Commit
·
ea585ab
1
Parent(s):
c3ec217
Upload 3 files
Browse files- .gitattributes +1 -0
- config_saved.json +1 -0
- supervised.pol.mdl +3 -0
- train_INFO.log +341 -0
.gitattributes
CHANGED
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@@ -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
ADDED
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{"args": {"seed": 0, "eval_freq": 2, "dataset_name": "multiwoz21", "model_path": "onvlab/policy/vtrace_DPT/supervised/experiments/sgd/save/supervised.pol.mdl"}, "config": {"batchsz": 64, "epoch": 40, "gamma": 0.99, "policy_lr": 5e-05, "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": 2, "print_per_batch": 400, "c": 1.0, "rho_bar": 1, "max_length": 10, "noisy_linear": false, "dataset_name": "multiwoz21", "data_percentage": 0.01, "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 sha256:6992b768e91941f87a8f8275c88e5e3accf998bf4a1f7fbb5eb0bb337bd7fa6f
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size 9331458
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train_INFO.log
ADDED
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@@ -0,0 +1,341 @@
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| 1 |
+
Visible device: cuda
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| 2 |
+
Seed used: 0
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| 3 |
+
Batch size: 64
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| 4 |
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Epochs: 40
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| 5 |
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Learning rate: 1e-05
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| 6 |
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Entropy weight: 0.01
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| 7 |
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Regularization weight: 0.0
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| 8 |
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Only use multiwoz like domains: False
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| 9 |
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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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| 11 |
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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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| 14 |
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Data set used for descriptions: multiwoz21
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| 15 |
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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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| 18 |
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Epoch: 0
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| 19 |
+
Precision: 0
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| 20 |
+
Recall: 0
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| 21 |
+
F1: 0
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| 22 |
+
Best Precision: 0.0
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| 23 |
+
Best Recall: 0.0
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| 24 |
+
Best F1: 0.0
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| 25 |
+
Epoch: 1
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| 26 |
+
Precision: 0
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| 27 |
+
Recall: 0
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| 28 |
+
F1: 0
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| 29 |
+
Best Precision: 0.0
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| 30 |
+
Best Recall: 0.0
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| 31 |
+
Best F1: 0.0
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| 32 |
+
Epoch: 2
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| 33 |
+
Average actions: 2.4348959922790527
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| 34 |
+
Average target actions: 2.28125
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| 35 |
+
Precision: 0.043010752688172046
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| 36 |
+
Recall: 0.0425531914893617
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| 37 |
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F1: 0.04278074866310161
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| 38 |
+
<<dialog policy>> epoch 2: saved network to mdl
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| 39 |
+
Best Precision: 0.043010752688172046
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| 40 |
+
Best Recall: 0.0425531914893617
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| 41 |
+
Best F1: 0.04278074866310161
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| 42 |
+
Epoch: 3
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| 43 |
+
Precision: 0.043010752688172046
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| 44 |
+
Recall: 0.0425531914893617
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| 45 |
+
F1: 0.04278074866310161
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| 46 |
+
Best Precision: 0.043010752688172046
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| 47 |
+
Best Recall: 0.0425531914893617
|
| 48 |
+
Best F1: 0.04278074866310161
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| 49 |
+
Epoch: 4
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| 50 |
+
Average actions: 2.4114584922790527
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| 51 |
+
Average target actions: 2.7890625
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| 52 |
+
Precision: 0.07058823529411765
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| 53 |
+
Recall: 0.06382978723404255
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| 54 |
+
F1: 0.06703910614525138
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| 55 |
+
<<dialog policy>> epoch 4: saved network to mdl
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| 56 |
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Best Precision: 0.07058823529411765
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| 57 |
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Best Recall: 0.06382978723404255
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| 58 |
+
Best F1: 0.06703910614525138
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| 59 |
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Epoch: 5
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| 60 |
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Precision: 0.07058823529411765
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| 61 |
+
Recall: 0.06382978723404255
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| 62 |
+
F1: 0.06703910614525138
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| 63 |
+
Best Precision: 0.07058823529411765
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| 64 |
+
Best Recall: 0.06382978723404255
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| 65 |
+
Best F1: 0.06703910614525138
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| 66 |
+
Epoch: 6
