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arabert_cross_organization_task4_fold3

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  1. README.md +100 -42
  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_task4_fold3
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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_task4_fold3
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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: 0.6313
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- - Qwk: 0.7591
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- - Mse: 0.6313
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  ## Model description
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@@ -36,49 +36,107 @@ 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 | 0.0308 | 2 | 2.1686 | 0.1373 | 2.1686 |
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- | No log | 0.0615 | 4 | 1.3354 | 0.2422 | 1.3354 |
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- | No log | 0.0923 | 6 | 1.2744 | 0.3955 | 1.2744 |
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- | No log | 0.1231 | 8 | 1.3615 | 0.4102 | 1.3615 |
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- | No log | 0.1538 | 10 | 1.3820 | 0.4241 | 1.3820 |
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- | No log | 0.1846 | 12 | 1.3279 | 0.3908 | 1.3279 |
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- | No log | 0.2154 | 14 | 1.2389 | 0.3748 | 1.2389 |
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- | No log | 0.2462 | 16 | 0.9489 | 0.5321 | 0.9489 |
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- | No log | 0.2769 | 18 | 0.7463 | 0.5725 | 0.7463 |
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- | No log | 0.3077 | 20 | 0.7171 | 0.5990 | 0.7171 |
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- | No log | 0.3385 | 22 | 0.7588 | 0.6627 | 0.7588 |
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- | No log | 0.3692 | 24 | 0.9354 | 0.7247 | 0.9354 |
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- | No log | 0.4 | 26 | 0.9834 | 0.7272 | 0.9834 |
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- | No log | 0.4308 | 28 | 0.8963 | 0.7209 | 0.8963 |
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- | No log | 0.4615 | 30 | 0.7839 | 0.6628 | 0.7839 |
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- | No log | 0.4923 | 32 | 0.7087 | 0.6243 | 0.7087 |
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- | No log | 0.5231 | 34 | 0.6705 | 0.6165 | 0.6705 |
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- | No log | 0.5538 | 36 | 0.6590 | 0.6372 | 0.6590 |
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- | No log | 0.5846 | 38 | 0.6539 | 0.6750 | 0.6539 |
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- | No log | 0.6154 | 40 | 0.6712 | 0.7059 | 0.6712 |
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- | No log | 0.6462 | 42 | 0.6866 | 0.7436 | 0.6866 |
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- | No log | 0.6769 | 44 | 0.7341 | 0.7518 | 0.7341 |
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- | No log | 0.7077 | 46 | 0.7524 | 0.7485 | 0.7524 |
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- | No log | 0.7385 | 48 | 0.7479 | 0.7512 | 0.7479 |
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- | No log | 0.7692 | 50 | 0.7060 | 0.7527 | 0.7060 |
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- | No log | 0.8 | 52 | 0.6730 | 0.7522 | 0.6730 |
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- | No log | 0.8308 | 54 | 0.6623 | 0.7596 | 0.6623 |
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- | No log | 0.8615 | 56 | 0.6499 | 0.7573 | 0.6499 |
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- | No log | 0.8923 | 58 | 0.6418 | 0.7520 | 0.6418 |
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- | No log | 0.9231 | 60 | 0.6393 | 0.7509 | 0.6393 |
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- | No log | 0.9538 | 62 | 0.6358 | 0.7591 | 0.6358 |
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- | No log | 0.9846 | 64 | 0.6313 | 0.7591 | 0.6313 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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_task4_fold2
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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_task4_fold2
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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: 1.7693
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+ - Qwk: -0.0357
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+ - Mse: 1.7659
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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 | 0.1111 | 2 | 4.1886 | 0.0011 | 4.1850 |
