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--- |
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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_fold6 |
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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_fold6 |
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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: 0.6885 |
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- Qwk: 0.4652 |
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- Mse: 0.6865 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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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 | 2.5610 | 0.0172 | 2.5631 | |
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| No log | 0.2667 | 4 | 1.3092 | 0.0773 | 1.3077 | |
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| No log | 0.4 | 6 | 0.6287 | 0.4047 | 0.6286 | |
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| No log | 0.5333 | 8 | 0.7953 | 0.4436 | 0.7955 | |
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| No log | 0.6667 | 10 | 0.6050 | 0.3695 | 0.6046 | |
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| No log | 0.8 | 12 | 0.5414 | 0.3312 | 0.5412 | |
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| No log | 0.9333 | 14 | 0.3774 | 0.5165 | 0.3781 | |
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| No log | 1.0667 | 16 | 0.3713 | 0.5340 | 0.3720 | |
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| No log | 1.2 | 18 | 0.3244 | 0.5756 | 0.3250 | |
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| No log | 1.3333 | 20 | 0.3167 | 0.6313 | 0.3171 | |
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| No log | 1.4667 | 22 | 0.3711 | 0.6258 | 0.3708 | |
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| No log | 1.6 | 24 | 0.3620 | 0.6705 | 0.3621 | |
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| No log | 1.7333 | 26 | 0.3546 | 0.6894 | 0.3547 | |
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| No log | 1.8667 | 28 | 0.3904 | 0.5542 | 0.3900 | |
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| No log | 2.0 | 30 | 0.4427 | 0.4960 | 0.4420 | |
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| No log | 2.1333 | 32 | 0.4085 | 0.5287 | 0.4081 | |
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| No log | 2.2667 | 34 | 0.3250 | 0.6490 | 0.3251 | |
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| No log | 2.4 | 36 | 0.3625 | 0.7352 | 0.3630 | |
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| No log | 2.5333 | 38 | 0.3719 | 0.7111 | 0.3719 | |
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| No log | 2.6667 | 40 | 0.4472 | 0.5221 | 0.4462 | |
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| No log | 2.8 | 42 | 0.5148 | 0.4902 | 0.5136 | |
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| No log | 2.9333 | 44 | 0.4050 | 0.5405 | 0.4043 | |
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| No log | 3.0667 | 46 | 0.3378 | 0.6397 | 0.3376 | |
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| No log | 3.2 | 48 | 0.3496 | 0.5949 | 0.3493 | |
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| No log | 3.3333 | 50 | 0.3447 | 0.6021 | 0.3444 | |
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| No log | 3.4667 | 52 | 0.3460 | 0.5885 | 0.3457 | |
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| No log | 3.6 | 54 | 0.3308 | 0.6420 | 0.3306 | |
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| No log | 3.7333 | 56 | 0.3377 | 0.6102 | 0.3374 | |
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| No log | 3.8667 | 58 | 0.3579 | 0.5907 | 0.3575 | |
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| No log | 4.0 | 60 | 0.3816 | 0.5790 | 0.3810 | |
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| No log | 4.1333 | 62 | 0.4251 | 0.5479 | 0.4242 | |
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| No log | 4.2667 | 64 | 0.4317 | 0.5444 | 0.4308 | |
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| No log | 4.4 | 66 | 0.5698 | 0.4745 | 0.5684 | |
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| No log | 4.5333 | 68 | 0.5338 | 0.4833 | 0.5325 | |
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| No log | 4.6667 | 70 | 0.4617 | 0.5347 | 0.4607 | |
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| No log | 4.8 | 72 | 0.4937 | 0.4804 | 0.4925 | |
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| No log | 4.9333 | 74 | 0.5167 | 0.4702 | 0.5156 | |
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| No log | 5.0667 | 76 | 0.4987 | 0.4743 | 0.4977 | |
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| No log | 5.2 | 78 | 0.5594 | 0.4792 | 0.5582 | |
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| No log | 5.3333 | 80 | 0.5679 | 0.4788 | 0.5667 | |
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| No log | 5.4667 | 82 | 0.5202 | 0.4874 | 0.5190 | |
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| No log | 5.6 | 84 | 0.5297 | 0.4891 | 0.5284 | |
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| No log | 5.7333 | 86 | 0.4835 | 0.4882 | 0.4825 | |
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| No log | 5.8667 | 88 | 0.5151 | 0.4891 | 0.5140 | |
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| No log | 6.0 | 90 | 0.6542 | 0.4666 | 0.6526 | |
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| No log | 6.1333 | 92 | 0.7260 | 0.4338 | 0.7242 | |
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| No log | 6.2667 | 94 | 0.5806 | 0.4788 | 0.5791 | |
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| No log | 6.4 | 96 | 0.4674 | 0.5006 | 0.4664 | |
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| No log | 6.5333 | 98 | 0.4558 | 0.5000 | 0.4549 | |
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| No log | 6.6667 | 100 | 0.5518 | 0.4839 | 0.5504 | |
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| No log | 6.8 | 102 | 0.6844 | 0.4344 | 0.6825 | |
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| No log | 6.9333 | 104 | 0.6391 | 0.4542 | 0.6374 | |
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| No log | 7.0667 | 106 | 0.5221 | 0.5072 | 0.5208 | |
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| No log | 7.2 | 108 | 0.5030 | 0.5053 | 0.5018 | |
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| No log | 7.3333 | 110 | 0.5677 | 0.4910 | 0.5661 | |
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| No log | 7.4667 | 112 | 0.6657 | 0.4587 | 0.6638 | |
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| No log | 7.6 | 114 | 0.6913 | 0.4396 | 0.6893 | |
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| No log | 7.7333 | 116 | 0.6322 | 0.4662 | 0.6303 | |
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| No log | 7.8667 | 118 | 0.5615 | 0.4847 | 0.5599 | |
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| No log | 8.0 | 120 | 0.5037 | 0.5192 | 0.5025 | |
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| No log | 8.1333 | 122 | 0.4986 | 0.5275 | 0.4974 | |
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| No log | 8.2667 | 124 | 0.5375 | 0.4975 | 0.5361 | |
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| No log | 8.4 | 126 | 0.6271 | 0.4694 | 0.6252 | |
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| No log | 8.5333 | 128 | 0.7181 | 0.4380 | 0.7160 | |
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| No log | 8.6667 | 130 | 0.7262 | 0.4320 | 0.7241 | |
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| No log | 8.8 | 132 | 0.6675 | 0.4566 | 0.6655 | |
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| No log | 8.9333 | 134 | 0.5875 | 0.4826 | 0.5859 | |
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| No log | 9.0667 | 136 | 0.5616 | 0.4930 | 0.5602 | |
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| No log | 9.2 | 138 | 0.5683 | 0.4914 | 0.5668 | |
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| No log | 9.3333 | 140 | 0.5908 | 0.4826 | 0.5892 | |
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| No log | 9.4667 | 142 | 0.6226 | 0.4814 | 0.6208 | |
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| No log | 9.6 | 144 | 0.6525 | 0.4656 | 0.6507 | |
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| No log | 9.7333 | 146 | 0.6742 | 0.4610 | 0.6723 | |
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| No log | 9.8667 | 148 | 0.6879 | 0.4652 | 0.6859 | |
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| No log | 10.0 | 150 | 0.6885 | 0.4652 | 0.6865 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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