Commit
·
2285042
1
Parent(s):
9b9ce11
Upload 3 files
Browse files- .gitattributes +1 -0
- config_saved.json +1 -0
- supervised.pol.mdl +3 -0
- train_INFO.log +351 -0
.gitattributes
CHANGED
@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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supervised.pol.mdl filter=lfs diff=lfs merge=lfs -text
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config_saved.json
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{"args": {"seed": 1, "eval_freq": 2, "dataset_name": "multiwoz21", "model_path": "NO/seed1/save/supervised.pol.mdl"}, "config": {"batchsz": 64, "epoch": 40, "gamma": 0.99, "policy_lr": 5e-06, "supervised_lr": 1e-05, "entropy_weight": 0.01, "value_lr": 0.0001, "save_dir": "save", "log_dir": "log", "save_per_epoch": 5000, "hidden_size": 256, "load": "save/best", "logging_mode": "INFO", "use_cer": true, "memory_size": 5000, "behaviour_cloning_weight": 0.1, "supervised_weight": 0.0, "online_offline_ratio": 0.2, "smoothed_value_function": false, "use_reservoir_sampling": false, "seed": 0, "lambda": 1, "tau": 0.001, "policy_freq": 1, "print_per_batch": 400, "c": 1.0, "rho_bar": 1, "max_length": 10, "noisy_linear": false, "dataset_name": "multiwoz21", "data_percentage": 1.0, "dialogue_order": 0, "multiwoz_like": false, "regularization_weight": 0.0, "enc_input_dim": 128, "enc_nhead": 2, "enc_d_hid": 128, "enc_nlayers": 4, "enc_dropout": 0.1, "dec_input_dim": 128, "dec_nhead": 2, "dec_d_hid": 128, "dec_nlayers": 2, "dec_dropout": 0.0, "action_embedding_dim": 128, "domain_embedding_dim": 64, "value_embedding_dim": 12, "node_embedding_dim": 128, "roberta_path": "", "node_attention": true, "semantic_descriptions": true, "freeze_roberta": true, "use_pooled": false, "mean": true, "roberta_actions": true, "independent_descriptions": true, "random_matrix": false, "distance_metric": false, "verbose": false, "ignore_features": [], "domains_removed": ["hospital", "police", "train", "hotel", "attraction", "taxi"], "only_active_values": false, "permuted_data": false, "need_weights": false, "cls_dim": 128, "independent": true, "old_critic": false, "pos_weight": 5, "weight_decay": 1e-05}, "policy_config": null}
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supervised.pol.mdl
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:847929fde204d26f279c7002ad7b8eb1108df943c24e207cd5bf01d2892f55ed
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size 9331458
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train_INFO.log
ADDED
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+
Visible device: cuda
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Seed used: 1
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Batch size: 64
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Epochs: 40
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Learning rate: 1e-05
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Entropy weight: 0.01
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Regularization weight: 0.0
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Only use multiwoz like domains: False
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We use: 100.0% of the data
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Dialogue order used: 0
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Vectorizer: Data set used is multiwoz21
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We filter state by active domains: True
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Vectorizer: Data set used is multiwoz21
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Embedding semantic descriptions: True
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Embedded descriptions successfully. Size: torch.Size([338, 768])
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Data set used for descriptions: multiwoz21
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We use Roberta to embed actions.