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+ | No log | 0.2222 | 4 | 2.2640 | 0.0 | 2.2614 |
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+ | No log | 0.3333 | 6 | 1.3362 | 0.0183 | 1.3332 |
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+ | No log | 0.4444 | 8 | 0.9155 | 0.0 | 0.9122 |
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+ | No log | 0.5556 | 10 | 0.9188 | -0.0048 | 0.9152 |
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+ | No log | 0.6667 | 12 | 0.8902 | -0.0315 | 0.8872 |
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+ | No log | 0.7778 | 14 | 0.8950 | 0.0741 | 0.8923 |
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+ | No log | 0.8889 | 16 | 0.8770 | 0.0875 | 0.8744 |
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+ | No log | 1.0 | 18 | 0.8807 | 0.1030 | 0.8782 |
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+ | No log | 1.1111 | 20 | 0.8915 | -0.0099 | 0.8887 |
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+ | No log | 1.2222 | 22 | 0.9457 | 0.0424 | 0.9431 |
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+ | No log | 1.3333 | 24 | 1.0318 | 0.0182 | 1.0292 |
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+ | No log | 1.4444 | 26 | 1.1586 | 0.0 | 1.1562 |
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+ | No log | 1.5556 | 28 | 1.2936 | 0.0 | 1.2909 |
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+ | No log | 1.6667 | 30 | 1.4219 | 0.0 | 1.4193 |
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+ | No log | 1.7778 | 32 | 1.4842 | 0.0 | 1.4816 |
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+ | No log | 1.8889 | 34 | 1.4765 | 0.0 | 1.4737 |
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+ | No log | 2.0 | 36 | 1.4797 | 0.0 | 1.4769 |
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+ | No log | 2.1111 | 38 | 1.4454 | 0.0 | 1.4425 |
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+ | No log | 2.2222 | 40 | 1.5693 | 0.0 | 1.5665 |
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+ | No log | 2.3333 | 42 | 1.6763 | 0.0 | 1.6737 |
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+ | No log | 2.4444 | 44 | 1.6705 | 0.0 | 1.6677 |
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+ | No log | 2.5556 | 46 | 1.4309 | 0.0182 | 1.4278 |
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+ | No log | 2.6667 | 48 | 1.3201 | 0.0536 | 1.3169 |
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+ | No log | 2.7778 | 50 | 1.5069 | 0.0182 | 1.5037 |
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+ | No log | 2.8889 | 52 | 1.6390 | 0.0 | 1.6360 |
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+ | No log | 3.0 | 54 | 1.5712 | 0.0 | 1.5682 |
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+ | No log | 3.1111 | 56 | 1.4444 | 0.0182 | 1.4413 |
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+ | No log | 3.2222 | 58 | 1.3827 | 0.0182 | 1.3796 |
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+ | No log | 3.3333 | 60 | 1.5276 | 0.0 | 1.5245 |
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+ | No log | 3.4444 | 62 | 1.5680 | 0.0025 | 1.5650 |
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+ | No log | 3.5556 | 64 | 1.5963 | 0.0328 | 1.5931 |
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+ | No log | 3.6667 | 66 | 1.5027 | -0.0118 | 1.4994 |
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+ | No log | 3.7778 | 68 | 1.5906 | 0.0485 | 1.5873 |
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+ | No log | 3.8889 | 70 | 1.7316 | 0.0225 | 1.7284 |
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+ | No log | 4.0 | 72 | 1.6752 | 0.0160 | 1.6719 |
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+ | No log | 4.1111 | 74 | 1.4644 | 0.0136 | 1.4611 |
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+ | No log | 4.2222 | 76 | 1.2946 | 0.0498 | 1.2914 |
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+ | No log | 4.3333 | 78 | 1.3892 | 0.0571 | 1.3860 |
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+ | No log | 4.4444 | 80 | 1.6935 | 0.0183 | 1.6903 |
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+ | No log | 4.5556 | 82 | 1.8327 | 0.0026 | 1.8295 |
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+ | No log | 4.6667 | 84 | 1.7518 | 0.0272 | 1.7486 |
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+ | No log | 4.7778 | 86 | 1.5355 | 0.0437 | 1.5322 |
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+ | No log | 4.8889 | 88 | 1.4546 | 0.0750 | 1.4513 |
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+ | No log | 5.0 | 90 | 1.6165 | 0.0875 | 1.6132 |
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+ | No log | 5.1111 | 92 | 1.8925 | 0.0054 | 1.8891 |
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+ | No log | 5.2222 | 94 | 1.9400 | -0.0784 | 1.9366 |
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+ | No log | 5.3333 | 96 | 1.7667 | 0.0162 | 1.7634 |
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+ | No log | 5.4444 | 98 | 1.5714 | 0.0700 | 1.5681 |
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+ | No log | 5.5556 | 100 | 1.6393 | 0.0586 | 1.6360 |
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+ | No log | 5.6667 | 102 | 1.7094 | 0.0144 | 1.7060 |
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+ | No log | 5.7778 | 104 | 1.8384 | 0.0162 | 1.8349 |
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+ | No log | 5.8889 | 106 | 1.7972 | 0.0130 | 1.7937 |
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+ | No log | 6.0 | 108 | 1.7520 | 0.0113 | 1.7486 |
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+ | No log | 6.1111 | 110 | 1.6669 | 0.0264 | 1.6636 |
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+ | No log | 6.2222 | 112 | 1.6880 | 0.0301 | 1.6846 |
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+ | No log | 6.3333 | 114 | 1.7562 | 0.0096 | 1.7528 |
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+ | No log | 6.4444 | 116 | 1.7980 | 0.0228 | 1.7947 |
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+ | No log | 6.5556 | 118 | 1.8220 | -0.0199 | 1.8187 |
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+ | No log | 6.6667 | 120 | 1.7461 | 0.0746 | 1.7429 |
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+ | No log | 6.7778 | 122 | 1.5563 | 0.0272 | 1.5532 |
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+ | No log | 6.8889 | 124 | 1.4185 | 0.0655 | 1.4154 |
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+ | No log | 7.0 | 126 | 1.4690 | 0.0697 | 1.4658 |
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+ | No log | 7.1111 | 128 | 1.6412 | 0.0722 | 1.6381 |
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+ | No log | 7.2222 | 130 | 1.8101 | -0.0325 | 1.8069 |
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+ | No log | 7.3333 | 132 | 1.8161 | -0.0588 | 1.8129 |
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+ | No log | 7.4444 | 134 | 1.6991 | 0.0758 | 1.6959 |
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+ | No log | 7.5556 | 136 | 1.5693 | 0.0476 | 1.5661 |
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+ | No log | 7.6667 | 138 | 1.5215 | 0.0437 | 1.5183 |
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+ | No log | 7.7778 | 140 | 1.5990 | 0.0699 | 1.5957 |
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+ | No log | 7.8889 | 142 | 1.7382 | 0.0363 | 1.7348 |
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+ | No log | 8.0 | 144 | 1.8943 | -0.0587 | 1.8909 |
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+ | No log | 8.1111 | 146 | 1.9468 | -0.0675 | 1.9434 |
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+ | No log | 8.2222 | 148 | 1.9074 | -0.0587 | 1.9040 |
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+ | No log | 8.3333 | 150 | 1.8074 | -0.0208 | 1.8040 |
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+ | No log | 8.4444 | 152 | 1.7220 | 0.0241 | 1.7186 |
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+ | No log | 8.5556 | 154 | 1.6877 | 0.0352 | 1.6843 |
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+ | No log | 8.6667 | 156 | 1.7113 | 0.0222 | 1.7079 |
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+ | No log | 8.7778 | 158 | 1.7927 | -0.0208 | 1.7893 |
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+ | No log | 8.8889 | 160 | 1.8848 | -0.0477 | 1.8813 |
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+ | No log | 9.0 | 162 | 1.9430 | -0.0613 | 1.9396 |
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+ | No log | 9.1111 | 164 | 1.9388 | -0.0613 | 1.9354 |
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+ | No log | 9.2222 | 166 | 1.8894 | -0.0477 | 1.8860 |
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+ | No log | 9.3333 | 168 | 1.8314 | -0.0424 | 1.8279 |
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+ | No log | 9.4444 | 170 | 1.7625 | -0.0357 | 1.7591 |
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+ | No log | 9.5556 | 172 | 1.7335 | 0.0264 | 1.7302 |
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+ | No log | 9.6667 | 174 | 1.7407 | 0.0264 | 1.7373 |
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+ | No log | 9.7778 | 176 | 1.7576 | -0.0102 | 1.7543 |
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+ | No log | 9.8889 | 178 | 1.7644 | -0.0357 | 1.7610 |
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+ | No log | 10.0 | 180 | 1.7693 | -0.0357 | 1.7659 |
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  ### Framework versions
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