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--- |
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library_name: transformers |
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base_model: aubmindlab/bert-base-arabertv02-twitter |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: Model4_withclasess-arabertv2_base_T2_WS_A100v2_F1__BL |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/so/Model4-with-add-clasess-T1-ArabertTv2-Bas-WS-A100-BL/runs/o8owefo8) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/so/Model4-with-add-clasess-T1-ArabertTv2-Bas-WS-A100-BL/runs/o8owefo8) |
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# Model4_withclasess-arabertv2_base_T2_WS_A100v2_F1__BL |
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This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-base-arabertv02-twitter) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0770 |
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- F1-micro: 0.8282 |
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- Roc Auc: 0.9072 |
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- Accuracy: 0.7912 |
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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: 5e-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: Use OptimizerNames.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 | F1-micro | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------:|:--------:| |
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| 0.1028 | 1.0 | 507 | 0.0644 | 0.7904 | 0.8639 | 0.7297 | |
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| 0.0476 | 2.0 | 1014 | 0.0556 | 0.8143 | 0.8828 | 0.7668 | |
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| 0.0308 | 3.0 | 1521 | 0.0570 | 0.8200 | 0.8929 | 0.7758 | |
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| 0.0206 | 4.0 | 2028 | 0.0624 | 0.8179 | 0.8979 | 0.7828 | |
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| 0.0134 | 5.0 | 2535 | 0.0696 | 0.8183 | 0.9016 | 0.7856 | |
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| 0.0097 | 6.0 | 3042 | 0.0743 | 0.8226 | 0.9052 | 0.7898 | |
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| 0.0077 | 7.0 | 3549 | 0.0779 | 0.8166 | 0.9039 | 0.7793 | |
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| 0.0054 | 8.0 | 4056 | 0.0809 | 0.8249 | 0.9063 | 0.7905 | |
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| 0.0045 | 9.0 | 4563 | 0.0770 | 0.8282 | 0.9072 | 0.7912 | |
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| 0.0036 | 10.0 | 5070 | 0.0812 | 0.8228 | 0.9049 | 0.7849 | |
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| 0.003 | 11.0 | 5577 | 0.0874 | 0.8250 | 0.9072 | 0.7919 | |
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| 0.0025 | 12.0 | 6084 | 0.0886 | 0.8258 | 0.9067 | 0.7863 | |
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### Framework versions |
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- Transformers 4.48.2 |
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- Pytorch 2.5.1+cu124 |
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- Tokenizers 0.21.0 |
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