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arabert_cross_development_task1_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_development_task1_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_development_task1_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: 0.5861
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- - Qwk: 0.7634
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- - Mse: 0.5861
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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 | 1.7502 | 0.1271 | 1.7502 |
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- | No log | 0.2667 | 4 | 1.2292 | 0.1987 | 1.2292 |
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- | No log | 0.4 | 6 | 1.3080 | 0.3555 | 1.3080 |
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- | No log | 0.5333 | 8 | 0.9607 | 0.4976 | 0.9607 |
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- | No log | 0.6667 | 10 | 0.8578 | 0.6328 | 0.8578 |
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- | No log | 0.8 | 12 | 0.8243 | 0.6683 | 0.8243 |
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- | No log | 0.9333 | 14 | 0.6736 | 0.6082 | 0.6736 |
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- | No log | 1.0667 | 16 | 0.6841 | 0.5941 | 0.6841 |
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- | No log | 1.2 | 18 | 0.6510 | 0.6300 | 0.6510 |
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- | No log | 1.3333 | 20 | 0.7744 | 0.7345 | 0.7744 |
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- | No log | 1.4667 | 22 | 0.6786 | 0.7336 | 0.6786 |
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- | No log | 1.6 | 24 | 0.5769 | 0.6663 | 0.5769 |
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- | No log | 1.7333 | 26 | 0.5647 | 0.6751 | 0.5647 |
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- | No log | 1.8667 | 28 | 0.6191 | 0.7228 | 0.6191 |
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- | No log | 2.0 | 30 | 0.6480 | 0.7149 | 0.6480 |
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- | No log | 2.1333 | 32 | 0.5930 | 0.6377 | 0.5930 |
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- | No log | 2.2667 | 34 | 0.5792 | 0.6840 | 0.5792 |
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- | No log | 2.4 | 36 | 0.6399 | 0.7684 | 0.6399 |
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- | No log | 2.5333 | 38 | 0.6099 | 0.7730 | 0.6099 |
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- | No log | 2.6667 | 40 | 0.5513 | 0.7336 | 0.5513 |
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- | No log | 2.8 | 42 | 0.5787 | 0.7674 | 0.5787 |
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- | No log | 2.9333 | 44 | 0.6353 | 0.7926 | 0.6353 |
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- | No log | 3.0667 | 46 | 0.5670 | 0.7594 | 0.5670 |
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- | No log | 3.2 | 48 | 0.6004 | 0.7827 | 0.6004 |
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- | No log | 3.3333 | 50 | 0.6263 | 0.7869 | 0.6263 |
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- | No log | 3.4667 | 52 | 0.5762 | 0.7498 | 0.5762 |
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- | No log | 3.6 | 54 | 0.5570 | 0.7472 | 0.5570 |
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- | No log | 3.7333 | 56 | 0.6280 | 0.7790 | 0.6280 |
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- | No log | 3.8667 | 58 | 0.6056 | 0.7764 | 0.6056 |
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- | No log | 4.0 | 60 | 0.5239 | 0.7299 | 0.5239 |
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- | No log | 4.1333 | 62 | 0.5192 | 0.7305 | 0.5192 |
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- | No log | 4.2667 | 64 | 0.5703 | 0.7631 | 0.5703 |
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- | No log | 4.4 | 66 | 0.6518 | 0.7918 | 0.6518 |
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- | No log | 4.5333 | 68 | 0.7302 | 0.7883 | 0.7302 |
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- | No log | 4.6667 | 70 | 0.6654 | 0.7960 | 0.6654 |
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- | No log | 4.8 | 72 | 0.5714 | 0.7539 | 0.5714 |
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- | No log | 4.9333 | 74 | 0.5149 | 0.7046 | 0.5149 |
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- | No log | 5.0667 | 76 | 0.5129 | 0.6751 | 0.5129 |
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- | No log | 5.2 | 78 | 0.5200 | 0.7257 | 0.5200 |
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- | No log | 5.3333 | 80 | 0.5968 | 0.7701 | 0.5968 |
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- | No log | 5.4667 | 82 | 0.6356 | 0.7899 | 0.6356 |
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- | No log | 5.6 | 84 | 0.5976 | 0.7718 | 0.5976 |
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- | No log | 5.7333 | 86 | 0.5510 | 0.7528 | 0.5510 |
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- | No log | 5.8667 | 88 | 0.5499 | 0.7505 | 0.5499 |
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- | No log | 6.0 | 90 | 0.5581 | 0.7507 | 0.5581 |
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- | No log | 6.1333 | 92 | 0.5846 | 0.7624 | 0.5846 |
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- | No log | 6.2667 | 94 | 0.6247 | 0.7828 | 0.6247 |
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- | No log | 6.4 | 96 | 0.6363 | 0.7865 | 0.6363 |
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- | No log | 6.5333 | 98 | 0.6065 | 0.7792 | 0.6065 |
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- | No log | 6.6667 | 100 | 0.5753 | 0.7552 | 0.5753 |
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- | No log | 6.8 | 102 | 0.5617 | 0.7438 | 0.5617 |
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- | No log | 6.9333 | 104 | 0.5593 | 0.7415 | 0.5593 |
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- | No log | 7.0667 | 106 | 0.5501 | 0.7410 | 0.5501 |
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- | No log | 7.2 | 108 | 0.5736 | 0.7489 | 0.5736 |
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- | No log | 7.3333 | 110 | 0.6235 | 0.7773 | 0.6235 |
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- | No log | 7.4667 | 112 | 0.6392 | 0.7840 | 0.6392 |
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- | No log | 7.6 | 114 | 0.6211 | 0.7732 | 0.6211 |
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- | No log | 7.7333 | 116 | 0.5970 | 0.7733 | 0.5970 |
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- | No log | 7.8667 | 118 | 0.5611 | 0.7530 | 0.5611 |
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- | No log | 8.0 | 120 | 0.5439 | 0.7470 | 0.5439 |
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- | No log | 8.1333 | 122 | 0.5497 | 0.7484 | 0.5497 |
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- | No log | 8.2667 | 124 | 0.5836 | 0.7580 | 0.5836 |
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- | No log | 8.4 | 126 | 0.6389 | 0.7749 | 0.6389 |
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- | No log | 8.5333 | 128 | 0.6778 | 0.7817 | 0.6778 |
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- | No log | 8.6667 | 130 | 0.6794 | 0.7790 | 0.6794 |
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- | No log | 8.8 | 132 | 0.6575 | 0.7769 | 0.6575 |
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- | No log | 8.9333 | 134 | 0.6182 | 0.7797 | 0.6182 |
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- | No log | 9.0667 | 136 | 0.5921 | 0.7689 | 0.5921 |
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- | No log | 9.2 | 138 | 0.5771 | 0.7588 | 0.5771 |
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- | No log | 9.3333 | 140 | 0.5657 | 0.7530 | 0.5657 |
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- | No log | 9.4667 | 142 | 0.5672 | 0.7530 | 0.5672 |
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- | No log | 9.6 | 144 | 0.5759 | 0.7639 | 0.5759 |
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- | No log | 9.7333 | 146 | 0.5809 | 0.7611 | 0.5809 |
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- | No log | 9.8667 | 148 | 0.5847 | 0.7611 | 0.5847 |
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- | No log | 10.0 | 150 | 0.5861 | 0.7634 | 0.5861 |
 
 
 
 
 
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_development_task1_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_development_task1_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: 0.3891
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+ - Qwk: 0.7487
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+ - Mse: 0.3891
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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 | 2.7046 | 0.0134 | 2.7046 |
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+ | No log | 0.25 | 4 | 1.3006 | 0.1103 | 1.3006 |
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+ | No log | 0.375 | 6 | 0.7355 | 0.3354 | 0.7355 |
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+ | No log | 0.5 | 8 | 0.8932 | 0.3820 | 0.8932 |
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+ | No log | 0.625 | 10 | 0.5839 | 0.4676 | 0.5839 |
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+ | No log | 0.75 | 12 | 0.4634 | 0.5294 | 0.4634 |
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+ | No log | 0.875 | 14 | 0.4578 | 0.5335 | 0.4578 |
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+ | No log | 1.0 | 16 | 0.5111 | 0.5160 | 0.5111 |
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+ | No log | 1.125 | 18 | 0.4822 | 0.6507 | 0.4822 |
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+ | No log | 1.25 | 20 | 0.4309 | 0.6257 | 0.4309 |
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+ | No log | 1.375 | 22 | 0.4637 | 0.6422 | 0.4637 |
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+ | No log | 1.5 | 24 | 0.5888 | 0.7264 | 0.5888 |
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+ | No log | 1.625 | 26 | 0.5751 | 0.7173 | 0.5751 |
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+ | No log | 1.75 | 28 | 0.4309 | 0.6445 | 0.4309 |
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+ | No log | 1.875 | 30 | 0.3977 | 0.6113 | 0.3977 |
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+ | No log | 2.0 | 32 | 0.4095 | 0.6330 | 0.4095 |
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+ | No log | 2.125 | 34 | 0.4861 | 0.7147 | 0.4861 |
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+ | No log | 2.25 | 36 | 0.5155 | 0.7516 | 0.5155 |
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+ | No log | 2.375 | 38 | 0.4703 | 0.7321 | 0.4703 |
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+ | No log | 2.5 | 40 | 0.3861 | 0.6978 | 0.3861 |
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+ | No log | 2.625 | 42 | 0.3964 | 0.7189 | 0.3964 |
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+ | No log | 2.75 | 44 | 0.5105 | 0.7660 | 0.5105 |
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+ | No log | 2.875 | 46 | 0.5630 | 0.7439 | 0.5630 |
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+ | No log | 3.0 | 48 | 0.4666 | 0.7758 | 0.4666 |
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+ | No log | 3.125 | 50 | 0.4033 | 0.7314 | 0.4033 |
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+ | No log | 3.25 | 52 | 0.3886 | 0.7225 | 0.3886 |
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+ | No log | 3.375 | 54 | 0.4264 | 0.7369 | 0.4264 |
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+ | No log | 3.5 | 56 | 0.4681 | 0.7538 | 0.4681 |
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+ | No log | 3.625 | 58 | 0.4255 | 0.7357 | 0.4255 |
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+ | No log | 3.75 | 60 | 0.3784 | 0.7381 | 0.3784 |
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+ | No log | 3.875 | 62 | 0.3835 | 0.7261 | 0.3835 |
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+ | No log | 4.0 | 64 | 0.3863 | 0.7091 | 0.3863 |
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+ | No log | 4.125 | 66 | 0.3964 | 0.7022 | 0.3964 |
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+ | No log | 4.25 | 68 | 0.4674 | 0.7519 | 0.4674 |
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+ | No log | 4.375 | 70 | 0.5670 | 0.7310 | 0.5670 |
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+ | No log | 4.5 | 72 | 0.5082 | 0.7265 | 0.5082 |
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+ | No log | 4.625 | 74 | 0.3989 | 0.7387 | 0.3989 |
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+ | No log | 4.75 | 76 | 0.3568 | 0.7218 | 0.3568 |
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+ | No log | 4.875 | 78 | 0.3670 | 0.7343 | 0.3670 |
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+ | No log | 5.0 | 80 | 0.4147 | 0.7453 | 0.4147 |
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+ | No log | 5.125 | 82 | 0.4613 | 0.7583 | 0.4613 |
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+ | No log | 5.25 | 84 | 0.4365 | 0.7493 | 0.4365 |
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+ | No log | 5.375 | 86 | 0.3787 | 0.7383 | 0.3787 |
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+ | No log | 5.5 | 88 | 0.3637 | 0.7327 | 0.3637 |
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+ | No log | 5.625 | 90 | 0.3896 | 0.7461 | 0.3896 |
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+ | No log | 5.75 | 92 | 0.4827 | 0.7585 | 0.4827 |
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+ | No log | 5.875 | 94 | 0.5207 | 0.7560 | 0.5207 |
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+ | No log | 6.0 | 96 | 0.4771 | 0.7622 | 0.4771 |
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+ | No log | 6.125 | 98 | 0.4131 | 0.7595 | 0.4131 |
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+ | No log | 6.25 | 100 | 0.3861 | 0.7447 | 0.3861 |
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+ | No log | 6.375 | 102 | 0.3770 | 0.7473 | 0.3770 |
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+ | No log | 6.5 | 104 | 0.4030 | 0.7421 | 0.4030 |
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+ | No log | 6.625 | 106 | 0.4334 | 0.7447 | 0.4334 |
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+ | No log | 6.75 | 108 | 0.4677 | 0.7616 | 0.4677 |
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+ | No log | 6.875 | 110 | 0.4931 | 0.7670 | 0.4931 |
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+ | No log | 7.0 | 112 | 0.4703 | 0.7622 | 0.4703 |
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+ | No log | 7.125 | 114 | 0.4736 | 0.7622 | 0.4736 |
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+ | No log | 7.25 | 116 | 0.4565 | 0.7580 | 0.4565 |
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+ | No log | 7.375 | 118 | 0.4114 | 0.7521 | 0.4114 |
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+ | No log | 7.5 | 120 | 0.3925 | 0.7534 | 0.3925 |
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+ | No log | 7.625 | 122 | 0.3937 | 0.7441 | 0.3937 |
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+ | No log | 7.75 | 124 | 0.3906 | 0.7441 | 0.3906 |
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+ | No log | 7.875 | 126 | 0.3958 | 0.7488 | 0.3958 |
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+ | No log | 8.0 | 128 | 0.4005 | 0.7481 | 0.4005 |
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+ | No log | 8.125 | 130 | 0.4095 | 0.7399 | 0.4095 |
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+ | No log | 8.25 | 132 | 0.4044 | 0.7426 | 0.4044 |
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+ | No log | 8.375 | 134 | 0.3885 | 0.7487 | 0.3885 |
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+ | No log | 8.5 | 136 | 0.3727 | 0.7455 | 0.3727 |
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+ | No log | 8.625 | 138 | 0.3751 | 0.7428 | 0.3751 |
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+ | No log | 8.75 | 140 | 0.3851 | 0.7477 | 0.3851 |
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+ | No log | 8.875 | 142 | 0.4024 | 0.7472 | 0.4024 |
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+ | No log | 9.0 | 144 | 0.4118 | 0.7505 | 0.4118 |
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+ | No log | 9.125 | 146 | 0.4171 | 0.7505 | 0.4171 |
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+ | No log | 9.25 | 148 | 0.4179 | 0.7495 | 0.4179 |
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+ | No log | 9.375 | 150 | 0.4096 | 0.7483 | 0.4096 |
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+ | No log | 9.5 | 152 | 0.4015 | 0.7555 | 0.4015 |
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+ | No log | 9.625 | 154 | 0.3949 | 0.7508 | 0.3949 |
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+ | No log | 9.75 | 156 | 0.3905 | 0.7487 | 0.3905 |
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+ | No log | 9.875 | 158 | 0.3894 | 0.7487 | 0.3894 |
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+ | No log | 10.0 | 160 | 0.3891 | 0.7487 | 0.3891 |
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  ### Framework versions