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arabert_cross_organization_task7_fold0

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bert
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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_task6_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_task6_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: 0.6971
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- - Qwk: 0.5467
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- - Mse: 0.6953
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  ## Model description
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@@ -47,91 +47,81 @@ The following hyperparameters were used during training:
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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 | 2.1812 | 0.0813 | 2.1796 |
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- | No log | 0.2353 | 4 | 1.1581 | 0.1541 | 1.1560 |
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- | No log | 0.3529 | 6 | 0.9175 | 0.4300 | 0.9172 |
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- | No log | 0.4706 | 8 | 0.7853 | 0.5387 | 0.7849 |
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- | No log | 0.5882 | 10 | 0.7421 | 0.3500 | 0.7415 |
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- | No log | 0.7059 | 12 | 0.7475 | 0.3575 | 0.7469 |
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- | No log | 0.8235 | 14 | 0.5277 | 0.6055 | 0.5272 |
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- | No log | 0.9412 | 16 | 0.6059 | 0.7252 | 0.6066 |
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- | No log | 1.0588 | 18 | 0.5616 | 0.7136 | 0.5620 |
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- | No log | 1.1765 | 20 | 0.5211 | 0.6304 | 0.5204 |
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- | No log | 1.2941 | 22 | 0.6860 | 0.5190 | 0.6841 |
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- | No log | 1.4118 | 24 | 0.6738 | 0.5216 | 0.6721 |
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- | No log | 1.5294 | 26 | 0.5480 | 0.6313 | 0.5472 |
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- | No log | 1.6471 | 28 | 0.5424 | 0.7060 | 0.5428 |
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- | No log | 1.7647 | 30 | 0.4918 | 0.6873 | 0.4920 |
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- | No log | 1.8824 | 32 | 0.5098 | 0.5684 | 0.5094 |
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- | No log | 2.0 | 34 | 0.5437 | 0.5294 | 0.5430 |
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- | No log | 2.1176 | 36 | 0.5312 | 0.5901 | 0.5302 |
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- | No log | 2.2353 | 38 | 0.5616 | 0.5966 | 0.5604 |
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- | No log | 2.3529 | 40 | 0.5882 | 0.5838 | 0.5868 |
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- | No log | 2.4706 | 42 | 0.5423 | 0.6000 | 0.5413 |
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- | No log | 2.5882 | 44 | 0.5067 | 0.6211 | 0.5059 |
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- | No log | 2.7059 | 46 | 0.4934 | 0.6349 | 0.4926 |
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- | No log | 2.8235 | 48 | 0.4940 | 0.6329 | 0.4932 |
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- | No log | 2.9412 | 50 | 0.5291 | 0.5677 | 0.5279 |
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- | No log | 3.0588 | 52 | 0.6166 | 0.5158 | 0.6151 |
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- | No log | 3.1765 | 54 | 0.6014 | 0.5588 | 0.5998 |
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- | No log | 3.2941 | 56 | 0.5316 | 0.5878 | 0.5303 |
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- | No log | 3.4118 | 58 | 0.5135 | 0.5990 | 0.5124 |
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- | No log | 3.5294 | 60 | 0.5285 | 0.5827 | 0.5273 |
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- | No log | 3.6471 | 62 | 0.5943 | 0.5492 | 0.5929 |
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- | No log | 3.7647 | 64 | 0.5882 | 0.5620 | 0.5868 |
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- | No log | 3.8824 | 66 | 0.5237 | 0.5937 | 0.5227 |
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- | No log | 4.0 | 68 | 0.5270 | 0.6150 | 0.5261 |
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- | No log | 4.1176 | 70 | 0.5820 | 0.5589 | 0.5806 |
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- | No log | 4.2353 | 72 | 0.6445 | 0.5284 | 0.6429 |
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- | No log | 4.3529 | 74 | 0.6153 | 0.5627 | 0.6139 |
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- | No log | 4.4706 | 76 | 0.6066 | 0.5783 | 0.6054 |
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- | No log | 4.5882 | 78 | 0.6378 | 0.5639 | 0.6363 |
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- | No log | 4.7059 | 80 | 0.7155 | 0.5342 | 0.7135 |
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- | No log | 4.8235 | 82 | 0.7123 | 0.5305 | 0.7104 |
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- | No log | 4.9412 | 84 | 0.6786 | 0.5363 | 0.6769 |
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- | No log | 5.0588 | 86 | 0.6340 | 0.5611 | 0.6326 |
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- | No log | 5.1765 | 88 | 0.6050 | 0.5630 | 0.6038 |
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- | No log | 5.2941 | 90 | 0.6307 | 0.5564 | 0.6293 |
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- | No log | 5.4118 | 92 | 0.6603 | 0.5449 | 0.6588 |
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- | No log | 5.5294 | 94 | 0.6765 | 0.5483 | 0.6748 |
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- | No log | 5.6471 | 96 | 0.6364 | 0.5686 | 0.6351 |
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- | No log | 5.7647 | 98 | 0.6144 | 0.5967 | 0.6132 |
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- | No log | 5.8824 | 100 | 0.6315 | 0.5826 | 0.6300 |
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- | No log | 6.0 | 102 | 0.6964 | 0.5217 | 0.6946 |
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- | No log | 6.1176 | 104 | 0.6906 | 0.5310 | 0.6887 |
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- | No log | 6.2353 | 106 | 0.6656 | 0.5513 | 0.6639 |
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- | No log | 6.3529 | 108 | 0.6273 | 0.5829 | 0.6259 |
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- | No log | 6.4706 | 110 | 0.6354 | 0.5748 | 0.6340 |
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- | No log | 6.5882 | 112 | 0.6855 | 0.5397 | 0.6839 |
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- | No log | 6.7059 | 114 | 0.7228 | 0.5179 | 0.7211 |
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- | No log | 6.8235 | 116 | 0.6976 | 0.5206 | 0.6960 |
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- | No log | 6.9412 | 118 | 0.6558 | 0.5456 | 0.6544 |
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- | No log | 7.0588 | 120 | 0.6618 | 0.5569 | 0.6605 |
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- | No log | 7.1765 | 122 | 0.7088 | 0.5397 | 0.7072 |
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- | No log | 7.2941 | 124 | 0.8015 | 0.4900 | 0.7996 |
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- | No log | 7.4118 | 126 | 0.8354 | 0.4798 | 0.8334 |
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- | No log | 7.5294 | 128 | 0.7861 | 0.4973 | 0.7842 |
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- | No log | 7.6471 | 130 | 0.7081 | 0.5399 | 0.7065 |
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- | No log | 7.7647 | 132 | 0.6756 | 0.5725 | 0.6741 |
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- | No log | 7.8824 | 134 | 0.6874 | 0.5524 | 0.6859 |
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- | No log | 8.0 | 136 | 0.7225 | 0.5459 | 0.7207 |
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- | No log | 8.1176 | 138 | 0.7336 | 0.5368 | 0.7317 |
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- | No log | 8.2353 | 140 | 0.7330 | 0.5258 | 0.7312 |
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- | No log | 8.3529 | 142 | 0.7088 | 0.5474 | 0.7070 |
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- | No log | 8.4706 | 144 | 0.7009 | 0.5474 | 0.6991 |
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- | No log | 8.5882 | 146 | 0.6880 | 0.5489 | 0.6863 |
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- | No log | 8.7059 | 148 | 0.6695 | 0.5530 | 0.6679 |
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- | No log | 8.8235 | 150 | 0.6654 | 0.5587 | 0.6638 |
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- | No log | 8.9412 | 152 | 0.6764 | 0.5464 | 0.6747 |
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- | No log | 9.0588 | 154 | 0.6945 | 0.5419 | 0.6927 |
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- | No log | 9.1765 | 156 | 0.7081 | 0.5278 | 0.7063 |
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- | No log | 9.2941 | 158 | 0.7099 | 0.5292 | 0.7080 |
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- | No log | 9.4118 | 160 | 0.7043 | 0.5419 | 0.7025 |
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- | No log | 9.5294 | 162 | 0.7049 | 0.5430 | 0.7031 |
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- | No log | 9.6471 | 164 | 0.7019 | 0.5430 | 0.7000 |
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- | No log | 9.7647 | 166 | 0.6996 | 0.5467 | 0.6978 |
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- | No log | 9.8824 | 168 | 0.6977 | 0.5467 | 0.6959 |
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- | No log | 10.0 | 170 | 0.6971 | 0.5467 | 0.6953 |
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_organization_task7_fold0
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_task7_fold0
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.