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Didnt load a model
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Start training
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Epoch: 0
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Average actions: 1.957058072090149
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Average target actions: 2.669339895248413
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+
Precision: 0.13822525597269625
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Recall: 0.10146667362597213
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F1: 0.11702736056346508
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+
<<dialog policy>> epoch 0: saved network to mdl
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Best Precision: 0.13822525597269625
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Best Recall: 0.10146667362597213
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Best F1: 0.11702736056346508
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Epoch: 1
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Precision: 0.13822525597269625
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Recall: 0.10146667362597213
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F1: 0.11702736056346508
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Best Precision: 0.13822525597269625
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+
Best Recall: 0.10146667362597213
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+
Best F1: 0.11702736056346508
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Epoch: 2
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Average actions: 2.0794308185577393
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Average target actions: 2.6675729751586914
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Precision: 0.22303363258743134
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Recall: 0.1737564591053813
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F1: 0.19533519143318176
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+
<<dialog policy>> epoch 2: saved network to mdl
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Best Precision: 0.22303363258743134
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Best Recall: 0.1737564591053813
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+
Best F1: 0.19533519143318176
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Epoch: 3
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Precision: 0.22303363258743134
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Recall: 0.1737564591053813
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F1: 0.19533519143318176
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+
Best Precision: 0.22303363258743134
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Best Recall: 0.1737564591053813
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Best F1: 0.19533519143318176
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Epoch: 4
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Average actions: 2.0110926628112793
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Average target actions: 2.665806293487549
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Precision: 0.26409084614319345
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Recall: 0.19907093272091445
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F1: 0.22701705306389688
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<<dialog policy>> epoch 4: saved network to mdl
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Best Precision: 0.26409084614319345
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Best Recall: 0.19907093272091445
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Best F1: 0.22701705306389688
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Epoch: 5
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Precision: 0.26409084614319345
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Recall: 0.19907093272091445
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F1: 0.22701705306389688
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Best Precision: 0.26409084614319345
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Best Recall: 0.19907093272091445
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Best F1: 0.22701705306389688
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Epoch: 6
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Average actions: 1.9673057794570923
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Average target actions: 2.667219877243042
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Precision: 0.2910210146465719
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Recall: 0.21467717521791324
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F1: 0.2470863871200288
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<<dialog policy>> epoch 6: saved network to mdl
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Best Precision: 0.2910210146465719
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Best Recall: 0.21467717521791324
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Best F1: 0.2470863871200288
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Epoch: 7
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Precision: 0.2910210146465719
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Recall: 0.21467717521791324
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F1: 0.2470863871200288
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Best Precision: 0.2910210146465719
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Best Recall: 0.21467717521791324
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Best F1: 0.2470863871200288
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Epoch: 8
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Average actions: 1.8258512020111084
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Average target actions: 2.667926549911499
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Precision: 0.30450038138825325
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Recall: 0.20836160551176994
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F1: 0.24742012457776819
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<<dialog policy>> epoch 8: saved network to mdl
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Best Precision: 0.30450038138825325
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Best Recall: 0.21467717521791324
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Best F1: 0.24742012457776819
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Epoch: 9
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Precision: 0.30450038138825325
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Recall: 0.20836160551176994
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F1: 0.24742012457776819
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Best Precision: 0.30450038138825325
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Best Recall: 0.21467717521791324
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Best F1: 0.24742012457776819
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Epoch: 10
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Average actions: 1.7796674966812134
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Average target actions: 2.66333270072937
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Precision: 0.3297132588483475
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Recall: 0.2202620178506185
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F1: 0.2640966268227048
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<<dialog policy>> epoch 10: saved network to mdl
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Best Precision: 0.3297132588483475
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Best Recall: 0.2202620178506185
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Best F1: 0.2640966268227048
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Epoch: 11
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Precision: 0.3297132588483475
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Recall: 0.2202620178506185
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F1: 0.2640966268227048
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Best Precision: 0.3297132588483475
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Best Recall: 0.2202620178506185
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Best F1: 0.2640966268227048
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Epoch: 12
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Average actions: 1.8398014307022095
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Average target actions: 2.67004656791687
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Precision: 0.34064769975786924
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Recall: 0.23498094890129964
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F1: 0.27811583011583013
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<<dialog policy>> epoch 12: saved network to mdl
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Best Precision: 0.34064769975786924
