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  1. README.md +83 -36
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -3,20 +3,20 @@ base_model: aubmindlab/bert-base-arabertv02
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  tags:
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  - generated_from_trainer
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  model-index:
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- - name: arabert_cross_organization_task5_fold1
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # arabert_cross_organization_task5_fold1
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  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8049
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- - Qwk: 0.3251
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- - Mse: 0.8049
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  ## Model description
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@@ -36,45 +36,92 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 1
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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- | No log | 0.0351 | 2 | 2.7876 | 0.0099 | 2.7876 |
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- | No log | 0.0702 | 4 | 1.5835 | 0.1105 | 1.5835 |
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- | No log | 0.1053 | 6 | 1.2849 | 0.2081 | 1.2849 |
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- | No log | 0.1404 | 8 | 1.2987 | 0.2334 | 1.2987 |
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- | No log | 0.1754 | 10 | 1.1249 | 0.2763 | 1.1249 |
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- | No log | 0.2105 | 12 | 0.7600 | 0.3021 | 0.7600 |
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- | No log | 0.2456 | 14 | 0.8150 | 0.3411 | 0.8150 |
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- | No log | 0.2807 | 16 | 0.8928 | 0.3266 | 0.8928 |
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- | No log | 0.3158 | 18 | 0.7030 | 0.3846 | 0.7030 |
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- | No log | 0.3509 | 20 | 0.6175 | 0.4902 | 0.6175 |
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- | No log | 0.3860 | 22 | 0.6241 | 0.5080 | 0.6241 |
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- | No log | 0.4211 | 24 | 0.6115 | 0.4542 | 0.6115 |
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- | No log | 0.4561 | 26 | 0.6354 | 0.3764 | 0.6354 |
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- | No log | 0.4912 | 28 | 0.8733 | 0.3207 | 0.8733 |
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- | No log | 0.5263 | 30 | 1.2551 | 0.2508 | 1.2551 |
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- | No log | 0.5614 | 32 | 1.3371 | 0.2419 | 1.3371 |
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- | No log | 0.5965 | 34 | 1.1165 | 0.2721 | 1.1165 |
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- | No log | 0.6316 | 36 | 0.8902 | 0.3213 | 0.8902 |
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- | No log | 0.6667 | 38 | 0.7152 | 0.3298 | 0.7152 |
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- | No log | 0.7018 | 40 | 0.6330 | 0.3874 | 0.6330 |
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- | No log | 0.7368 | 42 | 0.6428 | 0.3719 | 0.6428 |
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- | No log | 0.7719 | 44 | 0.6984 | 0.3350 | 0.6984 |
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- | No log | 0.8070 | 46 | 0.7832 | 0.3196 | 0.7832 |
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- | No log | 0.8421 | 48 | 0.8869 | 0.3143 | 0.8869 |
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- | No log | 0.8772 | 50 | 0.9002 | 0.3104 | 0.9002 |
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- | No log | 0.9123 | 52 | 0.8566 | 0.3170 | 0.8566 |
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- | No log | 0.9474 | 54 | 0.8238 | 0.3260 | 0.8238 |
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- | No log | 0.9825 | 56 | 0.8049 | 0.3251 | 0.8049 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  tags:
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  - generated_from_trainer
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  model-index:
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+ - name: arabert_cross_organization_task5_fold0
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ # arabert_cross_organization_task5_fold0
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  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8536
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+ - Qwk: 0.5305
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+ - Mse: 0.8521
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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+ | No log | 0.1333 | 2 | 2.8325 | 0.0355 | 2.8291 |
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+ | No log | 0.2667 | 4 | 1.6790 | 0.2071 | 1.6769 |
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+ | No log | 0.4 | 6 | 1.2491 | 0.3232 | 1.2479 |
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+ | No log | 0.5333 | 8 | 1.0946 | 0.4006 | 1.0940 |
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+ | No log | 0.6667 | 10 | 0.9240 | 0.5244 | 0.9238 |
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+ | No log | 0.8 | 12 | 1.0994 | 0.4812 | 1.0991 |
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+ | No log | 0.9333 | 14 | 1.0985 | 0.4785 | 1.0981 |
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+ | No log | 1.0667 | 16 | 0.9091 | 0.5213 | 0.9088 |
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+ | No log | 1.2 | 18 | 0.8691 | 0.5235 | 0.8687 |
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+ | No log | 1.3333 | 20 | 1.1009 | 0.4480 | 1.1002 |
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+ | No log | 1.4667 | 22 | 0.9916 | 0.4796 | 0.9909 |
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+ | No log | 1.6 | 24 | 0.8206 | 0.5231 | 0.8200 |
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+ | No log | 1.7333 | 26 | 0.8819 | 0.5255 | 0.8812 |
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+ | No log | 1.8667 | 28 | 1.1165 | 0.4625 | 1.1156 |
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+ | No log | 2.0 | 30 | 0.9537 | 0.5260 | 0.9531 |
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+ | No log | 2.1333 | 32 | 0.7775 | 0.6092 | 0.7773 |
