--- library_name: transformers base_model: SI2M-Lab/DarijaBERT tags: - generated_from_trainer model-index: - name: offres_classification_bert_v1 results: [] --- # 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: 0.0256 ## 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 | 132 | 0.0484 | | No log | 2.0 | 264 | 0.0225 | | No log | 3.0 | 396 | 0.0269 | | 0.1331 | 4.0 | 528 | 0.0217 | | 0.1331 | 5.0 | 660 | 0.0240 | | 0.1331 | 6.0 | 792 | 0.0248 | | 0.1331 | 7.0 | 924 | 0.0250 | | 0.0014 | 8.0 | 1056 | 0.0253 | | 0.0014 | 9.0 | 1188 | 0.0256 | | 0.0014 | 10.0 | 1320 | 0.0256 | ### Framework versions - Transformers 4.48.3 - Pytorch 2.5.1+cu124 - Datasets 2.21.0 - Tokenizers 0.21.0