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--- |
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base_model: SI2M-Lab/DarijaBERT |
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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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- recall |
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model-index: |
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- name: results |
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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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# results |
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This model is a fine-tuned version of [SI2M-Lab/DarijaBERT](https://huggingface.co/SI2M-Lab/DarijaBERT) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5291 |
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- Macro F1: 0.7697 |
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- Accuracy: 0.8007 |
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- Recall: 0.7687 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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 | Macro F1 | Accuracy | Recall | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:------:| |
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| 0.6848 | 0.9877 | 40 | 0.6040 | 0.6869 | 0.7504 | 0.6821 | |
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| 0.5937 | 2.0 | 81 | 0.5376 | 0.7396 | 0.7799 | 0.7286 | |
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| 0.4946 | 2.9877 | 121 | 0.5313 | 0.7474 | 0.7816 | 0.7434 | |
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| 0.386 | 4.0 | 162 | 0.5291 | 0.7697 | 0.8007 | 0.7687 | |
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| 0.3114 | 4.9877 | 202 | 0.5690 | 0.7391 | 0.7782 | 0.7329 | |
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| 0.2477 | 6.0 | 243 | 0.5891 | 0.7480 | 0.7834 | 0.7441 | |
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| 0.1804 | 6.9877 | 283 | 0.6194 | 0.7422 | 0.7764 | 0.7366 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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