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+ | No log | 2.2667 | 34 | 0.8262 | 0.5792 | 0.8258 |
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+ | No log | 2.4 | 36 | 0.9527 | 0.5326 | 0.9519 |
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+ | No log | 2.5333 | 38 | 0.8990 | 0.5382 | 0.8983 |
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+ | No log | 2.6667 | 40 | 0.7673 | 0.6124 | 0.7669 |
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+ | No log | 2.8 | 42 | 0.7340 | 0.6181 | 0.7335 |
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+ | No log | 2.9333 | 44 | 0.8826 | 0.5543 | 0.8815 |
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+ | No log | 3.0667 | 46 | 1.2982 | 0.4128 | 1.2965 |
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+ | No log | 3.2 | 48 | 1.1748 | 0.4370 | 1.1731 |
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+ | No log | 3.3333 | 50 | 0.7851 | 0.5568 | 0.7840 |
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+ | No log | 3.4667 | 52 | 0.6933 | 0.6150 | 0.6924 |
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+ | No log | 3.6 | 54 | 0.7593 | 0.5656 | 0.7582 |
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+ | No log | 3.7333 | 56 | 0.9243 | 0.4943 | 0.9229 |
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+ | No log | 3.8667 | 58 | 0.9098 | 0.5117 | 0.9084 |
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+ | No log | 4.0 | 60 | 0.7896 | 0.5674 | 0.7885 |
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+ | No log | 4.1333 | 62 | 0.7231 | 0.6204 | 0.7224 |
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+ | No log | 4.2667 | 64 | 0.7654 | 0.6006 | 0.7646 |
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+ | No log | 4.4 | 66 | 0.8645 | 0.5394 | 0.8632 |
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+ | No log | 4.5333 | 68 | 0.8997 | 0.5331 | 0.8983 |
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+ | No log | 4.6667 | 70 | 0.7948 | 0.5651 | 0.7936 |
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+ | No log | 4.8 | 72 | 0.7556 | 0.5765 | 0.7545 |
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+ | No log | 4.9333 | 74 | 0.7815 | 0.5752 | 0.7803 |
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+ | No log | 5.0667 | 76 | 0.7767 | 0.5824 | 0.7755 |
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+ | No log | 5.2 | 78 | 0.8240 | 0.5627 | 0.8228 |
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+ | No log | 5.3333 | 80 | 0.8544 | 0.5524 | 0.8531 |
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+ | No log | 5.4667 | 82 | 0.8799 | 0.5383 | 0.8785 |
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+ | No log | 5.6 | 84 | 0.8068 | 0.5637 | 0.8055 |
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+ | No log | 5.7333 | 86 | 0.7866 | 0.5790 | 0.7853 |
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+ | No log | 5.8667 | 88 | 0.8602 | 0.5505 | 0.8588 |
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+ | No log | 6.0 | 90 | 0.8403 | 0.5508 | 0.8390 |
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+ | No log | 6.1333 | 92 | 0.7915 | 0.5599 | 0.7903 |
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+ | No log | 6.2667 | 94 | 0.7576 | 0.5889 | 0.7565 |
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+ | No log | 6.4 | 96 | 0.7814 | 0.5709 | 0.7802 |
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+ | No log | 6.5333 | 98 | 0.7840 | 0.5682 | 0.7828 |
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+ | No log | 6.6667 | 100 | 0.8376 | 0.5500 | 0.8362 |
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+ | No log | 6.8 | 102 | 0.8823 | 0.5259 | 0.8808 |
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+ | No log | 6.9333 | 104 | 0.8409 | 0.5388 | 0.8395 |
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+ | No log | 7.0667 | 106 | 0.7908 | 0.5700 | 0.7895 |
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+ | No log | 7.2 | 108 | 0.8370 | 0.5398 | 0.8356 |
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+ | No log | 7.3333 | 110 | 0.9465 | 0.5061 | 0.9448 |
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+ | No log | 7.4667 | 112 | 0.9805 | 0.4909 | 0.9787 |
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+ | No log | 7.6 | 114 | 0.8809 | 0.5217 | 0.8793 |
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+ | No log | 7.7333 | 116 | 0.7546 | 0.5828 | 0.7533 |
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+ | No log | 7.8667 | 118 | 0.7282 | 0.5855 | 0.7270 |
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+ | No log | 8.0 | 120 | 0.7740 | 0.5703 | 0.7727 |
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+ | No log | 8.1333 | 122 | 0.8664 | 0.5129 | 0.8649 |
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+ | No log | 8.2667 | 124 | 0.8853 | 0.5069 | 0.8838 |
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+ | No log | 8.4 | 126 | 0.8189 | 0.5483 | 0.8175 |
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+ | No log | 8.5333 | 128 | 0.7717 | 0.5683 | 0.7704 |
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+ | No log | 8.6667 | 130 | 0.7625 | 0.5761 | 0.7613 |
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+ | No log | 8.8 | 132 | 0.7903 | 0.5682 | 0.7890 |
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+ | No log | 8.9333 | 134 | 0.8518 | 0.5384 | 0.8503 |
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+ | No log | 9.0667 | 136 | 0.9168 | 0.5056 | 0.9152 |
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+ | No log | 9.2 | 138 | 0.9669 | 0.4922 | 0.9652 |
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+ | No log | 9.3333 | 140 | 0.9617 | 0.4944 | 0.9600 |
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+ | No log | 9.4667 | 142 | 0.9232 | 0.5081 | 0.9216 |
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+ | No log | 9.6 | 144 | 0.8847 | 0.5249 | 0.8831 |
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+ | No log | 9.7333 | 146 | 0.8666 | 0.5296 | 0.8651 |
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+ | No log | 9.8667 | 148 | 0.8562 | 0.5305 | 0.8547 |
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+ | No log | 10.0 | 150 | 0.8536 | 0.5305 | 0.8521 |
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  ### Framework versions
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