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arabert_cross_organization_task6_fold6

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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_organization_task6_fold5
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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_organization_task6_fold5
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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: 0.4946
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- - Qwk: 0.7585
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- - Mse: 0.4958
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  ## Model description
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@@ -45,88 +45,93 @@ 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 | 1.3569 | 0.2073 | 1.3566 |
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- | No log | 0.25 | 4 | 0.8917 | 0.3804 | 0.8926 |
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- | No log | 0.375 | 6 | 1.3940 | 0.5002 | 1.3954 |
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- | No log | 0.5 | 8 | 1.1581 | 0.5869 | 1.1599 |
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- | No log | 0.625 | 10 | 0.8359 | 0.5005 | 0.8373 |
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- | No log | 0.75 | 12 | 0.8352 | 0.6240 | 0.8368 |
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- | No log | 0.875 | 14 | 0.7817 | 0.6808 | 0.7831 |
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- | No log | 1.0 | 16 | 0.6321 | 0.7284 | 0.6335 |
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- | No log | 1.125 | 18 | 0.5497 | 0.7013 | 0.5509 |
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- | No log | 1.25 | 20 | 0.6330 | 0.7733 | 0.6344 |
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- | No log | 1.375 | 22 | 0.9312 | 0.7286 | 0.9326 |
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- | No log | 1.5 | 24 | 0.9410 | 0.7373 | 0.9424 |
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- | No log | 1.625 | 26 | 0.6704 | 0.7704 | 0.6717 |
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- | No log | 1.75 | 28 | 0.5140 | 0.6654 | 0.5150 |
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- | No log | 1.875 | 30 | 0.5258 | 0.6207 | 0.5266 |
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- | No log | 2.0 | 32 | 0.4993 | 0.7208 | 0.5003 |
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- | No log | 2.125 | 34 | 0.5995 | 0.7661 | 0.6008 |
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- | No log | 2.25 | 36 | 0.6850 | 0.7821 | 0.6865 |
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- | No log | 2.375 | 38 | 0.6445 | 0.7839 | 0.6460 |
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- | No log | 2.5 | 40 | 0.5426 | 0.7571 | 0.5438 |
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- | No log | 2.625 | 42 | 0.5374 | 0.7584 | 0.5385 |
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- | No log | 2.75 | 44 | 0.5401 | 0.7508 | 0.5413 |
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- | No log | 2.875 | 46 | 0.5560 | 0.7716 | 0.5572 |
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- | No log | 3.0 | 48 | 0.5460 | 0.7794 | 0.5472 |
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- | No log | 3.125 | 50 | 0.5399 | 0.7800 | 0.5410 |
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- | No log | 3.25 | 52 | 0.4966 | 0.7520 | 0.4976 |
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- | No log | 3.375 | 54 | 0.4783 | 0.7484 | 0.4792 |
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- | No log | 3.5 | 56 | 0.5055 | 0.7654 | 0.5064 |
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- | No log | 3.625 | 58 | 0.4947 | 0.7569 | 0.4955 |
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- | No log | 3.75 | 60 | 0.5387 | 0.7681 | 0.5397 |
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- | No log | 3.875 | 62 | 0.6614 | 0.8077 | 0.6627 |
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- | No log | 4.0 | 64 | 0.6356 | 0.8243 | 0.6369 |
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- | No log | 4.125 | 66 | 0.4951 | 0.7545 | 0.4959 |
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- | No log | 4.25 | 68 | 0.4581 | 0.7123 | 0.4588 |
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- | No log | 4.375 | 70 | 0.4776 | 0.7450 | 0.4784 |
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- | No log | 4.5 | 72 | 0.5531 | 0.7823 | 0.5543 |
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- | No log | 4.625 | 74 | 0.5792 | 0.8103 | 0.5805 |
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- | No log | 4.75 | 76 | 0.5337 | 0.7801 | 0.5349 |
