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arabert_cross_relevance_task1_fold1

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  1. README.md +85 -41
  2. model.safetensors +1 -1
  3. runs/Sep02_02-03-55_a09311c9b42d/events.out.tfevents.1725242637.a09311c9b42d.22.0 +3 -0
  4. runs/Sep02_02-03-55_a09311c9b42d/events.out.tfevents.1725243376.a09311c9b42d.22.1 +3 -0
  5. runs/Sep02_02-16-18_a09311c9b42d/events.out.tfevents.1725243379.a09311c9b42d.22.2 +3 -0
  6. 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_relevance_task1_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_relevance_task1_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: 0.3646
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- - Qwk: 0.0454
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- - Mse: 0.3647
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  ## Model description
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@@ -36,48 +36,92 @@ 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 | 0.0323 | 2 | 0.3884 | -0.0193 | 0.3901 |
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- | No log | 0.0645 | 4 | 0.5676 | 0.0570 | 0.5677 |
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- | No log | 0.0968 | 6 | 0.6160 | 0.1181 | 0.6161 |
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- | No log | 0.1290 | 8 | 0.3914 | 0.0326 | 0.3913 |
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- | No log | 0.1613 | 10 | 0.2970 | 0.0245 | 0.2972 |
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- | No log | 0.1935 | 12 | 0.3016 | 0.0122 | 0.3018 |
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- | No log | 0.2258 | 14 | 0.2905 | 0.0122 | 0.2908 |
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- | No log | 0.2581 | 16 | 0.3013 | 0.0491 | 0.3016 |
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- | No log | 0.2903 | 18 | 0.3427 | 0.0284 | 0.3429 |
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- | No log | 0.3226 | 20 | 0.4170 | 0.0059 | 0.4170 |
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- | No log | 0.3548 | 22 | 0.4971 | 0.0518 | 0.4971 |
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- | No log | 0.3871 | 24 | 0.4934 | 0.0958 | 0.4933 |
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- | No log | 0.4194 | 26 | 0.4203 | -0.0430 | 0.4203 |
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- | No log | 0.4516 | 28 | 0.3668 | -0.0521 | 0.3669 |
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- | No log | 0.4839 | 30 | 0.3462 | -0.0092 | 0.3463 |
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- | No log | 0.5161 | 32 | 0.3500 | -0.0092 | 0.3500 |
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- | No log | 0.5484 | 34 | 0.3623 | -0.0010 | 0.3623 |
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- | No log | 0.5806 | 36 | 0.3911 | -0.0188 | 0.3911 |
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- | No log | 0.6129 | 38 | 0.3635 | -0.0135 | 0.3634 |
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- | No log | 0.6452 | 40 | 0.3500 | -0.0092 | 0.3500 |
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- | No log | 0.6774 | 42 | 0.3369 | -0.0048 | 0.3369 |
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- | No log | 0.7097 | 44 | 0.3357 | -0.0048 | 0.3358 |
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- | No log | 0.7419 | 46 | 0.3574 | 0.0537 | 0.3574 |
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- | No log | 0.7742 | 48 | 0.3901 | 0.0370 | 0.3901 |
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- | No log | 0.8065 | 50 | 0.3986 | 0.0723 | 0.3985 |
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- | No log | 0.8387 | 52 | 0.3875 | 0.0544 | 0.3875 |
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- | No log | 0.8710 | 54 | 0.3792 | 0.0586 | 0.3792 |
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- | No log | 0.9032 | 56 | 0.3727 | 0.0412 | 0.3727 |
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- | No log | 0.9355 | 58 | 0.3667 | 0.0454 | 0.3667 |
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- | No log | 0.9677 | 60 | 0.3648 | 0.0454 | 0.3648 |
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- | No log | 1.0 | 62 | 0.3646 | 0.0454 | 0.3647 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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_relevance_task1_fold0
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  results: []
8
  ---
9
 
10
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
11
  should probably proofread and complete it, then remove this comment. -->
12
 
13
+ # arabert_cross_relevance_task1_fold0
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15
  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: 0.2694
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+ - Qwk: 0.0109
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+ - Mse: 0.2694
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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 | 0.1333 | 2 | 2.2712 | 0.0 | 2.2712 |
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+ | No log | 0.2667 | 4 | 0.8815 | 0.0019 | 0.8815 |
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+ | No log | 0.4 | 6 | 0.2576 | 0.0339 | 0.2576 |
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+ | No log | 0.5333 | 8 | 0.2104 | 0.0276 | 0.2104 |
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+ | No log | 0.6667 | 10 | 0.3374 | 0.0345 | 0.3374 |
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+ | No log | 0.8 | 12 | 0.2690 | 0.0323 | 0.2690 |
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+ | No log | 0.9333 | 14 | 0.1682 | 0.0249 | 0.1682 |
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+ | No log | 1.0667 | 16 | 0.1503 | 0.0339 | 0.1503 |
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+ | No log | 1.2 | 18 | 0.1672 | 0.0339 | 0.1672 |
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+ | No log | 1.3333 | 20 | 0.2563 | 0.0263 | 0.2563 |
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+ | No log | 1.4667 | 22 | 0.3596 | 0.0519 | 0.3596 |
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+ | No log | 1.6 | 24 | 0.3144 | 0.0507 | 0.3144 |
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+ | No log | 1.7333 | 26 | 0.1940 | 0.0263 | 0.1940 |
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+ | No log | 1.8667 | 28 | 0.1460 | 0.0400 | 0.1460 |
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+ | No log | 2.0 | 30 | 0.1369 | 0.0364 | 0.1369 |
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+ | No log | 2.1333 | 32 | 0.1324 | 0.0372 | 0.1324 |
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+ | No log | 2.2667 | 34 | 0.1415 | 0.0339 | 0.1415 |
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+ | No log | 2.4 | 36 | 0.1809 | 0.0339 | 0.1809 |
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+ | No log | 2.5333 | 38 | 0.2294 | 0.0339 | 0.2294 |
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+ | No log | 2.6667 | 40 | 0.2654 | 0.0281 | 0.2654 |
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+ | No log | 2.8 | 42 | 0.2940 | 0.0245 | 0.2940 |
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+ | No log | 2.9333 | 44 | 0.2676 | 0.0245 | 0.2676 |
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+ | No log | 3.0667 | 46 | 0.2359 | 0.0245 | 0.2359 |
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+ | No log | 3.2 | 48 | 0.2040 | 0.0263 | 0.2040 |
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+ | No log | 3.3333 | 50 | 0.1696 | 0.0300 | 0.1696 |
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+ | No log | 3.4667 | 52 | 0.1616 | 0.0339 | 0.1616 |
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+ | No log | 3.6 | 54 | 0.1702 | 0.0319 | 0.1702 |
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+ | No log | 3.7333 | 56 | 0.2010 | 0.0281 | 0.2010 |
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+ | No log | 3.8667 | 58 | 0.2570 | 0.0228 | 0.2570 |
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+ | No log | 4.0 | 60 | 0.3107 | 0.0327 | 0.3107 |
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+ | No log | 4.1333 | 62 | 0.3132 | 0.0327 | 0.3132 |
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+ | No log | 4.2667 | 64 | 0.2646 | 0.0288 | 0.2646 |
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+ | No log | 4.4 | 66 | 0.2086 | 0.0263 | 0.2086 |
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+ | No log | 4.5333 | 68 | 0.1708 | 0.0300 | 0.1708 |
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+ | No log | 4.6667 | 70 | 0.1646 | 0.0179 | 0.1646 |
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+ | No log | 4.8 | 72 | 0.1786 | 0.0144 | 0.1786 |
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+ | No log | 4.9333 | 74 | 0.2198 | 0.0281 | 0.2198 |
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+ | No log | 5.0667 | 76 | 0.2585 | 0.0245 | 0.2585 |
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+ | No log | 5.2 | 78 | 0.2513 | 0.0263 | 0.2513 |
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+ | No log | 5.3333 | 80 | 0.2441 | 0.0263 | 0.2441 |
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+ | No log | 5.4667 | 82 | 0.2186 | 0.0197 | 0.2186 |
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+ | No log | 5.6 | 84 | 0.2061 | 0.0197 | 0.2061 |
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+ | No log | 5.7333 | 86 | 0.2178 | 0.0197 | 0.2178 |
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+ | No log | 5.8667 | 88 | 0.2322 | 0.0197 | 0.2322 |
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+ | No log | 6.0 | 90 | 0.2425 | 0.0245 | 0.2425 |
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+ | No log | 6.1333 | 92 | 0.2585 | 0.0245 | 0.2585 |
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+ | No log | 6.2667 | 94 | 0.2369 | 0.0195 | 0.2369 |
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+ | No log | 6.4 | 96 | 0.2110 | 0.0158 | 0.2110 |
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+ | No log | 6.5333 | 98 | 0.2006 | 0.0158 | 0.2006 |
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+ | No log | 6.6667 | 100 | 0.2175 | 0.0158 | 0.2175 |
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+ | No log | 6.8 | 102 | 0.2464 | 0.0210 | 0.2464 |
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+ | No log | 6.9333 | 104 | 0.2615 | 0.0225 | 0.2615 |
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+ | No log | 7.0667 | 106 | 0.2784 | 0.0288 | 0.2784 |
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+ | No log | 7.2 | 108 | 0.2991 | 0.0327 | 0.2991 |
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+ | No log | 7.3333 | 110 | 0.2942 | 0.0327 | 0.2942 |
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+ | No log | 7.4667 | 112 | 0.3083 | 0.0399 | 0.3083 |
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+ | No log | 7.6 | 114 | 0.2910 | 0.0221 | 0.2910 |
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+ | No log | 7.7333 | 116 | 0.2561 | 0.0093 | 0.2561 |
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+ | No log | 7.8667 | 118 | 0.2246 | 0.0125 | 0.2246 |
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+ | No log | 8.0 | 120 | 0.2152 | 0.0156 | 0.2152 |
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+ | No log | 8.1333 | 122 | 0.2131 | 0.0156 | 0.2131 |
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+ | No log | 8.2667 | 124 | 0.2238 | 0.0140 | 0.2238 |
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+ | No log | 8.4 | 126 | 0.2341 | 0.0123 | 0.2341 |
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+ | No log | 8.5333 | 128 | 0.2459 | 0.0123 | 0.2459 |
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+ | No log | 8.6667 | 130 | 0.2510 | 0.0123 | 0.2510 |
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+ | No log | 8.8 | 132 | 0.2702 | 0.0109 | 0.2702 |
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+ | No log | 8.9333 | 134 | 0.2776 | 0.0093 | 0.2776 |
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+ | No log | 9.0667 | 136 | 0.2862 | 0.0173 | 0.2862 |
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+ | No log | 9.2 | 138 | 0.2916 | 0.0158 | 0.2916 |
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+ | No log | 9.3333 | 140 | 0.2853 | 0.0158 | 0.2853 |
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+ | No log | 9.4667 | 142 | 0.2781 | 0.0173 | 0.2781 |
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+ | No log | 9.6 | 144 | 0.2737 | 0.0093 | 0.2737 |
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+ | No log | 9.7333 | 146 | 0.2709 | 0.0109 | 0.2709 |
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+ | No log | 9.8667 | 148 | 0.2693 | 0.0109 | 0.2693 |
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+ | No log | 10.0 | 150 | 0.2694 | 0.0109 | 0.2694 |
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  ### Framework versions
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