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arabert_cross_relevance_task7_fold0

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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_relevance_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_relevance_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: 0.4430
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- - Qwk: 0.1465
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- - Mse: 0.4429
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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 | 0.7830 | 0.0204 | 0.7810 |
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- | No log | 0.2353 | 4 | 0.3944 | 0.0715 | 0.3940 |
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- | No log | 0.3529 | 6 | 0.3437 | 0.0480 | 0.3436 |
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- | No log | 0.4706 | 8 | 0.3309 | 0.1105 | 0.3305 |
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- | No log | 0.5882 | 10 | 0.2835 | 0.1105 | 0.2836 |
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- | No log | 0.7059 | 12 | 0.2697 | 0.1105 | 0.2702 |
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- | No log | 0.8235 | 14 | 0.2695 | 0.1185 | 0.2700 |
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- | No log | 0.9412 | 16 | 0.2715 | 0.1326 | 0.2721 |
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- | No log | 1.0588 | 18 | 0.2745 | 0.2102 | 0.2750 |
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- | No log | 1.1765 | 20 | 0.2896 | 0.2067 | 0.2899 |
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- | No log | 1.2941 | 22 | 0.2766 | 0.2206 | 0.2770 |
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- | No log | 1.4118 | 24 | 0.2712 | 0.2420 | 0.2717 |
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- | No log | 1.5294 | 26 | 0.2809 | 0.2235 | 0.2814 |
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- | No log | 1.6471 | 28 | 0.2904 | 0.2076 | 0.2908 |
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- | No log | 1.7647 | 30 | 0.2687 | 0.2352 | 0.2692 |
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- | No log | 1.8824 | 32 | 0.2581 | 0.2477 | 0.2588 |
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- | No log | 2.0 | 34 | 0.2565 | 0.2472 | 0.2572 |
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- | No log | 2.1176 | 36 | 0.2641 | 0.2099 | 0.2646 |
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- | No log | 2.2353 | 38 | 0.3196 | 0.2033 | 0.3198 |
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- | No log | 2.3529 | 40 | 0.3095 | 0.2076 | 0.3097 |
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- | No log | 2.4706 | 42 | 0.2662 | 0.2084 | 0.2667 |
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- | No log | 2.5882 | 44 | 0.2644 | 0.2790 | 0.2651 |
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- | No log | 2.7059 | 46 | 0.2676 | 0.2311 | 0.2682 |
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- | No log | 2.8235 | 48 | 0.2943 | 0.2347 | 0.2946 |
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- | No log | 2.9412 | 50 | 0.3231 | 0.2150 | 0.3232 |
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- | No log | 3.0588 | 52 | 0.3309 | 0.2064 | 0.3309 |
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- | No log | 3.1765 | 54 | 0.3053 | 0.2252 | 0.3056 |
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- | No log | 3.2941 | 56 | 0.2808 | 0.2266 | 0.2812 |
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- | No log | 3.4118 | 58 | 0.2831 | 0.2170 | 0.2836 |
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- | No log | 3.5294 | 60 | 0.2875 | 0.2211 | 0.2881 |
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- | No log | 3.6471 | 62 | 0.3017 | 0.2140 | 0.3022 |
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- | No log | 3.7647 | 64 | 0.3078 | 0.2125 | 0.3084 |
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- | No log | 3.8824 | 66 | 0.3215 | 0.2117 | 0.3220 |
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- | No log | 4.0 | 68 | 0.3285 | 0.2052 | 0.3288 |
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- | No log | 4.1176 | 70 | 0.3679 | 0.1824 | 0.3679 |
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- | No log | 4.2353 | 72 | 0.3668 | 0.1824 | 0.3668 |
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- | No log | 4.3529 | 74 | 0.3216 | 0.2135 | 0.3219 |
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- | No log | 4.4706 | 76 | 0.2935 | 0.2301 | 0.2940 |
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- | No log | 4.5882 | 78 | 0.2944 | 0.2406 | 0.2949 |
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- | No log | 4.7059 | 80 | 0.3279 | 0.2200 | 0.3282 |
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- | No log | 4.8235 | 82 | 0.3629 | 0.1977 | 0.3631 |
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- | No log | 4.9412 | 84 | 0.3823 | 0.1898 | 0.3823 |
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- | No log | 5.0588 | 86 | 0.3659 | 0.1977 | 0.3659 |
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- | No log | 5.1765 | 88 | 0.3351 | 0.2019 | 0.3353 |
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- | No log | 5.2941 | 90 | 0.3442 | 0.2019 | 0.3443 |
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- | No log | 5.4118 | 92 | 0.3693 | 0.1977 | 0.3694 |
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- | No log | 5.5294 | 94 | 0.3861 | 0.1937 | 0.3861 |
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- | No log | 5.6471 | 96 | 0.3622 | 0.1977 | 0.3624 |
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- | No log | 5.7647 | 98 | 0.3369 | 0.2023 | 0.3373 |
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- | No log | 5.8824 | 100 | 0.3520 | 0.1939 | 0.3524 |
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- | No log | 6.0 | 102 | 0.3764 | 0.1898 | 0.3766 |
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- | No log | 6.1176 | 104 | 0.4008 | 0.1975 | 0.4009 |
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- | No log | 6.2353 | 106 | 0.4228 | 0.1899 | 0.4229 |
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- | No log | 6.3529 | 108 | 0.4377 | 0.1725 | 0.4376 |
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- | No log | 6.4706 | 110 | 0.4032 | 0.1824 | 0.4033 |
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- | No log | 6.5882 | 112 | 0.3828 | 0.1937 | 0.3829 |
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- | No log | 6.7059 | 114 | 0.4023 | 0.1975 | 0.4023 |
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- | No log | 6.8235 | 116 | 0.4098 | 0.1650 | 0.4097 |
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- | No log | 6.9412 | 118 | 0.4555 | 0.1465 | 0.4553 |
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- | No log | 7.0588 | 120 | 0.5148 | 0.1339 | 0.5144 |
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- | No log | 7.1765 | 122 | 0.5125 | 0.1339 | 0.5122 |
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- | No log | 7.2941 | 124 | 0.4645 | 0.1465 | 0.4643 |
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- | No log | 7.4118 | 126 | 0.3966 | 0.1751 | 0.3967 |
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- | No log | 7.5294 | 128 | 0.3450 | 0.1979 | 0.3452 |
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- | No log | 7.6471 | 130 | 0.3262 | 0.2210 | 0.3265 |
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- | No log | 7.7647 | 132 | 0.3261 | 0.2210 | 0.3265 |
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- | No log | 7.8824 | 134 | 0.3438 | 0.1979 | 0.3441 |
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- | No log | 8.0 | 136 | 0.3772 | 0.2015 | 0.3774 |
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- | No log | 8.1176 | 138 | 0.4155 | 0.1719 | 0.4155 |
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- | No log | 8.2353 | 140 | 0.4512 | 0.1528 | 0.4511 |
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- | No log | 8.3529 | 142 | 0.4592 | 0.1404 | 0.4590 |
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- | No log | 8.4706 | 144 | 0.4422 | 0.1465 | 0.4421 |
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- | No log | 8.5882 | 146 | 0.4170 | 0.1620 | 0.4170 |
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- | No log | 8.7059 | 148 | 0.4105 | 0.1757 | 0.4105 |
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- | No log | 8.8235 | 150 | 0.4205 | 0.1592 | 0.4204 |
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- | No log | 8.9412 | 152 | 0.4328 | 0.1465 | 0.4327 |
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- | No log | 9.0588 | 154 | 0.4368 | 0.1465 | 0.4367 |
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- | No log | 9.1765 | 156 | 0.4351 | 0.1465 | 0.4350 |
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- | No log | 9.2941 | 158 | 0.4352 | 0.1465 | 0.4352 |
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- | No log | 9.4118 | 160 | 0.4333 | 0.1465 | 0.4332 |
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- | No log | 9.5294 | 162 | 0.4373 | 0.1465 | 0.4372 |
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- | No log | 9.6471 | 164 | 0.4392 | 0.1465 | 0.4391 |
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- | No log | 9.7647 | 166 | 0.4394 | 0.1465 | 0.4393 |
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- | No log | 9.8824 | 168 | 0.4416 | 0.1465 | 0.4415 |
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- | No log | 10.0 | 170 | 0.4430 | 0.1465 | 0.4429 |
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_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_relevance_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.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2739
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+ - Qwk: 0.1498
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+ - Mse: 0.2741
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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 | 0.6915 | 0.0152 | 0.6916 |
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+ | No log | 0.2667 | 4 | 0.3007 | 0.0046 | 0.3008 |
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+ | No log | 0.4 | 6 | 0.2606 | 0.0103 | 0.2607 |
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+ | No log | 0.5333 | 8 | 0.2472 | -0.0037 | 0.2473 |
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+ | No log | 0.6667 | 10 | 0.2753 | 0.0398 | 0.2754 |
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+ | No log | 0.8 | 12 | 0.3087 | 0.0531 | 0.3087 |
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+ | No log | 0.9333 | 14 | 0.2871 | 0.0584 | 0.2872 |
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+ | No log | 1.0667 | 16 | 0.2862 | 0.0547 | 0.2864 |
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+ | No log | 1.2 | 18 | 0.2778 | 0.0673 | 0.2780 |
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+ | No log | 1.3333 | 20 | 0.2869 | 0.1208 | 0.2871 |
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+ | No log | 1.4667 | 22 | 0.2743 | 0.0873 | 0.2746 |
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+ | No log | 1.6 | 24 | 0.2612 | 0.0650 | 0.2614 |
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+ | No log | 1.7333 | 26 | 0.2604 | 0.0715 | 0.2606 |
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+ | No log | 1.8667 | 28 | 0.2749 | 0.0788 | 0.2752 |
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+ | No log | 2.0 | 30 | 0.3010 | 0.1611 | 0.3013 |
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+ | No log | 2.1333 | 32 | 0.2981 | 0.1189 | 0.2984 |
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+ | No log | 2.2667 | 34 | 0.2813 | 0.1170 | 0.2815 |
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+ | No log | 2.4 | 36 | 0.2636 | 0.0868 | 0.2638 |
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+ | No log | 2.5333 | 38 | 0.2577 | 0.0986 | 0.2579 |
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+ | No log | 2.6667 | 40 | 0.2578 | 0.0676 | 0.2580 |
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+ | No log | 2.8 | 42 | 0.2611 | 0.0743 | 0.2612 |
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+ | No log | 2.9333 | 44 | 0.2605 | 0.0949 | 0.2607 |
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+ | No log | 3.0667 | 46 | 0.2576 | 0.0837 | 0.2578 |
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+ | No log | 3.2 | 48 | 0.2526 | 0.0883 | 0.2528 |
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+ | No log | 3.3333 | 50 | 0.2493 | 0.0796 | 0.2494 |
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+ | No log | 3.4667 | 52 | 0.2494 | 0.0762 | 0.2495 |
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+ | No log | 3.6 | 54 | 0.2509 | 0.0762 | 0.2511 |
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+ | No log | 3.7333 | 56 | 0.2599 | 0.1102 | 0.2601 |
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+ | No log | 3.8667 | 58 | 0.2617 | 0.1201 | 0.2619 |
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+ | No log | 4.0 | 60 | 0.2569 | 0.1201 | 0.2571 |
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+ | No log | 4.1333 | 62 | 0.2518 | 0.1245 | 0.2520 |
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+ | No log | 4.2667 | 64 | 0.2475 | 0.1331 | 0.2476 |
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+ | No log | 4.4 | 66 | 0.2458 | 0.1627 | 0.2459 |
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+ | No log | 4.5333 | 68 | 0.2466 | 0.1664 | 0.2467 |
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+ | No log | 4.6667 | 70 | 0.2489 | 0.1701 | 0.2490 |
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+ | No log | 4.8 | 72 | 0.2533 | 0.1802 | 0.2534 |
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+ | No log | 4.9333 | 74 | 0.2587 | 0.1795 | 0.2588 |
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+ | No log | 5.0667 | 76 | 0.2679 | 0.1591 | 0.2681 |
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+ | No log | 5.2 | 78 | 0.2741 | 0.1432 | 0.2743 |
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+ | No log | 5.3333 | 80 | 0.2711 | 0.1317 | 0.2714 |
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+ | No log | 5.4667 | 82 | 0.2652 | 0.1368 | 0.2654 |
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+ | No log | 5.6 | 84 | 0.2681 | 0.1474 | 0.2683 |
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+ | No log | 5.7333 | 86 | 0.2684 | 0.1626 | 0.2686 |
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+ | No log | 5.8667 | 88 | 0.2645 | 0.1797 | 0.2647 |
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+ | No log | 6.0 | 90 | 0.2589 | 0.1859 | 0.2590 |
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+ | No log | 6.1333 | 92 | 0.2593 | 0.1154 | 0.2594 |
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+ | No log | 6.2667 | 94 | 0.2625 | 0.1365 | 0.2626 |
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+ | No log | 6.4 | 96 | 0.2688 | 0.1779 | 0.2690 |
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+ | No log | 6.5333 | 98 | 0.2740 | 0.2609 | 0.2742 |
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+ | No log | 6.6667 | 100 | 0.2759 | 0.2576 | 0.2760 |
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+ | No log | 6.8 | 102 | 0.2726 | 0.2039 | 0.2728 |
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+ | No log | 6.9333 | 104 | 0.2690 | 0.1750 | 0.2692 |
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+ | No log | 7.0667 | 106 | 0.2676 | 0.1430 | 0.2678 |
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+ | No log | 7.2 | 108 | 0.2660 | 0.1277 | 0.2662 |
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+ | No log | 7.3333 | 110 | 0.2660 | 0.1610 | 0.2661 |
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+ | No log | 7.4667 | 112 | 0.2678 | 0.1840 | 0.2679 |
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+ | No log | 7.6 | 114 | 0.2687 | 0.1801 | 0.2688 |
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+ | No log | 7.7333 | 116 | 0.2685 | 0.1647 | 0.2686 |
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+ | No log | 7.8667 | 118 | 0.2673 | 0.1609 | 0.2675 |
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+ | No log | 8.0 | 120 | 0.2674 | 0.1352 | 0.2676 |
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+ | No log | 8.1333 | 122 | 0.2685 | 0.1172 | 0.2687 |
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+ | No log | 8.2667 | 124 | 0.2696 | 0.1172 | 0.2697 |
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+ | No log | 8.4 | 126 | 0.2705 | 0.1304 | 0.2707 |
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+ | No log | 8.5333 | 128 | 0.2717 | 0.1481 | 0.2719 |
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+ | No log | 8.6667 | 130 | 0.2734 | 0.1645 | 0.2736 |
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+ | No log | 8.8 | 132 | 0.2747 | 0.1828 | 0.2748 |
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+ | No log | 8.9333 | 134 | 0.2744 | 0.1903 | 0.2746 |
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+ | No log | 9.0667 | 136 | 0.2741 | 0.1738 | 0.2742 |
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+ | No log | 9.2 | 138 | 0.2734 | 0.1664 | 0.2736 |
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+ | No log | 9.3333 | 140 | 0.2736 | 0.1700 | 0.2738 |
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+ | No log | 9.4667 | 142 | 0.2738 | 0.1700 | 0.2739 |
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+ | No log | 9.6 | 144 | 0.2739 | 0.1572 | 0.2741 |
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+ | No log | 9.7333 | 146 | 0.2738 | 0.1498 | 0.2740 |
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+ | No log | 9.8667 | 148 | 0.2739 | 0.1498 | 0.2741 |
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+ | No log | 10.0 | 150 | 0.2739 | 0.1498 | 0.2741 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions