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--- |
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library_name: transformers |
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base_model: aubmindlab/bert-base-arabertv2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: arabert_armis_multitask_hard |
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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_armis_multitask_hard |
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This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7896 |
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- Disagreement Accuracy: 0.5035 |
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- Disagreement F1: 0.4167 |
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- Target Accuracy: 0.6525 |
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- Target F1: 0.6202 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Disagreement Accuracy | Disagreement F1 | Target Accuracy | Target F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------------------:|:---------------:|:---------------:|:---------:| |
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| 0.8457 | 1.0 | 21 | 0.8400 | 0.5390 | 0.4961 | 0.4610 | 0.5778 | |
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| 0.8372 | 2.0 | 42 | 0.8325 | 0.5461 | 0.4386 | 0.6241 | 0.5225 | |
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| 0.8341 | 3.0 | 63 | 0.8290 | 0.5532 | 0.4324 | 0.5390 | 0.5517 | |
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| 0.8153 | 4.0 | 84 | 0.8240 | 0.5532 | 0.496 | 0.5603 | 0.5634 | |
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| 0.809 | 5.0 | 105 | 0.8209 | 0.5319 | 0.3125 | 0.5816 | 0.5874 | |
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| 0.79 | 6.0 | 126 | 0.8150 | 0.5390 | 0.4882 | 0.6099 | 0.5669 | |
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| 0.7857 | 7.0 | 147 | 0.8119 | 0.5177 | 0.3462 | 0.6312 | 0.5806 | |
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| 0.7775 | 8.0 | 168 | 0.8090 | 0.5035 | 0.3137 | 0.6099 | 0.5926 | |
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| 0.7763 | 9.0 | 189 | 0.8041 | 0.5106 | 0.448 | 0.6383 | 0.5984 | |
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| 0.7685 | 10.0 | 210 | 0.8015 | 0.5106 | 0.3670 | 0.6454 | 0.6094 | |
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| 0.7652 | 11.0 | 231 | 0.7990 | 0.5035 | 0.4262 | 0.6383 | 0.6165 | |
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| 0.7597 | 12.0 | 252 | 0.7979 | 0.5106 | 0.4651 | 0.6241 | 0.6074 | |
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| 0.753 | 13.0 | 273 | 0.7955 | 0.4894 | 0.4286 | 0.6454 | 0.6212 | |
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| 0.7475 | 14.0 | 294 | 0.7930 | 0.5035 | 0.4167 | 0.6596 | 0.6190 | |
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| 0.7465 | 15.0 | 315 | 0.7923 | 0.4965 | 0.4132 | 0.6525 | 0.6202 | |
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| 0.7425 | 16.0 | 336 | 0.7914 | 0.5035 | 0.4167 | 0.6454 | 0.6032 | |
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| 0.7407 | 17.0 | 357 | 0.7905 | 0.4965 | 0.4132 | 0.6525 | 0.6202 | |
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| 0.7397 | 18.0 | 378 | 0.7901 | 0.5248 | 0.4174 | 0.6525 | 0.6202 | |
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| 0.7362 | 19.0 | 399 | 0.7897 | 0.5035 | 0.4167 | 0.6525 | 0.6202 | |
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| 0.7358 | 20.0 | 420 | 0.7896 | 0.5035 | 0.4167 | 0.6525 | 0.6202 | |
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### Framework versions |
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- Transformers 4.57.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 4.3.0 |
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- Tokenizers 0.22.1 |
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