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arabert_cross_organization_task3_fold5

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@@ -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_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_task3_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: 0.4384
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- - Qwk: 0.7923
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- - Mse: 0.4384
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  ## Model description
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@@ -45,93 +45,88 @@ The following hyperparameters were used during training:
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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 | 2.0659 | 0.1309 | 2.0659 |
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- | No log | 0.2353 | 4 | 1.1312 | 0.2513 | 1.1312 |
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- | No log | 0.3529 | 6 | 1.2762 | 0.3076 | 1.2762 |
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- | No log | 0.4706 | 8 | 0.9742 | 0.3913 | 0.9742 |
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- | No log | 0.5882 | 10 | 0.8094 | 0.3950 | 0.8094 |
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- | No log | 0.7059 | 12 | 0.6869 | 0.4798 | 0.6869 |
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- | No log | 0.8235 | 14 | 0.5774 | 0.5954 | 0.5774 |
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- | No log | 0.9412 | 16 | 0.6003 | 0.7210 | 0.6003 |
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- | No log | 1.0588 | 18 | 0.5323 | 0.7387 | 0.5323 |
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- | No log | 1.1765 | 20 | 0.4319 | 0.7027 | 0.4319 |
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- | No log | 1.2941 | 22 | 0.4200 | 0.7041 | 0.4200 |
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- | No log | 1.4118 | 24 | 0.4896 | 0.7702 | 0.4896 |
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- | No log | 1.5294 | 26 | 0.4854 | 0.7637 | 0.4854 |
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- | No log | 1.6471 | 28 | 0.4346 | 0.7311 | 0.4346 |
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- | No log | 1.7647 | 30 | 0.4283 | 0.7225 | 0.4283 |
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- | No log | 1.8824 | 32 | 0.4469 | 0.6962 | 0.4469 |
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- | No log | 2.0 | 34 | 0.4554 | 0.7521 | 0.4554 |
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- | No log | 2.1176 | 36 | 0.6141 | 0.7808 | 0.6141 |
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- | No log | 2.2353 | 38 | 0.5954 | 0.7714 | 0.5954 |
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- | No log | 2.3529 | 40 | 0.4972 | 0.7836 | 0.4972 |
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- | No log | 2.4706 | 42 | 0.3941 | 0.7529 | 0.3941 |
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- | No log | 2.5882 | 44 | 0.3651 | 0.7446 | 0.3651 |
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- | No log | 2.7059 | 46 | 0.3529 | 0.7605 | 0.3529 |
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- | No log | 2.8235 | 48 | 0.3699 | 0.7870 | 0.3699 |
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- | No log | 2.9412 | 50 | 0.4844 | 0.8194 | 0.4844 |
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- | No log | 3.0588 | 52 | 0.5294 | 0.8187 | 0.5294 |
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- | No log | 3.1765 | 54 | 0.4291 | 0.8009 | 0.4291 |
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- | No log | 3.2941 | 56 | 0.3600 | 0.7917 | 0.3600 |
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- | No log | 3.4118 | 58 | 0.3588 | 0.7841 | 0.3588 |
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- | No log | 3.5294 | 60 | 0.4067 | 0.7876 | 0.4067 |
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- | No log | 3.6471 | 62 | 0.5014 | 0.8211 | 0.5014 |
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- | No log | 3.7647 | 64 | 0.4957 | 0.8087 | 0.4957 |
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- | No log | 3.8824 | 66 | 0.3997 | 0.7705 | 0.3997 |
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- | No log | 4.0 | 68 | 0.3670 | 0.7411 | 0.3670 |
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- | No log | 4.1176 | 70 | 0.3666 | 0.7485 | 0.3666 |
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- | No log | 4.2353 | 72 | 0.4185 | 0.7811 | 0.4185 |
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- | No log | 4.3529 | 74 | 0.5672 | 0.8114 | 0.5672 |
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- | No log | 4.4706 | 76 | 0.6146 | 0.7985 | 0.6146 |
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- | No log | 4.5882 | 78 | 0.5087 | 0.7803 | 0.5087 |
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- | No log | 4.7059 | 80 | 0.4307 | 0.7841 | 0.4307 |
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- | No log | 4.8235 | 82 | 0.4210 | 0.7338 | 0.4210 |
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- | No log | 4.9412 | 84 | 0.4161 | 0.7329 | 0.4161 |
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- | No log | 5.0588 | 86 | 0.4113 | 0.7754 | 0.4113 |
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- | No log | 5.1765 | 88 | 0.4423 | 0.8003 | 0.4423 |
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- | No log | 5.2941 | 90 | 0.4908 | 0.8117 | 0.4908 |
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- | No log | 5.4118 | 92 | 0.4559 | 0.8009 | 0.4559 |
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- | No log | 5.5294 | 94 | 0.4337 | 0.7982 | 0.4337 |
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- | No log | 5.6471 | 96 | 0.4283 | 0.8001 | 0.4283 |
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- | No log | 5.7647 | 98 | 0.4085 | 0.7829 | 0.4085 |
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- | No log | 5.8824 | 100 | 0.4060 | 0.7781 | 0.4060 |
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- | No log | 6.0 | 102 | 0.4389 | 0.7865 | 0.4389 |
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- | No log | 6.1176 | 104 | 0.4913 | 0.7924 | 0.4913 |
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- | No log | 6.2353 | 106 | 0.4747 | 0.7811 | 0.4747 |
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- | No log | 6.3529 | 108 | 0.4248 | 0.7908 | 0.4248 |
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- | No log | 6.4706 | 110 | 0.3799 | 0.7679 | 0.3799 |
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- | No log | 6.5882 | 112 | 0.3690 | 0.7547 | 0.3690 |
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- | No log | 6.7059 | 114 | 0.3767 | 0.7741 | 0.3767 |
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- | No log | 6.8235 | 116 | 0.4030 | 0.7842 | 0.4030 |
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- | No log | 6.9412 | 118 | 0.4559 | 0.8101 | 0.4559 |
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- | No log | 7.0588 | 120 | 0.4943 | 0.8129 | 0.4943 |
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- | No log | 7.1765 | 122 | 0.4753 | 0.8154 | 0.4753 |
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- | No log | 7.2941 | 124 | 0.4148 | 0.8032 | 0.4148 |
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- | No log | 7.4118 | 126 | 0.3867 | 0.7623 | 0.3867 |
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- | No log | 7.5294 | 128 | 0.3894 | 0.7606 | 0.3894 |
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- | No log | 7.6471 | 130 | 0.4128 | 0.7745 | 0.4128 |
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- | No log | 7.7647 | 132 | 0.4714 | 0.7941 | 0.4714 |
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- | No log | 7.8824 | 134 | 0.5145 | 0.8135 | 0.5145 |
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- | No log | 8.0 | 136 | 0.5184 | 0.8135 | 0.5184 |
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- | No log | 8.1176 | 138 | 0.4920 | 0.8112 | 0.4920 |
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- | No log | 8.2353 | 140 | 0.4462 | 0.8017 | 0.4462 |
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- | No log | 8.3529 | 142 | 0.4059 | 0.7727 | 0.4059 |
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- | No log | 8.4706 | 144 | 0.3943 | 0.7707 | 0.3943 |
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- | No log | 8.5882 | 146 | 0.3955 | 0.7715 | 0.3955 |
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- | No log | 8.7059 | 148 | 0.4024 | 0.7702 | 0.4024 |
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- | No log | 8.8235 | 150 | 0.4170 | 0.7875 | 0.4170 |
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- | No log | 8.9412 | 152 | 0.4406 | 0.7995 | 0.4406 |
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- | No log | 9.0588 | 154 | 0.4635 | 0.7980 | 0.4635 |
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- | No log | 9.1765 | 156 | 0.4777 | 0.8082 | 0.4777 |
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- | No log | 9.2941 | 158 | 0.4780 | 0.8082 | 0.4780 |
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- | No log | 9.4118 | 160 | 0.4663 | 0.7989 | 0.4663 |
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- | No log | 9.5294 | 162 | 0.4565 | 0.7957 | 0.4565 |
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- | No log | 9.6471 | 164 | 0.4496 | 0.7945 | 0.4496 |
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- | No log | 9.7647 | 166 | 0.4453 | 0.7965 | 0.4453 |
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- | No log | 9.8824 | 168 | 0.4404 | 0.7994 | 0.4404 |
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- | No log | 10.0 | 170 | 0.4384 | 0.7923 | 0.4384 |
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_organization_task3_fold5
7
  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_organization_task3_fold5
14
 
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: 0.4649
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+ - Qwk: 0.6602
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+ - Mse: 0.4652
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  ## Model description
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  ### 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