ChrisGeishauser
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Delete train_INFO.log
Browse files- train_INFO.log +0 -205
train_INFO.log
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Visible device: cuda
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Seed used: 0
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Vectorizer: Data set used is multiwoz21
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Start training
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Epoch: 0
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Precision: 0
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Recall: 0
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F1: 0
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Best Precision: 0.0
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Best Recall: 0.0
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Best F1: 0.0
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Epoch: 1
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Precision: 0
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Recall: 0
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F1: 0
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Best Precision: 0.0
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Best Recall: 0.0
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Best F1: 0.0
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Epoch: 2
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Average actions: 3.803938627243042
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Average target actions: 2.6072394847869873
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Precision: 0.36443668246783334
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Recall: 0.5317489209007229
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F1: 0.43247472824937616
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<<dialog policy>> epoch 2: saved network to mdl
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Best Precision: 0.36443668246783334
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Best Recall: 0.5317489209007229
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Best F1: 0.43247472824937616
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Epoch: 3
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Precision: 0.36443668246783334
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Recall: 0.5317489209007229
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F1: 0.43247472824937616
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Best Precision: 0.36443668246783334
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Best Recall: 0.5317489209007229
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Best F1: 0.43247472824937616
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Epoch: 4
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Average actions: 4.113307952880859
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Average target actions: 2.6075873374938965
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Precision: 0.3832530835696854
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Recall: 0.6043475999791981
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F1: 0.46905208774797685
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<<dialog policy>> epoch 4: saved network to mdl
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Best Precision: 0.3832530835696854
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Best Recall: 0.6043475999791981
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Best F1: 0.46905208774797685
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Epoch: 5
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Precision: 0.3832530835696854
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Recall: 0.6043475999791981
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F1: 0.46905208774797685
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Best Precision: 0.3832530835696854
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Best Recall: 0.6043475999791981
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Best F1: 0.46905208774797685
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Epoch: 6
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Average actions: 4.202342510223389
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Average target actions: 2.6075873374938965
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Precision: 0.3931234866828087
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Recall: 0.6332622601279317
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F1: 0.4851007887817704
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<<dialog policy>> epoch 6: saved network to mdl
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Best Precision: 0.3931234866828087
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Best Recall: 0.6332622601279317
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Best F1: 0.4851007887817704
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Epoch: 7
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Precision: 0.3931234866828087
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Recall: 0.6332622601279317
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F1: 0.4851007887817704
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Best Precision: 0.3931234866828087
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Best Recall: 0.6332622601279317
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Best F1: 0.4851007887817704
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Epoch: 8
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Average actions: 4.356949806213379
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Average target actions: 2.6075873374938965
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Precision: 0.3951788491446345
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Recall: 0.6607207863123408
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F1: 0.4945600342552405
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<<dialog policy>> epoch 8: saved network to mdl
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Best Precision: 0.3951788491446345
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Best Recall: 0.6607207863123408
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Best F1: 0.4945600342552405
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Epoch: 9
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Precision: 0.3951788491446345
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Recall: 0.6607207863123408
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F1: 0.4945600342552405
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Best Precision: 0.3951788491446345
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Best Recall: 0.6607207863123408
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Best F1: 0.4945600342552405
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Epoch: 10
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Average actions: 4.292381763458252
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Average target actions: 2.6075873374938965
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Precision: 0.4069264069264069
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Recall: 0.6697176140204899
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F1: 0.5062504913908326
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<<dialog policy>> epoch 10: saved network to mdl
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Best Precision: 0.4069264069264069
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Best Recall: 0.6697176140204899
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Best F1: 0.5062504913908326
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Epoch: 11
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Precision: 0.4069264069264069
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Recall: 0.6697176140204899
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F1: 0.5062504913908326
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Best Precision: 0.4069264069264069
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Best Recall: 0.6697176140204899
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Best F1: 0.5062504913908326
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Epoch: 12
