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arabert_cross_organization_task5_fold0

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  1. README.md +98 -36
  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_task5_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_task5_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: 1.0616
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- - Qwk: 0.4067
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- - Mse: 1.0582
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  ## Model description
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@@ -36,45 +36,107 @@ 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 | 5.7040 | 0.0041 | 5.6934 |
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- | No log | 0.0702 | 4 | 3.6828 | 0.1020 | 3.6741 |
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- | No log | 0.1053 | 6 | 1.8750 | 0.1959 | 1.8696 |
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- | No log | 0.1404 | 8 | 1.3481 | 0.2058 | 1.3438 |
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- | No log | 0.1754 | 10 | 1.3606 | 0.1303 | 1.3566 |
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- | No log | 0.2105 | 12 | 1.3160 | 0.1531 | 1.3118 |
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- | No log | 0.2456 | 14 | 1.2572 | 0.2212 | 1.2520 |
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- | No log | 0.2807 | 16 | 1.3235 | 0.2768 | 1.3176 |
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- | No log | 0.3158 | 18 | 1.8386 | 0.2517 | 1.8326 |
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- | No log | 0.3509 | 20 | 1.9134 | 0.2575 | 1.9072 |
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- | No log | 0.3860 | 22 | 1.3974 | 0.3300 | 1.3921 |
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- | No log | 0.4211 | 24 | 0.9768 | 0.4013 | 0.9729 |
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- | No log | 0.4561 | 26 | 0.8978 | 0.4336 | 0.8949 |
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- | No log | 0.4912 | 28 | 1.0559 | 0.3347 | 1.0530 |
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- | No log | 0.5263 | 30 | 1.2560 | 0.2634 | 1.2524 |
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- | No log | 0.5614 | 32 | 1.2328 | 0.2771 | 1.2293 |
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- | No log | 0.5965 | 34 | 1.0985 | 0.3080 | 1.0954 |
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- | No log | 0.6316 | 36 | 1.0534 | 0.3590 | 1.0503 |
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- | No log | 0.6667 | 38 | 1.0388 | 0.3636 | 1.0357 |
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- | No log | 0.7018 | 40 | 1.0268 | 0.3817 | 1.0237 |
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- | No log | 0.7368 | 42 | 1.0681 | 0.3831 | 1.0647 |
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- | No log | 0.7719 | 44 | 1.1110 | 0.3989 | 1.1074 |
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- | No log | 0.8070 | 46 | 1.1099 | 0.4060 | 1.1063 |
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- | No log | 0.8421 | 48 | 1.1339 | 0.4078 | 1.1302 |
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- | No log | 0.8772 | 50 | 1.1308 | 0.4017 | 1.1272 |
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- | No log | 0.9123 | 52 | 1.0884 | 0.4022 | 1.0849 |
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- | No log | 0.9474 | 54 | 1.0745 | 0.3960 | 1.0710 |
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- | No log | 0.9825 | 56 | 1.0616 | 0.4067 | 1.0582 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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_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_task4_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: 0.5671
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+ - Qwk: 0.6088
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+ - Mse: 0.5665
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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 | 0.1111 | 2 | 1.6087 | 0.0446 | 1.6095 |
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+ | No log | 0.2222 | 4 | 1.0873 | 0.0325 | 1.0875 |
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+ | No log | 0.3333 | 6 | 0.9052 | 0.3977 | 0.9045 |
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+ | No log | 0.4444 | 8 | 0.7546 | 0.3836 | 0.7542 |
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+ | No log | 0.5556 | 10 | 0.5626 | 0.4920 | 0.5622 |
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+ | No log | 0.6667 | 12 | 0.5049 | 0.6220 | 0.5048 |
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+ | No log | 0.7778 | 14 | 0.6046 | 0.5251 | 0.6033 |
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+ | No log | 0.8889 | 16 | 0.4861 | 0.6302 | 0.4861 |
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+ | No log | 1.0 | 18 | 0.6306 | 0.6759 | 0.6318 |
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+ | No log | 1.1111 | 20 | 0.5794 | 0.7289 | 0.5803 |
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+ | No log | 1.2222 | 22 | 0.4351 | 0.6154 | 0.4348 |
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+ | No log | 1.3333 | 24 | 0.5139 | 0.5149 | 0.5133 |
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+ | No log | 1.4444 | 26 | 0.4487 | 0.5967 | 0.4481 |
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+ | No log | 1.5556 | 28 | 0.4505 | 0.7663 | 0.4507 |
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+ | No log | 1.6667 | 30 | 0.4917 | 0.7702 | 0.4921 |
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+ | No log | 1.7778 | 32 | 0.4432 | 0.6859 | 0.4426 |
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+ | No log | 1.8889 | 34 | 0.5427 | 0.5673 | 0.5415 |
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+ | No log | 2.0 | 36 | 0.5133 | 0.5536 | 0.5122 |
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+ | No log | 2.1111 | 38 | 0.4171 | 0.6515 | 0.4166 |
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+ | No log | 2.2222 | 40 | 0.4265 | 0.6951 | 0.4260 |
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+ | No log | 2.3333 | 42 | 0.4487 | 0.6401 | 0.4480 |
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+ | No log | 2.4444 | 44 | 0.5093 | 0.5826 | 0.5082 |
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+ | No log | 2.5556 | 46 | 0.5193 | 0.5750 | 0.5182 |
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+ | No log | 2.6667 | 48 | 0.4705 | 0.6472 | 0.4699 |
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+ | No log | 2.7778 | 50 | 0.4668 | 0.7101 | 0.4666 |
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+ | No log | 2.8889 | 52 | 0.4574 | 0.7064 | 0.4572 |
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+ | No log | 3.0 | 54 | 0.4490 | 0.6031 | 0.4485 |
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+ | No log | 3.1111 | 56 | 0.5005 | 0.5434 | 0.4998 |
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+ | No log | 3.2222 | 58 | 0.4728 | 0.5714 | 0.4721 |
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+ | No log | 3.3333 | 60 | 0.4444 | 0.6493 | 0.4440 |
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+ | No log | 3.4444 | 62 | 0.4764 | 0.6914 | 0.4760 |
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+ | No log | 3.5556 | 64 | 0.5124 | 0.6726 | 0.5118 |
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+ | No log | 3.6667 | 66 | 0.5636 | 0.5952 | 0.5627 |
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+ | No log | 3.7778 | 68 | 0.5479 | 0.5977 | 0.5469 |
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+ | No log | 3.8889 | 70 | 0.5130 | 0.6191 | 0.5121 |
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+ | No log | 4.0 | 72 | 0.4884 | 0.6461 | 0.4879 |
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+ | No log | 4.1111 | 74 | 0.4839 | 0.5980 | 0.4832 |
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+ | No log | 4.2222 | 76 | 0.5315 | 0.5457 | 0.5305 |
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+ | No log | 4.3333 | 78 | 0.5336 | 0.5465 | 0.5326 |
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+ | No log | 4.4444 | 80 | 0.4907 | 0.5701 | 0.4901 |
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+ | No log | 4.5556 | 82 | 0.4836 | 0.6726 | 0.4834 |
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+ | No log | 4.6667 | 84 | 0.5058 | 0.6880 | 0.5058 |
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+ | No log | 4.7778 | 86 | 0.5131 | 0.6355 | 0.5127 |
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+ | No log | 4.8889 | 88 | 0.6336 | 0.5424 | 0.6325 |
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+ | No log | 5.0 | 90 | 0.7217 | 0.5167 | 0.7203 |
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+ | No log | 5.1111 | 92 | 0.6484 | 0.5394 | 0.6473 |
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+ | No log | 5.2222 | 94 | 0.5239 | 0.6047 | 0.5234 |
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+ | No log | 5.3333 | 96 | 0.4960 | 0.6591 | 0.4957 |
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+ | No log | 5.4444 | 98 | 0.4958 | 0.6725 | 0.4956 |
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+ | No log | 5.5556 | 100 | 0.5131 | 0.6097 | 0.5126 |
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+ | No log | 5.6667 | 102 | 0.5789 | 0.5640 | 0.5779 |
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+ | No log | 5.7778 | 104 | 0.6393 | 0.5598 | 0.6380 |
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+ | No log | 5.8889 | 106 | 0.6013 | 0.5640 | 0.6003 |
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+ | No log | 6.0 | 108 | 0.5576 | 0.6085 | 0.5569 |
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+ | No log | 6.1111 | 110 | 0.5394 | 0.6682 | 0.5389 |
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+ | No log | 6.2222 | 112 | 0.5429 | 0.6569 | 0.5424 |
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+ | No log | 6.3333 | 114 | 0.5841 | 0.5873 | 0.5832 |
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+ | No log | 6.4444 | 116 | 0.6113 | 0.5642 | 0.6102 |
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+ | No log | 6.5556 | 118 | 0.5828 | 0.5631 | 0.5818 |
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+ | No log | 6.6667 | 120 | 0.5283 | 0.6190 | 0.5277 |
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+ | No log | 6.7778 | 122 | 0.5137 | 0.6474 | 0.5132 |
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+ | No log | 6.8889 | 124 | 0.5253 | 0.6135 | 0.5246 |
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+ | No log | 7.0 | 126 | 0.5588 | 0.5693 | 0.5579 |
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+ | No log | 7.1111 | 128 | 0.5741 | 0.5644 | 0.5732 |
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+ | No log | 7.2222 | 130 | 0.5814 | 0.5627 | 0.5805 |
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+ | No log | 7.3333 | 132 | 0.5510 | 0.5687 | 0.5502 |
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+ | No log | 7.4444 | 134 | 0.5316 | 0.6227 | 0.5311 |
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+ | No log | 7.5556 | 136 | 0.5345 | 0.6034 | 0.5339 |
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+ | No log | 7.6667 | 138 | 0.5500 | 0.5709 | 0.5493 |
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+ | No log | 7.7778 | 140 | 0.5557 | 0.5748 | 0.5551 |
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+ | No log | 7.8889 | 142 | 0.5534 | 0.5855 | 0.5528 |
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+ | No log | 8.0 | 144 | 0.5613 | 0.5748 | 0.5606 |
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+ | No log | 8.1111 | 146 | 0.5663 | 0.5748 | 0.5657 |
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+ | No log | 8.2222 | 148 | 0.5748 | 0.5709 | 0.5741 |
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+ | No log | 8.3333 | 150 | 0.5887 | 0.5693 | 0.5880 |
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+ | No log | 8.4444 | 152 | 0.5802 | 0.5858 | 0.5796 |
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+ | No log | 8.5556 | 154 | 0.5690 | 0.6232 | 0.5685 |
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+ | No log | 8.6667 | 156 | 0.5680 | 0.6356 | 0.5676 |
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+ | No log | 8.7778 | 158 | 0.5770 | 0.6074 | 0.5764 |
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+ | No log | 8.8889 | 160 | 0.5943 | 0.5640 | 0.5935 |
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+ | No log | 9.0 | 162 | 0.6147 | 0.5503 | 0.6138 |
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+ | No log | 9.1111 | 164 | 0.6207 | 0.5539 | 0.6198 |
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+ | No log | 9.2222 | 166 | 0.6153 | 0.5503 | 0.6144 |
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+ | No log | 9.3333 | 168 | 0.5994 | 0.5602 | 0.5986 |
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+ | No log | 9.4444 | 170 | 0.5838 | 0.5640 | 0.5830 |
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+ | No log | 9.5556 | 172 | 0.5750 | 0.5795 | 0.5744 |
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+ | No log | 9.6667 | 174 | 0.5688 | 0.5982 | 0.5682 |
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+ | No log | 9.7778 | 176 | 0.5665 | 0.6054 | 0.5659 |
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+ | No log | 9.8889 | 178 | 0.5665 | 0.6054 | 0.5659 |
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+ | No log | 10.0 | 180 | 0.5671 | 0.6088 | 0.5665 |
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  ### Framework versions
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