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- | No log | 4.875 | 78 | 0.4762 | 0.7597 | 0.4771 |
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- | No log | 5.0 | 80 | 0.4679 | 0.7390 | 0.4687 |
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- | No log | 5.125 | 82 | 0.4753 | 0.7488 | 0.4762 |
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- | No log | 5.25 | 84 | 0.5131 | 0.7689 | 0.5143 |
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- | No log | 5.375 | 86 | 0.5442 | 0.7925 | 0.5455 |
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- | No log | 5.5 | 88 | 0.5074 | 0.7624 | 0.5086 |
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- | No log | 5.625 | 90 | 0.4586 | 0.7435 | 0.4596 |
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- | No log | 5.75 | 92 | 0.4498 | 0.7269 | 0.4507 |
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- | No log | 5.875 | 94 | 0.4604 | 0.7354 | 0.4614 |
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- | No log | 6.0 | 96 | 0.5055 | 0.7753 | 0.5068 |
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- | No log | 6.125 | 98 | 0.5761 | 0.7991 | 0.5776 |
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- | No log | 6.25 | 100 | 0.5566 | 0.7942 | 0.5580 |
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- | No log | 6.375 | 102 | 0.5097 | 0.7509 | 0.5109 |
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- | No log | 6.5 | 104 | 0.4777 | 0.7454 | 0.4787 |
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- | No log | 6.625 | 106 | 0.4691 | 0.7225 | 0.4700 |
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- | No log | 6.75 | 108 | 0.4712 | 0.7283 | 0.4720 |
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- | No log | 6.875 | 110 | 0.4817 | 0.7509 | 0.4827 |
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- | No log | 7.0 | 112 | 0.4772 | 0.7454 | 0.4781 |
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- | No log | 7.125 | 114 | 0.4790 | 0.7490 | 0.4799 |
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- | No log | 7.25 | 116 | 0.5003 | 0.7688 | 0.5014 |
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- | No log | 7.375 | 118 | 0.5353 | 0.7753 | 0.5366 |
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- | No log | 7.5 | 120 | 0.5284 | 0.7670 | 0.5297 |
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- | No log | 7.625 | 122 | 0.5075 | 0.7556 | 0.5086 |
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- | No log | 7.75 | 124 | 0.4824 | 0.7527 | 0.4834 |
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- | No log | 7.875 | 126 | 0.4782 | 0.7527 | 0.4792 |
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- | No log | 8.0 | 128 | 0.4745 | 0.7554 | 0.4755 |
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- | No log | 8.125 | 130 | 0.4803 | 0.7523 | 0.4813 |
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- | No log | 8.25 | 132 | 0.4946 | 0.7614 | 0.4957 |
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- | No log | 8.375 | 134 | 0.4938 | 0.7558 | 0.4950 |
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- | No log | 8.5 | 136 | 0.4888 | 0.7558 | 0.4900 |
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- | No log | 8.625 | 138 | 0.4775 | 0.7507 | 0.4786 |
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- | No log | 8.75 | 140 | 0.4714 | 0.7474 | 0.4724 |
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- | No log | 8.875 | 142 | 0.4668 | 0.7410 | 0.4677 |
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- | No log | 9.0 | 144 | 0.4672 | 0.7382 | 0.4681 |
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- | No log | 9.125 | 146 | 0.4689 | 0.7433 | 0.4698 |
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- | No log | 9.25 | 148 | 0.4738 | 0.7571 | 0.4748 |
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- | No log | 9.375 | 150 | 0.4814 | 0.7511 | 0.4825 |
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- | No log | 9.5 | 152 | 0.4866 | 0.7567 | 0.4877 |
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- | No log | 9.625 | 154 | 0.4900 | 0.7585 | 0.4911 |
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- | No log | 9.75 | 156 | 0.4909 | 0.7585 | 0.4921 |
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- | No log | 9.875 | 158 | 0.4930 | 0.7585 | 0.4942 |
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- | No log | 10.0 | 160 | 0.4946 | 0.7585 | 0.4958 |
 
 
 
 
 
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_organization_task6_fold6
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_organization_task6_fold6
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: 0.6971
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+ - Qwk: 0.5467
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+ - Mse: 0.6953
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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 | 0.1176 | 2 | 2.1812 | 0.0813 | 2.1796 |
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+ | No log | 0.2353 | 4 | 1.1581 | 0.1541 | 1.1560 |
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+ | No log | 0.3529 | 6 | 0.9175 | 0.4300 | 0.9172 |
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+ | No log | 0.4706 | 8 | 0.7853 | 0.5387 | 0.7849 |
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+ | No log | 0.5882 | 10 | 0.7421 | 0.3500 | 0.7415 |
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+ | No log | 0.7059 | 12 | 0.7475 | 0.3575 | 0.7469 |
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+ | No log | 0.8235 | 14 | 0.5277 | 0.6055 | 0.5272 |
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+ | No log | 0.9412 | 16 | 0.6059 | 0.7252 | 0.6066 |
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+ | No log | 1.0588 | 18 | 0.5616 | 0.7136 | 0.5620 |
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+ | No log | 1.1765 | 20 | 0.5211 | 0.6304 | 0.5204 |
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+ | No log | 1.2941 | 22 | 0.6860 | 0.5190 | 0.6841 |
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+ | No log | 1.4118 | 24 | 0.6738 | 0.5216 | 0.6721 |
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+ | No log | 1.5294 | 26 | 0.5480 | 0.6313 | 0.5472 |
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+ | No log | 1.6471 | 28 | 0.5424 | 0.7060 | 0.5428 |
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+ | No log | 1.7647 | 30 | 0.4918 | 0.6873 | 0.4920 |
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+ | No log | 1.8824 | 32 | 0.5098 | 0.5684 | 0.5094 |
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+ | No log | 2.0 | 34 | 0.5437 | 0.5294 | 0.5430 |
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+ | No log | 2.1176 | 36 | 0.5312 | 0.5901 | 0.5302 |
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+ | No log | 2.2353 | 38 | 0.5616 | 0.5966 | 0.5604 |
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+ | No log | 2.3529 | 40 | 0.5882 | 0.5838 | 0.5868 |
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+ | No log | 2.4706 | 42 | 0.5423 | 0.6000 | 0.5413 |
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+ | No log | 2.5882 | 44 | 0.5067 | 0.6211 | 0.5059 |
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+ | No log | 2.7059 | 46 | 0.4934 | 0.6349 | 0.4926 |
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+ | No log | 2.8235 | 48 | 0.4940 | 0.6329 | 0.4932 |
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+ | No log | 2.9412 | 50 | 0.5291 | 0.5677 | 0.5279 |
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+ | No log | 3.0588 | 52 | 0.6166 | 0.5158 | 0.6151 |
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+ | No log | 3.1765 | 54 | 0.6014 | 0.5588 | 0.5998 |
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+ | No log | 3.2941 | 56 | 0.5316 | 0.5878 | 0.5303 |
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+ | No log | 3.4118 | 58 | 0.5135 | 0.5990 | 0.5124 |
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+ | No log | 3.5294 | 60 | 0.5285 | 0.5827 | 0.5273 |
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+ | No log | 3.6471 | 62 | 0.5943 | 0.5492 | 0.5929 |
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+ | No log | 3.7647 | 64 | 0.5882 | 0.5620 | 0.5868 |
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+ | No log | 3.8824 | 66 | 0.5237 | 0.5937 | 0.5227 |
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+ | No log | 4.0 | 68 | 0.5270 | 0.6150 | 0.5261 |
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+ | No log | 4.1176 | 70 | 0.5820 | 0.5589 | 0.5806 |
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+ | No log | 4.2353 | 72 | 0.6445 | 0.5284 | 0.6429 |
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+ | No log | 4.3529 | 74 | 0.6153 | 0.5627 | 0.6139 |
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+ | No log | 4.4706 | 76 | 0.6066 | 0.5783 | 0.6054 |
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+ | No log | 4.5882 | 78 | 0.6378 | 0.5639 | 0.6363 |
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+ | No log | 4.7059 | 80 | 0.7155 | 0.5342 | 0.7135 |
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+ | No log | 4.8235 | 82 | 0.7123 | 0.5305 | 0.7104 |
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+ | No log | 4.9412 | 84 | 0.6786 | 0.5363 | 0.6769 |
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+ | No log | 5.0588 | 86 | 0.6340 | 0.5611 | 0.6326 |
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+ | No log | 5.1765 | 88 | 0.6050 | 0.5630 | 0.6038 |
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+ | No log | 5.2941 | 90 | 0.6307 | 0.5564 | 0.6293 |
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+ | No log | 5.4118 | 92 | 0.6603 | 0.5449 | 0.6588 |
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+ | No log | 5.5294 | 94 | 0.6765 | 0.5483 | 0.6748 |
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+ | No log | 5.6471 | 96 | 0.6364 | 0.5686 | 0.6351 |
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+ | No log | 5.7647 | 98 | 0.6144 | 0.5967 | 0.6132 |
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+ | No log | 5.8824 | 100 | 0.6315 | 0.5826 | 0.6300 |
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+ | No log | 6.0 | 102 | 0.6964 | 0.5217 | 0.6946 |
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+ | No log | 6.1176 | 104 | 0.6906 | 0.5310 | 0.6887 |
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+ | No log | 6.2353 | 106 | 0.6656 | 0.5513 | 0.6639 |
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+ | No log | 6.3529 | 108 | 0.6273 | 0.5829 | 0.6259 |
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+ | No log | 6.4706 | 110 | 0.6354 | 0.5748 | 0.6340 |
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+ | No log | 6.5882 | 112 | 0.6855 | 0.5397 | 0.6839 |
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+ | No log | 6.7059 | 114 | 0.7228 | 0.5179 | 0.7211 |
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+ | No log | 6.8235 | 116 | 0.6976 | 0.5206 | 0.6960 |
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+ | No log | 6.9412 | 118 | 0.6558 | 0.5456 | 0.6544 |
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+ | No log | 7.0588 | 120 | 0.6618 | 0.5569 | 0.6605 |
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+ | No log | 7.1765 | 122 | 0.7088 | 0.5397 | 0.7072 |
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+ | No log | 7.2941 | 124 | 0.8015 | 0.4900 | 0.7996 |
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+ | No log | 7.4118 | 126 | 0.8354 | 0.4798 | 0.8334 |
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+ | No log | 7.5294 | 128 | 0.7861 | 0.4973 | 0.7842 |
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+ | No log | 7.6471 | 130 | 0.7081 | 0.5399 | 0.7065 |
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+ | No log | 7.7647 | 132 | 0.6756 | 0.5725 | 0.6741 |
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+ | No log | 7.8824 | 134 | 0.6874 | 0.5524 | 0.6859 |
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+ | No log | 8.0 | 136 | 0.7225 | 0.5459 | 0.7207 |
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+ | No log | 8.1176 | 138 | 0.7336 | 0.5368 | 0.7317 |
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+ | No log | 8.2353 | 140 | 0.7330 | 0.5258 | 0.7312 |
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+ | No log | 8.3529 | 142 | 0.7088 | 0.5474 | 0.7070 |
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+ | No log | 8.4706 | 144 | 0.7009 | 0.5474 | 0.6991 |
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+ | No log | 8.5882 | 146 | 0.6880 | 0.5489 | 0.6863 |
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+ | No log | 8.7059 | 148 | 0.6695 | 0.5530 | 0.6679 |
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+ | No log | 8.8235 | 150 | 0.6654 | 0.5587 | 0.6638 |
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+ | No log | 8.9412 | 152 | 0.6764 | 0.5464 | 0.6747 |
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+ | No log | 9.0588 | 154 | 0.6945 | 0.5419 | 0.6927 |
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+ | No log | 9.1765 | 156 | 0.7081 | 0.5278 | 0.7063 |
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+ | No log | 9.2941 | 158 | 0.7099 | 0.5292 | 0.7080 |
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+ | No log | 9.4118 | 160 | 0.7043 | 0.5419 | 0.7025 |
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+ | No log | 9.5294 | 162 | 0.7049 | 0.5430 | 0.7031 |
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+ | No log | 9.6471 | 164 | 0.7019 | 0.5430 | 0.7000 |
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+ | No log | 9.7647 | 166 | 0.6996 | 0.5467 | 0.6978 |
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+ | No log | 9.8824 | 168 | 0.6977 | 0.5467 | 0.6959 |
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+ | No log | 10.0 | 170 | 0.6971 | 0.5467 | 0.6953 |
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  ### Framework versions