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arabert_cross_vocabulary_task1_fold2

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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_fold1
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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_fold1
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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: 0.8237
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- - Qwk: 0.0005
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- - Mse: 0.8231
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  ## Model description
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@@ -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 | 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
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_vocabulary_task1_fold2
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_fold2
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: 0.8384
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+ - Qwk: 0.0355
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+ - Mse: 0.8384
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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 | 4.6248 | -0.0324 | 4.6248 |
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+ | No log | 0.2353 | 4 | 1.7789 | 0.0201 | 1.7789 |
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+ | No log | 0.3529 | 6 | 0.8842 | 0.0565 | 0.8842 |
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+ | No log | 0.4706 | 8 | 0.8601 | -0.0731 | 0.8601 |
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+ | No log | 0.5882 | 10 | 0.8512 | -0.0838 | 0.8512 |
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+ | No log | 0.7059 | 12 | 0.7752 | -0.0229 | 0.7752 |
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+ | No log | 0.8235 | 14 | 0.7856 | 0.0496 | 0.7856 |
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+ | No log | 0.9412 | 16 | 0.7647 | 0.0550 | 0.7647 |
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+ | No log | 1.0588 | 18 | 0.8100 | 0.0 | 0.8100 |
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+ | No log | 1.1765 | 20 | 0.9168 | 0.0 | 0.9168 |
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+ | No log | 1.2941 | 22 | 0.8569 | 0.0 | 0.8569 |
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+ | No log | 1.4118 | 24 | 0.7547 | 0.0 | 0.7547 |
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+ | No log | 1.5294 | 26 | 0.7737 | 0.0 | 0.7737 |
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+ | No log | 1.6471 | 28 | 0.7574 | 0.0 | 0.7574 |
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+ | No log | 1.7647 | 30 | 0.7125 | 0.0550 | 0.7125 |
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+ | No log | 1.8824 | 32 | 0.7216 | 0.0 | 0.7216 |
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+ | No log | 2.0 | 34 | 1.0254 | -0.0072 | 1.0254 |
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+ | No log | 2.1176 | 36 | 1.2005 | 0.1411 | 1.2005 |
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+ | No log | 2.2353 | 38 | 1.0049 | -0.0072 | 1.0049 |
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+ | No log | 2.3529 | 40 | 0.7418 | 0.0140 | 0.7418 |
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+ | No log | 2.4706 | 42 | 0.7130 | 0.0441 | 0.7130 |
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+ | No log | 2.5882 | 44 | 0.7791 | 0.0 | 0.7791 |
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+ | No log | 2.7059 | 46 | 0.9107 | -0.0072 | 0.9107 |
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+ | No log | 2.8235 | 48 | 0.8828 | 0.0 | 0.8828 |
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+ | No log | 2.9412 | 50 | 0.7509 | 0.0268 | 0.7509 |
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+ | No log | 3.0588 | 52 | 0.7111 | 0.1173 | 0.7111 |
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+ | No log | 3.1765 | 54 | 0.7162 | 0.1309 | 0.7162 |
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+ | No log | 3.2941 | 56 | 0.7366 | 0.0386 | 0.7366 |
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+ | No log | 3.4118 | 58 | 0.8225 | 0.0 | 0.8225 |
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+ | No log | 3.5294 | 60 | 0.7895 | -0.0072 | 0.7895 |
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+ | No log | 3.6471 | 62 | 0.7926 | -0.0072 | 0.7926 |
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+ | No log | 3.7647 | 64 | 0.8031 | -0.0072 | 0.8031 |
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+ | No log | 3.8824 | 66 | 0.8109 | 0.0 | 0.8109 |
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+ | No log | 4.0 | 68 | 0.7670 | 0.0361 | 0.7670 |
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+ | No log | 4.1176 | 70 | 0.7062 | 0.0643 | 0.7062 |
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+ | No log | 4.2353 | 72 | 0.6998 | 0.1209 | 0.6998 |
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+ | No log | 4.3529 | 74 | 0.7169 | 0.0755 | 0.7169 |
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+ | No log | 4.4706 | 76 | 0.8345 | -0.0072 | 0.8345 |
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+ | No log | 4.5882 | 78 | 0.9136 | 0.0387 | 0.9136 |
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+ | No log | 4.7059 | 80 | 0.8757 | 0.0086 | 0.8757 |
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+ | No log | 4.8235 | 82 | 0.8750 | 0.0086 | 0.8750 |
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+ | No log | 4.9412 | 84 | 0.8295 | 0.0 | 0.8295 |
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+ | No log | 5.0588 | 86 | 0.7644 | 0.0069 | 0.7644 |
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+ | No log | 5.1765 | 88 | 0.7883 | 0.0069 | 0.7883 |
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+ | No log | 5.2941 | 90 | 0.8861 | 0.1343 | 0.8861 |
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+ | No log | 5.4118 | 92 | 0.8567 | -0.0144 | 0.8567 |
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+ | No log | 5.5294 | 94 | 0.7787 | 0.0480 | 0.7787 |
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+ | No log | 5.6471 | 96 | 0.7991 | 0.0361 | 0.7991 |
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+ | No log | 5.7647 | 98 | 0.8546 | 0.0361 | 0.8546 |
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+ | No log | 5.8824 | 100 | 0.8059 | 0.0434 | 0.8059 |
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+ | No log | 6.0 | 102 | 0.7338 | 0.0846 | 0.7338 |
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+ | No log | 6.1176 | 104 | 0.7167 | 0.1209 | 0.7167 |
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+ | No log | 6.2353 | 106 | 0.7205 | 0.1209 | 0.7205 |
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+ | No log | 6.3529 | 108 | 0.7597 | 0.0707 | 0.7597 |
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+ | No log | 6.4706 | 110 | 0.8598 | -0.0136 | 0.8598 |
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+ | No log | 6.5882 | 112 | 0.8616 | 0.0376 | 0.8616 |
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+ | No log | 6.7059 | 114 | 0.7980 | 0.0940 | 0.7980 |
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+ | No log | 6.8235 | 116 | 0.7853 | 0.0940 | 0.7853 |
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+ | No log | 6.9412 | 118 | 0.7673 | 0.1027 | 0.7673 |
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+ | No log | 7.0588 | 120 | 0.7550 | 0.1069 | 0.7550 |
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+ | No log | 7.1765 | 122 | 0.7670 | 0.1027 | 0.7670 |
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+ | No log | 7.2941 | 124 | 0.8362 | 0.0822 | 0.8362 |
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+ | No log | 7.4118 | 126 | 0.8895 | -0.0054 | 0.8895 |
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+ | No log | 7.5294 | 128 | 0.9417 | -0.0470 | 0.9417 |
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+ | No log | 7.6471 | 130 | 0.9102 | -0.0406 | 0.9102 |
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+ | No log | 7.7647 | 132 | 0.8290 | 0.0355 | 0.8290 |
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+ | No log | 7.8824 | 134 | 0.7603 | 0.0736 | 0.7603 |
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+ | No log | 8.0 | 136 | 0.7354 | 0.0643 | 0.7354 |
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+ | No log | 8.1176 | 138 | 0.7294 | 0.0643 | 0.7294 |
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+ | No log | 8.2353 | 140 | 0.7448 | 0.0596 | 0.7448 |
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+ | No log | 8.3529 | 142 | 0.7876 | -0.0216 | 0.7876 |
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+ | No log | 8.4706 | 144 | 0.8424 | 0.0081 | 0.8424 |
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+ | No log | 8.5882 | 146 | 0.8830 | 0.0295 | 0.8830 |
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+ | No log | 8.7059 | 148 | 0.8829 | 0.0295 | 0.8829 |
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+ | No log | 8.8235 | 150 | 0.8593 | 0.0295 | 0.8593 |
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+ | No log | 8.9412 | 152 | 0.8214 | 0.0355 | 0.8214 |
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+ | No log | 9.0588 | 154 | 0.7878 | 0.1217 | 0.7878 |
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+ | No log | 9.1765 | 156 | 0.7838 | 0.1255 | 0.7838 |
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+ | No log | 9.2941 | 158 | 0.7871 | 0.1255 | 0.7871 |
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+ | No log | 9.4118 | 160 | 0.7920 | 0.1255 | 0.7920 |
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+ | No log | 9.5294 | 162 | 0.7986 | 0.0388 | 0.7986 |
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+ | No log | 9.6471 | 164 | 0.8132 | 0.0479 | 0.8132 |
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+ | No log | 9.7647 | 166 | 0.8290 | 0.0355 | 0.8290 |
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+ | No log | 9.8824 | 168 | 0.8368 | 0.0355 | 0.8368 |
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+ | No log | 10.0 | 170 | 0.8384 | 0.0355 | 0.8384 |
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  ### Framework versions