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Best Recall: 0.23498094890129964
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Best F1: 0.27811583011583013
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Epoch: 13
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Precision: 0.34064769975786924
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Recall: 0.23498094890129964
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F1: 0.27811583011583013
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Best Precision: 0.34064769975786924
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Best Recall: 0.23498094890129964
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Best F1: 0.27811583011583013
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Epoch: 14
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Average actions: 1.7070426940917969
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Average target actions: 2.667219877243042
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Precision: 0.35462034091835903
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Recall: 0.22694295109348087
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F1: 0.2767663908338638
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Best Precision: 0.35462034091835903
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Best Recall: 0.23498094890129964
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Best F1: 0.27811583011583013
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Epoch: 15
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Precision: 0.35462034091835903
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Recall: 0.22694295109348087
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F1: 0.2767663908338638
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Best Precision: 0.35462034091835903
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Best Recall: 0.23498094890129964
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Best F1: 0.27811583011583013
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Epoch: 16
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Average actions: 1.6812468767166138
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Average target actions: 2.6643927097320557
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Precision: 0.34859650575474044
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Recall: 0.21974006994101988
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F1: 0.2695607632219234
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Best Precision: 0.35462034091835903
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Best Recall: 0.23498094890129964
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Best F1: 0.27811583011583013
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Epoch: 17
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Precision: 0.34859650575474044
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Recall: 0.21974006994101988
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F1: 0.2695607632219234
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Best Precision: 0.35462034091835903
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Best Recall: 0.23498094890129964
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Best F1: 0.27811583011583013
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Epoch: 18
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Average actions: 1.675270438194275
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Average target actions: 2.6640396118164062
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Precision: 0.35976419794088343
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Recall: 0.22616002922908293
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F1: 0.27772970547703746
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Best Precision: 0.35976419794088343
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Best Recall: 0.23498094890129964
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Best F1: 0.27811583011583013
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Epoch: 19
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Precision: 0.35976419794088343
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Recall: 0.22616002922908293
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F1: 0.27772970547703746
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Best Precision: 0.35976419794088343
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Best Recall: 0.23498094890129964
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Best F1: 0.27811583011583013
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Epoch: 20
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Average actions: 1.5666790008544922
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Average target actions: 2.6647462844848633
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Precision: 0.3769442716203004
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Recall: 0.2213581084607756
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F1: 0.27892140743176586
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<<dialog policy>> epoch 20: saved network to mdl
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Best Precision: 0.3769442716203004
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Best Recall: 0.23498094890129964
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Best F1: 0.27892140743176586
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Epoch: 21
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Precision: 0.3769442716203004
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Recall: 0.2213581084607756
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F1: 0.27892140743176586
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Best Precision: 0.3769442716203004
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Best Recall: 0.23498094890129964
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Best F1: 0.27892140743176586
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Epoch: 22
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Average actions: 1.6693706512451172
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Average target actions: 2.6661596298217773
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Precision: 0.3716379382130069
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Recall: 0.23294535205386502
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F1: 0.2863834702258727
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<<dialog policy>> epoch 22: saved network to mdl
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Best Precision: 0.3769442716203004
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Best Recall: 0.23498094890129964
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Best F1: 0.2863834702258727
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Epoch: 23
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Precision: 0.3716379382130069
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Recall: 0.23294535205386502
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F1: 0.2863834702258727
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+
Best Precision: 0.3769442716203004
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+
Best Recall: 0.23498094890129964
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Best F1: 0.2863834702258727
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+
Epoch: 24
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+
Average actions: 1.6701388359069824
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Average target actions: 2.6643927097320557
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Precision: 0.3714618714618715
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Recall: 0.23289315726290516
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F1: 0.2862917455327067
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Best Precision: 0.3769442716203004
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+
Best Recall: 0.23498094890129964
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Best F1: 0.2863834702258727
|
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Epoch: 25
|
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+
Precision: 0.3714618714618715
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Recall: 0.23289315726290516
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F1: 0.2862917455327067
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+
Best Precision: 0.3769442716203004
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+
Best Recall: 0.23498094890129964
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+
Best F1: 0.2863834702258727
|
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+
Epoch: 26
|
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Average actions: 1.6909722089767456
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Average target actions: 2.665099620819092
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Precision: 0.3781160016454134
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Recall: 0.2398872592515267
|
