| | --- |
| | library_name: transformers |
| | base_model: SI2M-Lab/DarijaBERT |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: offres_classification_bert_v1 |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # offres_classification_bert_v1 |
| | |
| | This model is a fine-tuned version of [SI2M-Lab/DarijaBERT](https://huggingface.co/SI2M-Lab/DarijaBERT) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0010 |
| | |
| | ## Model description |
| | |
| | More information needed |
| | |
| | ## Intended uses & limitations |
| | |
| | More information needed |
| | |
| | ## Training and evaluation data |
| | |
| | More information needed |
| | |
| | ## Training procedure |
| | |
| | ### Training hyperparameters |
| | |
| | The following hyperparameters were used during training: |
| | - learning_rate: 2e-05 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | No log | 1.0 | 135 | 0.0265 | |
| | | No log | 2.0 | 270 | 0.0045 | |
| | | No log | 3.0 | 405 | 0.0063 | |
| | | 0.1371 | 4.0 | 540 | 0.0023 | |
| | | 0.1371 | 5.0 | 675 | 0.0030 | |
| | | 0.1371 | 6.0 | 810 | 0.0020 | |
| | | 0.1371 | 7.0 | 945 | 0.0013 | |
| | | 0.0009 | 8.0 | 1080 | 0.0011 | |
| | | 0.0009 | 9.0 | 1215 | 0.0010 | |
| | | 0.0009 | 10.0 | 1350 | 0.0010 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.48.3 |
| | - Pytorch 2.5.1+cu124 |
| | - Datasets 2.21.0 |
| | - Tokenizers 0.21.0 |
| | |
