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arabert_cross_organization_task3_fold6

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  1. README.md +90 -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_task3_fold6
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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_fold6
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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: 0.5055
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- - Qwk: 0.5838
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- - Mse: 0.5052
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  ## Model description
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@@ -36,50 +36,97 @@ 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 | 0.0299 | 2 | 3.5113 | 0.0 | 3.5012 |
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- | No log | 0.0597 | 4 | 1.9058 | 0.1074 | 1.9002 |
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- | No log | 0.0896 | 6 | 1.0816 | 0.0978 | 1.0751 |
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- | No log | 0.1194 | 8 | 0.7956 | 0.4578 | 0.7887 |
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- | No log | 0.1493 | 10 | 0.7778 | 0.4834 | 0.7681 |
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- | No log | 0.1791 | 12 | 0.6588 | 0.5105 | 0.6489 |
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- | No log | 0.2090 | 14 | 0.7969 | 0.3865 | 0.7861 |
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- | No log | 0.2388 | 16 | 0.6719 | 0.4465 | 0.6665 |
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- | No log | 0.2687 | 18 | 1.4069 | 0.2490 | 1.3984 |
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- | No log | 0.2985 | 20 | 1.2196 | 0.2926 | 1.2121 |
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- | No log | 0.3284 | 22 | 0.5219 | 0.5519 | 0.5201 |
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- | No log | 0.3582 | 24 | 0.5779 | 0.7451 | 0.5779 |
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- | No log | 0.3881 | 26 | 0.5746 | 0.7696 | 0.5748 |
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- | No log | 0.4179 | 28 | 0.4534 | 0.6761 | 0.4523 |
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- | No log | 0.4478 | 30 | 0.6625 | 0.4658 | 0.6566 |
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- | No log | 0.4776 | 32 | 0.8391 | 0.3869 | 0.8326 |
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- | No log | 0.5075 | 34 | 0.6755 | 0.4375 | 0.6702 |
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- | No log | 0.5373 | 36 | 0.4815 | 0.5595 | 0.4784 |
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- | No log | 0.5672 | 38 | 0.4369 | 0.6522 | 0.4358 |
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- | No log | 0.5970 | 40 | 0.4525 | 0.7048 | 0.4524 |
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- | No log | 0.6269 | 42 | 0.4649 | 0.7361 | 0.4651 |
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- | No log | 0.6567 | 44 | 0.4373 | 0.7009 | 0.4376 |
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- | No log | 0.6866 | 46 | 0.4217 | 0.6875 | 0.4219 |
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- | No log | 0.7164 | 48 | 0.4478 | 0.6136 | 0.4477 |
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- | No log | 0.7463 | 50 | 0.4810 | 0.5861 | 0.4808 |
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- | No log | 0.7761 | 52 | 0.4821 | 0.6102 | 0.4823 |
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- | No log | 0.8060 | 54 | 0.4926 | 0.6087 | 0.4928 |
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- | No log | 0.8358 | 56 | 0.4939 | 0.6129 | 0.4942 |
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- | No log | 0.8657 | 58 | 0.4991 | 0.5907 | 0.4993 |
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- | No log | 0.8955 | 60 | 0.5140 | 0.5830 | 0.5138 |
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- | No log | 0.9254 | 62 | 0.5151 | 0.5761 | 0.5147 |
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- | No log | 0.9552 | 64 | 0.5062 | 0.5838 | 0.5059 |
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- | No log | 0.9851 | 66 | 0.5055 | 0.5838 | 0.5052 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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_fold5
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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_fold5
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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: 0.4649
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+ - Qwk: 0.6602
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+ - Mse: 0.4652
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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 | 0.125 | 2 | 1.3614 | 0.1417 | 1.3607 |
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+ | No log | 0.25 | 4 | 0.9919 | 0.1465 | 0.9922 |
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+ | No log | 0.375 | 6 | 0.7852 | 0.5086 | 0.7857 |
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+ | No log | 0.5 | 8 | 0.8360 | 0.6182 | 0.8371 |
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+ | No log | 0.625 | 10 | 0.6409 | 0.7584 | 0.6421 |
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+ | No log | 0.75 | 12 | 0.5760 | 0.6105 | 0.5765 |
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+ | No log | 0.875 | 14 | 0.5769 | 0.7460 | 0.5780 |
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+ | No log | 1.0 | 16 | 0.5277 | 0.7247 | 0.5287 |
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+ | No log | 1.125 | 18 | 0.5309 | 0.7698 | 0.5319 |
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+ | No log | 1.25 | 20 | 0.6352 | 0.7920 | 0.6365 |
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+ | No log | 1.375 | 22 | 0.4636 | 0.6839 | 0.4644 |
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+ | No log | 1.5 | 24 | 0.4773 | 0.7038 | 0.4782 |
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+ | No log | 1.625 | 26 | 0.5174 | 0.7610 | 0.5185 |
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+ | No log | 1.75 | 28 | 0.5482 | 0.7835 | 0.5494 |
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+ | No log | 1.875 | 30 | 0.4822 | 0.7417 | 0.4830 |
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+ | No log | 2.0 | 32 | 0.4561 | 0.6787 | 0.4566 |
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+ | No log | 2.125 | 34 | 0.4716 | 0.7343 | 0.4723 |
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+ | No log | 2.25 | 36 | 0.5650 | 0.7930 | 0.5660 |
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+ | No log | 2.375 | 38 | 0.4723 | 0.7646 | 0.4729 |
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+ | No log | 2.5 | 40 | 0.4662 | 0.6525 | 0.4664 |
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+ | No log | 2.625 | 42 | 0.4420 | 0.7033 | 0.4425 |
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+ | No log | 2.75 | 44 | 0.5038 | 0.7717 | 0.5047 |
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+ | No log | 2.875 | 46 | 0.5557 | 0.7833 | 0.5567 |
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+ | No log | 3.0 | 48 | 0.4661 | 0.7378 | 0.4667 |
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+ | No log | 3.125 | 50 | 0.4772 | 0.6547 | 0.4774 |
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+ | No log | 3.25 | 52 | 0.4713 | 0.6765 | 0.4715 |
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+ | No log | 3.375 | 54 | 0.4755 | 0.7516 | 0.4761 |
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+ | No log | 3.5 | 56 | 0.4959 | 0.7626 | 0.4966 |
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+ | No log | 3.625 | 58 | 0.4637 | 0.7460 | 0.4642 |
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+ | No log | 3.75 | 60 | 0.4762 | 0.7443 | 0.4768 |
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+ | No log | 3.875 | 62 | 0.4669 | 0.7437 | 0.4674 |
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+ | No log | 4.0 | 64 | 0.4555 | 0.7387 | 0.4559 |
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+ | No log | 4.125 | 66 | 0.4440 | 0.7154 | 0.4444 |
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+ | No log | 4.25 | 68 | 0.4456 | 0.6951 | 0.4460 |
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+ | No log | 4.375 | 70 | 0.4452 | 0.7223 | 0.4457 |
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+ | No log | 4.5 | 72 | 0.4717 | 0.7461 | 0.4723 |
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+ | No log | 4.625 | 74 | 0.4611 | 0.7342 | 0.4616 |
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+ | No log | 4.75 | 76 | 0.4659 | 0.7176 | 0.4664 |
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+ | No log | 4.875 | 78 | 0.4599 | 0.7400 | 0.4604 |
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+ | No log | 5.0 | 80 | 0.4602 | 0.7421 | 0.4608 |
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+ | No log | 5.125 | 82 | 0.4454 | 0.7202 | 0.4458 |
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+ | No log | 5.25 | 84 | 0.4601 | 0.6651 | 0.4603 |
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+ | No log | 5.375 | 86 | 0.4520 | 0.6947 | 0.4522 |
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+ | No log | 5.5 | 88 | 0.4471 | 0.7201 | 0.4474 |
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+ | No log | 5.625 | 90 | 0.4466 | 0.6992 | 0.4469 |
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+ | No log | 5.75 | 92 | 0.4632 | 0.6619 | 0.4633 |
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+ | No log | 5.875 | 94 | 0.4736 | 0.6395 | 0.4737 |
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+ | No log | 6.0 | 96 | 0.4485 | 0.6918 | 0.4488 |
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+ | No log | 6.125 | 98 | 0.4448 | 0.7136 | 0.4453 |
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+ | No log | 6.25 | 100 | 0.4413 | 0.6987 | 0.4417 |
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+ | No log | 6.375 | 102 | 0.4402 | 0.7137 | 0.4406 |
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+ | No log | 6.5 | 104 | 0.4399 | 0.7159 | 0.4404 |
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+ | No log | 6.625 | 106 | 0.4462 | 0.7259 | 0.4467 |
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+ | No log | 6.75 | 108 | 0.4442 | 0.7166 | 0.4447 |
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+ | No log | 6.875 | 110 | 0.4566 | 0.6877 | 0.4570 |
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+ | No log | 7.0 | 112 | 0.4729 | 0.6802 | 0.4732 |
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+ | No log | 7.125 | 114 | 0.4857 | 0.6695 | 0.4859 |
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+ | No log | 7.25 | 116 | 0.4685 | 0.7000 | 0.4689 |
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+ | No log | 7.375 | 118 | 0.4610 | 0.7218 | 0.4616 |
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+ | No log | 7.5 | 120 | 0.4550 | 0.7174 | 0.4555 |
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+ | No log | 7.625 | 122 | 0.4572 | 0.6892 | 0.4576 |
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+ | No log | 7.75 | 124 | 0.4506 | 0.7015 | 0.4510 |
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+ | No log | 7.875 | 126 | 0.4454 | 0.7045 | 0.4459 |
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+ | No log | 8.0 | 128 | 0.4457 | 0.7284 | 0.4464 |
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+ | No log | 8.125 | 130 | 0.4455 | 0.7283 | 0.4461 |
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+ | No log | 8.25 | 132 | 0.4411 | 0.7309 | 0.4416 |
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+ | No log | 8.375 | 134 | 0.4413 | 0.7252 | 0.4418 |
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+ | No log | 8.5 | 136 | 0.4455 | 0.6852 | 0.4459 |
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+ | No log | 8.625 | 138 | 0.4564 | 0.6632 | 0.4567 |
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+ | No log | 8.75 | 140 | 0.4538 | 0.6632 | 0.4541 |
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+ | No log | 8.875 | 142 | 0.4468 | 0.7039 | 0.4473 |
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+ | No log | 9.0 | 144 | 0.4474 | 0.7177 | 0.4479 |
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+ | No log | 9.125 | 146 | 0.4490 | 0.7156 | 0.4496 |
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+ | No log | 9.25 | 148 | 0.4504 | 0.7156 | 0.4510 |
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+ | No log | 9.375 | 150 | 0.4516 | 0.7127 | 0.4521 |
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+ | No log | 9.5 | 152 | 0.4547 | 0.6898 | 0.4551 |
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+ | No log | 9.625 | 154 | 0.4599 | 0.6702 | 0.4603 |
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+ | No log | 9.75 | 156 | 0.4646 | 0.6602 | 0.4649 |
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+ | No log | 9.875 | 158 | 0.4655 | 0.6602 | 0.4658 |
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+ | No log | 10.0 | 160 | 0.4649 | 0.6602 | 0.4652 |
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  ### Framework versions
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