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arabert_cross_organization_task1_fold3

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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_task1_fold2
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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_task1_fold2
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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: 1.1732
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- - Qwk: 0.1337
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- - Mse: 1.1732
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  ## Model description
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@@ -45,93 +45,83 @@ 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 | 4.6922 | -0.0262 | 4.6922 |
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- | No log | 0.2353 | 4 | 1.9697 | -0.0193 | 1.9697 |
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- | No log | 0.3529 | 6 | 1.2474 | -0.0024 | 1.2474 |
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- | No log | 0.4706 | 8 | 1.3039 | -0.1115 | 1.3039 |
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- | No log | 0.5882 | 10 | 1.2027 | -0.0222 | 1.2027 |
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- | No log | 0.7059 | 12 | 1.1028 | 0.0290 | 1.1028 |
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- | No log | 0.8235 | 14 | 1.1603 | 0.0257 | 1.1603 |
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- | No log | 0.9412 | 16 | 1.1285 | -0.0227 | 1.1285 |
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- | No log | 1.0588 | 18 | 1.1018 | 0.0835 | 1.1018 |
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- | No log | 1.1765 | 20 | 1.1034 | -0.0341 | 1.1034 |
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- | No log | 1.2941 | 22 | 1.0966 | 0.0201 | 1.0966 |
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- | No log | 1.4118 | 24 | 1.0911 | 0.0407 | 1.0911 |
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- | No log | 1.5294 | 26 | 1.0941 | 0.0854 | 1.0941 |
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- | No log | 1.6471 | 28 | 1.1027 | 0.0379 | 1.1027 |
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- | No log | 1.7647 | 30 | 1.1067 | 0.0462 | 1.1067 |
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- | No log | 1.8824 | 32 | 1.1142 | -0.0019 | 1.1142 |
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- | No log | 2.0 | 34 | 1.1210 | 0.0205 | 1.1210 |
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- | No log | 2.1176 | 36 | 1.1209 | 0.0124 | 1.1209 |
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- | No log | 2.2353 | 38 | 1.1138 | 0.0345 | 1.1138 |
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- | No log | 2.3529 | 40 | 1.1537 | 0.0350 | 1.1537 |
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- | No log | 2.4706 | 42 | 1.1387 | 0.0164 | 1.1387 |
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- | No log | 2.5882 | 44 | 1.1467 | 0.0448 | 1.1467 |
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- | No log | 2.7059 | 46 | 1.1779 | 0.0372 | 1.1779 |
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- | No log | 2.8235 | 48 | 1.1734 | 0.0435 | 1.1734 |
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- | No log | 2.9412 | 50 | 1.0971 | 0.0562 | 1.0971 |
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- | No log | 3.0588 | 52 | 1.0868 | 0.0993 | 1.0868 |
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- | No log | 3.1765 | 54 | 1.1937 | 0.0208 | 1.1937 |
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- | No log | 3.2941 | 56 | 1.1870 | -0.0026 | 1.1870 |
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- | No log | 3.4118 | 58 | 1.1154 | 0.0605 | 1.1154 |
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- | No log | 3.5294 | 60 | 1.1425 | 0.0586 | 1.1425 |
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- | No log | 3.6471 | 62 | 1.1710 | 0.0755 | 1.1710 |
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- | No log | 3.7647 | 64 | 1.2418 | -0.0251 | 1.2418 |
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- | No log | 3.8824 | 66 | 1.2678 | -0.0157 | 1.2678 |
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- | No log | 4.0 | 68 | 1.3259 | -0.0370 | 1.3259 |
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- | No log | 4.1176 | 70 | 1.4421 | -0.0243 | 1.4421 |
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- | No log | 4.2353 | 72 | 1.3217 | -0.0265 | 1.3217 |
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- | No log | 4.3529 | 74 | 1.1731 | 0.1242 | 1.1731 |
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- | No log | 4.4706 | 76 | 1.1656 | 0.1082 | 1.1656 |
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- | No log | 4.5882 | 78 | 1.2346 | -0.0387 | 1.2346 |
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- | No log | 4.7059 | 80 | 1.3196 | 0.0306 | 1.3196 |
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- | No log | 4.8235 | 82 | 1.2508 | -0.0093 | 1.2508 |
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- | No log | 4.9412 | 84 | 1.1905 | -0.0118 | 1.1905 |
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- | No log | 5.0588 | 86 | 1.1863 | 0.0002 | 1.1863 |
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- | No log | 5.1765 | 88 | 1.2464 | 0.0063 | 1.2464 |
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- | No log | 5.2941 | 90 | 1.2248 | 0.0177 | 1.2248 |
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- | No log | 5.4118 | 92 | 1.2140 | 0.0391 | 1.2140 |
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- | No log | 5.5294 | 94 | 1.2402 | 0.0177 | 1.2402 |
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- | No log | 5.6471 | 96 | 1.1852 | 0.1192 | 1.1852 |
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- | No log | 5.7647 | 98 | 1.1973 | 0.0602 | 1.1973 |
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- | No log | 5.8824 | 100 | 1.2330 | 0.0886 | 1.2330 |
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- | No log | 6.0 | 102 | 1.1570 | 0.0504 | 1.1570 |
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- | No log | 6.1176 | 104 | 1.1259 | 0.1211 | 1.1259 |
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- | No log | 6.2353 | 106 | 1.1231 | 0.1211 | 1.1231 |
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- | No log | 6.3529 | 108 | 1.1216 | 0.0835 | 1.1216 |
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- | No log | 6.4706 | 110 | 1.1530 | 0.0907 | 1.1530 |
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- | No log | 6.5882 | 112 | 1.1410 | 0.1176 | 1.1410 |
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- | No log | 6.7059 | 114 | 1.1564 | 0.1120 | 1.1564 |
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- | No log | 6.8235 | 116 | 1.2102 | 0.0988 | 1.2102 |
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- | No log | 6.9412 | 118 | 1.2596 | 0.0681 | 1.2596 |
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- | No log | 7.0588 | 120 | 1.2375 | 0.0722 | 1.2375 |
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- | No log | 7.1765 | 122 | 1.1821 | 0.1425 | 1.1821 |
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- | No log | 7.2941 | 124 | 1.1856 | 0.1180 | 1.1856 |
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- | No log | 7.4118 | 126 | 1.1952 | 0.1542 | 1.1952 |
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- | No log | 7.5294 | 128 | 1.2010 | 0.1643 | 1.2010 |
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- | No log | 7.6471 | 130 | 1.1966 | 0.1542 | 1.1966 |
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- | No log | 7.7647 | 132 | 1.2024 | 0.1589 | 1.2024 |
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- | No log | 7.8824 | 134 | 1.2473 | 0.0820 | 1.2473 |
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- | No log | 8.0 | 136 | 1.2492 | 0.0847 | 1.2492 |
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- | No log | 8.1176 | 138 | 1.2147 | 0.1538 | 1.2147 |
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- | No log | 8.2353 | 140 | 1.1859 | 0.0946 | 1.1859 |
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- | No log | 8.3529 | 142 | 1.1767 | 0.1220 | 1.1767 |
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- | No log | 8.4706 | 144 | 1.1738 | 0.1091 | 1.1738 |
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- | No log | 8.5882 | 146 | 1.1774 | 0.1326 | 1.1774 |
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- | No log | 8.7059 | 148 | 1.1779 | 0.1337 | 1.1779 |
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- | No log | 8.8235 | 150 | 1.1724 | 0.1326 | 1.1724 |
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- | No log | 8.9412 | 152 | 1.1684 | 0.1303 | 1.1684 |
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- | No log | 9.0588 | 154 | 1.1673 | 0.1468 | 1.1673 |
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- | No log | 9.1765 | 156 | 1.1674 | 0.1468 | 1.1674 |
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- | No log | 9.2941 | 158 | 1.1677 | 0.1326 | 1.1677 |
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- | No log | 9.4118 | 160 | 1.1752 | 0.1369 | 1.1752 |
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- | No log | 9.5294 | 162 | 1.1826 | 0.1538 | 1.1826 |
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- | No log | 9.6471 | 164 | 1.1796 | 0.1229 | 1.1796 |
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- | No log | 9.7647 | 166 | 1.1767 | 0.1369 | 1.1767 |
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- | No log | 9.8824 | 168 | 1.1735 | 0.1337 | 1.1735 |
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- | No log | 10.0 | 170 | 1.1732 | 0.1337 | 1.1732 |
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_organization_task1_fold3
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_task1_fold3
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: 0.5415
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+ - Qwk: 0.7472
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+ - Mse: 0.5415
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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 | 0.1333 | 2 | 1.8315 | 0.1530 | 1.8315 |
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+ | No log | 0.2667 | 4 | 1.4232 | 0.1303 | 1.4232 |
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+ | No log | 0.4 | 6 | 1.3057 | 0.4221 | 1.3057 |
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+ | No log | 0.5333 | 8 | 0.9837 | 0.5056 | 0.9837 |
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+ | No log | 0.6667 | 10 | 0.9513 | 0.7091 | 0.9513 |
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+ | No log | 0.8 | 12 | 0.8371 | 0.7415 | 0.8371 |
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+ | No log | 0.9333 | 14 | 0.7233 | 0.6918 | 0.7233 |
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+ | No log | 1.0667 | 16 | 0.6922 | 0.7196 | 0.6922 |
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+ | No log | 1.2 | 18 | 0.6535 | 0.7225 | 0.6535 |
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+ | No log | 1.3333 | 20 | 0.6214 | 0.6382 | 0.6214 |
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+ | No log | 1.4667 | 22 | 0.6214 | 0.6481 | 0.6214 |
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+ | No log | 1.6 | 24 | 0.6577 | 0.6929 | 0.6577 |
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+ | No log | 1.7333 | 26 | 0.6144 | 0.6652 | 0.6144 |
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+ | No log | 1.8667 | 28 | 0.7474 | 0.5722 | 0.7474 |
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+ | No log | 2.0 | 30 | 0.6810 | 0.6294 | 0.6810 |
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+ | No log | 2.1333 | 32 | 0.6202 | 0.7358 | 0.6202 |
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+ | No log | 2.2667 | 34 | 0.6151 | 0.6751 | 0.6151 |
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+ | No log | 2.4 | 36 | 0.6002 | 0.6738 | 0.6002 |
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+ | No log | 2.5333 | 38 | 0.5749 | 0.7000 | 0.5749 |
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+ | No log | 2.6667 | 40 | 0.5666 | 0.7675 | 0.5666 |
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+ | No log | 2.8 | 42 | 0.6051 | 0.7937 | 0.6051 |
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+ | No log | 2.9333 | 44 | 0.5435 | 0.7839 | 0.5435 |
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+ | No log | 3.0667 | 46 | 0.5462 | 0.6799 | 0.5462 |
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+ | No log | 3.2 | 48 | 0.5199 | 0.7618 | 0.5199 |
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+ | No log | 3.3333 | 50 | 0.5686 | 0.7827 | 0.5686 |
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+ | No log | 3.4667 | 52 | 0.5681 | 0.7750 | 0.5681 |
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+ | No log | 3.6 | 54 | 0.5202 | 0.7756 | 0.5202 |
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+ | No log | 3.7333 | 56 | 0.5295 | 0.7412 | 0.5295 |
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+ | No log | 3.8667 | 58 | 0.5478 | 0.7632 | 0.5478 |
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+ | No log | 4.0 | 60 | 0.5733 | 0.7573 | 0.5733 |
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+ | No log | 4.1333 | 62 | 0.6257 | 0.7566 | 0.6257 |
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+ | No log | 4.2667 | 64 | 0.5977 | 0.7451 | 0.5977 |
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+ | No log | 4.4 | 66 | 0.6316 | 0.6778 | 0.6316 |
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+ | No log | 4.5333 | 68 | 0.5693 | 0.7216 | 0.5693 |
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+ | No log | 4.6667 | 70 | 0.5614 | 0.7730 | 0.5614 |
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+ | No log | 4.8 | 72 | 0.5561 | 0.7771 | 0.5561 |
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+ | No log | 4.9333 | 74 | 0.5439 | 0.7692 | 0.5439 |
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+ | No log | 5.0667 | 76 | 0.5722 | 0.7788 | 0.5722 |
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+ | No log | 5.2 | 78 | 0.5816 | 0.7777 | 0.5816 |
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+ | No log | 5.3333 | 80 | 0.5828 | 0.7436 | 0.5828 |
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+ | No log | 5.4667 | 82 | 0.5916 | 0.6944 | 0.5916 |
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+ | No log | 5.6 | 84 | 0.5655 | 0.7296 | 0.5655 |
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+ | No log | 5.7333 | 86 | 0.5767 | 0.7728 | 0.5767 |
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+ | No log | 5.8667 | 88 | 0.5590 | 0.7795 | 0.5590 |
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+ | No log | 6.0 | 90 | 0.5207 | 0.7385 | 0.5207 |
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+ | No log | 6.1333 | 92 | 0.5177 | 0.7374 | 0.5177 |
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+ | No log | 6.2667 | 94 | 0.5230 | 0.7756 | 0.5230 |
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+ | No log | 6.4 | 96 | 0.5599 | 0.7771 | 0.5599 |
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+ | No log | 6.5333 | 98 | 0.5687 | 0.7802 | 0.5687 |
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+ | No log | 6.6667 | 100 | 0.5450 | 0.7589 | 0.5450 |
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+ | No log | 6.8 | 102 | 0.5470 | 0.7329 | 0.5470 |
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+ | No log | 6.9333 | 104 | 0.5539 | 0.7073 | 0.5539 |
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+ | No log | 7.0667 | 106 | 0.5586 | 0.7035 | 0.5586 |
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+ | No log | 7.2 | 108 | 0.5647 | 0.7449 | 0.5647 |
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+ | No log | 7.3333 | 110 | 0.5807 | 0.7533 | 0.5807 |
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+ | No log | 7.4667 | 112 | 0.5667 | 0.7369 | 0.5667 |
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+ | No log | 7.6 | 114 | 0.5602 | 0.7153 | 0.5602 |
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+ | No log | 7.7333 | 116 | 0.5570 | 0.7251 | 0.5570 |
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+ | No log | 7.8667 | 118 | 0.5524 | 0.7335 | 0.5524 |
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+ | No log | 8.0 | 120 | 0.5563 | 0.7569 | 0.5563 |
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+ | No log | 8.1333 | 122 | 0.5503 | 0.7474 | 0.5503 |
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+ | No log | 8.2667 | 124 | 0.5434 | 0.7544 | 0.5434 |
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+ | No log | 8.4 | 126 | 0.5579 | 0.7695 | 0.5579 |
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+ | No log | 8.5333 | 128 | 0.5668 | 0.7794 | 0.5668 |
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+ | No log | 8.6667 | 130 | 0.5537 | 0.7567 | 0.5537 |
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+ | No log | 8.8 | 132 | 0.5391 | 0.7511 | 0.5391 |
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+ | No log | 8.9333 | 134 | 0.5365 | 0.7457 | 0.5365 |
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+ | No log | 9.0667 | 136 | 0.5367 | 0.7452 | 0.5367 |
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+ | No log | 9.2 | 138 | 0.5391 | 0.7439 | 0.5391 |
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+ | No log | 9.3333 | 140 | 0.5431 | 0.7438 | 0.5431 |
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+ | No log | 9.4667 | 142 | 0.5435 | 0.7438 | 0.5435 |
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+ | No log | 9.6 | 144 | 0.5455 | 0.7477 | 0.5455 |
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+ | No log | 9.7333 | 146 | 0.5440 | 0.7438 | 0.5440 |
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+ | No log | 9.8667 | 148 | 0.5422 | 0.7427 | 0.5422 |
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+ | No log | 10.0 | 150 | 0.5415 | 0.7472 | 0.5415 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions