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results_b4_may_2020.txt
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results_b4_may_2020.txt
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#best results (v3 only true and false)
(20, 'bert', 0.001, 64) AVG: 0.8689458689458691 F1: 0.8048860297358954
(20, 'bert', 0.001, 128) AVG: 0.8461538461538461 F1: 0.7740770142060579
(50, 'bert', 0.001, 64) AVG: 0.8632478632478631 F1: 0.8004196578449229
(50, 'bert', 0.001, 128) AVG: 0.8433048433048432 F1: 0.778212630705005
(100, 'bert', 0.001, 64) AVG: 0.8404558404558404 F1: 0.777913092832243
(100, 'bert', 0.001, 128) AVG: 0.8404558404558404 F1: 0.7756993848714084
(200, 'bert', 0.001, 64) AVG: 0.8461538461538463 F1: 0.7837240762294333
(200, 'bert', 0.001, 128) AVG: 0.8490028490028491 F1: 0.7872591335774856
#v3 DATA UNTREATED (only TRUE AND FALSE)
TrainsetLen:(321, 863) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.674074074074074 F1: 0.6317521210058843
TrainsetLen:(321, 863) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.6419753086419753 F1: 0.6206380610389128
TrainsetLen:(321, 863) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7012345679012346 F1: 0.6727209485881337
TrainsetLen:(321, 863) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.7135802469135801 F1: 0.6750098172684134
TrainsetLen:(321, 863) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7209876543209877 F1: 0.6852421740160232
TrainsetLen:(321, 863) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7185185185185186 F1: 0.6733793440279496
TrainsetLen:(321, 863) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7185185185185186 F1: 0.674738569439763
TrainsetLen:(321, 863) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7086419753086419 F1: 0.6719901857720199
#v3 DATA WITH "collapse classes"(mfalse as false and mtrue as true)
TrainsetLen:(353, 863) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.5511111111111111 F1: 0.5202772056303212
TrainsetLen:(353, 863) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.5977777777777777 F1: 0.5281472877276544
TrainsetLen:(353, 863) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.6377777777777779 F1: 0.5734684309519958
TrainsetLen:(353, 863) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.6177777777777779 F1: 0.5527584727168625
TrainsetLen:(353, 863) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.6377777777777778 F1: 0.5667083239343146
TrainsetLen:(353, 863) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.6577777777777778 F1: 0.5923872909441649
TrainsetLen:(353, 863) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.6955555555555555 F1: 0.612916011218967
TrainsetLen:(353, 863) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.6977777777777778 F1: 0.6149284284801225
### v4
#v4 collapse classes TRUE (mfalse as false and mtrue as true)
TrainsetLen:(714, 863) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7200435729847494 F1: 0.6699397164211037
TrainsetLen:(714, 863) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.7135076252723311 F1: 0.6461261238899867
TrainsetLen:(714, 863) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.6938997821350763 F1: 0.6184620894860654
TrainsetLen:(714, 863) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.6993464052287582 F1: 0.6173890567697676
TrainsetLen:(714, 863) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7026143790849674 F1: 0.6325587470930653
TrainsetLen:(714, 863) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.6971677559912854 F1: 0.6182563348734601
TrainsetLen:(714, 863) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.6982570806100218 F1: 0.6229358109323447
TrainsetLen:(714, 863) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.681917211328976 F1: 0.5825949753772455
#v4 collapse classes FALSE
TrainsetLen:(621, 863) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.8068181818181818 F1: 0.6736731854097592
TrainsetLen:(621, 863) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.7904040404040404 F1: 0.63375637160123
TrainsetLen:(621, 863) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.821969696969697 F1: 0.6974293813962524
TrainsetLen:(621, 863) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.8068181818181819 F1: 0.678988100884967
TrainsetLen:(621, 863) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.797979797979798 F1: 0.6598348950974141
TrainsetLen:(621, 863) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.8207070707070707 F1: 0.6812435697912221
TrainsetLen:(621, 863) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.8257575757575758 F1: 0.7020408639234332
TrainsetLen:(621, 863) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.821969696969697 F1: 0.6911847994317742
extra runs on v4 with collapse TRUE
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7108585858585859 F1: 0.6453638742997793
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.7361111111111112 F1: 0.6524153647353638
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7512626262626262 F1: 0.679105064425823
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.7537878787878789 F1: 0.6599440523915497
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7714646464646465 F1: 0.6828075704363097
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7676767676767676 F1: 0.6659756337122071
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7563131313131314 F1: 0.6778670696533675
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7563131313131313 F1: 0.6599403910084006
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.736111111111111 F1: 0.6799477797422496
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.7209595959595959 F1: 0.6539917585784987
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7398989898989898 F1: 0.6570805019707451
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.7550505050505051 F1: 0.6709194492641729
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7550505050505051 F1: 0.6758224511210706
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7689393939393939 F1: 0.6842658104094728
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7676767676767676 F1: 0.6742618250237543
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7487373737373737 F1: 0.6608583420738596
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.720959595959596 F1: 0.6719383217130562
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.7247474747474747 F1: 0.6488320913931492
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7537878787878787 F1: 0.674723628343655
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.75 F1: 0.6585813905274365
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.744949494949495 F1: 0.6530331041672234
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7575757575757577 F1: 0.6596980647151749
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7474747474747474 F1: 0.6773976263194514
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7664141414141413 F1: 0.6804002351873376
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7260101010101011 F1: 0.6788560207435248
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.7196969696969697 F1: 0.6589760494254284
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7424242424242424 F1: 0.6726399920832415
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.755050505050505 F1: 0.6596147418139722
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7386363636363636 F1: 0.6639696682256817
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7664141414141414 F1: 0.6854829163023655
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7537878787878788 F1: 0.647909325719363
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.758838383838384 F1: 0.6659725761150626
same setup but now forcing reload of data
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7020202020202021 F1: 0.6429561664146669
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.7196969696969697 F1: 0.6527417764233955
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7487373737373737 F1: 0.6741703116948756
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.7398989898989898 F1: 0.6508415887436871
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7638888888888888 F1: 0.6751024469468984
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7676767676767676 F1: 0.6860083204645555
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7512626262626263 F1: 0.6705467962770736
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7739898989898989 F1: 0.6582146746295336
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7184343434343434 F1: 0.6538781559720095
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.7234848484848485 F1: 0.6455339050691581
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7373737373737373 F1: 0.658538161202205
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.731060606060606 F1: 0.6487966432424572
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7474747474747475 F1: 0.6575578569710953
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7474747474747475 F1: 0.6568408106541741
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7512626262626263 F1: 0.6613052542695734
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7525252525252526 F1: 0.6515079494411358
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7373737373737373 F1: 0.6651754803968628
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.7247474747474748 F1: 0.6633974608169947
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7411616161616162 F1: 0.648631870516612
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.73989898989899 F1: 0.6431713643065384
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.720959595959596 F1: 0.6510955569532964
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7424242424242424 F1: 0.6516454559404898
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7651515151515151 F1: 0.6627425697504856
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7613636363636364 F1: 0.6644260018620556
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7449494949494949 F1: 0.67988720484891
TrainsetLen:(622, 863) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.7260101010101011 F1: 0.6546237960627617
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7512626262626263 F1: 0.6669366069639944
TrainsetLen:(622, 863) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.7525252525252525 F1: 0.6685546064594037
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7702020202020203 F1: 0.6907380426648446
TrainsetLen:(622, 863) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7815656565656566 F1: 0.6766624642049663
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7815656565656566 F1: 0.6776362735856254
TrainsetLen:(622, 863) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7664141414141414 F1: 0.6736258544817799
****** RESULTS v4 / COLLAPSE FALSE / WITHOUT COMPLEXITY FEATURE ****
TrainsetLen:(622, 838) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.6679292929292928 F1: 0.5625836651193156
TrainsetLen:(622, 838) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.6502525252525252 F1: 0.5590409561495737
TrainsetLen:(622, 838) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.6818181818181819 F1: 0.5784616663930958
TrainsetLen:(622, 838) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.7032828282828282 F1: 0.5787442659027983
TrainsetLen:(622, 838) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7083333333333334 F1: 0.5865571491744946
TrainsetLen:(622, 838) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.720959595959596 F1: 0.5918099381254462
TrainsetLen:(622, 838) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7083333333333334 F1: 0.5837470218572236
TrainsetLen:(622, 838) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7083333333333334 F1: 0.5904233084727503
****** RESULTS v4+EM / COLLAPSE FALSE / WITHOUT COMPLEXITY FEATURE ****
TrainsetLen:(958, 838) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.6985294117647058 F1: 0.6923286478694658
TrainsetLen:(958, 838) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.6985294117647058 F1: 0.6949907186478541
TrainsetLen:(958, 838) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7246732026143791 F1: 0.7192915855762092
TrainsetLen:(958, 838) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.6977124183006536 F1: 0.6950168541521303
TrainsetLen:(958, 838) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7148692810457516 F1: 0.7124557133525391
TrainsetLen:(958, 838) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.6960784313725491 F1: 0.692717044442946
TrainsetLen:(958, 838) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7181372549019607 F1: 0.7170111793674744
TrainsetLen:(958, 838) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.6691176470588236 F1: 0.6657771320172347
TrainsetLen:(958, 838) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7034313725490197 F1: 0.6986750433315349
TrainsetLen:(958, 838) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.690359477124183 F1: 0.6857559732656683
TrainsetLen:(958, 838) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7361111111111113 F1: 0.7336126814414345
TrainsetLen:(958, 838) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.7156862745098038 F1: 0.7144554235102608
TrainsetLen:(958, 838) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7222222222222221 F1: 0.7206525742509755
TrainsetLen:(958, 838) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7107843137254901 F1: 0.7084226542893836
TrainsetLen:(958, 838) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7001633986928104 F1: 0.6985383689131368
TrainsetLen:(958, 838) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.707516339869281 F1: 0.7050394393027103
#de volta ao dataset v4 apenas, vou testar qual o problema das features.... inicialmente COM complexity!
# v4+em com:True
TrainsetLen:(625, 865) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7340823970037453 F1: 0.674367151776623
TrainsetLen:(625, 865) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.717852684144819 F1: 0.6619213297172962
TrainsetLen:(625, 865) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7390761548064918 F1: 0.6788578581842117
TrainsetLen:(625, 865) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.7315855181023719 F1: 0.6652669954565833
TrainsetLen:(625, 865) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7540574282147314 F1: 0.6944338544068681
TrainsetLen:(625, 865) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7440699126092384 F1: 0.6897296822410642
TrainsetLen:(625, 865) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.727840199750312 F1: 0.6483899504533129
TrainsetLen:(625, 865) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7365792759051185 F1: 0.6679192568439285
TrainsetLen:(1061, 865) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7093451066961001 F1: 0.6946134328417058
TrainsetLen:(1061, 865) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.698307579102281 F1: 0.667962324694504
TrainsetLen:(1061, 865) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7152317880794701 F1: 0.6802564767398763
TrainsetLen:(1061, 865) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.712288447387785 F1: 0.6791362630176496
TrainsetLen:(1061, 865) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7041942604856513 F1: 0.6766260717234183
TrainsetLen:(1061, 865) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7019867549668873 F1: 0.6663619576937596
TrainsetLen:(1061, 865) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7122884473877852 F1: 0.6848153800333173
TrainsetLen:(1061, 865) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7167034584253127 F1: 0.6859640029737792
# v4+em com:False
TrainsetLen:(1061, 865) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7078734363502577 F1: 0.6897344257954485
TrainsetLen:(1061, 865) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.6835908756438558 F1: 0.6674025293735191
TrainsetLen:(1061, 865) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7144959529065489 F1: 0.6944605620594334
TrainsetLen:(1061, 865) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.7181751287711553 F1: 0.6892359950575031
TrainsetLen:(1061, 865) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7078734363502575 F1: 0.6867923030794718
TrainsetLen:(1061, 865) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7078734363502576 F1: 0.6850653926369469
TrainsetLen:(1061, 865) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7078734363502576 F1: 0.6827734560155078
TrainsetLen:(1061, 865) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7027225901398088 F1: 0.6696055221832401
TrainsetLen:(1061, 865) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7005150846210448 F1: 0.690905688401158
TrainsetLen:(1061, 840) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7027225901398086 F1: 0.6856016389054808
TrainsetLen:(1061, 840) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.7115526122148638 F1: 0.6911435277704809
TrainsetLen:(1061, 840) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.723325974981604 F1: 0.6971652993155492
TrainsetLen:(1061, 840) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.7174392935982339 F1: 0.6904006560807419
TrainsetLen:(1061, 840) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7284768211920529 F1: 0.6966029444063674
TrainsetLen:(1061, 840) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7122884473877851 F1: 0.680121418209873
TrainsetLen:(1061, 840) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7218543046357616 F1: 0.6933612535336773
TrainsetLen:(1061, 840) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7203826342899189 F1: 0.6846833904561664
TrainsetLen:(1061, 840) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7144959529065489 F1: 0.6996083410616397
TrainsetLen:(1061, 840) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.700515084621045 F1: 0.6753712614530487
TrainsetLen:(1061, 840) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7270051508462105 F1: 0.7090652179735304
TrainsetLen:(1061, 840) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.720382634289919 F1: 0.6927175506011944
TrainsetLen:(1061, 840) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7218543046357615 F1: 0.6914917525215568
TrainsetLen:(1061, 840) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7218543046357616 F1: 0.6879307263086961
TrainsetLen:(1061, 840) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7225901398086829 F1: 0.6962001926890139
TrainsetLen:(1061, 840) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7196467991169977 F1: 0.6847207434813863
TrainsetLen:(1061, 840) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7049300956585725 F1: 0.6951064084083606
TrainsetLen:(1061, 840) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.7078734363502576 F1: 0.6923177874802946
TrainsetLen:(1061, 840) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7086092715231787 F1: 0.6837486811208242
TrainsetLen:(1061, 840) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.7225901398086828 F1: 0.6913756747360043
TrainsetLen:(1061, 840) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7328918322295804 F1: 0.7024758876127236
TrainsetLen:(1061, 840) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.7211184694628403 F1: 0.693562796880557
TrainsetLen:(1061, 840) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7284768211920529 F1: 0.6968979883135755
TrainsetLen:(1061, 840) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7189109639440765 F1: 0.685009522723463
TrainsetLen:(1061, 840) #EPOCH: (20, 'bert', 0.001, 64) AVG: 0.7137601177336277 F1: 0.7001789670925925
TrainsetLen:(1061, 840) #EPOCH: (20, 'bert', 0.001, 128) AVG: 0.7093451066961001 F1: 0.6891535902389705
TrainsetLen:(1061, 840) #EPOCH: (50, 'bert', 0.001, 64) AVG: 0.7225901398086829 F1: 0.7016274143939377
TrainsetLen:(1061, 840) #EPOCH: (50, 'bert', 0.001, 128) AVG: 0.7358351729212658 F1: 0.7080396716550684
TrainsetLen:(1061, 840) #EPOCH: (100, 'bert', 0.001, 64) AVG: 0.7247976453274466 F1: 0.7032433510360142
TrainsetLen:(1061, 840) #EPOCH: (100, 'bert', 0.001, 128) AVG: 0.720382634289919 F1: 0.6982341220351648
TrainsetLen:(1061, 840) #EPOCH: (200, 'bert', 0.001, 64) AVG: 0.7373068432671082 F1: 0.7119445611222622
TrainsetLen:(1061, 840) #EPOCH: (200, 'bert', 0.001, 128) AVG: 0.7218543046357616 F1: 0.6898839566364092