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F1: 0.2935428242958421
|
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+
<<dialog policy>> epoch 26: saved network to mdl
|
244 |
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Best Precision: 0.3781160016454134
|
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+
Best Recall: 0.2398872592515267
|
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+
Best F1: 0.2935428242958421
|
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+
Epoch: 27
|
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Precision: 0.3781160016454134
|
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Recall: 0.2398872592515267
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F1: 0.2935428242958421
|
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+
Best Precision: 0.3781160016454134
|
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+
Best Recall: 0.2398872592515267
|
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Best F1: 0.2935428242958421
|
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+
Epoch: 28
|
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+
Average actions: 1.8047566413879395
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Average target actions: 2.6643927097320557
|
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Precision: 0.3654779326811985
|
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+
Recall: 0.24766428310454616
|
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F1: 0.29525231783958683
|
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+
<<dialog policy>> epoch 28: saved network to mdl
|
261 |
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Best Precision: 0.3781160016454134
|
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+
Best Recall: 0.24766428310454616
|
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+
Best F1: 0.29525231783958683
|
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Epoch: 29
|
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Precision: 0.3654779326811985
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Recall: 0.24766428310454616
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F1: 0.29525231783958683
|
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Best Precision: 0.3781160016454134
|
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Best Recall: 0.24766428310454616
|
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Best F1: 0.29525231783958683
|
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+
Epoch: 30
|
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Average actions: 1.680601716041565
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Average target actions: 2.6640396118164062
|
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Precision: 0.37665562913907286
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Recall: 0.23748629886737305
|
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F1: 0.2913025384935497
|
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Best Precision: 0.3781160016454134
|
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Best Recall: 0.24766428310454616
|
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Best F1: 0.29525231783958683
|
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Epoch: 31
|
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Precision: 0.37665562913907286
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Recall: 0.23748629886737305
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F1: 0.2913025384935497
|
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Best Precision: 0.3781160016454134
|
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Best Recall: 0.24766428310454616
|
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Best F1: 0.29525231783958683
|
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+
Epoch: 32
|
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Average actions: 1.7778853178024292
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Average target actions: 2.667219877243042
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Precision: 0.3660120491354354
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Recall: 0.2441672321102354
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F1: 0.2929242329367564
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Best Precision: 0.3781160016454134
|
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Best Recall: 0.24766428310454616
|
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Best F1: 0.29525231783958683
|
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+
Epoch: 33
|
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Precision: 0.3660120491354354
|
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Recall: 0.2441672321102354
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F1: 0.2929242329367564
|
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Best Precision: 0.3781160016454134
|
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Best Recall: 0.24766428310454616
|
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+
Best F1: 0.29525231783958683
|
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+
Epoch: 34
|
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+
Average actions: 1.726846694946289
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Average target actions: 2.66333270072937
|
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Precision: 0.3723121526938874
|
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Recall: 0.24129651860744297
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F1: 0.29281732961743095
|
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Best Precision: 0.3781160016454134
|
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Best Recall: 0.24766428310454616
|
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Best F1: 0.29525231783958683
|
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+
Epoch: 35
|
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Precision: 0.3723121526938874
|
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Recall: 0.24129651860744297
|
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F1: 0.29281732961743095
|
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Best Precision: 0.3781160016454134
|
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Best Recall: 0.24766428310454616
|
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+
Best F1: 0.29525231783958683
|
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+
Epoch: 36
|
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+
Average actions: 1.8067078590393066
|
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Average target actions: 2.6675729751586914
|
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Precision: 0.37099753694581283
|
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Recall: 0.2515788924265358
|
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F1: 0.29983515287238344
|
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+
<<dialog policy>> epoch 36: saved network to mdl
|
326 |
+
Best Precision: 0.3781160016454134
|
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+
Best Recall: 0.2515788924265358
|
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Best F1: 0.29983515287238344
|
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+
Epoch: 37
|
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Precision: 0.37099753694581283
|
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Recall: 0.2515788924265358
|
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F1: 0.29983515287238344
|
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+
Best Precision: 0.3781160016454134
|
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Best Recall: 0.2515788924265358
|
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Best F1: 0.29983515287238344
|
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+
Epoch: 38
|
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+
Average actions: 1.7964909076690674
|
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Average target actions: 2.6647462844848633
|
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Precision: 0.36536823356307596
|
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Recall: 0.2462550237486299
|
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F1: 0.2942130207034173
|
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+
Best Precision: 0.3781160016454134
|
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+
Best Recall: 0.2515788924265358
|
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+
Best F1: 0.29983515287238344
|
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+
Epoch: 39
|
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+
Precision: 0.36536823356307596
|
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+
Recall: 0.2462550237486299
|
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+
F1: 0.2942130207034173
|
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+
Best Precision: 0.3781160016454134
|
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+
Best Recall: 0.2515788924265358
|
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+
Best F1: 0.29983515287238344
|