question-detection-de-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: 0.1731
- Accuracy: 0.9664
- F1: 0.9664
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 |
|---|---|---|---|---|---|
| 0.2426 | 1.0 | 149 | 0.2434 | 0.9396 | 0.9396 |
| 0.1182 | 2.0 | 298 | 0.1731 | 0.9664 | 0.9664 |
| 0.0419 | 3.0 | 447 | 0.3419 | 0.9396 | 0.9396 |
| 0.0004 | 4.0 | 596 | 0.3351 | 0.9430 | 0.9429 |
| 0.0003 | 5.0 | 745 | 0.3070 | 0.9564 | 0.9564 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
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