train_INFO.log

Visible device: cuda
Seed used: 0
Vectorizer: Data set used is multiwoz21
Start training
Epoch: 0
Precision: 0
Recall: 0
F1: 0
Best Precision: 0.0
Best Recall: 0.0
Best F1: 0.0
Epoch: 1
Precision: 0
Recall: 0
F1: 0
Best Precision: 0.0
Best Recall: 0.0
Best F1: 0.0
Epoch: 2
Average actions: 3.803938627243042
Average target actions: 2.6072394847869873
Precision: 0.36443668246783334
Recall: 0.5317489209007229
F1: 0.43247472824937616
<<dialog policy>> epoch 2: saved network to mdl
Best Precision: 0.36443668246783334
Best Recall: 0.5317489209007229
Best F1: 0.43247472824937616
Epoch: 3
Precision: 0.36443668246783334
Recall: 0.5317489209007229
F1: 0.43247472824937616
Best Precision: 0.36443668246783334
Best Recall: 0.5317489209007229
Best F1: 0.43247472824937616
Epoch: 4
Average actions: 4.113307952880859
Average target actions: 2.6075873374938965
Precision: 0.3832530835696854
Recall: 0.6043475999791981
F1: 0.46905208774797685
<<dialog policy>> epoch 4: saved network to mdl
Best Precision: 0.3832530835696854
Best Recall: 0.6043475999791981
Best F1: 0.46905208774797685
Epoch: 5
Precision: 0.3832530835696854
Recall: 0.6043475999791981
F1: 0.46905208774797685
Best Precision: 0.3832530835696854
Best Recall: 0.6043475999791981
Best F1: 0.46905208774797685
Epoch: 6
Average actions: 4.202342510223389
Average target actions: 2.6075873374938965
Precision: 0.3931234866828087
Recall: 0.6332622601279317
F1: 0.4851007887817704
<<dialog policy>> epoch 6: saved network to mdl
Best Precision: 0.3931234866828087
Best Recall: 0.6332622601279317
Best F1: 0.4851007887817704
Epoch: 7
Precision: 0.3931234866828087
Recall: 0.6332622601279317
F1: 0.4851007887817704
Best Precision: 0.3931234866828087
Best Recall: 0.6332622601279317
Best F1: 0.4851007887817704
Epoch: 8
Average actions: 4.356949806213379
Average target actions: 2.6075873374938965
Precision: 0.3951788491446345
Recall: 0.6607207863123408
F1: 0.4945600342552405
<<dialog policy>> epoch 8: saved network to mdl
Best Precision: 0.3951788491446345
Best Recall: 0.6607207863123408
Best F1: 0.4945600342552405
Epoch: 9
Precision: 0.3951788491446345
Recall: 0.6607207863123408
F1: 0.4945600342552405
Best Precision: 0.3951788491446345
Best Recall: 0.6607207863123408
Best F1: 0.4945600342552405
Epoch: 10
Average actions: 4.292381763458252
Average target actions: 2.6075873374938965
Precision: 0.4069264069264069
Recall: 0.6697176140204899
F1: 0.5062504913908326
<<dialog policy>> epoch 10: saved network to mdl
Best Precision: 0.4069264069264069
Best Recall: 0.6697176140204899
Best F1: 0.5062504913908326
Epoch: 11
Precision: 0.4069264069264069
Recall: 0.6697176140204899
F1: 0.5062504913908326
Best Precision: 0.4069264069264069
Best Recall: 0.6697176140204899
Best F1: 0.5062504913908326
Epoch: 12
Average actions: 4.411757946014404
Average target actions: 2.608457088470459
Precision: 0.4065842862412394
Recall: 0.6878672837901086
F1: 0.5110797704835687
<<dialog policy>> epoch 12: saved network to mdl
Best Precision: 0.4069264069264069
Best Recall: 0.6878672837901086
Best F1: 0.5110797704835687
Epoch: 13
Precision: 0.4065842862412394
Recall: 0.6878672837901086
F1: 0.5110797704835687
Best Precision: 0.4069264069264069
Best Recall: 0.6878672837901086
Best F1: 0.5110797704835687
Epoch: 14
Average actions: 4.343286514282227
Average target actions: 2.608804702758789
Precision: 0.4146211979264256
Recall: 0.6904675230121171
F1: 0.5181167196737625
<<dialog policy>> epoch 14: saved network to mdl
Best Precision: 0.4146211979264256
Best Recall: 0.6904675230121171
Best F1: 0.5181167196737625
Epoch: 15
Precision: 0.4146211979264256
Recall: 0.6904675230121171
F1: 0.5181167196737625
Best Precision: 0.4146211979264256
Best Recall: 0.6904675230121171
Best F1: 0.5181167196737625
Epoch: 16
Average actions: 4.276244640350342
Average target actions: 2.608457088470459
Precision: 0.4216435662406039
Recall: 0.6913516043476
F1: 0.5238189053942235
<<dialog policy>> epoch 16: saved network to mdl
Best Precision: 0.4216435662406039
Best Recall: 0.6913516043476
Best F1: 0.5238189053942235
Epoch: 17
Precision: 0.4216435662406039
Recall: 0.6913516043476
F1: 0.5238189053942235
Best Precision: 0.4216435662406039
Best Recall: 0.6913516043476
Best F1: 0.5238189053942235
Epoch: 18
Average actions: 4.305194854736328
Average target actions: 2.6089789867401123
Precision: 0.4217372134038801
Recall: 0.6963960684382964
F1: 0.5253329671838528
<<dialog policy>> epoch 18: saved network to mdl
Best Precision: 0.4217372134038801
Best Recall: 0.6963960684382964
Best F1: 0.5253329671838528
Epoch: 19
Precision: 0.4217372134038801
Recall: 0.6963960684382964
F1: 0.5253329671838528
Best Precision: 0.4217372134038801
Best Recall: 0.6963960684382964
Best F1: 0.5253329671838528
Epoch: 20
Average actions: 4.321138858795166
Average target actions: 2.6060221195220947
Precision: 0.42330383480825956
Recall: 0.7014925373134329
F1: 0.5279968685781387
<<dialog policy>> epoch 20: saved network to mdl
Best Precision: 0.42330383480825956
Best Recall: 0.7014925373134329
Best F1: 0.5279968685781387
Epoch: 21
Precision: 0.42330383480825956
Recall: 0.7014925373134329
F1: 0.5279968685781387
Best Precision: 0.42330383480825956
Best Recall: 0.7014925373134329
Best F1: 0.5279968685781387
Epoch: 22
Average actions: 4.332869529724121
Average target actions: 2.6077613830566406
Precision: 0.42460478948192204
Recall: 0.7053928961464455
F1: 0.5301129479813969
<<dialog policy>> epoch 22: saved network to mdl
Best Precision: 0.42460478948192204
Best Recall: 0.7053928961464455
Best F1: 0.5301129479813969
Epoch: 23
Precision: 0.42460478948192204
Recall: 0.7053928961464455
F1: 0.5301129479813969
Best Precision: 0.42460478948192204
Best Recall: 0.7053928961464455
Best F1: 0.5301129479813969