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arabert_cross_organization_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_organization_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_organization_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: 0.4588
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- - Qwk: 0.6885
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- - Mse: 0.4588
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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 | 3.0429 | 0.0044 | 3.0429 |
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- | No log | 0.25 | 4 | 1.6578 | 0.1373 | 1.6578 |
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- | No log | 0.375 | 6 | 0.9445 | 0.3393 | 0.9445 |
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- | No log | 0.5 | 8 | 0.7446 | 0.4700 | 0.7446 |
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- | No log | 0.625 | 10 | 0.8109 | 0.4239 | 0.8109 |
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- | No log | 0.75 | 12 | 0.5652 | 0.6068 | 0.5652 |
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- | No log | 0.875 | 14 | 0.6877 | 0.6129 | 0.6877 |
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- | No log | 1.0 | 16 | 0.5401 | 0.6022 | 0.5401 |
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- | No log | 1.125 | 18 | 0.5571 | 0.5613 | 0.5571 |
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- | No log | 1.25 | 20 | 0.4854 | 0.6440 | 0.4854 |
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- | No log | 1.375 | 22 | 0.5443 | 0.7366 | 0.5443 |
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- | No log | 1.5 | 24 | 0.5077 | 0.7444 | 0.5077 |
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- | No log | 1.625 | 26 | 0.5015 | 0.6266 | 0.5015 |
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- | No log | 1.75 | 28 | 0.5012 | 0.6164 | 0.5012 |
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- | No log | 1.875 | 30 | 0.4504 | 0.7043 | 0.4504 |
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- | No log | 2.0 | 32 | 0.4864 | 0.7187 | 0.4864 |
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- | No log | 2.125 | 34 | 0.4305 | 0.7243 | 0.4305 |
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- | No log | 2.25 | 36 | 0.4572 | 0.6579 | 0.4572 |
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- | No log | 2.375 | 38 | 0.4545 | 0.7032 | 0.4545 |
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- | No log | 2.5 | 40 | 0.4159 | 0.7123 | 0.4159 |
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- | No log | 2.625 | 42 | 0.4122 | 0.7591 | 0.4122 |
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- | No log | 2.75 | 44 | 0.4424 | 0.7617 | 0.4424 |
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- | No log | 2.875 | 46 | 0.4110 | 0.7600 | 0.4110 |
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- | No log | 3.0 | 48 | 0.3993 | 0.7372 | 0.3993 |
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- | No log | 3.125 | 50 | 0.3990 | 0.7391 | 0.3990 |
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- | No log | 3.25 | 52 | 0.3923 | 0.7306 | 0.3923 |
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- | No log | 3.375 | 54 | 0.4375 | 0.7685 | 0.4375 |
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- | No log | 3.5 | 56 | 0.4628 | 0.7698 | 0.4628 |
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- | No log | 3.625 | 58 | 0.4089 | 0.7365 | 0.4089 |
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- | No log | 3.75 | 60 | 0.4113 | 0.7238 | 0.4113 |
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- | No log | 3.875 | 62 | 0.4117 | 0.7308 | 0.4117 |
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- | No log | 4.0 | 64 | 0.4183 | 0.7175 | 0.4183 |
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- | No log | 4.125 | 66 | 0.4326 | 0.7175 | 0.4326 |
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- | No log | 4.25 | 68 | 0.4439 | 0.7360 | 0.4439 |
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- | No log | 4.375 | 70 | 0.4530 | 0.7375 | 0.4530 |
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- | No log | 4.5 | 72 | 0.4458 | 0.7040 | 0.4458 |
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- | No log | 4.625 | 74 | 0.4431 | 0.7054 | 0.4431 |
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- | No log | 4.75 | 76 | 0.4403 | 0.6980 | 0.4403 |
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- | No log | 4.875 | 78 | 0.4350 | 0.7144 | 0.4350 |
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- | No log | 5.0 | 80 | 0.4311 | 0.7511 | 0.4311 |
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- | No log | 5.125 | 82 | 0.4257 | 0.7418 | 0.4257 |
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- | No log | 5.25 | 84 | 0.4298 | 0.7174 | 0.4298 |
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- | No log | 5.375 | 86 | 0.4420 | 0.6877 | 0.4420 |
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- | No log | 5.5 | 88 | 0.4344 | 0.7174 | 0.4344 |
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- | No log | 5.625 | 90 | 0.4324 | 0.7146 | 0.4324 |
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- | No log | 5.75 | 92 | 0.4363 | 0.7566 | 0.4363 |
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- | No log | 5.875 | 94 | 0.4499 | 0.7689 | 0.4499 |
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- | No log | 6.0 | 96 | 0.4217 | 0.7367 | 0.4217 |
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- | No log | 6.125 | 98 | 0.4252 | 0.7237 | 0.4252 |
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- | No log | 6.25 | 100 | 0.4235 | 0.7141 | 0.4235 |
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- | No log | 6.375 | 102 | 0.4211 | 0.7230 | 0.4211 |
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- | No log | 6.5 | 104 | 0.4285 | 0.7493 | 0.4285 |
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- | No log | 6.625 | 106 | 0.4367 | 0.7530 | 0.4367 |
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- | No log | 6.75 | 108 | 0.4214 | 0.7457 | 0.4214 |
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- | No log | 6.875 | 110 | 0.4380 | 0.6930 | 0.4380 |
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- | No log | 7.0 | 112 | 0.4555 | 0.6727 | 0.4555 |
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- | No log | 7.125 | 114 | 0.4358 | 0.6947 | 0.4358 |
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- | No log | 7.25 | 116 | 0.4270 | 0.7277 | 0.4270 |
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- | No log | 7.375 | 118 | 0.4349 | 0.7457 | 0.4349 |
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- | No log | 7.5 | 120 | 0.4430 | 0.7382 | 0.4430 |
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- | No log | 7.625 | 122 | 0.4539 | 0.7257 | 0.4539 |
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- | No log | 7.75 | 124 | 0.4623 | 0.7204 | 0.4623 |
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- | No log | 7.875 | 126 | 0.4640 | 0.7110 | 0.4640 |
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- | No log | 8.0 | 128 | 0.4644 | 0.7115 | 0.4644 |
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- | No log | 8.125 | 130 | 0.4639 | 0.7095 | 0.4639 |
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- | No log | 8.25 | 132 | 0.4612 | 0.7073 | 0.4612 |
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- | No log | 8.375 | 134 | 0.4652 | 0.6865 | 0.4652 |
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- | No log | 8.5 | 136 | 0.4689 | 0.6753 | 0.4689 |
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- | No log | 8.625 | 138 | 0.4608 | 0.6849 | 0.4608 |
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- | No log | 8.75 | 140 | 0.4553 | 0.6907 | 0.4553 |
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- | No log | 8.875 | 142 | 0.4538 | 0.6930 | 0.4538 |
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- | No log | 9.0 | 144 | 0.4537 | 0.7172 | 0.4537 |
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- | No log | 9.125 | 146 | 0.4564 | 0.7273 | 0.4564 |
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- | No log | 9.25 | 148 | 0.4582 | 0.7294 | 0.4582 |
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- | No log | 9.375 | 150 | 0.4572 | 0.7267 | 0.4572 |
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- | No log | 9.5 | 152 | 0.4559 | 0.7093 | 0.4559 |
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- | No log | 9.625 | 154 | 0.4566 | 0.7000 | 0.4566 |
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- | No log | 9.75 | 156 | 0.4582 | 0.6885 | 0.4582 |
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- | No log | 9.875 | 158 | 0.4588 | 0.6885 | 0.4588 |
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- | No log | 10.0 | 160 | 0.4588 | 0.6885 | 0.4588 |
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_organization_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_organization_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: 0.4714
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+ - Qwk: 0.7597
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+ - Mse: 0.4723
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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 | 1.3842 | 0.1724 | 1.3839 |
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+ | No log | 0.2667 | 4 | 0.9780 | 0.3534 | 0.9789 |
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+ | No log | 0.4 | 6 | 1.4683 | 0.4626 | 1.4695 |
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+ | No log | 0.5333 | 8 | 1.2844 | 0.5615 | 1.2856 |
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+ | No log | 0.6667 | 10 | 0.8166 | 0.5501 | 0.8177 |
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+ | No log | 0.8 | 12 | 0.6646 | 0.5615 | 0.6656 |
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+ | No log | 0.9333 | 14 | 0.6181 | 0.6308 | 0.6192 |
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+ | No log | 1.0667 | 16 | 0.6395 | 0.7598 | 0.6406 |
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+ | No log | 1.2 | 18 | 0.5961 | 0.7503 | 0.5973 |
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+ | No log | 1.3333 | 20 | 0.5222 | 0.7439 | 0.5233 |
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+ | No log | 1.4667 | 22 | 0.5709 | 0.7564 | 0.5721 |
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+ | No log | 1.6 | 24 | 0.5337 | 0.7493 | 0.5348 |
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+ | No log | 1.7333 | 26 | 0.5381 | 0.7745 | 0.5392 |
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+ | No log | 1.8667 | 28 | 0.5385 | 0.7823 | 0.5395 |
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+ | No log | 2.0 | 30 | 0.5204 | 0.7694 | 0.5215 |
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+ | No log | 2.1333 | 32 | 0.5481 | 0.7727 | 0.5492 |
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+ | No log | 2.2667 | 34 | 0.4767 | 0.7478 | 0.4777 |
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+ | No log | 2.4 | 36 | 0.4552 | 0.7226 | 0.4561 |
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+ | No log | 2.5333 | 38 | 0.4590 | 0.7366 | 0.4599 |
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+ | No log | 2.6667 | 40 | 0.4443 | 0.7177 | 0.4451 |
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+ | No log | 2.8 | 42 | 0.4514 | 0.7415 | 0.4522 |
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+ | No log | 2.9333 | 44 | 0.5579 | 0.8045 | 0.5590 |
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+ | No log | 3.0667 | 46 | 0.7664 | 0.7863 | 0.7678 |
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+ | No log | 3.2 | 48 | 0.6906 | 0.7958 | 0.6919 |
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+ | No log | 3.3333 | 50 | 0.4951 | 0.7710 | 0.4961 |
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+ | No log | 3.4667 | 52 | 0.4583 | 0.7404 | 0.4591 |
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+ | No log | 3.6 | 54 | 0.4705 | 0.7615 | 0.4715 |
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+ | No log | 3.7333 | 56 | 0.4873 | 0.7626 | 0.4884 |
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+ | No log | 3.8667 | 58 | 0.4498 | 0.7546 | 0.4507 |
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+ | No log | 4.0 | 60 | 0.4307 | 0.7203 | 0.4315 |
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+ | No log | 4.1333 | 62 | 0.4439 | 0.7456 | 0.4449 |
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+ | No log | 4.2667 | 64 | 0.4697 | 0.7618 | 0.4707 |
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+ | No log | 4.4 | 66 | 0.4679 | 0.7644 | 0.4689 |
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+ | No log | 4.5333 | 68 | 0.4351 | 0.7431 | 0.4359 |
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+ | No log | 4.6667 | 70 | 0.4379 | 0.7504 | 0.4388 |
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+ | No log | 4.8 | 72 | 0.4599 | 0.7566 | 0.4608 |
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+ | No log | 4.9333 | 74 | 0.4597 | 0.7542 | 0.4606 |
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+ | No log | 5.0667 | 76 | 0.4453 | 0.7436 | 0.4462 |
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+ | No log | 5.2 | 78 | 0.4534 | 0.7462 | 0.4543 |
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+ | No log | 5.3333 | 80 | 0.4416 | 0.7345 | 0.4424 |
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+ | No log | 5.4667 | 82 | 0.4467 | 0.7332 | 0.4475 |
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+ | No log | 5.6 | 84 | 0.4936 | 0.7561 | 0.4946 |
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+ | No log | 5.7333 | 86 | 0.5611 | 0.7947 | 0.5622 |
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+ | No log | 5.8667 | 88 | 0.5154 | 0.7747 | 0.5164 |
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+ | No log | 6.0 | 90 | 0.4950 | 0.7700 | 0.4960 |
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+ | No log | 6.1333 | 92 | 0.4817 | 0.7588 | 0.4827 |
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+ | No log | 6.2667 | 94 | 0.4527 | 0.7499 | 0.4536 |
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+ | No log | 6.4 | 96 | 0.4380 | 0.7228 | 0.4388 |
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+ | No log | 6.5333 | 98 | 0.4383 | 0.7248 | 0.4391 |
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+ | No log | 6.6667 | 100 | 0.4494 | 0.7409 | 0.4502 |
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+ | No log | 6.8 | 102 | 0.4509 | 0.7297 | 0.4518 |
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+ | No log | 6.9333 | 104 | 0.4765 | 0.7516 | 0.4775 |
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+ | No log | 7.0667 | 106 | 0.4854 | 0.7631 | 0.4864 |
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+ | No log | 7.2 | 108 | 0.4991 | 0.7766 | 0.5001 |
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+ | No log | 7.3333 | 110 | 0.5297 | 0.7654 | 0.5308 |
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+ | No log | 7.4667 | 112 | 0.5591 | 0.7862 | 0.5603 |
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+ | No log | 7.6 | 114 | 0.5193 | 0.7711 | 0.5204 |
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+ | No log | 7.7333 | 116 | 0.4710 | 0.7587 | 0.4719 |
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+ | No log | 7.8667 | 118 | 0.4527 | 0.7448 | 0.4536 |
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+ | No log | 8.0 | 120 | 0.4573 | 0.7500 | 0.4582 |
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+ | No log | 8.1333 | 122 | 0.4652 | 0.7567 | 0.4661 |
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+ | No log | 8.2667 | 124 | 0.4728 | 0.7600 | 0.4738 |
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+ | No log | 8.4 | 126 | 0.4700 | 0.7563 | 0.4709 |
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+ | No log | 8.5333 | 128 | 0.4667 | 0.7515 | 0.4677 |
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+ | No log | 8.6667 | 130 | 0.4712 | 0.7538 | 0.4722 |
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+ | No log | 8.8 | 132 | 0.4748 | 0.7555 | 0.4757 |
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+ | No log | 8.9333 | 134 | 0.4694 | 0.7533 | 0.4703 |
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+ | No log | 9.0667 | 136 | 0.4637 | 0.7429 | 0.4646 |
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+ | No log | 9.2 | 138 | 0.4616 | 0.7432 | 0.4625 |
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+ | No log | 9.3333 | 140 | 0.4664 | 0.7454 | 0.4673 |
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+ | No log | 9.4667 | 142 | 0.4737 | 0.7588 | 0.4746 |
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+ | No log | 9.6 | 144 | 0.4748 | 0.7567 | 0.4757 |
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+ | No log | 9.7333 | 146 | 0.4743 | 0.7586 | 0.4752 |
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+ | No log | 9.8667 | 148 | 0.4718 | 0.7597 | 0.4727 |
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+ | No log | 10.0 | 150 | 0.4714 | 0.7597 | 0.4723 |
 
 
 
 
 
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  ### Framework versions