-
Notifications
You must be signed in to change notification settings - Fork 0
/
last_results.txt
183 lines (180 loc) · 22.5 KB
/
last_results.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
TrainShape:(1182, 837) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7715514542437619 VAR: 0.0004561393867217342 F1: 0.7700569259674002 SEED: 27966
EM:
TrainShape:(367, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7962425415255604 VAR: 0.00511283092569434 F1: 0.7724194937224348 SEED: 27966
V4+T1:
TrainShape:(1033, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7778084206655635 VAR: 0.001000328217122271 F1: 0.7762594354428232 SEED: 27966
V4+EM+T1:
TrainShape:(1393, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7580861659588627 VAR: 0.0010649839439679906 F1: 0.7565851190415939 SEED: 27966
V4+EM:
TrainShape:(1111, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7009173013472033 VAR: 0.0006575531504132824 F1: 0.6802253901353477 SEED: 27966
V4:
TrainShape:(428, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7822139961219814 VAR: 0.002733094927438084 F1: 0.6638400688680162 SEED: 27966
TrainShape:(428, 768) #EPOCH: ([], 200, only_bert, 0.0001, 256, 0.5, 32) AVG: 0.7767495152476642 VAR: 0.0024914140039895075 F1: 0.6489133364321619 SEED: 27966
V4+EM:
TrainShape:(1111, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7079452272908209 VAR: 0.0006697995169520422 F1: 0.6871734149192805 SEED: 27966
==
SNOPES:
TrainShape:(1722, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.830255751950232 VAR: 0.0006536631922473066 F1: 0.4862570236870748 SEED: 27966
SNOPES:
TrainShape:(1722, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.830255751950232 VAR: 0.0006536631922473066 F1: 0.4862570236870748 SEED: 27966
V4:
TrainShape:(428, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7822139961219814 VAR: 0.002733094927438084 F1: 0.6638400688680162 SEED: 27966
TrainShape:(428, 768) #EPOCH: ([], 200, only_bert, 0.0001, 256, 0.5, 32) AVG: 0.7767495152476642 VAR: 0.0024914140039895075 F1: 0.6489133364321619 SEED: 27966
V4+EM:
TrainShape:(1111, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.70095268423427 VAR: 0.00048486083381435316 F1: 0.682087536047316 SEED: 27966
V4+EM+T2:
TrainShape:(1182, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7530603299834069 VAR: 0.001646489814804352 F1: 0.7518725090010488 SEED: 27966
TrainShape:(1182, 768) #EPOCH: ([], 200, only_bert, 0.0001, 256, 0.5, 32) AVG: 0.7590166244012397 VAR: 0.0015636108414139062 F1: 0.7573260537091735 SEED: 27966
V4+EM+T2#:
TrainShape:(1050, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7879741486452896 VAR: 0.002128979743556332 F1: 0.7865494905642644 SEED: 27966
TrainShape:(1050, 768) #EPOCH: ([], 200, only_bert, 0.0001, 256, 0.5, 32) AVG: 0.8124384787472034 VAR: 0.0012845898944603223 F1: 0.8106966247010453 SEED: 27966
FEVER:
TrainShape:(3962, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.6717707106399686 VAR: 0.00023430723443625763 F1: 0.6694974328617441 SEED: 27966
====
SNOPES:
TrainShape:(1722, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.8307019372487923 VAR: 0.0004875895117583953 F1: 0.5005329050343599 SEED: 27966
V4:
TrainShape:(428, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7822139961219814 VAR: 0.002733094927438084 F1: 0.6638400688680162 SEED: 27966
TrainShape:(428, 768) #EPOCH: ([], 200, only_bert, 0.0001, 256, 0.5, 32) AVG: 0.7767495152476642 VAR: 0.0024914140039895075 F1: 0.6489133364321619 SEED: 27966
V4+EM:
TrainShape:(1111, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7079452272908209 VAR: 0.0006697995169520422 F1: 0.6871734149192805 SEED: 27966
V4+EM+T2#:
TrainShape:(1050, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7968729803629133 VAR: 0.001992087974880207 F1: 0.795337718836493 SEED: 27966
TrainShape:(1050, 768) #EPOCH: ([], 200, only_bert, 0.0001, 256, 0.5, 32) AVG: 0.8124384787472034 VAR: 0.0012845898944603223 F1: 0.8106966247010453 SEED: 27966
V4+EM+T2:
TrainShape:(1050, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7968729803629133 VAR: 0.001992087974880207 F1: 0.795337718836493 SEED: 27966
TrainShape:(1050, 768) #EPOCH: ([], 200, only_bert, 0.0001, 256, 0.5, 32) AVG: 0.8124384787472034 VAR: 0.0012845898944603223 F1: 0.8106966247010453 SEED: 27966
V4+EM+T2#:
TrainShape:(1050, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7968729803629133 VAR: 0.001992087974880207 F1: 0.795337718836493 SEED: 27966
TrainShape:(1050, 768) #EPOCH: ([], 200, only_bert, 0.0001, 256, 0.5, 32) AVG: 0.8124384787472034 VAR: 0.0012845898944603223 F1: 0.8106966247010453 SEED: 27966
=======
V4+EM+T2#:
TrainShape:(1050, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7968729803629133 VAR: 0.001992087974880207 F1: 0.795337718836493 SEED: 27966
TrainShape:(1050, 768) #EPOCH: ([], 200, only_bert, 0.0001, 256, 0.5, 32) AVG: 0.8124384787472034 VAR: 0.0012845898944603223 F1: 0.8106966247010453 SEED: 27966
V4+EM+T2:
TrainShape:(1182, 870) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7530603299834069 VAR: 0.001646489814804352 F1: 0.7518725090010488 SEED: 27966
TrainShape:(1182, 768) #EPOCH: ([], 200, only_bert, 0.0001, 256, 0.5, 32) AVG: 0.7590166244012397 VAR: 0.0015636108414139062 F1: 0.7573260537091735 SEED: 27966
GROUP ABLATION:
Results without inf:
TrainShape:(1182, 837) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7557214864907172 VAR: 0.0013541197252360626 F1: 0.7542889819800106 SEED: 27966
Results without div:
TrainShape:(1182, 860) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7511075107228954 VAR: 0.0014135574804223488 F1: 0.7496553231600228 SEED: 27966
Results without qua:
TrainShape:(1182, 823) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7563906890829968 VAR: 0.0007520395713590869 F1: 0.7549691700717861 SEED: 27966
Results without aff:
TrainShape:(1182, 864) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7504343946651639 VAR: 0.00159791017724997 F1: 0.749090267161891 SEED: 27966
Results without sbj:
TrainShape:(1182, 868) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7458517266209576 VAR: 0.0007399685502100286 F1: 0.7441767339381784 SEED: 27966
Results without spe:
TrainShape:(1182, 869) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7497808459346921 VAR: 0.0012456469499864406 F1: 0.7479477359476279 SEED: 27966
Results without pau:
