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arabert_cross_organization_task2_fold5

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  1. README.md +90 -38
  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_task2_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_task2_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: 0.5338
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- - Qwk: 0.6563
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- - Mse: 0.5338
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  ## Model description
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@@ -36,45 +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 | 0.0351 | 2 | 1.4933 | 0.0796 | 1.4933 |
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- | No log | 0.0702 | 4 | 1.0985 | 0.2006 | 1.0985 |
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- | No log | 0.1053 | 6 | 0.8563 | 0.5811 | 0.8563 |
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- | No log | 0.1404 | 8 | 0.8377 | 0.5890 | 0.8377 |
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- | No log | 0.1754 | 10 | 1.0313 | 0.6686 | 1.0313 |
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- | No log | 0.2105 | 12 | 1.0210 | 0.6960 | 1.0210 |
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- | No log | 0.2456 | 14 | 0.8872 | 0.7330 | 0.8872 |
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- | No log | 0.2807 | 16 | 0.6636 | 0.7027 | 0.6636 |
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- | No log | 0.3158 | 18 | 0.5884 | 0.6640 | 0.5884 |
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- | No log | 0.3509 | 20 | 0.5966 | 0.6545 | 0.5966 |
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- | No log | 0.3860 | 22 | 0.6144 | 0.7166 | 0.6144 |
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- | No log | 0.4211 | 24 | 0.6400 | 0.7196 | 0.6400 |
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- | No log | 0.4561 | 26 | 0.6245 | 0.7154 | 0.6245 |
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- | No log | 0.4912 | 28 | 0.5935 | 0.6768 | 0.5935 |
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- | No log | 0.5263 | 30 | 0.6015 | 0.6341 | 0.6015 |
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- | No log | 0.5614 | 32 | 0.5935 | 0.6802 | 0.5935 |
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- | No log | 0.5965 | 34 | 0.6388 | 0.7358 | 0.6388 |
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- | No log | 0.6316 | 36 | 0.7400 | 0.7569 | 0.7400 |
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- | No log | 0.6667 | 38 | 0.7588 | 0.7466 | 0.7588 |
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- | No log | 0.7018 | 40 | 0.7102 | 0.7380 | 0.7102 |
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- | No log | 0.7368 | 42 | 0.6395 | 0.7193 | 0.6395 |
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- | No log | 0.7719 | 44 | 0.5860 | 0.6989 | 0.5860 |
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- | No log | 0.8070 | 46 | 0.5570 | 0.6637 | 0.5570 |
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- | No log | 0.8421 | 48 | 0.5375 | 0.6563 | 0.5375 |
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- | No log | 0.8772 | 50 | 0.5297 | 0.6484 | 0.5297 |
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- | No log | 0.9123 | 52 | 0.5288 | 0.6484 | 0.5288 |
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- | No log | 0.9474 | 54 | 0.5317 | 0.6543 | 0.5317 |
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- | No log | 0.9825 | 56 | 0.5338 | 0.6563 | 0.5338 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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_task2_fold4
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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_task2_fold4
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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: 0.4343
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+ - Qwk: 0.7442
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+ - Mse: 0.4343
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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 | 3.0559 | 0.0132 | 3.0559 |
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+ | No log | 0.25 | 4 | 1.5018 | 0.1018 | 1.5018 |
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+ | No log | 0.375 | 6 | 0.9403 | 0.3496 | 0.9403 |
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+ | No log | 0.5 | 8 | 1.0512 | 0.4227 | 1.0512 |
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+ | No log | 0.625 | 10 | 0.7038 | 0.5121 | 0.7038 |
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+ | No log | 0.75 | 12 | 0.7727 | 0.4566 | 0.7727 |
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+ | No log | 0.875 | 14 | 0.5989 | 0.5213 | 0.5989 |
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+ | No log | 1.0 | 16 | 0.6428 | 0.6397 | 0.6428 |
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+ | No log | 1.125 | 18 | 0.6331 | 0.7095 | 0.6331 |
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+ | No log | 1.25 | 20 | 0.5024 | 0.6478 | 0.5024 |
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+ | No log | 1.375 | 22 | 0.7624 | 0.4770 | 0.7624 |
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+ | No log | 1.5 | 24 | 0.5793 | 0.5485 | 0.5793 |
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+ | No log | 1.625 | 26 | 0.4887 | 0.6546 | 0.4887 |
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+ | No log | 1.75 | 28 | 0.5482 | 0.6854 | 0.5482 |
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+ | No log | 1.875 | 30 | 0.5328 | 0.7446 | 0.5328 |
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+ | No log | 2.0 | 32 | 0.4476 | 0.6785 | 0.4476 |
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+ | No log | 2.125 | 34 | 0.5184 | 0.5745 | 0.5184 |
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+ | No log | 2.25 | 36 | 0.4772 | 0.6201 | 0.4772 |
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+ | No log | 2.375 | 38 | 0.4229 | 0.7095 | 0.4229 |
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+ | No log | 2.5 | 40 | 0.4747 | 0.7500 | 0.4747 |
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+ | No log | 2.625 | 42 | 0.4556 | 0.7201 | 0.4556 |
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+ | No log | 2.75 | 44 | 0.4703 | 0.6407 | 0.4703 |
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+ | No log | 2.875 | 46 | 0.4875 | 0.6566 | 0.4875 |
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+ | No log | 3.0 | 48 | 0.5070 | 0.7290 | 0.5070 |
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+ | No log | 3.125 | 50 | 0.4950 | 0.7764 | 0.4950 |
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+ | No log | 3.25 | 52 | 0.4192 | 0.7444 | 0.4192 |
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+ | No log | 3.375 | 54 | 0.4132 | 0.6919 | 0.4132 |
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+ | No log | 3.5 | 56 | 0.4024 | 0.7128 | 0.4024 |
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+ | No log | 3.625 | 58 | 0.4094 | 0.7451 | 0.4094 |
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+ | No log | 3.75 | 60 | 0.4675 | 0.7828 | 0.4675 |
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+ | No log | 3.875 | 62 | 0.4559 | 0.7636 | 0.4559 |
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+ | No log | 4.0 | 64 | 0.4150 | 0.7449 | 0.4150 |
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+ | No log | 4.125 | 66 | 0.3994 | 0.7551 | 0.3994 |
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+ | No log | 4.25 | 68 | 0.3872 | 0.7513 | 0.3872 |
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+ | No log | 4.375 | 70 | 0.3951 | 0.7719 | 0.3951 |
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+ | No log | 4.5 | 72 | 0.4536 | 0.7801 | 0.4536 |
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+ | No log | 4.625 | 74 | 0.4695 | 0.7891 | 0.4695 |
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+ | No log | 4.75 | 76 | 0.4253 | 0.7787 | 0.4253 |
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+ | No log | 4.875 | 78 | 0.3967 | 0.7809 | 0.3967 |
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+ | No log | 5.0 | 80 | 0.3954 | 0.7506 | 0.3954 |
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+ | No log | 5.125 | 82 | 0.4062 | 0.7844 | 0.4062 |
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+ | No log | 5.25 | 84 | 0.4096 | 0.7688 | 0.4096 |
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+ | No log | 5.375 | 86 | 0.4305 | 0.7167 | 0.4305 |
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+ | No log | 5.5 | 88 | 0.4607 | 0.6647 | 0.4607 |
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+ | No log | 5.625 | 90 | 0.4776 | 0.6876 | 0.4776 |
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+ | No log | 5.75 | 92 | 0.4996 | 0.7150 | 0.4996 |
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+ | No log | 5.875 | 94 | 0.5241 | 0.7677 | 0.5241 |
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+ | No log | 6.0 | 96 | 0.5059 | 0.7933 | 0.5059 |
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+ | No log | 6.125 | 98 | 0.4470 | 0.7830 | 0.4470 |
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+ | No log | 6.25 | 100 | 0.4010 | 0.7665 | 0.4010 |
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+ | No log | 6.375 | 102 | 0.4147 | 0.6921 | 0.4147 |
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+ | No log | 6.5 | 104 | 0.4226 | 0.6845 | 0.4226 |
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+ | No log | 6.625 | 106 | 0.4193 | 0.7197 | 0.4193 |
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+ | No log | 6.75 | 108 | 0.4395 | 0.7571 | 0.4395 |
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+ | No log | 6.875 | 110 | 0.4602 | 0.7536 | 0.4602 |
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+ | No log | 7.0 | 112 | 0.4569 | 0.7332 | 0.4569 |
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+ | No log | 7.125 | 114 | 0.4359 | 0.7109 | 0.4359 |
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+ | No log | 7.25 | 116 | 0.4245 | 0.7097 | 0.4245 |
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+ | No log | 7.375 | 118 | 0.4142 | 0.7397 | 0.4142 |
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+ | No log | 7.5 | 120 | 0.4102 | 0.7558 | 0.4102 |
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+ | No log | 7.625 | 122 | 0.4179 | 0.7845 | 0.4179 |
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+ | No log | 7.75 | 124 | 0.4170 | 0.7876 | 0.4170 |
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+ | No log | 7.875 | 126 | 0.4173 | 0.7876 | 0.4173 |
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+ | No log | 8.0 | 128 | 0.4157 | 0.7629 | 0.4157 |
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+ | No log | 8.125 | 130 | 0.4165 | 0.7617 | 0.4165 |
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+ | No log | 8.25 | 132 | 0.4198 | 0.7551 | 0.4198 |
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+ | No log | 8.375 | 134 | 0.4256 | 0.7560 | 0.4256 |
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+ | No log | 8.5 | 136 | 0.4285 | 0.7405 | 0.4285 |
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+ | No log | 8.625 | 138 | 0.4320 | 0.7413 | 0.4320 |
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+ | No log | 8.75 | 140 | 0.4361 | 0.7522 | 0.4361 |
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+ | No log | 8.875 | 142 | 0.4387 | 0.7512 | 0.4387 |
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+ | No log | 9.0 | 144 | 0.4377 | 0.7502 | 0.4377 |
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+ | No log | 9.125 | 146 | 0.4356 | 0.7447 | 0.4356 |
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+ | No log | 9.25 | 148 | 0.4354 | 0.7421 | 0.4354 |
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+ | No log | 9.375 | 150 | 0.4355 | 0.7421 | 0.4355 |
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+ | No log | 9.5 | 152 | 0.4365 | 0.7421 | 0.4365 |
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+ | No log | 9.625 | 154 | 0.4364 | 0.7421 | 0.4364 |
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+ | No log | 9.75 | 156 | 0.4354 | 0.7509 | 0.4354 |
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+ | No log | 9.875 | 158 | 0.4347 | 0.7442 | 0.4347 |
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+ | No log | 10.0 | 160 | 0.4343 | 0.7442 | 0.4343 |
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  ### Framework versions
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