question_classification
This model is a fine-tuned version of SI2M-Lab/DarijaBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0124
- Accuracy: 0.9980
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 246 | 0.0347 | 0.9878 |
| No log | 2.0 | 492 | 0.0305 | 0.9939 |
| 0.0995 | 3.0 | 738 | 0.0414 | 0.9939 |
| 0.0995 | 4.0 | 984 | 0.0274 | 0.9939 |
| 0.0052 | 5.0 | 1230 | 0.0124 | 0.9980 |
| 0.0052 | 6.0 | 1476 | 0.0125 | 0.9980 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.0
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Base model
SI2M-Lab/DarijaBERT