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| 67 |
+
Average actions: 2.1536459922790527
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| 68 |
+
Average target actions: 2.5859375
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| 69 |
+
Precision: 0.049079754601226995
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| 70 |
+
Recall: 0.0425531914893617
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| 71 |
+
F1: 0.045584045584045586
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| 72 |
+
Best Precision: 0.07058823529411765
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| 73 |
+
Best Recall: 0.06382978723404255
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| 74 |
+
Best F1: 0.06703910614525138
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| 75 |
+
Epoch: 7
|
| 76 |
+
Precision: 0.049079754601226995
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| 77 |
+
Recall: 0.0425531914893617
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| 78 |
+
F1: 0.045584045584045586
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| 79 |
+
Best Precision: 0.07058823529411765
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| 80 |
+
Best Recall: 0.06382978723404255
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| 81 |
+
Best F1: 0.06703910614525138
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| 82 |
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Epoch: 8
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| 83 |
+
Average actions: 2.15625
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| 84 |
+
Average target actions: 2.5520834922790527
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| 85 |
+
Precision: 0.07547169811320754
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| 86 |
+
Recall: 0.06382978723404255
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| 87 |
+
F1: 0.06916426512968299
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| 88 |
+
<<dialog policy>> epoch 8: saved network to mdl
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| 89 |
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Best Precision: 0.07547169811320754
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| 90 |
+
Best Recall: 0.06382978723404255
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| 91 |
+
Best F1: 0.06916426512968299
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| 92 |
+
Epoch: 9
|
| 93 |
+
Precision: 0.07547169811320754
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| 94 |
+
Recall: 0.06382978723404255
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| 95 |
+
F1: 0.06916426512968299
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| 96 |
+
Best Precision: 0.07547169811320754
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| 97 |
+
Best Recall: 0.06382978723404255
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| 98 |
+
Best F1: 0.06916426512968299
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| 99 |
+
Epoch: 10
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| 100 |
+
Average actions: 2.0572915077209473
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| 101 |
+
Average target actions: 2.3489584922790527
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| 102 |
+
Precision: 0.04516129032258064
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| 103 |
+
Recall: 0.03723404255319149
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| 104 |
+
F1: 0.04081632653061224
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| 105 |
+
Best Precision: 0.07547169811320754
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| 106 |
+
Best Recall: 0.06382978723404255
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| 107 |
+
Best F1: 0.06916426512968299
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| 108 |
+
Epoch: 11
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| 109 |
+
Precision: 0.04516129032258064
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| 110 |
+
Recall: 0.03723404255319149
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| 111 |
+
F1: 0.04081632653061224
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| 112 |
+
Best Precision: 0.07547169811320754
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| 113 |
+
Best Recall: 0.06382978723404255
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| 114 |
+
Best F1: 0.06916426512968299
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| 115 |
+
Epoch: 12
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| 116 |
+
Average actions: 1.984375
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| 117 |
+
Average target actions: 2.5520834922790527
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| 118 |
+
Precision: 0.08666666666666667
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| 119 |
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Recall: 0.06914893617021277
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| 120 |
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F1: 0.07692307692307691
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| 121 |
+
<<dialog policy>> epoch 12: saved network to mdl
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| 122 |
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Best Precision: 0.08666666666666667
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| 123 |
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Best Recall: 0.06914893617021277
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| 124 |
+
Best F1: 0.07692307692307691
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| 125 |
+
Epoch: 13
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| 126 |
+
Precision: 0.08666666666666667
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| 127 |
+
Recall: 0.06914893617021277
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| 128 |
+
F1: 0.07692307692307691
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| 129 |
+
Best Precision: 0.08666666666666667
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| 130 |
+
Best Recall: 0.06914893617021277
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| 131 |
+
Best F1: 0.07692307692307691
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| 132 |
+
Epoch: 14
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| 133 |
+
Average actions: 2.0416665077209473
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| 134 |
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Average target actions: 2.3828125
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| 135 |
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Precision: 0.05228758169934641
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| 136 |
+
Recall: 0.0425531914893617
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| 137 |
+
F1: 0.046920821114369494
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| 138 |
+
Best Precision: 0.08666666666666667
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| 139 |
+
Best Recall: 0.06914893617021277
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| 140 |
+
Best F1: 0.07692307692307691
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| 141 |
+
Epoch: 15
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| 142 |
+
Precision: 0.05228758169934641
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| 143 |
+
Recall: 0.0425531914893617
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| 144 |
+
F1: 0.046920821114369494
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| 145 |
+
Best Precision: 0.08666666666666667
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| 146 |
+
Best Recall: 0.06914893617021277
|
| 147 |
+
Best F1: 0.07692307692307691
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| 148 |
+
Epoch: 16
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| 149 |
+
Average actions: 2.1666665077209473
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| 150 |
+
Average target actions: 2.2135417461395264
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| 151 |
+
Precision: 0.1346153846153846
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| 152 |
+
Recall: 0.11170212765957446
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| 153 |
+
F1: 0.12209302325581395
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| 154 |
+
<<dialog policy>> epoch 16: saved network to mdl
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| 155 |
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Best Precision: 0.1346153846153846
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| 156 |
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Best Recall: 0.11170212765957446
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| 157 |
+
Best F1: 0.12209302325581395
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| 158 |
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Epoch: 17
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| 159 |
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Precision: 0.1346153846153846
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| 160 |
+
Recall: 0.11170212765957446
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| 161 |
+
F1: 0.12209302325581395
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| 162 |
+
Best Precision: 0.1346153846153846
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| 163 |
+
Best Recall: 0.11170212765957446
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| 164 |
+
Best F1: 0.12209302325581395
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| 165 |
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Epoch: 18
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| 166 |
+
Average actions: 1.7734375
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| 167 |
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Average target actions: 2.5520834922790527
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| 168 |
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Precision: 0.0661764705882353
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| 169 |
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Recall: 0.047872340425531915
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| 170 |
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F1: 0.05555555555555556
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| 171 |
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Best Precision: 0.1346153846153846
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| 172 |
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Best Recall: 0.11170212765957446
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| 173 |
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Best F1: 0.12209302325581395
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| 174 |
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Epoch: 19
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| 175 |
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Precision: 0.0661764705882353
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| 176 |
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Recall: 0.047872340425531915
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| 177 |
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F1: 0.05555555555555556
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| 178 |
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Best Precision: 0.1346153846153846
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| 179 |
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Best Recall: 0.11170212765957446
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| 180 |
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Best F1: 0.12209302325581395
|
| 181 |
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Epoch: 20
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| 182 |
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Average actions: 2.1328125
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| 183 |
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Average target actions: 2.6197917461395264
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| 184 |
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Precision: 0.1346153846153846
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| 185 |
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Recall: 0.11170212765957446
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| 186 |
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F1: 0.12209302325581395
|
| 187 |
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Best Precision: 0.1346153846153846
|
| 188 |
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Best Recall: 0.11170212765957446
|
| 189 |
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Best F1: 0.12209302325581395
|
| 190 |
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Epoch: 21
|
| 191 |
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Precision: 0.1346153846153846
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| 192 |
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Recall: 0.11170212765957446
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| 193 |
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F1: 0.12209302325581395
|
| 194 |
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Best Precision: 0.1346153846153846
|
| 195 |
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Best Recall: 0.11170212765957446
|
| 196 |
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Best F1: 0.12209302325581395
|
| 197 |
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Epoch: 22
|
| 198 |
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Average actions: 1.9296875
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| 199 |
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Average target actions: 2.1119792461395264
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| 200 |
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Precision: 0.08391608391608392
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| 201 |
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Recall: 0.06382978723404255
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| 202 |
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F1: 0.07250755287009063
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| 203 |
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Best Precision: 0.1346153846153846
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| 204 |
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Best Recall: 0.11170212765957446
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| 205 |
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Best F1: 0.12209302325581395
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| 206 |
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Epoch: 23
|
| 207 |
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Precision: 0.08391608391608392
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| 208 |
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Recall: 0.06382978723404255
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| 209 |
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F1: 0.07250755287009063
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| 210 |
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Best Precision: 0.1346153846153846
|
| 211 |
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Best Recall: 0.11170212765957446
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| 212 |
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Best F1: 0.12209302325581395
|
| 213 |
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Epoch: 24
|
| 214 |
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Average actions: 2.2213540077209473
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| 215 |
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Average target actions: 2.3151042461395264
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| 216 |
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Precision: 0.09815950920245399
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| 217 |
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Recall: 0.0851063829787234
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F1: 0.09116809116809117
|
| 219 |
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Best Precision: 0.1346153846153846
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| 220 |
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Best Recall: 0.11170212765957446
|
| 221 |
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Best F1: 0.12209302325581395
|
| 222 |
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Epoch: 25
|
| 223 |
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Precision: 0.09815950920245399
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| 224 |
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Recall: 0.0851063829787234
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| 225 |
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F1: 0.09116809116809117
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| 226 |
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Best Precision: 0.1346153846153846
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| 227 |
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Best Recall: 0.11170212765957446
|
| 228 |
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Best F1: 0.12209302325581395
|
| 229 |
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Epoch: 26
|
| 230 |
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Average actions: 2.1171875
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| 231 |
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Average target actions: 2.7890625
|
| 232 |
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Precision: 0.12987012987012986
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Recall: 0.10638297872340426
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F1: 0.11695906432748537
|
| 235 |
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Best Precision: 0.1346153846153846
|
| 236 |
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Best Recall: 0.11170212765957446
|
| 237 |
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Best F1: 0.12209302325581395
|
| 238 |
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Epoch: 27
|
| 239 |
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Precision: 0.12987012987012986
|
| 240 |
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Recall: 0.10638297872340426
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| 241 |
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F1: 0.11695906432748537
|
| 242 |
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Best Precision: 0.1346153846153846
|
| 243 |
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Best Recall: 0.11170212765957446
|
| 244 |
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Best F1: 0.12209302325581395
|
| 245 |
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Epoch: 28
|
| 246 |
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Average actions: 1.7734375
|
| 247 |
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Average target actions: 2.484375
|
| 248 |
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Precision: 0.08823529411764706
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| 249 |
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Recall: 0.06382978723404255
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F1: 0.07407407407407407
|
| 251 |
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Best Precision: 0.1346153846153846
|
| 252 |
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Best Recall: 0.11170212765957446
|
| 253 |
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Best F1: 0.12209302325581395
|
| 254 |
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Epoch: 29
|
| 255 |
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Precision: 0.08823529411764706
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| 256 |
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Recall: 0.06382978723404255
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| 257 |
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F1: 0.07407407407407407
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| 258 |
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Best Precision: 0.1346153846153846
|
| 259 |
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Best Recall: 0.11170212765957446
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| 260 |
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Best F1: 0.12209302325581395
|
| 261 |
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Epoch: 30
|
| 262 |
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Average actions: 2.1822915077209473
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| 263 |
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Average target actions: 2.3489584922790527
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| 264 |
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Precision: 0.10126582278481013
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| 265 |
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Recall: 0.0851063829787234
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F1: 0.09248554913294797
|
| 267 |
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Best Precision: 0.1346153846153846
|
| 268 |
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Best Recall: 0.11170212765957446
