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--- |
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library_name: peft |
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base_model: aubmindlab/bert-base-arabertv02 |
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tags: |
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- base_model:adapter:aubmindlab/bert-base-arabertv02 |
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- lora |
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- transformers |
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metrics: |
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- accuracy |
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model-index: |
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- name: bert-eou-classifier_teacher |
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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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# bert-eou-classifier_teacher |
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This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1555 |
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- Accuracy: 0.791 |
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- Auc: 0.865 |
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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: 0.0002 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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 | Accuracy | Auc | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-----:| |
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| 0.5875 | 1.0 | 622 | 0.4866 | 0.75 | 0.845 | |
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| 0.4703 | 2.0 | 1244 | 0.5337 | 0.76 | 0.855 | |
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| 0.4097 | 3.0 | 1866 | 0.5273 | 0.785 | 0.869 | |
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| 0.3598 | 4.0 | 2488 | 0.5383 | 0.795 | 0.868 | |
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| 0.3278 | 5.0 | 3110 | 0.6127 | 0.803 | 0.878 | |
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| 0.3019 | 6.0 | 3732 | 0.6487 | 0.804 | 0.878 | |
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| 0.2616 | 7.0 | 4354 | 0.7659 | 0.801 | 0.874 | |
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| 0.2451 | 8.0 | 4976 | 0.8012 | 0.793 | 0.871 | |
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| 0.2241 | 9.0 | 5598 | 0.8936 | 0.802 | 0.87 | |
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| 0.2044 | 10.0 | 6220 | 0.9513 | 0.8 | 0.869 | |
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| 0.2015 | 11.0 | 6842 | 0.9689 | 0.802 | 0.869 | |
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| 0.1834 | 12.0 | 7464 | 0.9756 | 0.799 | 0.869 | |
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| 0.1731 | 13.0 | 8086 | 0.9917 | 0.796 | 0.866 | |
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| 0.1455 | 14.0 | 8708 | 1.0958 | 0.794 | 0.863 | |
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| 0.1557 | 15.0 | 9330 | 1.0042 | 0.796 | 0.869 | |
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| 0.1316 | 16.0 | 9952 | 1.0996 | 0.796 | 0.865 | |
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| 0.1335 | 17.0 | 10574 | 1.2024 | 0.794 | 0.863 | |
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| 0.1201 | 18.0 | 11196 | 1.1508 | 0.791 | 0.865 | |
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| 0.1204 | 19.0 | 11818 | 1.1580 | 0.798 | 0.865 | |
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| 0.1137 | 20.0 | 12440 | 1.1555 | 0.791 | 0.865 | |
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### Framework versions |
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- PEFT 0.18.0 |
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- Transformers 4.57.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.22.1 |
