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arabert_cross_vocabulary_task1_fold5

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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_fold4
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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_fold4
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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: 0.3485
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- - Qwk: 0.8274
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- - Mse: 0.3485
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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 | 3.3451 | 0.0078 | 3.3451 |
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- | No log | 0.25 | 4 | 1.7732 | 0.1006 | 1.7732 |
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- | No log | 0.375 | 6 | 0.9918 | 0.3397 | 0.9918 |
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- | No log | 0.5 | 8 | 1.0024 | 0.4328 | 1.0024 |
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- | No log | 0.625 | 10 | 0.7301 | 0.4216 | 0.7301 |
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- | No log | 0.75 | 12 | 0.5802 | 0.5631 | 0.5802 |
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- | No log | 0.875 | 14 | 0.6362 | 0.6894 | 0.6362 |
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- | No log | 1.0 | 16 | 0.7395 | 0.5514 | 0.7395 |
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- | No log | 1.125 | 18 | 0.6416 | 0.6725 | 0.6416 |
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- | No log | 1.25 | 20 | 0.4261 | 0.7695 | 0.4261 |
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- | No log | 1.375 | 22 | 0.4028 | 0.7538 | 0.4028 |
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- | No log | 1.5 | 24 | 0.4106 | 0.7411 | 0.4106 |
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- | No log | 1.625 | 26 | 0.4467 | 0.8262 | 0.4467 |
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- | No log | 1.75 | 28 | 0.5005 | 0.8064 | 0.5005 |
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- | No log | 1.875 | 30 | 0.4228 | 0.7273 | 0.4228 |
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- | No log | 2.0 | 32 | 0.4315 | 0.6938 | 0.4315 |
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- | No log | 2.125 | 34 | 0.5164 | 0.7418 | 0.5164 |
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- | No log | 2.25 | 36 | 0.5729 | 0.7839 | 0.5729 |
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- | No log | 2.375 | 38 | 0.4661 | 0.8238 | 0.4661 |
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- | No log | 2.5 | 40 | 0.3578 | 0.7987 | 0.3578 |
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- | No log | 2.625 | 42 | 0.3452 | 0.7759 | 0.3452 |
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- | No log | 2.75 | 44 | 0.3973 | 0.8179 | 0.3973 |
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- | No log | 2.875 | 46 | 0.4218 | 0.8271 | 0.4218 |
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- | No log | 3.0 | 48 | 0.4017 | 0.8252 | 0.4017 |
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- | No log | 3.125 | 50 | 0.3564 | 0.8053 | 0.3564 |
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- | No log | 3.25 | 52 | 0.3357 | 0.8030 | 0.3357 |
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- | No log | 3.375 | 54 | 0.3797 | 0.8226 | 0.3797 |
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- | No log | 3.5 | 56 | 0.3918 | 0.8236 | 0.3918 |
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- | No log | 3.625 | 58 | 0.3278 | 0.8144 | 0.3278 |
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- | No log | 3.75 | 60 | 0.3256 | 0.8144 | 0.3256 |
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- | No log | 3.875 | 62 | 0.3437 | 0.8131 | 0.3437 |
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- | No log | 4.0 | 64 | 0.3613 | 0.8186 | 0.3613 |
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- | No log | 4.125 | 66 | 0.3373 | 0.8172 | 0.3373 |
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- | No log | 4.25 | 68 | 0.3211 | 0.8140 | 0.3211 |
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- | No log | 4.375 | 70 | 0.3426 | 0.8269 | 0.3426 |
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- | No log | 4.5 | 72 | 0.3901 | 0.8236 | 0.3901 |
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- | No log | 4.625 | 74 | 0.3966 | 0.8286 | 0.3966 |
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- | No log | 4.75 | 76 | 0.3865 | 0.8324 | 0.3865 |
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- | No log | 4.875 | 78 | 0.4241 | 0.8202 | 0.4241 |
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- | No log | 5.0 | 80 | 0.4385 | 0.8219 | 0.4385 |
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- | No log | 5.125 | 82 | 0.3778 | 0.8292 | 0.3778 |
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- | No log | 5.25 | 84 | 0.3614 | 0.8202 | 0.3614 |
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- | No log | 5.375 | 86 | 0.3526 | 0.8104 | 0.3526 |
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- | No log | 5.5 | 88 | 0.3321 | 0.8030 | 0.3321 |
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- | No log | 5.625 | 90 | 0.3304 | 0.8053 | 0.3304 |
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- | No log | 5.75 | 92 | 0.3951 | 0.8300 | 0.3951 |
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- | No log | 5.875 | 94 | 0.4136 | 0.8290 | 0.4136 |
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- | No log | 6.0 | 96 | 0.3632 | 0.8271 | 0.3632 |
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- | No log | 6.125 | 98 | 0.3475 | 0.8169 | 0.3475 |
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- | No log | 6.25 | 100 | 0.3496 | 0.8214 | 0.3496 |
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- | No log | 6.375 | 102 | 0.3335 | 0.8234 | 0.3335 |
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- | No log | 6.5 | 104 | 0.3458 | 0.8254 | 0.3458 |
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- | No log | 6.625 | 106 | 0.3502 | 0.8263 | 0.3502 |
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- | No log | 6.75 | 108 | 0.3362 | 0.8182 | 0.3362 |
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- | No log | 6.875 | 110 | 0.3599 | 0.8388 | 0.3599 |
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- | No log | 7.0 | 112 | 0.4336 | 0.8458 | 0.4336 |
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- | No log | 7.125 | 114 | 0.5158 | 0.8403 | 0.5158 |
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- | No log | 7.25 | 116 | 0.4762 | 0.8348 | 0.4762 |
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- | No log | 7.375 | 118 | 0.3764 | 0.8311 | 0.3764 |
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- | No log | 7.5 | 120 | 0.3240 | 0.7922 | 0.3240 |
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- | No log | 7.625 | 122 | 0.3223 | 0.7975 | 0.3223 |
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- | No log | 7.75 | 124 | 0.3420 | 0.8307 | 0.3420 |
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- | No log | 7.875 | 126 | 0.4217 | 0.8418 | 0.4217 |
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- | No log | 8.0 | 128 | 0.5511 | 0.8211 | 0.5511 |
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- | No log | 8.125 | 130 | 0.6089 | 0.8259 | 0.6089 |
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- | No log | 8.25 | 132 | 0.5762 | 0.8177 | 0.5762 |
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- | No log | 8.375 | 134 | 0.4857 | 0.8304 | 0.4857 |
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- | No log | 8.5 | 136 | 0.3859 | 0.8416 | 0.3859 |
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- | No log | 8.625 | 138 | 0.3411 | 0.8297 | 0.3411 |
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- | No log | 8.75 | 140 | 0.3342 | 0.8297 | 0.3342 |
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- | No log | 8.875 | 142 | 0.3479 | 0.8274 | 0.3479 |
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- | No log | 9.0 | 144 | 0.3703 | 0.8408 | 0.3703 |
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- | No log | 9.125 | 146 | 0.3868 | 0.8480 | 0.3868 |
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- | No log | 9.25 | 148 | 0.3835 | 0.8520 | 0.3835 |
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- | No log | 9.375 | 150 | 0.3675 | 0.8384 | 0.3675 |
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- | No log | 9.5 | 152 | 0.3528 | 0.8250 | 0.3528 |
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- | No log | 9.625 | 154 | 0.3467 | 0.8274 | 0.3467 |
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- | No log | 9.75 | 156 | 0.3454 | 0.8274 | 0.3454 |
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- | No log | 9.875 | 158 | 0.3471 | 0.8274 | 0.3471 |
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- | No log | 10.0 | 160 | 0.3485 | 0.8274 | 0.3485 |
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_vocabulary_task1_fold5
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_fold5
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: 0.2973
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+ - Qwk: 0.8562
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+ - Mse: 0.2979
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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 | 1.8520 | 0.1480 | 1.8511 |
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+ | No log | 0.2667 | 4 | 1.0651 | 0.3341 | 1.0655 |
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+ | No log | 0.4 | 6 | 1.1438 | 0.4927 | 1.1443 |
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+ | No log | 0.5333 | 8 | 0.9722 | 0.6250 | 0.9725 |
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+ | No log | 0.6667 | 10 | 0.6730 | 0.6107 | 0.6733 |
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+ | No log | 0.8 | 12 | 0.5341 | 0.7630 | 0.5344 |
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+ | No log | 0.9333 | 14 | 0.4706 | 0.8016 | 0.4708 |
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+ | No log | 1.0667 | 16 | 0.4255 | 0.8194 | 0.4256 |
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+ | No log | 1.2 | 18 | 0.4901 | 0.8387 | 0.4901 |
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+ | No log | 1.3333 | 20 | 0.4642 | 0.8545 | 0.4642 |
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+ | No log | 1.4667 | 22 | 0.3781 | 0.8345 | 0.3782 |
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+ | No log | 1.6 | 24 | 0.3229 | 0.8175 | 0.3231 |
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+ | No log | 1.7333 | 26 | 0.3530 | 0.8366 | 0.3532 |
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+ | No log | 1.8667 | 28 | 0.4548 | 0.8719 | 0.4547 |
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+ | No log | 2.0 | 30 | 0.6182 | 0.8633 | 0.6181 |
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+ | No log | 2.1333 | 32 | 0.5731 | 0.8699 | 0.5733 |
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+ | No log | 2.2667 | 34 | 0.3622 | 0.8422 | 0.3626 |
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+ | No log | 2.4 | 36 | 0.2913 | 0.8430 | 0.2916 |
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+ | No log | 2.5333 | 38 | 0.2887 | 0.8426 | 0.2890 |
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+ | No log | 2.6667 | 40 | 0.2802 | 0.8370 | 0.2805 |
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+ | No log | 2.8 | 42 | 0.3048 | 0.8363 | 0.3050 |
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+ | No log | 2.9333 | 44 | 0.3487 | 0.8575 | 0.3490 |
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+ | No log | 3.0667 | 46 | 0.3168 | 0.8493 | 0.3171 |
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+ | No log | 3.2 | 48 | 0.2820 | 0.8372 | 0.2823 |
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+ | No log | 3.3333 | 50 | 0.3036 | 0.8603 | 0.3040 |
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+ | No log | 3.4667 | 52 | 0.3945 | 0.8659 | 0.3949 |
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+ | No log | 3.6 | 54 | 0.3717 | 0.8677 | 0.3721 |
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+ | No log | 3.7333 | 56 | 0.2969 | 0.8614 | 0.2973 |
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+ | No log | 3.8667 | 58 | 0.2569 | 0.8385 | 0.2572 |
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+ | No log | 4.0 | 60 | 0.2971 | 0.7270 | 0.2975 |
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+ | No log | 4.1333 | 62 | 0.3312 | 0.6927 | 0.3316 |
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+ | No log | 4.2667 | 64 | 0.2800 | 0.7702 | 0.2804 |
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+ | No log | 4.4 | 66 | 0.2896 | 0.8502 | 0.2900 |
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+ | No log | 4.5333 | 68 | 0.4169 | 0.8694 | 0.4173 |
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+ | No log | 4.6667 | 70 | 0.4616 | 0.8813 | 0.4620 |
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+ | No log | 4.8 | 72 | 0.3663 | 0.8659 | 0.3668 |
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+ | No log | 4.9333 | 74 | 0.2765 | 0.8520 | 0.2769 |
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+ | No log | 5.0667 | 76 | 0.3059 | 0.7201 | 0.3063 |
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+ | No log | 5.2 | 78 | 0.3256 | 0.6901 | 0.3260 |
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+ | No log | 5.3333 | 80 | 0.2884 | 0.7612 | 0.2888 |
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+ | No log | 5.4667 | 82 | 0.2705 | 0.8362 | 0.2710 |
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+ | No log | 5.6 | 84 | 0.3435 | 0.8601 | 0.3440 |
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+ | No log | 5.7333 | 86 | 0.4426 | 0.8795 | 0.4430 |
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+ | No log | 5.8667 | 88 | 0.4328 | 0.8789 | 0.4333 |
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+ | No log | 6.0 | 90 | 0.3734 | 0.8717 | 0.3738 |
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+ | No log | 6.1333 | 92 | 0.3017 | 0.8603 | 0.3022 |
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+ | No log | 6.2667 | 94 | 0.2650 | 0.8366 | 0.2655 |
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+ | No log | 6.4 | 96 | 0.2634 | 0.8175 | 0.2639 |
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+ | No log | 6.5333 | 98 | 0.2676 | 0.8404 | 0.2681 |
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+ | No log | 6.6667 | 100 | 0.2966 | 0.8607 | 0.2972 |
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+ | No log | 6.8 | 102 | 0.3292 | 0.8611 | 0.3297 |
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+ | No log | 6.9333 | 104 | 0.3536 | 0.8685 | 0.3541 |
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+ | No log | 7.0667 | 106 | 0.3466 | 0.8685 | 0.3470 |
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+ | No log | 7.2 | 108 | 0.3070 | 0.8599 | 0.3075 |
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+ | No log | 7.3333 | 110 | 0.2886 | 0.8636 | 0.2891 |
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+ | No log | 7.4667 | 112 | 0.2905 | 0.8636 | 0.2910 |
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+ | No log | 7.6 | 114 | 0.2879 | 0.8636 | 0.2884 |
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+ | No log | 7.7333 | 116 | 0.2898 | 0.8633 | 0.2904 |
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+ | No log | 7.8667 | 118 | 0.2981 | 0.8587 | 0.2987 |
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+ | No log | 8.0 | 120 | 0.2958 | 0.8593 | 0.2963 |
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+ | No log | 8.1333 | 122 | 0.3001 | 0.8607 | 0.3006 |
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+ | No log | 8.2667 | 124 | 0.2931 | 0.8606 | 0.2936 |
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+ | No log | 8.4 | 126 | 0.2793 | 0.8630 | 0.2798 |
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+ | No log | 8.5333 | 128 | 0.2685 | 0.8532 | 0.2690 |
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+ | No log | 8.6667 | 130 | 0.2691 | 0.8518 | 0.2696 |
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+ | No log | 8.8 | 132 | 0.2769 | 0.8571 | 0.2775 |
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+ | No log | 8.9333 | 134 | 0.2923 | 0.8575 | 0.2929 |
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+ | No log | 9.0667 | 136 | 0.3156 | 0.8576 | 0.3161 |
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+ | No log | 9.2 | 138 | 0.3326 | 0.8643 | 0.3332 |
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+ | No log | 9.3333 | 140 | 0.3349 | 0.8643 | 0.3355 |
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+ | No log | 9.4667 | 142 | 0.3280 | 0.8657 | 0.3286 |
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+ | No log | 9.6 | 144 | 0.3162 | 0.8599 | 0.3168 |
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+ | No log | 9.7333 | 146 | 0.3062 | 0.8582 | 0.3068 |
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+ | No log | 9.8667 | 148 | 0.2995 | 0.8549 | 0.3001 |
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+ | No log | 10.0 | 150 | 0.2973 | 0.8562 | 0.2979 |
 
 
 
 
 
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  ### Framework versions