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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_vocabulary_task5_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_vocabulary_task5_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: 0.3339 |
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- Qwk: 0.8270 |
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- Mse: 0.3339 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 1 |
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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 | 0.0351 | 2 | 3.7424 | 0.0021 | 3.7424 | |
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| No log | 0.0702 | 4 | 1.7368 | 0.2488 | 1.7368 | |
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| No log | 0.1053 | 6 | 0.8992 | 0.2497 | 0.8992 | |
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| No log | 0.1404 | 8 | 0.7327 | 0.6064 | 0.7327 | |
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| No log | 0.1754 | 10 | 0.8042 | 0.5559 | 0.8042 | |
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| No log | 0.2105 | 12 | 0.9939 | 0.6771 | 0.9939 | |
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| No log | 0.2456 | 14 | 0.9616 | 0.6986 | 0.9616 | |
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| No log | 0.2807 | 16 | 0.8004 | 0.6308 | 0.8004 | |
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| No log | 0.3158 | 18 | 0.6373 | 0.6016 | 0.6373 | |
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| No log | 0.3509 | 20 | 0.6361 | 0.6470 | 0.6361 | |
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| No log | 0.3860 | 22 | 0.5967 | 0.7168 | 0.5967 | |
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| No log | 0.4211 | 24 | 0.4872 | 0.7622 | 0.4872 | |
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| No log | 0.4561 | 26 | 0.4462 | 0.7864 | 0.4462 | |
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| No log | 0.4912 | 28 | 0.4171 | 0.8029 | 0.4171 | |
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| No log | 0.5263 | 30 | 0.3844 | 0.8207 | 0.3844 | |
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| No log | 0.5614 | 32 | 0.4099 | 0.8533 | 0.4099 | |
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| No log | 0.5965 | 34 | 0.4527 | 0.8592 | 0.4527 | |
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| No log | 0.6316 | 36 | 0.4782 | 0.8573 | 0.4782 | |
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| No log | 0.6667 | 38 | 0.4629 | 0.8620 | 0.4629 | |
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| No log | 0.7018 | 40 | 0.3818 | 0.8464 | 0.3818 | |
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| No log | 0.7368 | 42 | 0.3245 | 0.8055 | 0.3245 | |
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| No log | 0.7719 | 44 | 0.3187 | 0.7617 | 0.3187 | |
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| No log | 0.8070 | 46 | 0.3176 | 0.7494 | 0.3176 | |
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| No log | 0.8421 | 48 | 0.3184 | 0.7414 | 0.3184 | |
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| No log | 0.8772 | 50 | 0.3131 | 0.7715 | 0.3131 | |
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| No log | 0.9123 | 52 | 0.3167 | 0.8053 | 0.3167 | |
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| No log | 0.9474 | 54 | 0.3273 | 0.8208 | 0.3273 | |
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| No log | 0.9825 | 56 | 0.3339 | 0.8270 | 0.3339 | |
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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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