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| 269 |
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Best F1: 0.12209302325581395
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| 270 |
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Epoch: 31
|
| 271 |
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Precision: 0.10126582278481013
|
| 272 |
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Recall: 0.0851063829787234
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F1: 0.09248554913294797
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| 274 |
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Best Precision: 0.1346153846153846
|
| 275 |
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Best Recall: 0.11170212765957446
|
| 276 |
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Best F1: 0.12209302325581395
|
| 277 |
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Epoch: 32
|
| 278 |
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Average actions: 2.0442707538604736
|
| 279 |
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Average target actions: 2.6197917461395264
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| 280 |
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Precision: 0.12345679012345678
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Recall: 0.10638297872340426
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F1: 0.11428571428571428
|
| 283 |
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Best Precision: 0.1346153846153846
|
| 284 |
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Best Recall: 0.11170212765957446
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| 285 |
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Best F1: 0.12209302325581395
|
| 286 |
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Epoch: 33
|
| 287 |
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Precision: 0.12345679012345678
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| 288 |
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Recall: 0.10638297872340426
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F1: 0.11428571428571428
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Best Precision: 0.1346153846153846
|
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Best Recall: 0.11170212765957446
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Best F1: 0.12209302325581395
|
| 293 |
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Epoch: 34
|
| 294 |
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Average actions: 1.8307292461395264
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Average target actions: 2.5859375
|
| 296 |
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Precision: 0.11510791366906475
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Recall: 0.0851063829787234
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F1: 0.09785932721712538
|
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Best Precision: 0.1346153846153846
|
| 300 |
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Best Recall: 0.11170212765957446
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Best F1: 0.12209302325581395
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| 302 |
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Epoch: 35
|
| 303 |
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Precision: 0.11510791366906475
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Recall: 0.0851063829787234
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F1: 0.09785932721712538
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Best Precision: 0.1346153846153846
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| 307 |
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Best Recall: 0.11170212765957446
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Best F1: 0.12209302325581395
|
| 309 |
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Epoch: 36
|
| 310 |
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Average actions: 2.2838540077209473
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| 311 |
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Average target actions: 2.3489584922790527
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| 312 |
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Precision: 0.1286549707602339
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| 313 |
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Recall: 0.11702127659574468
|
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F1: 0.12256267409470752
|
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+
<<dialog policy>> epoch 36: saved network to mdl
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| 316 |
+
Best Precision: 0.1346153846153846
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| 317 |
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Best Recall: 0.11702127659574468
|
| 318 |
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Best F1: 0.12256267409470752
|
| 319 |
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Epoch: 37
|
| 320 |
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Precision: 0.1286549707602339
|
| 321 |
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Recall: 0.11702127659574468
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F1: 0.12256267409470752
|
| 323 |
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Best Precision: 0.1346153846153846
|
| 324 |
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Best Recall: 0.11702127659574468
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| 325 |
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Best F1: 0.12256267409470752
|
| 326 |
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Epoch: 38
|
| 327 |
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Average actions: 1.9479167461395264
|
| 328 |
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Average target actions: 2.7552084922790527
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| 329 |
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Precision: 0.12337662337662338
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| 330 |
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Recall: 0.10106382978723404
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F1: 0.1111111111111111
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Best Precision: 0.1346153846153846
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| 333 |
+
Best Recall: 0.11702127659574468
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Best F1: 0.12256267409470752
|
| 335 |
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Epoch: 39
|
| 336 |
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Precision: 0.12337662337662338
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Recall: 0.10106382978723404
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F1: 0.1111111111111111
|
| 339 |
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Best Precision: 0.1346153846153846
|
| 340 |
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Best Recall: 0.11702127659574468
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+
Best F1: 0.12256267409470752
|