TrainShape:(1182, 869) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7603393757239911 VAR: 0.0007868877737571947 F1: 0.7586553177337382 SEED: 27966
Results without unc:
TrainShape:(1182, 869) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.748489402335556 VAR: 0.0006319726906572117 F1: 0.7469578288466692 SEED: 27966
Results without pas:
TrainShape:(1182, 869) #EPOCH: ([], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.748489402335556 VAR: 0.0006319726906572117 F1: 0.7469578288466692 SEED: 27966
INDIVIDUAL ABLATION:
TrainShape:(1182, 869) #EPOCH: ([0], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7524420024420025 VAR: 0.000503151022257162 F1: 0.7511624643300601 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([1], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7511231645847031 VAR: 0.000498173578408049 F1: 0.7497403465714327 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([2], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7563867756175449 VAR: 0.0004561880584649734 F1: 0.7550417050935258 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([3], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7563906890829967 VAR: 0.0006564425091191987 F1: 0.7549445154154708 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([4], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7432218778372625 VAR: 0.0006723306936681117 F1: 0.741960693111088 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([5], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.749142951066028 VAR: 0.0008748585649987989 F1: 0.7476598993378913 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([6], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7511192511192512 VAR: 0.0007263692853319645 F1: 0.7496777479570856 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([7], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7517727998497228 VAR: 0.0007713022484247307 F1: 0.7503197219057957 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([8], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7563906890829968 VAR: 0.0004230239780220154 F1: 0.755008058457673 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([9], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7511035972574435 VAR: 0.0010479177633522295 F1: 0.7496273366238558 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([10], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7524263485801947 VAR: 0.0009740590821724788 F1: 0.7510365449557863 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([11], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7550640242947935 VAR: 0.0007687632313444818 F1: 0.7536363005279861 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([12], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7491272972042204 VAR: 0.0011436459850663442 F1: 0.7473157499096542 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([13], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7497925863310478 VAR: 0.0008167367234445235 F1: 0.7480031016961046 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([14], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7530759838452147 VAR: 0.0009871548441459797 F1: 0.7516759860429029 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([15], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.753749099902946 VAR: 0.0006664180417229915 F1: 0.7523480020888997 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([16], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7517806267806268 VAR: 0.0005250701534474742 F1: 0.7502576897445409 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([17], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.75375692683385 VAR: 0.0006073543452707677 F1: 0.7522892114245282 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([18], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7465131022823331 VAR: 0.0006305735235336218 F1: 0.7449616670545771 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([19], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7484659215428446 VAR: 0.0009967656909253557 F1: 0.7466723741212093 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([20], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.753745186437494 VAR: 0.0007934862715190864 F1: 0.7520071650788547 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([21], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7563946025484487 VAR: 0.0006326383510247748 F1: 0.7547218231031518 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([22], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7484737484737485 VAR: 0.0008600714216597351 F1: 0.7467788627907934 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([23], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7563789486866409 VAR: 0.0010152033987898437 F1: 0.7547733733947706 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([24], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7557175730252653 VAR: 0.0007534253529875259 F1: 0.7541735326655142 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([25], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7530720703797625 VAR: 0.0011068087961061297 F1: 0.7514843049344965 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([26], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7577017000093924 VAR: 0.0007305507669911501 F1: 0.7557385332522158 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([27], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7550679377602454 VAR: 0.000742739807162673 F1: 0.7533455471672107 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([28], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7530798973106666 VAR: 0.0007499554773314326 F1: 0.7513945303705519 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([29], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7596740865971634 VAR: 0.0007753800154693146 F1: 0.7580642230959632 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([30], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7557136595598133 VAR: 0.0009201552950032724 F1: 0.754032539698827 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([31], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7563828621520929 VAR: 0.0006298677373110287 F1: 0.7549629548117474 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([32], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.754394821702514 