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arabert_cross_organization_task7_fold4

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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_task7_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_task7_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: 1.2477
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- - Qwk: 0.0397
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- - Mse: 1.2477
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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 | 4.6630 | -0.0214 | 4.6630 |
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- | No log | 0.2353 | 4 | 1.9131 | -0.0296 | 1.9131 |
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- | No log | 0.3529 | 6 | 1.4779 | 0.0333 | 1.4779 |
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- | No log | 0.4706 | 8 | 1.3898 | -0.0031 | 1.3898 |
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- | No log | 0.5882 | 10 | 1.1632 | -0.0182 | 1.1632 |
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- | No log | 0.7059 | 12 | 1.2046 | 0.0046 | 1.2046 |
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- | No log | 0.8235 | 14 | 1.1480 | -0.0723 | 1.1480 |
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- | No log | 0.9412 | 16 | 1.1436 | -0.0110 | 1.1436 |
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- | No log | 1.0588 | 18 | 1.1619 | -0.0110 | 1.1619 |
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- | No log | 1.1765 | 20 | 1.1482 | -0.0110 | 1.1482 |
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- | No log | 1.2941 | 22 | 1.1202 | -0.0110 | 1.1202 |
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- | No log | 1.4118 | 24 | 1.1170 | 0.0062 | 1.1170 |
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- | No log | 1.5294 | 26 | 1.1174 | 0.0413 | 1.1174 |
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- | No log | 1.6471 | 28 | 1.1486 | -0.0248 | 1.1486 |
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- | No log | 1.7647 | 30 | 1.2697 | 0.0 | 1.2697 |
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- | No log | 1.8824 | 32 | 1.2498 | -0.0147 | 1.2498 |
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- | No log | 2.0 | 34 | 1.1692 | -0.0248 | 1.1692 |
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- | No log | 2.1176 | 36 | 1.1913 | -0.0203 | 1.1913 |
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- | No log | 2.2353 | 38 | 1.2360 | -0.0255 | 1.2360 |
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- | No log | 2.3529 | 40 | 1.1562 | -0.0046 | 1.1562 |
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- | No log | 2.4706 | 42 | 1.1715 | -0.0074 | 1.1715 |
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- | No log | 2.5882 | 44 | 1.2562 | -0.0147 | 1.2562 |
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- | No log | 2.7059 | 46 | 1.1883 | -0.0039 | 1.1883 |
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- | No log | 2.8235 | 48 | 1.1458 | 0.0518 | 1.1458 |
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- | No log | 2.9412 | 50 | 1.2475 | -0.0289 | 1.2475 |
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- | No log | 3.0588 | 52 | 1.3234 | 0.0059 | 1.3234 |
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- | No log | 3.1765 | 54 | 1.1838 | -0.0002 | 1.1838 |
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- | No log | 3.2941 | 56 | 1.1405 | 0.0753 | 1.1405 |
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- | No log | 3.4118 | 58 | 1.1817 | 0.0686 | 1.1817 |
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- | No log | 3.5294 | 60 | 1.1663 | 0.0753 | 1.1663 |
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- | No log | 3.6471 | 62 | 1.1574 | 0.0944 | 1.1574 |
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- | No log | 3.7647 | 64 | 1.1895 | 0.0474 | 1.1895 |
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- | No log | 3.8824 | 66 | 1.1771 | 0.0160 | 1.1771 |
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- | No log | 4.0 | 68 | 1.1811 | 0.0725 | 1.1811 |
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- | No log | 4.1176 | 70 | 1.2361 | 0.0469 | 1.2361 |
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- | No log | 4.2353 | 72 | 1.2386 | 0.0650 | 1.2386 |
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- | No log | 4.3529 | 74 | 1.1740 | 0.1183 | 1.1740 |
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- | No log | 4.4706 | 76 | 1.1578 | 0.1142 | 1.1578 |