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Average actions: 4.411757946014404
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Average target actions: 2.608457088470459
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Precision: 0.4065842862412394
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Recall: 0.6878672837901086
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F1: 0.5110797704835687
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<<dialog policy>> epoch 12: saved network to mdl
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Best Precision: 0.4069264069264069
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Best Recall: 0.6878672837901086
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Best F1: 0.5110797704835687
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Epoch: 13
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Precision: 0.4065842862412394
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Recall: 0.6878672837901086
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F1: 0.5110797704835687
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Best Precision: 0.4069264069264069
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Best Recall: 0.6878672837901086
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Best F1: 0.5110797704835687
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Epoch: 14
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Average actions: 4.343286514282227
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Average target actions: 2.608804702758789
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Precision: 0.4146211979264256
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Recall: 0.6904675230121171
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F1: 0.5181167196737625
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<<dialog policy>> epoch 14: saved network to mdl
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Best Precision: 0.4146211979264256
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Best Recall: 0.6904675230121171
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Best F1: 0.5181167196737625
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Epoch: 15
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Precision: 0.4146211979264256
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Recall: 0.6904675230121171
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F1: 0.5181167196737625
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Best Precision: 0.4146211979264256
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Best Recall: 0.6904675230121171
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Best F1: 0.5181167196737625
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Epoch: 16
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Average actions: 4.276244640350342
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Average target actions: 2.608457088470459
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Precision: 0.4216435662406039
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Recall: 0.6913516043476
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F1: 0.5238189053942235
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<<dialog policy>> epoch 16: saved network to mdl
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Best Precision: 0.4216435662406039
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Best Recall: 0.6913516043476
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Best F1: 0.5238189053942235
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Epoch: 17
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Precision: 0.4216435662406039
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Recall: 0.6913516043476
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F1: 0.5238189053942235
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Best Precision: 0.4216435662406039
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Best Recall: 0.6913516043476
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Best F1: 0.5238189053942235
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Epoch: 18
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Average actions: 4.305194854736328
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Average target actions: 2.6089789867401123
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Precision: 0.4217372134038801
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Recall: 0.6963960684382964
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F1: 0.5253329671838528
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<<dialog policy>> epoch 18: saved network to mdl
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Best Precision: 0.4217372134038801
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Best Recall: 0.6963960684382964
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Best F1: 0.5253329671838528
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Epoch: 19
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Precision: 0.4217372134038801
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Recall: 0.6963960684382964
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F1: 0.5253329671838528
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Best Precision: 0.4217372134038801
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Best Recall: 0.6963960684382964
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Best F1: 0.5253329671838528
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Epoch: 20
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Average actions: 4.321138858795166
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Average target actions: 2.6060221195220947
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Precision: 0.42330383480825956
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Recall: 0.7014925373134329
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F1: 0.5279968685781387
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<<dialog policy>> epoch 20: saved network to mdl
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Best Precision: 0.42330383480825956
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Best Recall: 0.7014925373134329
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Best F1: 0.5279968685781387
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Epoch: 21
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Precision: 0.42330383480825956
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Recall: 0.7014925373134329
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F1: 0.5279968685781387
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Best Precision: 0.42330383480825956
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Best Recall: 0.7014925373134329
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Best F1: 0.5279968685781387
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Epoch: 22
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Average actions: 4.332869529724121
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Average target actions: 2.6077613830566406
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Precision: 0.42460478948192204
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Recall: 0.7053928961464455
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F1: 0.5301129479813969
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<<dialog policy>> epoch 22: saved network to mdl
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Best Precision: 0.42460478948192204
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Best Recall: 0.7053928961464455
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Best F1: 0.5301129479813969
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Epoch: 23
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Precision: 0.42460478948192204
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Recall: 0.7053928961464455
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F1: 0.5301129479813969
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Best Precision: 0.42460478948192204
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Best Recall: 0.7053928961464455
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Best F1: 0.5301129479813969
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