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arabert_cross_organization_task4_fold0

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  1. README.md +93 -40
  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_fold0
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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_fold0
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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: 1.1023
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- - Qwk: 0.4017
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- - Mse: 1.1000
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  ## Model description
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@@ -36,49 +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 | 0.0308 | 2 | 5.2466 | 0.0047 | 5.2318 |
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- | No log | 0.0615 | 4 | 3.0149 | 0.0313 | 3.0039 |
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- | No log | 0.0923 | 6 | 1.6670 | 0.1824 | 1.6592 |
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- | No log | 0.1231 | 8 | 1.4331 | 0.2243 | 1.4268 |
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- | No log | 0.1538 | 10 | 1.4489 | 0.2256 | 1.4427 |
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- | No log | 0.1846 | 12 | 1.3526 | 0.2698 | 1.3470 |
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- | No log | 0.2154 | 14 | 1.3686 | 0.3009 | 1.3631 |
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- | No log | 0.2462 | 16 | 1.0285 | 0.4056 | 1.0252 |
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- | No log | 0.2769 | 18 | 0.9867 | 0.4291 | 0.9843 |
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- | No log | 0.3077 | 20 | 1.0798 | 0.3689 | 1.0775 |
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- | No log | 0.3385 | 22 | 1.1705 | 0.3319 | 1.1680 |
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- | No log | 0.3692 | 24 | 1.2867 | 0.3001 | 1.2834 |
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- | No log | 0.4 | 26 | 1.2586 | 0.3019 | 1.2552 |
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- | No log | 0.4308 | 28 | 1.1448 | 0.3398 | 1.1420 |
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- | No log | 0.4615 | 30 | 1.1329 | 0.3524 | 1.1300 |
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- | No log | 0.4923 | 32 | 1.1121 | 0.4110 | 1.1093 |
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- | No log | 0.5231 | 34 | 1.0232 | 0.4460 | 1.0208 |
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- | No log | 0.5538 | 36 | 0.9867 | 0.4624 | 0.9846 |
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- | No log | 0.5846 | 38 | 0.9445 | 0.4961 | 0.9426 |
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- | No log | 0.6154 | 40 | 0.9253 | 0.5188 | 0.9236 |
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- | No log | 0.6462 | 42 | 0.8784 | 0.5424 | 0.8771 |
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- | No log | 0.6769 | 44 | 0.8530 | 0.5649 | 0.8520 |
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- | No log | 0.7077 | 46 | 0.8734 | 0.5542 | 0.8724 |
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- | No log | 0.7385 | 48 | 0.9381 | 0.5209 | 0.9368 |
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- | No log | 0.7692 | 50 | 0.9567 | 0.5068 | 0.9553 |
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- | No log | 0.8 | 52 | 0.9749 | 0.4930 | 0.9733 |
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- | No log | 0.8308 | 54 | 0.9936 | 0.4779 | 0.9918 |
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- | No log | 0.8615 | 56 | 1.0273 | 0.4512 | 1.0254 |
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- | No log | 0.8923 | 58 | 1.0502 | 0.4401 | 1.0482 |
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- | No log | 0.9231 | 60 | 1.0757 | 0.4232 | 1.0735 |
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- | No log | 0.9538 | 62 | 1.0953 | 0.4054 | 1.0930 |
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- | No log | 0.9846 | 64 | 1.1023 | 0.4017 | 1.1000 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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_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: 0.6744
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+ - Qwk: 0.5374
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+ - Mse: 0.6727
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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 | 2.0484 | 0.0727 | 2.0464 |
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+ | No log | 0.2353 | 4 | 1.0229 | 0.2634 | 1.0209 |
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+ | No log | 0.3529 | 6 | 1.0565 | 0.3738 | 1.0563 |
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+ | No log | 0.4706 | 8 | 0.8346 | 0.5570 | 0.8340 |
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+ | No log | 0.5882 | 10 | 0.7369 | 0.3583 | 0.7363 |
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+ | No log | 0.7059 | 12 | 0.6299 | 0.3918 | 0.6296 |
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+ | No log | 0.8235 | 14 | 0.5123 | 0.5734 | 0.5122 |
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+ | No log | 0.9412 | 16 | 0.4760 | 0.6338 | 0.4759 |
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+ | No log | 1.0588 | 18 | 0.4963 | 0.5827 | 0.4956 |
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+ | No log | 1.1765 | 20 | 0.5522 | 0.5578 | 0.5507 |
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+ | No log | 1.2941 | 22 | 0.5052 | 0.6935 | 0.5043 |
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+ | No log | 1.4118 | 24 | 0.4977 | 0.6903 | 0.4967 |
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+ | No log | 1.5294 | 26 | 0.5405 | 0.5739 | 0.5389 |
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+ | No log | 1.6471 | 28 | 0.5155 | 0.5351 | 0.5142 |
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+ | No log | 1.7647 | 30 | 0.4597 | 0.6960 | 0.4592 |
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+ | No log | 1.8824 | 32 | 0.5096 | 0.7559 | 0.5095 |
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+ | No log | 2.0 | 34 | 0.4755 | 0.7285 | 0.4750 |
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+ | No log | 2.1176 | 36 | 0.4913 | 0.5583 | 0.4902 |
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+ | No log | 2.2353 | 38 | 0.5379 | 0.5453 | 0.5365 |
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+ | No log | 2.3529 | 40 | 0.4972 | 0.5887 | 0.4960 |
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+ | No log | 2.4706 | 42 | 0.4876 | 0.6288 | 0.4866 |
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+ | No log | 2.5882 | 44 | 0.4834 | 0.6174 | 0.4824 |
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+ | No log | 2.7059 | 46 | 0.4806 | 0.6244 | 0.4797 |
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+ | No log | 2.8235 | 48 | 0.5129 | 0.5775 | 0.5117 |
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+ | No log | 2.9412 | 50 | 0.5356 | 0.5568 | 0.5343 |
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+ | No log | 3.0588 | 52 | 0.5206 | 0.5719 | 0.5195 |
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+ | No log | 3.1765 | 54 | 0.4824 | 0.6328 | 0.4817 |
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+ | No log | 3.2941 | 56 | 0.4890 | 0.6817 | 0.4886 |
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+ | No log | 3.4118 | 58 | 0.4872 | 0.6139 | 0.4865 |
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+ | No log | 3.5294 | 60 | 0.5427 | 0.5620 | 0.5416 |
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+ | No log | 3.6471 | 62 | 0.5604 | 0.5617 | 0.5591 |
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+ | No log | 3.7647 | 64 | 0.5186 | 0.5723 | 0.5175 |
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+ | No log | 3.8824 | 66 | 0.5145 | 0.5822 | 0.5135 |
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+ | No log | 4.0 | 68 | 0.5162 | 0.5904 | 0.5152 |
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+ | No log | 4.1176 | 70 | 0.5201 | 0.5923 | 0.5191 |
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+ | No log | 4.2353 | 72 | 0.5476 | 0.5839 | 0.5464 |
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+ | No log | 4.3529 | 74 | 0.5528 | 0.5930 | 0.5517 |
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+ | No log | 4.4706 | 76 | 0.5558 | 0.5946 | 0.5547 |
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+ | No log | 4.5882 | 78 | 0.5638 | 0.5843 | 0.5626 |
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+ | No log | 4.7059 | 80 | 0.5691 | 0.5607 | 0.5679 |
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+ | No log | 4.8235 | 82 | 0.6117 | 0.5231 | 0.6104 |
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+ | No log | 4.9412 | 84 | 0.5964 | 0.5445 | 0.5952 |
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+ | No log | 5.0588 | 86 | 0.5870 | 0.5441 | 0.5858 |
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+ | No log | 5.1765 | 88 | 0.5544 | 0.5918 | 0.5534 |
