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arabert_cross_organization_task3_fold3

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  1. README.md +100 -41
  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_task3_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_task3_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: 0.6774
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- - Qwk: 0.7501
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- - Mse: 0.6774
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  ## Model description
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@@ -36,48 +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 | 0.0317 | 2 | 2.2856 | 0.0652 | 2.2856 |
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- | No log | 0.0635 | 4 | 1.6398 | 0.1328 | 1.6398 |
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- | No log | 0.0952 | 6 | 1.3659 | 0.3054 | 1.3659 |
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- | No log | 0.1270 | 8 | 1.5662 | 0.3262 | 1.5662 |
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- | No log | 0.1587 | 10 | 1.3385 | 0.3693 | 1.3385 |
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- | No log | 0.1905 | 12 | 1.3612 | 0.2651 | 1.3612 |
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- | No log | 0.2222 | 14 | 1.2329 | 0.2904 | 1.2329 |
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- | No log | 0.2540 | 16 | 1.0232 | 0.5183 | 1.0232 |
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- | No log | 0.2857 | 18 | 1.0661 | 0.6592 | 1.0661 |
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- | No log | 0.3175 | 20 | 0.9924 | 0.6396 | 0.9924 |
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- | No log | 0.3492 | 22 | 0.8250 | 0.5647 | 0.8250 |
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- | No log | 0.3810 | 24 | 0.7736 | 0.5773 | 0.7736 |
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- | No log | 0.4127 | 26 | 0.7476 | 0.5679 | 0.7476 |
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- | No log | 0.4444 | 28 | 0.7257 | 0.5766 | 0.7257 |
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- | No log | 0.4762 | 30 | 0.7059 | 0.6299 | 0.7059 |
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- | No log | 0.5079 | 32 | 0.7311 | 0.6989 | 0.7311 |
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- | No log | 0.5397 | 34 | 0.7963 | 0.7287 | 0.7963 |
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- | No log | 0.5714 | 36 | 0.8902 | 0.7248 | 0.8902 |
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- | No log | 0.6032 | 38 | 0.8515 | 0.7375 | 0.8515 |
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- | No log | 0.6349 | 40 | 0.7404 | 0.7477 | 0.7404 |
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- | No log | 0.6667 | 42 | 0.6799 | 0.7282 | 0.6799 |
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- | No log | 0.6984 | 44 | 0.6543 | 0.7057 | 0.6543 |
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- | No log | 0.7302 | 46 | 0.6557 | 0.6928 | 0.6557 |
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- | No log | 0.7619 | 48 | 0.6577 | 0.6860 | 0.6577 |
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- | No log | 0.7937 | 50 | 0.6623 | 0.7073 | 0.6623 |
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- | No log | 0.8254 | 52 | 0.6768 | 0.7312 | 0.6768 |
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- | No log | 0.8571 | 54 | 0.6939 | 0.7420 | 0.6939 |
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- | No log | 0.8889 | 56 | 0.6978 | 0.7414 | 0.6978 |
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- | No log | 0.9206 | 58 | 0.6922 | 0.7509 | 0.6922 |
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- | No log | 0.9524 | 60 | 0.6825 | 0.7501 | 0.6825 |
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- | No log | 0.9841 | 62 | 0.6774 | 0.7501 | 0.6774 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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_task3_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_task3_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: 1.6024
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+ - Qwk: 0.0538
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+ - Mse: 1.6024
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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 | 4.4408 | 0.0040 | 4.4408 |
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+ | No log | 0.2222 | 4 | 2.1445 | -0.0019 | 2.1445 |
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+ | No log | 0.3333 | 6 | 1.2335 | -0.0070 | 1.2335 |
