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arabert_cross_vocabulary_task1_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_vocabulary_task1_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_vocabulary_task1_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: 0.9563
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- - Qwk: 0.3128
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- - Mse: 0.9563
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  ## Model description
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@@ -45,83 +45,88 @@ 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 | 0.1333 | 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
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_vocabulary_task1_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_vocabulary_task1_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: 0.8237
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+ - Qwk: 0.0005
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+ - Mse: 0.8231
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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 | 0.125 | 2 | 6.3728 | -0.0031 | 6.3683 |
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+ | No log | 0.25 | 4 | 2.4100 | -0.0135 | 2.4074 |
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+ | No log | 0.375 | 6 | 0.8300 | 0.0029 | 0.8281 |
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+ | No log | 0.5 | 8 | 0.5694 | 0.0422 | 0.5684 |
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+ | No log | 0.625 | 10 | 0.5771 | 0.0819 | 0.5758 |
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+ | No log | 0.75 | 12 | 0.5787 | 0.0393 | 0.5780 |
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+ | No log | 0.875 | 14 | 0.5560 | 0.0075 | 0.5555 |
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+ | No log | 1.0 | 16 | 0.5627 | -0.0083 | 0.5623 |
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+ | No log | 1.125 | 18 | 0.6677 | 0.0 | 0.6674 |
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+ | No log | 1.25 | 20 | 0.7346 | 0.0 | 0.7343 |
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+ | No log | 1.375 | 22 | 0.6544 | 0.0 | 0.6540 |
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+ | No log | 1.5 | 24 | 0.7414 | 0.0 | 0.7411 |
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+ | No log | 1.625 | 26 | 0.7091 | 0.0 | 0.7088 |
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+ | No log | 1.75 | 28 | 0.5841 | 0.0 | 0.5836 |
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+ | No log | 1.875 | 30 | 0.5323 | 0.0422 | 0.5314 |
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+ | No log | 2.0 | 32 | 0.5359 | 0.0488 | 0.5349 |
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+ | No log | 2.125 | 34 | 0.5392 | 0.0 | 0.5385 |
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+ | No log | 2.25 | 36 | 0.6346 | 0.0 | 0.6342 |
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+ | No log | 2.375 | 38 | 0.7730 | 0.0 | 0.7727 |
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+ | No log | 2.5 | 40 | 0.7599 | 0.0 | 0.7595 |
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+ | No log | 2.625 | 42 | 0.6719 | 0.0 | 0.6714 |
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+ | No log | 2.75 | 44 | 0.7595 | 0.0 | 0.7591 |
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+ | No log | 2.875 | 46 | 0.8678 | 0.0202 | 0.8675 |
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+ | No log | 3.0 | 48 | 0.8677 | 0.0151 | 0.8674 |
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+ | No log | 3.125 | 50 | 0.9100 | 0.0193 | 0.9096 |
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+ | No log | 3.25 | 52 | 1.2346 | 0.0466 | 1.2345 |
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+ | No log | 3.375 | 54 | 1.3974 | 0.1074 | 1.3974 |
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+ | No log | 3.5 | 56 | 1.1473 | 0.0657 | 1.1472 |
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+ | No log | 3.625 | 58 | 0.7783 | -0.0050 | 0.7779 |
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+ | No log | 3.75 | 60 | 0.6393 | 0.0 | 0.6387 |
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+ | No log | 3.875 | 62 | 0.6653 | 0.0 | 0.6648 |
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+ | No log | 4.0 | 64 | 0.6339 | 0.0 | 0.6334 |
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+ | No log | 4.125 | 66 | 0.6583 | 0.0 | 0.6578 |
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+ | No log | 4.25 | 68 | 0.7357 | 0.0 | 0.7353 |
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+ | No log | 4.375 | 70 | 0.9251 | -0.0269 | 0.9248 |
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+ | No log | 4.5 | 72 | 1.0004 | 0.0702 | 1.0001 |
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+ | No log | 4.625 | 74 | 1.0757 | 0.0049 | 1.0754 |
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+ | No log | 4.75 | 76 | 1.0881 | 0.0049 | 1.0878 |
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+ | No log | 4.875 | 78 | 0.8102 | -0.0195 | 0.8097 |
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+ | No log | 5.0 | 80 | 0.6847 | 0.0 | 0.6840 |
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+ | No log | 5.125 | 82 | 0.7337 | -0.0050 | 0.7331 |
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+ | No log | 5.25 | 84 | 0.7008 | 0.0 | 0.7001 |
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+ | No log | 5.375 | 86 | 0.7016 | -0.0050 | 0.7009 |
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+ | No log | 5.5 | 88 | 0.7481 | -0.0195 | 0.7475 |
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+ | No log | 5.625 | 90 | 0.7384 | 0.0051 | 0.7377 |
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+ | No log | 5.75 | 92 | 0.7519 | 0.0003 | 0.7511 |
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+ | No log | 5.875 | 94 | 0.9434 | 0.0457 | 0.9429 |
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+ | No log | 6.0 | 96 | 1.1388 | 0.1084 | 1.1387 |
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+ | No log | 6.125 | 98 | 1.1119 | 0.1087 | 1.1118 |
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+ | No log | 6.25 | 100 | 0.9851 | 0.0611 | 0.9849 |
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+ | No log | 6.375 | 102 | 0.8431 | 0.0327 | 0.8426 |
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+ | No log | 6.5 | 104 | 0.7529 | -0.0242 | 0.7523 |
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+ | No log | 6.625 | 106 | 0.7658 | -0.0242 | 0.7653 |
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+ | No log | 6.75 | 108 | 0.8717 | 0.0376 | 0.8713 |
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+ | No log | 6.875 | 110 | 0.9321 | 0.0376 | 0.9319 |
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+ | No log | 7.0 | 112 | 0.9103 | 0.0426 | 0.9101 |
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+ | No log | 7.125 | 114 | 0.8699 | 0.0193 | 0.8696 |
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+ | No log | 7.25 | 116 | 0.7446 | -0.0195 | 0.7440 |
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+ | No log | 7.375 | 118 | 0.6938 | -0.0446 | 0.6931 |
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+ | No log | 7.5 | 120 | 0.6932 | -0.0446 | 0.6926 |
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+ | No log | 7.625 | 122 | 0.7665 | -0.0242 | 0.7659 |
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+ | No log | 7.75 | 124 | 0.9012 | -0.0078 | 0.9008 |
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+ | No log | 7.875 | 126 | 0.9982 | 0.0480 | 0.9978 |
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+ | No log | 8.0 | 128 | 1.0450 | 0.0602 | 1.0446 |
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+ | No log | 8.125 | 130 | 1.0164 | 0.0643 | 1.0160 |
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+ | No log | 8.25 | 132 | 0.9926 | 0.0728 | 0.9921 |
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+ | No log | 8.375 | 134 | 0.9480 | 0.0328 | 0.9475 |
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+ | No log | 8.5 | 136 | 0.9640 | 0.0245 | 0.9635 |
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+ | No log | 8.625 | 138 | 0.9946 | 0.0501 | 0.9942 |
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+ | No log | 8.75 | 140 | 0.9731 | 0.0245 | 0.9727 |
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+ | No log | 8.875 | 142 | 0.9147 | 0.0213 | 0.9142 |
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+ | No log | 9.0 | 144 | 0.8829 | 0.0177 | 0.8824 |
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+ | No log | 9.125 | 146 | 0.8432 | 0.0231 | 0.8426 |
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+ | No log | 9.25 | 148 | 0.8012 | 0.0050 | 0.8006 |
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+ | No log | 9.375 | 150 | 0.7936 | -0.0182 | 0.7929 |
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+ | No log | 9.5 | 152 | 0.7870 | -0.0182 | 0.7863 |
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+ | No log | 9.625 | 154 | 0.8001 | 0.0050 | 0.7994 |
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+ | No log | 9.75 | 156 | 0.8093 | 0.0050 | 0.8086 |
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+ | No log | 9.875 | 158 | 0.8204 | 0.0005 | 0.8198 |
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+ | No log | 10.0 | 160 | 0.8237 | 0.0005 | 0.8231 |
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  ### Framework versions