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- | No log | 4.5882 | 78 | 1.1478 | 0.0927 | 1.1478 |
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- | No log | 4.7059 | 80 | 1.1556 | 0.0890 | 1.1556 |
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- | No log | 4.8235 | 82 | 1.1743 | 0.0682 | 1.1743 |
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- | No log | 4.9412 | 84 | 1.1621 | 0.0682 | 1.1621 |
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- | No log | 5.0588 | 86 | 1.1329 | 0.0963 | 1.1329 |
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- | No log | 5.1765 | 88 | 1.1322 | 0.1113 | 1.1322 |
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- | No log | 5.2941 | 90 | 1.1440 | 0.1234 | 1.1440 |
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- | No log | 5.4118 | 92 | 1.2118 | 0.0376 | 1.2118 |
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- | No log | 5.5294 | 94 | 1.2862 | 0.0713 | 1.2862 |
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- | No log | 5.6471 | 96 | 1.3217 | 0.0599 | 1.3217 |
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- | No log | 5.7647 | 98 | 1.2121 | 0.0624 | 1.2121 |
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- | No log | 5.8824 | 100 | 1.1592 | 0.1501 | 1.1592 |
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- | No log | 6.0 | 102 | 1.1912 | 0.0385 | 1.1912 |
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- | No log | 6.1176 | 104 | 1.1673 | 0.0828 | 1.1673 |
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- | No log | 6.2353 | 106 | 1.1644 | 0.0448 | 1.1644 |
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- | No log | 6.3529 | 108 | 1.2438 | 0.0629 | 1.2438 |
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- | No log | 6.4706 | 110 | 1.3083 | 0.0622 | 1.3083 |
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- | No log | 6.5882 | 112 | 1.2970 | 0.0470 | 1.2970 |
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- | No log | 6.7059 | 114 | 1.2160 | 0.0295 | 1.2160 |
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- | No log | 6.8235 | 116 | 1.1682 | 0.0881 | 1.1682 |
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- | No log | 6.9412 | 118 | 1.1659 | 0.0898 | 1.1659 |
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- | No log | 7.0588 | 120 | 1.1694 | 0.1029 | 1.1694 |
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- | No log | 7.1765 | 122 | 1.1813 | 0.0829 | 1.1813 |
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- | No log | 7.2941 | 124 | 1.1840 | 0.0847 | 1.1840 |
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- | No log | 7.4118 | 126 | 1.1941 | 0.0847 | 1.1941 |
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- | No log | 7.5294 | 128 | 1.2296 | 0.0915 | 1.2296 |
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- | No log | 7.6471 | 130 | 1.2731 | 0.0561 | 1.2731 |
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- | No log | 7.7647 | 132 | 1.2863 | 0.0680 | 1.2863 |
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- | No log | 7.8824 | 134 | 1.2644 | 0.0391 | 1.2644 |
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- | No log | 8.0 | 136 | 1.2471 | 0.0771 | 1.2471 |
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- | No log | 8.1176 | 138 | 1.2423 | 0.0789 | 1.2423 |
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- | No log | 8.2353 | 140 | 1.2401 | 0.0596 | 1.2401 |
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- | No log | 8.3529 | 142 | 1.2475 | 0.0596 | 1.2475 |
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- | No log | 8.4706 | 144 | 1.2539 | 0.0703 | 1.2539 |
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- | No log | 8.5882 | 146 | 1.2593 | 0.0794 | 1.2593 |
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- | No log | 8.7059 | 148 | 1.2770 | 0.0551 | 1.2770 |
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- | No log | 8.8235 | 150 | 1.2937 | 0.0858 | 1.2937 |
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- | No log | 8.9412 | 152 | 1.2970 | 0.0840 | 1.2970 |
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- | No log | 9.0588 | 154 | 1.3005 | 0.0657 | 1.3005 |
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- | No log | 9.1765 | 156 | 1.2860 | 0.0657 | 1.2860 |
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- | No log | 9.2941 | 158 | 1.2799 | 0.0355 | 1.2799 |
