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arabert_cross_organization_task6_fold3

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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_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_task6_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: 1.0752
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- - Qwk: 0.1211
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- - Mse: 1.0727
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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 | 3.7816 | 0.0007 | 3.7767 |
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- | No log | 0.2353 | 4 | 1.3542 | 0.0008 | 1.3493 |
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- | No log | 0.3529 | 6 | 0.8381 | 0.0381 | 0.8355 |
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- | No log | 0.4706 | 8 | 0.8831 | -0.0815 | 0.8796 |
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- | No log | 0.5882 | 10 | 0.8969 | 0.0429 | 0.8931 |
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- | No log | 0.7059 | 12 | 0.8250 | 0.0520 | 0.8218 |
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- | No log | 0.8235 | 14 | 1.0019 | 0.0182 | 0.9999 |
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- | No log | 0.9412 | 16 | 1.1717 | -0.0025 | 1.1701 |
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- | No log | 1.0588 | 18 | 1.2136 | -0.0025 | 1.2120 |
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- | No log | 1.1765 | 20 | 1.1606 | 0.0 | 1.1587 |
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- | No log | 1.2941 | 22 | 1.2446 | 0.0 | 1.2426 |
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- | No log | 1.4118 | 24 | 1.3967 | 0.0 | 1.3948 |
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- | No log | 1.5294 | 26 | 1.4847 | 0.0253 | 1.4827 |
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- | No log | 1.6471 | 28 | 1.3244 | 0.0231 | 1.3221 |
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- | No log | 1.7647 | 30 | 1.0785 | 0.0360 | 1.0760 |
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- | No log | 1.8824 | 32 | 0.8498 | 0.1972 | 0.8470 |
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- | No log | 2.0 | 34 | 0.9134 | 0.1247 | 0.9107 |
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- | No log | 2.1176 | 36 | 1.1156 | 0.0182 | 1.1130 |
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- | No log | 2.2353 | 38 | 1.0973 | 0.0 | 1.0948 |
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- | No log | 2.3529 | 40 | 1.0822 | 0.0182 | 1.0794 |
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- | No log | 2.4706 | 42 | 1.0078 | 0.0789 | 1.0047 |
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- | No log | 2.5882 | 44 | 1.1175 | 0.0880 | 1.1144 |
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- | No log | 2.7059 | 46 | 1.3284 | 0.0465 | 1.3253 |
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- | No log | 2.8235 | 48 | 1.6008 | 0.0931 | 1.5976 |
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- | No log | 2.9412 | 50 | 2.1079 | 0.0276 | 2.1049 |
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- | No log | 3.0588 | 52 | 2.2734 | 0.0412 | 2.2705 |
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- | No log | 3.1765 | 54 | 1.8347 | 0.1369 | 1.8320 |
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- | No log | 3.2941 | 56 | 1.3122 | 0.0884 | 1.3096 |
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- | No log | 3.4118 | 58 | 1.2595 | 0.0664 | 1.2569 |
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- | No log | 3.5294 | 60 | 1.4282 | 0.1006 | 1.4256 |
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- | No log | 3.6471 | 62 | 1.5462 | 0.1413 | 1.5436 |
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- | No log | 3.7647 | 64 | 1.3829 | 0.0593 | 1.3803 |
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- | No log | 3.8824 | 66 | 0.9939 | 0.1230 | 0.9914 |
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- | No log | 4.0 | 68 | 0.8054 | 0.1788 | 0.8030 |
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- | No log | 4.1176 | 70 | 0.7868 | 0.1816 | 0.7845 |
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- | No log | 4.2353 | 72 | 0.9015 | 0.1607 | 0.8991 |
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- | No log | 4.3529 | 74 | 1.2405 | 0.0483 | 1.2379 |
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- | No log | 4.4706 | 76 | 1.4275 | 0.0040 | 1.4247 |
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- | No log | 4.5882 | 78 | 1.3885 | 0.0201 | 1.3856 |
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- | No log | 4.7059 | 80 | 1.2664 | 0.0431 | 1.2634 |
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- | No log | 4.8235 | 82 | 1.0916 | 0.0750 | 1.0885 |
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- | No log | 4.9412 | 84 | 1.0885 | 0.0159 | 1.0854 |