VAR: 0.0009077816758986132 F1: 0.7526699476580381 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([33], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7504539619924235 VAR: 0.0008903501774522375 F1: 0.7488048087838455 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([34], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7550679377602454 VAR: 0.0005248825114719685 F1: 0.7534507127877572 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([35], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7557371403525249 VAR: 0.0007584328146518526 F1: 0.7542865873949971 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([36], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7491546914623838 VAR: 0.00044810006446003605 F1: 0.7475169277867835 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([37], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7517845402460788 VAR: 0.0006874794904196467 F1: 0.7503289878521061 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([38], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7530994646379261 VAR: 0.0006771670844161473 F1: 0.7518223146987486 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([39], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.749150777996932 VAR: 0.0006368198633143851 F1: 0.7474865756680296 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([40], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7537647537647538 VAR: 0.0007674484510381466 F1: 0.7521208598991015 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([41], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7557371403525249 VAR: 0.0006572847845097397 F1: 0.754267063036279 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([42], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7563867756175449 VAR: 0.0006745098645308883 F1: 0.7544441407280578 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([43], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7524420024420024 VAR: 0.0006213467210064305 F1: 0.7511904108736275 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([44], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7537451864374941 VAR: 0.0008485080078920176 F1: 0.752067192635481 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([45], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7517610594533672 VAR: 0.0009292379813870157 F1: 0.7503511828673515 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([46], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7504539619924235 VAR: 0.0008834056784243795 F1: 0.7488960766364207 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([47], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7478045458814689 VAR: 0.0011788622732658977 F1: 0.7458704968698974 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([48], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7458399862246016 VAR: 0.0008013320707639322 F1: 0.7441573822676741 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([49], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7517532325224633 VAR: 0.0011122958076836978 F1: 0.7500015636392823 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([50], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7504500485269716 VAR: 0.0008457545165851104 F1: 0.7490732322753845 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([51], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7550522838984377 VAR: 0.0010341255574353625 F1: 0.7531903344240987 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([52], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7491272972042203 VAR: 0.0008929939812119224 F1: 0.7472378909530533 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([53], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7484737484737485 VAR: 0.0007511427738143821 F1: 0.746725123817978 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([54], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7484854888701044 VAR: 0.0008843257550910842 F1: 0.7470881962922086 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([55], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7517727998497229 VAR: 0.0009146978417845618 F1: 0.7503897178154875 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([56], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7504539619924235 VAR: 0.0007502990587939292 F1: 0.7488070646202382 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([57], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.747158824081901 VAR: 0.0007570708634930408 F1: 0.7454608847542246 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([58], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7471666510128048 VAR: 0.0007677642813367817 F1: 0.7455463695196732 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([59], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7537295325756864 VAR: 0.0010225856678330344 F1: 0.7521124069103201 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([60], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7484737484737485 VAR: 0.0007919039038314234 F1: 0.746999301058991 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([61], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7530759838452146 VAR: 0.0010502359044472736 F1: 0.7515384708552867 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([62], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7537295325756864 VAR: 0.000999243814723317 F1: 0.7521563627603237 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([63], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7530877242415703 VAR: 0.000645612081390308 F1: 0.7512508595993513 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([64], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7563789486866409 VAR: 0.0007117593083635047 F1: 0.7546471164449415 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([65], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7550601108293415 VAR: 0.0010049562049583727 F1: 0.7534477485915685 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([66], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7557214864907174 VAR: 0.0007130433050940338 F1: 0.7540973262303958 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([67], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7530798973106666 VAR: 0.0007897875865980523 F1: 0.7513150934741264 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([68], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7497964997964998 VAR: 0.0007999287072722955 F1: 0.7484904522682064 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([69], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7570324974171129 VAR: 0.0008906116693792531 F1: 0.7553256430386576 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([70], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7504461350615196 VAR: 0.0009661311321313052 F1: 0.7487778412451966 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([71], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7550679377602455 VAR: 0.0005956512874014621 F1: 0.7535917713413282 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([72], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7550640242947936 VAR: 0.0009252117040846512 F1: 0.7533906592758897 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([73], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7550561973638897 VAR: 0.0008280331930698116 F1: 0.753165940608674 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([74], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.753753013368398 VAR: 0.0009155135912281909 F1: 0.7521943346751937 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([75], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7530838107761185 VAR: 0.0009996136770893354 F1: 0.7516082658162448 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([76], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7563750352211891 VAR: 0.000691295091667895 F1: 0.7548986705902268 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([77], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7504578754578753 VAR: 0.0007016201786668006 F1: 0.7486796017546861 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([78], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7544026486334179 VAR: 0.0008412059599284608 F1: 0.7527454346528084 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([79], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7530877242415704 VAR: 0.0007087860437666455 F1: 0.7515596948762646 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([80], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7478201997432766 VAR: 0.0007322768832571774 F1: 0.7459862741495464 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([81], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7484776619392003 VAR: 0.0007172045094127398 F1: 0.7467868160084514 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([82], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7517806267806267 VAR: 0.0006201098032371082 F1: 0.750041841340226 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([83], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7504578754578755 VAR: 0.0007647941410431387 F1: 0.7488477623766663 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([84], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7517845402460788 VAR: 0.0006649737559853086 F1: 0.7502196062833961 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([85], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7517727998497229 VAR: 0.0006957257211933511 F1: 0.7504872651009489 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([86], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7478241132087285 VAR: 0.000621280773704233 F1: 0.7460735553261197 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([87], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7471783914091605 VAR: 0.0007845473949745531 F1: 0.7456363570524633 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([88], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7471666510128049 VAR: 0.0004870117294948661 F1: 0.7453377874840853 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([89], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7517767133151748 VAR: 0.0006928841061574976 F1: 0.7501049472248301 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([90], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.753749099902946 VAR: 0.0006149265842016662 F1: 0.7522228550243728 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([91], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.751123164584703 VAR: 0.0007321495219554859 F1: 0.749478757742017 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([92], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7563789486866409 VAR: 0.0008431936906431955 F1: 0.7550274617723058 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([93], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7445328887636581 VAR: 0.0009510266269724212 F1: 0.7430272609446019 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([94], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7530916377070223 VAR: 0.0007829041952654493 F1: 0.7514007200849545 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([95], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7550601108293417 VAR: 0.0007863556926673305 F1: 0.7532667463481415 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([96], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7577017000093922 VAR: 0.0008169736804021664 F1: 0.7561884760885068 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([97], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7563789486866411 VAR: 0.0009209998676755903 F1: 0.7548694904637941 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([98], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7497808459346921 VAR: 0.0012456469499864406 F1: 0.7479477359476279 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([99], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.7603393757239911 VAR: 0.0007868877737571947 F1: 0.7586553177337382 SEED: 27966
TrainShape:(1182, 869) #EPOCH: ([100], 200, bert, 0.0001, 256, 0.5, 32) AVG: 0.748489402335556 VAR: 0.0006319726906572117 F1: 0.7469578288466692 SEED: 27966
TrainShape:(1182, 870) #EPOCH: ([], 200, bert, 0.0005, 256, 0.5, 32) AVG: 0.7576938730784885 VAR: 0.0011328595119954434 F1: 0.7565905027888475 SEED: 27966
TrainShape:(1182, 837) #EPOCH: ([], 200, bert, 0.0005, 256, 0.5, 32) AVG: 0.7517845402460787 VAR: 0.0006316216353713372 F1: 0.7495019747721474 SEED: 27966
TrainShape:(1182, 837) #EPOCH: ([], 200, bert, 0.0005, 256, 0.5, 32) AVG: 0.7517845402460787 VAR: 0.0006316216353713372 F1: 0.7495019747721474 SEED: 27966