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 <> 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 <> 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 <> 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 <> 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 <> 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 <> 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 <> 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 <> 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 <> 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 <> 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 <> 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