ChrisGeishauser
commited on
Commit
•
9008d50
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Parent(s):
43fdfbe
Upload 3 files
Browse files- .gitattributes +1 -0
- config_saved.json +1 -0
- supervised.pol.mdl +3 -0
- train_INFO.log +345 -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": 0, "eval_freq": 2, "dataset_name": "multiwoz21", "model_path": "experiments/seed0/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": 0.01, "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 sha256:167f64fd660907849c157f0423778600b6613ce4c6fc98247484c0e279b36206
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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: 0
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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: 1.0% 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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Loaded model from experiments/seed0/save/supervised.pol.mdl
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Start training
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Epoch: 0
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Average actions: 1.9973957538604736
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Average target actions: 2.5520834922790527
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+
Precision: 0.09615384615384616
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Recall: 0.07462686567164178
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F1: 0.08403361344537816
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+
<<dialog policy>> epoch 0: saved network to mdl
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Best Precision: 0.09615384615384616
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Best Recall: 0.07462686567164178
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Best F1: 0.08403361344537816
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Epoch: 1
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Precision: 0.09615384615384616
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Recall: 0.07462686567164178
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F1: 0.08403361344537816
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+
Best Precision: 0.09615384615384616
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Best Recall: 0.07462686567164178
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+
Best F1: 0.08403361344537816
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Epoch: 2
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Average actions: 2.3515625
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Average target actions: 2.6197917461395264
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Precision: 0.10526315789473684
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Recall: 0.08955223880597014
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F1: 0.0967741935483871
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+
<<dialog policy>> epoch 2: saved network to mdl
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Best Precision: 0.10526315789473684
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Best Recall: 0.08955223880597014
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+
Best F1: 0.0967741935483871
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Epoch: 3
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Precision: 0.10526315789473684
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Recall: 0.08955223880597014
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F1: 0.0967741935483871
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+
Best Precision: 0.10526315789473684
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+
Best Recall: 0.08955223880597014
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+
Best F1: 0.0967741935483871
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Epoch: 4
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Average actions: 1.6770832538604736
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Average target actions: 2.8567709922790527
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Precision: 0.1347517730496454
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Recall: 0.0945273631840796
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F1: 0.11111111111111112
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+
<<dialog policy>> epoch 4: saved network to mdl
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Best Precision: 0.1347517730496454
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Best Recall: 0.0945273631840796
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+
Best F1: 0.11111111111111112
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Epoch: 5
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Precision: 0.1347517730496454
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Recall: 0.0945273631840796
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F1: 0.11111111111111112
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+
Best Precision: 0.1347517730496454
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Best Recall: 0.0945273631840796
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Best F1: 0.11111111111111112
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Epoch: 6
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Average actions: 1.9088542461395264
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Average target actions: 2.7213542461395264
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Precision: 0.12080536912751678
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Recall: 0.08955223880597014
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F1: 0.10285714285714286
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Best Precision: 0.1347517730496454
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Best Recall: 0.0945273631840796
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Best F1: 0.11111111111111112
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Epoch: 7
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Precision: 0.12080536912751678
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Recall: 0.08955223880597014
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F1: 0.10285714285714286
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Best Precision: 0.1347517730496454
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Best Recall: 0.0945273631840796
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Best F1: 0.11111111111111112
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Epoch: 8
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Average actions: 2.0572915077209473
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Average target actions: 2.8229167461395264
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Precision: 0.12903225806451613
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Recall: 0.09950248756218906
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F1: 0.11235955056179776
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<<dialog policy>> epoch 8: saved network to mdl
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Best Precision: 0.1347517730496454
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Best Recall: 0.09950248756218906
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Best F1: 0.11235955056179776
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Epoch: 9
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Precision: 0.12903225806451613
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Recall: 0.09950248756218906
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F1: 0.11235955056179776
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Best Precision: 0.1347517730496454
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Best Recall: 0.09950248756218906
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Best F1: 0.11235955056179776
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Epoch: 10
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Average actions: 2.0911459922790527
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Average target actions: 2.6875
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Precision: 0.11612903225806452
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Recall: 0.08955223880597014
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F1: 0.10112359550561797
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Best Precision: 0.1347517730496454
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Best Recall: 0.09950248756218906
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Best F1: 0.11235955056179776
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Epoch: 11
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Precision: 0.11612903225806452
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Recall: 0.08955223880597014
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F1: 0.10112359550561797
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Best Precision: 0.1347517730496454
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Best Recall: 0.09950248756218906
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Best F1: 0.11235955056179776
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Epoch: 12
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Average actions: 2.0833332538604736
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Average target actions: 2.5859375
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Precision: 0.11976047904191617
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Recall: 0.09950248756218906
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F1: 0.10869565217391305
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Best Precision: 0.1347517730496454
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Best Recall: 0.09950248756218906
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Best F1: 0.11235955056179776
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Epoch: 13
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Precision: 0.11976047904191617
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Recall: 0.09950248756218906
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F1: 0.10869565217391305
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Best Precision: 0.1347517730496454
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Best Recall: 0.09950248756218906
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Best F1: 0.11235955056179776
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Epoch: 14
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Average actions: 2.1119790077209473
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Average target actions: 2.7213542461395264
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Precision: 0.16778523489932887
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Recall: 0.12437810945273632
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F1: 0.14285714285714285
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<<dialog policy>> epoch 14: saved network to mdl
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Best Precision: 0.16778523489932887
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Best Recall: 0.12437810945273632
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Best F1: 0.14285714285714285
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Epoch: 15
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Precision: 0.16778523489932887
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Recall: 0.12437810945273632
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F1: 0.14285714285714285
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Best Precision: 0.16778523489932887
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Best Recall: 0.12437810945273632
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Best F1: 0.14285714285714285
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Epoch: 16
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Average actions: 1.7994792461395264
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Average target actions: 2.5520834922790527
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Precision: 0.10135135135135136
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Recall: 0.07462686567164178
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F1: 0.08595988538681948
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Best Precision: 0.16778523489932887
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Best Recall: 0.12437810945273632
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Best F1: 0.14285714285714285
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Epoch: 17
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Precision: 0.10135135135135136
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Recall: 0.07462686567164178
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F1: 0.08595988538681948
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Best Precision: 0.16778523489932887
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Best Recall: 0.12437810945273632
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Best F1: 0.14285714285714285
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Epoch: 18
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Average actions: 2.0572915077209473
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Average target actions: 2.7552084922790527
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Precision: 0.13548387096774195
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Recall: 0.1044776119402985
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F1: 0.11797752808988765
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Best Precision: 0.16778523489932887
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Best Recall: 0.12437810945273632
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Best F1: 0.14285714285714285
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Epoch: 19
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Precision: 0.13548387096774195
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Recall: 0.1044776119402985
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F1: 0.11797752808988765
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Best Precision: 0.16778523489932887
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Best Recall: 0.12437810945273632
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Best F1: 0.14285714285714285
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Epoch: 20
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Average actions: 1.9661457538604736
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Average target actions: 2.7213542461395264
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Precision: 0.1118421052631579
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Recall: 0.0845771144278607
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F1: 0.0963172804532578
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Best Precision: 0.16778523489932887
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Best Recall: 0.12437810945273632
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Best F1: 0.14285714285714285
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Epoch: 21
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Precision: 0.1118421052631579
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Recall: 0.0845771144278607
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F1: 0.0963172804532578
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Best Precision: 0.16778523489932887
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Best Recall: 0.12437810945273632
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Best F1: 0.14285714285714285
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Epoch: 22
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Average actions: 1.9557292461395264
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Average target actions: 2.5520834922790527
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Precision: 0.07741935483870968
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Recall: 0.05970149253731343
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F1: 0.06741573033707865
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Best Precision: 0.16778523489932887
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Best Recall: 0.12437810945273632
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Best F1: 0.14285714285714285
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Epoch: 23
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Precision: 0.07741935483870968
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Recall: 0.05970149253731343
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F1: 0.06741573033707865
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Best Precision: 0.16778523489932887
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Best Recall: 0.12437810945273632
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Best F1: 0.14285714285714285
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Epoch: 24
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Average actions: 2.0833334922790527
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Average target actions: 2.8229167461395264
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Precision: 0.09090909090909091
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Recall: 0.06965174129353234
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F1: 0.07887323943661972
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Best Precision: 0.16778523489932887
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Best Recall: 0.12437810945273632
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Best F1: 0.14285714285714285
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Epoch: 25
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Precision: 0.09090909090909091
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Recall: 0.06965174129353234
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F1: 0.07887323943661972
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Best Precision: 0.16778523489932887
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Best Recall: 0.12437810945273632
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Best F1: 0.14285714285714285
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Epoch: 26
|
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Average actions: 1.7135417461395264
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Average target actions: 2.6197917461395264
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Precision: 0.145985401459854
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Recall: 0.09950248756218906
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F1: 0.1183431952662722
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Best Precision: 0.16778523489932887
|
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Best Recall: 0.12437810945273632
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Best F1: 0.14285714285714285
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Epoch: 27
|
243 |
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Precision: 0.145985401459854
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Recall: 0.09950248756218906
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F1: 0.1183431952662722
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Best Precision: 0.16778523489932887
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Best Recall: 0.12437810945273632
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Best F1: 0.14285714285714285
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Epoch: 28
|
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Average actions: 2.0364584922790527
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Average target actions: 2.5520834922790527
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Precision: 0.16891891891891891
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Recall: 0.12437810945273632
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F1: 0.14326647564469916
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<<dialog policy>> epoch 28: saved network to mdl
|
256 |
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Best Precision: 0.16891891891891891
|
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Best Recall: 0.12437810945273632
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Best F1: 0.14326647564469916
|
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Epoch: 29
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Precision: 0.16891891891891891
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Recall: 0.12437810945273632
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F1: 0.14326647564469916
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Best Precision: 0.16891891891891891
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Best Recall: 0.12437810945273632
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Best F1: 0.14326647564469916
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Epoch: 30
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Average actions: 2.0026040077209473
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Average target actions: 2.3828125
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Precision: 0.16216216216216217
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Recall: 0.11940298507462686
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F1: 0.13753581661891118
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Best Precision: 0.16891891891891891
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Best Recall: 0.12437810945273632
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Best F1: 0.14326647564469916
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Epoch: 31
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Precision: 0.16216216216216217
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Recall: 0.11940298507462686
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F1: 0.13753581661891118
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Best Precision: 0.16891891891891891
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Best Recall: 0.12437810945273632
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Best F1: 0.14326647564469916
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Epoch: 32
|
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Average actions: 1.8046875
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Average target actions: 2.6875
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Precision: 0.12142857142857143
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Recall: 0.0845771144278607
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F1: 0.09970674486803519
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Best Precision: 0.16891891891891891
|
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Best Recall: 0.12437810945273632
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Best F1: 0.14326647564469916
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Epoch: 33
|
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Precision: 0.12142857142857143
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Recall: 0.0845771144278607
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F1: 0.09970674486803519
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Best Precision: 0.16891891891891891
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Best Recall: 0.12437810945273632
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Best F1: 0.14326647564469916
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Epoch: 34
|
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Average actions: 1.9348957538604736
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Average target actions: 2.6875
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Precision: 0.12162162162162163
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Recall: 0.08955223880597014
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F1: 0.10315186246418337
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Best Precision: 0.16891891891891891
|
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Best Recall: 0.12437810945273632
|
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Best F1: 0.14326647564469916
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Epoch: 35
|
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Precision: 0.12162162162162163
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Recall: 0.08955223880597014
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F1: 0.10315186246418337
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Best Precision: 0.16891891891891891
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Best Recall: 0.12437810945273632
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Best F1: 0.14326647564469916
|
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Epoch: 36
|
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Average actions: 2.0989584922790527
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Average target actions: 2.484375
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Precision: 0.14743589743589744
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Recall: 0.11442786069651742
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F1: 0.1288515406162465
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Best Precision: 0.16891891891891891
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Best Recall: 0.12437810945273632
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Best F1: 0.14326647564469916
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Epoch: 37
|
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Precision: 0.14743589743589744
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Recall: 0.11442786069651742
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F1: 0.1288515406162465
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Best Precision: 0.16891891891891891
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Best Recall: 0.12437810945273632
|
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Best F1: 0.14326647564469916
|
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Epoch: 38
|
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Average actions: 2.0260415077209473
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Average target actions: 2.5520834922790527
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Precision: 0.1456953642384106
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Recall: 0.10945273631840796
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F1: 0.12499999999999997
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Best Precision: 0.16891891891891891
|
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Best Recall: 0.12437810945273632
|
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Best F1: 0.14326647564469916
|
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Epoch: 39
|
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Precision: 0.1456953642384106
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Recall: 0.10945273631840796
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F1: 0.12499999999999997
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Best Precision: 0.16891891891891891
|
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Best Recall: 0.12437810945273632
|
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Best F1: 0.14326647564469916
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