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arabert_cross_organization_task4_fold4

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  1. README.md +95 -90
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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_task4_fold3
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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_fold3
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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: 0.5515
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- - Qwk: 0.8285
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- - Mse: 0.5515
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  ## Model description
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@@ -47,91 +47,96 @@ 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 | 1.8640 | 0.0713 | 1.8640 |
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- | No log | 0.2353 | 4 | 1.2390 | 0.2961 | 1.2390 |
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- | No log | 0.3529 | 6 | 1.0659 | 0.5023 | 1.0659 |
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- | No log | 0.4706 | 8 | 0.7195 | 0.6388 | 0.7195 |
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- | No log | 0.5882 | 10 | 0.6736 | 0.6636 | 0.6736 |
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- | No log | 0.7059 | 12 | 0.6560 | 0.7539 | 0.6560 |
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- | No log | 0.8235 | 14 | 0.6088 | 0.7149 | 0.6088 |
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- | No log | 0.9412 | 16 | 0.5695 | 0.7426 | 0.5695 |
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- | No log | 1.0588 | 18 | 0.5646 | 0.7706 | 0.5646 |
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- | No log | 1.1765 | 20 | 0.5616 | 0.7796 | 0.5616 |
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- | No log | 1.2941 | 22 | 0.5516 | 0.7811 | 0.5516 |
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- | No log | 1.4118 | 24 | 0.5475 | 0.7868 | 0.5475 |
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- | No log | 1.5294 | 26 | 0.5246 | 0.7436 | 0.5246 |
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- | No log | 1.6471 | 28 | 0.5463 | 0.6820 | 0.5463 |
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- | No log | 1.7647 | 30 | 0.5511 | 0.7714 | 0.5511 |
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- | No log | 1.8824 | 32 | 0.6634 | 0.7890 | 0.6634 |
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- | No log | 2.0 | 34 | 0.5815 | 0.7811 | 0.5815 |
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- | No log | 2.1176 | 36 | 0.5186 | 0.7320 | 0.5186 |
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- | No log | 2.2353 | 38 | 0.5161 | 0.7348 | 0.5161 |
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- | No log | 2.3529 | 40 | 0.5145 | 0.7637 | 0.5145 |
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- | No log | 2.4706 | 42 | 0.5367 | 0.7805 | 0.5367 |
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- | No log | 2.5882 | 44 | 0.5238 | 0.7807 | 0.5238 |
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- | No log | 2.7059 | 46 | 0.5169 | 0.7771 | 0.5169 |
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- | No log | 2.8235 | 48 | 0.5287 | 0.7852 | 0.5287 |
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- | No log | 2.9412 | 50 | 0.5446 | 0.7867 | 0.5446 |
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- | No log | 3.0588 | 52 | 0.5892 | 0.7786 | 0.5892 |
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- | No log | 3.1765 | 54 | 0.5913 | 0.7818 | 0.5913 |
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- | No log | 3.2941 | 56 | 0.5352 | 0.7813 | 0.5352 |
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- | No log | 3.4118 | 58 | 0.5197 | 0.7785 | 0.5197 |
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- | No log | 3.5294 | 60 | 0.5895 | 0.7951 | 0.5895 |
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- | No log | 3.6471 | 62 | 0.6125 | 0.7950 | 0.6125 |
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- | No log | 3.7647 | 64 | 0.5768 | 0.7875 | 0.5768 |
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- | No log | 3.8824 | 66 | 0.5110 | 0.7717 | 0.5110 |
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- | No log | 4.0 | 68 | 0.5375 | 0.7910 | 0.5375 |
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- | No log | 4.1176 | 70 | 0.6011 | 0.7996 | 0.6011 |
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- | No log | 4.2353 | 72 | 0.5525 | 0.7824 | 0.5525 |
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- | No log | 4.3529 | 74 | 0.5620 | 0.7907 | 0.5620 |
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- | No log | 4.4706 | 76 | 0.5220 | 0.7908 | 0.5220 |
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- | No log | 4.5882 | 78 | 0.5028 | 0.7641 | 0.5028 |
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- | No log | 4.7059 | 80 | 0.5102 | 0.7841 | 0.5102 |
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- | No log | 4.8235 | 82 | 0.6101 | 0.8166 | 0.6101 |
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- | No log | 4.9412 | 84 | 0.7637 | 0.8377 | 0.7637 |
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- | No log | 5.0588 | 86 | 0.6895 | 0.8271 | 0.6895 |
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- | No log | 5.1765 | 88 | 0.5154 | 0.7893 | 0.5154 |
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- | No log | 5.2941 | 90 | 0.4808 | 0.7932 | 0.4808 |
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- | No log | 5.4118 | 92 | 0.5241 | 0.7847 | 0.5241 |
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- | No log | 5.5294 | 94 | 0.6303 | 0.8282 | 0.6303 |
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- | No log | 5.6471 | 96 | 0.6026 | 0.8213 | 0.6026 |
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- | No log | 5.7647 | 98 | 0.5078 | 0.8217 | 0.5078 |
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- | No log | 5.8824 | 100 | 0.4940 | 0.8070 | 0.4940 |
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- | No log | 6.0 | 102 | 0.5633 | 0.8182 | 0.5633 |
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- | No log | 6.1176 | 104 | 0.7172 | 0.8375 | 0.7172 |
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- | No log | 6.2353 | 106 | 0.7195 | 0.8305 | 0.7195 |
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- | No log | 6.3529 | 108 | 0.5965 | 0.8196 | 0.5965 |
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- | No log | 6.4706 | 110 | 0.5114 | 0.7928 | 0.5114 |
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- | No log | 6.5882 | 112 | 0.5064 | 0.7886 | 0.5064 |
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- | No log | 6.7059 | 114 | 0.5439 | 0.8123 | 0.5439 |
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- | No log | 6.8235 | 116 | 0.6118 | 0.8257 | 0.6118 |
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- | No log | 6.9412 | 118 | 0.6143 | 0.8179 | 0.6143 |
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- | No log | 7.0588 | 120 | 0.6140 | 0.8174 | 0.6140 |
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- | No log | 7.1765 | 122 | 0.5766 | 0.8207 | 0.5766 |
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- | No log | 7.2941 | 124 | 0.5369 | 0.8188 | 0.5369 |
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- | No log | 7.4118 | 126 | 0.5480 | 0.8132 | 0.5480 |
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- | No log | 7.5294 | 128 | 0.6078 | 0.8236 | 0.6078 |
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- | No log | 7.6471 | 130 | 0.6701 | 0.8235 | 0.6701 |
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- | No log | 7.7647 | 132 | 0.6414 | 0.8221 | 0.6414 |
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- | No log | 7.8824 | 134 | 0.5864 | 0.8195 | 0.5864 |
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- | No log | 8.0 | 136 | 0.5473 | 0.8186 | 0.5473 |
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- | No log | 8.1176 | 138 | 0.5345 | 0.8188 | 0.5345 |
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- | No log | 8.2353 | 140 | 0.5432 | 0.8202 | 0.5432 |
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- | No log | 8.3529 | 142 | 0.5420 | 0.8239 | 0.5420 |
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- | No log | 8.4706 | 144 | 0.5381 | 0.8188 | 0.5381 |
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- | No log | 8.5882 | 146 | 0.5139 | 0.8016 | 0.5139 |
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- | No log | 8.7059 | 148 | 0.5052 | 0.7981 | 0.5052 |
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- | No log | 8.8235 | 150 | 0.5095 | 0.7948 | 0.5095 |
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- | No log | 8.9412 | 152 | 0.5334 | 0.8173 | 0.5334 |
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- | No log | 9.0588 | 154 | 0.5783 | 0.8340 | 0.5783 |
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- | No log | 9.1765 | 156 | 0.6036 | 0.8366 | 0.6036 |
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- | No log | 9.2941 | 158 | 0.6056 | 0.8403 | 0.6056 |
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- | No log | 9.4118 | 160 | 0.5911 | 0.8320 | 0.5911 |
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- | No log | 9.5294 | 162 | 0.5683 | 0.8301 | 0.5683 |
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- | No log | 9.6471 | 164 | 0.5583 | 0.8287 | 0.5583 |
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- | No log | 9.7647 | 166 | 0.5530 | 0.8269 | 0.5530 |
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- | No log | 9.8824 | 168 | 0.5512 | 0.8285 | 0.5512 |
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- | No log | 10.0 | 170 | 0.5515 | 0.8285 | 0.5515 |
 
 
 
 
 
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_organization_task4_fold4
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_task4_fold4
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: 0.5141
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+ - Qwk: 0.7810
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+ - Mse: 0.5141
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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 | 0.1111 | 2 | 1.8597 | 0.1122 | 1.8597 |
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+ | No log | 0.2222 | 4 | 1.3020 | 0.0409 | 1.3020 |
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+ | No log | 0.3333 | 6 | 1.0459 | 0.3503 | 1.0459 |
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+ | No log | 0.4444 | 8 | 0.7138 | 0.4906 | 0.7138 |
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+ | No log | 0.5556 | 10 | 0.5900 | 0.6224 | 0.5900 |
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+ | No log | 0.6667 | 12 | 0.5708 | 0.6214 | 0.5708 |
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+ | No log | 0.7778 | 14 | 0.4881 | 0.6661 | 0.4881 |
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+ | No log | 0.8889 | 16 | 0.4843 | 0.6880 | 0.4843 |
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+ | No log | 1.0 | 18 | 0.5772 | 0.7185 | 0.5772 |
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+ | No log | 1.1111 | 20 | 0.4344 | 0.7515 | 0.4344 |
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+ | No log | 1.2222 | 22 | 0.4173 | 0.6853 | 0.4173 |
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+ | No log | 1.3333 | 24 | 0.4326 | 0.7470 | 0.4326 |
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+ | No log | 1.4444 | 26 | 0.6327 | 0.7329 | 0.6327 |
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+ | No log | 1.5556 | 28 | 0.6486 | 0.7640 | 0.6486 |
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+ | No log | 1.6667 | 30 | 0.4510 | 0.7633 | 0.4510 |
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+ | No log | 1.7778 | 32 | 0.3885 | 0.7569 | 0.3885 |
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+ | No log | 1.8889 | 34 | 0.4049 | 0.7722 | 0.4049 |
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+ | No log | 2.0 | 36 | 0.5466 | 0.7900 | 0.5466 |
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+ | No log | 2.1111 | 38 | 0.5445 | 0.7886 | 0.5445 |
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+ | No log | 2.2222 | 40 | 0.4445 | 0.7553 | 0.4445 |
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+ | No log | 2.3333 | 42 | 0.4182 | 0.7437 | 0.4182 |
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+ | No log | 2.4444 | 44 | 0.4202 | 0.7536 | 0.4202 |
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+ | No log | 2.5556 | 46 | 0.5364 | 0.7929 | 0.5364 |
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+ | No log | 2.6667 | 48 | 0.6070 | 0.7880 | 0.6070 |
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+ | No log | 2.7778 | 50 | 0.4960 | 0.7859 | 0.4960 |
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+ | No log | 2.8889 | 52 | 0.4044 | 0.7719 | 0.4044 |
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+ | No log | 3.0 | 54 | 0.3938 | 0.7606 | 0.3938 |
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+ | No log | 3.1111 | 56 | 0.4669 | 0.7947 | 0.4669 |
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+ | No log | 3.2222 | 58 | 0.5343 | 0.7820 | 0.5343 |
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+ | No log | 3.3333 | 60 | 0.4763 | 0.7853 | 0.4763 |
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+ | No log | 3.4444 | 62 | 0.4091 | 0.7835 | 0.4091 |
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+ | No log | 3.5556 | 64 | 0.4119 | 0.7882 | 0.4119 |
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+ | No log | 3.6667 | 66 | 0.4525 | 0.7813 | 0.4525 |
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+ | No log | 3.7778 | 68 | 0.4761 | 0.7828 | 0.4761 |
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+ | No log | 3.8889 | 70 | 0.4893 | 0.7931 | 0.4893 |
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+ | No log | 4.0 | 72 | 0.4435 | 0.7862 | 0.4435 |
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+ | No log | 4.1111 | 74 | 0.4754 | 0.7918 | 0.4754 |
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+ | No log | 4.2222 | 76 | 0.5004 | 0.7931 | 0.5004 |
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+ | No log | 4.3333 | 78 | 0.5554 | 0.8090 | 0.5554 |
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+ | No log | 4.4444 | 80 | 0.5319 | 0.7947 | 0.5319 |
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+ | No log | 4.5556 | 82 | 0.4459 | 0.7781 | 0.4459 |
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+ | No log | 4.6667 | 84 | 0.4355 | 0.7725 | 0.4355 |
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+ | No log | 4.7778 | 86 | 0.4699 | 0.7823 | 0.4699 |
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+ | No log | 4.8889 | 88 | 0.4860 | 0.7900 | 0.4860 |
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+ | No log | 5.0 | 90 | 0.4400 | 0.7892 | 0.4400 |
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+ | No log | 5.1111 | 92 | 0.4221 | 0.7376 | 0.4221 |
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+ | No log | 5.2222 | 94 | 0.4264 | 0.7879 | 0.4264 |
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+ | No log | 5.3333 | 96 | 0.4728 | 0.8106 | 0.4728 |
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+ | No log | 5.4444 | 98 | 0.5254 | 0.8043 | 0.5254 |
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+ | No log | 5.5556 | 100 | 0.4876 | 0.8048 | 0.4876 |
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+ | No log | 5.6667 | 102 | 0.4400 | 0.7767 | 0.4400 |
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+ | No log | 5.7778 | 104 | 0.4191 | 0.7487 | 0.4191 |
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+ | No log | 5.8889 | 106 | 0.4281 | 0.7643 | 0.4281 |
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+ | No log | 6.0 | 108 | 0.4819 | 0.7888 | 0.4819 |
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+ | No log | 6.1111 | 110 | 0.5487 | 0.8063 | 0.5487 |
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+ | No log | 6.2222 | 112 | 0.6060 | 0.7903 | 0.6060 |
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+ | No log | 6.3333 | 114 | 0.5618 | 0.7847 | 0.5618 |
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+ | No log | 6.4444 | 116 | 0.5080 | 0.7689 | 0.5080 |
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+ | No log | 6.5556 | 118 | 0.4883 | 0.7543 | 0.4883 |
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+ | No log | 6.6667 | 120 | 0.4979 | 0.7597 | 0.4979 |
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+ | No log | 6.7778 | 122 | 0.5155 | 0.7757 | 0.5155 |
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+ | No log | 6.8889 | 124 | 0.5239 | 0.7883 | 0.5239 |
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+ | No log | 7.0 | 126 | 0.5025 | 0.7973 | 0.5025 |
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+ | No log | 7.1111 | 128 | 0.4784 | 0.7894 | 0.4784 |
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+ | No log | 7.2222 | 130 | 0.4608 | 0.7714 | 0.4608 |
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+ | No log | 7.3333 | 132 | 0.4592 | 0.7608 | 0.4592 |
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+ | No log | 7.4444 | 134 | 0.4736 | 0.7898 | 0.4736 |
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+ | No log | 7.5556 | 136 | 0.5099 | 0.7905 | 0.5099 |
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+ | No log | 7.6667 | 138 | 0.5575 | 0.8010 | 0.5575 |
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+ | No log | 7.7778 | 140 | 0.5556 | 0.8167 | 0.5556 |
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+ | No log | 7.8889 | 142 | 0.5181 | 0.7957 | 0.5181 |
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+ | No log | 8.0 | 144 | 0.4691 | 0.7885 | 0.4691 |
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+ | No log | 8.1111 | 146 | 0.4424 | 0.7890 | 0.4424 |
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+ | No log | 8.2222 | 148 | 0.4411 | 0.7803 | 0.4411 |
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+ | No log | 8.3333 | 150 | 0.4646 | 0.7859 | 0.4646 |
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+ | No log | 8.4444 | 152 | 0.4939 | 0.8070 | 0.4939 |
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+ | No log | 8.5556 | 154 | 0.5186 | 0.8172 | 0.5186 |
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+ | No log | 8.6667 | 156 | 0.5307 | 0.8195 | 0.5307 |
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+ | No log | 8.7778 | 158 | 0.5184 | 0.8146 | 0.5184 |
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+ | No log | 8.8889 | 160 | 0.4898 | 0.8099 | 0.4898 |
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+ | No log | 9.0 | 162 | 0.4741 | 0.7957 | 0.4741 |
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+ | No log | 9.1111 | 164 | 0.4724 | 0.7948 | 0.4724 |
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+ | No log | 9.2222 | 166 | 0.4828 | 0.7937 | 0.4828 |
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+ | No log | 9.3333 | 168 | 0.4861 | 0.7937 | 0.4861 |
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+ | No log | 9.4444 | 170 | 0.4940 | 0.7848 | 0.4940 |
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+ | No log | 9.5556 | 172 | 0.5042 | 0.7810 | 0.5042 |
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+ | No log | 9.6667 | 174 | 0.5129 | 0.7810 | 0.5129 |
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+ | No log | 9.7778 | 176 | 0.5142 | 0.7810 | 0.5142 |
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+ | No log | 9.8889 | 178 | 0.5135 | 0.7810 | 0.5135 |
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+ | No log | 10.0 | 180 | 0.5141 | 0.7810 | 0.5141 |
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  ### Framework versions