"Derby" + 0.006*"leaders" + 0.005*"well" + 0.005*"need" + 0.005*"appropriate" + 0.005*"plans" + 0.004*"2022" +2024-07-25 12:39:59,082 - topic #1 (0.333): 0.024*"’" + 0.011*"needs" + 0.008*"quality" + 0.007*"Derby" + 0.007*"receive" + 0.007*"plans" + 0.006*"progress" + 0.006*"well" + 0.006*"leaders" + 0.005*"appropriate" +2024-07-25 12:39:59,083 - topic #2 (0.333): 0.018*"’" + 0.008*"needs" + 0.007*"Derby" + 0.006*"good" + 0.006*"quality" + 0.005*"progress" + 0.005*"need" + 0.005*"oversight" + 0.005*"appropriate" + 0.005*"views" +2024-07-25 12:39:59,083 - topic diff=0.776746, rho=1.000000 +2024-07-25 12:39:59,083 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:39:59.083462', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:00,869 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:00,869 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:00,869 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:00,869 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:00,869 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:00,869 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:00,870 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:00,870 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:00,870 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:00,870 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:00,870 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:00,870 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:02,029 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:02,033 - built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2035 corpus positions) +2024-07-25 12:40:02,033 - Dictionary lifecycle event {'msg': "built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2035 corpus positions)", 'datetime': '2024-07-25T12:40:02.033717', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:02,035 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:02,035 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:02,035 - using serial LDA version on this node +2024-07-25 12:40:02,036 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:02,036 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:02,039 - -8.035 per-word bound, 262.3 perplexity estimate based on a held-out corpus of 1 documents with 2035 words +2024-07-25 12:40:02,039 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:02,041 - topic #0 (0.333): 0.017*"’" + 0.010*"well" + 0.008*"Derbyshire" + 0.005*"positive" + 0.005*"good" + 0.005*"needs" + 0.005*"education" + 0.005*"need" + 0.005*"plans" + 0.005*"health" +2024-07-25 12:40:02,041 - topic #1 (0.333): 0.012*"’" + 0.006*"well" + 0.006*"plans" + 0.005*"Derbyshire" + 0.005*"10" + 0.004*"30" + 0.004*"progress" + 0.004*"effective" + 0.004*"leaders" + 0.004*"health" +2024-07-25 12:40:02,041 - topic #2 (0.333): 0.010*"’" + 0.005*"Derbyshire" + 0.004*"well" + 0.004*"plans" + 0.004*"leaders" + 0.004*"needs" + 0.003*"positive" + 0.003*"health" + 0.003*"10" + 0.003*"risk" +2024-07-25 12:40:02,041 - topic diff=0.771858, rho=1.000000 +2024-07-25 12:40:02,041 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:02.041899', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:03,007 - Inspection date 2023-10-30 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:03,007 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:03,008 - Inspection date 2023-10-30 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:03,008 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:03,008 - Inspection date 2023-10-30 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:03,008 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:03,008 - Inspection date 2023-10-30 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:03,008 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:03,009 - Inspection date 2023-10-30 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:03,009 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:03,009 - Inspection date 2023-10-30 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:03,009 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:04,368 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:04,370 - built Dictionary<1175 unique tokens: ['0161', '0300', '1', '1,000', '10']...> from 1 documents (total 2313 corpus positions) +2024-07-25 12:40:04,370 - Dictionary lifecycle event {'msg': "built Dictionary<1175 unique tokens: ['0161', '0300', '1', '1,000', '10']...> from 1 documents (total 2313 corpus positions)", 'datetime': '2024-07-25T12:40:04.370430', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:04,371 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:04,371 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:04,371 - using serial LDA version on this node +2024-07-25 12:40:04,372 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:04,372 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:04,376 - -8.140 per-word bound, 282.1 perplexity estimate based on a held-out corpus of 1 documents with 2313 words +2024-07-25 12:40:04,376 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:04,377 - topic #0 (0.333): 0.010*"’" + 0.007*"well" + 0.005*"risk" + 0.004*"progress" + 0.004*"Devon" + 0.004*"leaders" + 0.004*"including" + 0.003*"needs" + 0.003*"practice" + 0.003*"health" +2024-07-25 12:40:04,377 - topic #1 (0.333): 0.009*"’" + 0.005*"leaders" + 0.004*"health" + 0.004*"risk" + 0.004*"need" + 0.004*"case" + 0.004*"protection" + 0.004*"progress" + 0.004*"well" + 0.004*"practice" +2024-07-25 12:40:04,378 - topic #2 (0.333): 0.009*"’" + 0.006*"well" + 0.006*"health" + 0.005*"leaders" + 0.005*"progress" + 0.005*"risk" + 0.005*"living" + 0.005*"time" + 0.004*"protection" + 0.004*"areas" +2024-07-25 12:40:04,378 - topic diff=0.733291, rho=1.000000 +2024-07-25 12:40:04,378 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:04.378250', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:05,406 - Inspection date 2020-01-20 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:05,406 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:05,406 - Inspection date 2020-01-20 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:05,406 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:05,406 - Inspection date 2020-01-20 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:05,407 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:05,407 - Inspection date 2020-01-20 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:05,407 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:05,407 - Inspection date 2020-01-20 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:05,407 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:05,407 - Inspection date 2020-01-20 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:05,408 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:07,116 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:07,119 - built Dictionary<1175 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2429 corpus positions) +2024-07-25 12:40:07,119 - Dictionary lifecycle event {'msg': "built Dictionary<1175 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2429 corpus positions)", 'datetime': '2024-07-25T12:40:07.119312', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:07,120 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:07,120 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:07,120 - using serial LDA version on this node +2024-07-25 12:40:07,121 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:07,121 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:07,125 - -8.116 per-word bound, 277.4 perplexity estimate based on a held-out corpus of 1 documents with 2429 words +2024-07-25 12:40:07,125 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:07,126 - topic #0 (0.333): 0.021*"’" + 0.007*"Doncaster" + 0.006*"well" + 0.005*"leaders" + 0.005*"quality" + 0.005*"many" + 0.005*"oversight" + 0.005*"information" + 0.005*"25" + 0.005*"records" +2024-07-25 12:40:07,126 - topic #1 (0.333): 0.013*"’" + 0.006*"well" + 0.006*"Doncaster" + 0.004*"many" + 0.004*"plans" + 0.004*"arrangements" + 0.004*"leaders" + 0.004*"February" + 0.004*"effective" + 0.004*"protection" +2024-07-25 12:40:07,127 - topic #2 (0.333): 0.024*"’" + 0.008*"well" + 0.006*"records" + 0.006*"progress" + 0.005*"plans" + 0.005*"leaders" + 0.005*"Doncaster" + 0.005*"many" + 0.005*"experiences" + 0.005*"information" +2024-07-25 12:40:07,127 - topic diff=0.775553, rho=1.000000 +2024-07-25 12:40:07,127 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:07.127445', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:09,038 - Inspection date 2022-02-14 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:09,038 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:09,039 - Inspection date 2022-02-14 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:09,039 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:09,039 - Inspection date 2022-02-14 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:09,039 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:09,040 - Inspection date 2022-02-14 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:09,040 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:09,040 - Inspection date 2022-02-14 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:09,040 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:09,040 - Inspection date 2022-02-14 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:09,040 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:10,887 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:10,890 - built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1942 corpus positions) +2024-07-25 12:40:10,891 - Dictionary lifecycle event {'msg': "built Dictionary<1067 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1942 corpus positions)", 'datetime': '2024-07-25T12:40:10.891176', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:10,892 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:10,893 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:10,893 - using serial LDA version on this node +2024-07-25 12:40:10,894 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:10,894 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:10,900 - -8.100 per-word bound, 274.4 perplexity estimate based on a held-out corpus of 1 documents with 1942 words +2024-07-25 12:40:10,900 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:10,902 - topic #0 (0.333): 0.010*"’" + 0.009*"Dorset" + 0.006*"good" + 0.005*"arrangements" + 0.005*"well" + 0.004*"needs" + 0.004*"October" + 0.004*"8" + 0.004*"September" + 0.004*"leaders" +2024-07-25 12:40:10,902 - topic #1 (0.333): 0.012*"’" + 0.008*"Dorset" + 0.006*"well" + 0.006*"good" + 0.005*"needs" + 0.004*"need" + 0.004*"including" + 0.004*"2021" + 0.004*"leaders" + 0.004*"quality" +2024-07-25 12:40:10,903 - topic #2 (0.333): 0.019*"’" + 0.006*"Dorset" + 0.006*"well" + 0.005*"good" + 0.004*"change" + 0.004*"arrangements" + 0.004*"needs" + 0.004*"8" + 0.004*"Senior" + 0.004*"27" +2024-07-25 12:40:10,903 - topic diff=0.712281, rho=1.000000 +2024-07-25 12:40:10,903 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:10.903679', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:12,009 - Inspection date 2021-09-27 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:12,010 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:12,010 - Inspection date 2021-09-27 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:12,010 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:12,011 - Inspection date 2021-09-27 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:12,011 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:12,011 - Inspection date 2021-09-27 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:12,011 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:12,012 - Inspection date 2021-09-27 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:12,012 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:12,012 - Inspection date 2021-09-27 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:12,012 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:13,393 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:13,395 - built Dictionary<1050 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2138 corpus positions) +2024-07-25 12:40:13,395 - Dictionary lifecycle event {'msg': "built Dictionary<1050 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2138 corpus positions)", 'datetime': '2024-07-25T12:40:13.395614', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:13,396 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:13,396 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:13,397 - using serial LDA version on this node +2024-07-25 12:40:13,397 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:13,397 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:13,401 - -8.011 per-word bound, 257.9 perplexity estimate based on a held-out corpus of 1 documents with 2138 words +2024-07-25 12:40:13,401 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:13,402 - topic #0 (0.333): 0.018*"’" + 0.012*"needs" + 0.009*"Dudley" + 0.006*"plans" + 0.006*"arrangements" + 0.005*"ensure" + 0.005*"always" + 0.005*"well" + 0.004*"experiences" + 0.004*"quality" +2024-07-25 12:40:13,402 - topic #1 (0.333): 0.014*"’" + 0.010*"needs" + 0.008*"Dudley" + 0.006*"well" + 0.005*"plans" + 0.005*"always" + 0.005*"oversight" + 0.005*"arrangements" + 0.005*"ensure" + 0.004*"enough" +2024-07-25 12:40:13,402 - topic #2 (0.333): 0.012*"’" + 0.009*"needs" + 0.005*"well" + 0.005*"Dudley" + 0.005*"However" + 0.005*"always" + 0.005*"management" + 0.005*"quality" + 0.005*"arrangements" + 0.004*"31" +2024-07-25 12:40:13,403 - topic diff=0.758432, rho=1.000000 +2024-07-25 12:40:13,403 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:13.403238', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:14,390 - Inspection date 2022-10-31 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:14,391 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:14,391 - Inspection date 2022-10-31 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:14,391 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:14,391 - Inspection date 2022-10-31 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:14,391 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:14,391 - Inspection date 2022-10-31 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:14,392 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:14,392 - Inspection date 2022-10-31 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:14,392 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:14,392 - Inspection date 2022-10-31 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:14,392 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:16,086 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:16,089 - built Dictionary<1051 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2278 corpus positions) +2024-07-25 12:40:16,090 - Dictionary lifecycle event {'msg': "built Dictionary<1051 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2278 corpus positions)", 'datetime': '2024-07-25T12:40:16.090114', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:16,091 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:16,091 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:16,091 - using serial LDA version on this node +2024-07-25 12:40:16,092 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:16,092 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:16,095 - -7.975 per-word bound, 251.6 perplexity estimate based on a held-out corpus of 1 documents with 2278 words +2024-07-25 12:40:16,095 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:16,097 - topic #0 (0.333): 0.015*"’" + 0.013*"needs" + 0.008*"well" + 0.008*"May" + 0.008*"plans" + 0.007*"Durham" + 0.007*"ensure" + 0.005*"practice" + 0.005*"number" + 0.005*"carers" +2024-07-25 12:40:16,097 - topic #1 (0.333): 0.015*"’" + 0.009*"needs" + 0.007*"Durham" + 0.006*"May" + 0.006*"well" + 0.005*"plans" + 0.005*"practice" + 0.005*"ensure" + 0.005*"2022" + 0.005*"leaders" +2024-07-25 12:40:16,097 - topic #2 (0.333): 0.013*"’" + 0.009*"needs" + 0.006*"May" + 0.006*"Durham" + 0.005*"well" + 0.005*"practice" + 0.005*"plans" + 0.005*"ensure" + 0.004*"progress" + 0.004*"20" +2024-07-25 12:40:16,097 - topic diff=0.780292, rho=1.000000 +2024-07-25 12:40:16,098 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:16.098076', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:17,179 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:17,180 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:17,180 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:17,180 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:17,180 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:17,180 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:17,181 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:17,181 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:17,181 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:17,181 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:17,181 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:17,181 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:18,727 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:18,729 - built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2014 corpus positions) +2024-07-25 12:40:18,729 - Dictionary lifecycle event {'msg': "built Dictionary<972 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2014 corpus positions)", 'datetime': '2024-07-25T12:40:18.729725', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:18,730 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:18,730 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:18,731 - using serial LDA version on this node +2024-07-25 12:40:18,731 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:18,731 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:18,734 - -7.925 per-word bound, 243.0 perplexity estimate based on a held-out corpus of 1 documents with 2014 words +2024-07-25 12:40:18,734 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:18,736 - topic #0 (0.333): 0.020*"’" + 0.011*"needs" + 0.010*"plans" + 0.009*"well" + 0.008*"Riding" + 0.007*"progress" + 0.007*"East" + 0.006*"10" + 0.005*"place" + 0.005*"education" +2024-07-25 12:40:18,736 - topic #1 (0.333): 0.014*"’" + 0.008*"well" + 0.007*"needs" + 0.007*"progress" + 0.006*"plans" + 0.006*"East" + 0.005*"30" + 0.005*"good" + 0.005*"partners" + 0.005*"Riding" +2024-07-25 12:40:18,736 - topic #2 (0.333): 0.012*"’" + 0.008*"plans" + 0.008*"needs" + 0.007*"well" + 0.006*"progress" + 0.006*"East" + 0.005*"Riding" + 0.005*"January" + 0.004*"partners" + 0.004*"2023" +2024-07-25 12:40:18,736 - topic diff=0.776506, rho=1.000000 +2024-07-25 12:40:18,736 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:18.736764', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:19,624 - Inspection date 2023-01-30 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:19,624 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:19,625 - Inspection date 2023-01-30 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:19,625 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:19,625 - Inspection date 2023-01-30 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:19,625 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:19,625 - Inspection date 2023-01-30 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:19,625 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:19,626 - Inspection date 2023-01-30 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:19,626 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:19,626 - Inspection date 2023-01-30 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:19,626 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:21,297 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:21,301 - built Dictionary<1111 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2220 corpus positions) +2024-07-25 12:40:21,301 - Dictionary lifecycle event {'msg': "built Dictionary<1111 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2220 corpus positions)", 'datetime': '2024-07-25T12:40:21.301441', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:21,303 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:21,303 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:21,303 - using serial LDA version on this node +2024-07-25 12:40:21,304 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:21,304 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:21,310 - -8.080 per-word bound, 270.6 perplexity estimate based on a held-out corpus of 1 documents with 2220 words +2024-07-25 12:40:21,310 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:21,312 - topic #0 (0.333): 0.010*"’" + 0.009*"well" + 0.007*"plans" + 0.007*"Sussex" + 0.007*"East" + 0.006*"needs" + 0.005*"including" + 0.005*"progress" + 0.005*"impact" + 0.004*"December" +2024-07-25 12:40:21,313 - topic #1 (0.333): 0.021*"’" + 0.010*"well" + 0.009*"needs" + 0.008*"plans" + 0.007*"progress" + 0.007*"including" + 0.006*"East" + 0.006*"Sussex" + 0.005*"effective" + 0.005*"impact" +2024-07-25 12:40:21,313 - topic #2 (0.333): 0.017*"’" + 0.009*"well" + 0.007*"plans" + 0.007*"needs" + 0.006*"East" + 0.006*"impact" + 0.006*"relationships" + 0.005*"11" + 0.005*"progress" + 0.005*"experiences" +2024-07-25 12:40:21,313 - topic diff=0.756391, rho=1.000000 +2024-07-25 12:40:21,313 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:21.313834', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:22,511 - Inspection date 2023-12-11 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:22,512 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:22,512 - Inspection date 2023-12-11 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:22,512 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:22,512 - Inspection date 2023-12-11 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:22,512 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:22,513 - Inspection date 2023-12-11 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:22,513 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:22,513 - Inspection date 2023-12-11 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:22,513 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:22,513 - Inspection date 2023-12-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:22,513 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:24,209 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:24,211 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2686 corpus positions) +2024-07-25 12:40:24,212 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2686 corpus positions)", 'datetime': '2024-07-25T12:40:24.212117', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:24,213 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:24,213 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:24,213 - using serial LDA version on this node +2024-07-25 12:40:24,214 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:24,214 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:24,217 - -8.008 per-word bound, 257.5 perplexity estimate based on a held-out corpus of 1 documents with 2686 words +2024-07-25 12:40:24,218 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:24,219 - topic #0 (0.333): 0.017*"’" + 0.007*"well" + 0.007*"needs" + 0.006*"progress" + 0.005*"family" + 0.005*"understand" + 0.005*"practice" + 0.005*"quality" + 0.004*"helped" + 0.004*"need" +2024-07-25 12:40:24,219 - topic #1 (0.333): 0.019*"’" + 0.008*"well" + 0.006*"plans" + 0.006*"progress" + 0.005*"needs" + 0.005*"Essex" + 0.005*"‘" + 0.005*"advisers" + 0.005*"risk" + 0.005*"experiences" +2024-07-25 12:40:24,219 - topic #2 (0.333): 0.017*"’" + 0.007*"plans" + 0.007*"progress" + 0.006*"needs" + 0.005*"well" + 0.005*"family" + 0.005*"experiences" + 0.005*"health" + 0.005*"understand" + 0.005*"parents" +2024-07-25 12:40:24,220 - topic diff=0.805277, rho=1.000000 +2024-07-25 12:40:24,220 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:24.220184', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:25,182 - Inspection date 2023-06-26 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:25,182 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:25,183 - Inspection date 2023-06-26 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:25,183 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:25,183 - Inspection date 2023-06-26 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:25,183 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:25,184 - Inspection date 2023-06-26 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:25,184 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:25,184 - Inspection date 2023-06-26 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:25,184 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:25,184 - Inspection date 2023-06-26 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:25,185 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:27,006 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:27,009 - built Dictionary<1112 unique tokens: ['0161', '0300', '0–19', '1', '10']...> from 1 documents (total 2356 corpus positions) +2024-07-25 12:40:27,009 - Dictionary lifecycle event {'msg': "built Dictionary<1112 unique tokens: ['0161', '0300', '0–19', '1', '10']...> from 1 documents (total 2356 corpus positions)", 'datetime': '2024-07-25T12:40:27.009456', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:27,010 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:27,010 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:27,010 - using serial LDA version on this node +2024-07-25 12:40:27,011 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:27,011 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:27,015 - -8.042 per-word bound, 263.5 perplexity estimate based on a held-out corpus of 1 documents with 2356 words +2024-07-25 12:40:27,015 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:27,016 - topic #0 (0.333): 0.018*"’" + 0.008*"good" + 0.008*"effective" + 0.007*"quality" + 0.007*"practice" + 0.006*"needs" + 0.006*"plans" + 0.005*"timely" + 0.005*"need" + 0.005*"well" +2024-07-25 12:40:27,016 - topic #1 (0.333): 0.011*"’" + 0.010*"effective" + 0.007*"good" + 0.006*"practice" + 0.006*"needs" + 0.006*"well" + 0.005*"quality" + 0.005*"timely" + 0.005*"home" + 0.004*"early" +2024-07-25 12:40:27,016 - topic #2 (0.333): 0.011*"’" + 0.008*"effective" + 0.007*"practice" + 0.006*"well" + 0.006*"needs" + 0.006*"quality" + 0.005*"improve" + 0.005*"good" + 0.005*"timely" + 0.005*"early" +2024-07-25 12:40:27,016 - topic diff=0.769066, rho=1.000000 +2024-07-25 12:40:27,017 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:27.017107', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:27,945 - Inspection date 2019-04-29 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:27,945 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:27,945 - Inspection date 2019-04-29 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:27,945 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:27,946 - Inspection date 2019-04-29 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:27,946 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:27,946 - Inspection date 2019-04-29 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:27,946 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:27,946 - Inspection date 2019-04-29 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:27,946 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:27,947 - Inspection date 2019-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:27,947 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:29,499 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:29,502 - built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2579 corpus positions) +2024-07-25 12:40:29,502 - Dictionary lifecycle event {'msg': "built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2579 corpus positions)", 'datetime': '2024-07-25T12:40:29.502925', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:29,504 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:29,505 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:29,505 - using serial LDA version on this node +2024-07-25 12:40:29,505 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:29,505 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:29,510 - -8.055 per-word bound, 265.9 perplexity estimate based on a held-out corpus of 1 documents with 2579 words +2024-07-25 12:40:29,510 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:29,512 - topic #0 (0.333): 0.018*"’" + 0.010*"needs" + 0.008*"plans" + 0.007*"2022" + 0.006*"Gloucestershire" + 0.006*"progress" + 0.006*"February" + 0.005*"protection" + 0.005*"experienced" + 0.005*"7" +2024-07-25 12:40:29,512 - topic #1 (0.333): 0.021*"’" + 0.009*"February" + 0.007*"needs" + 0.007*"2022" + 0.007*"well" + 0.006*"plans" + 0.005*"experienced" + 0.005*"appropriate" + 0.005*"Gloucestershire" + 0.005*"18" +2024-07-25 12:40:29,512 - topic #2 (0.333): 0.011*"’" + 0.007*"needs" + 0.006*"2022" + 0.005*"February" + 0.004*"well" + 0.004*"plans" + 0.004*"timely" + 0.004*"18" + 0.004*"progress" + 0.004*"quality" +2024-07-25 12:40:29,512 - topic diff=0.834403, rho=1.000000 +2024-07-25 12:40:29,512 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:29.512677', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:30,660 - Inspection date 2022-02-07 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:30,660 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:30,660 - Inspection date 2022-02-07 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:30,661 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:30,661 - Inspection date 2022-02-07 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:30,661 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:30,661 - Inspection date 2022-02-07 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:30,661 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:30,661 - Inspection date 2022-02-07 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:30,662 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:30,662 - Inspection date 2022-02-07 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:30,662 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:32,680 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:32,683 - built Dictionary<1172 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2652 corpus positions) +2024-07-25 12:40:32,683 - Dictionary lifecycle event {'msg': "built Dictionary<1172 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2652 corpus positions)", 'datetime': '2024-07-25T12:40:32.683476', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:32,684 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:32,684 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:32,685 - using serial LDA version on this node +2024-07-25 12:40:32,685 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:32,685 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:32,689 - -8.055 per-word bound, 265.9 perplexity estimate based on a held-out corpus of 1 documents with 2652 words +2024-07-25 12:40:32,689 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:32,690 - topic #0 (0.333): 0.012*"’" + 0.007*"many" + 0.006*"needs" + 0.005*"including" + 0.005*"quality" + 0.005*"recently" + 0.005*"Halton" + 0.005*"24" + 0.005*"plans" + 0.005*"lack" +2024-07-25 12:40:32,691 - topic #1 (0.333): 0.015*"’" + 0.008*"needs" + 0.007*"Halton" + 0.006*"need" + 0.006*"plans" + 0.006*"quality" + 0.005*"including" + 0.005*"13" + 0.005*"many" + 0.005*"Leaders" +2024-07-25 12:40:32,691 - topic #2 (0.333): 0.018*"’" + 0.006*"quality" + 0.006*"needs" + 0.006*"many" + 0.006*"Halton" + 0.005*"including" + 0.005*"protection" + 0.005*"experiences" + 0.005*"need" + 0.004*"carers" +2024-07-25 12:40:32,691 - topic diff=0.803777, rho=1.000000 +2024-07-25 12:40:32,691 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:32.691640', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:33,593 - Inspection date 2024-05-13 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:33,593 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:33,593 - Inspection date 2024-05-13 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:33,593 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:33,594 - Inspection date 2024-05-13 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:33,594 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:33,594 - Inspection date 2024-05-13 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:33,594 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:33,594 - Inspection date 2024-05-13 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:33,594 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:33,594 - Inspection date 2024-05-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:33,595 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:35,139 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:35,143 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2524 corpus positions) +2024-07-25 12:40:35,143 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2524 corpus positions)", 'datetime': '2024-07-25T12:40:35.143933', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:35,145 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:35,146 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:35,146 - using serial LDA version on this node +2024-07-25 12:40:35,146 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:35,147 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:35,153 - -7.974 per-word bound, 251.4 perplexity estimate based on a held-out corpus of 1 documents with 2524 words +2024-07-25 12:40:35,153 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:35,155 - topic #0 (0.333): 0.017*"’" + 0.009*"new" + 0.007*"progress" + 0.007*"well" + 0.007*"family" + 0.007*"plans" + 0.006*"quality" + 0.005*"need" + 0.005*"achieve" + 0.005*"practice" +2024-07-25 12:40:35,155 - topic #1 (0.333): 0.016*"’" + 0.008*"family" + 0.007*"plans" + 0.007*"well" + 0.006*"new" + 0.006*"needs" + 0.005*"practice" + 0.005*"receive" + 0.005*"Hampshire" + 0.005*"progress" +2024-07-25 12:40:35,155 - topic #2 (0.333): 0.016*"’" + 0.007*"well" + 0.006*"family" + 0.006*"progress" + 0.005*"plans" + 0.005*"quality" + 0.005*"achieve" + 0.005*"new" + 0.005*"receive" + 0.004*"needs" +2024-07-25 12:40:35,156 - topic diff=0.810636, rho=1.000000 +2024-07-25 12:40:35,156 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:35.156374', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:36,161 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:36,161 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:36,161 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:36,161 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:36,161 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:36,161 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:36,162 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:36,162 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:36,162 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:36,162 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:36,162 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:36,162 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:37,856 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:37,859 - built Dictionary<1171 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2584 corpus positions) +2024-07-25 12:40:37,859 - Dictionary lifecycle event {'msg': "built Dictionary<1171 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2584 corpus positions)", 'datetime': '2024-07-25T12:40:37.859654', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:37,860 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:37,860 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:37,861 - using serial LDA version on this node +2024-07-25 12:40:37,861 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:37,861 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:37,865 - -8.069 per-word bound, 268.5 perplexity estimate based on a held-out corpus of 1 documents with 2584 words +2024-07-25 12:40:37,865 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:37,867 - topic #0 (0.333): 0.024*"’" + 0.008*"Hartlepool" + 0.008*"March" + 0.008*"needs" + 0.007*"well" + 0.006*"18" + 0.005*"plans" + 0.005*"strong" + 0.005*"effective" + 0.005*"ensure" +2024-07-25 12:40:37,867 - topic #1 (0.333): 0.016*"’" + 0.007*"March" + 0.006*"leaders" + 0.006*"Hartlepool" + 0.005*"needs" + 0.004*"well" + 0.004*"strong" + 0.004*"practice" + 0.004*"supported" + 0.004*"progress" +2024-07-25 12:40:37,867 - topic #2 (0.333): 0.015*"’" + 0.007*"March" + 0.007*"leaders" + 0.006*"needs" + 0.005*"Hartlepool" + 0.005*"clear" + 0.005*"well" + 0.005*"practice" + 0.005*"plans" + 0.004*"22" +2024-07-25 12:40:37,867 - topic diff=0.802571, rho=1.000000 +2024-07-25 12:40:37,868 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:37.868006', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:38,832 - Inspection date 2024-03-18 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:38,832 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:38,832 - Inspection date 2024-03-18 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:38,833 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:38,833 - Inspection date 2024-03-18 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:38,833 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:38,833 - Inspection date 2024-03-18 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:38,833 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:38,833 - Inspection date 2024-03-18 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:38,834 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:38,834 - Inspection date 2024-03-18 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:38,834 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:40,965 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:40,969 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions) +2024-07-25 12:40:40,969 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2531 corpus positions)", 'datetime': '2024-07-25T12:40:40.969755', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:40,971 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:40,971 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:40,972 - using serial LDA version on this node +2024-07-25 12:40:40,972 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:40,973 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:40,979 - -8.041 per-word bound, 263.3 perplexity estimate based on a held-out corpus of 1 documents with 2531 words +2024-07-25 12:40:40,979 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:40,981 - topic #0 (0.333): 0.014*"’" + 0.004*"practice" + 0.004*"Herefordshire" + 0.004*"many" + 0.004*"plans" + 0.004*"lack" + 0.004*"needs" + 0.004*"impact" + 0.004*"carers" + 0.004*"including" +2024-07-25 12:40:40,982 - topic #1 (0.333): 0.020*"’" + 0.006*"practice" + 0.006*"Herefordshire" + 0.006*"lack" + 0.005*"needs" + 0.005*"impact" + 0.005*"18" + 0.005*"July" + 0.005*"many" + 0.004*"plans" +2024-07-25 12:40:40,982 - topic #2 (0.333): 0.015*"’" + 0.005*"practice" + 0.005*"Herefordshire" + 0.005*"impact" + 0.005*"lack" + 0.004*"needs" + 0.004*"many" + 0.004*"progress" + 0.004*"29" + 0.004*"quality" +2024-07-25 12:40:40,982 - topic diff=0.794851, rho=1.000000 +2024-07-25 12:40:40,982 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:40.982735', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:42,096 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:42,096 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:42,097 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:42,097 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:42,097 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:42,097 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:42,097 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:42,097 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:42,097 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:42,098 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:42,098 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:42,098 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:43,834 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:43,837 - built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '100']...> from 1 documents (total 2456 corpus positions) +2024-07-25 12:40:43,837 - Dictionary lifecycle event {'msg': "built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '100']...> from 1 documents (total 2456 corpus positions)", 'datetime': '2024-07-25T12:40:43.837774', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:43,838 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:43,839 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:43,839 - using serial LDA version on this node +2024-07-25 12:40:43,839 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:43,839 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:43,843 - -8.134 per-word bound, 281.0 perplexity estimate based on a held-out corpus of 1 documents with 2456 words +2024-07-25 12:40:43,843 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:43,845 - topic #0 (0.333): 0.024*"’" + 0.008*"well" + 0.007*"needs" + 0.006*"Hertfordshire" + 0.005*"plans" + 0.004*"positive" + 0.004*"January" + 0.004*"receive" + 0.004*"need" + 0.004*"supported" +2024-07-25 12:40:43,845 - topic #1 (0.333): 0.024*"’" + 0.007*"Hertfordshire" + 0.007*"needs" + 0.006*"receive" + 0.005*"well" + 0.005*"27" + 0.005*"Leaders" + 0.004*"family" + 0.004*"need" + 0.004*"‘" +2024-07-25 12:40:43,845 - topic #2 (0.333): 0.020*"’" + 0.006*"Hertfordshire" + 0.005*"well" + 0.005*"needs" + 0.004*"leaders" + 0.004*"2023" + 0.004*"plans" + 0.004*"positive" + 0.004*"risk" + 0.004*"receive" +2024-07-25 12:40:43,845 - topic diff=0.790524, rho=1.000000 +2024-07-25 12:40:43,845 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:43.845941', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:45,559 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:45,559 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:45,560 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:45,560 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:45,560 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:45,560 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:45,560 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:45,560 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:45,561 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:45,561 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:45,561 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:45,561 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:47,381 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:47,383 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '10-year']...> from 1 documents (total 1934 corpus positions) +2024-07-25 12:40:47,383 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '10-year']...> from 1 documents (total 1934 corpus positions)", 'datetime': '2024-07-25T12:40:47.383258', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:47,384 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:47,384 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:47,384 - using serial LDA version on this node +2024-07-25 12:40:47,385 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:47,385 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:47,388 - -7.958 per-word bound, 248.7 perplexity estimate based on a held-out corpus of 1 documents with 1934 words +2024-07-25 12:40:47,388 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:47,389 - topic #0 (0.333): 0.017*"’" + 0.008*"leaders" + 0.006*"progress" + 0.005*"plans" + 0.005*"supported" + 0.005*"well" + 0.005*"improve" + 0.005*"needs" + 0.005*"3" + 0.005*"good" +2024-07-25 12:40:47,390 - topic #1 (0.333): 0.019*"’" + 0.008*"leaders" + 0.006*"needs" + 0.005*"plans" + 0.005*"well" + 0.005*"Senior" + 0.005*"Wight" + 0.005*"progress" + 0.005*"Isle" + 0.005*"protection" +2024-07-25 12:40:47,390 - topic #2 (0.333): 0.016*"’" + 0.008*"leaders" + 0.006*"well" + 0.006*"needs" + 0.005*"Isle" + 0.005*"Senior" + 0.005*"practice" + 0.005*"Wight" + 0.005*"PAs" + 0.005*"supported" +2024-07-25 12:40:47,390 - topic diff=0.768768, rho=1.000000 +2024-07-25 12:40:47,390 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:47.390479', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:48,314 - Inspection date 2023-10-30 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:48,315 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:48,315 - Inspection date 2023-10-30 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:48,315 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:48,315 - Inspection date 2023-10-30 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:48,315 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:48,316 - Inspection date 2023-10-30 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:48,316 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:48,316 - Inspection date 2023-10-30 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:48,316 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:48,316 - Inspection date 2023-10-30 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:48,316 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:50,658 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:50,663 - built Dictionary<1298 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2888 corpus positions) +2024-07-25 12:40:50,663 - Dictionary lifecycle event {'msg': "built Dictionary<1298 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2888 corpus positions)", 'datetime': '2024-07-25T12:40:50.663662', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:50,665 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:50,665 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:50,666 - using serial LDA version on this node +2024-07-25 12:40:50,666 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:50,667 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:50,674 - -8.172 per-word bound, 288.4 perplexity estimate based on a held-out corpus of 1 documents with 2888 words +2024-07-25 12:40:50,674 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:50,677 - topic #0 (0.333): 0.019*"’" + 0.009*"Kent" + 0.006*"Council" + 0.005*"needs" + 0.005*"well" + 0.004*"progress" + 0.004*"County" + 0.004*"supported" + 0.004*"appropriate" + 0.004*"leaders" +2024-07-25 12:40:50,678 - topic #1 (0.333): 0.013*"’" + 0.009*"Kent" + 0.007*"well" + 0.006*"needs" + 0.006*"supported" + 0.005*"Council" + 0.005*"County" + 0.005*"ensure" + 0.004*"practice" + 0.004*"provide" +2024-07-25 12:40:50,678 - topic #2 (0.333): 0.020*"’" + 0.011*"Kent" + 0.009*"needs" + 0.006*"supported" + 0.006*"Council" + 0.006*"well" + 0.006*"progress" + 0.006*"County" + 0.005*"practice" + 0.005*"leaders" +2024-07-25 12:40:50,678 - topic diff=0.803176, rho=1.000000 +2024-07-25 12:40:50,678 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:50.678808', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:51,685 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:51,685 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:51,685 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:51,685 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:51,685 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:51,686 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:51,686 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:51,686 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:51,686 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:51,686 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:51,686 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:51,686 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:53,504 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:53,507 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1970 corpus positions) +2024-07-25 12:40:53,508 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1970 corpus positions)", 'datetime': '2024-07-25T12:40:53.507993', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:53,509 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:53,509 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:53,510 - using serial LDA version on this node +2024-07-25 12:40:53,510 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:53,510 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:53,516 - -7.945 per-word bound, 246.5 perplexity estimate based on a held-out corpus of 1 documents with 1970 words +2024-07-25 12:40:53,516 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:53,518 - topic #0 (0.333): 0.014*"’" + 0.006*"planning" + 0.006*"risks" + 0.006*"well" + 0.006*"need" + 0.005*"practice" + 0.005*"teams" + 0.005*"Hull" + 0.005*"number" + 0.005*"right" +2024-07-25 12:40:53,519 - topic #1 (0.333): 0.017*"’" + 0.008*"number" + 0.007*"protection" + 0.007*"planning" + 0.007*"Hull" + 0.006*"well" + 0.006*"practice" + 0.006*"need" + 0.006*"oversight" + 0.006*"management" +2024-07-25 12:40:53,519 - topic #2 (0.333): 0.015*"’" + 0.006*"number" + 0.006*"planning" + 0.006*"practice" + 0.005*"protection" + 0.005*"well" + 0.005*"management" + 0.004*"risks" + 0.004*"oversight" + 0.004*"need" +2024-07-25 12:40:53,519 - topic diff=0.769479, rho=1.000000 +2024-07-25 12:40:53,519 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:53.519803', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:54,686 - Inspection date 2022-11-14 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:54,686 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:54,686 - Inspection date 2022-11-14 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:54,686 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:54,686 - Inspection date 2022-11-14 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:54,687 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:54,687 - Inspection date 2022-11-14 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:54,687 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:54,687 - Inspection date 2022-11-14 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:54,687 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:54,687 - Inspection date 2022-11-14 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:54,688 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:56,385 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:56,387 - built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2489 corpus positions) +2024-07-25 12:40:56,388 - Dictionary lifecycle event {'msg': "built Dictionary<1142 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2489 corpus positions)", 'datetime': '2024-07-25T12:40:56.388104', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:56,389 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:56,389 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:56,389 - using serial LDA version on this node +2024-07-25 12:40:56,390 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:56,390 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:56,393 - -8.051 per-word bound, 265.2 perplexity estimate based on a held-out corpus of 1 documents with 2489 words +2024-07-25 12:40:56,393 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:56,395 - topic #0 (0.333): 0.012*"’" + 0.007*"quality" + 0.006*"practice" + 0.006*"plans" + 0.006*"well" + 0.006*"good" + 0.005*"Senior" + 0.005*"senior" + 0.005*"protection" + 0.005*"permanence" +2024-07-25 12:40:56,395 - topic #1 (0.333): 0.013*"’" + 0.008*"quality" + 0.007*"practice" + 0.006*"good" + 0.006*"permanence" + 0.005*"training" + 0.005*"needs" + 0.005*"need" + 0.005*"well" + 0.005*"Senior" +2024-07-25 12:40:56,395 - topic #2 (0.333): 0.009*"’" + 0.005*"result" + 0.005*"good" + 0.005*"plans" + 0.005*"permanence" + 0.004*"quality" + 0.004*"need" + 0.004*"practice" + 0.004*"protection" + 0.004*"needs" +2024-07-25 12:40:56,395 - topic diff=0.788317, rho=1.000000 +2024-07-25 12:40:56,395 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:56.395948', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:57,442 - Inspection date 2019-06-10 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:57,443 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:57,443 - Inspection date 2019-06-10 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:57,443 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:57,443 - Inspection date 2019-06-10 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:57,444 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:57,444 - Inspection date 2019-06-10 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:57,444 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:57,444 - Inspection date 2019-06-10 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:57,444 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:57,444 - Inspection date 2019-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:57,445 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:59,014 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:40:59,016 - built Dictionary<886 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1837 corpus positions) +2024-07-25 12:40:59,016 - Dictionary lifecycle event {'msg': "built Dictionary<886 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1837 corpus positions)", 'datetime': '2024-07-25T12:40:59.016947', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:59,017 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:40:59,017 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:40:59,018 - using serial LDA version on this node +2024-07-25 12:40:59,018 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:40:59,018 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:40:59,021 - -7.833 per-word bound, 228.1 perplexity estimate based on a held-out corpus of 1 documents with 1837 words +2024-07-25 12:40:59,021 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:40:59,023 - topic #0 (0.333): 0.009*"’" + 0.008*"progress" + 0.008*"needs" + 0.006*"plans" + 0.005*"quality" + 0.005*"risk" + 0.005*"2021" + 0.004*"October" + 0.004*"11" + 0.004*"abuse" +2024-07-25 12:40:59,023 - topic #1 (0.333): 0.014*"’" + 0.009*"progress" + 0.008*"quality" + 0.007*"needs" + 0.006*"experiences" + 0.005*"Knowsley" + 0.005*"impact" + 0.005*"good" + 0.005*"plans" + 0.005*"need" +2024-07-25 12:40:59,023 - topic #2 (0.333): 0.018*"’" + 0.009*"plans" + 0.008*"progress" + 0.007*"Knowsley" + 0.007*"needs" + 0.007*"2021" + 0.007*"quality" + 0.005*"experiences" + 0.005*"need" + 0.005*"good" +2024-07-25 12:40:59,023 - topic diff=0.753199, rho=1.000000 +2024-07-25 12:40:59,023 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:40:59.023870', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:40:59,930 - Inspection date 2021-10-11 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:40:59,931 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:59,931 - Inspection date 2021-10-11 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:40:59,931 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:59,931 - Inspection date 2021-10-11 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:40:59,932 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:59,932 - Inspection date 2021-10-11 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:40:59,932 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:59,932 - Inspection date 2021-10-11 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:40:59,932 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:40:59,932 - Inspection date 2021-10-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:40:59,933 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:01,292 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:01,295 - built Dictionary<1048 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2263 corpus positions) +2024-07-25 12:41:01,295 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2263 corpus positions)", 'datetime': '2024-07-25T12:41:01.295508', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:01,296 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:01,296 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:01,296 - using serial LDA version on this node +2024-07-25 12:41:01,297 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:01,297 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:01,300 - -7.976 per-word bound, 251.8 perplexity estimate based on a held-out corpus of 1 documents with 2263 words +2024-07-25 12:41:01,301 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:01,302 - topic #0 (0.333): 0.014*"’" + 0.008*"well" + 0.007*"needs" + 0.007*"supported" + 0.006*"Lancashire" + 0.006*"need" + 0.006*"live" + 0.005*"plans" + 0.005*"positive" + 0.004*"parents" +2024-07-25 12:41:01,302 - topic #1 (0.333): 0.014*"’" + 0.008*"well" + 0.008*"needs" + 0.007*"need" + 0.005*"Lancashire" + 0.005*"positive" + 0.005*"information" + 0.005*"supported" + 0.005*"number" + 0.004*"parents" +2024-07-25 12:41:01,302 - topic #2 (0.333): 0.020*"’" + 0.010*"well" + 0.008*"need" + 0.007*"needs" + 0.006*"Lancashire" + 0.006*"practice" + 0.006*"plans" + 0.005*"progress" + 0.005*"health" + 0.005*"parents" +2024-07-25 12:41:01,302 - topic diff=0.780694, rho=1.000000 +2024-07-25 12:41:01,303 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:01.303185', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:02,251 - Inspection date 2022-11-28 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:02,251 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:02,252 - Inspection date 2022-11-28 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:02,252 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:02,252 - Inspection date 2022-11-28 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:02,252 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:02,252 - Inspection date 2022-11-28 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:02,253 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:02,253 - Inspection date 2022-11-28 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:02,253 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:02,253 - Inspection date 2022-11-28 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:02,253 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:03,725 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:03,728 - built Dictionary<1071 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2261 corpus positions) +2024-07-25 12:41:03,728 - Dictionary lifecycle event {'msg': "built Dictionary<1071 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2261 corpus positions)", 'datetime': '2024-07-25T12:41:03.728837', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:03,729 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:03,730 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:03,730 - using serial LDA version on this node +2024-07-25 12:41:03,730 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:03,730 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:03,734 - -8.009 per-word bound, 257.5 perplexity estimate based on a held-out corpus of 1 documents with 2261 words +2024-07-25 12:41:03,734 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:03,735 - topic #0 (0.333): 0.015*"’" + 0.007*"Leeds" + 0.007*"needs" + 0.006*"well" + 0.004*"risk" + 0.004*"practice" + 0.004*"plans" + 0.004*"ensure" + 0.004*"21" + 0.004*"benefit" +2024-07-25 12:41:03,736 - topic #1 (0.333): 0.018*"’" + 0.008*"Leeds" + 0.007*"needs" + 0.006*"practice" + 0.006*"well" + 0.005*"risk" + 0.005*"protection" + 0.004*"ensure" + 0.004*"supported" + 0.004*"March" +2024-07-25 12:41:03,736 - topic #2 (0.333): 0.015*"’" + 0.007*"needs" + 0.007*"Leeds" + 0.006*"well" + 0.006*"risk" + 0.005*"plans" + 0.005*"4" + 0.004*"2022" + 0.004*"ensure" + 0.004*"including" +2024-07-25 12:41:03,736 - topic diff=0.773729, rho=1.000000 +2024-07-25 12:41:03,736 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:03.736608', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:05,366 - Inspection date 2022-02-21 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:05,366 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:05,367 - Inspection date 2022-02-21 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:05,367 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:05,367 - Inspection date 2022-02-21 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:05,367 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:05,368 - Inspection date 2022-02-21 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:05,368 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:05,368 - Inspection date 2022-02-21 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:05,369 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:05,369 - Inspection date 2022-02-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:05,369 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:06,675 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:06,677 - built Dictionary<932 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1950 corpus positions) +2024-07-25 12:41:06,677 - Dictionary lifecycle event {'msg': "built Dictionary<932 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1950 corpus positions)", 'datetime': '2024-07-25T12:41:06.677174', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:06,678 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:06,678 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:06,678 - using serial LDA version on this node +2024-07-25 12:41:06,678 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:06,679 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:06,684 - -7.870 per-word bound, 234.0 perplexity estimate based on a held-out corpus of 1 documents with 1950 words +2024-07-25 12:41:06,684 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:06,686 - topic #0 (0.333): 0.017*"’" + 0.009*"2021" + 0.009*"Leicester" + 0.007*"well" + 0.006*"needs" + 0.006*"good" + 0.006*"ensure" + 0.005*"including" + 0.005*"20" + 0.005*"1" +2024-07-25 12:41:06,686 - topic #1 (0.333): 0.018*"’" + 0.008*"well" + 0.007*"Leicester" + 0.007*"needs" + 0.006*"2021" + 0.006*"number" + 0.006*"ensure" + 0.005*"good" + 0.005*"20" + 0.005*"protection" +2024-07-25 12:41:06,687 - topic #2 (0.333): 0.023*"’" + 0.011*"well" + 0.009*"2021" + 0.007*"Leicester" + 0.007*"needs" + 0.006*"good" + 0.006*"1" + 0.005*"City" + 0.005*"number" + 0.005*"September" +2024-07-25 12:41:06,687 - topic diff=0.777580, rho=1.000000 +2024-07-25 12:41:06,687 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:06.687589', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:07,748 - Inspection date 2021-09-20 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:07,748 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:07,749 - Inspection date 2021-09-20 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:07,749 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:07,749 - Inspection date 2021-09-20 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:07,749 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:07,749 - Inspection date 2021-09-20 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:07,749 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:07,750 - Inspection date 2021-09-20 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:07,750 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:07,750 - Inspection date 2021-09-20 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:07,750 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:09,372 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:09,375 - built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2745 corpus positions) +2024-07-25 12:41:09,376 - Dictionary lifecycle event {'msg': "built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2745 corpus positions)", 'datetime': '2024-07-25T12:41:09.376016', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:09,377 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:09,377 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:09,377 - using serial LDA version on this node +2024-07-25 12:41:09,378 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:09,378 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:09,382 - -8.109 per-word bound, 276.2 perplexity estimate based on a held-out corpus of 1 documents with 2745 words +2024-07-25 12:41:09,382 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:09,383 - topic #0 (0.333): 0.016*"’" + 0.008*"well" + 0.008*"Leicestershire" + 0.006*"needs" + 0.006*"PAs" + 0.005*"experiences" + 0.005*"progress" + 0.005*"family" + 0.005*"ensure" + 0.004*"plans" +2024-07-25 12:41:09,383 - topic #1 (0.333): 0.021*"’" + 0.008*"well" + 0.006*"Leicestershire" + 0.006*"understand" + 0.006*"family" + 0.005*"risk" + 0.005*"plans" + 0.005*"needs" + 0.005*"experiences" + 0.005*"need" +2024-07-25 12:41:09,384 - topic #2 (0.333): 0.016*"’" + 0.010*"well" + 0.007*"need" + 0.006*"family" + 0.006*"Leicestershire" + 0.005*"experiences" + 0.004*"needs" + 0.004*"risk" + 0.004*"understand" + 0.004*"plans" +2024-07-25 12:41:09,384 - topic diff=0.811800, rho=1.000000 +2024-07-25 12:41:09,384 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:09.384406', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:10,338 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:10,338 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:10,339 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:10,339 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:10,339 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:10,339 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:10,339 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:10,340 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:10,340 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:10,340 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:10,340 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:10,340 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:12,134 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:12,137 - built Dictionary<1323 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2927 corpus positions) +2024-07-25 12:41:12,138 - Dictionary lifecycle event {'msg': "built Dictionary<1323 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2927 corpus positions)", 'datetime': '2024-07-25T12:41:12.138030', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:12,139 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:12,139 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:12,139 - using serial LDA version on this node +2024-07-25 12:41:12,140 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:12,140 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:12,144 - -8.188 per-word bound, 291.6 perplexity estimate based on a held-out corpus of 1 documents with 2927 words +2024-07-25 12:41:12,144 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:12,146 - topic #0 (0.333): 0.026*"’" + 0.009*"Lincolnshire" + 0.007*"needs" + 0.006*"well" + 0.006*"plans" + 0.005*"progress" + 0.005*"family" + 0.005*"28" + 0.004*"need" + 0.004*"number" +2024-07-25 12:41:12,146 - topic #1 (0.333): 0.019*"’" + 0.008*"needs" + 0.006*"well" + 0.006*"Lincolnshire" + 0.005*"24" + 0.005*"2023" + 0.005*"family" + 0.004*"progress" + 0.004*"education" + 0.004*"need" +2024-07-25 12:41:12,146 - topic #2 (0.333): 0.015*"’" + 0.006*"Lincolnshire" + 0.005*"needs" + 0.004*"well" + 0.003*"plans" + 0.003*"28" + 0.003*"progress" + 0.003*"provide" + 0.003*"supported" + 0.003*"effective" +2024-07-25 12:41:12,146 - topic diff=0.804649, rho=1.000000 +2024-07-25 12:41:12,146 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:12.146617', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:13,142 - Inspection date 2023-04-24 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:13,143 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:13,143 - Inspection date 2023-04-24 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:13,143 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:13,143 - Inspection date 2023-04-24 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:13,143 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:13,143 - Inspection date 2023-04-24 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:13,144 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:13,144 - Inspection date 2023-04-24 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:13,144 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:13,144 - Inspection date 2023-04-24 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:13,144 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:14,917 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:14,919 - built Dictionary<1134 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions) +2024-07-25 12:41:14,919 - Dictionary lifecycle event {'msg': "built Dictionary<1134 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)", 'datetime': '2024-07-25T12:41:14.919919', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:14,921 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:14,921 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:14,921 - using serial LDA version on this node +2024-07-25 12:41:14,922 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:14,922 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:14,925 - -7.992 per-word bound, 254.6 perplexity estimate based on a held-out corpus of 1 documents with 2720 words +2024-07-25 12:41:14,926 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:14,927 - topic #0 (0.333): 0.017*"’" + 0.009*"needs" + 0.007*"need" + 0.007*"always" + 0.006*"practice" + 0.006*"Liverpool" + 0.005*"2023" + 0.005*"timely" + 0.005*"quality" + 0.004*"health" +2024-07-25 12:41:14,927 - topic #1 (0.333): 0.025*"’" + 0.007*"quality" + 0.007*"needs" + 0.007*"need" + 0.006*"Liverpool" + 0.006*"always" + 0.006*"practice" + 0.005*"13" + 0.005*"protection" + 0.005*"24" +2024-07-25 12:41:14,927 - topic #2 (0.333): 0.012*"’" + 0.007*"practice" + 0.006*"always" + 0.005*"protection" + 0.005*"needs" + 0.005*"Liverpool" + 0.004*"quality" + 0.004*"need" + 0.004*"24" + 0.004*"receive" +2024-07-25 12:41:14,928 - topic diff=0.847131, rho=1.000000 +2024-07-25 12:41:14,928 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:14.928236', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:16,409 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:16,410 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:16,410 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:16,411 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:16,411 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:16,411 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:16,411 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:16,412 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:16,412 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:16,412 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:16,412 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:16,412 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:18,318 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:18,322 - built Dictionary<1193 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2610 corpus positions) +2024-07-25 12:41:18,322 - Dictionary lifecycle event {'msg': "built Dictionary<1193 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2610 corpus positions)", 'datetime': '2024-07-25T12:41:18.322805', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:18,324 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:18,325 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:18,325 - using serial LDA version on this node +2024-07-25 12:41:18,325 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:18,326 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:18,329 - -8.098 per-word bound, 274.0 perplexity estimate based on a held-out corpus of 1 documents with 2610 words +2024-07-25 12:41:18,330 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:18,331 - topic #0 (0.333): 0.024*"’" + 0.006*"needs" + 0.006*"carers" + 0.006*"good" + 0.006*"plans" + 0.005*"well" + 0.005*"practice" + 0.005*"timely" + 0.005*"e" + 0.005*"Dagenham" +2024-07-25 12:41:18,331 - topic #1 (0.333): 0.024*"’" + 0.009*"needs" + 0.006*"plans" + 0.006*"good" + 0.005*"progress" + 0.005*"information" + 0.004*"Barking" + 0.004*"London" + 0.004*"well" + 0.004*"carers" +2024-07-25 12:41:18,331 - topic #2 (0.333): 0.018*"’" + 0.008*"needs" + 0.006*"practice" + 0.005*"well" + 0.005*"plans" + 0.005*"information" + 0.005*"progress" + 0.004*"Barking" + 0.004*"good" + 0.004*"planning" +2024-07-25 12:41:18,332 - topic diff=0.799493, rho=1.000000 +2024-07-25 12:41:18,332 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:18.332195', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:19,210 - Inspection date 2023-07-10 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:19,210 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:19,210 - Inspection date 2023-07-10 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:19,210 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:19,211 - Inspection date 2023-07-10 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:19,211 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:19,211 - Inspection date 2023-07-10 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:19,211 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:19,211 - Inspection date 2023-07-10 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:19,211 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:19,212 - Inspection date 2023-07-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:19,212 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:20,946 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:20,949 - built Dictionary<1132 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2445 corpus positions) +2024-07-25 12:41:20,949 - Dictionary lifecycle event {'msg': "built Dictionary<1132 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2445 corpus positions)", 'datetime': '2024-07-25T12:41:20.949141', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:20,950 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:20,950 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:20,950 - using serial LDA version on this node +2024-07-25 12:41:20,951 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:20,951 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:20,954 - -8.054 per-word bound, 265.7 perplexity estimate based on a held-out corpus of 1 documents with 2445 words +2024-07-25 12:41:20,954 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:20,956 - topic #0 (0.333): 0.023*"’" + 0.009*"well" + 0.009*"needs" + 0.007*"Barnet" + 0.007*"plans" + 0.005*"10" + 0.005*"risk" + 0.005*"experiences" + 0.005*"effective" + 0.005*"14" +2024-07-25 12:41:20,956 - topic #1 (0.333): 0.018*"’" + 0.009*"needs" + 0.008*"Barnet" + 0.006*"plans" + 0.006*"well" + 0.004*"understand" + 0.004*"June" + 0.004*"information" + 0.004*"progress" + 0.004*"need" +2024-07-25 12:41:20,956 - topic #2 (0.333): 0.020*"’" + 0.008*"needs" + 0.007*"plans" + 0.006*"well" + 0.005*"Barnet" + 0.005*"experiences" + 0.005*"strong" + 0.004*"2024" + 0.004*"14" + 0.004*"information" +2024-07-25 12:41:20,956 - topic diff=0.791148, rho=1.000000 +2024-07-25 12:41:20,957 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:20.956982', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:22,246 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:22,246 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:22,247 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:22,247 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:22,247 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:22,248 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:22,248 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:22,248 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:22,248 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:22,248 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:22,249 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:22,249 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:23,870 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:23,872 - built Dictionary<1190 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2563 corpus positions) +2024-07-25 12:41:23,872 - Dictionary lifecycle event {'msg': "built Dictionary<1190 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2563 corpus positions)", 'datetime': '2024-07-25T12:41:23.872913', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:23,874 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:23,874 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:23,874 - using serial LDA version on this node +2024-07-25 12:41:23,874 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:23,875 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:23,878 - -8.104 per-word bound, 275.1 perplexity estimate based on a held-out corpus of 1 documents with 2563 words +2024-07-25 12:41:23,879 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:23,880 - topic #0 (0.333): 0.014*"’" + 0.007*"well" + 0.006*"need" + 0.006*"needs" + 0.005*"plans" + 0.004*"oversight" + 0.004*"helps" + 0.004*"make" + 0.004*"practice" + 0.004*"Bexley" +2024-07-25 12:41:23,880 - topic #1 (0.333): 0.022*"’" + 0.007*"effective" + 0.007*"well" + 0.006*"needs" + 0.005*"Bexley" + 0.005*"need" + 0.004*"plans" + 0.004*"make" + 0.004*"10" + 0.004*"clear" +2024-07-25 12:41:23,880 - topic #2 (0.333): 0.021*"’" + 0.007*"needs" + 0.006*"Bexley" + 0.006*"need" + 0.006*"plans" + 0.005*"well" + 0.005*"effective" + 0.005*"10" + 0.004*"practice" + 0.004*"6" +2024-07-25 12:41:23,881 - topic diff=0.781646, rho=1.000000 +2024-07-25 12:41:23,881 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:23.881261', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:24,858 - Inspection date 2023-02-06 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:24,858 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:24,858 - Inspection date 2023-02-06 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:24,858 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:24,858 - Inspection date 2023-02-06 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:24,858 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:24,859 - Inspection date 2023-02-06 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:24,859 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:24,859 - Inspection date 2023-02-06 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:24,859 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:24,859 - Inspection date 2023-02-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:24,859 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:26,691 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:26,693 - built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2371 corpus positions) +2024-07-25 12:41:26,693 - Dictionary lifecycle event {'msg': "built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2371 corpus positions)", 'datetime': '2024-07-25T12:41:26.693798', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:26,694 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:26,694 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:26,695 - using serial LDA version on this node +2024-07-25 12:41:26,695 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:26,695 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:26,699 - -7.930 per-word bound, 243.9 perplexity estimate based on a held-out corpus of 1 documents with 2371 words +2024-07-25 12:41:26,699 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:26,700 - topic #0 (0.333): 0.019*"’" + 0.008*"leaders" + 0.007*"well" + 0.007*"plans" + 0.006*"progress" + 0.006*"good" + 0.006*"information" + 0.005*"senior" + 0.005*"Brent" + 0.005*"practice" +2024-07-25 12:41:26,700 - topic #1 (0.333): 0.017*"’" + 0.009*"well" + 0.008*"leaders" + 0.006*"number" + 0.006*"quality" + 0.006*"plans" + 0.006*"Brent" + 0.006*"progress" + 0.005*"senior" + 0.005*"range" +2024-07-25 12:41:26,701 - topic #2 (0.333): 0.016*"’" + 0.009*"well" + 0.007*"progress" + 0.007*"good" + 0.007*"plans" + 0.006*"leaders" + 0.006*"practice" + 0.006*"needs" + 0.005*"quality" + 0.005*"number" +2024-07-25 12:41:26,701 - topic diff=0.816465, rho=1.000000 +2024-07-25 12:41:26,701 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:26.701452', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:27,774 - Inspection date 2023-02-20 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:27,775 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:27,775 - Inspection date 2023-02-20 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:27,775 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:27,775 - Inspection date 2023-02-20 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:27,776 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:27,776 - Inspection date 2023-02-20 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:27,776 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:27,776 - Inspection date 2023-02-20 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:27,776 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:27,777 - Inspection date 2023-02-20 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:27,777 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:29,532 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:29,535 - built Dictionary<1266 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2640 corpus positions) +2024-07-25 12:41:29,535 - Dictionary lifecycle event {'msg': "built Dictionary<1266 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2640 corpus positions)", 'datetime': '2024-07-25T12:41:29.535416', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:29,536 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:29,536 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:29,537 - using serial LDA version on this node +2024-07-25 12:41:29,537 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:29,537 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:29,541 - -8.179 per-word bound, 289.9 perplexity estimate based on a held-out corpus of 1 documents with 2640 words +2024-07-25 12:41:29,541 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:29,543 - topic #0 (0.333): 0.014*"’" + 0.005*"Bromley" + 0.005*"well" + 0.004*"needs" + 0.004*"health" + 0.004*"plans" + 0.004*"progress" + 0.003*"practice" + 0.003*"experiences" + 0.003*"education" +2024-07-25 12:41:29,543 - topic #1 (0.333): 0.019*"’" + 0.011*"Bromley" + 0.007*"well" + 0.007*"needs" + 0.006*"plans" + 0.006*"leaders" + 0.006*"practice" + 0.005*"education" + 0.005*"health" + 0.005*"13" +2024-07-25 12:41:29,543 - topic #2 (0.333): 0.024*"’" + 0.009*"Bromley" + 0.008*"needs" + 0.007*"well" + 0.005*"leaders" + 0.005*"plans" + 0.005*"practice" + 0.004*"education" + 0.004*"relationships" + 0.004*"carers" +2024-07-25 12:41:29,543 - topic diff=0.792251, rho=1.000000 +2024-07-25 12:41:29,543 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:29.543851', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:30,478 - Inspection date 2023-11-13 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:30,478 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:30,479 - Inspection date 2023-11-13 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:30,479 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:30,479 - Inspection date 2023-11-13 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:30,479 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:30,479 - Inspection date 2023-11-13 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:30,479 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:30,480 - Inspection date 2023-11-13 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:30,480 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:30,480 - Inspection date 2023-11-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:30,480 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:31,932 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:31,934 - built Dictionary<993 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1735 corpus positions) +2024-07-25 12:41:31,934 - Dictionary lifecycle event {'msg': "built Dictionary<993 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1735 corpus positions)", 'datetime': '2024-07-25T12:41:31.934809', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:31,935 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:31,935 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:31,936 - using serial LDA version on this node +2024-07-25 12:41:31,936 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:31,936 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:31,939 - -8.061 per-word bound, 267.1 perplexity estimate based on a held-out corpus of 1 documents with 1735 words +2024-07-25 12:41:31,940 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:31,941 - topic #0 (0.333): 0.010*"’" + 0.007*"Camden" + 0.006*"leaders" + 0.006*"practice" + 0.006*"well" + 0.005*"protection" + 0.005*"response" + 0.004*"needs" + 0.004*"appropriate" + 0.004*"25" +2024-07-25 12:41:31,941 - topic #1 (0.333): 0.012*"’" + 0.007*"leaders" + 0.007*"Camden" + 0.006*"needs" + 0.006*"practice" + 0.005*"protection" + 0.005*"well" + 0.005*"29" + 0.004*"appropriate" + 0.004*"progress" +2024-07-25 12:41:31,941 - topic #2 (0.333): 0.010*"’" + 0.007*"Camden" + 0.006*"practice" + 0.005*"leaders" + 0.005*"protection" + 0.005*"well" + 0.004*"response" + 0.004*"29" + 0.004*"April" + 0.004*"needs" +2024-07-25 12:41:31,941 - topic diff=0.701172, rho=1.000000 +2024-07-25 12:41:31,941 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:31.941946', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:32,960 - Inspection date 2022-04-25 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:32,960 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:32,960 - Inspection date 2022-04-25 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:32,960 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:32,961 - Inspection date 2022-04-25 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:32,961 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:32,961 - Inspection date 2022-04-25 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:32,961 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:32,961 - Inspection date 2022-04-25 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:32,961 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:32,962 - Inspection date 2022-04-25 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:32,962 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:34,707 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:34,710 - built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2209 corpus positions) +2024-07-25 12:41:34,710 - Dictionary lifecycle event {'msg': "built Dictionary<1046 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2209 corpus positions)", 'datetime': '2024-07-25T12:41:34.710218', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:34,711 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:34,711 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:34,711 - using serial LDA version on this node +2024-07-25 12:41:34,712 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:34,712 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:34,715 - -7.992 per-word bound, 254.5 perplexity estimate based on a held-out corpus of 1 documents with 2209 words +2024-07-25 12:41:34,715 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:34,717 - topic #0 (0.333): 0.009*"’" + 0.007*"well" + 0.005*"needs" + 0.005*"Croydon" + 0.005*"good" + 0.005*"ensure" + 0.004*"health" + 0.004*"improved" + 0.004*"need" + 0.004*"plans" +2024-07-25 12:41:34,717 - topic #1 (0.333): 0.015*"’" + 0.008*"needs" + 0.008*"well" + 0.007*"Croydon" + 0.007*"need" + 0.007*"quality" + 0.006*"Senior" + 0.006*"good" + 0.006*"effective" + 0.005*"plans" +2024-07-25 12:41:34,717 - topic #2 (0.333): 0.010*"’" + 0.007*"needs" + 0.006*"well" + 0.006*"ensure" + 0.004*"Senior" + 0.004*"improved" + 0.004*"quality" + 0.004*"However" + 0.004*"experiences" + 0.004*"plans" +2024-07-25 12:41:34,717 - topic diff=0.783366, rho=1.000000 +2024-07-25 12:41:34,717 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:34.717799', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:35,860 - Inspection date 2020-02-03 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:35,861 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:35,861 - Inspection date 2020-02-03 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:35,861 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:35,861 - Inspection date 2020-02-03 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:35,861 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:35,861 - Inspection date 2020-02-03 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:35,862 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:35,862 - Inspection date 2020-02-03 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:35,862 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:35,862 - Inspection date 2020-02-03 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:35,862 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:37,780 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:37,782 - built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2365 corpus positions) +2024-07-25 12:41:37,782 - Dictionary lifecycle event {'msg': "built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2365 corpus positions)", 'datetime': '2024-07-25T12:41:37.782728', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:37,783 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:37,783 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:37,784 - using serial LDA version on this node +2024-07-25 12:41:37,784 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:37,784 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:37,788 - -8.050 per-word bound, 265.1 perplexity estimate based on a held-out corpus of 1 documents with 2365 words +2024-07-25 12:41:37,788 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:37,789 - topic #0 (0.333): 0.014*"’" + 0.009*"Ealing" + 0.009*"well" + 0.006*"plans" + 0.006*"progress" + 0.006*"needs" + 0.005*"April" + 0.005*"3" + 0.005*"good" + 0.005*"need" +2024-07-25 12:41:37,790 - topic #1 (0.333): 0.017*"’" + 0.007*"Ealing" + 0.007*"well" + 0.006*"needs" + 0.005*"effective" + 0.005*"London" + 0.005*"progress" + 0.004*"need" + 0.004*"plans" + 0.004*"improve" +2024-07-25 12:41:37,790 - topic #2 (0.333): 0.020*"’" + 0.007*"Ealing" + 0.006*"progress" + 0.006*"well" + 0.006*"need" + 0.006*"needs" + 0.005*"effective" + 0.005*"plans" + 0.004*"experiences" + 0.004*"Borough" +2024-07-25 12:41:37,790 - topic diff=0.782891, rho=1.000000 +2024-07-25 12:41:37,790 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:37.790648', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:38,824 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:38,825 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:38,825 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:38,825 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:38,825 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:38,825 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:38,826 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:38,826 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:38,826 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:38,826 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:38,826 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:38,826 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:40,514 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:40,516 - built Dictionary<999 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2104 corpus positions) +2024-07-25 12:41:40,516 - Dictionary lifecycle event {'msg': "built Dictionary<999 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2104 corpus positions)", 'datetime': '2024-07-25T12:41:40.516648', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:40,517 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:40,517 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:40,518 - using serial LDA version on this node +2024-07-25 12:41:40,518 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:40,518 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:40,521 - -7.937 per-word bound, 245.1 perplexity estimate based on a held-out corpus of 1 documents with 2104 words +2024-07-25 12:41:40,522 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:40,523 - topic #0 (0.333): 0.012*"’" + 0.008*"good" + 0.008*"ensure" + 0.007*"needs" + 0.007*"Enfield" + 0.006*"quality" + 0.006*"effective" + 0.006*"clear" + 0.006*"range" + 0.005*"practice" +2024-07-25 12:41:40,523 - topic #1 (0.333): 0.015*"’" + 0.010*"needs" + 0.008*"practice" + 0.007*"clear" + 0.007*"ensure" + 0.007*"good" + 0.007*"Enfield" + 0.007*"effective" + 0.006*"timely" + 0.006*"leaders" +2024-07-25 12:41:40,523 - topic #2 (0.333): 0.012*"’" + 0.009*"practice" + 0.007*"ensure" + 0.007*"needs" + 0.007*"effective" + 0.006*"good" + 0.005*"quality" + 0.005*"leaders" + 0.005*"clear" + 0.005*"timely" +2024-07-25 12:41:40,523 - topic diff=0.781266, rho=1.000000 +2024-07-25 12:41:40,524 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:40.524008', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:41,465 - Inspection date 2019-03-04 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:41,465 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:41,465 - Inspection date 2019-03-04 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:41,465 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:41,465 - Inspection date 2019-03-04 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:41,466 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:41,466 - Inspection date 2019-03-04 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:41,466 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:41,466 - Inspection date 2019-03-04 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:41,466 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:41,466 - Inspection date 2019-03-04 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:41,466 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:42,971 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:42,973 - built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2078 corpus positions) +2024-07-25 12:41:42,973 - Dictionary lifecycle event {'msg': "built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2078 corpus positions)", 'datetime': '2024-07-25T12:41:42.973679', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:42,974 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:42,974 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:42,975 - using serial LDA version on this node +2024-07-25 12:41:42,975 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:42,975 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:42,979 - -7.986 per-word bound, 253.5 perplexity estimate based on a held-out corpus of 1 documents with 2078 words +2024-07-25 12:41:42,979 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:42,980 - topic #0 (0.333): 0.015*"’" + 0.010*"Greenwich" + 0.008*"well" + 0.007*"needs" + 0.006*"plans" + 0.005*"progress" + 0.004*"provide" + 0.004*"June" + 0.004*"carers" + 0.004*"2024" +2024-07-25 12:41:42,980 - topic #1 (0.333): 0.022*"’" + 0.014*"Greenwich" + 0.007*"plans" + 0.007*"needs" + 0.006*"well" + 0.005*"3" + 0.005*"progress" + 0.005*"quality" + 0.005*"2024" + 0.005*"7" +2024-07-25 12:41:42,981 - topic #2 (0.333): 0.014*"’" + 0.008*"Greenwich" + 0.007*"needs" + 0.006*"well" + 0.005*"7" + 0.005*"provide" + 0.004*"plans" + 0.004*"3" + 0.004*"progress" + 0.004*"Royal" +2024-07-25 12:41:42,981 - topic diff=0.759007, rho=1.000000 +2024-07-25 12:41:42,981 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:42.981373', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:44,022 - Inspection date 2024-06-03 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:44,022 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:44,023 - Inspection date 2024-06-03 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:44,023 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:44,023 - Inspection date 2024-06-03 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:44,023 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:44,024 - Inspection date 2024-06-03 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:44,024 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:44,024 - Inspection date 2024-06-03 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:44,024 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:44,024 - Inspection date 2024-06-03 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:44,024 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:45,989 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:45,991 - built Dictionary<1122 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2603 corpus positions) +2024-07-25 12:41:45,991 - Dictionary lifecycle event {'msg': "built Dictionary<1122 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2603 corpus positions)", 'datetime': '2024-07-25T12:41:45.991731', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:45,992 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:45,992 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:45,993 - using serial LDA version on this node +2024-07-25 12:41:45,993 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:45,993 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:45,997 - -7.996 per-word bound, 255.3 perplexity estimate based on a held-out corpus of 1 documents with 2603 words +2024-07-25 12:41:45,997 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:45,998 - topic #0 (0.333): 0.012*"’" + 0.009*"practice" + 0.007*"number" + 0.007*"within" + 0.006*"quality" + 0.006*"However" + 0.005*"effective" + 0.005*"protection" + 0.005*"plans" + 0.005*"needs" +2024-07-25 12:41:45,999 - topic #1 (0.333): 0.014*"’" + 0.010*"practice" + 0.006*"effective" + 0.006*"number" + 0.006*"needs" + 0.006*"small" + 0.005*"planning" + 0.005*"plans" + 0.005*"leaders" + 0.005*"carers" +2024-07-25 12:41:45,999 - topic #2 (0.333): 0.014*"’" + 0.010*"practice" + 0.008*"planning" + 0.006*"number" + 0.005*"plans" + 0.005*"including" + 0.005*"effective" + 0.005*"needs" + 0.005*"need" + 0.005*"small" +2024-07-25 12:41:45,999 - topic diff=0.836979, rho=1.000000 +2024-07-25 12:41:45,999 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:45.999484', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:47,250 - Inspection date 2019-11-11 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:47,251 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:47,251 - Inspection date 2019-11-11 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:47,251 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:47,251 - Inspection date 2019-11-11 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:47,251 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:47,251 - Inspection date 2019-11-11 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:47,251 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:47,252 - Inspection date 2019-11-11 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:47,252 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:47,252 - Inspection date 2019-11-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:47,252 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:49,219 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:49,222 - built Dictionary<1330 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions) +2024-07-25 12:41:49,222 - Dictionary lifecycle event {'msg': "built Dictionary<1330 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)", 'datetime': '2024-07-25T12:41:49.222578', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:49,223 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:49,224 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:49,224 - using serial LDA version on this node +2024-07-25 12:41:49,224 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:49,224 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:49,229 - -8.205 per-word bound, 295.0 perplexity estimate based on a held-out corpus of 1 documents with 2905 words +2024-07-25 12:41:49,229 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:49,230 - topic #0 (0.333): 0.016*"’" + 0.008*"well" + 0.006*"receive" + 0.006*"needs" + 0.005*"Fulham" + 0.005*"protection" + 0.004*"leaders" + 0.004*"need" + 0.004*"supported" + 0.004*"2024" +2024-07-25 12:41:49,230 - topic #1 (0.333): 0.011*"’" + 0.006*"well" + 0.005*"needs" + 0.005*"plans" + 0.005*"receive" + 0.004*"effective" + 0.004*"practice" + 0.004*"Hammersmith" + 0.004*"Leaders" + 0.004*"supported" +2024-07-25 12:41:49,231 - topic #2 (0.333): 0.016*"’" + 0.008*"well" + 0.006*"receive" + 0.005*"plans" + 0.005*"needs" + 0.005*"15" + 0.005*"Hammersmith" + 0.004*"effective" + 0.004*"Fulham" + 0.004*"11" +2024-07-25 12:41:49,231 - topic diff=0.798789, rho=1.000000 +2024-07-25 12:41:49,231 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:49.231388', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:50,115 - Inspection date 2024-03-11 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:50,116 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:50,116 - Inspection date 2024-03-11 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:50,116 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:50,116 - Inspection date 2024-03-11 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:50,116 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:50,116 - Inspection date 2024-03-11 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:50,117 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:50,117 - Inspection date 2024-03-11 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:50,117 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:50,117 - Inspection date 2024-03-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:50,117 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:52,277 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:52,281 - built Dictionary<1252 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2620 corpus positions) +2024-07-25 12:41:52,281 - Dictionary lifecycle event {'msg': "built Dictionary<1252 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2620 corpus positions)", 'datetime': '2024-07-25T12:41:52.281835', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:52,289 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:52,289 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:52,289 - using serial LDA version on this node +2024-07-25 12:41:52,290 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:52,290 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:52,309 - -8.176 per-word bound, 289.2 perplexity estimate based on a held-out corpus of 1 documents with 2620 words +2024-07-25 12:41:52,310 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:52,312 - topic #0 (0.333): 0.018*"’" + 0.010*"Haringey" + 0.010*"needs" + 0.007*"plans" + 0.006*"well" + 0.005*"need" + 0.005*"progress" + 0.005*"good" + 0.005*"24" + 0.005*"13" +2024-07-25 12:41:52,312 - topic #1 (0.333): 0.016*"’" + 0.007*"Haringey" + 0.007*"plans" + 0.006*"well" + 0.006*"good" + 0.006*"needs" + 0.005*"need" + 0.004*"education" + 0.004*"progress" + 0.004*"timely" +2024-07-25 12:41:52,313 - topic #2 (0.333): 0.010*"’" + 0.006*"plans" + 0.005*"Haringey" + 0.005*"needs" + 0.004*"progress" + 0.004*"good" + 0.004*"well" + 0.004*"need" + 0.004*"education" + 0.003*"leaders" +2024-07-25 12:41:52,313 - topic diff=0.796240, rho=1.000000 +2024-07-25 12:41:52,313 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.02s', 'datetime': '2024-07-25T12:41:52.313768', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:53,422 - Inspection date 2023-02-13 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:53,422 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:53,422 - Inspection date 2023-02-13 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:53,422 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:53,422 - Inspection date 2023-02-13 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:53,423 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:53,423 - Inspection date 2023-02-13 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:53,423 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:53,423 - Inspection date 2023-02-13 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:53,423 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:53,423 - Inspection date 2023-02-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:53,423 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:55,072 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:55,074 - built Dictionary<942 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1732 corpus positions) +2024-07-25 12:41:55,074 - Dictionary lifecycle event {'msg': "built Dictionary<942 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1732 corpus positions)", 'datetime': '2024-07-25T12:41:55.074517', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:55,075 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:55,075 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:55,075 - using serial LDA version on this node +2024-07-25 12:41:55,076 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:55,076 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:55,079 - -7.975 per-word bound, 251.7 perplexity estimate based on a held-out corpus of 1 documents with 1732 words +2024-07-25 12:41:55,079 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:55,080 - topic #0 (0.333): 0.013*"’" + 0.011*"good" + 0.008*"well" + 0.007*"needs" + 0.006*"impact" + 0.005*"need" + 0.005*"practice" + 0.005*"experiences" + 0.004*"plans" + 0.004*"protection" +2024-07-25 12:41:55,081 - topic #1 (0.333): 0.013*"’" + 0.012*"good" + 0.009*"needs" + 0.009*"well" + 0.006*"plans" + 0.006*"early" + 0.006*"protection" + 0.005*"practice" + 0.005*"impact" + 0.005*"need" +2024-07-25 12:41:55,081 - topic #2 (0.333): 0.008*"’" + 0.008*"good" + 0.007*"well" + 0.006*"needs" + 0.005*"impact" + 0.005*"plans" + 0.004*"need" + 0.004*"protection" + 0.004*"early" + 0.004*"practice" +2024-07-25 12:41:55,081 - topic diff=0.702210, rho=1.000000 +2024-07-25 12:41:55,081 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:55.081580', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:56,992 - Inspection date 2020-02-10 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:56,993 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:56,993 - Inspection date 2020-02-10 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:56,993 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:56,993 - Inspection date 2020-02-10 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:56,994 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:56,994 - Inspection date 2020-02-10 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:56,994 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:56,994 - Inspection date 2020-02-10 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:56,995 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:56,995 - Inspection date 2020-02-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:56,995 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:58,819 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:41:58,822 - built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2243 corpus positions) +2024-07-25 12:41:58,823 - Dictionary lifecycle event {'msg': "built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2243 corpus positions)", 'datetime': '2024-07-25T12:41:58.822972', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:58,824 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:41:58,824 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:41:58,825 - using serial LDA version on this node +2024-07-25 12:41:58,825 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:41:58,826 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:41:58,831 - -8.007 per-word bound, 257.3 perplexity estimate based on a held-out corpus of 1 documents with 2243 words +2024-07-25 12:41:58,832 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:41:58,834 - topic #0 (0.333): 0.020*"’" + 0.011*"Havering" + 0.007*"plans" + 0.006*"quality" + 0.006*"effective" + 0.004*"oversight" + 0.004*"needs" + 0.004*"many" + 0.004*"2023" + 0.004*"December" +2024-07-25 12:41:58,834 - topic #1 (0.333): 0.019*"’" + 0.014*"Havering" + 0.011*"quality" + 0.006*"plans" + 0.005*"effective" + 0.005*"oversight" + 0.005*"needs" + 0.005*"22" + 0.004*"practice" + 0.004*"11" +2024-07-25 12:41:58,834 - topic #2 (0.333): 0.014*"’" + 0.009*"Havering" + 0.009*"quality" + 0.007*"plans" + 0.006*"oversight" + 0.005*"11" + 0.005*"needs" + 0.004*"effective" + 0.004*"practice" + 0.004*"well" +2024-07-25 12:41:58,834 - topic diff=0.764325, rho=1.000000 +2024-07-25 12:41:58,835 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:41:58.835087', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:41:59,818 - Inspection date 2023-12-11 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:41:59,819 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:59,819 - Inspection date 2023-12-11 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:41:59,819 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:59,819 - Inspection date 2023-12-11 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:41:59,819 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:59,820 - Inspection date 2023-12-11 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:41:59,820 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:59,820 - Inspection date 2023-12-11 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:41:59,820 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:41:59,820 - Inspection date 2023-12-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:41:59,820 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:01,620 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:01,622 - built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2511 corpus positions) +2024-07-25 12:42:01,622 - Dictionary lifecycle event {'msg': "built Dictionary<1161 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2511 corpus positions)", 'datetime': '2024-07-25T12:42:01.622956', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:01,624 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:01,624 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:01,624 - using serial LDA version on this node +2024-07-25 12:42:01,624 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:01,624 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:01,628 - -8.080 per-word bound, 270.6 perplexity estimate based on a held-out corpus of 1 documents with 2511 words +2024-07-25 12:42:01,628 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:01,630 - topic #0 (0.333): 0.021*"’" + 0.009*"well" + 0.008*"Hillingdon" + 0.007*"needs" + 0.007*"plans" + 0.005*"need" + 0.005*"team" + 0.004*"6" + 0.004*"senior" + 0.004*"improve" +2024-07-25 12:42:01,630 - topic #1 (0.333): 0.017*"’" + 0.010*"needs" + 0.008*"plans" + 0.007*"well" + 0.006*"Hillingdon" + 0.004*"experiences" + 0.004*"2" + 0.004*"leaders" + 0.004*"need" + 0.004*"6" +2024-07-25 12:42:01,630 - topic #2 (0.333): 0.015*"’" + 0.012*"needs" + 0.009*"Hillingdon" + 0.008*"plans" + 0.006*"well" + 0.005*"team" + 0.004*"October" + 0.004*"leaders" + 0.004*"2" + 0.004*"6" +2024-07-25 12:42:01,630 - topic diff=0.794642, rho=1.000000 +2024-07-25 12:42:01,630 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:01.630727', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:02,816 - Inspection date 2023-10-02 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:02,816 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:02,817 - Inspection date 2023-10-02 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:02,817 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:02,822 - Inspection date 2023-10-02 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:02,822 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:02,823 - Inspection date 2023-10-02 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:02,823 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:02,823 - Inspection date 2023-10-02 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:02,824 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:02,825 - Inspection date 2023-10-02 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:02,825 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:04,548 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:04,550 - built Dictionary<1070 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2271 corpus positions) +2024-07-25 12:42:04,550 - Dictionary lifecycle event {'msg': "built Dictionary<1070 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2271 corpus positions)", 'datetime': '2024-07-25T12:42:04.550834', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:04,551 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:04,552 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:04,552 - using serial LDA version on this node +2024-07-25 12:42:04,552 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:04,552 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:04,556 - -8.005 per-word bound, 256.9 perplexity estimate based on a held-out corpus of 1 documents with 2271 words +2024-07-25 12:42:04,556 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:04,557 - topic #0 (0.333): 0.018*"’" + 0.011*"needs" + 0.008*"effective" + 0.007*"well" + 0.007*"Hounslow" + 0.006*"timely" + 0.005*"oversight" + 0.005*"plans" + 0.005*"20" + 0.004*"strong" +2024-07-25 12:42:04,557 - topic #1 (0.333): 0.020*"’" + 0.013*"well" + 0.012*"needs" + 0.008*"effective" + 0.007*"Hounslow" + 0.007*"timely" + 0.005*"16" + 0.005*"plans" + 0.004*"training" + 0.004*"experiences" +2024-07-25 12:42:04,558 - topic #2 (0.333): 0.022*"’" + 0.009*"well" + 0.008*"needs" + 0.007*"Hounslow" + 0.006*"plans" + 0.006*"effective" + 0.005*"timely" + 0.004*"strong" + 0.004*"progress" + 0.004*"experiences" +2024-07-25 12:42:04,558 - topic diff=0.784335, rho=1.000000 +2024-07-25 12:42:04,558 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:04.558233', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:05,510 - Inspection date 2023-10-16 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:05,510 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:05,510 - Inspection date 2023-10-16 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:05,511 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:05,511 - Inspection date 2023-10-16 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:05,511 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:05,511 - Inspection date 2023-10-16 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:05,511 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:05,512 - Inspection date 2023-10-16 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:05,512 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:05,512 - Inspection date 2023-10-16 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:05,512 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:07,034 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:07,036 - built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1982 corpus positions) +2024-07-25 12:42:07,036 - Dictionary lifecycle event {'msg': "built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1982 corpus positions)", 'datetime': '2024-07-25T12:42:07.036964', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:07,037 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:07,038 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:07,038 - using serial LDA version on this node +2024-07-25 12:42:07,038 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:07,038 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:07,042 - -7.927 per-word bound, 243.4 perplexity estimate based on a held-out corpus of 1 documents with 1982 words +2024-07-25 12:42:07,042 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:07,043 - topic #0 (0.333): 0.011*"’" + 0.010*"well" + 0.008*"needs" + 0.007*"quality" + 0.005*"highly" + 0.005*"good" + 0.005*"risk" + 0.005*"plans" + 0.005*"leaders" + 0.005*"effective" +2024-07-25 12:42:07,043 - topic #1 (0.333): 0.014*"’" + 0.011*"needs" + 0.010*"well" + 0.008*"good" + 0.007*"highly" + 0.006*"plans" + 0.006*"effective" + 0.005*"quality" + 0.005*"leaders" + 0.004*"practice" +2024-07-25 12:42:07,043 - topic #2 (0.333): 0.012*"needs" + 0.012*"’" + 0.010*"well" + 0.008*"plans" + 0.006*"Islington" + 0.006*"leaders" + 0.005*"highly" + 0.005*"effective" + 0.005*"practice" + 0.005*"quality" +2024-07-25 12:42:07,044 - topic diff=0.740703, rho=1.000000 +2024-07-25 12:42:07,044 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:07.044179', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:09,375 - Inspection date 2020-03-09 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:09,376 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:09,376 - Inspection date 2020-03-09 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:09,377 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:09,377 - Inspection date 2020-03-09 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:09,377 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:09,377 - Inspection date 2020-03-09 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:09,378 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:09,378 - Inspection date 2020-03-09 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:09,378 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:09,378 - Inspection date 2020-03-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:09,378 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:10,822 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:10,824 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2090 corpus positions) +2024-07-25 12:42:10,824 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2090 corpus positions)", 'datetime': '2024-07-25T12:42:10.824557', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:10,825 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:10,825 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:10,825 - using serial LDA version on this node +2024-07-25 12:42:10,826 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:10,826 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:10,829 - -7.909 per-word bound, 240.3 perplexity estimate based on a held-out corpus of 1 documents with 2090 words +2024-07-25 12:42:10,829 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:10,830 - topic #0 (0.333): 0.016*"’" + 0.008*"needs" + 0.008*"well" + 0.008*"good" + 0.007*"plans" + 0.006*"impact" + 0.006*"Lambeth" + 0.006*"progress" + 0.005*"4" + 0.005*"need" +2024-07-25 12:42:10,831 - topic #1 (0.333): 0.013*"’" + 0.010*"needs" + 0.008*"well" + 0.008*"plans" + 0.007*"Lambeth" + 0.006*"good" + 0.006*"need" + 0.005*"progress" + 0.005*"impact" + 0.005*"leaders" +2024-07-25 12:42:10,831 - topic #2 (0.333): 0.016*"’" + 0.009*"needs" + 0.008*"well" + 0.007*"plans" + 0.006*"good" + 0.006*"Lambeth" + 0.006*"need" + 0.006*"progress" + 0.005*"leaders" + 0.005*"24" +2024-07-25 12:42:10,831 - topic diff=0.796913, rho=1.000000 +2024-07-25 12:42:10,831 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:10.831568', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:11,776 - Inspection date 2022-10-24 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:11,776 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:11,777 - Inspection date 2022-10-24 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:11,777 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:11,777 - Inspection date 2022-10-24 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:11,777 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:11,777 - Inspection date 2022-10-24 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:11,777 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:11,778 - Inspection date 2022-10-24 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:11,778 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:11,778 - Inspection date 2022-10-24 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:11,778 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:13,202 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:13,207 - built Dictionary<1115 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2352 corpus positions) +2024-07-25 12:42:13,207 - Dictionary lifecycle event {'msg': "built Dictionary<1115 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2352 corpus positions)", 'datetime': '2024-07-25T12:42:13.207393', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:13,208 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:13,208 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:13,208 - using serial LDA version on this node +2024-07-25 12:42:13,209 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:13,209 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:13,213 - -8.051 per-word bound, 265.2 perplexity estimate based on a held-out corpus of 1 documents with 2352 words +2024-07-25 12:42:13,213 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:13,214 - topic #0 (0.333): 0.014*"’" + 0.008*"needs" + 0.008*"well" + 0.006*"plans" + 0.005*"Lewisham" + 0.005*"progress" + 0.005*"effective" + 0.004*"good" + 0.004*"2023" + 0.004*"December" +2024-07-25 12:42:13,214 - topic #1 (0.333): 0.021*"’" + 0.009*"well" + 0.007*"effective" + 0.007*"plans" + 0.007*"needs" + 0.006*"Lewisham" + 0.006*"4" + 0.005*"progress" + 0.005*"leaders" + 0.005*"receive" +2024-07-25 12:42:13,214 - topic #2 (0.333): 0.017*"’" + 0.007*"well" + 0.006*"needs" + 0.006*"plans" + 0.006*"effective" + 0.006*"Lewisham" + 0.005*"good" + 0.005*"arrangements" + 0.005*"progress" + 0.005*"need" +2024-07-25 12:42:13,214 - topic diff=0.767255, rho=1.000000 +2024-07-25 12:42:13,215 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:13.215029', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:14,251 - Inspection date 2023-12-04 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:14,252 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:14,252 - Inspection date 2023-12-04 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:14,253 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:14,253 - Inspection date 2023-12-04 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:14,253 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:14,253 - Inspection date 2023-12-04 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:14,253 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:14,254 - Inspection date 2023-12-04 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:14,254 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:14,254 - Inspection date 2023-12-04 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:14,254 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:15,877 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:15,879 - built Dictionary<1015 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2032 corpus positions) +2024-07-25 12:42:15,879 - Dictionary lifecycle event {'msg': "built Dictionary<1015 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2032 corpus positions)", 'datetime': '2024-07-25T12:42:15.879220', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:15,880 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:15,880 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:15,880 - using serial LDA version on this node +2024-07-25 12:42:15,880 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:15,881 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:15,884 - -7.989 per-word bound, 254.1 perplexity estimate based on a held-out corpus of 1 documents with 2032 words +2024-07-25 12:42:15,884 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:15,885 - topic #0 (0.333): 0.016*"’" + 0.006*"well" + 0.005*"needs" + 0.005*"Merton" + 0.005*"progress" + 0.005*"plans" + 0.004*"good" + 0.004*"early" + 0.004*"family" + 0.004*"4" +2024-07-25 12:42:15,886 - topic #1 (0.333): 0.016*"’" + 0.010*"well" + 0.007*"needs" + 0.006*"Merton" + 0.005*"plans" + 0.005*"ensure" + 0.005*"family" + 0.004*"across" + 0.004*"information" + 0.004*"2022" +2024-07-25 12:42:15,886 - topic #2 (0.333): 0.014*"’" + 0.007*"Merton" + 0.007*"well" + 0.005*"28" + 0.004*"needs" + 0.004*"progress" + 0.004*"risk" + 0.004*"family" + 0.004*"highly" + 0.004*"4" +2024-07-25 12:42:15,886 - topic diff=0.755131, rho=1.000000 +2024-07-25 12:42:15,886 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:15.886538', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:16,830 - Inspection date 2022-02-28 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:16,830 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:16,830 - Inspection date 2022-02-28 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:16,830 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:16,830 - Inspection date 2022-02-28 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:16,830 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:16,831 - Inspection date 2022-02-28 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:16,831 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:16,831 - Inspection date 2022-02-28 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:16,831 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:16,831 - Inspection date 2022-02-28 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:16,831 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:18,534 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:18,537 - built Dictionary<1153 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2540 corpus positions) +2024-07-25 12:42:18,537 - Dictionary lifecycle event {'msg': "built Dictionary<1153 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2540 corpus positions)", 'datetime': '2024-07-25T12:42:18.537293', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:18,538 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:18,538 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:18,538 - using serial LDA version on this node +2024-07-25 12:42:18,539 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:18,539 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:18,543 - -8.062 per-word bound, 267.2 perplexity estimate based on a held-out corpus of 1 documents with 2540 words +2024-07-25 12:42:18,543 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:18,544 - topic #0 (0.333): 0.018*"’" + 0.007*"needs" + 0.007*"need" + 0.007*"progress" + 0.006*"Newham" + 0.006*"effective" + 0.006*"plans" + 0.005*"risks" + 0.004*"good" + 0.004*"18" +2024-07-25 12:42:18,544 - topic #1 (0.333): 0.019*"’" + 0.009*"needs" + 0.008*"Newham" + 0.007*"plans" + 0.007*"practice" + 0.006*"effective" + 0.006*"progress" + 0.005*"good" + 0.005*"Leaders" + 0.005*"need" +2024-07-25 12:42:18,545 - topic #2 (0.333): 0.020*"’" + 0.008*"needs" + 0.007*"practice" + 0.006*"Newham" + 0.006*"need" + 0.005*"progress" + 0.005*"plans" + 0.005*"good" + 0.005*"effective" + 0.004*"well" +2024-07-25 12:42:18,545 - topic diff=0.773736, rho=1.000000 +2024-07-25 12:42:18,545 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:18.545252', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:19,574 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:19,575 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:19,575 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:19,575 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:19,575 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:19,575 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:19,576 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:19,576 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:19,576 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:19,576 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:19,576 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:19,576 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:21,842 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:21,844 - built Dictionary<1204 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2389 corpus positions) +2024-07-25 12:42:21,844 - Dictionary lifecycle event {'msg': "built Dictionary<1204 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2389 corpus positions)", 'datetime': '2024-07-25T12:42:21.844759', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:21,845 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:21,846 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:21,846 - using serial LDA version on this node +2024-07-25 12:42:21,846 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:21,846 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:21,850 - -8.163 per-word bound, 286.7 perplexity estimate based on a held-out corpus of 1 documents with 2389 words +2024-07-25 12:42:21,850 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:21,852 - topic #0 (0.333): 0.009*"’" + 0.007*"Redbridge" + 0.005*"practice" + 0.005*"needs" + 0.005*"supported" + 0.005*"carers" + 0.005*"leaders" + 0.004*"well" + 0.004*"effective" + 0.004*"family" +2024-07-25 12:42:21,852 - topic #1 (0.333): 0.012*"’" + 0.007*"Redbridge" + 0.005*"needs" + 0.004*"protection" + 0.004*"family" + 0.004*"practice" + 0.004*"supported" + 0.004*"risk" + 0.004*"14" + 0.004*"2024" +2024-07-25 12:42:21,852 - topic #2 (0.333): 0.019*"’" + 0.007*"Redbridge" + 0.005*"carers" + 0.005*"early" + 0.005*"supported" + 0.005*"needs" + 0.005*"family" + 0.005*"leaders" + 0.005*"practice" + 0.004*"risk" +2024-07-25 12:42:21,853 - topic diff=0.755453, rho=1.000000 +2024-07-25 12:42:21,853 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:21.853246', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:22,787 - Inspection date 2024-06-10 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:22,788 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:22,788 - Inspection date 2024-06-10 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:22,788 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:22,788 - Inspection date 2024-06-10 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:22,788 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:22,788 - Inspection date 2024-06-10 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:22,789 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:22,789 - Inspection date 2024-06-10 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:22,789 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:22,789 - Inspection date 2024-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:22,789 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:24,196 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:24,200 - built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1818 corpus positions) +2024-07-25 12:42:24,200 - Dictionary lifecycle event {'msg': "built Dictionary<968 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1818 corpus positions)", 'datetime': '2024-07-25T12:42:24.200720', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:24,202 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:24,202 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:24,202 - using serial LDA version on this node +2024-07-25 12:42:24,203 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:24,203 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:24,209 - -7.987 per-word bound, 253.7 perplexity estimate based on a held-out corpus of 1 documents with 1818 words +2024-07-25 12:42:24,209 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:24,212 - topic #0 (0.333): 0.013*"’" + 0.011*"well" + 0.008*"Richmond" + 0.006*"needs" + 0.006*"good" + 0.006*"team" + 0.005*"ensure" + 0.005*"supported" + 0.004*"strong" + 0.004*"range" +2024-07-25 12:42:24,212 - topic #1 (0.333): 0.019*"’" + 0.011*"well" + 0.009*"needs" + 0.008*"Richmond" + 0.007*"supported" + 0.006*"need" + 0.005*"good" + 0.005*"team" + 0.005*"additional" + 0.005*"2022" +2024-07-25 12:42:24,212 - topic #2 (0.333): 0.013*"’" + 0.010*"well" + 0.008*"Richmond" + 0.006*"needs" + 0.006*"need" + 0.005*"team" + 0.004*"ensure" + 0.004*"strong" + 0.004*"good" + 0.004*"additional" +2024-07-25 12:42:24,212 - topic diff=0.740968, rho=1.000000 +2024-07-25 12:42:24,213 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:24.213191', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:25,085 - Inspection date 2022-01-31 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:25,085 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:25,086 - Inspection date 2022-01-31 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:25,086 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:25,086 - Inspection date 2022-01-31 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:25,086 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:25,086 - Inspection date 2022-01-31 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:25,087 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:25,087 - Inspection date 2022-01-31 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:25,087 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:25,087 - Inspection date 2022-01-31 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:25,087 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:26,314 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:26,316 - built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions) +2024-07-25 12:42:26,317 - Dictionary lifecycle event {'msg': "built Dictionary<945 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1878 corpus positions)", 'datetime': '2024-07-25T12:42:26.317011', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:26,317 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:26,318 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:26,318 - using serial LDA version on this node +2024-07-25 12:42:26,318 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:26,318 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:26,321 - -7.916 per-word bound, 241.5 perplexity estimate based on a held-out corpus of 1 documents with 1878 words +2024-07-25 12:42:26,322 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:26,323 - topic #0 (0.333): 0.010*"’" + 0.006*"Southwark" + 0.006*"well" + 0.005*"good" + 0.005*"needs" + 0.004*"plans" + 0.004*"need" + 0.004*"leaders" + 0.004*"practice" + 0.004*"receive" +2024-07-25 12:42:26,323 - topic #1 (0.333): 0.012*"’" + 0.010*"Southwark" + 0.009*"good" + 0.007*"well" + 0.007*"progress" + 0.006*"plans" + 0.006*"needs" + 0.005*"receive" + 0.004*"need" + 0.004*"education" +2024-07-25 12:42:26,323 - topic #2 (0.333): 0.024*"’" + 0.010*"Southwark" + 0.009*"needs" + 0.008*"well" + 0.008*"good" + 0.007*"effective" + 0.006*"need" + 0.006*"strong" + 0.006*"Leaders" + 0.006*"progress" +2024-07-25 12:42:26,323 - topic diff=0.778328, rho=1.000000 +2024-07-25 12:42:26,324 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:26.324037', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:27,628 - Inspection date 2022-09-26 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:27,628 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:27,628 - Inspection date 2022-09-26 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:27,628 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:27,628 - Inspection date 2022-09-26 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:27,629 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:27,629 - Inspection date 2022-09-26 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:27,629 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:27,629 - Inspection date 2022-09-26 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:27,629 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:27,629 - Inspection date 2022-09-26 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:27,630 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:28,932 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:28,934 - built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1847 corpus positions) +2024-07-25 12:42:28,934 - Dictionary lifecycle event {'msg': "built Dictionary<976 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1847 corpus positions)", 'datetime': '2024-07-25T12:42:28.934274', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:28,935 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:28,935 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:28,935 - using serial LDA version on this node +2024-07-25 12:42:28,936 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:28,936 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:28,939 - -7.986 per-word bound, 253.5 perplexity estimate based on a held-out corpus of 1 documents with 1847 words +2024-07-25 12:42:28,939 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:28,941 - topic #0 (0.333): 0.016*"’" + 0.007*"well" + 0.006*"Sutton" + 0.006*"needs" + 0.005*"good" + 0.005*"progress" + 0.005*"receive" + 0.004*"effective" + 0.004*"protection" + 0.004*"10" +2024-07-25 12:42:28,941 - topic #1 (0.333): 0.020*"’" + 0.007*"well" + 0.006*"needs" + 0.006*"6" + 0.005*"supported" + 0.005*"Sutton" + 0.005*"good" + 0.005*"effective" + 0.005*"receive" + 0.004*"need" +2024-07-25 12:42:28,941 - topic #2 (0.333): 0.014*"’" + 0.006*"Sutton" + 0.006*"well" + 0.006*"progress" + 0.005*"needs" + 0.005*"understand" + 0.005*"effective" + 0.004*"receive" + 0.004*"leaders" + 0.004*"December" +2024-07-25 12:42:28,941 - topic diff=0.721449, rho=1.000000 +2024-07-25 12:42:28,941 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:28.941797', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:30,906 - Inspection date 2021-12-06 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:30,906 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:30,907 - Inspection date 2021-12-06 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:30,907 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:30,907 - Inspection date 2021-12-06 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:30,907 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:30,907 - Inspection date 2021-12-06 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:30,908 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:30,908 - Inspection date 2021-12-06 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:30,908 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:30,908 - Inspection date 2021-12-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:30,908 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:32,551 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:32,556 - built Dictionary<1194 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions) +2024-07-25 12:42:32,559 - Dictionary lifecycle event {'msg': "built Dictionary<1194 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2465 corpus positions)", 'datetime': '2024-07-25T12:42:32.559383', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:32,561 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:32,561 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:32,562 - using serial LDA version on this node +2024-07-25 12:42:32,562 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:32,562 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:32,569 - -8.135 per-word bound, 281.0 perplexity estimate based on a held-out corpus of 1 documents with 2465 words +2024-07-25 12:42:32,569 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:32,572 - topic #0 (0.333): 0.016*"’" + 0.007*"plans" + 0.007*"effective" + 0.006*"‘" + 0.006*"good" + 0.006*"progress" + 0.006*"early" + 0.005*"including" + 0.005*"well" + 0.005*"practice" +2024-07-25 12:42:32,572 - topic #1 (0.333): 0.011*"’" + 0.007*"good" + 0.006*"well" + 0.006*"effective" + 0.006*"practice" + 0.005*"plans" + 0.005*"need" + 0.005*"‘" + 0.005*"early" + 0.005*"needs" +2024-07-25 12:42:32,573 - topic #2 (0.333): 0.017*"’" + 0.007*"good" + 0.005*"plans" + 0.005*"needs" + 0.005*"well" + 0.005*"‘" + 0.005*"effective" + 0.005*"practice" + 0.004*"carers" + 0.004*"need" +2024-07-25 12:42:32,573 - topic diff=0.770864, rho=1.000000 +2024-07-25 12:42:32,573 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:32.573596', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:33,886 - Inspection date 2019-06-10 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:33,886 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:33,886 - Inspection date 2019-06-10 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:33,886 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:33,887 - Inspection date 2019-06-10 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:33,887 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:33,887 - Inspection date 2019-06-10 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:33,887 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:33,887 - Inspection date 2019-06-10 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:33,887 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:33,888 - Inspection date 2019-06-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:33,888 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:35,172 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:35,175 - built Dictionary<1036 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions) +2024-07-25 12:42:35,175 - Dictionary lifecycle event {'msg': "built Dictionary<1036 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2199 corpus positions)", 'datetime': '2024-07-25T12:42:35.175234', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:35,176 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:35,176 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:35,176 - using serial LDA version on this node +2024-07-25 12:42:35,177 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:35,177 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:35,180 - -7.972 per-word bound, 251.1 perplexity estimate based on a held-out corpus of 1 documents with 2199 words +2024-07-25 12:42:35,180 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:35,181 - topic #0 (0.333): 0.015*"’" + 0.010*"well" + 0.009*"good" + 0.009*"needs" + 0.007*"effective" + 0.007*"need" + 0.005*"plans" + 0.005*"timely" + 0.005*"risk" + 0.004*"strong" +2024-07-25 12:42:35,182 - topic #1 (0.333): 0.015*"well" + 0.012*"’" + 0.009*"good" + 0.008*"effective" + 0.008*"needs" + 0.005*"need" + 0.005*"plans" + 0.005*"ensure" + 0.004*"progress" + 0.004*"timely" +2024-07-25 12:42:35,182 - topic #2 (0.333): 0.016*"’" + 0.010*"well" + 0.010*"needs" + 0.006*"effective" + 0.006*"need" + 0.005*"plans" + 0.005*"good" + 0.005*"risk" + 0.005*"timely" + 0.004*"appropriately" +2024-07-25 12:42:35,182 - topic diff=0.781431, rho=1.000000 +2024-07-25 12:42:35,182 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:35.182573', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:36,155 - Inspection date 2019-01-28 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:36,155 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:36,155 - Inspection date 2019-01-28 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:36,155 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:36,156 - Inspection date 2019-01-28 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:36,156 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:36,156 - Inspection date 2019-01-28 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:36,156 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:36,156 - Inspection date 2019-01-28 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:36,156 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:36,156 - Inspection date 2019-01-28 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:36,157 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:37,397 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:37,398 - built Dictionary<884 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1772 corpus positions) +2024-07-25 12:42:37,399 - Dictionary lifecycle event {'msg': "built Dictionary<884 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1772 corpus positions)", 'datetime': '2024-07-25T12:42:37.399101', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:37,400 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:37,400 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:37,400 - using serial LDA version on this node +2024-07-25 12:42:37,400 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:37,400 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:37,403 - -7.851 per-word bound, 230.8 perplexity estimate based on a held-out corpus of 1 documents with 1772 words +2024-07-25 12:42:37,404 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:37,405 - topic #0 (0.333): 0.009*"’" + 0.005*"well" + 0.005*"progress" + 0.005*"ensure" + 0.005*"needs" + 0.005*"quality" + 0.004*"improve" + 0.004*"Wandsworth" + 0.004*"Senior" + 0.004*"practice" +2024-07-25 12:42:37,405 - topic #1 (0.333): 0.009*"’" + 0.006*"Wandsworth" + 0.006*"protection" + 0.005*"needs" + 0.005*"progress" + 0.005*"well" + 0.005*"good" + 0.005*"18" + 0.005*"supported" + 0.005*"effective" +2024-07-25 12:42:37,405 - topic #2 (0.333): 0.015*"’" + 0.008*"well" + 0.006*"Senior" + 0.006*"practice" + 0.005*"needs" + 0.005*"7" + 0.005*"progress" + 0.005*"team" + 0.005*"effective" + 0.005*"protection" +2024-07-25 12:42:37,405 - topic diff=0.758998, rho=1.000000 +2024-07-25 12:42:37,405 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:37.405901', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:38,374 - Inspection date 2022-11-07 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:38,374 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:38,375 - Inspection date 2022-11-07 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:38,375 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:38,375 - Inspection date 2022-11-07 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:38,376 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:38,376 - Inspection date 2022-11-07 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:38,376 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:38,377 - Inspection date 2022-11-07 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:38,377 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:38,377 - Inspection date 2022-11-07 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:38,377 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:40,186 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:40,188 - built Dictionary<1136 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2101 corpus positions) +2024-07-25 12:42:40,188 - Dictionary lifecycle event {'msg': "built Dictionary<1136 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2101 corpus positions)", 'datetime': '2024-07-25T12:42:40.188891', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:40,190 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:40,190 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:40,190 - using serial LDA version on this node +2024-07-25 12:42:40,190 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:40,191 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:40,194 - -8.156 per-word bound, 285.1 perplexity estimate based on a held-out corpus of 1 documents with 2101 words +2024-07-25 12:42:40,194 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:40,196 - topic #0 (0.333): 0.015*"’" + 0.008*"practice" + 0.007*"needs" + 0.005*"highly" + 0.005*"well" + 0.004*"quality" + 0.004*"many" + 0.003*"across" + 0.003*"number" + 0.003*"family" +2024-07-25 12:42:40,196 - topic #1 (0.333): 0.011*"’" + 0.007*"needs" + 0.006*"practice" + 0.006*"highly" + 0.004*"across" + 0.004*"well" + 0.004*"direct" + 0.004*"many" + 0.003*"shared" + 0.003*"family" +2024-07-25 12:42:40,196 - topic #2 (0.333): 0.012*"’" + 0.006*"practice" + 0.005*"highly" + 0.005*"well" + 0.004*"many" + 0.004*"family" + 0.003*"high" + 0.003*"interventions" + 0.003*"across" + 0.003*"needs" +2024-07-25 12:42:40,196 - topic diff=0.694428, rho=1.000000 +2024-07-25 12:42:40,197 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:40.197092', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:41,359 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:41,359 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:41,359 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:41,359 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:41,359 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:41,359 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:41,360 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:41,360 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:41,360 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:41,360 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:41,360 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:41,360 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:43,247 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:43,250 - built Dictionary<1199 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2593 corpus positions) +2024-07-25 12:42:43,250 - Dictionary lifecycle event {'msg': "built Dictionary<1199 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2593 corpus positions)", 'datetime': '2024-07-25T12:42:43.250611', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:43,251 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:43,251 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:43,252 - using serial LDA version on this node +2024-07-25 12:42:43,252 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:43,252 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:43,256 - -8.106 per-word bound, 275.6 perplexity estimate based on a held-out corpus of 1 documents with 2593 words +2024-07-25 12:42:43,256 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:43,258 - topic #0 (0.333): 0.016*"’" + 0.006*"needs" + 0.005*"progress" + 0.005*"need" + 0.005*"quality" + 0.005*"Luton" + 0.005*"plans" + 0.005*"receive" + 0.005*"well" + 0.005*"good" +2024-07-25 12:42:43,258 - topic #1 (0.333): 0.021*"’" + 0.007*"plans" + 0.007*"Luton" + 0.007*"need" + 0.006*"needs" + 0.006*"impact" + 0.006*"good" + 0.006*"effective" + 0.005*"progress" + 0.005*"including" +2024-07-25 12:42:43,258 - topic #2 (0.333): 0.012*"’" + 0.007*"need" + 0.006*"effective" + 0.006*"needs" + 0.005*"ensure" + 0.004*"plans" + 0.004*"impact" + 0.004*"good" + 0.004*"11" + 0.004*"quality" +2024-07-25 12:42:43,258 - topic diff=0.795195, rho=1.000000 +2024-07-25 12:42:43,258 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:43.258900', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:44,629 - Inspection date 2022-07-11 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:44,630 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:44,630 - Inspection date 2022-07-11 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:44,630 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:44,630 - Inspection date 2022-07-11 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:44,631 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:44,631 - Inspection date 2022-07-11 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:44,631 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:44,631 - Inspection date 2022-07-11 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:44,631 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:44,632 - Inspection date 2022-07-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:44,632 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:46,216 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:46,219 - built Dictionary<871 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1938 corpus positions) +2024-07-25 12:42:46,220 - Dictionary lifecycle event {'msg': "built Dictionary<871 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1938 corpus positions)", 'datetime': '2024-07-25T12:42:46.220217', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:46,221 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:46,221 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:46,221 - using serial LDA version on this node +2024-07-25 12:42:46,221 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:46,222 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:46,225 - -7.770 per-word bound, 218.3 perplexity estimate based on a held-out corpus of 1 documents with 1938 words +2024-07-25 12:42:46,225 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:46,226 - topic #0 (0.333): 0.020*"’" + 0.011*"Manchester" + 0.010*"needs" + 0.007*"supported" + 0.007*"well" + 0.006*"plans" + 0.005*"always" + 0.005*"effective" + 0.005*"protection" + 0.004*"quality" +2024-07-25 12:42:46,226 - topic #1 (0.333): 0.023*"’" + 0.009*"needs" + 0.009*"Manchester" + 0.007*"well" + 0.006*"supported" + 0.006*"always" + 0.006*"education" + 0.006*"protection" + 0.005*"family" + 0.005*"plans" +2024-07-25 12:42:46,226 - topic #2 (0.333): 0.019*"’" + 0.011*"Manchester" + 0.009*"needs" + 0.008*"always" + 0.007*"supported" + 0.006*"well" + 0.005*"disabled" + 0.005*"plans" + 0.005*"education" + 0.005*"quality" +2024-07-25 12:42:46,226 - topic diff=0.809603, rho=1.000000 +2024-07-25 12:42:46,227 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:46.227089', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:47,124 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:47,124 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:47,124 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:47,124 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:47,125 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:47,125 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:47,125 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:47,125 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:47,125 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:47,125 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:47,125 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:47,126 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:48,508 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:48,510 - built Dictionary<922 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1857 corpus positions) +2024-07-25 12:42:48,511 - Dictionary lifecycle event {'msg': "built Dictionary<922 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1857 corpus positions)", 'datetime': '2024-07-25T12:42:48.511034', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:48,512 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:48,512 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:48,512 - using serial LDA version on this node +2024-07-25 12:42:48,513 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:48,513 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:48,519 - -7.890 per-word bound, 237.3 perplexity estimate based on a held-out corpus of 1 documents with 1857 words +2024-07-25 12:42:48,519 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:48,521 - topic #0 (0.333): 0.015*"’" + 0.010*"Medway" + 0.009*"quality" + 0.009*"practice" + 0.007*"well" + 0.007*"needs" + 0.006*"leaders" + 0.006*"oversight" + 0.005*"experiences" + 0.005*"impact" +2024-07-25 12:42:48,521 - topic #1 (0.333): 0.013*"’" + 0.008*"Medway" + 0.007*"well" + 0.006*"practice" + 0.006*"quality" + 0.006*"oversight" + 0.005*"leaders" + 0.005*"needs" + 0.005*"impact" + 0.004*"28" +2024-07-25 12:42:48,521 - topic #2 (0.333): 0.018*"’" + 0.009*"Medway" + 0.008*"practice" + 0.008*"well" + 0.007*"quality" + 0.007*"leaders" + 0.006*"good" + 0.006*"needs" + 0.006*"improve" + 0.006*"impact" +2024-07-25 12:42:48,521 - topic diff=0.766091, rho=1.000000 +2024-07-25 12:42:48,522 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:48.522046', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:49,525 - Inspection date 2023-07-17 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:49,525 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:49,525 - Inspection date 2023-07-17 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:49,525 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:49,525 - Inspection date 2023-07-17 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:49,526 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:49,526 - Inspection date 2023-07-17 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:49,526 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:49,526 - Inspection date 2023-07-17 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:49,526 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:49,526 - Inspection date 2023-07-17 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:49,527 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:51,496 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:51,498 - built Dictionary<1068 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2278 corpus positions) +2024-07-25 12:42:51,498 - Dictionary lifecycle event {'msg': "built Dictionary<1068 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2278 corpus positions)", 'datetime': '2024-07-25T12:42:51.498658', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:51,499 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:51,499 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:51,500 - using serial LDA version on this node +2024-07-25 12:42:51,500 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:51,500 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:51,504 - -8.000 per-word bound, 256.0 perplexity estimate based on a held-out corpus of 1 documents with 2278 words +2024-07-25 12:42:51,504 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:51,505 - topic #0 (0.333): 0.016*"’" + 0.007*"Middlesbrough" + 0.007*"well" + 0.006*"plans" + 0.006*"effective" + 0.006*"practice" + 0.006*"progress" + 0.005*"13" + 0.005*"place" + 0.005*"impact" +2024-07-25 12:42:51,505 - topic #1 (0.333): 0.013*"’" + 0.007*"effective" + 0.007*"Middlesbrough" + 0.007*"needs" + 0.007*"plans" + 0.006*"well" + 0.005*"progress" + 0.005*"practice" + 0.005*"means" + 0.005*"24" +2024-07-25 12:42:51,505 - topic #2 (0.333): 0.011*"’" + 0.008*"plans" + 0.007*"effective" + 0.006*"needs" + 0.006*"Middlesbrough" + 0.006*"well" + 0.005*"practice" + 0.004*"good" + 0.004*"13" + 0.004*"24" +2024-07-25 12:42:51,506 - topic diff=0.782368, rho=1.000000 +2024-07-25 12:42:51,506 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:51.506219', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:52,831 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:52,831 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:52,831 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:52,832 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:52,832 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:52,832 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:52,832 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:52,832 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:52,832 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:52,832 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:52,833 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:52,833 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:54,654 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:54,658 - built Dictionary<1101 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2328 corpus positions) +2024-07-25 12:42:54,658 - Dictionary lifecycle event {'msg': "built Dictionary<1101 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2328 corpus positions)", 'datetime': '2024-07-25T12:42:54.658669', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:54,660 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:54,660 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:54,660 - using serial LDA version on this node +2024-07-25 12:42:54,661 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:54,661 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:54,668 - -8.035 per-word bound, 262.3 perplexity estimate based on a held-out corpus of 1 documents with 2328 words +2024-07-25 12:42:54,668 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:54,670 - topic #0 (0.333): 0.009*"’" + 0.005*"Milton" + 0.004*"well" + 0.004*"need" + 0.004*"25" + 0.004*"Keynes" + 0.004*"5" + 0.004*"practice" + 0.004*"2021" + 0.004*"family" +2024-07-25 12:42:54,670 - topic #1 (0.333): 0.016*"’" + 0.006*"Milton" + 0.006*"well" + 0.006*"Keynes" + 0.006*"need" + 0.005*"plans" + 0.005*"practice" + 0.005*"good" + 0.005*"team" + 0.004*"education" +2024-07-25 12:42:54,671 - topic #2 (0.333): 0.017*"’" + 0.007*"Keynes" + 0.006*"Milton" + 0.006*"well" + 0.005*"need" + 0.005*"leaders" + 0.005*"practice" + 0.005*"October" + 0.005*"25" + 0.004*"impact" +2024-07-25 12:42:54,671 - topic diff=0.787914, rho=1.000000 +2024-07-25 12:42:54,671 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:54.671394', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:55,639 - Inspection date 2021-10-25 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:42:55,640 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:55,640 - Inspection date 2021-10-25 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:42:55,640 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:55,640 - Inspection date 2021-10-25 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:42:55,640 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:55,641 - Inspection date 2021-10-25 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:42:55,641 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:55,641 - Inspection date 2021-10-25 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:42:55,641 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:55,642 - Inspection date 2021-10-25 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:42:55,642 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:42:59,274 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:42:59,277 - built Dictionary<956 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2076 corpus positions) +2024-07-25 12:42:59,277 - Dictionary lifecycle event {'msg': "built Dictionary<956 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2076 corpus positions)", 'datetime': '2024-07-25T12:42:59.277928', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:42:59,279 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:42:59,279 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:42:59,280 - using serial LDA version on this node +2024-07-25 12:42:59,280 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:42:59,280 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:42:59,287 - -7.880 per-word bound, 235.5 perplexity estimate based on a held-out corpus of 1 documents with 2076 words +2024-07-25 12:42:59,287 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:42:59,289 - topic #0 (0.333): 0.011*"’" + 0.010*"plans" + 0.008*"needs" + 0.007*"Newcastle" + 0.007*"progress" + 0.006*"good" + 0.006*"management" + 0.006*"making" + 0.006*"protection" + 0.005*"29" +2024-07-25 12:42:59,290 - topic #1 (0.333): 0.020*"’" + 0.012*"plans" + 0.008*"needs" + 0.007*"well" + 0.007*"protection" + 0.007*"Newcastle" + 0.006*"good" + 0.006*"planning" + 0.006*"ensure" + 0.006*"making" +2024-07-25 12:42:59,290 - topic #2 (0.333): 0.015*"’" + 0.008*"plans" + 0.007*"good" + 0.007*"Newcastle" + 0.007*"protection" + 0.007*"needs" + 0.006*"well" + 0.006*"progress" + 0.005*"ensure" + 0.005*"need" +2024-07-25 12:42:59,290 - topic diff=0.783786, rho=1.000000 +2024-07-25 12:42:59,290 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:42:59.290907', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:01,996 - Inspection date 2021-11-29 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:01,997 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:01,999 - Inspection date 2021-11-29 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:01,999 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:01,999 - Inspection date 2021-11-29 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:02,000 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:02,000 - Inspection date 2021-11-29 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:02,000 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:02,001 - Inspection date 2021-11-29 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:02,001 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:02,001 - Inspection date 2021-11-29 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:02,001 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:07,047 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:07,049 - built Dictionary<1221 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2655 corpus positions) +2024-07-25 12:43:07,049 - Dictionary lifecycle event {'msg': "built Dictionary<1221 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2655 corpus positions)", 'datetime': '2024-07-25T12:43:07.049960', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:07,051 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:07,051 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:07,051 - using serial LDA version on this node +2024-07-25 12:43:07,051 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:07,052 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:07,056 - -8.125 per-word bound, 279.2 perplexity estimate based on a held-out corpus of 1 documents with 2655 words +2024-07-25 12:43:07,056 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:07,057 - topic #0 (0.333): 0.019*"’" + 0.009*"well" + 0.007*"Norfolk" + 0.007*"needs" + 0.005*"18" + 0.005*"practice" + 0.005*"carers" + 0.005*"leaders" + 0.004*"plans" + 0.004*"range" +2024-07-25 12:43:07,057 - topic #1 (0.333): 0.018*"’" + 0.008*"well" + 0.007*"carers" + 0.006*"Norfolk" + 0.006*"practice" + 0.005*"supported" + 0.005*"leaders" + 0.005*"effective" + 0.005*"needs" + 0.004*"18" +2024-07-25 12:43:07,057 - topic #2 (0.333): 0.014*"’" + 0.010*"Norfolk" + 0.008*"well" + 0.006*"carers" + 0.006*"supported" + 0.006*"needs" + 0.005*"practice" + 0.005*"progress" + 0.005*"including" + 0.005*"plans" +2024-07-25 12:43:07,058 - topic diff=0.778290, rho=1.000000 +2024-07-25 12:43:07,058 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:07.058216', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:08,353 - Inspection date 2022-11-07 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:08,353 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:08,353 - Inspection date 2022-11-07 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:08,353 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:08,353 - Inspection date 2022-11-07 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:08,353 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:08,354 - Inspection date 2022-11-07 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:08,354 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:08,354 - Inspection date 2022-11-07 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:08,354 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:08,354 - Inspection date 2022-11-07 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:08,354 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:10,197 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:10,199 - built Dictionary<958 unique tokens: ['0161', '021', '0300', '1', '10']...> from 1 documents (total 2045 corpus positions) +2024-07-25 12:43:10,199 - Dictionary lifecycle event {'msg': "built Dictionary<958 unique tokens: ['0161', '021', '0300', '1', '10']...> from 1 documents (total 2045 corpus positions)", 'datetime': '2024-07-25T12:43:10.199374', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:10,200 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:10,200 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:10,200 - using serial LDA version on this node +2024-07-25 12:43:10,201 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:10,201 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:10,204 - -7.889 per-word bound, 237.0 perplexity estimate based on a held-out corpus of 1 documents with 2045 words +2024-07-25 12:43:10,204 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:10,205 - topic #0 (0.333): 0.016*"’" + 0.009*"practice" + 0.008*"leaders" + 0.008*"planning" + 0.007*"risk" + 0.007*"needs" + 0.006*"need" + 0.005*"2021" + 0.005*"North" + 0.005*"many" +2024-07-25 12:43:10,205 - topic #1 (0.333): 0.010*"’" + 0.007*"practice" + 0.006*"risk" + 0.005*"leaders" + 0.004*"needs" + 0.004*"October" + 0.004*"many" + 0.004*"However" + 0.004*"harm" + 0.004*"2021" +2024-07-25 12:43:10,206 - topic #2 (0.333): 0.014*"’" + 0.007*"risk" + 0.006*"needs" + 0.005*"planning" + 0.005*"practice" + 0.005*"need" + 0.005*"leaders" + 0.005*"many" + 0.005*"Lincolnshire" + 0.005*"oversight" +2024-07-25 12:43:10,206 - topic diff=0.781201, rho=1.000000 +2024-07-25 12:43:10,206 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:10.206338', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:11,128 - Inspection date 2021-10-04 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:11,128 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:11,128 - Inspection date 2021-10-04 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:11,128 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:11,128 - Inspection date 2021-10-04 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:11,128 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:11,129 - Inspection date 2021-10-04 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:11,129 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:11,129 - Inspection date 2021-10-04 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:11,129 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:11,129 - Inspection date 2021-10-04 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:11,129 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:12,493 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:12,496 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2174 corpus positions) +2024-07-25 12:43:12,496 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2174 corpus positions)", 'datetime': '2024-07-25T12:43:12.496226', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:12,497 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:12,497 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:12,497 - using serial LDA version on this node +2024-07-25 12:43:12,498 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:12,498 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:12,501 - -8.064 per-word bound, 267.7 perplexity estimate based on a held-out corpus of 1 documents with 2174 words +2024-07-25 12:43:12,501 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:12,503 - topic #0 (0.333): 0.019*"’" + 0.006*"family" + 0.006*"‘" + 0.006*"North" + 0.005*"leaders" + 0.005*"10" + 0.005*"Lincolnshire" + 0.005*"approach" + 0.005*"need" + 0.005*"well" +2024-07-25 12:43:12,503 - topic #1 (0.333): 0.017*"’" + 0.007*"‘" + 0.006*"approach" + 0.006*"family" + 0.005*"well" + 0.005*"Lincolnshire" + 0.005*"leaders" + 0.004*"need" + 0.004*"10" + 0.004*"practice" +2024-07-25 12:43:12,503 - topic #2 (0.333): 0.024*"’" + 0.008*"‘" + 0.006*"family" + 0.006*"North" + 0.006*"Lincolnshire" + 0.005*"leaders" + 0.005*"well" + 0.004*"need" + 0.004*"10" + 0.004*"approach" +2024-07-25 12:43:12,503 - topic diff=0.750582, rho=1.000000 +2024-07-25 12:43:12,503 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:12.503842', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:13,433 - Inspection date 2022-10-10 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:13,433 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:13,433 - Inspection date 2022-10-10 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:13,433 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:13,434 - Inspection date 2022-10-10 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:13,434 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:13,434 - Inspection date 2022-10-10 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:13,434 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:13,434 - Inspection date 2022-10-10 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:13,434 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:13,434 - Inspection date 2022-10-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:13,435 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:15,655 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:15,659 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2204 corpus positions) +2024-07-25 12:43:15,659 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2204 corpus positions)", 'datetime': '2024-07-25T12:43:15.659748', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:15,661 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:15,661 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:15,662 - using serial LDA version on this node +2024-07-25 12:43:15,662 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:15,662 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:15,666 - -8.028 per-word bound, 260.9 perplexity estimate based on a held-out corpus of 1 documents with 2204 words +2024-07-25 12:43:15,666 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:15,668 - topic #0 (0.333): 0.019*"’" + 0.008*"North" + 0.007*"well" + 0.007*"Northamptonshire" + 0.005*"NCT" + 0.005*"plans" + 0.005*"practice" + 0.005*"needs" + 0.005*"impact" + 0.004*"quality" +2024-07-25 12:43:15,668 - topic #1 (0.333): 0.015*"’" + 0.008*"Northamptonshire" + 0.007*"well" + 0.006*"North" + 0.005*"impact" + 0.005*"Leaders" + 0.005*"practice" + 0.005*"needs" + 0.005*"need" + 0.005*"3" +2024-07-25 12:43:15,668 - topic #2 (0.333): 0.016*"’" + 0.009*"Northamptonshire" + 0.008*"quality" + 0.005*"Leaders" + 0.005*"14" + 0.005*"North" + 0.005*"experiences" + 0.005*"practice" + 0.005*"well" + 0.004*"need" +2024-07-25 12:43:15,668 - topic diff=0.742790, rho=1.000000 +2024-07-25 12:43:15,668 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:15.668752', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:16,577 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:16,577 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:16,577 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:16,577 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:16,578 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:16,578 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:16,578 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:16,578 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:16,578 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:16,578 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:16,579 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:16,579 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:18,030 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:18,033 - built Dictionary<1219 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2902 corpus positions) +2024-07-25 12:43:18,033 - Dictionary lifecycle event {'msg': "built Dictionary<1219 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2902 corpus positions)", 'datetime': '2024-07-25T12:43:18.033443', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:18,034 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:18,034 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:18,035 - using serial LDA version on this node +2024-07-25 12:43:18,035 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:18,035 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:18,039 - -8.069 per-word bound, 268.6 perplexity estimate based on a held-out corpus of 1 documents with 2902 words +2024-07-25 12:43:18,039 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:18,041 - topic #0 (0.333): 0.017*"’" + 0.008*"quality" + 0.008*"needs" + 0.007*"number" + 0.007*"always" + 0.006*"progress" + 0.006*"need" + 0.005*"North" + 0.005*"effective" + 0.005*"Somerset" +2024-07-25 12:43:18,041 - topic #1 (0.333): 0.020*"’" + 0.007*"quality" + 0.006*"North" + 0.005*"needs" + 0.005*"practice" + 0.005*"well" + 0.005*"24" + 0.005*"Somerset" + 0.005*"always" + 0.005*"experienced" +2024-07-25 12:43:18,041 - topic #2 (0.333): 0.014*"’" + 0.007*"practice" + 0.007*"Somerset" + 0.006*"needs" + 0.006*"quality" + 0.006*"always" + 0.006*"risk" + 0.006*"number" + 0.006*"North" + 0.005*"well" +2024-07-25 12:43:18,041 - topic diff=0.829075, rho=1.000000 +2024-07-25 12:43:18,042 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:18.042055', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:19,744 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:19,744 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:19,744 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:19,744 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:19,745 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:19,745 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:19,745 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:19,745 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:19,745 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:19,745 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:19,746 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:19,746 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:21,821 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:21,824 - built Dictionary<1273 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2518 corpus positions) +2024-07-25 12:43:21,824 - Dictionary lifecycle event {'msg': "built Dictionary<1273 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2518 corpus positions)", 'datetime': '2024-07-25T12:43:21.824823', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:21,826 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:21,826 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:21,826 - using serial LDA version on this node +2024-07-25 12:43:21,826 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:21,826 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:21,831 - -8.222 per-word bound, 298.6 perplexity estimate based on a held-out corpus of 1 documents with 2518 words +2024-07-25 12:43:21,831 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:21,832 - topic #0 (0.333): 0.014*"’" + 0.005*"leaders" + 0.005*"make" + 0.005*"well" + 0.005*"quality" + 0.005*"need" + 0.004*"progress" + 0.004*"foster" + 0.004*"needs" + 0.004*"experiences" +2024-07-25 12:43:21,832 - topic #1 (0.333): 0.019*"’" + 0.007*"well" + 0.005*"leaders" + 0.005*"need" + 0.005*"needs" + 0.005*"quality" + 0.004*"make" + 0.004*"understand" + 0.004*"protection" + 0.004*"clear" +2024-07-25 12:43:21,833 - topic #2 (0.333): 0.014*"’" + 0.006*"well" + 0.005*"early" + 0.005*"need" + 0.005*"leaders" + 0.005*"impact" + 0.004*"quality" + 0.004*"make" + 0.004*"needs" + 0.004*"family" +2024-07-25 12:43:21,833 - topic diff=0.730910, rho=1.000000 +2024-07-25 12:43:21,833 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:21.833282', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:22,828 - Inspection date 2020-03-09 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:22,828 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:22,828 - Inspection date 2020-03-09 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:22,829 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:22,829 - Inspection date 2020-03-09 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:22,829 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:22,829 - Inspection date 2020-03-09 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:22,829 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:22,829 - Inspection date 2020-03-09 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:22,830 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:22,830 - Inspection date 2020-03-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:22,830 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:24,250 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:24,253 - built Dictionary<1259 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2759 corpus positions) +2024-07-25 12:43:24,253 - Dictionary lifecycle event {'msg': "built Dictionary<1259 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2759 corpus positions)", 'datetime': '2024-07-25T12:43:24.253143', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:24,254 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:24,254 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:24,254 - using serial LDA version on this node +2024-07-25 12:43:24,255 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:24,255 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:24,259 - -8.149 per-word bound, 283.8 perplexity estimate based on a held-out corpus of 1 documents with 2759 words +2024-07-25 12:43:24,259 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:24,260 - topic #0 (0.333): 0.017*"’" + 0.008*"well" + 0.007*"North" + 0.007*"practice" + 0.006*"Yorkshire" + 0.006*"needs" + 0.005*"family" + 0.005*"need" + 0.005*"7" + 0.005*"‘" +2024-07-25 12:43:24,261 - topic #1 (0.333): 0.026*"’" + 0.009*"well" + 0.007*"North" + 0.006*"family" + 0.006*"Yorkshire" + 0.006*"needs" + 0.006*"practice" + 0.005*"2023" + 0.005*"3" + 0.005*"‘" +2024-07-25 12:43:24,261 - topic #2 (0.333): 0.016*"’" + 0.007*"well" + 0.006*"Yorkshire" + 0.005*"practice" + 0.005*"‘" + 0.005*"family" + 0.004*"North" + 0.004*"needs" + 0.004*"live" + 0.004*"3" +2024-07-25 12:43:24,261 - topic diff=0.802076, rho=1.000000 +2024-07-25 12:43:24,261 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:24.261558', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:25,765 - Inspection date 2023-07-03 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:25,766 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:25,766 - Inspection date 2023-07-03 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:25,766 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:25,767 - Inspection date 2023-07-03 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:25,767 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:25,767 - Inspection date 2023-07-03 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:25,768 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:25,768 - Inspection date 2023-07-03 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:25,768 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:25,768 - Inspection date 2023-07-03 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:25,768 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:27,722 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:27,724 - built Dictionary<1218 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2884 corpus positions) +2024-07-25 12:43:27,725 - Dictionary lifecycle event {'msg': "built Dictionary<1218 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2884 corpus positions)", 'datetime': '2024-07-25T12:43:27.724988', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:27,726 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:27,726 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:27,726 - using serial LDA version on this node +2024-07-25 12:43:27,727 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:27,727 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:27,731 - -8.075 per-word bound, 269.6 perplexity estimate based on a held-out corpus of 1 documents with 2884 words +2024-07-25 12:43:27,731 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:27,732 - topic #0 (0.333): 0.019*"’" + 0.009*"family" + 0.008*"needs" + 0.007*"strong" + 0.006*"well" + 0.006*"Northumberland" + 0.006*"experiences" + 0.005*"leaders" + 0.005*"effective" + 0.005*"progress" +2024-07-25 12:43:27,732 - topic #1 (0.333): 0.020*"’" + 0.008*"leaders" + 0.007*"family" + 0.006*"well" + 0.006*"Northumberland" + 0.005*"experiences" + 0.005*"needs" + 0.005*"strong" + 0.005*"practice" + 0.005*"provide" +2024-07-25 12:43:27,733 - topic #2 (0.333): 0.017*"’" + 0.007*"experiences" + 0.006*"strong" + 0.006*"needs" + 0.006*"family" + 0.006*"leaders" + 0.005*"practice" + 0.005*"Northumberland" + 0.005*"receive" + 0.004*"well" +2024-07-25 12:43:27,733 - topic diff=0.835316, rho=1.000000 +2024-07-25 12:43:27,733 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:27.733270', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:28,707 - Inspection date 2024-05-20 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:28,707 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:28,707 - Inspection date 2024-05-20 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:28,707 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:28,708 - Inspection date 2024-05-20 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:28,708 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:28,708 - Inspection date 2024-05-20 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:28,708 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:28,708 - Inspection date 2024-05-20 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:28,708 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:28,708 - Inspection date 2024-05-20 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:28,709 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:30,415 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:30,417 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions) +2024-07-25 12:43:30,417 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)", 'datetime': '2024-07-25T12:43:30.417953', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:30,419 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:30,419 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:30,419 - using serial LDA version on this node +2024-07-25 12:43:30,419 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:30,419 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:30,423 - -8.023 per-word bound, 260.1 perplexity estimate based on a held-out corpus of 1 documents with 2316 words +2024-07-25 12:43:30,423 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:30,424 - topic #0 (0.333): 0.016*"’" + 0.007*"needs" + 0.007*"Nottingham" + 0.006*"effective" + 0.004*"impact" + 0.004*"oversight" + 0.004*"plans" + 0.004*"practice" + 0.004*"City" + 0.004*"consistently" +2024-07-25 12:43:30,425 - topic #1 (0.333): 0.012*"’" + 0.007*"needs" + 0.006*"effective" + 0.006*"Nottingham" + 0.005*"impact" + 0.005*"plans" + 0.005*"11" + 0.005*"practice" + 0.005*"City" + 0.005*"However" +2024-07-25 12:43:30,425 - topic #2 (0.333): 0.013*"’" + 0.009*"needs" + 0.007*"plans" + 0.005*"11" + 0.005*"oversight" + 0.005*"However" + 0.005*"City" + 0.004*"impact" + 0.004*"Nottingham" + 0.004*"risk" +2024-07-25 12:43:30,425 - topic diff=0.761744, rho=1.000000 +2024-07-25 12:43:30,425 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:30.425616', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:31,481 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:31,481 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:31,482 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:31,482 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:31,482 - Inspection date None / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:31,482 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:31,482 - Inspection date None / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:31,482 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:31,482 - Inspection date None / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:31,483 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:31,483 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:31,483 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:32,995 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:32,997 - built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2129 corpus positions) +2024-07-25 12:43:32,997 - Dictionary lifecycle event {'msg': "built Dictionary<1048 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2129 corpus positions)", 'datetime': '2024-07-25T12:43:32.997668', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:32,998 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:32,998 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:32,999 - using serial LDA version on this node +2024-07-25 12:43:32,999 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:32,999 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:33,003 - -8.010 per-word bound, 257.8 perplexity estimate based on a held-out corpus of 1 documents with 2129 words +2024-07-25 12:43:33,003 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:33,004 - topic #0 (0.333): 0.022*"’" + 0.010*"needs" + 0.009*"well" + 0.006*"Nottinghamshire" + 0.006*"plans" + 0.005*"Leaders" + 0.005*"effective" + 0.005*"20" + 0.005*"practice" + 0.005*"leaders" +2024-07-25 12:43:33,004 - topic #1 (0.333): 0.011*"’" + 0.007*"well" + 0.006*"Nottinghamshire" + 0.005*"plans" + 0.005*"needs" + 0.004*"Leaders" + 0.004*"risks" + 0.004*"leaders" + 0.003*"May" + 0.003*"24" +2024-07-25 12:43:33,004 - topic #2 (0.333): 0.016*"’" + 0.009*"well" + 0.009*"needs" + 0.007*"Nottinghamshire" + 0.005*"plans" + 0.005*"effective" + 0.005*"2024" + 0.004*"leaders" + 0.004*"practice" + 0.004*"provide" +2024-07-25 12:43:33,004 - topic diff=0.777263, rho=1.000000 +2024-07-25 12:43:33,005 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:33.005104', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:33,890 - Inspection date 2024-05-20 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:33,891 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:33,891 - Inspection date 2024-05-20 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:33,891 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:33,891 - Inspection date 2024-05-20 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:33,892 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:33,892 - Inspection date 2024-05-20 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:33,892 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:33,892 - Inspection date 2024-05-20 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:33,892 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:33,892 - Inspection date 2024-05-20 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:33,892 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:35,511 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:35,513 - built Dictionary<1152 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2441 corpus positions) +2024-07-25 12:43:35,514 - Dictionary lifecycle event {'msg': "built Dictionary<1152 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2441 corpus positions)", 'datetime': '2024-07-25T12:43:35.514043', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:35,515 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:35,515 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:35,515 - using serial LDA version on this node +2024-07-25 12:43:35,515 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:35,516 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:35,519 - -8.076 per-word bound, 269.8 perplexity estimate based on a held-out corpus of 1 documents with 2441 words +2024-07-25 12:43:35,519 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:35,521 - topic #0 (0.333): 0.013*"’" + 0.009*"plans" + 0.008*"well" + 0.008*"needs" + 0.007*"PAs" + 0.005*"progress" + 0.005*"practice" + 0.005*"clear" + 0.005*"Oldham" + 0.005*"leaders" +2024-07-25 12:43:35,521 - topic #1 (0.333): 0.013*"’" + 0.009*"well" + 0.008*"plans" + 0.006*"Oldham" + 0.005*"leaders" + 0.005*"needs" + 0.005*"practice" + 0.005*"PAs" + 0.005*"risk" + 0.005*"effective" +2024-07-25 12:43:35,521 - topic #2 (0.333): 0.011*"’" + 0.007*"Oldham" + 0.007*"plans" + 0.007*"well" + 0.007*"practice" + 0.006*"leaders" + 0.005*"progress" + 0.005*"needs" + 0.005*"supported" + 0.005*"risk" +2024-07-25 12:43:35,521 - topic diff=0.779228, rho=1.000000 +2024-07-25 12:43:35,521 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:35.521955', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:36,843 - Inspection date 2024-05-13 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:36,843 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:36,843 - Inspection date 2024-05-13 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:36,843 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:36,844 - Inspection date 2024-05-13 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:36,844 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:36,844 - Inspection date 2024-05-13 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:36,844 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:36,844 - Inspection date 2024-05-13 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:36,844 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:36,845 - Inspection date 2024-05-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:36,845 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:38,732 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:38,734 - built Dictionary<1066 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2294 corpus positions) +2024-07-25 12:43:38,734 - Dictionary lifecycle event {'msg': "built Dictionary<1066 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2294 corpus positions)", 'datetime': '2024-07-25T12:43:38.734889', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:38,736 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:38,736 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:38,736 - using serial LDA version on this node +2024-07-25 12:43:38,736 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:38,736 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:38,740 - -7.995 per-word bound, 255.0 perplexity estimate based on a held-out corpus of 1 documents with 2294 words +2024-07-25 12:43:38,740 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:38,742 - topic #0 (0.333): 0.025*"’" + 0.009*"needs" + 0.007*"Oxfordshire" + 0.007*"well" + 0.006*"risk" + 0.006*"receive" + 0.006*"supported" + 0.005*"good" + 0.005*"quality" + 0.005*"progress" +2024-07-25 12:43:38,742 - topic #1 (0.333): 0.019*"’" + 0.012*"needs" + 0.007*"Oxfordshire" + 0.007*"well" + 0.006*"good" + 0.006*"risk" + 0.005*"23" + 0.005*"supported" + 0.005*"arrangements" + 0.005*"12" +2024-07-25 12:43:38,742 - topic #2 (0.333): 0.012*"’" + 0.007*"needs" + 0.006*"Oxfordshire" + 0.006*"well" + 0.005*"risk" + 0.005*"good" + 0.005*"supported" + 0.005*"12" + 0.005*"practice" + 0.004*"quality" +2024-07-25 12:43:38,742 - topic diff=0.787072, rho=1.000000 +2024-07-25 12:43:38,742 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:38.742771', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:39,674 - Inspection date 2024-02-12 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:39,674 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:39,674 - Inspection date 2024-02-12 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:39,674 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:39,675 - Inspection date 2024-02-12 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:39,675 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:39,675 - Inspection date 2024-02-12 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:39,675 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:39,675 - Inspection date 2024-02-12 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:39,675 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:39,676 - Inspection date 2024-02-12 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:39,676 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:41,234 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:41,236 - built Dictionary<893 unique tokens: ['0-25', '0161', '0300', '1', '10']...> from 1 documents (total 1737 corpus positions) +2024-07-25 12:43:41,236 - Dictionary lifecycle event {'msg': "built Dictionary<893 unique tokens: ['0-25', '0161', '0300', '1', '10']...> from 1 documents (total 1737 corpus positions)", 'datetime': '2024-07-25T12:43:41.236874', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:41,237 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:41,237 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:41,238 - using serial LDA version on this node +2024-07-25 12:43:41,238 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:41,238 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:41,241 - -7.883 per-word bound, 236.0 perplexity estimate based on a held-out corpus of 1 documents with 1737 words +2024-07-25 12:43:41,241 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:41,242 - topic #0 (0.333): 0.014*"’" + 0.014*"needs" + 0.008*"need" + 0.007*"Peterborough" + 0.006*"2023" + 0.006*"well" + 0.005*"progress" + 0.005*"8" + 0.005*"supported" + 0.005*"plans" +2024-07-25 12:43:41,243 - topic #1 (0.333): 0.014*"’" + 0.012*"needs" + 0.007*"well" + 0.007*"Peterborough" + 0.006*"2023" + 0.006*"need" + 0.006*"progress" + 0.006*"plans" + 0.006*"supported" + 0.005*"December" +2024-07-25 12:43:41,243 - topic #2 (0.333): 0.015*"’" + 0.013*"needs" + 0.007*"Peterborough" + 0.006*"need" + 0.006*"2023" + 0.005*"progress" + 0.005*"8" + 0.005*"well" + 0.005*"receive" + 0.005*"education" +2024-07-25 12:43:41,243 - topic diff=0.727753, rho=1.000000 +2024-07-25 12:43:41,243 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:41.243640', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:42,188 - Inspection date 2023-11-27 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:42,188 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:42,189 - Inspection date 2023-11-27 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:42,189 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:42,189 - Inspection date 2023-11-27 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:42,189 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:42,189 - Inspection date 2023-11-27 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:42,189 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:42,189 - Inspection date 2023-11-27 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:42,189 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:42,190 - Inspection date 2023-11-27 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:42,190 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:43,930 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:43,934 - built Dictionary<1232 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions) +2024-07-25 12:43:43,935 - Dictionary lifecycle event {'msg': "built Dictionary<1232 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2905 corpus positions)", 'datetime': '2024-07-25T12:43:43.934981', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:43,937 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:43,937 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:43,937 - using serial LDA version on this node +2024-07-25 12:43:43,938 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:43,938 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:43,945 - -8.086 per-word bound, 271.6 perplexity estimate based on a held-out corpus of 1 documents with 2905 words +2024-07-25 12:43:43,945 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:43,947 - topic #0 (0.333): 0.015*"’" + 0.010*"needs" + 0.006*"well" + 0.005*"Plymouth" + 0.005*"risks" + 0.005*"practice" + 0.005*"2" + 0.005*"education" + 0.005*"plans" + 0.004*"leaders" +2024-07-25 12:43:43,947 - topic #1 (0.333): 0.010*"’" + 0.007*"needs" + 0.007*"well" + 0.006*"Plymouth" + 0.006*"practice" + 0.005*"appropriate" + 0.005*"February" + 0.005*"education" + 0.004*"benefit" + 0.004*"2024" +2024-07-25 12:43:43,948 - topic #2 (0.333): 0.013*"’" + 0.008*"Plymouth" + 0.008*"well" + 0.007*"needs" + 0.005*"practice" + 0.005*"plans" + 0.005*"City" + 0.005*"February" + 0.005*"2" + 0.004*"timely" +2024-07-25 12:43:43,948 - topic diff=0.835376, rho=1.000000 +2024-07-25 12:43:43,948 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:43.948525', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:45,033 - Inspection date 2024-01-22 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:45,033 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:45,033 - Inspection date 2024-01-22 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:45,034 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:45,034 - Inspection date 2024-01-22 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:45,034 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:45,034 - Inspection date 2024-01-22 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:45,034 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:45,034 - Inspection date 2024-01-22 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:45,034 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:45,034 - Inspection date 2024-01-22 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:45,035 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:46,870 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:46,875 - built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2738 corpus positions) +2024-07-25 12:43:46,875 - Dictionary lifecycle event {'msg': "built Dictionary<1223 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2738 corpus positions)", 'datetime': '2024-07-25T12:43:46.875737', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:46,877 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:46,878 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:46,878 - using serial LDA version on this node +2024-07-25 12:43:46,879 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:46,879 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:46,885 - -8.110 per-word bound, 276.3 perplexity estimate based on a held-out corpus of 1 documents with 2738 words +2024-07-25 12:43:46,886 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:46,888 - topic #0 (0.333): 0.017*"’" + 0.008*"care-experienced" + 0.006*"Portsmouth" + 0.006*"well" + 0.005*"needs" + 0.005*"family" + 0.004*"plans" + 0.004*"progress" + 0.004*"practice" + 0.004*"health" +2024-07-25 12:43:46,888 - topic #1 (0.333): 0.015*"’" + 0.008*"well" + 0.007*"care-experienced" + 0.006*"Portsmouth" + 0.005*"health" + 0.005*"needs" + 0.005*"practice" + 0.005*"leaders" + 0.005*"risk" + 0.005*"progress" +2024-07-25 12:43:46,888 - topic #2 (0.333): 0.018*"’" + 0.008*"needs" + 0.008*"care-experienced" + 0.007*"Portsmouth" + 0.007*"well" + 0.006*"family" + 0.006*"plans" + 0.005*"health" + 0.005*"need" + 0.004*"receive" +2024-07-25 12:43:46,889 - topic diff=0.796687, rho=1.000000 +2024-07-25 12:43:46,889 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:46.889386', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:48,176 - Inspection date 2023-05-15 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:48,177 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:48,177 - Inspection date 2023-05-15 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:48,177 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:48,177 - Inspection date 2023-05-15 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:48,177 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:48,177 - Inspection date 2023-05-15 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:48,178 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:48,178 - Inspection date 2023-05-15 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:48,178 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:48,178 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:48,178 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:49,681 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:49,685 - built Dictionary<1231 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2562 corpus positions) +2024-07-25 12:43:49,685 - Dictionary lifecycle event {'msg': "built Dictionary<1231 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2562 corpus positions)", 'datetime': '2024-07-25T12:43:49.685928', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:49,687 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:49,688 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:49,688 - using serial LDA version on this node +2024-07-25 12:43:49,689 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:49,689 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:49,696 - -8.158 per-word bound, 285.7 perplexity estimate based on a held-out corpus of 1 documents with 2562 words +2024-07-25 12:43:49,696 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:49,698 - topic #0 (0.333): 0.015*"’" + 0.005*"PAs" + 0.005*"needs" + 0.005*"plans" + 0.005*"progress" + 0.004*"timely" + 0.004*"arrangements" + 0.004*"22" + 0.004*"practice" + 0.004*"effective" +2024-07-25 12:43:49,698 - topic #1 (0.333): 0.016*"’" + 0.008*"needs" + 0.006*"well" + 0.005*"Reading" + 0.005*"PAs" + 0.005*"progress" + 0.005*"plans" + 0.004*"clear" + 0.004*"3" + 0.004*"22" +2024-07-25 12:43:49,699 - topic #2 (0.333): 0.011*"’" + 0.006*"needs" + 0.005*"PAs" + 0.005*"2024" + 0.005*"well" + 0.005*"plans" + 0.005*"progress" + 0.004*"Reading" + 0.004*"May" + 0.004*"clear" +2024-07-25 12:43:49,699 - topic diff=0.761572, rho=1.000000 +2024-07-25 12:43:49,699 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:49.699452', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:50,776 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:50,776 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:50,776 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:50,776 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:50,777 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:50,777 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:50,777 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:50,777 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:50,777 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:50,777 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:50,778 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:50,778 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:52,433 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:52,436 - built Dictionary<1112 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2515 corpus positions) +2024-07-25 12:43:52,436 - Dictionary lifecycle event {'msg': "built Dictionary<1112 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2515 corpus positions)", 'datetime': '2024-07-25T12:43:52.436296', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:52,437 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:52,437 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:52,437 - using serial LDA version on this node +2024-07-25 12:43:52,438 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:52,438 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:52,441 - -8.004 per-word bound, 256.7 perplexity estimate based on a held-out corpus of 1 documents with 2515 words +2024-07-25 12:43:52,442 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:52,443 - topic #0 (0.333): 0.014*"’" + 0.008*"leaders" + 0.006*"However" + 0.006*"consistently" + 0.005*"plans" + 0.005*"Cleveland" + 0.005*"20" + 0.005*"2022" + 0.005*"practice" + 0.004*"Redcar" +2024-07-25 12:43:52,443 - topic #1 (0.333): 0.022*"’" + 0.006*"needs" + 0.005*"However" + 0.005*"Redcar" + 0.005*"consistently" + 0.005*"risk" + 0.005*"practice" + 0.005*"leaders" + 0.005*"20" + 0.005*"plans" +2024-07-25 12:43:52,443 - topic #2 (0.333): 0.016*"’" + 0.007*"plans" + 0.006*"needs" + 0.005*"2022" + 0.005*"However" + 0.005*"leaders" + 0.005*"consistently" + 0.005*"carers" + 0.005*"risk" + 0.004*"July" +2024-07-25 12:43:52,443 - topic diff=0.798001, rho=1.000000 +2024-07-25 12:43:52,444 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:52.444123', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:53,454 - Inspection date None / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:53,454 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:53,455 - Inspection date None / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:53,455 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:53,455 - Inspection date None / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:53,455 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:53,455 - Inspection date None / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:53,455 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:53,455 - Inspection date None / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:53,455 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:53,456 - Inspection date None / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:53,456 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:54,772 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:54,776 - built Dictionary<1150 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2656 corpus positions) +2024-07-25 12:43:54,776 - Dictionary lifecycle event {'msg': "built Dictionary<1150 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2656 corpus positions)", 'datetime': '2024-07-25T12:43:54.776930', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:54,778 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:54,778 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:54,779 - using serial LDA version on this node +2024-07-25 12:43:54,779 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:54,779 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:54,786 - -8.025 per-word bound, 260.5 perplexity estimate based on a held-out corpus of 1 documents with 2656 words +2024-07-25 12:43:54,786 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:54,789 - topic #0 (0.333): 0.022*"’" + 0.011*"experienced" + 0.011*"practice" + 0.009*"needs" + 0.006*"quality" + 0.005*"response" + 0.005*"well" + 0.005*"plans" + 0.005*"good" + 0.005*"consistently" +2024-07-25 12:43:54,789 - topic #1 (0.333): 0.021*"’" + 0.009*"experienced" + 0.007*"needs" + 0.007*"response" + 0.006*"plans" + 0.005*"practice" + 0.005*"quality" + 0.005*"good" + 0.005*"Rochdale" + 0.005*"progress" +2024-07-25 12:43:54,789 - topic #2 (0.333): 0.017*"’" + 0.007*"experienced" + 0.007*"plans" + 0.007*"practice" + 0.007*"consistently" + 0.006*"needs" + 0.005*"response" + 0.005*"good" + 0.005*"Rochdale" + 0.004*"3" +2024-07-25 12:43:54,789 - topic diff=0.818953, rho=1.000000 +2024-07-25 12:43:54,789 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:54.789773', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:56,293 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:56,293 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:56,293 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:56,293 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:56,294 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:56,294 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:56,294 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:56,294 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:56,294 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:56,294 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:56,294 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:56,294 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:57,992 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:43:57,997 - built Dictionary<1127 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2366 corpus positions) +2024-07-25 12:43:57,997 - Dictionary lifecycle event {'msg': "built Dictionary<1127 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2366 corpus positions)", 'datetime': '2024-07-25T12:43:57.997743', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:57,999 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:43:57,999 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:43:58,000 - using serial LDA version on this node +2024-07-25 12:43:58,000 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:43:58,000 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:43:58,008 - -8.062 per-word bound, 267.2 perplexity estimate based on a held-out corpus of 1 documents with 2366 words +2024-07-25 12:43:58,008 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:43:58,010 - topic #0 (0.333): 0.021*"’" + 0.009*"Rotherham" + 0.007*"needs" + 0.005*"ensure" + 0.005*"However" + 0.005*"Council" + 0.005*"plans" + 0.005*"good" + 0.005*"well" + 0.004*"27" +2024-07-25 12:43:58,012 - topic #1 (0.333): 0.011*"’" + 0.008*"Rotherham" + 0.006*"well" + 0.005*"Council" + 0.005*"However" + 0.004*"Borough" + 0.004*"needs" + 0.004*"July" + 0.004*"plans" + 0.004*"ensure" +2024-07-25 12:43:58,013 - topic #2 (0.333): 0.010*"’" + 0.008*"Rotherham" + 0.007*"needs" + 0.006*"good" + 0.005*"well" + 0.004*"ensure" + 0.004*"protection" + 0.004*"1" + 0.004*"Borough" + 0.004*"Metropolitan" +2024-07-25 12:43:58,013 - topic diff=0.771632, rho=1.000000 +2024-07-25 12:43:58,013 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:43:58.013474', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:43:59,123 - Inspection date 2022-06-27 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:43:59,124 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:59,124 - Inspection date 2022-06-27 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:43:59,124 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:59,124 - Inspection date 2022-06-27 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:43:59,124 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:59,124 - Inspection date 2022-06-27 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:43:59,125 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:59,125 - Inspection date 2022-06-27 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:43:59,125 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:43:59,125 - Inspection date 2022-06-27 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:43:59,125 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:00,580 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:00,583 - built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2380 corpus positions) +2024-07-25 12:44:00,583 - Dictionary lifecycle event {'msg': "built Dictionary<1119 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2380 corpus positions)", 'datetime': '2024-07-25T12:44:00.583537', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:00,584 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:00,584 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:00,584 - using serial LDA version on this node +2024-07-25 12:44:00,585 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:00,585 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:00,589 - -8.050 per-word bound, 265.0 perplexity estimate based on a held-out corpus of 1 documents with 2380 words +2024-07-25 12:44:00,589 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:00,590 - topic #0 (0.333): 0.011*"’" + 0.011*"practice" + 0.010*"well" + 0.006*"highly" + 0.006*"needs" + 0.006*"strong" + 0.005*"progress" + 0.004*"effective" + 0.004*"leaders" + 0.004*"risk" +2024-07-25 12:44:00,590 - topic #1 (0.333): 0.017*"well" + 0.011*"’" + 0.011*"practice" + 0.009*"highly" + 0.007*"strong" + 0.006*"effective" + 0.006*"leaders" + 0.005*"high" + 0.005*"needs" + 0.005*"professionals" +2024-07-25 12:44:00,590 - topic #2 (0.333): 0.013*"well" + 0.012*"’" + 0.010*"practice" + 0.007*"highly" + 0.006*"strong" + 0.005*"needs" + 0.005*"effective" + 0.005*"leaders" + 0.004*"need" + 0.004*"high" +2024-07-25 12:44:00,590 - topic diff=0.770349, rho=1.000000 +2024-07-25 12:44:00,591 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:00.591086', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:01,822 - Inspection date 2019-09-09 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:01,823 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:01,823 - Inspection date 2019-09-09 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:01,823 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:01,824 - Inspection date 2019-09-09 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:01,824 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:01,824 - Inspection date 2019-09-09 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:01,824 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:01,825 - Inspection date 2019-09-09 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:01,825 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:01,825 - Inspection date 2019-09-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:01,825 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:03,450 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:03,452 - built Dictionary<1107 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2257 corpus positions) +2024-07-25 12:44:03,453 - Dictionary lifecycle event {'msg': "built Dictionary<1107 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2257 corpus positions)", 'datetime': '2024-07-25T12:44:03.453037', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:03,454 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:03,454 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:03,454 - using serial LDA version on this node +2024-07-25 12:44:03,454 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:03,454 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:03,458 - -8.060 per-word bound, 266.9 perplexity estimate based on a held-out corpus of 1 documents with 2257 words +2024-07-25 12:44:03,458 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:03,460 - topic #0 (0.333): 0.018*"’" + 0.011*"well" + 0.009*"needs" + 0.008*"plans" + 0.005*"effective" + 0.005*"clear" + 0.005*"practice" + 0.005*"good" + 0.005*"risk" + 0.004*"range" +2024-07-25 12:44:03,460 - topic #1 (0.333): 0.011*"’" + 0.009*"plans" + 0.006*"well" + 0.006*"needs" + 0.005*"good" + 0.004*"need" + 0.004*"practice" + 0.004*"regularly" + 0.004*"Kingston" + 0.004*"effective" +2024-07-25 12:44:03,460 - topic #2 (0.333): 0.009*"’" + 0.008*"well" + 0.008*"plans" + 0.007*"needs" + 0.006*"good" + 0.005*"need" + 0.005*"parents" + 0.004*"supported" + 0.004*"appropriate" + 0.004*"effective" +2024-07-25 12:44:03,460 - topic diff=0.757437, rho=1.000000 +2024-07-25 12:44:03,460 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:03.460607', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:04,666 - Inspection date 2019-10-21 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:04,666 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:04,666 - Inspection date 2019-10-21 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:04,667 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:04,667 - Inspection date 2019-10-21 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:04,667 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:04,667 - Inspection date 2019-10-21 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:04,667 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:04,667 - Inspection date 2019-10-21 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:04,668 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:04,668 - Inspection date 2019-10-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:04,668 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:06,314 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:06,316 - built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2088 corpus positions) +2024-07-25 12:44:06,317 - Dictionary lifecycle event {'msg': "built Dictionary<1109 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2088 corpus positions)", 'datetime': '2024-07-25T12:44:06.317072', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:06,318 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:06,318 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:06,318 - using serial LDA version on this node +2024-07-25 12:44:06,318 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:06,319 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:06,322 - -8.116 per-word bound, 277.5 perplexity estimate based on a held-out corpus of 1 documents with 2088 words +2024-07-25 12:44:06,322 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:06,324 - topic #0 (0.333): 0.011*"’" + 0.005*"needs" + 0.005*"benefit" + 0.004*"well" + 0.004*"quality" + 0.004*"use" + 0.004*"plans" + 0.004*"actions" + 0.004*"information" + 0.004*"always" +2024-07-25 12:44:06,324 - topic #1 (0.333): 0.013*"’" + 0.007*"well" + 0.005*"needs" + 0.005*"effective" + 0.005*"plans" + 0.005*"quality" + 0.005*"use" + 0.004*"However" + 0.004*"health" + 0.004*"information" +2024-07-25 12:44:06,324 - topic #2 (0.333): 0.010*"’" + 0.005*"quality" + 0.005*"well" + 0.004*"plans" + 0.004*"needs" + 0.004*"information" + 0.003*"management" + 0.003*"case" + 0.003*"early" + 0.003*"informed" +2024-07-25 12:44:06,324 - topic diff=0.715778, rho=1.000000 +2024-07-25 12:44:06,324 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:06.324973', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:07,634 - Inspection date 2020-01-13 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:07,635 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:07,635 - Inspection date 2020-01-13 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:07,635 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:07,636 - Inspection date 2020-01-13 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:07,636 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:07,636 - Inspection date 2020-01-13 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:07,636 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:07,637 - Inspection date 2020-01-13 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:07,637 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:07,637 - Inspection date 2020-01-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:07,637 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:09,271 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:09,273 - built Dictionary<1089 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2211 corpus positions) +2024-07-25 12:44:09,273 - Dictionary lifecycle event {'msg': "built Dictionary<1089 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2211 corpus positions)", 'datetime': '2024-07-25T12:44:09.273594', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:09,274 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:09,274 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:09,275 - using serial LDA version on this node +2024-07-25 12:44:09,275 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:09,275 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:09,279 - -8.051 per-word bound, 265.3 perplexity estimate based on a held-out corpus of 1 documents with 2211 words +2024-07-25 12:44:09,279 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:09,280 - topic #0 (0.333): 0.021*"’" + 0.008*"Rutland" + 0.008*"effective" + 0.007*"needs" + 0.006*"need" + 0.006*"plans" + 0.006*"positive" + 0.006*"impact" + 0.005*"15" + 0.005*"practice" +2024-07-25 12:44:09,280 - topic #1 (0.333): 0.019*"’" + 0.011*"Rutland" + 0.010*"needs" + 0.007*"impact" + 0.006*"effective" + 0.006*"positive" + 0.005*"plans" + 0.005*"good" + 0.005*"need" + 0.005*"26" +2024-07-25 12:44:09,280 - topic #2 (0.333): 0.013*"’" + 0.006*"Rutland" + 0.006*"impact" + 0.005*"needs" + 0.005*"effective" + 0.004*"well" + 0.004*"practice" + 0.004*"positive" + 0.004*"good" + 0.004*"15" +2024-07-25 12:44:09,281 - topic diff=0.780367, rho=1.000000 +2024-07-25 12:44:09,281 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:09.281155', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:10,322 - Inspection date 2024-04-15 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:10,322 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:10,322 - Inspection date 2024-04-15 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:10,322 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:10,323 - Inspection date 2024-04-15 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:10,323 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:10,323 - Inspection date 2024-04-15 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:10,323 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:10,323 - Inspection date 2024-04-15 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:10,323 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:10,324 - Inspection date 2024-04-15 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:10,324 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:11,711 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:11,713 - built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2253 corpus positions) +2024-07-25 12:44:11,713 - Dictionary lifecycle event {'msg': "built Dictionary<1069 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2253 corpus positions)", 'datetime': '2024-07-25T12:44:11.713775', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:11,714 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:11,714 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:11,715 - using serial LDA version on this node +2024-07-25 12:44:11,715 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:11,715 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:11,719 - -8.007 per-word bound, 257.3 perplexity estimate based on a held-out corpus of 1 documents with 2253 words +2024-07-25 12:44:11,719 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:11,720 - topic #0 (0.333): 0.017*"’" + 0.009*"needs" + 0.008*"plans" + 0.008*"well" + 0.008*"Salford" + 0.007*"effective" + 0.006*"practice" + 0.006*"planning" + 0.005*"6" + 0.005*"experiences" +2024-07-25 12:44:11,721 - topic #1 (0.333): 0.013*"’" + 0.007*"plans" + 0.006*"well" + 0.006*"needs" + 0.005*"effective" + 0.005*"quality" + 0.005*"planning" + 0.004*"practice" + 0.004*"risks" + 0.004*"appropriate" +2024-07-25 12:44:11,721 - topic #2 (0.333): 0.010*"’" + 0.007*"plans" + 0.007*"effective" + 0.006*"well" + 0.005*"needs" + 0.005*"progress" + 0.004*"leaders" + 0.004*"Salford" + 0.004*"2023" + 0.004*"quality" +2024-07-25 12:44:11,721 - topic diff=0.792536, rho=1.000000 +2024-07-25 12:44:11,721 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:11.721529', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:12,563 - Inspection date 2023-11-06 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:12,563 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:12,563 - Inspection date 2023-11-06 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:12,563 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:12,564 - Inspection date 2023-11-06 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:12,564 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:12,564 - Inspection date 2023-11-06 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:12,564 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:12,564 - Inspection date 2023-11-06 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:12,564 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:12,565 - Inspection date 2023-11-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:12,565 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:14,499 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:14,501 - built Dictionary<995 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2066 corpus positions) +2024-07-25 12:44:14,502 - Dictionary lifecycle event {'msg': "built Dictionary<995 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2066 corpus positions)", 'datetime': '2024-07-25T12:44:14.502044', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:14,503 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:14,503 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:14,503 - using serial LDA version on this node +2024-07-25 12:44:14,503 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:14,503 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:14,507 - -7.945 per-word bound, 246.4 perplexity estimate based on a held-out corpus of 1 documents with 2066 words +2024-07-25 12:44:14,507 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:14,508 - topic #0 (0.333): 0.017*"’" + 0.007*"Sandwell" + 0.007*"needs" + 0.006*"well" + 0.005*"plans" + 0.005*"quality" + 0.005*"20" + 0.005*"9" + 0.004*"progress" + 0.004*"Trust" +2024-07-25 12:44:14,508 - topic #1 (0.333): 0.010*"’" + 0.009*"needs" + 0.008*"well" + 0.007*"plans" + 0.006*"Sandwell" + 0.006*"quality" + 0.005*"Trust" + 0.004*"progress" + 0.004*"good" + 0.004*"many" +2024-07-25 12:44:14,509 - topic #2 (0.333): 0.014*"’" + 0.008*"plans" + 0.008*"needs" + 0.008*"Sandwell" + 0.006*"well" + 0.006*"quality" + 0.005*"education" + 0.005*"number" + 0.005*"9" + 0.005*"Trust" +2024-07-25 12:44:14,509 - topic diff=0.763246, rho=1.000000 +2024-07-25 12:44:14,509 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:14.509333', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:15,496 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:15,496 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:15,497 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:15,497 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:15,497 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:15,497 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:15,497 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:15,497 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:15,497 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:15,498 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:15,498 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:15,498 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:17,319 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:17,322 - built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2300 corpus positions) +2024-07-25 12:44:17,322 - Dictionary lifecycle event {'msg': "built Dictionary<1023 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2300 corpus positions)", 'datetime': '2024-07-25T12:44:17.322222', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:17,323 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:17,323 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:17,323 - using serial LDA version on this node +2024-07-25 12:44:17,324 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:17,324 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:17,327 - -7.928 per-word bound, 243.6 perplexity estimate based on a held-out corpus of 1 documents with 2300 words +2024-07-25 12:44:17,327 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:17,329 - topic #0 (0.333): 0.011*"’" + 0.008*"needs" + 0.006*"protection" + 0.006*"practice" + 0.005*"management" + 0.005*"oversight" + 0.005*"many" + 0.005*"4" + 0.004*"need" + 0.004*"timely" +2024-07-25 12:44:17,329 - topic #1 (0.333): 0.017*"’" + 0.011*"needs" + 0.007*"practice" + 0.006*"including" + 0.006*"always" + 0.005*"many" + 0.005*"timely" + 0.005*"lack" + 0.005*"management" + 0.005*"oversight" +2024-07-25 12:44:17,329 - topic #2 (0.333): 0.018*"’" + 0.008*"needs" + 0.007*"oversight" + 0.005*"practice" + 0.005*"lack" + 0.005*"◼" + 0.005*"protection" + 0.005*"including" + 0.005*"March" + 0.005*"Sefton" +2024-07-25 12:44:17,329 - topic diff=0.794691, rho=1.000000 +2024-07-25 12:44:17,329 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:17.329685', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:18,324 - Inspection date 2022-02-21 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:18,324 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:18,324 - Inspection date 2022-02-21 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:18,324 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:18,324 - Inspection date 2022-02-21 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:18,325 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:18,325 - Inspection date 2022-02-21 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:18,325 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:18,325 - Inspection date 2022-02-21 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:18,325 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:18,325 - Inspection date 2022-02-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:18,326 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:21,088 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:21,092 - built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2327 corpus positions) +2024-07-25 12:44:21,093 - Dictionary lifecycle event {'msg': "built Dictionary<1124 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2327 corpus positions)", 'datetime': '2024-07-25T12:44:21.093132', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:21,094 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:21,095 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:21,095 - using serial LDA version on this node +2024-07-25 12:44:21,096 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:21,096 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:21,102 - -8.067 per-word bound, 268.1 perplexity estimate based on a held-out corpus of 1 documents with 2327 words +2024-07-25 12:44:21,102 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:21,104 - topic #0 (0.333): 0.021*"’" + 0.010*"Sheffield" + 0.007*"well" + 0.007*"needs" + 0.005*"leaders" + 0.005*"practice" + 0.005*"health" + 0.004*"plans" + 0.004*"adviser" + 0.004*"ensure" +2024-07-25 12:44:21,105 - topic #1 (0.333): 0.018*"’" + 0.009*"Sheffield" + 0.007*"needs" + 0.006*"well" + 0.006*"practice" + 0.005*"health" + 0.004*"leaders" + 0.004*"effective" + 0.004*"quality" + 0.004*"ensure" +2024-07-25 12:44:21,105 - topic #2 (0.333): 0.022*"’" + 0.013*"Sheffield" + 0.010*"needs" + 0.007*"well" + 0.006*"leaders" + 0.006*"practice" + 0.005*"health" + 0.005*"11" + 0.005*"good" + 0.005*"quality" +2024-07-25 12:44:21,105 - topic diff=0.771695, rho=1.000000 +2024-07-25 12:44:21,105 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:21.105962', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:22,441 - Inspection date 2023-09-11 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:22,442 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:22,442 - Inspection date 2023-09-11 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:22,442 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:22,442 - Inspection date 2023-09-11 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:22,442 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:22,442 - Inspection date 2023-09-11 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:22,443 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:22,443 - Inspection date 2023-09-11 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:22,443 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:22,443 - Inspection date 2023-09-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:22,443 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:23,752 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:23,754 - built Dictionary<939 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1749 corpus positions) +2024-07-25 12:44:23,754 - Dictionary lifecycle event {'msg': "built Dictionary<939 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 1749 corpus positions)", 'datetime': '2024-07-25T12:44:23.754570', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:23,755 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:23,755 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:23,755 - using serial LDA version on this node +2024-07-25 12:44:23,756 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:23,756 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:23,759 - -7.960 per-word bound, 249.1 perplexity estimate based on a held-out corpus of 1 documents with 1749 words +2024-07-25 12:44:23,759 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:23,760 - topic #0 (0.333): 0.023*"’" + 0.010*"needs" + 0.008*"well" + 0.008*"Shropshire" + 0.006*"plans" + 0.006*"progress" + 0.006*"practice" + 0.005*"making" + 0.005*"2022" + 0.005*"11" +2024-07-25 12:44:23,761 - topic #1 (0.333): 0.013*"’" + 0.007*"needs" + 0.006*"well" + 0.006*"Shropshire" + 0.005*"progress" + 0.005*"2022" + 0.005*"7" + 0.005*"making" + 0.005*"plans" + 0.004*"effectively" +2024-07-25 12:44:23,761 - topic #2 (0.333): 0.011*"’" + 0.007*"needs" + 0.005*"Shropshire" + 0.005*"progress" + 0.005*"well" + 0.005*"2022" + 0.004*"training" + 0.004*"making" + 0.004*"7" + 0.004*"plans" +2024-07-25 12:44:23,761 - topic diff=0.741175, rho=1.000000 +2024-07-25 12:44:23,761 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:23.761664', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:24,632 - Inspection date 2022-02-07 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:24,632 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:24,633 - Inspection date 2022-02-07 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:24,633 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:24,633 - Inspection date 2022-02-07 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:24,633 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:24,633 - Inspection date 2022-02-07 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:24,633 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:24,633 - Inspection date 2022-02-07 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:24,634 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:24,634 - Inspection date 2022-02-07 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:24,634 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:26,665 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:26,668 - built Dictionary<1113 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2352 corpus positions) +2024-07-25 12:44:26,668 - Dictionary lifecycle event {'msg': "built Dictionary<1113 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2352 corpus positions)", 'datetime': '2024-07-25T12:44:26.668607', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:26,669 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:26,669 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:26,670 - using serial LDA version on this node +2024-07-25 12:44:26,670 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:26,670 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:26,674 - -8.043 per-word bound, 263.8 perplexity estimate based on a held-out corpus of 1 documents with 2352 words +2024-07-25 12:44:26,674 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:26,675 - topic #0 (0.333): 0.014*"’" + 0.008*"Slough" + 0.007*"needs" + 0.006*"plans" + 0.005*"practice" + 0.005*"impact" + 0.005*"quality" + 0.005*"leaders" + 0.004*"senior" + 0.004*"supported" +2024-07-25 12:44:26,675 - topic #1 (0.333): 0.019*"’" + 0.008*"Slough" + 0.007*"quality" + 0.007*"practice" + 0.007*"plans" + 0.006*"3" + 0.005*"needs" + 0.005*"impact" + 0.005*"However" + 0.005*"23" +2024-07-25 12:44:26,675 - topic #2 (0.333): 0.012*"’" + 0.007*"Slough" + 0.006*"needs" + 0.005*"quality" + 0.005*"plans" + 0.004*"leaders" + 0.004*"need" + 0.004*"However" + 0.004*"2023" + 0.004*"practice" +2024-07-25 12:44:26,676 - topic diff=0.797216, rho=1.000000 +2024-07-25 12:44:26,676 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:26.676216', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:27,634 - Inspection date 2023-01-23 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:27,635 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:27,635 - Inspection date 2023-01-23 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:27,635 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:27,635 - Inspection date 2023-01-23 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:27,635 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:27,635 - Inspection date 2023-01-23 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:27,636 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:27,636 - Inspection date 2023-01-23 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:27,636 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:27,636 - Inspection date 2023-01-23 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:27,636 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:29,228 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:29,230 - built Dictionary<996 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2163 corpus positions) +2024-07-25 12:44:29,231 - Dictionary lifecycle event {'msg': "built Dictionary<996 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2163 corpus positions)", 'datetime': '2024-07-25T12:44:29.231086', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:29,232 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:29,232 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:29,232 - using serial LDA version on this node +2024-07-25 12:44:29,232 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:29,232 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:29,236 - -7.920 per-word bound, 242.2 perplexity estimate based on a held-out corpus of 1 documents with 2163 words +2024-07-25 12:44:29,236 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:29,237 - topic #0 (0.333): 0.016*"’" + 0.010*"lack" + 0.009*"2022" + 0.008*"Solihull" + 0.006*"need" + 0.006*"risk" + 0.006*"experiences" + 0.005*"quality" + 0.005*"practice" + 0.005*"means" +2024-07-25 12:44:29,237 - topic #1 (0.333): 0.017*"’" + 0.010*"lack" + 0.009*"2022" + 0.007*"need" + 0.006*"risk" + 0.006*"practice" + 0.005*"Solihull" + 0.005*"effective" + 0.005*"quality" + 0.005*"plans" +2024-07-25 12:44:29,238 - topic #2 (0.333): 0.013*"’" + 0.011*"lack" + 0.007*"2022" + 0.006*"quality" + 0.005*"significant" + 0.005*"effective" + 0.005*"risk" + 0.004*"Solihull" + 0.004*"experiences" + 0.004*"practice" +2024-07-25 12:44:29,238 - topic diff=0.789957, rho=1.000000 +2024-07-25 12:44:29,238 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:29.238218', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:30,335 - Inspection date 2022-10-31 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:30,336 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:30,336 - Inspection date 2022-10-31 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:30,336 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:30,337 - Inspection date 2022-10-31 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:30,337 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:30,337 - Inspection date 2022-10-31 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:30,337 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:30,338 - Inspection date 2022-10-31 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:30,338 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:30,338 - Inspection date 2022-10-31 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:30,338 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:32,448 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:32,450 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2181 corpus positions) +2024-07-25 12:44:32,450 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2181 corpus positions)", 'datetime': '2024-07-25T12:44:32.450878', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:32,451 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:32,452 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:32,452 - using serial LDA version on this node +2024-07-25 12:44:32,452 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:32,452 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:32,456 - -7.921 per-word bound, 242.3 perplexity estimate based on a held-out corpus of 1 documents with 2181 words +2024-07-25 12:44:32,456 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:32,457 - topic #0 (0.333): 0.018*"’" + 0.011*"well" + 0.009*"needs" + 0.007*"good" + 0.007*"Somerset" + 0.006*"effective" + 0.005*"plans" + 0.005*"positive" + 0.005*"practice" + 0.005*"supported" +2024-07-25 12:44:32,457 - topic #1 (0.333): 0.017*"’" + 0.008*"needs" + 0.007*"well" + 0.006*"Somerset" + 0.006*"plans" + 0.005*"need" + 0.005*"leaders" + 0.005*"supported" + 0.005*"including" + 0.005*"number" +2024-07-25 12:44:32,457 - topic #2 (0.333): 0.015*"’" + 0.008*"well" + 0.007*"needs" + 0.007*"Somerset" + 0.006*"plans" + 0.006*"leaders" + 0.005*"progress" + 0.005*"number" + 0.005*"good" + 0.005*"supported" +2024-07-25 12:44:32,458 - topic diff=0.803079, rho=1.000000 +2024-07-25 12:44:32,458 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:32.458188', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:33,386 - Inspection date 2022-07-18 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:33,387 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:33,387 - Inspection date 2022-07-18 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:33,387 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:33,387 - Inspection date 2022-07-18 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:33,387 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:33,388 - Inspection date 2022-07-18 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:33,388 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:33,388 - Inspection date 2022-07-18 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:33,388 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:33,388 - Inspection date 2022-07-18 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:33,388 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:34,836 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:34,839 - built Dictionary<1188 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2751 corpus positions) +2024-07-25 12:44:34,839 - Dictionary lifecycle event {'msg': "built Dictionary<1188 unique tokens: ['0', '0161', '0300', '1', '10']...> from 1 documents (total 2751 corpus positions)", 'datetime': '2024-07-25T12:44:34.839597', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:34,840 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:34,840 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:34,841 - using serial LDA version on this node +2024-07-25 12:44:34,841 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:34,841 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:34,845 - -8.052 per-word bound, 265.5 perplexity estimate based on a held-out corpus of 1 documents with 2751 words +2024-07-25 12:44:34,845 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:34,847 - topic #0 (0.333): 0.018*"’" + 0.010*"needs" + 0.007*"June" + 0.006*"2024" + 0.006*"leaders" + 0.006*"effective" + 0.006*"plans" + 0.006*"well" + 0.005*"understand" + 0.005*"progress" +2024-07-25 12:44:34,847 - topic #1 (0.333): 0.014*"’" + 0.009*"needs" + 0.007*"2024" + 0.007*"leaders" + 0.006*"June" + 0.006*"ensure" + 0.005*"Gloucestershire" + 0.005*"strong" + 0.005*"effective" + 0.004*"well" +2024-07-25 12:44:34,847 - topic #2 (0.333): 0.020*"’" + 0.010*"needs" + 0.007*"leaders" + 0.006*"well" + 0.006*"June" + 0.006*"2024" + 0.005*"plans" + 0.005*"ensure" + 0.005*"South" + 0.005*"understand" +2024-07-25 12:44:34,847 - topic diff=0.834260, rho=1.000000 +2024-07-25 12:44:34,847 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:34.847868', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:35,774 - Inspection date 2024-06-03 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:35,775 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:35,775 - Inspection date 2024-06-03 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:35,775 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:35,775 - Inspection date 2024-06-03 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:35,775 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:35,776 - Inspection date 2024-06-03 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:35,776 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:35,776 - Inspection date 2024-06-03 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:35,776 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:35,776 - Inspection date 2024-06-03 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:35,776 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:37,843 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:37,845 - built Dictionary<981 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2189 corpus positions) +2024-07-25 12:44:37,845 - Dictionary lifecycle event {'msg': 'built Dictionary<981 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2189 corpus positions)', 'datetime': '2024-07-25T12:44:37.845830', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:37,846 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:37,846 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:37,847 - using serial LDA version on this node +2024-07-25 12:44:37,847 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:37,847 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:37,851 - -7.888 per-word bound, 236.8 perplexity estimate based on a held-out corpus of 1 documents with 2189 words +2024-07-25 12:44:37,851 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:37,852 - topic #0 (0.333): 0.021*"’" + 0.008*"needs" + 0.006*"South" + 0.006*"Tyneside" + 0.005*"15" + 0.005*"carers" + 0.005*"However" + 0.005*"oversight" + 0.005*"2023" + 0.005*"effective" +2024-07-25 12:44:37,852 - topic #1 (0.333): 0.027*"’" + 0.011*"needs" + 0.009*"Tyneside" + 0.008*"South" + 0.006*"oversight" + 0.006*"carers" + 0.005*"effective" + 0.005*"However" + 0.005*"management" + 0.005*"December" +2024-07-25 12:44:37,852 - topic #2 (0.333): 0.023*"’" + 0.007*"South" + 0.007*"needs" + 0.006*"Tyneside" + 0.005*"2022" + 0.005*"management" + 0.005*"14" + 0.005*"oversight" + 0.005*"2023" + 0.004*"progress" +2024-07-25 12:44:37,853 - topic diff=0.799923, rho=1.000000 +2024-07-25 12:44:37,853 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:37.853189', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:38,838 - Inspection date 2022-12-05 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:38,838 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:38,838 - Inspection date 2022-12-05 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:38,838 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:38,838 - Inspection date 2022-12-05 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:38,839 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:38,839 - Inspection date 2022-12-05 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:38,839 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:38,839 - Inspection date 2022-12-05 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:38,839 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:38,839 - Inspection date 2022-12-05 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:38,839 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:40,579 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:40,581 - built Dictionary<1178 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2318 corpus positions) +2024-07-25 12:44:40,581 - Dictionary lifecycle event {'msg': "built Dictionary<1178 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2318 corpus positions)", 'datetime': '2024-07-25T12:44:40.581655', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:40,582 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:40,582 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:40,583 - using serial LDA version on this node +2024-07-25 12:44:40,583 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:40,583 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:40,587 - -8.146 per-word bound, 283.2 perplexity estimate based on a held-out corpus of 1 documents with 2318 words +2024-07-25 12:44:40,587 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:40,589 - topic #0 (0.333): 0.014*"’" + 0.006*"Southampton" + 0.005*"plans" + 0.005*"improve" + 0.005*"experiences" + 0.005*"progress" + 0.004*"including" + 0.004*"2023" + 0.004*"5" + 0.004*"good" +2024-07-25 12:44:40,589 - topic #1 (0.333): 0.021*"’" + 0.006*"Southampton" + 0.006*"plans" + 0.005*"including" + 0.005*"progress" + 0.004*"improve" + 0.004*"needs" + 0.004*"make" + 0.004*"16" + 0.004*"5" +2024-07-25 12:44:40,589 - topic #2 (0.333): 0.013*"’" + 0.006*"plans" + 0.005*"needs" + 0.005*"well" + 0.005*"Southampton" + 0.005*"5" + 0.004*"progress" + 0.004*"improve" + 0.004*"16" + 0.004*"timely" +2024-07-25 12:44:40,589 - topic diff=0.740455, rho=1.000000 +2024-07-25 12:44:40,589 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:40.589748', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:41,964 - Inspection date 2023-06-05 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:41,964 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:41,964 - Inspection date 2023-06-05 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:41,964 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:41,965 - Inspection date 2023-06-05 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:41,965 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:41,965 - Inspection date 2023-06-05 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:41,965 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:41,965 - Inspection date 2023-06-05 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:41,965 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:41,966 - Inspection date 2023-06-05 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:41,966 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:43,898 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:43,900 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2086 corpus positions) +2024-07-25 12:44:43,900 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2086 corpus positions)", 'datetime': '2024-07-25T12:44:43.900745', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:43,901 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:43,901 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:43,902 - using serial LDA version on this node +2024-07-25 12:44:43,902 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:43,902 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:43,906 - -7.947 per-word bound, 246.7 perplexity estimate based on a held-out corpus of 1 documents with 2086 words +2024-07-25 12:44:43,906 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:43,907 - topic #0 (0.333): 0.011*"’" + 0.007*"planning" + 0.006*"practice" + 0.006*"quality" + 0.005*"good" + 0.005*"carers" + 0.005*"protection" + 0.005*"within" + 0.005*"leaders" + 0.005*"need" +2024-07-25 12:44:43,907 - topic #1 (0.333): 0.014*"’" + 0.007*"leaders" + 0.007*"planning" + 0.007*"practice" + 0.006*"protection" + 0.005*"quality" + 0.005*"risk" + 0.005*"However" + 0.005*"effective" + 0.005*"number" +2024-07-25 12:44:43,907 - topic #2 (0.333): 0.014*"’" + 0.009*"planning" + 0.008*"quality" + 0.008*"practice" + 0.006*"number" + 0.006*"leaders" + 0.005*"within" + 0.005*"always" + 0.005*"needs" + 0.005*"protection" +2024-07-25 12:44:43,908 - topic diff=0.770550, rho=1.000000 +2024-07-25 12:44:43,908 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:43.908200', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:45,706 - Inspection date 2019-07-15 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:45,706 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:45,707 - Inspection date 2019-07-15 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:45,707 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:45,707 - Inspection date 2019-07-15 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:45,707 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:45,707 - Inspection date 2019-07-15 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:45,707 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:45,708 - Inspection date 2019-07-15 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:45,708 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:45,708 - Inspection date 2019-07-15 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:45,708 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:47,164 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:47,166 - built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2218 corpus positions) +2024-07-25 12:44:47,167 - Dictionary lifecycle event {'msg': "built Dictionary<1092 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2218 corpus positions)", 'datetime': '2024-07-25T12:44:47.167079', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:47,168 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:47,168 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:47,168 - using serial LDA version on this node +2024-07-25 12:44:47,168 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:47,169 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:47,172 - -8.051 per-word bound, 265.2 perplexity estimate based on a held-out corpus of 1 documents with 2218 words +2024-07-25 12:44:47,172 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:47,174 - topic #0 (0.333): 0.015*"’" + 0.007*"well" + 0.007*"St" + 0.007*"needs" + 0.007*"10" + 0.007*"progress" + 0.007*"Helens" + 0.006*"receive" + 0.005*"good" + 0.005*"21" +2024-07-25 12:44:47,174 - topic #1 (0.333): 0.017*"’" + 0.008*"St" + 0.007*"needs" + 0.007*"well" + 0.007*"Helens" + 0.006*"need" + 0.006*"risk" + 0.006*"good" + 0.005*"receive" + 0.005*"progress" +2024-07-25 12:44:47,174 - topic #2 (0.333): 0.015*"’" + 0.009*"Helens" + 0.007*"St" + 0.007*"needs" + 0.006*"21" + 0.006*"need" + 0.005*"progress" + 0.005*"good" + 0.005*"well" + 0.005*"oversight" +2024-07-25 12:44:47,174 - topic diff=0.767832, rho=1.000000 +2024-07-25 12:44:47,174 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:47.174716', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:48,210 - Inspection date 2023-07-10 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:48,210 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:48,210 - Inspection date 2023-07-10 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:48,210 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:48,210 - Inspection date 2023-07-10 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:48,210 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:48,211 - Inspection date 2023-07-10 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:48,211 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:48,211 - Inspection date 2023-07-10 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:48,211 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:48,211 - Inspection date 2023-07-10 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:48,211 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:49,917 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:49,919 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2334 corpus positions) +2024-07-25 12:44:49,919 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2334 corpus positions)", 'datetime': '2024-07-25T12:44:49.919646', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:49,920 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:49,920 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:49,921 - using serial LDA version on this node +2024-07-25 12:44:49,921 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:49,921 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:49,925 - -7.993 per-word bound, 254.7 perplexity estimate based on a held-out corpus of 1 documents with 2334 words +2024-07-25 12:44:49,925 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:49,926 - topic #0 (0.333): 0.019*"’" + 0.010*"needs" + 0.006*"quality" + 0.006*"practice" + 0.006*"progress" + 0.006*"oversight" + 0.005*"Staffordshire" + 0.005*"health" + 0.005*"ensure" + 0.005*"plans" +2024-07-25 12:44:49,926 - topic #1 (0.333): 0.018*"’" + 0.014*"needs" + 0.006*"health" + 0.006*"Staffordshire" + 0.006*"practice" + 0.006*"progress" + 0.006*"quality" + 0.005*"ensure" + 0.005*"plans" + 0.005*"oversight" +2024-07-25 12:44:49,926 - topic #2 (0.333): 0.013*"’" + 0.011*"needs" + 0.006*"quality" + 0.006*"ensure" + 0.006*"oversight" + 0.005*"progress" + 0.005*"practice" + 0.004*"health" + 0.004*"Staffordshire" + 0.004*"good" +2024-07-25 12:44:49,927 - topic diff=0.801267, rho=1.000000 +2024-07-25 12:44:49,927 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:49.927221', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:50,814 - Inspection date 2023-11-06 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:50,814 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:50,814 - Inspection date 2023-11-06 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:50,814 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:50,815 - Inspection date 2023-11-06 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:50,815 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:50,815 - Inspection date 2023-11-06 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:50,815 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:50,815 - Inspection date 2023-11-06 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:50,815 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:50,816 - Inspection date 2023-11-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:50,816 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:52,783 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:52,785 - built Dictionary<1060 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions) +2024-07-25 12:44:52,785 - Dictionary lifecycle event {'msg': "built Dictionary<1060 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2316 corpus positions)", 'datetime': '2024-07-25T12:44:52.785908', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:52,786 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:52,787 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:52,787 - using serial LDA version on this node +2024-07-25 12:44:52,787 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:52,787 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:52,791 - -7.978 per-word bound, 252.2 perplexity estimate based on a held-out corpus of 1 documents with 2316 words +2024-07-25 12:44:52,791 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:52,792 - topic #0 (0.333): 0.013*"’" + 0.010*"practice" + 0.008*"well" + 0.007*"Stockport" + 0.006*"strong" + 0.006*"needs" + 0.005*"risk" + 0.005*"leaders" + 0.005*"plans" + 0.005*"ensure" +2024-07-25 12:44:52,792 - topic #1 (0.333): 0.009*"’" + 0.009*"well" + 0.007*"needs" + 0.006*"Stockport" + 0.005*"practice" + 0.005*"strong" + 0.005*"risk" + 0.004*"team" + 0.004*"ensure" + 0.004*"1" +2024-07-25 12:44:52,793 - topic #2 (0.333): 0.010*"’" + 0.007*"well" + 0.006*"plans" + 0.006*"Stockport" + 0.006*"practice" + 0.005*"quality" + 0.005*"needs" + 0.005*"strong" + 0.004*"28" + 0.004*"range" +2024-07-25 12:44:52,793 - topic diff=0.790834, rho=1.000000 +2024-07-25 12:44:52,793 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:52.793438', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:53,841 - Inspection date 2022-03-28 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:53,842 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:53,842 - Inspection date 2022-03-28 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:53,842 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:53,843 - Inspection date 2022-03-28 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:53,843 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:53,843 - Inspection date 2022-03-28 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:53,843 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:53,843 - Inspection date 2022-03-28 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:53,843 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:53,844 - Inspection date 2022-03-28 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:53,844 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:55,445 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:55,447 - built Dictionary<1044 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2269 corpus positions) +2024-07-25 12:44:55,447 - Dictionary lifecycle event {'msg': "built Dictionary<1044 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2269 corpus positions)", 'datetime': '2024-07-25T12:44:55.447519', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:55,448 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:55,448 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:55,448 - using serial LDA version on this node +2024-07-25 12:44:55,449 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:55,449 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:55,452 - -7.966 per-word bound, 250.0 perplexity estimate based on a held-out corpus of 1 documents with 2269 words +2024-07-25 12:44:55,452 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:55,454 - topic #0 (0.333): 0.017*"’" + 0.007*"well" + 0.007*"leaders" + 0.006*"plans" + 0.006*"on-Tees" + 0.005*"needs" + 0.004*"good" + 0.004*"quality" + 0.004*"Stockton" + 0.004*"17" +2024-07-25 12:44:55,454 - topic #1 (0.333): 0.020*"’" + 0.009*"leaders" + 0.009*"plans" + 0.008*"needs" + 0.007*"Stockton" + 0.007*"on-Tees" + 0.007*"well" + 0.006*"quality" + 0.005*"good" + 0.005*"carers" +2024-07-25 12:44:55,454 - topic #2 (0.333): 0.020*"’" + 0.009*"plans" + 0.009*"leaders" + 0.007*"quality" + 0.006*"good" + 0.006*"senior" + 0.005*"needs" + 0.005*"Stockton" + 0.005*"well" + 0.005*"17" +2024-07-25 12:44:55,454 - topic diff=0.771562, rho=1.000000 +2024-07-25 12:44:55,454 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:55.454779', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:56,339 - Inspection date 2023-03-06 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:56,340 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:56,340 - Inspection date 2023-03-06 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:56,340 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:56,340 - Inspection date 2023-03-06 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:56,340 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:56,340 - Inspection date 2023-03-06 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:56,341 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:56,341 - Inspection date 2023-03-06 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:56,341 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:56,341 - Inspection date 2023-03-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:56,341 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:57,884 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:44:57,887 - built Dictionary<986 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2165 corpus positions) +2024-07-25 12:44:57,887 - Dictionary lifecycle event {'msg': "built Dictionary<986 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2165 corpus positions)", 'datetime': '2024-07-25T12:44:57.887333', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:57,888 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:44:57,888 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:44:57,888 - using serial LDA version on this node +2024-07-25 12:44:57,889 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:44:57,889 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:44:57,892 - -7.904 per-word bound, 239.5 perplexity estimate based on a held-out corpus of 1 documents with 2165 words +2024-07-25 12:44:57,892 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:44:57,893 - topic #0 (0.333): 0.014*"’" + 0.009*"needs" + 0.008*"Stoke" + 0.007*"However" + 0.006*"well" + 0.006*"protection" + 0.006*"ensure" + 0.005*"plans" + 0.005*"quality" + 0.005*"need" +2024-07-25 12:44:57,894 - topic #1 (0.333): 0.023*"’" + 0.008*"on-Trent" + 0.008*"plans" + 0.008*"needs" + 0.007*"However" + 0.007*"well" + 0.006*"Stoke" + 0.006*"progress" + 0.005*"quality" + 0.005*"ensure" +2024-07-25 12:44:57,894 - topic #2 (0.333): 0.013*"’" + 0.009*"needs" + 0.007*"well" + 0.007*"on-Trent" + 0.006*"protection" + 0.006*"Stoke" + 0.005*"plans" + 0.005*"ensure" + 0.005*"However" + 0.005*"3" +2024-07-25 12:44:57,894 - topic diff=0.778211, rho=1.000000 +2024-07-25 12:44:57,894 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:44:57.894576', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:44:58,786 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:44:58,786 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:58,787 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:44:58,787 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:58,787 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:44:58,787 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:58,787 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:44:58,787 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:58,788 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:44:58,788 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:44:58,788 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:44:58,788 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:00,246 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:00,249 - built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2286 corpus positions) +2024-07-25 12:45:00,249 - Dictionary lifecycle event {'msg': "built Dictionary<1192 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2286 corpus positions)", 'datetime': '2024-07-25T12:45:00.249248', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:00,250 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:00,250 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:00,250 - using serial LDA version on this node +2024-07-25 12:45:00,251 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:00,251 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:00,258 - -8.180 per-word bound, 290.0 perplexity estimate based on a held-out corpus of 1 documents with 2286 words +2024-07-25 12:45:00,258 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:00,261 - topic #0 (0.333): 0.013*"’" + 0.007*"progress" + 0.006*"well" + 0.005*"leaders" + 0.005*"effective" + 0.005*"good" + 0.004*"needs" + 0.004*"ensure" + 0.004*"practice" + 0.004*"issues" +2024-07-25 12:45:00,261 - topic #1 (0.333): 0.013*"’" + 0.007*"well" + 0.006*"progress" + 0.005*"leaders" + 0.005*"effective" + 0.004*"ensure" + 0.004*"carers" + 0.004*"good" + 0.004*"need" + 0.004*"practice" +2024-07-25 12:45:00,261 - topic #2 (0.333): 0.013*"’" + 0.006*"well" + 0.005*"good" + 0.005*"progress" + 0.004*"effective" + 0.004*"practice" + 0.004*"ensure" + 0.003*"needs" + 0.003*"experiences" + 0.003*"high" +2024-07-25 12:45:00,261 - topic diff=0.722914, rho=1.000000 +2024-07-25 12:45:00,261 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:00.261861', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:01,577 - Got stderr: Jul 25, 2024 12:45:01 PM org.apache.pdfbox.pdmodel.font.PDTrueTypeFont WARNING: Using fallback font 'LiberationSans' for 'TimesNewRomanPSMT' -2024-07-15 10:48:07,600 - Inspection date 2019-04-08 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:07,600 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:07,601 - Inspection date 2019-04-08 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:07,601 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:07,601 - Inspection date 2019-04-08 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:07,601 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:07,601 - Inspection date 2019-04-08 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:07,601 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:07,601 - Inspection date 2019-04-08 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:07,602 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:07,602 - Inspection date 2019-04-08 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:07,602 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:09,011 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:09,014 - built Dictionary<1128 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2409 corpus positions) -2024-07-15 10:48:09,015 - Dictionary lifecycle event {'msg': "built Dictionary<1128 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2409 corpus positions)", 'datetime': '2024-07-15T10:48:09.015201', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:09,016 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:09,016 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:09,016 - using serial LDA version on this node -2024-07-15 10:48:09,017 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:09,017 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:09,021 - -8.055 per-word bound, 265.9 perplexity estimate based on a held-out corpus of 1 documents with 2409 words -2024-07-15 10:48:09,021 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:09,023 - topic #0 (0.333): 0.017*"’" + 0.008*"well" + 0.007*"Sunderland" + 0.007*"needs" + 0.006*"experienced" + 0.006*"quality" + 0.006*"TfC" + 0.005*"practice" + 0.005*"highly" + 0.005*"council" -2024-07-15 10:48:09,023 - topic #1 (0.333): 0.013*"’" + 0.007*"well" + 0.006*"quality" + 0.005*"needs" + 0.005*"parents" + 0.005*"need" + 0.004*"protection" + 0.004*"training" + 0.004*"practice" + 0.004*"Sunderland" -2024-07-15 10:48:09,023 - topic #2 (0.333): 0.018*"’" + 0.007*"quality" + 0.006*"needs" + 0.006*"well" + 0.005*"Sunderland" + 0.004*"good" + 0.004*"council" + 0.004*"practice" + 0.004*"experienced" + 0.004*"result" -2024-07-15 10:48:09,024 - topic diff=0.786320, rho=1.000000 -2024-07-15 10:48:09,024 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:09.024225', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:10,186 - Inspection date 2021-06-28 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:10,186 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:10,186 - Inspection date 2021-06-28 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:10,186 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:10,186 - Inspection date 2021-06-28 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:10,187 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:10,187 - Inspection date 2021-06-28 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:10,187 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:10,187 - Inspection date 2021-06-28 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:10,187 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:10,187 - Inspection date 2021-06-28 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:10,188 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:11,793 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:11,796 - built Dictionary<1016 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2111 corpus positions) -2024-07-15 10:48:11,797 - Dictionary lifecycle event {'msg': "built Dictionary<1016 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2111 corpus positions)", 'datetime': '2024-07-15T10:48:11.797007', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:11,798 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:11,798 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:11,799 - using serial LDA version on this node -2024-07-15 10:48:11,799 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:11,799 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:11,805 - -7.958 per-word bound, 248.7 perplexity estimate based on a held-out corpus of 1 documents with 2111 words -2024-07-15 10:48:11,805 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:11,808 - topic #0 (0.333): 0.017*"’" + 0.010*"well" + 0.010*"needs" + 0.009*"practice" + 0.007*"progress" + 0.006*"effective" + 0.006*"plans" + 0.005*"carers" + 0.005*"good" + 0.005*"However" -2024-07-15 10:48:11,808 - topic #1 (0.333): 0.012*"’" + 0.012*"needs" + 0.008*"well" + 0.006*"progress" + 0.005*"17" + 0.005*"plans" + 0.005*"practice" + 0.005*"ensure" + 0.004*"However" + 0.004*"quality" -2024-07-15 10:48:11,809 - topic #2 (0.333): 0.010*"’" + 0.009*"well" + 0.007*"needs" + 0.006*"practice" + 0.006*"good" + 0.005*"progress" + 0.005*"quality" + 0.005*"carers" + 0.005*"Surrey" + 0.004*"January" -2024-07-15 10:48:11,809 - topic diff=0.765161, rho=1.000000 -2024-07-15 10:48:11,809 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:11.809429', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:13,050 - Inspection date 2022-01-17 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:13,050 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:13,050 - Inspection date 2022-01-17 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:13,050 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:13,050 - Inspection date 2022-01-17 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:13,050 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:13,051 - Inspection date 2022-01-17 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:13,051 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:13,051 - Inspection date 2022-01-17 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:13,051 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:13,051 - Inspection date 2022-01-17 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:13,051 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:14,549 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:14,551 - built Dictionary<951 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2229 corpus positions) -2024-07-15 10:48:14,551 - Dictionary lifecycle event {'msg': "built Dictionary<951 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2229 corpus positions)", 'datetime': '2024-07-15T10:48:14.551530', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:14,552 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:14,552 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:14,552 - using serial LDA version on this node -2024-07-15 10:48:14,553 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:14,553 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:14,556 - -7.831 per-word bound, 227.7 perplexity estimate based on a held-out corpus of 1 documents with 2229 words -2024-07-15 10:48:14,556 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:14,558 - topic #0 (0.333): 0.015*"’" + 0.010*"needs" + 0.007*"Swindon" + 0.007*"need" + 0.005*"well" + 0.005*"always" + 0.005*"plans" + 0.004*"health" + 0.004*"impact" + 0.004*"many" -2024-07-15 10:48:14,558 - topic #1 (0.333): 0.029*"’" + 0.015*"needs" + 0.009*"well" + 0.009*"need" + 0.009*"Swindon" + 0.007*"always" + 0.007*"plans" + 0.007*"health" + 0.006*"effective" + 0.006*"impact" -2024-07-15 10:48:14,558 - topic #2 (0.333): 0.017*"’" + 0.012*"needs" + 0.010*"Swindon" + 0.009*"need" + 0.008*"well" + 0.007*"plans" + 0.006*"always" + 0.005*"impact" + 0.005*"many" + 0.005*"Borough" -2024-07-15 10:48:14,558 - topic diff=0.845518, rho=1.000000 -2024-07-15 10:48:14,558 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:14.558696', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:15,543 - Inspection date 2023-07-17 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:15,543 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:15,543 - Inspection date 2023-07-17 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:15,543 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:15,544 - Inspection date 2023-07-17 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:15,544 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:15,544 - Inspection date 2023-07-17 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:15,544 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:15,544 - Inspection date 2023-07-17 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:15,544 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:15,545 - Inspection date 2023-07-17 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:15,545 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:17,033 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:17,036 - built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2491 corpus positions) -2024-07-15 10:48:17,036 - Dictionary lifecycle event {'msg': "built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2491 corpus positions)", 'datetime': '2024-07-15T10:48:17.036481', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:17,037 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:17,037 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:17,037 - using serial LDA version on this node -2024-07-15 10:48:17,038 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:17,038 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:17,041 - -7.942 per-word bound, 245.9 perplexity estimate based on a held-out corpus of 1 documents with 2491 words -2024-07-15 10:48:17,042 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:17,043 - topic #0 (0.333): 0.018*"’" + 0.011*"needs" + 0.008*"impact" + 0.007*"risk" + 0.006*"practice" + 0.006*"experienced" + 0.006*"quality" + 0.005*"experiences" + 0.005*"effective" + 0.005*"Tameside" -2024-07-15 10:48:17,043 - topic #1 (0.333): 0.013*"’" + 0.007*"needs" + 0.006*"4" + 0.006*"risk" + 0.006*"2023" + 0.005*"quality" + 0.005*"leaders" + 0.005*"response" + 0.005*"impact" + 0.004*"progress" -2024-07-15 10:48:17,043 - topic #2 (0.333): 0.017*"’" + 0.008*"needs" + 0.005*"experienced" + 0.005*"15" + 0.005*"practice" + 0.005*"quality" + 0.005*"2023" + 0.005*"impact" + 0.005*"experiences" + 0.005*"risk" -2024-07-15 10:48:17,043 - topic diff=0.820074, rho=1.000000 -2024-07-15 10:48:17,044 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:17.043981', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:18,704 - Inspection date 2023-12-04 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:18,705 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:18,705 - Inspection date 2023-12-04 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:18,705 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:18,705 - Inspection date 2023-12-04 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:18,705 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:18,705 - Inspection date 2023-12-04 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:18,705 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:18,706 - Inspection date 2023-12-04 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:18,706 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:18,706 - Inspection date 2023-12-04 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:18,706 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:20,092 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:20,095 - built Dictionary<1077 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2452 corpus positions) -2024-07-15 10:48:20,095 - Dictionary lifecycle event {'msg': "built Dictionary<1077 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2452 corpus positions)", 'datetime': '2024-07-15T10:48:20.095168', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:20,096 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:20,096 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:20,096 - using serial LDA version on this node -2024-07-15 10:48:20,096 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:20,097 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:20,101 - -7.970 per-word bound, 250.7 perplexity estimate based on a held-out corpus of 1 documents with 2452 words -2024-07-15 10:48:20,102 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:20,103 - topic #0 (0.333): 0.014*"’" + 0.009*"needs" + 0.006*"Telford" + 0.006*"Family" + 0.005*"benefit" + 0.005*"plans" + 0.005*"Wrekin" + 0.004*"2024" + 0.004*"leaders" + 0.004*"3" -2024-07-15 10:48:20,103 - topic #1 (0.333): 0.020*"’" + 0.012*"needs" + 0.011*"Wrekin" + 0.009*"Telford" + 0.007*"well" + 0.006*"plans" + 0.005*"effective" + 0.005*"3" + 0.005*"benefit" + 0.005*"29" -2024-07-15 10:48:20,103 - topic #2 (0.333): 0.027*"’" + 0.011*"needs" + 0.007*"benefit" + 0.007*"Telford" + 0.007*"Wrekin" + 0.006*"effective" + 0.006*"well" + 0.006*"Family" + 0.005*"PAs" + 0.005*"provide" -2024-07-15 10:48:20,103 - topic diff=0.825432, rho=1.000000 -2024-07-15 10:48:20,103 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:20.103959', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:21,177 - Inspection date 2024-04-29 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:21,177 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:21,178 - Inspection date 2024-04-29 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:21,178 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:21,178 - Inspection date 2024-04-29 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:21,178 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:21,178 - Inspection date 2024-04-29 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:21,178 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:21,179 - Inspection date 2024-04-29 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:21,179 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:21,179 - Inspection date 2024-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:21,179 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:22,525 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:22,528 - built Dictionary<1138 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2160 corpus positions) -2024-07-15 10:48:22,528 - Dictionary lifecycle event {'msg': "built Dictionary<1138 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2160 corpus positions)", 'datetime': '2024-07-15T10:48:22.528199', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:22,529 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:22,529 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:22,529 - using serial LDA version on this node -2024-07-15 10:48:22,530 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:22,530 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:22,533 - -8.140 per-word bound, 282.1 perplexity estimate based on a held-out corpus of 1 documents with 2160 words -2024-07-15 10:48:22,533 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:22,535 - topic #0 (0.333): 0.014*"’" + 0.006*"well" + 0.005*"need" + 0.005*"leaders" + 0.005*"carers" + 0.004*"ensure" + 0.004*"Thurrock" + 0.004*"practice" + 0.004*"needs" + 0.004*"effective" -2024-07-15 10:48:22,535 - topic #1 (0.333): 0.012*"’" + 0.008*"well" + 0.005*"carers" + 0.005*"need" + 0.004*"practice" + 0.004*"ensure" + 0.004*"effective" + 0.004*"plans" + 0.004*"protection" + 0.003*"needs" -2024-07-15 10:48:22,535 - topic #2 (0.333): 0.014*"’" + 0.011*"well" + 0.006*"carers" + 0.005*"needs" + 0.004*"need" + 0.004*"impact" + 0.004*"protect" + 0.004*"practice" + 0.004*"parents" + 0.004*"Thurrock" -2024-07-15 10:48:22,535 - topic diff=0.722700, rho=1.000000 -2024-07-15 10:48:22,535 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:22.535978', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:24,702 - Inspection date 2019-11-11 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:24,702 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:24,702 - Inspection date 2019-11-11 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:24,703 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:24,703 - Inspection date 2019-11-11 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:24,703 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:24,703 - Inspection date 2019-11-11 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:24,703 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:24,703 - Inspection date 2019-11-11 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:24,703 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:24,704 - Inspection date 2019-11-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:24,704 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:25,913 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:25,915 - built Dictionary<1054 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2065 corpus positions) -2024-07-15 10:48:25,915 - Dictionary lifecycle event {'msg': "built Dictionary<1054 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2065 corpus positions)", 'datetime': '2024-07-15T10:48:25.915933', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:25,916 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:25,917 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:25,917 - using serial LDA version on this node -2024-07-15 10:48:25,917 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:25,917 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:25,921 - -8.040 per-word bound, 263.1 perplexity estimate based on a held-out corpus of 1 documents with 2065 words -2024-07-15 10:48:25,922 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:25,923 - topic #0 (0.333): 0.014*"’" + 0.008*"well" + 0.005*"needs" + 0.005*"timely" + 0.005*"Torbay" + 0.005*"good" + 0.004*"progress" + 0.004*"effective" + 0.004*"March" + 0.004*"1" -2024-07-15 10:48:25,923 - topic #1 (0.333): 0.015*"’" + 0.008*"well" + 0.006*"Torbay" + 0.005*"good" + 0.005*"effective" + 0.004*"21" + 0.004*"progress" + 0.004*"needs" + 0.004*"team" + 0.004*"timely" -2024-07-15 10:48:25,923 - topic #2 (0.333): 0.019*"’" + 0.010*"well" + 0.009*"Torbay" + 0.007*"needs" + 0.007*"good" + 0.005*"effective" + 0.005*"2022" + 0.005*"team" + 0.004*"21" + 0.004*"agencies" -2024-07-15 10:48:25,923 - topic diff=0.764314, rho=1.000000 -2024-07-15 10:48:25,923 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:25.923955', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:26,935 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:26,935 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:26,936 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:26,936 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:26,936 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:26,936 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:26,936 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:26,937 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:26,937 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:26,937 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:26,937 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:26,937 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:28,281 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:28,283 - built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2448 corpus positions) -2024-07-15 10:48:28,283 - Dictionary lifecycle event {'msg': "built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2448 corpus positions)", 'datetime': '2024-07-15T10:48:28.283659', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:28,284 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:28,284 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:28,285 - using serial LDA version on this node -2024-07-15 10:48:28,285 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:28,285 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:28,289 - -7.918 per-word bound, 241.8 perplexity estimate based on a held-out corpus of 1 documents with 2448 words -2024-07-15 10:48:28,289 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:28,290 - topic #0 (0.333): 0.019*"’" + 0.009*"needs" + 0.008*"plans" + 0.007*"quality" + 0.007*"well" + 0.007*"Trafford" + 0.006*"leaders" + 0.006*"impact" + 0.005*"team" + 0.005*"placed" -2024-07-15 10:48:28,290 - topic #1 (0.333): 0.018*"’" + 0.009*"Trafford" + 0.009*"needs" + 0.007*"well" + 0.007*"practice" + 0.006*"plans" + 0.005*"ensure" + 0.005*"placed" + 0.005*"quality" + 0.004*"leaders" -2024-07-15 10:48:28,290 - topic #2 (0.333): 0.010*"’" + 0.010*"needs" + 0.007*"Trafford" + 0.007*"quality" + 0.006*"well" + 0.005*"plans" + 0.005*"leaders" + 0.005*"impact" + 0.005*"practice" + 0.004*"2" -2024-07-15 10:48:28,290 - topic diff=0.833741, rho=1.000000 -2024-07-15 10:48:28,291 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:28.291083', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:29,597 - Inspection date 2022-11-21 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:29,598 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:29,598 - Inspection date 2022-11-21 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:29,598 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:29,598 - Inspection date 2022-11-21 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:29,598 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:29,598 - Inspection date 2022-11-21 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:29,599 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:29,599 - Inspection date 2022-11-21 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:29,599 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:29,599 - Inspection date 2022-11-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:29,599 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:31,382 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:31,385 - built Dictionary<1162 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2626 corpus positions) -2024-07-15 10:48:31,385 - Dictionary lifecycle event {'msg': 'built Dictionary<1162 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2626 corpus positions)', 'datetime': '2024-07-15T10:48:31.385321', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:31,386 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:31,386 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:31,386 - using serial LDA version on this node -2024-07-15 10:48:31,387 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:31,387 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:31,391 - -8.049 per-word bound, 264.9 perplexity estimate based on a held-out corpus of 1 documents with 2626 words -2024-07-15 10:48:31,391 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:31,392 - topic #0 (0.333): 0.022*"’" + 0.007*"leaders" + 0.007*"needs" + 0.005*"well" + 0.005*"4" + 0.005*"information" + 0.005*"oversight" + 0.005*"Senior" + 0.005*"good" + 0.004*"Walsall" -2024-07-15 10:48:31,392 - topic #1 (0.333): 0.025*"’" + 0.008*"leaders" + 0.007*"needs" + 0.007*"Walsall" + 0.006*"well" + 0.005*"information" + 0.005*"positive" + 0.004*"4" + 0.004*"2021" + 0.004*"records" -2024-07-15 10:48:31,393 - topic #2 (0.333): 0.015*"’" + 0.006*"leaders" + 0.005*"needs" + 0.005*"well" + 0.005*"Walsall" + 0.005*"Senior" + 0.004*"oversight" + 0.004*"good" + 0.004*"4" + 0.004*"carers" -2024-07-15 10:48:31,393 - topic diff=0.816721, rho=1.000000 -2024-07-15 10:48:31,393 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:31.393410', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:32,356 - Inspection date 2021-10-04 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:32,356 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:32,356 - Inspection date 2021-10-04 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:32,356 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:32,356 - Inspection date 2021-10-04 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:32,357 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:32,357 - Inspection date 2021-10-04 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:32,357 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:32,357 - Inspection date 2021-10-04 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:32,357 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:32,357 - Inspection date 2021-10-04 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:32,358 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:33,826 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:33,828 - built Dictionary<1110 unique tokens: ['0161', '0300', '08', '1', '10']...> from 1 documents (total 2187 corpus positions) -2024-07-15 10:48:33,828 - Dictionary lifecycle event {'msg': "built Dictionary<1110 unique tokens: ['0161', '0300', '08', '1', '10']...> from 1 documents (total 2187 corpus positions)", 'datetime': '2024-07-15T10:48:33.828919', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:33,830 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:33,830 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:33,830 - using serial LDA version on this node -2024-07-15 10:48:33,830 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:33,831 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:33,834 - -8.086 per-word bound, 271.7 perplexity estimate based on a held-out corpus of 1 documents with 2187 words -2024-07-15 10:48:33,834 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:33,836 - topic #0 (0.333): 0.013*"’" + 0.006*"practice" + 0.006*"well" + 0.005*"plans" + 0.004*"need" + 0.004*"progress" + 0.004*"Senior" + 0.004*"good" + 0.004*"information" + 0.003*"home" -2024-07-15 10:48:33,836 - topic #1 (0.333): 0.016*"’" + 0.007*"practice" + 0.007*"well" + 0.005*"number" + 0.005*"plans" + 0.004*"home" + 0.004*"Senior" + 0.004*"carers" + 0.004*"information" + 0.004*"receive" -2024-07-15 10:48:33,836 - topic #2 (0.333): 0.013*"’" + 0.007*"well" + 0.005*"practice" + 0.004*"progress" + 0.004*"number" + 0.004*"Senior" + 0.004*"good" + 0.004*"small" + 0.004*"provided" + 0.004*"needs" -2024-07-15 10:48:33,836 - topic diff=0.718968, rho=1.000000 -2024-07-15 10:48:33,836 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:33.836802', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:34,861 - Inspection date 2019-07-08 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:34,862 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:34,862 - Inspection date 2019-07-08 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:34,862 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:34,862 - Inspection date 2019-07-08 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:34,862 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:34,862 - Inspection date 2019-07-08 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:34,862 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:34,863 - Inspection date 2019-07-08 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:34,863 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:34,863 - Inspection date 2019-07-08 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:34,863 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:36,393 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:36,397 - built Dictionary<1040 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2113 corpus positions) -2024-07-15 10:48:36,397 - Dictionary lifecycle event {'msg': "built Dictionary<1040 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2113 corpus positions)", 'datetime': '2024-07-15T10:48:36.397629', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:36,399 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:36,399 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:36,399 - using serial LDA version on this node -2024-07-15 10:48:36,400 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:36,400 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:36,406 - -8.003 per-word bound, 256.5 perplexity estimate based on a held-out corpus of 1 documents with 2113 words -2024-07-15 10:48:36,407 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:36,409 - topic #0 (0.333): 0.014*"’" + 0.008*"needs" + 0.007*"well" + 0.007*"Warwickshire" + 0.006*"plans" + 0.005*"good" + 0.005*"carers" + 0.005*"practice" + 0.005*"information" + 0.004*"supported" -2024-07-15 10:48:36,409 - topic #1 (0.333): 0.012*"’" + 0.007*"well" + 0.007*"plans" + 0.006*"needs" + 0.005*"progress" + 0.005*"effective" + 0.005*"Warwickshire" + 0.005*"practice" + 0.005*"3" + 0.005*"quality" -2024-07-15 10:48:36,409 - topic #2 (0.333): 0.007*"’" + 0.005*"plans" + 0.005*"Warwickshire" + 0.004*"well" + 0.004*"good" + 0.004*"needs" + 0.004*"clear" + 0.004*"practice" + 0.004*"3" + 0.004*"ensure" -2024-07-15 10:48:36,409 - topic diff=0.768686, rho=1.000000 -2024-07-15 10:48:36,410 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:36.410138', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:37,313 - Inspection date 2021-11-22 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:37,314 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:37,314 - Inspection date 2021-11-22 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:37,314 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:37,314 - Inspection date 2021-11-22 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:37,314 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:37,314 - Inspection date 2021-11-22 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:37,314 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:37,315 - Inspection date 2021-11-22 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:37,315 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:37,315 - Inspection date 2021-11-22 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:37,315 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:38,339 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:38,342 - built Dictionary<1115 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2146 corpus positions) -2024-07-15 10:48:38,342 - Dictionary lifecycle event {'msg': "built Dictionary<1115 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2146 corpus positions)", 'datetime': '2024-07-15T10:48:38.342296', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:38,343 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:38,343 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:38,343 - using serial LDA version on this node -2024-07-15 10:48:38,344 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:38,344 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:38,348 - -8.110 per-word bound, 276.2 perplexity estimate based on a held-out corpus of 1 documents with 2146 words -2024-07-15 10:48:38,348 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:38,349 - topic #0 (0.333): 0.015*"’" + 0.008*"Berkshire" + 0.007*"West" + 0.006*"well" + 0.004*"plans" + 0.004*"needs" + 0.004*"need" + 0.004*"2022" + 0.004*"early" + 0.004*"working" -2024-07-15 10:48:38,349 - topic #1 (0.333): 0.016*"’" + 0.006*"West" + 0.005*"well" + 0.005*"need" + 0.005*"Berkshire" + 0.004*"practice" + 0.004*"18" + 0.004*"working" + 0.004*"14" + 0.004*"strong" -2024-07-15 10:48:38,349 - topic #2 (0.333): 0.012*"’" + 0.006*"well" + 0.006*"Berkshire" + 0.006*"West" + 0.005*"needs" + 0.004*"plans" + 0.004*"14" + 0.004*"early" + 0.004*"agency" + 0.004*"March" -2024-07-15 10:48:38,349 - topic diff=0.712237, rho=1.000000 -2024-07-15 10:48:38,350 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:38.350133', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:39,369 - Inspection date 2022-03-14 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:39,370 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:39,370 - Inspection date 2022-03-14 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:39,370 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:39,370 - Inspection date 2022-03-14 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:39,371 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:39,371 - Inspection date 2022-03-14 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:39,371 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:39,372 - Inspection date 2022-03-14 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:39,372 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:39,372 - Inspection date 2022-03-14 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:39,372 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:40,650 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:40,652 - built Dictionary<1087 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2224 corpus positions) -2024-07-15 10:48:40,652 - Dictionary lifecycle event {'msg': "built Dictionary<1087 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2224 corpus positions)", 'datetime': '2024-07-15T10:48:40.652392', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:40,653 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:40,653 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:40,653 - using serial LDA version on this node -2024-07-15 10:48:40,654 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:40,654 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:40,657 - -8.041 per-word bound, 263.3 perplexity estimate based on a held-out corpus of 1 documents with 2224 words -2024-07-15 10:48:40,658 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:40,659 - topic #0 (0.333): 0.013*"’" + 0.007*"Northamptonshire" + 0.005*"well" + 0.005*"3" + 0.005*"West" + 0.005*"plans" + 0.004*"needs" + 0.004*"quality" + 0.004*"experiences" + 0.004*"2022" -2024-07-15 10:48:40,659 - topic #1 (0.333): 0.016*"’" + 0.008*"quality" + 0.008*"Northamptonshire" + 0.007*"West" + 0.006*"well" + 0.006*"practice" + 0.005*"impact" + 0.004*"NCT" + 0.004*"14" + 0.004*"needs" -2024-07-15 10:48:40,659 - topic #2 (0.333): 0.020*"’" + 0.009*"Northamptonshire" + 0.007*"quality" + 0.007*"West" + 0.006*"well" + 0.006*"practice" + 0.006*"needs" + 0.005*"NCT" + 0.005*"impact" + 0.005*"need" -2024-07-15 10:48:40,660 - topic diff=0.759948, rho=1.000000 -2024-07-15 10:48:40,660 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:40.660179', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:42,100 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:42,100 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:42,101 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:42,101 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:42,101 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:42,101 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:42,102 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:42,102 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:42,102 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:42,102 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:42,103 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:42,103 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:43,432 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:43,434 - built Dictionary<1233 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions) -2024-07-15 10:48:43,435 - Dictionary lifecycle event {'msg': "built Dictionary<1233 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)", 'datetime': '2024-07-15T10:48:43.434980', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:43,436 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:43,436 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:43,436 - using serial LDA version on this node -2024-07-15 10:48:43,436 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:43,437 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:43,441 - -8.126 per-word bound, 279.3 perplexity estimate based on a held-out corpus of 1 documents with 2720 words -2024-07-15 10:48:43,441 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:43,442 - topic #0 (0.333): 0.014*"’" + 0.005*"well" + 0.005*"plans" + 0.005*"needs" + 0.005*"number" + 0.004*"West" + 0.004*"education" + 0.004*"good" + 0.004*"health" + 0.004*"13" -2024-07-15 10:48:43,442 - topic #1 (0.333): 0.007*"’" + 0.005*"needs" + 0.005*"well" + 0.004*"Sussex" + 0.004*"plans" + 0.004*"West" + 0.003*"health" + 0.003*"24" + 0.003*"practice" + 0.003*"education" -2024-07-15 10:48:43,442 - topic #2 (0.333): 0.016*"’" + 0.007*"plans" + 0.007*"well" + 0.006*"needs" + 0.006*"Sussex" + 0.006*"West" + 0.006*"13" + 0.005*"quality" + 0.005*"supported" + 0.005*"practice" -2024-07-15 10:48:43,443 - topic diff=0.832550, rho=1.000000 -2024-07-15 10:48:43,443 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:43.443202', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:44,308 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:44,308 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:44,309 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:44,309 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:44,309 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:44,309 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:44,310 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:44,310 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:44,310 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:44,310 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:44,311 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:44,311 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:45,823 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:45,825 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2451 corpus positions) -2024-07-15 10:48:45,825 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2451 corpus positions)", 'datetime': '2024-07-15T10:48:45.825469', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:45,826 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:45,826 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:45,826 - using serial LDA version on this node -2024-07-15 10:48:45,827 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:45,827 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:45,831 - -7.969 per-word bound, 250.6 perplexity estimate based on a held-out corpus of 1 documents with 2451 words -2024-07-15 10:48:45,831 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:45,832 - topic #0 (0.333): 0.014*"’" + 0.007*"Furness" + 0.006*"plans" + 0.006*"appropriate" + 0.006*"Westmorland" + 0.006*"need" + 0.005*"needs" + 0.005*"protection" + 0.005*"3" + 0.005*"quality" -2024-07-15 10:48:45,832 - topic #1 (0.333): 0.016*"’" + 0.009*"plans" + 0.007*"needs" + 0.007*"Westmorland" + 0.006*"need" + 0.006*"appropriate" + 0.005*"Furness" + 0.005*"quality" + 0.004*"well" + 0.004*"leaders" -2024-07-15 10:48:45,832 - topic #2 (0.333): 0.009*"’" + 0.007*"Furness" + 0.007*"needs" + 0.007*"plans" + 0.006*"Westmorland" + 0.005*"appropriate" + 0.005*"April" + 0.005*"protection" + 0.005*"need" + 0.005*"progress" -2024-07-15 10:48:45,832 - topic diff=0.798428, rho=1.000000 -2024-07-15 10:48:45,833 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:45.833034', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:46,845 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:46,846 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:46,846 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:46,846 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:46,846 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:46,846 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:46,846 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:46,847 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:46,847 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:46,847 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:46,847 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:46,847 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:48,524 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:48,526 - built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2416 corpus positions) -2024-07-15 10:48:48,526 - Dictionary lifecycle event {'msg': "built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2416 corpus positions)", 'datetime': '2024-07-15T10:48:48.526840', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:48,527 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:48,528 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:48,528 - using serial LDA version on this node -2024-07-15 10:48:48,528 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:48,528 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:48,532 - -7.963 per-word bound, 249.5 perplexity estimate based on a held-out corpus of 1 documents with 2416 words -2024-07-15 10:48:48,532 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:48,533 - topic #0 (0.333): 0.010*"’" + 0.006*"plans" + 0.006*"Wigan" + 0.006*"May" + 0.006*"practice" + 0.005*"quality" + 0.005*"needs" + 0.004*"identified" + 0.004*"appropriate" + 0.004*"leaders" -2024-07-15 10:48:48,534 - topic #1 (0.333): 0.015*"’" + 0.008*"practice" + 0.008*"May" + 0.006*"quality" + 0.006*"plans" + 0.006*"9" + 0.006*"needs" + 0.006*"appropriate" + 0.005*"Wigan" + 0.005*"timely" -2024-07-15 10:48:48,534 - topic #2 (0.333): 0.012*"’" + 0.008*"May" + 0.007*"plans" + 0.006*"needs" + 0.006*"Wigan" + 0.005*"appropriate" + 0.005*"leaders" + 0.005*"quality" + 0.005*"practice" + 0.005*"increased" -2024-07-15 10:48:48,534 - topic diff=0.794111, rho=1.000000 -2024-07-15 10:48:48,534 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:48.534442', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:49,465 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:49,466 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:49,466 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:49,466 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:49,466 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:49,466 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:49,467 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:49,467 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:49,467 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:49,467 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:49,467 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:49,467 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:51,084 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:51,086 - built Dictionary<1090 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2600 corpus positions) -2024-07-15 10:48:51,086 - Dictionary lifecycle event {'msg': "built Dictionary<1090 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2600 corpus positions)", 'datetime': '2024-07-15T10:48:51.086763', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:51,087 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:51,087 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:51,088 - using serial LDA version on this node -2024-07-15 10:48:51,088 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:51,088 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:51,092 - -7.954 per-word bound, 248.0 perplexity estimate based on a held-out corpus of 1 documents with 2600 words -2024-07-15 10:48:51,092 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:51,093 - topic #0 (0.333): 0.012*"’" + 0.010*"well" + 0.006*"need" + 0.006*"progress" + 0.006*"needs" + 0.005*"plans" + 0.005*"risk" + 0.005*"Wiltshire" + 0.005*"including" + 0.005*"supported" -2024-07-15 10:48:51,093 - topic #1 (0.333): 0.019*"’" + 0.013*"well" + 0.008*"needs" + 0.007*"Wiltshire" + 0.007*"need" + 0.006*"risk" + 0.006*"parents" + 0.006*"progress" + 0.006*"including" + 0.006*"ensure" -2024-07-15 10:48:51,094 - topic #2 (0.333): 0.013*"’" + 0.009*"well" + 0.006*"needs" + 0.006*"need" + 0.006*"parents" + 0.005*"quality" + 0.005*"including" + 0.005*"ensure" + 0.005*"supported" + 0.005*"progress" -2024-07-15 10:48:51,094 - topic diff=0.830868, rho=1.000000 -2024-07-15 10:48:51,094 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:51.094286', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:52,099 - Inspection date 2023-09-25 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:52,100 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:52,100 - Inspection date 2023-09-25 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:52,100 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:52,100 - Inspection date 2023-09-25 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:52,100 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:52,100 - Inspection date 2023-09-25 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:52,100 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:52,101 - Inspection date 2023-09-25 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:52,101 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:52,101 - Inspection date 2023-09-25 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:52,101 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:53,883 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:53,885 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions) -2024-07-15 10:48:53,885 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)", 'datetime': '2024-07-15T10:48:53.885320', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:53,886 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:53,886 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:53,886 - using serial LDA version on this node -2024-07-15 10:48:53,886 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:53,887 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:53,890 - -7.906 per-word bound, 239.9 perplexity estimate based on a held-out corpus of 1 documents with 2233 words -2024-07-15 10:48:53,890 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:53,891 - topic #0 (0.333): 0.012*"needs" + 0.012*"’" + 0.008*"ensure" + 0.006*"plans" + 0.006*"practice" + 0.006*"18" + 0.005*"well" + 0.005*"number" + 0.005*"2023" + 0.005*"response" -2024-07-15 10:48:53,891 - topic #1 (0.333): 0.013*"’" + 0.009*"Wirral" + 0.006*"needs" + 0.006*"plans" + 0.006*"ensure" + 0.005*"practice" + 0.005*"good" + 0.005*"well" + 0.005*"risk" + 0.005*"number" -2024-07-15 10:48:53,892 - topic #2 (0.333): 0.009*"needs" + 0.008*"Wirral" + 0.008*"’" + 0.007*"ensure" + 0.007*"plans" + 0.006*"practice" + 0.006*"response" + 0.006*"29" + 0.005*"appropriate" + 0.005*"number" -2024-07-15 10:48:53,892 - topic diff=0.802121, rho=1.000000 -2024-07-15 10:48:53,892 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:53.892346', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:54,848 - Inspection date 2023-09-18 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:54,848 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:54,848 - Inspection date 2023-09-18 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:54,848 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:54,849 - Inspection date 2023-09-18 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:54,849 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:54,849 - Inspection date 2023-09-18 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:54,849 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:54,849 - Inspection date 2023-09-18 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:54,849 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:54,849 - Inspection date 2023-09-18 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:54,849 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:56,174 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:56,176 - built Dictionary<1096 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2214 corpus positions) -2024-07-15 10:48:56,176 - Dictionary lifecycle event {'msg': "built Dictionary<1096 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2214 corpus positions)", 'datetime': '2024-07-15T10:48:56.176462', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:56,177 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:56,177 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:56,177 - using serial LDA version on this node -2024-07-15 10:48:56,178 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:56,178 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:56,181 - -8.058 per-word bound, 266.4 perplexity estimate based on a held-out corpus of 1 documents with 2214 words -2024-07-15 10:48:56,182 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:56,183 - topic #0 (0.333): 0.008*"’" + 0.005*"plans" + 0.005*"provided" + 0.005*"effective" + 0.004*"progress" + 0.004*"needs" + 0.004*"experiences" + 0.004*"6" + 0.004*"well" + 0.004*"ensure" -2024-07-15 10:48:56,183 - topic #1 (0.333): 0.012*"’" + 0.007*"plans" + 0.007*"needs" + 0.007*"progress" + 0.006*"effective" + 0.006*"protection" + 0.005*"well" + 0.005*"impact" + 0.005*"experiences" + 0.005*"17" -2024-07-15 10:48:56,183 - topic #2 (0.333): 0.015*"’" + 0.007*"plans" + 0.007*"effective" + 0.006*"needs" + 0.006*"well" + 0.005*"progress" + 0.005*"provided" + 0.005*"17" + 0.005*"quality" + 0.004*"parents" -2024-07-15 10:48:56,183 - topic diff=0.761405, rho=1.000000 -2024-07-15 10:48:56,183 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:56.183861', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:57,239 - Inspection date 2023-03-06 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:57,239 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:57,239 - Inspection date 2023-03-06 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:57,240 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:57,240 - Inspection date 2023-03-06 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:57,240 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:57,240 - Inspection date 2023-03-06 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:57,240 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:57,240 - Inspection date 2023-03-06 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:57,240 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:57,241 - Inspection date 2023-03-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:57,241 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:58,726 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:48:58,731 - built Dictionary<1095 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions) -2024-07-15 10:48:58,731 - Dictionary lifecycle event {'msg': "built Dictionary<1095 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)", 'datetime': '2024-07-15T10:48:58.731668', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:58,733 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:48:58,733 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:48:58,734 - using serial LDA version on this node -2024-07-15 10:48:58,734 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:48:58,734 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:48:58,740 - -8.048 per-word bound, 264.7 perplexity estimate based on a held-out corpus of 1 documents with 2233 words -2024-07-15 10:48:58,741 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:48:58,743 - topic #0 (0.333): 0.012*"’" + 0.008*"needs" + 0.005*"plans" + 0.005*"effective" + 0.005*"risk" + 0.005*"Wolverhampton" + 0.005*"risks" + 0.004*"April" + 0.004*"education" + 0.004*"28" -2024-07-15 10:48:58,743 - topic #1 (0.333): 0.008*"’" + 0.006*"effective" + 0.005*"needs" + 0.005*"quality" + 0.005*"Wolverhampton" + 0.004*"supported" + 0.004*"experiences" + 0.004*"risk" + 0.004*"plans" + 0.003*"well" -2024-07-15 10:48:58,743 - topic #2 (0.333): 0.019*"’" + 0.008*"needs" + 0.006*"Wolverhampton" + 0.006*"effective" + 0.006*"risks" + 0.006*"leaders" + 0.006*"receive" + 0.005*"plans" + 0.005*"quality" + 0.005*"education" -2024-07-15 10:48:58,743 - topic diff=0.752295, rho=1.000000 -2024-07-15 10:48:58,744 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:48:58.744044', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:48:59,817 - Inspection date 2022-03-28 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:48:59,817 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:59,817 - Inspection date 2022-03-28 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:48:59,817 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:59,818 - Inspection date 2022-03-28 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:48:59,818 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:59,818 - Inspection date 2022-03-28 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:48:59,818 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:59,818 - Inspection date 2022-03-28 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:48:59,818 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:48:59,819 - Inspection date 2022-03-28 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:48:59,819 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:49:01,460 - adding document #0 to Dictionary<0 unique tokens: []> -2024-07-15 10:49:01,462 - built Dictionary<1041 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2343 corpus positions) -2024-07-15 10:49:01,462 - Dictionary lifecycle event {'msg': "built Dictionary<1041 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2343 corpus positions)", 'datetime': '2024-07-15T10:49:01.462800', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:49:01,463 - using symmetric alpha at 0.3333333333333333 -2024-07-15 10:49:01,463 - using symmetric eta at 0.3333333333333333 -2024-07-15 10:49:01,464 - using serial LDA version on this node -2024-07-15 10:49:01,464 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 -2024-07-15 10:49:01,464 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy -2024-07-15 10:49:01,468 - -7.947 per-word bound, 246.7 perplexity estimate based on a held-out corpus of 1 documents with 2343 words -2024-07-15 10:49:01,468 - PROGRESS: pass 0, at document #1/1 -2024-07-15 10:49:01,469 - topic #0 (0.333): 0.021*"’" + 0.010*"well" + 0.008*"Worcestershire" + 0.007*"needs" + 0.007*"progress" + 0.006*"ensure" + 0.006*"leaders" + 0.006*"plans" + 0.006*"appropriate" + 0.005*"experiences" -2024-07-15 10:49:01,469 - topic #1 (0.333): 0.022*"’" + 0.009*"plans" + 0.009*"needs" + 0.008*"leaders" + 0.007*"progress" + 0.007*"Worcestershire" + 0.007*"well" + 0.006*"ensure" + 0.006*"appropriate" + 0.005*"PAs" -2024-07-15 10:49:01,469 - topic #2 (0.333): 0.011*"’" + 0.008*"well" + 0.008*"plans" + 0.006*"needs" + 0.005*"progress" + 0.005*"leaders" + 0.005*"Worcestershire" + 0.005*"appropriate" + 0.004*"15" + 0.004*"26" -2024-07-15 10:49:01,470 - topic diff=0.811008, rho=1.000000 -2024-07-15 10:49:01,470 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-15T10:49:01.470222', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} -2024-07-15 10:49:02,664 - Inspection date 2023-05-15 / Column 'overall_effectiveness' not found in the DataFrame. -2024-07-15 10:49:02,664 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:49:02,664 - Inspection date 2023-05-15 / Column 'impact_of_leaders' not found in the DataFrame. -2024-07-15 10:49:02,664 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:49:02,665 - Inspection date 2023-05-15 / Column 'help_and_protection' not found in the DataFrame. -2024-07-15 10:49:02,665 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:49:02,665 - Inspection date 2023-05-15 / Column 'in_care' not found in the DataFrame. -2024-07-15 10:49:02,665 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:49:02,665 - Inspection date 2023-05-15 / Column 'care_leavers' not found in the DataFrame. -2024-07-15 10:49:02,665 - Index(['judgement', 'grade'], dtype='object') -2024-07-15 10:49:02,666 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame. -2024-07-15 10:49:02,666 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:01,584 - Inspection date 2019-04-08 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:01,584 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:01,584 - Inspection date 2019-04-08 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:01,584 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:01,584 - Inspection date 2019-04-08 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:01,585 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:01,585 - Inspection date 2019-04-08 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:01,585 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:01,585 - Inspection date 2019-04-08 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:01,585 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:01,585 - Inspection date 2019-04-08 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:01,585 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:03,412 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:03,415 - built Dictionary<1128 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2409 corpus positions) +2024-07-25 12:45:03,415 - Dictionary lifecycle event {'msg': "built Dictionary<1128 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2409 corpus positions)", 'datetime': '2024-07-25T12:45:03.415245', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:03,416 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:03,416 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:03,416 - using serial LDA version on this node +2024-07-25 12:45:03,417 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:03,417 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:03,420 - -8.058 per-word bound, 266.4 perplexity estimate based on a held-out corpus of 1 documents with 2409 words +2024-07-25 12:45:03,421 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:03,422 - topic #0 (0.333): 0.014*"’" + 0.006*"needs" + 0.006*"quality" + 0.006*"Sunderland" + 0.006*"well" + 0.005*"protection" + 0.005*"parents" + 0.004*"experienced" + 0.004*"robust" + 0.004*"TfC" +2024-07-25 12:45:03,422 - topic #1 (0.333): 0.017*"’" + 0.007*"well" + 0.007*"quality" + 0.006*"needs" + 0.005*"parents" + 0.005*"training" + 0.005*"practice" + 0.005*"experienced" + 0.005*"Sunderland" + 0.004*"council" +2024-07-25 12:45:03,422 - topic #2 (0.333): 0.017*"’" + 0.008*"well" + 0.007*"quality" + 0.007*"needs" + 0.006*"Sunderland" + 0.005*"experienced" + 0.005*"good" + 0.005*"practice" + 0.005*"council" + 0.004*"robust" +2024-07-25 12:45:03,423 - topic diff=0.780946, rho=1.000000 +2024-07-25 12:45:03,423 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:03.423166', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:04,614 - Inspection date 2021-06-28 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:04,614 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:04,615 - Inspection date 2021-06-28 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:04,615 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:04,615 - Inspection date 2021-06-28 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:04,615 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:04,615 - Inspection date 2021-06-28 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:04,616 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:04,616 - Inspection date 2021-06-28 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:04,616 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:04,616 - Inspection date 2021-06-28 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:04,616 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:06,167 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:06,170 - built Dictionary<1016 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2111 corpus positions) +2024-07-25 12:45:06,171 - Dictionary lifecycle event {'msg': "built Dictionary<1016 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2111 corpus positions)", 'datetime': '2024-07-25T12:45:06.170990', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:06,172 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:06,172 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:06,173 - using serial LDA version on this node +2024-07-25 12:45:06,173 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:06,173 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:06,179 - -7.966 per-word bound, 250.0 perplexity estimate based on a held-out corpus of 1 documents with 2111 words +2024-07-25 12:45:06,179 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:06,181 - topic #0 (0.333): 0.015*"’" + 0.011*"well" + 0.010*"needs" + 0.007*"practice" + 0.006*"17" + 0.006*"progress" + 0.005*"quality" + 0.005*"However" + 0.005*"carers" + 0.005*"receive" +2024-07-25 12:45:06,182 - topic #1 (0.333): 0.014*"’" + 0.010*"needs" + 0.008*"progress" + 0.008*"well" + 0.008*"practice" + 0.006*"plans" + 0.006*"effective" + 0.005*"good" + 0.005*"However" + 0.005*"carers" +2024-07-25 12:45:06,182 - topic #2 (0.333): 0.010*"’" + 0.008*"needs" + 0.008*"well" + 0.006*"practice" + 0.006*"plans" + 0.005*"progress" + 0.005*"good" + 0.004*"carers" + 0.004*"supported" + 0.004*"Surrey" +2024-07-25 12:45:06,182 - topic diff=0.758750, rho=1.000000 +2024-07-25 12:45:06,182 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:06.182943', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:07,671 - Inspection date 2022-01-17 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:07,672 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:07,672 - Inspection date 2022-01-17 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:07,672 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:07,672 - Inspection date 2022-01-17 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:07,673 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:07,673 - Inspection date 2022-01-17 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:07,673 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:07,673 - Inspection date 2022-01-17 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:07,673 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:07,674 - Inspection date 2022-01-17 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:07,674 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:09,329 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:09,331 - built Dictionary<951 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2229 corpus positions) +2024-07-25 12:45:09,331 - Dictionary lifecycle event {'msg': "built Dictionary<951 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2229 corpus positions)", 'datetime': '2024-07-25T12:45:09.331405', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:09,332 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:09,332 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:09,332 - using serial LDA version on this node +2024-07-25 12:45:09,333 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:09,333 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:09,336 - -7.823 per-word bound, 226.5 perplexity estimate based on a held-out corpus of 1 documents with 2229 words +2024-07-25 12:45:09,336 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:09,337 - topic #0 (0.333): 0.019*"’" + 0.010*"needs" + 0.009*"Swindon" + 0.009*"need" + 0.008*"plans" + 0.006*"well" + 0.006*"health" + 0.006*"always" + 0.005*"effective" + 0.005*"Council" +2024-07-25 12:45:09,338 - topic #1 (0.333): 0.025*"’" + 0.017*"needs" + 0.011*"Swindon" + 0.009*"well" + 0.008*"need" + 0.007*"always" + 0.006*"impact" + 0.006*"many" + 0.005*"Council" + 0.005*"plans" +2024-07-25 12:45:09,338 - topic #2 (0.333): 0.019*"’" + 0.009*"needs" + 0.009*"need" + 0.007*"well" + 0.006*"plans" + 0.005*"Swindon" + 0.005*"effective" + 0.005*"always" + 0.005*"Borough" + 0.004*"health" +2024-07-25 12:45:09,338 - topic diff=0.833238, rho=1.000000 +2024-07-25 12:45:09,338 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:09.338458', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:10,399 - Inspection date 2023-07-17 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:10,400 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:10,400 - Inspection date 2023-07-17 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:10,400 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:10,400 - Inspection date 2023-07-17 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:10,400 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:10,401 - Inspection date 2023-07-17 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:10,401 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:10,401 - Inspection date 2023-07-17 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:10,401 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:10,401 - Inspection date 2023-07-17 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:10,401 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:11,885 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:11,887 - built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2491 corpus positions) +2024-07-25 12:45:11,887 - Dictionary lifecycle event {'msg': "built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2491 corpus positions)", 'datetime': '2024-07-25T12:45:11.887689', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:11,888 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:11,888 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:11,889 - using serial LDA version on this node +2024-07-25 12:45:11,889 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:11,889 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:11,893 - -7.943 per-word bound, 246.2 perplexity estimate based on a held-out corpus of 1 documents with 2491 words +2024-07-25 12:45:11,893 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:11,894 - topic #0 (0.333): 0.011*"’" + 0.006*"needs" + 0.006*"risk" + 0.005*"experienced" + 0.005*"impact" + 0.005*"leaders" + 0.005*"quality" + 0.004*"plans" + 0.004*"practice" + 0.004*"2023" +2024-07-25 12:45:11,894 - topic #1 (0.333): 0.019*"’" + 0.009*"needs" + 0.007*"quality" + 0.006*"impact" + 0.006*"response" + 0.006*"experienced" + 0.006*"risk" + 0.005*"15" + 0.005*"practice" + 0.005*"Tameside" +2024-07-25 12:45:11,895 - topic #2 (0.333): 0.017*"’" + 0.010*"needs" + 0.006*"risk" + 0.006*"impact" + 0.006*"4" + 0.005*"progress" + 0.005*"experiences" + 0.005*"practice" + 0.005*"effective" + 0.005*"2023" +2024-07-25 12:45:11,895 - topic diff=0.825456, rho=1.000000 +2024-07-25 12:45:11,895 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:11.895437', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:13,374 - Inspection date 2023-12-04 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:13,375 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:13,375 - Inspection date 2023-12-04 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:13,375 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:13,376 - Inspection date 2023-12-04 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:13,376 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:13,376 - Inspection date 2023-12-04 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:13,376 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:13,376 - Inspection date 2023-12-04 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:13,377 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:13,377 - Inspection date 2023-12-04 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:13,377 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:14,728 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:14,730 - built Dictionary<1077 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2452 corpus positions) +2024-07-25 12:45:14,730 - Dictionary lifecycle event {'msg': "built Dictionary<1077 unique tokens: ['00', '0161', '03', '0300', '1']...> from 1 documents (total 2452 corpus positions)", 'datetime': '2024-07-25T12:45:14.730699', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:14,732 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:14,732 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:14,732 - using serial LDA version on this node +2024-07-25 12:45:14,732 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:14,732 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:14,737 - -7.965 per-word bound, 249.9 perplexity estimate based on a held-out corpus of 1 documents with 2452 words +2024-07-25 12:45:14,737 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:14,739 - topic #0 (0.333): 0.018*"’" + 0.010*"needs" + 0.006*"benefit" + 0.006*"Wrekin" + 0.005*"Family" + 0.005*"Telford" + 0.005*"effective" + 0.005*"well" + 0.005*"understand" + 0.004*"29" +2024-07-25 12:45:14,739 - topic #1 (0.333): 0.022*"’" + 0.010*"needs" + 0.007*"Telford" + 0.007*"well" + 0.006*"Wrekin" + 0.005*"Family" + 0.005*"benefit" + 0.005*"plans" + 0.005*"effective" + 0.005*"ensure" +2024-07-25 12:45:14,739 - topic #2 (0.333): 0.023*"’" + 0.012*"needs" + 0.010*"Wrekin" + 0.010*"Telford" + 0.006*"benefit" + 0.006*"plans" + 0.005*"well" + 0.005*"effective" + 0.005*"3" + 0.005*"Family" +2024-07-25 12:45:14,739 - topic diff=0.817826, rho=1.000000 +2024-07-25 12:45:14,740 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:14.740007', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:15,808 - Inspection date 2024-04-29 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:15,808 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:15,808 - Inspection date 2024-04-29 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:15,808 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:15,808 - Inspection date 2024-04-29 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:15,808 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:15,808 - Inspection date 2024-04-29 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:15,809 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:15,809 - Inspection date 2024-04-29 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:15,809 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:15,809 - Inspection date 2024-04-29 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:15,809 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:17,400 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:17,403 - built Dictionary<1138 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2160 corpus positions) +2024-07-25 12:45:17,403 - Dictionary lifecycle event {'msg': "built Dictionary<1138 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2160 corpus positions)", 'datetime': '2024-07-25T12:45:17.403463', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:17,404 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:17,404 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:17,404 - using serial LDA version on this node +2024-07-25 12:45:17,405 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:17,405 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:17,409 - -8.137 per-word bound, 281.4 perplexity estimate based on a held-out corpus of 1 documents with 2160 words +2024-07-25 12:45:17,409 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:17,410 - topic #0 (0.333): 0.010*"’" + 0.007*"well" + 0.004*"carers" + 0.004*"need" + 0.004*"practice" + 0.003*"needs" + 0.003*"leaders" + 0.003*"ensure" + 0.003*"protection" + 0.003*"parents" +2024-07-25 12:45:17,410 - topic #1 (0.333): 0.011*"’" + 0.006*"well" + 0.005*"carers" + 0.005*"need" + 0.004*"quality" + 0.004*"ensure" + 0.004*"effective" + 0.003*"needs" + 0.003*"protection" + 0.003*"good" +2024-07-25 12:45:17,411 - topic #2 (0.333): 0.016*"’" + 0.010*"well" + 0.007*"carers" + 0.006*"need" + 0.005*"needs" + 0.005*"practice" + 0.005*"Thurrock" + 0.005*"ensure" + 0.004*"leaders" + 0.004*"effective" +2024-07-25 12:45:17,411 - topic diff=0.741642, rho=1.000000 +2024-07-25 12:45:17,411 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:17.411293', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:19,636 - Inspection date 2019-11-11 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:19,637 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:19,637 - Inspection date 2019-11-11 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:19,637 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:19,637 - Inspection date 2019-11-11 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:19,637 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:19,638 - Inspection date 2019-11-11 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:19,638 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:19,638 - Inspection date 2019-11-11 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:19,638 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:19,638 - Inspection date 2019-11-11 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:19,639 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:21,054 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:21,056 - built Dictionary<1054 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2065 corpus positions) +2024-07-25 12:45:21,057 - Dictionary lifecycle event {'msg': "built Dictionary<1054 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2065 corpus positions)", 'datetime': '2024-07-25T12:45:21.057088', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:21,058 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:21,058 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:21,058 - using serial LDA version on this node +2024-07-25 12:45:21,058 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:21,059 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:21,062 - -8.040 per-word bound, 263.1 perplexity estimate based on a held-out corpus of 1 documents with 2065 words +2024-07-25 12:45:21,062 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:21,064 - topic #0 (0.333): 0.019*"’" + 0.010*"well" + 0.008*"Torbay" + 0.006*"needs" + 0.006*"good" + 0.006*"timely" + 0.005*"effective" + 0.005*"progress" + 0.005*"2022" + 0.005*"21" +2024-07-25 12:45:21,064 - topic #1 (0.333): 0.015*"’" + 0.008*"Torbay" + 0.007*"well" + 0.005*"effective" + 0.005*"needs" + 0.005*"good" + 0.005*"progress" + 0.004*"plans" + 0.004*"team" + 0.004*"21" +2024-07-25 12:45:21,064 - topic #2 (0.333): 0.015*"’" + 0.010*"well" + 0.006*"good" + 0.006*"Torbay" + 0.006*"needs" + 0.004*"effective" + 0.004*"1" + 0.004*"ensure" + 0.004*"team" + 0.004*"March" +2024-07-25 12:45:21,064 - topic diff=0.748704, rho=1.000000 +2024-07-25 12:45:21,064 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:21.064814', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:22,040 - Inspection date 2022-03-21 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:22,041 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:22,041 - Inspection date 2022-03-21 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:22,041 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:22,041 - Inspection date 2022-03-21 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:22,041 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:22,042 - Inspection date 2022-03-21 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:22,042 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:22,042 - Inspection date 2022-03-21 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:22,042 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:22,042 - Inspection date 2022-03-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:22,042 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:23,641 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:23,643 - built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2448 corpus positions) +2024-07-25 12:45:23,643 - Dictionary lifecycle event {'msg': "built Dictionary<1038 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2448 corpus positions)", 'datetime': '2024-07-25T12:45:23.643460', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:23,644 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:23,644 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:23,644 - using serial LDA version on this node +2024-07-25 12:45:23,645 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:23,645 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:23,648 - -7.913 per-word bound, 241.1 perplexity estimate based on a held-out corpus of 1 documents with 2448 words +2024-07-25 12:45:23,649 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:23,650 - topic #0 (0.333): 0.017*"’" + 0.009*"needs" + 0.008*"well" + 0.007*"Trafford" + 0.007*"plans" + 0.005*"practice" + 0.005*"placed" + 0.005*"impact" + 0.005*"quality" + 0.005*"team" +2024-07-25 12:45:23,650 - topic #1 (0.333): 0.013*"’" + 0.010*"needs" + 0.008*"Trafford" + 0.008*"plans" + 0.008*"quality" + 0.006*"practice" + 0.006*"well" + 0.005*"team" + 0.005*"leaders" + 0.005*"impact" +2024-07-25 12:45:23,650 - topic #2 (0.333): 0.019*"’" + 0.009*"needs" + 0.008*"Trafford" + 0.008*"well" + 0.007*"quality" + 0.007*"leaders" + 0.006*"plans" + 0.005*"placed" + 0.005*"ensure" + 0.005*"practice" +2024-07-25 12:45:23,650 - topic diff=0.823372, rho=1.000000 +2024-07-25 12:45:23,650 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:23.650897', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:25,082 - Inspection date 2022-11-21 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:25,082 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:25,082 - Inspection date 2022-11-21 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:25,083 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:25,083 - Inspection date 2022-11-21 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:25,083 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:25,084 - Inspection date 2022-11-21 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:25,084 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:25,084 - Inspection date 2022-11-21 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:25,084 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:25,084 - Inspection date 2022-11-21 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:25,085 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:27,079 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:27,081 - built Dictionary<1162 unique tokens: ["'s", '0161', '0300', '1', '10']...> from 1 documents (total 2626 corpus positions) +2024-07-25 12:45:27,081 - Dictionary lifecycle event {'msg': 'built Dictionary<1162 unique tokens: ["\'s", \'0161\', \'0300\', \'1\', \'10\']...> from 1 documents (total 2626 corpus positions)', 'datetime': '2024-07-25T12:45:27.081784', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:27,082 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:27,083 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:27,083 - using serial LDA version on this node +2024-07-25 12:45:27,083 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:27,083 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:27,087 - -8.050 per-word bound, 265.0 perplexity estimate based on a held-out corpus of 1 documents with 2626 words +2024-07-25 12:45:27,087 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:27,089 - topic #0 (0.333): 0.020*"’" + 0.007*"leaders" + 0.007*"needs" + 0.006*"Walsall" + 0.005*"4" + 0.004*"oversight" + 0.004*"Senior" + 0.004*"good" + 0.004*"need" + 0.004*"2021" +2024-07-25 12:45:27,089 - topic #1 (0.333): 0.013*"’" + 0.007*"leaders" + 0.006*"well" + 0.006*"needs" + 0.005*"4" + 0.005*"15" + 0.004*"information" + 0.004*"Walsall" + 0.004*"risk" + 0.004*"records" +2024-07-25 12:45:27,089 - topic #2 (0.333): 0.028*"’" + 0.007*"leaders" + 0.006*"well" + 0.006*"needs" + 0.005*"information" + 0.005*"Walsall" + 0.005*"Senior" + 0.005*"good" + 0.005*"oversight" + 0.004*"plans" +2024-07-25 12:45:27,089 - topic diff=0.812971, rho=1.000000 +2024-07-25 12:45:27,090 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:27.090053', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:28,090 - Inspection date 2021-10-04 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:28,091 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:28,091 - Inspection date 2021-10-04 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:28,092 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:28,092 - Inspection date 2021-10-04 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:28,092 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:28,092 - Inspection date 2021-10-04 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:28,093 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:28,093 - Inspection date 2021-10-04 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:28,093 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:28,094 - Inspection date 2021-10-04 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:28,094 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:29,394 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:29,396 - built Dictionary<1110 unique tokens: ['0161', '0300', '08', '1', '10']...> from 1 documents (total 2187 corpus positions) +2024-07-25 12:45:29,397 - Dictionary lifecycle event {'msg': "built Dictionary<1110 unique tokens: ['0161', '0300', '08', '1', '10']...> from 1 documents (total 2187 corpus positions)", 'datetime': '2024-07-25T12:45:29.397138', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:29,398 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:29,398 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:29,398 - using serial LDA version on this node +2024-07-25 12:45:29,398 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:29,399 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:29,402 - -8.088 per-word bound, 272.2 perplexity estimate based on a held-out corpus of 1 documents with 2187 words +2024-07-25 12:45:29,402 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:29,404 - topic #0 (0.333): 0.010*"’" + 0.006*"well" + 0.005*"practice" + 0.005*"number" + 0.004*"provided" + 0.004*"need" + 0.004*"Senior" + 0.004*"plans" + 0.004*"progress" + 0.004*"improve" +2024-07-25 12:45:29,404 - topic #1 (0.333): 0.017*"’" + 0.008*"practice" + 0.006*"well" + 0.005*"Senior" + 0.005*"home" + 0.005*"progress" + 0.004*"good" + 0.004*"plans" + 0.004*"information" + 0.004*"number" +2024-07-25 12:45:29,404 - topic #2 (0.333): 0.014*"’" + 0.007*"well" + 0.006*"practice" + 0.005*"plans" + 0.004*"number" + 0.004*"carers" + 0.004*"needs" + 0.004*"small" + 0.004*"protection" + 0.004*"high" +2024-07-25 12:45:29,404 - topic diff=0.724572, rho=1.000000 +2024-07-25 12:45:29,404 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:29.404895', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:30,373 - Inspection date 2019-07-08 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:30,373 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:30,374 - Inspection date 2019-07-08 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:30,374 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:30,374 - Inspection date 2019-07-08 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:30,374 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:30,375 - Inspection date 2019-07-08 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:30,375 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:30,375 - Inspection date 2019-07-08 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:30,376 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:30,376 - Inspection date 2019-07-08 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:30,376 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:31,911 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:31,913 - built Dictionary<1040 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2113 corpus positions) +2024-07-25 12:45:31,913 - Dictionary lifecycle event {'msg': "built Dictionary<1040 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2113 corpus positions)", 'datetime': '2024-07-25T12:45:31.913895', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:31,914 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:31,915 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:31,915 - using serial LDA version on this node +2024-07-25 12:45:31,915 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:31,915 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:31,919 - -8.005 per-word bound, 256.9 perplexity estimate based on a held-out corpus of 1 documents with 2113 words +2024-07-25 12:45:31,919 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:31,920 - topic #0 (0.333): 0.013*"’" + 0.008*"needs" + 0.007*"plans" + 0.006*"Warwickshire" + 0.005*"well" + 0.005*"3" + 0.005*"good" + 0.005*"practice" + 0.005*"clear" + 0.005*"effective" +2024-07-25 12:45:31,920 - topic #1 (0.333): 0.010*"’" + 0.007*"well" + 0.005*"practice" + 0.005*"plans" + 0.004*"needs" + 0.004*"Warwickshire" + 0.004*"good" + 0.004*"quality" + 0.004*"supported" + 0.004*"carers" +2024-07-25 12:45:31,921 - topic #2 (0.333): 0.012*"’" + 0.007*"well" + 0.007*"Warwickshire" + 0.006*"plans" + 0.006*"needs" + 0.005*"22" + 0.005*"practice" + 0.005*"carers" + 0.005*"progress" + 0.005*"Senior" +2024-07-25 12:45:31,921 - topic diff=0.760788, rho=1.000000 +2024-07-25 12:45:31,921 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:31.921297', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:32,898 - Inspection date 2021-11-22 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:32,898 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:32,898 - Inspection date 2021-11-22 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:32,898 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:32,899 - Inspection date 2021-11-22 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:32,899 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:32,899 - Inspection date 2021-11-22 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:32,899 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:32,899 - Inspection date 2021-11-22 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:32,899 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:32,900 - Inspection date 2021-11-22 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:32,900 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:33,923 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:33,925 - built Dictionary<1115 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2146 corpus positions) +2024-07-25 12:45:33,925 - Dictionary lifecycle event {'msg': "built Dictionary<1115 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2146 corpus positions)", 'datetime': '2024-07-25T12:45:33.925355', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:33,926 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:33,926 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:33,926 - using serial LDA version on this node +2024-07-25 12:45:33,927 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:33,927 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:33,931 - -8.108 per-word bound, 276.0 perplexity estimate based on a held-out corpus of 1 documents with 2146 words +2024-07-25 12:45:33,931 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:33,932 - topic #0 (0.333): 0.017*"’" + 0.007*"West" + 0.006*"Berkshire" + 0.006*"well" + 0.005*"plans" + 0.004*"needs" + 0.004*"need" + 0.004*"18" + 0.004*"agency" + 0.004*"early" +2024-07-25 12:45:33,932 - topic #1 (0.333): 0.012*"’" + 0.005*"West" + 0.005*"Berkshire" + 0.005*"well" + 0.004*"14" + 0.004*"agency" + 0.004*"working" + 0.004*"March" + 0.004*"18" + 0.004*"needs" +2024-07-25 12:45:33,932 - topic #2 (0.333): 0.013*"’" + 0.007*"West" + 0.007*"Berkshire" + 0.006*"well" + 0.004*"need" + 0.004*"practice" + 0.004*"plans" + 0.004*"needs" + 0.004*"early" + 0.004*"progress" +2024-07-25 12:45:33,932 - topic diff=0.712619, rho=1.000000 +2024-07-25 12:45:33,933 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:33.933066', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:34,944 - Inspection date 2022-03-14 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:34,945 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:34,945 - Inspection date 2022-03-14 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:34,945 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:34,946 - Inspection date 2022-03-14 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:34,946 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:34,946 - Inspection date 2022-03-14 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:34,946 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:34,947 - Inspection date 2022-03-14 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:34,947 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:34,947 - Inspection date 2022-03-14 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:34,947 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:36,640 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:36,644 - built Dictionary<1087 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2224 corpus positions) +2024-07-25 12:45:36,645 - Dictionary lifecycle event {'msg': "built Dictionary<1087 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2224 corpus positions)", 'datetime': '2024-07-25T12:45:36.645018', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:36,646 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:36,647 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:36,647 - using serial LDA version on this node +2024-07-25 12:45:36,648 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:36,648 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:36,654 - -8.043 per-word bound, 263.8 perplexity estimate based on a held-out corpus of 1 documents with 2224 words +2024-07-25 12:45:36,655 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:36,657 - topic #0 (0.333): 0.017*"’" + 0.008*"Northamptonshire" + 0.008*"West" + 0.005*"well" + 0.005*"NCT" + 0.005*"quality" + 0.005*"3" + 0.004*"needs" + 0.004*"impact" + 0.004*"practice" +2024-07-25 12:45:36,657 - topic #1 (0.333): 0.014*"’" + 0.007*"Northamptonshire" + 0.006*"well" + 0.006*"quality" + 0.006*"West" + 0.005*"need" + 0.005*"impact" + 0.004*"plans" + 0.004*"practice" + 0.004*"October" +2024-07-25 12:45:36,657 - topic #2 (0.333): 0.019*"’" + 0.008*"Northamptonshire" + 0.008*"quality" + 0.007*"practice" + 0.007*"well" + 0.006*"needs" + 0.006*"West" + 0.005*"experiences" + 0.005*"plans" + 0.005*"NCT" +2024-07-25 12:45:36,658 - topic diff=0.755884, rho=1.000000 +2024-07-25 12:45:36,658 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:36.658374', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:37,662 - Inspection date 2022-10-03 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:37,662 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:37,662 - Inspection date 2022-10-03 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:37,662 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:37,662 - Inspection date 2022-10-03 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:37,663 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:37,663 - Inspection date 2022-10-03 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:37,663 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:37,663 - Inspection date 2022-10-03 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:37,663 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:37,663 - Inspection date 2022-10-03 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:37,664 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:39,128 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:39,130 - built Dictionary<1233 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions) +2024-07-25 12:45:39,131 - Dictionary lifecycle event {'msg': "built Dictionary<1233 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2720 corpus positions)", 'datetime': '2024-07-25T12:45:39.131070', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:39,132 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:39,132 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:39,132 - using serial LDA version on this node +2024-07-25 12:45:39,133 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:39,133 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:39,137 - -8.120 per-word bound, 278.2 perplexity estimate based on a held-out corpus of 1 documents with 2720 words +2024-07-25 12:45:39,137 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:39,138 - topic #0 (0.333): 0.010*"’" + 0.006*"Sussex" + 0.006*"well" + 0.006*"needs" + 0.005*"13" + 0.005*"plans" + 0.004*"number" + 0.004*"supported" + 0.004*"health" + 0.004*"quality" +2024-07-25 12:45:39,139 - topic #1 (0.333): 0.013*"’" + 0.006*"well" + 0.005*"West" + 0.005*"plans" + 0.005*"quality" + 0.004*"needs" + 0.004*"Sussex" + 0.004*"practice" + 0.004*"13" + 0.004*"number" +2024-07-25 12:45:39,139 - topic #2 (0.333): 0.017*"’" + 0.008*"plans" + 0.006*"needs" + 0.006*"well" + 0.005*"West" + 0.005*"13" + 0.005*"supported" + 0.004*"Sussex" + 0.004*"number" + 0.004*"health" +2024-07-25 12:45:39,139 - topic diff=0.806627, rho=1.000000 +2024-07-25 12:45:39,139 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:39.139601', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:40,095 - Inspection date 2023-03-13 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:40,096 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:40,096 - Inspection date 2023-03-13 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:40,096 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:40,097 - Inspection date 2023-03-13 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:40,097 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:40,097 - Inspection date 2023-03-13 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:40,097 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:40,097 - Inspection date 2023-03-13 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:40,098 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:40,098 - Inspection date 2023-03-13 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:40,098 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:41,654 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:41,657 - built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2451 corpus positions) +2024-07-25 12:45:41,657 - Dictionary lifecycle event {'msg': "built Dictionary<1076 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2451 corpus positions)", 'datetime': '2024-07-25T12:45:41.657228', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:41,658 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:41,658 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:41,658 - using serial LDA version on this node +2024-07-25 12:45:41,659 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:41,659 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:41,664 - -7.967 per-word bound, 250.2 perplexity estimate based on a held-out corpus of 1 documents with 2451 words +2024-07-25 12:45:41,664 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:41,666 - topic #0 (0.333): 0.014*"’" + 0.009*"plans" + 0.007*"needs" + 0.007*"need" + 0.006*"Furness" + 0.006*"appropriate" + 0.006*"Westmorland" + 0.006*"protection" + 0.005*"quality" + 0.005*"progress" +2024-07-25 12:45:41,666 - topic #1 (0.333): 0.011*"’" + 0.007*"needs" + 0.006*"appropriate" + 0.005*"plans" + 0.005*"Westmorland" + 0.005*"protection" + 0.004*"quality" + 0.004*"April" + 0.004*"Furness" + 0.004*"progress" +2024-07-25 12:45:41,666 - topic #2 (0.333): 0.013*"’" + 0.008*"Westmorland" + 0.008*"Furness" + 0.007*"plans" + 0.006*"need" + 0.006*"needs" + 0.005*"quality" + 0.005*"appropriate" + 0.005*"leaders" + 0.004*"response" +2024-07-25 12:45:41,666 - topic diff=0.801129, rho=1.000000 +2024-07-25 12:45:41,667 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:41.667070', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:43,102 - Inspection date 2024-04-22 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:43,102 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:43,102 - Inspection date 2024-04-22 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:43,102 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:43,102 - Inspection date 2024-04-22 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:43,103 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:43,103 - Inspection date 2024-04-22 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:43,103 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:43,103 - Inspection date 2024-04-22 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:43,103 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:43,103 - Inspection date 2024-04-22 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:43,103 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:44,515 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:44,518 - built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2416 corpus positions) +2024-07-25 12:45:44,518 - Dictionary lifecycle event {'msg': "built Dictionary<1064 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2416 corpus positions)", 'datetime': '2024-07-25T12:45:44.518181', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:44,519 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:44,519 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:44,519 - using serial LDA version on this node +2024-07-25 12:45:44,520 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:44,520 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:44,523 - -7.958 per-word bound, 248.7 perplexity estimate based on a held-out corpus of 1 documents with 2416 words +2024-07-25 12:45:44,523 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:44,525 - topic #0 (0.333): 0.012*"’" + 0.007*"May" + 0.006*"plans" + 0.006*"practice" + 0.005*"quality" + 0.005*"timely" + 0.005*"2022" + 0.004*"Wigan" + 0.004*"needs" + 0.004*"appropriate" +2024-07-25 12:45:44,525 - topic #1 (0.333): 0.011*"’" + 0.007*"practice" + 0.007*"Wigan" + 0.006*"May" + 0.006*"plans" + 0.006*"leaders" + 0.006*"needs" + 0.006*"quality" + 0.005*"appropriate" + 0.005*"9" +2024-07-25 12:45:44,525 - topic #2 (0.333): 0.014*"’" + 0.008*"May" + 0.007*"needs" + 0.007*"plans" + 0.006*"practice" + 0.006*"appropriate" + 0.005*"Wigan" + 0.005*"quality" + 0.005*"leaders" + 0.004*"9" +2024-07-25 12:45:44,525 - topic diff=0.793934, rho=1.000000 +2024-07-25 12:45:44,525 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:44.525626', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:45,636 - Inspection date 2022-05-09 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:45,637 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:45,637 - Inspection date 2022-05-09 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:45,637 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:45,638 - Inspection date 2022-05-09 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:45,638 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:45,638 - Inspection date 2022-05-09 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:45,638 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:45,638 - Inspection date 2022-05-09 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:45,639 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:45,639 - Inspection date 2022-05-09 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:45,639 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:47,229 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:47,231 - built Dictionary<1090 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2600 corpus positions) +2024-07-25 12:45:47,231 - Dictionary lifecycle event {'msg': "built Dictionary<1090 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2600 corpus positions)", 'datetime': '2024-07-25T12:45:47.231882', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:47,232 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:47,233 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:47,233 - using serial LDA version on this node +2024-07-25 12:45:47,233 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:47,233 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:47,237 - -7.954 per-word bound, 248.0 perplexity estimate based on a held-out corpus of 1 documents with 2600 words +2024-07-25 12:45:47,237 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:47,238 - topic #0 (0.333): 0.017*"’" + 0.012*"well" + 0.007*"needs" + 0.007*"progress" + 0.007*"need" + 0.006*"risk" + 0.006*"including" + 0.006*"quality" + 0.005*"supported" + 0.005*"ensure" +2024-07-25 12:45:47,239 - topic #1 (0.333): 0.015*"’" + 0.012*"well" + 0.008*"needs" + 0.006*"Wiltshire" + 0.006*"need" + 0.006*"parents" + 0.006*"supported" + 0.005*"family" + 0.005*"risk" + 0.005*"plans" +2024-07-25 12:45:47,239 - topic #2 (0.333): 0.013*"’" + 0.009*"well" + 0.006*"needs" + 0.006*"need" + 0.006*"Wiltshire" + 0.006*"including" + 0.006*"parents" + 0.005*"progress" + 0.005*"plans" + 0.005*"ensure" +2024-07-25 12:45:47,239 - topic diff=0.831852, rho=1.000000 +2024-07-25 12:45:47,239 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:47.239695', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:48,654 - Inspection date 2023-09-25 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:48,657 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:48,658 - Inspection date 2023-09-25 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:48,658 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:48,658 - Inspection date 2023-09-25 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:48,659 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:48,659 - Inspection date 2023-09-25 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:48,659 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:48,660 - Inspection date 2023-09-25 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:48,660 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:48,660 - Inspection date 2023-09-25 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:48,660 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:50,090 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:50,093 - built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions) +2024-07-25 12:45:50,093 - Dictionary lifecycle event {'msg': "built Dictionary<1000 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)", 'datetime': '2024-07-25T12:45:50.093210', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:50,094 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:50,094 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:50,094 - using serial LDA version on this node +2024-07-25 12:45:50,095 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:50,095 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:50,098 - -7.908 per-word bound, 240.2 perplexity estimate based on a held-out corpus of 1 documents with 2233 words +2024-07-25 12:45:50,098 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:50,099 - topic #0 (0.333): 0.012*"needs" + 0.011*"’" + 0.008*"Wirral" + 0.007*"ensure" + 0.006*"plans" + 0.005*"risk" + 0.005*"practice" + 0.005*"well" + 0.005*"number" + 0.005*"good" +2024-07-25 12:45:50,100 - topic #1 (0.333): 0.009*"needs" + 0.008*"’" + 0.006*"plans" + 0.006*"practice" + 0.006*"response" + 0.006*"ensure" + 0.005*"well" + 0.005*"18" + 0.005*"2023" + 0.005*"small" +2024-07-25 12:45:50,100 - topic #2 (0.333): 0.013*"’" + 0.009*"ensure" + 0.008*"Wirral" + 0.008*"needs" + 0.007*"plans" + 0.006*"practice" + 0.006*"well" + 0.005*"number" + 0.005*"small" + 0.005*"18" +2024-07-25 12:45:50,100 - topic diff=0.804334, rho=1.000000 +2024-07-25 12:45:50,100 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:50.100682', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:51,050 - Inspection date 2023-09-18 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:51,051 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:51,051 - Inspection date 2023-09-18 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:51,051 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:51,051 - Inspection date 2023-09-18 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:51,051 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:51,051 - Inspection date 2023-09-18 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:51,052 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:51,052 - Inspection date 2023-09-18 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:51,052 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:51,052 - Inspection date 2023-09-18 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:51,052 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:52,705 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:52,707 - built Dictionary<1096 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2214 corpus positions) +2024-07-25 12:45:52,707 - Dictionary lifecycle event {'msg': "built Dictionary<1096 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2214 corpus positions)", 'datetime': '2024-07-25T12:45:52.707660', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:52,708 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:52,708 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:52,709 - using serial LDA version on this node +2024-07-25 12:45:52,709 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:52,709 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:52,713 - -8.064 per-word bound, 267.5 perplexity estimate based on a held-out corpus of 1 documents with 2214 words +2024-07-25 12:45:52,713 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:52,714 - topic #0 (0.333): 0.012*"’" + 0.006*"effective" + 0.006*"progress" + 0.006*"plans" + 0.005*"well" + 0.005*"needs" + 0.005*"quality" + 0.005*"Council" + 0.005*"6" + 0.004*"ensure" +2024-07-25 12:45:52,714 - topic #1 (0.333): 0.011*"’" + 0.006*"plans" + 0.006*"effective" + 0.005*"provided" + 0.005*"needs" + 0.005*"progress" + 0.005*"well" + 0.005*"experiences" + 0.005*"March" + 0.004*"good" +2024-07-25 12:45:52,715 - topic #2 (0.333): 0.014*"’" + 0.008*"plans" + 0.007*"needs" + 0.006*"17" + 0.006*"effective" + 0.005*"progress" + 0.005*"well" + 0.005*"Borough" + 0.005*"protection" + 0.005*"provided" +2024-07-25 12:45:52,715 - topic diff=0.755295, rho=1.000000 +2024-07-25 12:45:52,715 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:52.715313', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:53,776 - Inspection date 2023-03-06 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:53,776 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:53,776 - Inspection date 2023-03-06 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:53,776 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:53,777 - Inspection date 2023-03-06 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:53,777 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:53,777 - Inspection date 2023-03-06 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:53,777 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:53,778 - Inspection date 2023-03-06 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:53,778 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:53,778 - Inspection date 2023-03-06 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:53,778 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:55,239 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:55,241 - built Dictionary<1095 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions) +2024-07-25 12:45:55,241 - Dictionary lifecycle event {'msg': "built Dictionary<1095 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2233 corpus positions)", 'datetime': '2024-07-25T12:45:55.241517', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:55,242 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:55,242 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:55,242 - using serial LDA version on this node +2024-07-25 12:45:55,243 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:55,243 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:55,247 - -8.047 per-word bound, 264.6 perplexity estimate based on a held-out corpus of 1 documents with 2233 words +2024-07-25 12:45:55,247 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:55,248 - topic #0 (0.333): 0.010*"’" + 0.004*"effective" + 0.004*"Wolverhampton" + 0.004*"plans" + 0.004*"receive" + 0.004*"quality" + 0.004*"City" + 0.004*"needs" + 0.004*"supported" + 0.004*"experiences" +2024-07-25 12:45:55,248 - topic #1 (0.333): 0.016*"’" + 0.008*"needs" + 0.006*"effective" + 0.005*"leaders" + 0.005*"quality" + 0.005*"Wolverhampton" + 0.005*"plans" + 0.005*"strong" + 0.005*"receive" + 0.004*"risk" +2024-07-25 12:45:55,248 - topic #2 (0.333): 0.015*"’" + 0.009*"needs" + 0.006*"effective" + 0.006*"Wolverhampton" + 0.006*"risks" + 0.005*"well" + 0.005*"plans" + 0.005*"education" + 0.005*"receive" + 0.005*"risk" +2024-07-25 12:45:55,249 - topic diff=0.743938, rho=1.000000 +2024-07-25 12:45:55,249 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:55.249145', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:56,346 - Inspection date 2022-03-28 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:56,347 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:56,347 - Inspection date 2022-03-28 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:56,347 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:56,347 - Inspection date 2022-03-28 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:56,348 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:56,348 - Inspection date 2022-03-28 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:56,348 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:56,348 - Inspection date 2022-03-28 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:56,348 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:56,349 - Inspection date 2022-03-28 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:56,349 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:57,820 - adding document #0 to Dictionary<0 unique tokens: []> +2024-07-25 12:45:57,822 - built Dictionary<1041 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2343 corpus positions) +2024-07-25 12:45:57,823 - Dictionary lifecycle event {'msg': "built Dictionary<1041 unique tokens: ['0161', '0300', '1', '10', '11']...> from 1 documents (total 2343 corpus positions)", 'datetime': '2024-07-25T12:45:57.823090', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:57,824 - using symmetric alpha at 0.3333333333333333 +2024-07-25 12:45:57,824 - using symmetric eta at 0.3333333333333333 +2024-07-25 12:45:57,824 - using serial LDA version on this node +2024-07-25 12:45:57,824 - running online (single-pass) LDA training, 3 topics, 1 passes over the supplied corpus of 1 documents, updating model once every 1 documents, evaluating perplexity every 1 documents, iterating 50x with a convergence threshold of 0.001000 +2024-07-25 12:45:57,824 - too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy +2024-07-25 12:45:57,828 - -7.943 per-word bound, 246.1 perplexity estimate based on a held-out corpus of 1 documents with 2343 words +2024-07-25 12:45:57,828 - PROGRESS: pass 0, at document #1/1 +2024-07-25 12:45:57,829 - topic #0 (0.333): 0.017*"’" + 0.007*"plans" + 0.007*"needs" + 0.006*"well" + 0.006*"Worcestershire" + 0.006*"progress" + 0.006*"Senior" + 0.005*"leaders" + 0.004*"26" + 0.004*"ensure" +2024-07-25 12:45:57,829 - topic #1 (0.333): 0.022*"’" + 0.009*"well" + 0.008*"progress" + 0.007*"plans" + 0.007*"Worcestershire" + 0.007*"needs" + 0.006*"appropriate" + 0.006*"leaders" + 0.005*"ensure" + 0.005*"PAs" +2024-07-25 12:45:57,830 - topic #2 (0.333): 0.017*"’" + 0.009*"well" + 0.009*"plans" + 0.008*"needs" + 0.008*"leaders" + 0.007*"ensure" + 0.007*"Worcestershire" + 0.006*"appropriate" + 0.005*"15" + 0.005*"experiences" +2024-07-25 12:45:57,830 - topic diff=0.806639, rho=1.000000 +2024-07-25 12:45:57,830 - LdaModel lifecycle event {'msg': 'trained LdaModel in 0.01s', 'datetime': '2024-07-25T12:45:57.830338', 'gensim': '4.3.2', 'python': '3.10.13 (main, Jul 9 2024, 21:32:52) [GCC 9.4.0]', 'platform': 'Linux-6.5.0-1022-azure-x86_64-with-glibc2.31', 'event': 'created'} +2024-07-25 12:45:58,967 - Inspection date 2023-05-15 / Column 'overall_effectiveness' not found in the DataFrame. +2024-07-25 12:45:58,973 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:58,973 - Inspection date 2023-05-15 / Column 'impact_of_leaders' not found in the DataFrame. +2024-07-25 12:45:58,973 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:58,974 - Inspection date 2023-05-15 / Column 'help_and_protection' not found in the DataFrame. +2024-07-25 12:45:58,974 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:58,974 - Inspection date 2023-05-15 / Column 'in_care' not found in the DataFrame. +2024-07-25 12:45:58,974 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:58,975 - Inspection date 2023-05-15 / Column 'care_leavers' not found in the DataFrame. +2024-07-25 12:45:58,975 - Index(['judgement', 'grade'], dtype='object') +2024-07-25 12:45:58,975 - Inspection date 2023-05-15 / Column 'in_care_and_care_leavers' not found in the DataFrame. +2024-07-25 12:45:58,975 - Index(['judgement', 'grade'], dtype='object')
      SE E10000014 Hampshireofsted.gov.uk/50083968ofsted.gov.uk/50253183 outstanding shortDonna Marriott29/04/2019Kendra Bell10/06/2024 outstanding outstanding outstandinginspection_pre_dates_judgementgood
      80473 GL E09000003 Barnetofsted.gov.uk/50088889ofsted.gov.uk/50253182 goodstandardAndy Whippey13/05/2019shortNaintara Khosla10/06/2024 good goodoutstanding goodinspection_pre_dates_judgement
      80488 GL E09000011 Greenwichofsted.gov.uk/50143727goodofsted.gov.uk/50252576outstanding shortAndy Whippey09/12/2019goodgoodTom Anthony03/06/2024outstanding goodinspection_pre_dates_judgementoutstandingoutstanding
      80496 GL E09000026 Redbridgeofsted.gov.uk/50083969ofsted.gov.uk/50253184 outstanding shortLouise Hocking29/04/2019Brenda Mclaughlin10/06/2024outstandingoutstanding outstanding outstandinggoodinspection_pre_dates_judgement
      80513 SW E06000025 South Gloucestershireofsted.gov.uk/50074950requires improvementofsted.gov.uk/50253185good standardEmmy Tomsett04/03/2019requires improvementrequires improvementrequires improvementinspection_pre_dates_judgementAnna Gravelle03/06/2024goodgoodgoodgood
      80557

      Summarised outcomes of published short and standard ILACS inspection reports by Ofsted, refreshed daily.
      An expanded version of the shown summary sheet, refreshed concurrently, is available to       download here as an .xlsx file.
      Data summary is based on the original ILACS Outcomes Summary published periodically by the ADCS: https://adcs.org.uk/inspection/article/ilacs-outcomes-summary. Read the tool/project background details and future work..

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