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- | No log | 5.0588 | 86 | 1.1736 | 0.0869 | 1.1705 |
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- | No log | 5.1765 | 88 | 1.3914 | 0.1105 | 1.3885 |
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- | No log | 5.2941 | 90 | 1.5037 | 0.0839 | 1.5010 |
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- | No log | 5.4118 | 92 | 1.4052 | 0.0391 | 1.4026 |
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- | No log | 5.5294 | 94 | 1.2441 | 0.0662 | 1.2417 |
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- | No log | 5.6471 | 96 | 1.1952 | 0.0646 | 1.1929 |
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- | No log | 5.7647 | 98 | 1.1442 | 0.0814 | 1.1419 |
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- | No log | 5.8824 | 100 | 1.1950 | 0.0855 | 1.1926 |
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- | No log | 6.0 | 102 | 1.3191 | 0.0880 | 1.3167 |
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- | No log | 6.1176 | 104 | 1.4094 | 0.0999 | 1.4070 |
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- | No log | 6.2353 | 106 | 1.2755 | 0.1507 | 1.2730 |
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- | No log | 6.3529 | 108 | 1.0797 | 0.1262 | 1.0770 |
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- | No log | 6.4706 | 110 | 0.9830 | 0.1381 | 0.9804 |
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- | No log | 6.5882 | 112 | 0.9647 | 0.1405 | 0.9620 |
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- | No log | 6.7059 | 114 | 1.0370 | 0.1146 | 1.0345 |
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- | No log | 6.8235 | 116 | 1.1227 | 0.0885 | 1.1203 |
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- | No log | 6.9412 | 118 | 1.2057 | 0.1026 | 1.2033 |
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- | No log | 7.0588 | 120 | 1.2261 | 0.0518 | 1.2238 |
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- | No log | 7.1765 | 122 | 1.2047 | 0.0652 | 1.2023 |
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- | No log | 7.2941 | 124 | 1.0652 | 0.1195 | 1.0628 |
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- | No log | 7.4118 | 126 | 0.9603 | 0.1804 | 0.9578 |
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- | No log | 7.5294 | 128 | 0.9421 | 0.1812 | 0.9395 |
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- | No log | 7.6471 | 130 | 1.0068 | 0.1111 | 1.0041 |
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- | No log | 7.7647 | 132 | 1.1676 | 0.1367 | 1.1650 |
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- | No log | 7.8824 | 134 | 1.3081 | 0.1382 | 1.3055 |
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- | No log | 8.0 | 136 | 1.3954 | 0.1123 | 1.3929 |
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- | No log | 8.1176 | 138 | 1.3854 | 0.1123 | 1.3829 |
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- | No log | 8.2353 | 140 | 1.2987 | 0.1203 | 1.2962 |
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- | No log | 8.3529 | 142 | 1.1429 | 0.1190 | 1.1405 |
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- | No log | 8.4706 | 144 | 1.0515 | 0.1232 | 1.0491 |
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- | No log | 8.5882 | 146 | 1.0416 | 0.1371 | 1.0392 |
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- | No log | 8.7059 | 148 | 1.0625 | 0.1438 | 1.0601 |
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- | No log | 8.8235 | 150 | 1.0904 | 0.1152 | 1.0880 |
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- | No log | 8.9412 | 152 | 1.1358 | 0.1190 | 1.1334 |
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- | No log | 9.0588 | 154 | 1.1786 | 0.1043 | 1.1762 |
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- | No log | 9.1765 | 156 | 1.1978 | 0.1043 | 1.1954 |
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- | No log | 9.2941 | 158 | 1.1835 | 0.1043 | 1.1810 |
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- | No log | 9.4118 | 160 | 1.1423 | 0.1190 | 1.1399 |
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- | No log | 9.5294 | 162 | 1.1135 | 0.1336 | 1.1110 |
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- | No log | 9.6471 | 164 | 1.1006 | 0.1132 | 1.0981 |
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- | No log | 9.7647 | 166 | 1.0926 | 0.1277 | 1.0902 |
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- | No log | 9.8824 | 168 | 1.0805 | 0.1211 | 1.0780 |
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- | No log | 10.0 | 170 | 1.0752 | 0.1211 | 1.0727 |
 
 
 
 
 
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_organization_task6_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_task6_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: 1.3563
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+ - Qwk: -0.0016
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+ - Mse: 1.3563
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  ## 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 | 5.0067 | -0.0021 | 5.0067 |
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+ | No log | 0.2222 | 4 | 2.3688 | 0.0294 | 2.3688 |
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+ | No log | 0.3333 | 6 | 1.3423 | -0.0120 | 1.3423 |
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+ | No log | 0.4444 | 8 | 1.5207 | -0.0996 | 1.5207 |
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+ | No log | 0.5556 | 10 | 1.1292 | -0.0620 | 1.1292 |
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+ | No log | 0.6667 | 12 | 1.1093 | -0.0624 | 1.1093 |
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+ | No log | 0.7778 | 14 | 1.1280 | -0.1037 | 1.1280 |
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+ | No log | 0.8889 | 16 | 1.1271 | -0.0458 | 1.1271 |
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+ | No log | 1.0 | 18 | 1.1353 | -0.0286 | 1.1353 |
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+ | No log | 1.1111 | 20 | 1.2273 | 0.0 | 1.2273 |
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+ | No log | 1.2222 | 22 | 1.1922 | 0.0071 | 1.1922 |
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+ | No log | 1.3333 | 24 | 1.1874 | 0.0071 | 1.1874 |
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+ | No log | 1.4444 | 26 | 1.1668 | -0.0325 | 1.1668 |
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+ | No log | 1.5556 | 28 | 1.1666 | -0.0039 | 1.1666 |
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+ | No log | 1.6667 | 30 | 1.1595 | -0.0073 | 1.1595 |
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+ | No log | 1.7778 | 32 | 1.1718 | 0.0290 | 1.1718 |
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+ | No log | 1.8889 | 34 | 1.2238 | 0.0 | 1.2238 |
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+ | No log | 2.0 | 36 | 1.2276 | 0.0 | 1.2276 |
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+ | No log | 2.1111 | 38 | 1.1870 | -0.0366 | 1.1870 |
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+ | No log | 2.2222 | 40 | 1.1871 | -0.0785 | 1.1871 |
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+ | No log | 2.3333 | 42 | 1.2823 | -0.0775 | 1.2823 |
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+ | No log | 2.4444 | 44 | 1.2667 | -0.0775 | 1.2667 |
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+ | No log | 2.5556 | 46 | 1.1897 | -0.1036 | 1.1897 |
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+ | No log | 2.6667 | 48 | 1.2024 | -0.0005 | 1.2024 |
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+ | No log | 2.7778 | 50 | 1.2359 | -0.0107 | 1.2359 |
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+ | No log | 2.8889 | 52 | 1.2436 | -0.0073 | 1.2436 |
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+ | No log | 3.0 | 54 | 1.2335 | -0.0335 | 1.2335 |
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+ | No log | 3.1111 | 56 | 1.2366 | -0.0073 | 1.2366 |
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+ | No log | 3.2222 | 58 | 1.2111 | -0.0305 | 1.2111 |
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+ | No log | 3.3333 | 60 | 1.1935 | 0.0372 | 1.1935 |
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+ | No log | 3.4444 | 62 | 1.2135 | -0.0513 | 1.2135 |
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+ | No log | 3.5556 | 64 | 1.2077 | -0.0335 | 1.2077 |
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+ | No log | 3.6667 | 66 | 1.2202 | 0.0152 | 1.2202 |
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+ | No log | 3.7778 | 68 | 1.2293 | 0.0152 | 1.2293 |
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+ | No log | 3.8889 | 70 | 1.2441 | 0.0021 | 1.2441 |
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+ | No log | 4.0 | 72 | 1.2616 | 0.0583 | 1.2616 |
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+ | No log | 4.1111 | 74 | 1.2524 | -0.0046 | 1.2524 |
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+ | No log | 4.2222 | 76 | 1.2555 | -0.0433 | 1.2555 |
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+ | No log | 4.3333 | 78 | 1.2534 | 0.0522 | 1.2534 |
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+ | No log | 4.4444 | 80 | 1.2663 | 0.0174 | 1.2663 |
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+ | No log | 4.5556 | 82 | 1.2903 | -0.0521 | 1.2903 |
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+ | No log | 4.6667 | 84 | 1.2865 | -0.0521 | 1.2865 |
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+ | No log | 4.7778 | 86 | 1.2537 | -0.0389 | 1.2537 |
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+ | No log | 4.8889 | 88 | 1.2394 | -0.0348 | 1.2394 |
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+ | No log | 5.0 | 90 | 1.2581 | -0.0668 | 1.2581 |
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+ | No log | 5.1111 | 92 | 1.2785 | -0.0442 | 1.2785 |
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+ | No log | 5.2222 | 94 | 1.2996 | 0.0353 | 1.2996 |
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+ | No log | 5.3333 | 96 | 1.3274 | 0.0118 | 1.3274 |
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+ | No log | 5.4444 | 98 | 1.3336 | -0.0386 | 1.3336 |
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+ | No log | 5.5556 | 100 | 1.2963 | -0.0161 | 1.2963 |
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+ | No log | 5.6667 | 102 | 1.2938 | 0.0144 | 1.2938 |
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+ | No log | 5.7778 | 104 | 1.3454 | -0.0160 | 1.3454 |
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+ | No log | 5.8889 | 106 | 1.3525 | -0.0233 | 1.3525 |
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+ | No log | 6.0 | 108 | 1.3385 | 0.0349 | 1.3385 |
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+ | No log | 6.1111 | 110 | 1.3741 | -0.0338 | 1.3741 |
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+ | No log | 6.2222 | 112 | 1.4104 | -0.0362 | 1.4104 |
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+ | No log | 6.3333 | 114 | 1.4214 | -0.0478 | 1.4214 |
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+ | No log | 6.4444 | 116 | 1.4394 | -0.0301 | 1.4394 |
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+ | No log | 6.5556 | 118 | 1.4439 | -0.0301 | 1.4439 |
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+ | No log | 6.6667 | 120 | 1.3931 | -0.0486 | 1.3931 |
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+ | No log | 6.7778 | 122 | 1.3303 | -0.0123 | 1.3303 |
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+ | No log | 6.8889 | 124 | 1.2675 | -0.0795 | 1.2675 |
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+ | No log | 7.0 | 126 | 1.2466 | -0.0580 | 1.2466 |
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+ | No log | 7.1111 | 128 | 1.2543 | -0.0097 | 1.2543 |
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+ | No log | 7.2222 | 130 | 1.2895 | -0.0149 | 1.2895 |
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+ | No log | 7.3333 | 132 | 1.3307 | 0.0443 | 1.3307 |
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+ | No log | 7.4444 | 134 | 1.3809 | -0.0384 | 1.3809 |
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+ | No log | 7.5556 | 136 | 1.4319 | -0.1211 | 1.4319 |
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+ | No log | 7.6667 | 138 | 1.4611 | -0.0542 | 1.4611 |
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+ | No log | 7.7778 | 140 | 1.4378 | -0.0509 | 1.4378 |
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+ | No log | 7.8889 | 142 | 1.3913 | -0.0200 | 1.3913 |
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+ | No log | 8.0 | 144 | 1.3657 | -0.0247 | 1.3657 |
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+ | No log | 8.1111 | 146 | 1.3785 | -0.0093 | 1.3785 |
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+ | No log | 8.2222 | 148 | 1.3631 | 0.0143 | 1.3631 |
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+ | No log | 8.3333 | 150 | 1.3158 | -0.0532 | 1.3158 |
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+ | No log | 8.4444 | 152 | 1.2825 | 0.0371 | 1.2825 |
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+ | No log | 8.5556 | 154 | 1.2704 | 0.0035 | 1.2704 |
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+ | No log | 8.6667 | 156 | 1.2773 | 0.0377 | 1.2773 |
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+ | No log | 8.7778 | 158 | 1.2959 | 0.0377 | 1.2959 |
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+ | No log | 8.8889 | 160 | 1.3175 | 0.0625 | 1.3175 |
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+ | No log | 9.0 | 162 | 1.3404 | -0.0274 | 1.3404 |
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+ | No log | 9.1111 | 164 | 1.3572 | -0.0400 | 1.3572 |
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+ | No log | 9.2222 | 166 | 1.3639 | -0.0274 | 1.3639 |
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+ | No log | 9.3333 | 168 | 1.3672 | -0.0274 | 1.3672 |
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+ | No log | 9.4444 | 170 | 1.3652 | -0.0274 | 1.3652 |
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+ | No log | 9.5556 | 172 | 1.3654 | -0.0146 | 1.3654 |
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+ | No log | 9.6667 | 174 | 1.3609 | -0.0016 | 1.3609 |
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+ | No log | 9.7778 | 176 | 1.3588 | -0.0016 | 1.3588 |
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+ | No log | 9.8889 | 178 | 1.3572 | -0.0016 | 1.3572 |
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+ | No log | 10.0 | 180 | 1.3563 | -0.0016 | 1.3563 |
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  ### Framework versions