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+ | No log | 0.4444 | 8 | 1.2037 | -0.0160 | 1.2037 |
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+ | No log | 0.5556 | 10 | 1.2041 | -0.0073 | 1.2041 |
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+ | No log | 0.6667 | 12 | 1.1517 | 0.0051 | 1.1517 |
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+ | No log | 0.7778 | 14 | 1.2374 | 0.0328 | 1.2374 |
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+ | No log | 0.8889 | 16 | 1.1607 | -0.0476 | 1.1607 |
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+ | No log | 1.0 | 18 | 1.1734 | -0.0518 | 1.1734 |
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+ | No log | 1.1111 | 20 | 1.2625 | -0.0809 | 1.2625 |
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+ | No log | 1.2222 | 22 | 1.3757 | 0.0003 | 1.3757 |
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+ | No log | 1.3333 | 24 | 1.1818 | -0.1060 | 1.1818 |
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+ | No log | 1.4444 | 26 | 1.2926 | 0.0 | 1.2926 |
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+ | No log | 1.5556 | 28 | 1.6227 | -0.0906 | 1.6227 |
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+ | No log | 1.6667 | 30 | 1.8505 | 0.0618 | 1.8505 |
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+ | No log | 1.7778 | 32 | 1.4810 | 0.0402 | 1.4810 |
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+ | No log | 1.8889 | 34 | 1.6514 | 0.0454 | 1.6514 |
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+ | No log | 2.0 | 36 | 1.9399 | 0.0198 | 1.9399 |
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+ | No log | 2.1111 | 38 | 1.6927 | 0.0351 | 1.6927 |
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+ | No log | 2.2222 | 40 | 1.5365 | 0.0112 | 1.5365 |
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+ | No log | 2.3333 | 42 | 1.7530 | 0.0199 | 1.7530 |
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+ | No log | 2.4444 | 44 | 1.5376 | 0.0302 | 1.5376 |
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+ | No log | 2.5556 | 46 | 1.4487 | -0.0223 | 1.4487 |
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+ | No log | 2.6667 | 48 | 1.7456 | 0.0144 | 1.7456 |
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+ | No log | 2.7778 | 50 | 1.9590 | 0.0498 | 1.9590 |
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+ | No log | 2.8889 | 52 | 1.6503 | 0.0145 | 1.6503 |
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+ | No log | 3.0 | 54 | 1.4764 | -0.0314 | 1.4764 |
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+ | No log | 3.1111 | 56 | 1.6835 | 0.0294 | 1.6835 |
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+ | No log | 3.2222 | 58 | 1.7955 | 0.0312 | 1.7955 |
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+ | No log | 3.3333 | 60 | 1.7538 | 0.0635 | 1.7538 |
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+ | No log | 3.4444 | 62 | 1.4927 | 0.0176 | 1.4927 |
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+ | No log | 3.5556 | 64 | 1.6904 | 0.0720 | 1.6904 |
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+ | No log | 3.6667 | 66 | 1.8393 | 0.0312 | 1.8393 |
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+ | No log | 3.7778 | 68 | 1.8313 | 0.0254 | 1.8313 |
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+ | No log | 3.8889 | 70 | 1.6934 | 0.0842 | 1.6934 |
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+ | No log | 4.0 | 72 | 1.5049 | 0.0730 | 1.5049 |
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+ | No log | 4.1111 | 74 | 1.6026 | 0.0175 | 1.6026 |
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+ | No log | 4.2222 | 76 | 1.5882 | 0.0325 | 1.5882 |
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+ | No log | 4.3333 | 78 | 1.6196 | 0.0264 | 1.6196 |
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+ | No log | 4.4444 | 80 | 1.5514 | 0.0974 | 1.5514 |
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+ | No log | 4.5556 | 82 | 1.4767 | 0.0909 | 1.4767 |
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+ | No log | 4.6667 | 84 | 1.2836 | 0.1034 | 1.2836 |
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+ | No log | 4.7778 | 86 | 1.3626 | 0.0270 | 1.3626 |
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+ | No log | 4.8889 | 88 | 1.6465 | 0.0229 | 1.6465 |
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+ | No log | 5.0 | 90 | 1.8343 | -0.0220 | 1.8343 |
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+ | No log | 5.1111 | 92 | 1.6557 | 0.0083 | 1.6557 |
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+ | No log | 5.2222 | 94 | 1.3225 | -0.0058 | 1.3225 |
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+ | No log | 5.3333 | 96 | 1.2482 | 0.0470 | 1.2482 |
