question-detection-it-20260119
This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1114
- Accuracy: 0.9798
- F1: 0.9798
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 OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4592 | 1.0 | 148 | 0.1517 | 0.9562 | 0.9562 |
| 0.0588 | 2.0 | 296 | 0.1934 | 0.9630 | 0.9629 |
| 0.0345 | 3.0 | 444 | 0.2038 | 0.9596 | 0.9596 |
| 0.0382 | 4.0 | 592 | 0.1114 | 0.9798 | 0.9798 |
| 0.0005 | 5.0 | 740 | 0.1290 | 0.9697 | 0.9697 |
| 0.0004 | 6.0 | 888 | 0.1305 | 0.9697 | 0.9697 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
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