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arabert_cross_vocabulary_task1_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_task7_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_task7_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: 0.4397
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- - Qwk: 0.1488
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- - Mse: 0.4393
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  ## Model description
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@@ -45,88 +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 | 0.125 | 2 | 0.7246 | 0.0092 | 0.7226 |
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- | No log | 0.25 | 4 | 0.3923 | 0.1169 | 0.3915 |
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- | No log | 0.375 | 6 | 0.3543 | 0.0420 | 0.3537 |
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- | No log | 0.5 | 8 | 0.3794 | 0.1151 | 0.3788 |
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- | No log | 0.625 | 10 | 0.3085 | 0.0822 | 0.3084 |
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- | No log | 0.75 | 12 | 0.2791 | 0.0429 | 0.2796 |
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- | No log | 0.875 | 14 | 0.2793 | 0.0732 | 0.2799 |
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- | No log | 1.0 | 16 | 0.2798 | 0.0822 | 0.2804 |
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- | No log | 1.125 | 18 | 0.2748 | 0.1450 | 0.2754 |
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- | No log | 1.25 | 20 | 0.2618 | 0.1769 | 0.2623 |
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- | No log | 1.375 | 22 | 0.2610 | 0.2119 | 0.2614 |
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- | No log | 1.5 | 24 | 0.2714 | 0.2099 | 0.2716 |
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- | No log | 1.625 | 26 | 0.2877 | 0.2282 | 0.2877 |
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- | No log | 1.75 | 28 | 0.3085 | 0.2170 | 0.3085 |
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- | No log | 1.875 | 30 | 0.2818 | 0.2521 | 0.2819 |
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- | No log | 2.0 | 32 | 0.2704 | 0.2285 | 0.2706 |
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- | No log | 2.125 | 34 | 0.2630 | 0.2177 | 0.2635 |
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- | No log | 2.25 | 36 | 0.2577 | 0.1930 | 0.2582 |
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- | No log | 2.375 | 38 | 0.2575 | 0.2186 | 0.2579 |
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- | No log | 2.5 | 40 | 0.2613 | 0.2282 | 0.2617 |
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- | No log | 2.625 | 42 | 0.2766 | 0.2044 | 0.2769 |
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- | No log | 2.75 | 44 | 0.2809 | 0.2091 | 0.2811 |
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- | No log | 2.875 | 46 | 0.2689 | 0.2194 | 0.2691 |
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- | No log | 3.0 | 48 | 0.2629 | 0.2198 | 0.2632 |
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- | No log | 3.125 | 50 | 0.2671 | 0.2133 | 0.2672 |
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- | No log | 3.25 | 52 | 0.2896 | 0.2170 | 0.2895 |
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- | No log | 3.375 | 54 | 0.3099 | 0.2118 | 0.3097 |
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- | No log | 3.5 | 56 | 0.2867 | 0.2181 | 0.2867 |
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- | No log | 3.625 | 58 | 0.2681 | 0.2108 | 0.2683 |
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- | No log | 3.75 | 60 | 0.2670 | 0.2042 | 0.2674 |
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- | No log | 3.875 | 62 | 0.2777 | 0.2220 | 0.2780 |
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- | No log | 4.0 | 64 | 0.2823 | 0.2220 | 0.2826 |
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- | No log | 4.125 | 66 | 0.2925 | 0.2150 | 0.2927 |
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- | No log | 4.25 | 68 | 0.3165 | 0.2285 | 0.3164 |
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- | No log | 4.375 | 70 | 0.3340 | 0.2156 | 0.3337 |
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- | No log | 4.5 | 72 | 0.3690 | 0.1876 | 0.3685 |
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- | No log | 4.625 | 74 | 0.3812 | 0.1800 | 0.3806 |
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- | No log | 4.75 | 76 | 0.3599 | 0.1954 | 0.3594 |
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- | No log | 4.875 | 78 | 0.3297 | 0.2097 | 0.3294 |
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- | No log | 5.0 | 80 | 0.3082 | 0.2063 | 0.3081 |
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- | No log | 5.125 | 82 | 0.2990 | 0.2193 | 0.2991 |
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- | No log | 5.25 | 84 | 0.3004 | 0.2193 | 0.3005 |
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- | No log | 5.375 | 86 | 0.3010 | 0.2140 | 0.3011 |
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- | No log | 5.5 | 88 | 0.3297 | 0.1814 | 0.3298 |
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- | No log | 5.625 | 90 | 0.3943 | 0.1785 | 0.3943 |
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- | No log | 5.75 | 92 | 0.4229 | 0.1592 | 0.4228 |
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- | No log | 5.875 | 94 | 0.3892 | 0.1719 | 0.3892 |
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- | No log | 6.0 | 96 | 0.3418 | 0.1836 | 0.3418 |
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- | No log | 6.125 | 98 | 0.3361 | 0.1932 | 0.3360 |
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- | No log | 6.25 | 100 | 0.3641 | 0.1930 | 0.3638 |
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- | No log | 6.375 | 102 | 0.3934 | 0.1844 | 0.3930 |
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- | No log | 6.5 | 104 | 0.3956 | 0.1915 | 0.3953 |
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- | No log | 6.625 | 106 | 0.3700 | 0.2006 | 0.3700 |
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- | No log | 6.75 | 108 | 0.3683 | 0.1800 | 0.3684 |
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- | No log | 6.875 | 110 | 0.3757 | 0.1785 | 0.3758 |
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- | No log | 7.0 | 112 | 0.4066 | 0.1688 | 0.4066 |
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- | No log | 7.125 | 114 | 0.4152 | 0.1695 | 0.4151 |
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- | No log | 7.25 | 116 | 0.3917 | 0.1790 | 0.3917 |
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- | No log | 7.375 | 118 | 0.3540 | 0.1833 | 0.3542 |
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- | No log | 7.5 | 120 | 0.3449 | 0.1998 | 0.3451 |
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- | No log | 7.625 | 122 | 0.3587 | 0.1955 | 0.3588 |
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- | No log | 7.75 | 124 | 0.3969 | 0.1807 | 0.3968 |
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- | No log | 7.875 | 126 | 0.4580 | 0.1405 | 0.4577 |
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- | No log | 8.0 | 128 | 0.5018 | 0.1433 | 0.5013 |
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- | No log | 8.125 | 130 | 0.5002 | 0.1433 | 0.4997 |
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- | No log | 8.25 | 132 | 0.4689 | 0.1442 | 0.4684 |
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- | No log | 8.375 | 134 | 0.4386 | 0.1488 | 0.4382 |
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- | No log | 8.5 | 136 | 0.4174 | 0.1550 | 0.4171 |
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- | No log | 8.625 | 138 | 0.4152 | 0.1613 | 0.4149 |
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- | No log | 8.75 | 140 | 0.4293 | 0.1550 | 0.4290 |
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- | No log | 8.875 | 142 | 0.4512 | 0.1427 | 0.4508 |
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- | No log | 9.0 | 144 | 0.4641 | 0.1405 | 0.4637 |
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- | No log | 9.125 | 146 | 0.4566 | 0.1427 | 0.4562 |
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- | No log | 9.25 | 148 | 0.4432 | 0.1427 | 0.4429 |
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- | No log | 9.375 | 150 | 0.4330 | 0.1550 | 0.4327 |
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- | No log | 9.5 | 152 | 0.4301 | 0.1613 | 0.4298 |
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- | No log | 9.625 | 154 | 0.4343 | 0.1550 | 0.4340 |
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- | No log | 9.75 | 156 | 0.4358 | 0.1550 | 0.4354 |
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- | No log | 9.875 | 158 | 0.4385 | 0.1488 | 0.4381 |
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- | No log | 10.0 | 160 | 0.4397 | 0.1488 | 0.4393 |
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_vocabulary_task1_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_vocabulary_task1_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: 0.9563
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+ - Qwk: 0.3128
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+ - Mse: 0.9563
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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 | 4.7632 | 0.0048 | 4.7632 |
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+ | No log | 0.2667 | 4 | 2.1783 | 0.0291 | 2.1783 |
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+ | No log | 0.4 | 6 | 1.1081 | 0.1198 | 1.1081 |
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+ | No log | 0.5333 | 8 | 1.2015 | 0.1712 | 1.2015 |
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+ | No log | 0.6667 | 10 | 1.9526 | 0.1246 | 1.9526 |
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+ | No log | 0.8 | 12 | 1.0676 | 0.2290 | 1.0676 |
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+ | No log | 0.9333 | 14 | 0.5840 | 0.4151 | 0.5840 |
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+ | No log | 1.0667 | 16 | 0.5753 | 0.4082 | 0.5753 |
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+ | No log | 1.2 | 18 | 0.8160 | 0.2285 | 0.8160 |
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+ | No log | 1.3333 | 20 | 1.0681 | 0.2071 | 1.0681 |
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+ | No log | 1.4667 | 22 | 0.9546 | 0.2910 | 0.9546 |
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+ | No log | 1.6 | 24 | 0.8621 | 0.3677 | 0.8621 |
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+ | No log | 1.7333 | 26 | 0.9054 | 0.3700 | 0.9054 |
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+ | No log | 1.8667 | 28 | 0.9001 | 0.3161 | 0.9001 |
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+ | No log | 2.0 | 30 | 0.7765 | 0.3323 | 0.7765 |
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+ | No log | 2.1333 | 32 | 0.8465 | 0.2482 | 0.8465 |
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+ | No log | 2.2667 | 34 | 0.7701 | 0.2998 | 0.7701 |
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+ | No log | 2.4 | 36 | 0.6622 | 0.3947 | 0.6622 |
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+ | No log | 2.5333 | 38 | 0.8242 | 0.3282 | 0.8242 |
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+ | No log | 2.6667 | 40 | 1.1963 | 0.2592 | 1.1963 |
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+ | No log | 2.8 | 42 | 1.0937 | 0.2903 | 1.0937 |
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+ | No log | 2.9333 | 44 | 0.7877 | 0.3934 | 0.7877 |
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+ | No log | 3.0667 | 46 | 0.5972 | 0.4479 | 0.5972 |
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+ | No log | 3.2 | 48 | 0.6227 | 0.4269 | 0.6227 |
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+ | No log | 3.3333 | 50 | 0.8396 | 0.3376 | 0.8396 |
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+ | No log | 3.4667 | 52 | 1.0463 | 0.2697 | 1.0463 |
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+ | No log | 3.6 | 54 | 0.8738 | 0.3001 | 0.8738 |
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+ | No log | 3.7333 | 56 | 0.6019 | 0.4289 | 0.6019 |
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+ | No log | 3.8667 | 58 | 0.5198 | 0.4722 | 0.5198 |
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+ | No log | 4.0 | 60 | 0.5541 | 0.4554 | 0.5541 |
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+ | No log | 4.1333 | 62 | 0.7597 | 0.3733 | 0.7597 |
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+ | No log | 4.2667 | 64 | 0.9356 | 0.3432 | 0.9356 |
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+ | No log | 4.4 | 66 | 0.8464 | 0.3610 | 0.8464 |
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+ | No log | 4.5333 | 68 | 0.7096 | 0.3687 | 0.7096 |
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+ | No log | 4.6667 | 70 | 0.7102 | 0.3574 | 0.7102 |
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+ | No log | 4.8 | 72 | 0.7078 | 0.3669 | 0.7078 |
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+ | No log | 4.9333 | 74 | 0.8143 | 0.3480 | 0.8143 |
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+ | No log | 5.0667 | 76 | 0.9307 | 0.3211 | 0.9307 |
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+ | No log | 5.2 | 78 | 0.9263 | 0.3242 | 0.9263 |
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+ | No log | 5.3333 | 80 | 0.7661 | 0.3610 | 0.7661 |
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+ | No log | 5.4667 | 82 | 0.6978 | 0.3853 | 0.6978 |
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+ | No log | 5.6 | 84 | 0.8151 | 0.3739 | 0.8151 |
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+ | No log | 5.7333 | 86 | 0.8609 | 0.3869 | 0.8609 |
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+ | No log | 5.8667 | 88 | 0.7966 | 0.3804 | 0.7966 |
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+ | No log | 6.0 | 90 | 0.7527 | 0.3801 | 0.7527 |
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+ | No log | 6.1333 | 92 | 0.7607 | 0.3861 | 0.7607 |
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+ | No log | 6.2667 | 94 | 0.8652 | 0.3306 | 0.8652 |
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+ | No log | 6.4 | 96 | 0.9460 | 0.3135 | 0.9460 |
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+ | No log | 6.5333 | 98 | 1.0831 | 0.2779 | 1.0831 |
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+ | No log | 6.6667 | 100 | 1.0697 | 0.2892 | 1.0697 |
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+ | No log | 6.8 | 102 | 0.9442 | 0.3343 | 0.9442 |
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+ | No log | 6.9333 | 104 | 1.0589 | 0.2994 | 1.0589 |
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+ | No log | 7.0667 | 106 | 1.1776 | 0.2674 | 1.1776 |
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+ | No log | 7.2 | 108 | 1.1644 | 0.2696 | 1.1644 |
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+ | No log | 7.3333 | 110 | 0.9516 | 0.3314 | 0.9516 |
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+ | No log | 7.4667 | 112 | 0.8591 | 0.3636 | 0.8591 |
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+ | No log | 7.6 | 114 | 0.9364 | 0.3335 | 0.9364 |
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+ | No log | 7.7333 | 116 | 0.9971 | 0.3111 | 0.9971 |
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+ | No log | 7.8667 | 118 | 0.9728 | 0.3155 | 0.9728 |
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+ | No log | 8.0 | 120 | 0.8721 | 0.3499 | 0.8721 |
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+ | No log | 8.1333 | 122 | 0.8160 | 0.3628 | 0.8160 |
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+ | No log | 8.2667 | 124 | 0.8194 | 0.3688 | 0.8194 |
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+ | No log | 8.4 | 126 | 0.8317 | 0.3748 | 0.8317 |
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+ | No log | 8.5333 | 128 | 0.8909 | 0.3437 | 0.8909 |
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+ | No log | 8.6667 | 130 | 0.9882 | 0.3225 | 0.9882 |
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+ | No log | 8.8 | 132 | 1.0839 | 0.2850 | 1.0839 |
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+ | No log | 8.9333 | 134 | 1.1055 | 0.2859 | 1.1055 |
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+ | No log | 9.0667 | 136 | 1.1389 | 0.2859 | 1.1389 |
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+ | No log | 9.2 | 138 | 1.1417 | 0.2795 | 1.1417 |
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+ | No log | 9.3333 | 140 | 1.0801 | 0.2923 | 1.0801 |
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+ | No log | 9.4667 | 142 | 1.0176 | 0.3061 | 1.0176 |
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+ | No log | 9.6 | 144 | 0.9751 | 0.3091 | 0.9751 |
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+ | No log | 9.7333 | 146 | 0.9550 | 0.3128 | 0.9550 |
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+ | No log | 9.8667 | 148 | 0.9569 | 0.3128 | 0.9569 |
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+ | No log | 10.0 | 150 | 0.9563 | 0.3128 | 0.9563 |
 
 
 
 
 
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  ### Framework versions