16
  It achieves the following results on the evaluation set:
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+ - Loss: 0.7058
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+ - Qwk: 0.5975
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+ - Mse: 0.7057
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21
  ## Model description
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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 | 3.8864 | 0.0541 | 3.8830 |
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+ | No log | 0.2667 | 4 | 2.5481 | 0.0079 | 2.5460 |
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+ | No log | 0.4 | 6 | 1.6996 | 0.2037 | 1.6983 |
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+ | No log | 0.5333 | 8 | 1.3776 | 0.2939 | 1.3765 |
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+ | No log | 0.6667 | 10 | 1.3355 | 0.3347 | 1.3345 |
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+ | No log | 0.8 | 12 | 1.2773 | 0.3590 | 1.2767 |
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+ | No log | 0.9333 | 14 | 1.4284 | 0.3342 | 1.4277 |
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+ | No log | 1.0667 | 16 | 1.1577 | 0.3897 | 1.1573 |
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+ | No log | 1.2 | 18 | 0.9645 | 0.4536 | 0.9641 |
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+ | No log | 1.3333 | 20 | 1.1001 | 0.4324 | 1.0996 |
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+ | No log | 1.4667 | 22 | 1.0995 | 0.4399 | 1.0990 |
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+ | No log | 1.6 | 24 | 0.9787 | 0.4704 | 0.9783 |
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+ | No log | 1.7333 | 26 | 0.8116 | 0.5438 | 0.8112 |
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+ | No log | 1.8667 | 28 | 0.8107 | 0.5471 | 0.8103 |
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+ | No log | 2.0 | 30 | 0.9069 | 0.4983 | 0.9063 |
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+ | No log | 2.1333 | 32 | 0.8730 | 0.5346 | 0.8726 |
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+ | No log | 2.2667 | 34 | 0.9141 | 0.5284 | 0.9138 |
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+ | No log | 2.4 | 36 | 0.7576 | 0.6068 | 0.7578 |
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+ | No log | 2.5333 | 38 | 0.7560 | 0.6087 | 0.7563 |
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+ | No log | 2.6667 | 40 | 0.8005 | 0.6059 | 0.8007 |
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+ | No log | 2.8 | 42 | 0.9430 | 0.5399 | 0.9430 |
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+ | No log | 2.9333 | 44 | 0.8990 | 0.5542 | 0.8990 |
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+ | No log | 3.0667 | 46 | 0.8494 | 0.5672 | 0.8494 |
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+ | No log | 3.2 | 48 | 0.8095 | 0.5752 | 0.8094 |
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+ | No log | 3.3333 | 50 | 0.7424 | 0.6012 | 0.7425 |
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+ | No log | 3.4667 | 52 | 0.7009 | 0.6100 | 0.7011 |
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+ | No log | 3.6 | 54 | 0.7078 | 0.6055 | 0.7080 |
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+ | No log | 3.7333 | 56 | 0.8222 | 0.5652 | 0.8223 |
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+ | No log | 3.8667 | 58 | 0.8211 | 0.5742 | 0.8212 |
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+ | No log | 4.0 | 60 | 0.7561 | 0.5870 | 0.7562 |
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+ | No log | 4.1333 | 62 | 0.6981 | 0.6055 | 0.6982 |
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+ | No log | 4.2667 | 64 | 0.6970 | 0.6051 | 0.6971 |
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+ | No log | 4.4 | 66 | 0.7327 | 0.5991 | 0.7326 |
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+ | No log | 4.5333 | 68 | 0.8809 | 0.5424 | 0.8806 |
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+ | No log | 4.6667 | 70 | 0.8266 | 0.5559 | 0.8263 |
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+ | No log | 4.8 | 72 | 0.7118 | 0.5954 | 0.7117 |
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+ | No log | 4.9333 | 74 | 0.6923 | 0.6040 | 0.6923 |
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+ | No log | 5.0667 | 76 | 0.7259 | 0.5893 | 0.7259 |
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+ | No log | 5.2 | 78 | 0.7425 | 0.5832 | 0.7425 |
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+ | No log | 5.3333 | 80 | 0.6843 | 0.6051 | 0.6843 |
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+ | No log | 5.4667 | 82 | 0.6647 | 0.6118 | 0.6647 |
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+ | No log | 5.6 | 84 | 0.6805 | 0.6104 | 0.6804 |
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+ | No log | 5.7333 | 86 | 0.7021 | 0.5992 | 0.7019 |
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+ | No log | 5.8667 | 88 | 0.6896 | 0.6158 | 0.6894 |
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+ | No log | 6.0 | 90 | 0.6658 | 0.6204 | 0.6657 |
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+ | No log | 6.1333 | 92 | 0.6774 | 0.6118 | 0.6774 |
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+ | No log | 6.2667 | 94 | 0.7472 | 0.5748 | 0.7471 |
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+ | No log | 6.4 | 96 | 0.8444 | 0.5491 | 0.8442 |
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+ | No log | 6.5333 | 98 | 0.8227 | 0.5502 | 0.8225 |
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+ | No log | 6.6667 | 100 | 0.7455 | 0.5671 | 0.7453 |
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+ | No log | 6.8 | 102 | 0.7062 | 0.5907 | 0.7060 |
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+ | No log | 6.9333 | 104 | 0.6458 | 0.6143 | 0.6457 |
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+ | No log | 7.0667 | 106 | 0.6289 | 0.6250 | 0.6288 |
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+ | No log | 7.2 | 108 | 0.6373 | 0.6205 | 0.6371 |
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+ | No log | 7.3333 | 110 | 0.6669 | 0.6113 | 0.6666 |
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+ | No log | 7.4667 | 112 | 0.7012 | 0.6035 | 0.7009 |
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+ | No log | 7.6 | 114 | 0.6942 | 0.5999 | 0.6939 |
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+ | No log | 7.7333 | 116 | 0.6669 | 0.6083 | 0.6668 |
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+ | No log | 7.8667 | 118 | 0.6470 | 0.6177 | 0.6469 |
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+ | No log | 8.0 | 120 | 0.6439 | 0.6292 | 0.6438 |
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+ | No log | 8.1333 | 122 | 0.6501 | 0.6098 | 0.6500 |
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+ | No log | 8.2667 | 124 | 0.6801 | 0.6013 | 0.6800 |
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+ | No log | 8.4 | 126 | 0.7382 | 0.5951 | 0.7380 |
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+ | No log | 8.5333 | 128 | 0.7558 | 0.5885 | 0.7556 |
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+ | No log | 8.6667 | 130 | 0.7227 | 0.5947 | 0.7225 |
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+ | No log | 8.8 | 132 | 0.6780 | 0.6014 | 0.6780 |
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+ | No log | 8.9333 | 134 | 0.6554 | 0.6101 | 0.6554 |
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+ | No log | 9.0667 | 136 | 0.6520 | 0.6154 | 0.6520 |
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+ | No log | 9.2 | 138 | 0.6597 | 0.6100 | 0.6596 |
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+ | No log | 9.3333 | 140 | 0.6690 | 0.6141 | 0.6689 |
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+ | No log | 9.4667 | 142 | 0.6790 | 0.6041 | 0.6789 |
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+ | No log | 9.6 | 144 | 0.6910 | 0.5976 | 0.6909 |
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+ | No log | 9.7333 | 146 | 0.7025 | 0.5975 | 0.7024 |
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+ | No log | 9.8667 | 148 | 0.7059 | 0.5975 | 0.7057 |
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+ | No log | 10.0 | 150 | 0.7058 | 0.5975 | 0.7057 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions