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arabert_cross_relevance_task4_fold1

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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_task4_fold0
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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_task4_fold0
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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: 0.2736
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- - Qwk: 0.1560
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- - Mse: 0.2738
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  ## Model description
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@@ -47,91 +47,91 @@ 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 | 0.5899 | 0.0303 | 0.5899 |
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- | No log | 0.2353 | 4 | 0.2991 | 0.0083 | 0.2993 |
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- | No log | 0.3529 | 6 | 0.2856 | 0.0046 | 0.2859 |
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- | No log | 0.4706 | 8 | 0.3724 | 0.0918 | 0.3727 |
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- | No log | 0.5882 | 10 | 0.3677 | 0.1010 | 0.3680 |
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- | No log | 0.7059 | 12 | 0.2967 | 0.0745 | 0.2971 |
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- | No log | 0.8235 | 14 | 0.2878 | 0.0745 | 0.2883 |
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- | No log | 0.9412 | 16 | 0.3092 | 0.0849 | 0.3099 |
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- | No log | 1.0588 | 18 | 0.3111 | 0.0769 | 0.3118 |
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- | No log | 1.1765 | 20 | 0.3278 | 0.0860 | 0.3286 |
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- | No log | 1.2941 | 22 | 0.3356 | 0.0940 | 0.3363 |
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- | No log | 1.4118 | 24 | 0.3182 | 0.0930 | 0.3188 |
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- | No log | 1.5294 | 26 | 0.2840 | 0.0711 | 0.2844 |
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- | No log | 1.6471 | 28 | 0.2640 | 0.0745 | 0.2644 |
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- | No log | 1.7647 | 30 | 0.2617 | 0.0787 | 0.2620 |
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- | No log | 1.8824 | 32 | 0.2721 | 0.0686 | 0.2724 |
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- | No log | 2.0 | 34 | 0.2784 | 0.0709 | 0.2787 |
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- | No log | 2.1176 | 36 | 0.2850 | 0.1325 | 0.2852 |
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- | No log | 2.2353 | 38 | 0.2912 | 0.2051 | 0.2915 |
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- | No log | 2.3529 | 40 | 0.2922 | 0.1733 | 0.2925 |
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- | No log | 2.4706 | 42 | 0.2846 | 0.1093 | 0.2850 |
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- | No log | 2.5882 | 44 | 0.2920 | 0.1049 | 0.2924 |
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- | No log | 2.7059 | 46 | 0.3062 | 0.1101 | 0.3066 |
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- | No log | 2.8235 | 48 | 0.2956 | 0.1049 | 0.2961 |
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- | No log | 2.9412 | 50 | 0.2664 | 0.1066 | 0.2668 |
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- | No log | 3.0588 | 52 | 0.2583 | 0.1197 | 0.2587 |
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- | No log | 3.1765 | 54 | 0.2638 | 0.1594 | 0.2642 |
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- | No log | 3.2941 | 56 | 0.2611 | 0.1408 | 0.2615 |
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- | No log | 3.4118 | 58 | 0.2742 | 0.1087 | 0.2747 |
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- | No log | 3.5294 | 60 | 0.2867 | 0.0956 | 0.2872 |
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- | No log | 3.6471 | 62 | 0.3015 | 0.0985 | 0.3019 |
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- | No log | 3.7647 | 64 | 0.2991 | 0.1076 | 0.2995 |
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- | No log | 3.8824 | 66 | 0.2717 | 0.1219 | 0.2721 |
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- | No log | 4.0 | 68 | 0.2625 | 0.1787 | 0.2628 |
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- | No log | 4.1176 | 70 | 0.2648 | 0.2139 | 0.2651 |
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- | No log | 4.2353 | 72 | 0.2608 | 0.1889 | 0.2611 |
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- | No log | 4.3529 | 74 | 0.2596 | 0.1230 | 0.2599 |
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- | No log | 4.4706 | 76 | 0.2657 | 0.1072 | 0.2660 |
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- | No log | 4.5882 | 78 | 0.2691 | 0.1064 | 0.2695 |
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- | No log | 4.7059 | 80 | 0.2573 | 0.0987 | 0.2577 |
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- | No log | 4.8235 | 82 | 0.2467 | 0.1026 | 0.2470 |
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- | No log | 4.9412 | 84 | 0.2538 | 0.1374 | 0.2541 |
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- | No log | 5.0588 | 86 | 0.2632 | 0.1541 | 0.2635 |
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- | No log | 5.1765 | 88 | 0.2699 | 0.1482 | 0.2702 |
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- | No log | 5.2941 | 90 | 0.2684 | 0.1464 | 0.2687 |
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- | No log | 5.4118 | 92 | 0.2643 | 0.1446 | 0.2646 |
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- | No log | 5.5294 | 94 | 0.2663 | 0.1381 | 0.2665 |
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- | No log | 5.6471 | 96 | 0.2594 | 0.1117 | 0.2597 |
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- | No log | 5.7647 | 98 | 0.2596 | 0.1043 | 0.2599 |
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- | No log | 5.8824 | 100 | 0.2557 | 0.1095 | 0.2559 |
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- | No log | 6.0 | 102 | 0.2552 | 0.1192 | 0.2555 |
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- | No log | 6.1176 | 104 | 0.2623 | 0.1286 | 0.2626 |
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- | No log | 6.2353 | 106 | 0.2589 | 0.1349 | 0.2592 |
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- | No log | 6.3529 | 108 | 0.2591 | 0.1493 | 0.2593 |
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- | No log | 6.4706 | 110 | 0.2623 | 0.1697 | 0.2626 |
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- | No log | 6.5882 | 112 | 0.2713 | 0.1744 | 0.2716 |
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- | No log | 6.7059 | 114 | 0.2740 | 0.1744 | 0.2743 |
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- | No log | 6.8235 | 116 | 0.2753 | 0.1499 | 0.2756 |
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- | No log | 6.9412 | 118 | 0.2729 | 0.1471 | 0.2732 |
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- | No log | 7.0588 | 120 | 0.2685 | 0.1437 | 0.2688 |
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- | No log | 7.1765 | 122 | 0.2665 | 0.1388 | 0.2667 |
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- | No log | 7.2941 | 124 | 0.2587 | 0.1432 | 0.2589 |
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- | No log | 7.4118 | 126 | 0.2538 | 0.1376 | 0.2541 |
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- | No log | 7.5294 | 128 | 0.2554 | 0.1388 | 0.2557 |
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- | No log | 7.6471 | 130 | 0.2570 | 0.1592 | 0.2572 |
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- | No log | 7.7647 | 132 | 0.2582 | 0.1593 | 0.2584 |
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- | No log | 7.8824 | 134 | 0.2619 | 0.1575 | 0.2621 |
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- | No log | 8.0 | 136 | 0.2676 | 0.1543 | 0.2678 |
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- | No log | 8.1176 | 138 | 0.2711 | 0.1419 | 0.2714 |
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- | No log | 8.2353 | 140 | 0.2745 | 0.1388 | 0.2747 |
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- | No log | 8.3529 | 142 | 0.2729 | 0.1388 | 0.2731 |
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- | No log | 8.4706 | 144 | 0.2716 | 0.1325 | 0.2718 |
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- | No log | 8.5882 | 146 | 0.2731 | 0.1295 | 0.2734 |
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- | No log | 8.7059 | 148 | 0.2726 | 0.1287 | 0.2729 |
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- | No log | 8.8235 | 150 | 0.2748 | 0.1306 | 0.2751 |
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- | No log | 8.9412 | 152 | 0.2760 | 0.1400 | 0.2762 |
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- | No log | 9.0588 | 154 | 0.2751 | 0.1400 | 0.2754 |
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- | No log | 9.1765 | 156 | 0.2728 | 0.1478 | 0.2731 |
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- | No log | 9.2941 | 158 | 0.2721 | 0.1478 | 0.2723 |
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- | No log | 9.4118 | 160 | 0.2716 | 0.1478 | 0.2718 |
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- | No log | 9.5294 | 162 | 0.2714 | 0.1478 | 0.2717 |
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- | No log | 9.6471 | 164 | 0.2722 | 0.1478 | 0.2725 |
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- | No log | 9.7647 | 166 | 0.2731 | 0.1560 | 0.2733 |
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- | No log | 9.8824 | 168 | 0.2734 | 0.1560 | 0.2736 |
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- | No log | 10.0 | 170 | 0.2736 | 0.1560 | 0.2738 |
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task4_fold1
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_task4_fold1
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: 0.1626
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+ - Qwk: 0.0272
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+ - Mse: 0.1626
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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 | 0.1176 | 2 | 0.6734 | 0.0010 | 0.6734 |
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+ | No log | 0.2353 | 4 | 0.1546 | 0.0127 | 0.1546 |
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+ | No log | 0.3529 | 6 | 0.1344 | 0.0033 | 0.1344 |
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+ | No log | 0.4706 | 8 | 0.2292 | 0.0185 | 0.2292 |
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+ | No log | 0.5882 | 10 | 0.2260 | 0.0185 | 0.2260 |
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+ | No log | 0.7059 | 12 | 0.1786 | 0.0273 | 0.1786 |
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+ | No log | 0.8235 | 14 | 0.1782 | 0.0359 | 0.1782 |
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+ | No log | 0.9412 | 16 | 0.1951 | 0.0339 | 0.1951 |
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+ | No log | 1.0588 | 18 | 0.2431 | 0.0300 | 0.2431 |
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+ | No log | 1.1765 | 20 | 0.2607 | 0.0228 | 0.2607 |
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+ | No log | 1.2941 | 22 | 0.1938 | 0.0332 | 0.1938 |
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+ | No log | 1.4118 | 24 | 0.1436 | 0.0511 | 0.1436 |
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+ | No log | 1.5294 | 26 | 0.1294 | 0.0733 | 0.1294 |
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+ | No log | 1.6471 | 28 | 0.1285 | 0.0553 | 0.1285 |
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+ | No log | 1.7647 | 30 | 0.1515 | 0.0273 | 0.1515 |
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+ | No log | 1.8824 | 32 | 0.1764 | 0.0273 | 0.1764 |
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+ | No log | 2.0 | 34 | 0.1880 | 0.0273 | 0.1880 |
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+ | No log | 2.1176 | 36 | 0.1700 | 0.0254 | 0.1700 |
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+ | No log | 2.2353 | 38 | 0.1359 | 0.0273 | 0.1359 |
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+ | No log | 2.3529 | 40 | 0.1300 | 0.0307 | 0.1300 |
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+ | No log | 2.4706 | 42 | 0.1359 | 0.0304 | 0.1359 |
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+ | No log | 2.5882 | 44 | 0.1557 | 0.0319 | 0.1557 |
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+ | No log | 2.7059 | 46 | 0.1602 | 0.0335 | 0.1602 |
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+ | No log | 2.8235 | 48 | 0.1456 | 0.0423 | 0.1456 |
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+ | No log | 2.9412 | 50 | 0.1501 | 0.0339 | 0.1501 |
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+ | No log | 3.0588 | 52 | 0.1611 | 0.0339 | 0.1611 |
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+ | No log | 3.1765 | 54 | 0.1440 | 0.0355 | 0.1440 |
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+ | No log | 3.2941 | 56 | 0.1348 | 0.0441 | 0.1348 |
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+ | No log | 3.4118 | 58 | 0.1332 | 0.0475 | 0.1332 |
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+ | No log | 3.5294 | 60 | 0.1443 | 0.0458 | 0.1443 |
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+ | No log | 3.6471 | 62 | 0.1652 | 0.0389 | 0.1652 |
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+ | No log | 3.7647 | 64 | 0.1647 | 0.0458 | 0.1647 |
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+ | No log | 3.8824 | 66 | 0.1513 | 0.0529 | 0.1513 |
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+ | No log | 4.0 | 68 | 0.1475 | 0.0603 | 0.1475 |
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+ | No log | 4.1176 | 70 | 0.1571 | 0.0510 | 0.1571 |
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+ | No log | 4.2353 | 72 | 0.1593 | 0.0529 | 0.1593 |
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+ | No log | 4.3529 | 74 | 0.1445 | 0.0510 | 0.1445 |
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+ | No log | 4.4706 | 76 | 0.1337 | 0.0675 | 0.1337 |
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+ | No log | 4.5882 | 78 | 0.1314 | 0.0614 | 0.1314 |
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+ | No log | 4.7059 | 80 | 0.1364 | 0.0516 | 0.1364 |
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+ | No log | 4.8235 | 82 | 0.1610 | 0.0406 | 0.1610 |
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+ | No log | 4.9412 | 84 | 0.1875 | 0.0355 | 0.1875 |
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+ | No log | 5.0588 | 86 | 0.1836 | 0.0335 | 0.1836 |
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+ | No log | 5.1765 | 88 | 0.1626 | 0.0389 | 0.1626 |
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+ | No log | 5.2941 | 90 | 0.1440 | 0.0493 | 0.1440 |
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+ | No log | 5.4118 | 92 | 0.1353 | 0.0939 | 0.1353 |
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+ | No log | 5.5294 | 94 | 0.1367 | 0.1075 | 0.1367 |
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+ | No log | 5.6471 | 96 | 0.1399 | 0.0853 | 0.1399 |
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+ | No log | 5.7647 | 98 | 0.1521 | 0.0470 | 0.1521 |
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+ | No log | 5.8824 | 100 | 0.1665 | 0.0352 | 0.1665 |
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+ | No log | 6.0 | 102 | 0.1631 | 0.0372 | 0.1631 |
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+ | No log | 6.1176 | 104 | 0.1511 | 0.0372 | 0.1511 |
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+ | No log | 6.2353 | 106 | 0.1430 | 0.0463 | 0.1430 |
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+ | No log | 6.3529 | 108 | 0.1385 | 0.0708 | 0.1385 |
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+ | No log | 6.4706 | 110 | 0.1378 | 0.1029 | 0.1378 |
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+ | No log | 6.5882 | 112 | 0.1410 | 0.0775 | 0.1410 |
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+ | No log | 6.7059 | 114 | 0.1514 | 0.0515 | 0.1514 |
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+ | No log | 6.8235 | 116 | 0.1742 | 0.0351 | 0.1742 |
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+ | No log | 6.9412 | 118 | 0.1831 | 0.0317 | 0.1831 |
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+ | No log | 7.0588 | 120 | 0.1684 | 0.0347 | 0.1684 |
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+ | No log | 7.1765 | 122 | 0.1531 | 0.0652 | 0.1531 |
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+ | No log | 7.2941 | 124 | 0.1443 | 0.0679 | 0.1443 |
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+ | No log | 7.4118 | 126 | 0.1417 | 0.0749 | 0.1417 |
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+ | No log | 7.5294 | 128 | 0.1432 | 0.0618 | 0.1432 |
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+ | No log | 7.6471 | 130 | 0.1495 | 0.0614 | 0.1495 |
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+ | No log | 7.7647 | 132 | 0.1521 | 0.0495 | 0.1521 |
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+ | No log | 7.8824 | 134 | 0.1575 | 0.0420 | 0.1575 |
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+ | No log | 8.0 | 136 | 0.1621 | 0.0415 | 0.1621 |
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+ | No log | 8.1176 | 138 | 0.1649 | 0.0360 | 0.1649 |
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+ | No log | 8.2353 | 140 | 0.1614 | 0.0397 | 0.1614 |
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+ | No log | 8.3529 | 142 | 0.1589 | 0.0415 | 0.1589 |
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+ | No log | 8.4706 | 144 | 0.1604 | 0.0397 | 0.1604 |
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+ | No log | 8.5882 | 146 | 0.1587 | 0.0420 | 0.1587 |
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+ | No log | 8.7059 | 148 | 0.1531 | 0.0457 | 0.1531 |
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+ | No log | 8.8235 | 150 | 0.1511 | 0.0515 | 0.1511 |
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+ | No log | 8.9412 | 152 | 0.1466 | 0.0614 | 0.1466 |
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+ | No log | 9.0588 | 154 | 0.1458 | 0.0514 | 0.1458 |
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+ | No log | 9.1765 | 156 | 0.1471 | 0.0514 | 0.1471 |
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+ | No log | 9.2941 | 158 | 0.1511 | 0.0495 | 0.1511 |
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+ | No log | 9.4118 | 160 | 0.1570 | 0.0438 | 0.1570 |
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+ | No log | 9.5294 | 162 | 0.1612 | 0.0290 | 0.1612 |
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+ | No log | 9.6471 | 164 | 0.1642 | 0.0272 | 0.1642 |
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+ | No log | 9.7647 | 166 | 0.1639 | 0.0272 | 0.1639 |
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+ | No log | 9.8824 | 168 | 0.1630 | 0.0272 | 0.1630 |
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+ | No log | 10.0 | 170 | 0.1626 | 0.0272 | 0.1626 |
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  ### Framework versions