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+ | No log | 5.2941 | 90 | 0.5807 | 0.5683 | 0.5796 |
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+ | No log | 5.4118 | 92 | 0.6445 | 0.5409 | 0.6429 |
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+ | No log | 5.5294 | 94 | 0.6914 | 0.5268 | 0.6896 |
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+ | No log | 5.6471 | 96 | 0.6566 | 0.5829 | 0.6550 |
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+ | No log | 5.7647 | 98 | 0.6232 | 0.5841 | 0.6218 |
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+ | No log | 5.8824 | 100 | 0.6460 | 0.5480 | 0.6445 |
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+ | No log | 6.0 | 102 | 0.7138 | 0.5185 | 0.7121 |
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+ | No log | 6.1176 | 104 | 0.7136 | 0.4997 | 0.7120 |
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+ | No log | 6.2353 | 106 | 0.6311 | 0.5377 | 0.6297 |
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+ | No log | 6.3529 | 108 | 0.5676 | 0.5748 | 0.5666 |
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+ | No log | 6.4706 | 110 | 0.5579 | 0.5804 | 0.5571 |
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+ | No log | 6.5882 | 112 | 0.5941 | 0.5534 | 0.5929 |
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+ | No log | 6.7059 | 114 | 0.6495 | 0.5405 | 0.6479 |
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+ | No log | 6.8235 | 116 | 0.6811 | 0.5303 | 0.6793 |
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+ | No log | 6.9412 | 118 | 0.6469 | 0.5504 | 0.6453 |
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+ | No log | 7.0588 | 120 | 0.6031 | 0.5779 | 0.6018 |
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+ | No log | 7.1765 | 122 | 0.6073 | 0.5800 | 0.6059 |
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+ | No log | 7.2941 | 124 | 0.6215 | 0.5636 | 0.6200 |
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+ | No log | 7.4118 | 126 | 0.6881 | 0.5394 | 0.6862 |
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+ | No log | 7.5294 | 128 | 0.7415 | 0.5163 | 0.7395 |
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+ | No log | 7.6471 | 130 | 0.7372 | 0.5194 | 0.7352 |
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+ | No log | 7.7647 | 132 | 0.6878 | 0.5221 | 0.6860 |
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+ | No log | 7.8824 | 134 | 0.6484 | 0.5397 | 0.6467 |
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+ | No log | 8.0 | 136 | 0.6265 | 0.5443 | 0.6250 |
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+ | No log | 8.1176 | 138 | 0.6341 | 0.5416 | 0.6325 |
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+ | No log | 8.2353 | 140 | 0.6558 | 0.5401 | 0.6541 |
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+ | No log | 8.3529 | 142 | 0.6638 | 0.5263 | 0.6621 |
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+ | No log | 8.4706 | 144 | 0.6606 | 0.5378 | 0.6589 |
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+ | No log | 8.5882 | 146 | 0.6408 | 0.5416 | 0.6392 |
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+ | No log | 8.7059 | 148 | 0.6283 | 0.5514 | 0.6267 |
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+ | No log | 8.8235 | 150 | 0.6390 | 0.5462 | 0.6374 |
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+ | No log | 8.9412 | 152 | 0.6538 | 0.5432 | 0.6522 |
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+ | No log | 9.0588 | 154 | 0.6607 | 0.5432 | 0.6590 |
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+ | No log | 9.1765 | 156 | 0.6707 | 0.5374 | 0.6690 |
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+ | No log | 9.2941 | 158 | 0.6864 | 0.5207 | 0.6846 |
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+ | No log | 9.4118 | 160 | 0.6949 | 0.5207 | 0.6931 |
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+ | No log | 9.5294 | 162 | 0.6950 | 0.5207 | 0.6932 |
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+ | No log | 9.6471 | 164 | 0.6884 | 0.5221 | 0.6866 |
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+ | No log | 9.7647 | 166 | 0.6794 | 0.5336 | 0.6777 |
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+ | No log | 9.8824 | 168 | 0.6756 | 0.5374 | 0.6739 |
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+ | No log | 10.0 | 170 | 0.6744 | 0.5374 | 0.6727 |
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  ### Framework versions
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