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+ | No log | 5.4444 | 98 | 1.3076 | 0.0607 | 1.3076 |
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+ | No log | 5.5556 | 100 | 1.6016 | 0.0775 | 1.6016 |
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+ | No log | 5.6667 | 102 | 1.8225 | 0.0197 | 1.8225 |
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+ | No log | 5.7778 | 104 | 1.7541 | -0.0002 | 1.7541 |
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+ | No log | 5.8889 | 106 | 1.5325 | 0.0489 | 1.5325 |
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+ | No log | 6.0 | 108 | 1.4866 | 0.1203 | 1.4866 |
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+ | No log | 6.1111 | 110 | 1.5168 | 0.0747 | 1.5168 |
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+ | No log | 6.2222 | 112 | 1.5806 | 0.0628 | 1.5806 |
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+ | No log | 6.3333 | 114 | 1.5301 | 0.0840 | 1.5301 |
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+ | No log | 6.4444 | 116 | 1.5252 | 0.1176 | 1.5252 |
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+ | No log | 6.5556 | 118 | 1.6195 | 0.0414 | 1.6195 |
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+ | No log | 6.6667 | 120 | 1.7519 | -0.0347 | 1.7519 |
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+ | No log | 6.7778 | 122 | 1.7121 | 0.0055 | 1.7121 |
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+ | No log | 6.8889 | 124 | 1.5662 | 0.0951 | 1.5662 |
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+ | No log | 7.0 | 126 | 1.5098 | 0.1301 | 1.5098 |
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+ | No log | 7.1111 | 128 | 1.5746 | 0.12 | 1.5746 |
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+ | No log | 7.2222 | 130 | 1.7267 | -0.0092 | 1.7267 |
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+ | No log | 7.3333 | 132 | 1.7245 | -0.0092 | 1.7245 |
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+ | No log | 7.4444 | 134 | 1.5965 | 0.0502 | 1.5965 |
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+ | No log | 7.5556 | 136 | 1.5245 | 0.0966 | 1.5245 |
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+ | No log | 7.6667 | 138 | 1.4468 | 0.0095 | 1.4468 |
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+ | No log | 7.7778 | 140 | 1.4564 | 0.0425 | 1.4564 |
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+ | No log | 7.8889 | 142 | 1.5131 | 0.0840 | 1.5131 |
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+ | No log | 8.0 | 144 | 1.6343 | 0.0606 | 1.6343 |
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+ | No log | 8.1111 | 146 | 1.6708 | 0.0339 | 1.6708 |
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+ | No log | 8.2222 | 148 | 1.7099 | 0.0339 | 1.7099 |
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+ | No log | 8.3333 | 150 | 1.7246 | 0.0339 | 1.7246 |
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+ | No log | 8.4444 | 152 | 1.7128 | 0.0339 | 1.7128 |
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+ | No log | 8.5556 | 154 | 1.6734 | 0.0657 | 1.6734 |
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+ | No log | 8.6667 | 156 | 1.6578 | 0.0520 | 1.6578 |
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+ | No log | 8.7778 | 158 | 1.7162 | 0.0533 | 1.7162 |
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+ | No log | 8.8889 | 160 | 1.7512 | -0.0403 | 1.7512 |
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+ | No log | 9.0 | 162 | 1.7393 | -0.0034 | 1.7393 |
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+ | No log | 9.1111 | 164 | 1.6847 | 0.0542 | 1.6847 |
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+ | No log | 9.2222 | 166 | 1.6059 | 0.0442 | 1.6059 |
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+ | No log | 9.3333 | 168 | 1.5649 | 0.0881 | 1.5649 |
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+ | No log | 9.4444 | 170 | 1.5449 | 0.1090 | 1.5449 |
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+ | No log | 9.5556 | 172 | 1.5536 | 0.1090 | 1.5536 |
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+ | No log | 9.6667 | 174 | 1.5814 | 0.0419 | 1.5814 |
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+ | No log | 9.7778 | 176 | 1.5969 | 0.0560 | 1.5969 |
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+ | No log | 9.8889 | 178 | 1.6011 | 0.0560 | 1.6011 |
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+ | No log | 10.0 | 180 | 1.6024 | 0.0538 | 1.6024 |
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  ### Framework versions
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