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arabert_cross_organization_task4_fold2

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  1. README.md +93 -43
  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_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: 1.3326
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- - Qwk: -0.0168
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- - Mse: 1.3108
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  ## Model description
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@@ -36,52 +36,102 @@ 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 | 0.0282 | 2 | 5.7271 | 0.0134 | 5.7480 |
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- | No log | 0.0563 | 4 | 2.8011 | 0.0108 | 2.8128 |
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- | No log | 0.0845 | 6 | 1.1853 | 0.0747 | 1.1830 |
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- | No log | 0.1127 | 8 | 0.8362 | 0.0389 | 0.8275 |
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- | No log | 0.1408 | 10 | 0.8333 | 0.1288 | 0.8213 |
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- | No log | 0.1690 | 12 | 0.8688 | 0.1267 | 0.8595 |
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- | No log | 0.1972 | 14 | 0.9519 | 0.1054 | 0.9385 |
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- | No log | 0.2254 | 16 | 0.9970 | 0.0306 | 0.9822 |
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- | No log | 0.2535 | 18 | 1.0292 | 0.0258 | 1.0103 |
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- | No log | 0.2817 | 20 | 1.0334 | -0.0628 | 1.0157 |
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- | No log | 0.3099 | 22 | 1.0686 | -0.1440 | 1.0532 |
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- | No log | 0.3380 | 24 | 1.1200 | 0.0189 | 1.0994 |
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- | No log | 0.3662 | 26 | 1.2013 | 0.0103 | 1.1805 |
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- | No log | 0.3944 | 28 | 1.2303 | -0.0460 | 1.2082 |
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- | No log | 0.4225 | 30 | 1.2347 | -0.0420 | 1.2132 |
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- | No log | 0.4507 | 32 | 1.1787 | -0.0368 | 1.1561 |
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- | No log | 0.4789 | 34 | 1.1677 | -0.0346 | 1.1449 |
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- | No log | 0.5070 | 36 | 1.1550 | 0.0020 | 1.1329 |
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- | No log | 0.5352 | 38 | 1.1940 | -0.0866 | 1.1731 |
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- | No log | 0.5634 | 40 | 1.1923 | -0.0408 | 1.1735 |
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- | No log | 0.5915 | 42 | 1.1642 | -0.0408 | 1.1467 |
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- | No log | 0.6197 | 44 | 1.0921 | -0.0468 | 1.0757 |
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- | No log | 0.6479 | 46 | 1.0848 | -0.0448 | 1.0687 |
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- | No log | 0.6761 | 48 | 1.0785 | -0.0317 | 1.0615 |
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- | No log | 0.7042 | 50 | 1.0877 | 0.0101 | 1.0705 |
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- | No log | 0.7324 | 52 | 1.1100 | -0.0298 | 1.0927 |
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- | No log | 0.7606 | 54 | 1.1436 | -0.0217 | 1.1254 |
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- | No log | 0.7887 | 56 | 1.1970 | -0.0235 | 1.1785 |
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- | No log | 0.8169 | 58 | 1.2422 | -0.0168 | 1.2238 |
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- | No log | 0.8451 | 60 | 1.2565 | -0.0168 | 1.2371 |
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- | No log | 0.8732 | 62 | 1.2821 | -0.0168 | 1.2624 |
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- | No log | 0.9014 | 64 | 1.3042 | -0.0168 | 1.2840 |
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- | No log | 0.9296 | 66 | 1.3287 | -0.0168 | 1.3079 |
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- | No log | 0.9577 | 68 | 1.3368 | -0.0168 | 1.3154 |
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- | No log | 0.9859 | 70 | 1.3326 | -0.0168 | 1.3108 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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_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_task4_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: 0.7438
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+ - Qwk: 0.4143
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+ - Mse: 0.7438
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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 | 0.1176 | 2 | 3.2005 | 0.0155 | 3.2005 |
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+ | No log | 0.2353 | 4 | 1.7053 | -0.0034 | 1.7053 |
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+ | No log | 0.3529 | 6 | 1.1027 | 0.1636 | 1.1027 |
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+ | No log | 0.4706 | 8 | 1.0959 | 0.1953 | 1.0959 |
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+ | No log | 0.5882 | 10 | 1.1008 | 0.2356 | 1.1008 |
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+ | No log | 0.7059 | 12 | 0.7123 | 0.3763 | 0.7123 |
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+ | No log | 0.8235 | 14 | 0.7466 | 0.4020 | 0.7466 |
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+ | No log | 0.9412 | 16 | 0.9174 | 0.3522 | 0.9174 |
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+ | No log | 1.0588 | 18 | 0.9416 | 0.3154 | 0.9416 |
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+ | No log | 1.1765 | 20 | 0.7002 | 0.3766 | 0.7002 |
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+ | No log | 1.2941 | 22 | 0.6826 | 0.3709 | 0.6826 |
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+ | No log | 1.4118 | 24 | 0.6996 | 0.3822 | 0.6996 |
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+ | No log | 1.5294 | 26 | 0.6165 | 0.4733 | 0.6165 |
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+ | No log | 1.6471 | 28 | 0.5696 | 0.5228 | 0.5696 |
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+ | No log | 1.7647 | 30 | 0.7076 | 0.4534 | 0.7076 |
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+ | No log | 1.8824 | 32 | 0.7251 | 0.4533 | 0.7251 |
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+ | No log | 2.0 | 34 | 0.5922 | 0.4921 | 0.5922 |
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+ | No log | 2.1176 | 36 | 0.5428 | 0.5484 | 0.5428 |
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+ | No log | 2.2353 | 38 | 0.5662 | 0.5159 | 0.5662 |
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+ | No log | 2.3529 | 40 | 0.6256 | 0.4714 | 0.6256 |
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+ | No log | 2.4706 | 42 | 0.6008 | 0.4805 | 0.6008 |
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+ | No log | 2.5882 | 44 | 0.5493 | 0.5367 | 0.5493 |
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+ | No log | 2.7059 | 46 | 0.5855 | 0.5042 | 0.5855 |
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+ | No log | 2.8235 | 48 | 0.6888 | 0.4526 | 0.6888 |
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+ | No log | 2.9412 | 50 | 0.6594 | 0.4838 | 0.6594 |
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+ | No log | 3.0588 | 52 | 0.5913 | 0.5174 | 0.5913 |
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+ | No log | 3.1765 | 54 | 0.5440 | 0.5485 | 0.5440 |
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+ | No log | 3.2941 | 56 | 0.5766 | 0.5008 | 0.5766 |
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+ | No log | 3.4118 | 58 | 0.7541 | 0.4405 | 0.7541 |
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+ | No log | 3.5294 | 60 | 0.6666 | 0.4686 | 0.6666 |
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+ | No log | 3.6471 | 62 | 0.5454 | 0.5289 | 0.5454 |
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+ | No log | 3.7647 | 64 | 0.5373 | 0.5502 | 0.5373 |
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+ | No log | 3.8824 | 66 | 0.5811 | 0.4814 | 0.5811 |
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+ | No log | 4.0 | 68 | 0.8522 | 0.3958 | 0.8522 |
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+ | No log | 4.1176 | 70 | 0.9611 | 0.3420 | 0.9611 |
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+ | No log | 4.2353 | 72 | 0.7150 | 0.4366 | 0.7150 |
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+ | No log | 4.3529 | 74 | 0.5129 | 0.5461 | 0.5129 |
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+ | No log | 4.4706 | 76 | 0.5130 | 0.5731 | 0.5130 |
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+ | No log | 4.5882 | 78 | 0.5549 | 0.5002 | 0.5549 |
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+ | No log | 4.7059 | 80 | 0.6423 | 0.4682 | 0.6423 |
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+ | No log | 4.8235 | 82 | 0.6433 | 0.4655 | 0.6433 |
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+ | No log | 4.9412 | 84 | 0.6814 | 0.4383 | 0.6814 |
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+ | No log | 5.0588 | 86 | 0.6506 | 0.4536 | 0.6506 |
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+ | No log | 5.1765 | 88 | 0.6845 | 0.4340 | 0.6845 |
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+ | No log | 5.2941 | 90 | 0.6105 | 0.4691 | 0.6105 |
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+ | No log | 5.4118 | 92 | 0.5818 | 0.5096 | 0.5818 |
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+ | No log | 5.5294 | 94 | 0.6505 | 0.4675 | 0.6505 |
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+ | No log | 5.6471 | 96 | 0.8762 | 0.4031 | 0.8762 |
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+ | No log | 5.7647 | 98 | 0.9354 | 0.3979 | 0.9354 |
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+ | No log | 5.8824 | 100 | 0.7273 | 0.4370 | 0.7273 |
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+ | No log | 6.0 | 102 | 0.5439 | 0.5370 | 0.5439 |
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+ | No log | 6.1176 | 104 | 0.5275 | 0.5934 | 0.5275 |
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+ | No log | 6.2353 | 106 | 0.5389 | 0.5407 | 0.5389 |
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+ | No log | 6.3529 | 108 | 0.6632 | 0.4439 | 0.6632 |
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+ | No log | 6.4706 | 110 | 0.7438 | 0.4262 | 0.7438 |
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+ | No log | 6.5882 | 112 | 0.7194 | 0.4386 | 0.7194 |
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+ | No log | 6.7059 | 114 | 0.6649 | 0.4611 | 0.6649 |
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+ | No log | 6.8235 | 116 | 0.6469 | 0.4620 | 0.6469 |
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+ | No log | 6.9412 | 118 | 0.6869 | 0.4426 | 0.6869 |
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+ | No log | 7.0588 | 120 | 0.6784 | 0.4431 | 0.6784 |
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+ | No log | 7.1765 | 122 | 0.6099 | 0.4604 | 0.6099 |
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+ | No log | 7.2941 | 124 | 0.6103 | 0.4469 | 0.6103 |
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+ | No log | 7.4118 | 126 | 0.6514 | 0.4384 | 0.6514 |
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+ | No log | 7.5294 | 128 | 0.7174 | 0.4218 | 0.7174 |
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+ | No log | 7.6471 | 130 | 0.7205 | 0.4218 | 0.7205 |
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+ | No log | 7.7647 | 132 | 0.6510 | 0.4378 | 0.6510 |
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+ | No log | 7.8824 | 134 | 0.5851 | 0.4688 | 0.5851 |
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+ | No log | 8.0 | 136 | 0.5810 | 0.4909 | 0.5810 |
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+ | No log | 8.1176 | 138 | 0.6226 | 0.4464 | 0.6226 |
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+ | No log | 8.2353 | 140 | 0.7068 | 0.4404 | 0.7068 |
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+ | No log | 8.3529 | 142 | 0.8169 | 0.4120 | 0.8169 |
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+ | No log | 8.4706 | 144 | 0.8268 | 0.4106 | 0.8268 |
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+ | No log | 8.5882 | 146 | 0.7821 | 0.4211 | 0.7821 |
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+ | No log | 8.7059 | 148 | 0.7186 | 0.4252 | 0.7186 |
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+ | No log | 8.8235 | 150 | 0.6896 | 0.4345 | 0.6896 |
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+ | No log | 8.9412 | 152 | 0.6602 | 0.4409 | 0.6602 |
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+ | No log | 9.0588 | 154 | 0.6525 | 0.4435 | 0.6525 |
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+ | No log | 9.1765 | 156 | 0.6577 | 0.4435 | 0.6577 |
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+ | No log | 9.2941 | 158 | 0.6779 | 0.4325 | 0.6779 |
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+ | No log | 9.4118 | 160 | 0.7177 | 0.4166 | 0.7177 |
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+ | No log | 9.5294 | 162 | 0.7502 | 0.4106 | 0.7502 |
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+ | No log | 9.6471 | 164 | 0.7522 | 0.4057 | 0.7522 |
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+ | No log | 9.7647 | 166 | 0.7503 | 0.4106 | 0.7503 |
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+ | No log | 9.8824 | 168 | 0.7475 | 0.4150 | 0.7475 |
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+ | No log | 10.0 | 170 | 0.7438 | 0.4143 | 0.7438 |
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  ### Framework versions
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