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- | No log | 9.4118 | 160 | 1.2697 | 0.0407 | 1.2697 |
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- | No log | 9.5294 | 162 | 1.2616 | 0.0653 | 1.2616 |
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- | No log | 9.6471 | 164 | 1.2564 | 0.0374 | 1.2564 |
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- | No log | 9.7647 | 166 | 1.2527 | 0.0397 | 1.2527 |
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- | No log | 9.8824 | 168 | 1.2493 | 0.0397 | 1.2493 |
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- | No log | 10.0 | 170 | 1.2477 | 0.0397 | 1.2477 |
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_organization_task7_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_task7_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.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5739
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+ - Qwk: 0.7967
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+ - Mse: 0.5739
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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 | 1.9448 | 0.1649 | 1.9447 |
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+ | No log | 0.2667 | 4 | 1.4779 | 0.0771 | 1.4779 |
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+ | No log | 0.4 | 6 | 1.3512 | 0.4234 | 1.3512 |
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+ | No log | 0.5333 | 8 | 0.9818 | 0.5170 | 0.9818 |
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+ | No log | 0.6667 | 10 | 0.9848 | 0.7218 | 0.9848 |
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+ | No log | 0.8 | 12 | 0.7546 | 0.7580 | 0.7546 |
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+ | No log | 0.9333 | 14 | 0.6613 | 0.7635 | 0.6613 |
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+ | No log | 1.0667 | 16 | 0.5901 | 0.7415 | 0.5901 |
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+ | No log | 1.2 | 18 | 0.5891 | 0.6836 | 0.5891 |
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+ | No log | 1.3333 | 20 | 0.6666 | 0.7927 | 0.6666 |
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+ | No log | 1.4667 | 22 | 0.7821 | 0.7742 | 0.7821 |
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+ | No log | 1.6 | 24 | 0.5788 | 0.7710 | 0.5788 |
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+ | No log | 1.7333 | 26 | 0.5726 | 0.6635 | 0.5726 |
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+ | No log | 1.8667 | 28 | 0.5773 | 0.7575 | 0.5773 |
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+ | No log | 2.0 | 30 | 0.8482 | 0.7672 | 0.8482 |
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+ | No log | 2.1333 | 32 | 0.9640 | 0.7499 | 0.9640 |
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+ | No log | 2.2667 | 34 | 0.7191 | 0.7738 | 0.7191 |
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+ | No log | 2.4 | 36 | 0.5565 | 0.7624 | 0.5565 |
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+ | No log | 2.5333 | 38 | 0.5998 | 0.6630 | 0.5998 |
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+ | No log | 2.6667 | 40 | 0.5526 | 0.7554 | 0.5526 |
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+ | No log | 2.8 | 42 | 0.6355 | 0.7866 | 0.6355 |
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+ | No log | 2.9333 | 44 | 0.7893 | 0.7696 | 0.7893 |
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+ | No log | 3.0667 | 46 | 0.7015 | 0.7820 | 0.7015 |
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+ | No log | 3.2 | 48 | 0.5349 | 0.7719 | 0.5349 |
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+ | No log | 3.3333 | 50 | 0.5250 | 0.7364 | 0.5250 |
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+ | No log | 3.4667 | 52 | 0.5324 | 0.7720 | 0.5324 |
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+ | No log | 3.6 | 54 | 0.6922 | 0.7790 | 0.6922 |
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+ | No log | 3.7333 | 56 | 0.7969 | 0.7647 | 0.7969 |
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+ | No log | 3.8667 | 58 | 0.7515 | 0.7687 | 0.7515 |
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+ | No log | 4.0 | 60 | 0.5754 | 0.7791 | 0.5754 |
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+ | No log | 4.1333 | 62 | 0.5295 | 0.7890 | 0.5295 |
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+ | No log | 4.2667 | 64 | 0.5568 | 0.7950 | 0.5568 |
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+ | No log | 4.4 | 66 | 0.6597 | 0.7830 | 0.6597 |
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+ | No log | 4.5333 | 68 | 0.7200 | 0.7855 | 0.7200 |
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+ | No log | 4.6667 | 70 | 0.6382 | 0.7912 | 0.6382 |
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+ | No log | 4.8 | 72 | 0.5464 | 0.7964 | 0.5464 |
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+ | No log | 4.9333 | 74 | 0.5642 | 0.7927 | 0.5642 |
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+ | No log | 5.0667 | 76 | 0.5529 | 0.7877 | 0.5529 |
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+ | No log | 5.2 | 78 | 0.5685 | 0.7941 | 0.5685 |
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+ | No log | 5.3333 | 80 | 0.5692 | 0.8019 | 0.5692 |
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+ | No log | 5.4667 | 82 | 0.5649 | 0.8048 | 0.5649 |
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+ | No log | 5.6 | 84 | 0.5735 | 0.8008 | 0.5735 |
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+ | No log | 5.7333 | 86 | 0.5626 | 0.7884 | 0.5626 |
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+ | No log | 5.8667 | 88 | 0.5496 | 0.7807 | 0.5496 |
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+ | No log | 6.0 | 90 | 0.5597 | 0.7832 | 0.5597 |
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+ | No log | 6.1333 | 92 | 0.5892 | 0.8044 | 0.5892 |
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+ | No log | 6.2667 | 94 | 0.5985 | 0.8021 | 0.5985 |
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+ | No log | 6.4 | 96 | 0.5764 | 0.7946 | 0.5764 |
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+ | No log | 6.5333 | 98 | 0.5254 | 0.7832 | 0.5254 |
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+ | No log | 6.6667 | 100 | 0.5198 | 0.7806 | 0.5198 |
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+ | No log | 6.8 | 102 | 0.5624 | 0.7979 | 0.5624 |
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+ | No log | 6.9333 | 104 | 0.5920 | 0.7935 | 0.5920 |
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+ | No log | 7.0667 | 106 | 0.6267 | 0.8062 | 0.6267 |
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+ | No log | 7.2 | 108 | 0.6433 | 0.8077 | 0.6433 |
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+ | No log | 7.3333 | 110 | 0.5670 | 0.7975 | 0.5670 |
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+ | No log | 7.4667 | 112 | 0.5349 | 0.7881 | 0.5349 |
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+ | No log | 7.6 | 114 | 0.5360 | 0.7932 | 0.5360 |
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+ | No log | 7.7333 | 116 | 0.5494 | 0.7932 | 0.5494 |
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+ | No log | 7.8667 | 118 | 0.5884 | 0.8142 | 0.5884 |
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+ | No log | 8.0 | 120 | 0.6313 | 0.8158 | 0.6313 |
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+ | No log | 8.1333 | 122 | 0.6069 | 0.8159 | 0.6069 |
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+ | No log | 8.2667 | 124 | 0.5732 | 0.8053 | 0.5732 |
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+ | No log | 8.4 | 126 | 0.5567 | 0.7975 | 0.5567 |
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+ | No log | 8.5333 | 128 | 0.5440 | 0.7789 | 0.5440 |
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+ | No log | 8.6667 | 130 | 0.5462 | 0.7810 | 0.5462 |
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+ | No log | 8.8 | 132 | 0.5522 | 0.7873 | 0.5522 |
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+ | No log | 8.9333 | 134 | 0.5458 | 0.7876 | 0.5458 |
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+ | No log | 9.0667 | 136 | 0.5390 | 0.7905 | 0.5390 |
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+ | No log | 9.2 | 138 | 0.5392 | 0.7901 | 0.5392 |
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+ | No log | 9.3333 | 140 | 0.5491 | 0.7943 | 0.5491 |
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+ | No log | 9.4667 | 142 | 0.5675 | 0.7937 | 0.5675 |
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+ | No log | 9.6 | 144 | 0.5753 | 0.7967 | 0.5753 |
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+ | No log | 9.7333 | 146 | 0.5745 | 0.7967 | 0.5745 |
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+ | No log | 9.8667 | 148 | 0.5743 | 0.7967 | 0.5743 |
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+ | No log | 10.0 | 150 | 0.5739 | 0.7967 | 0.5739 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions