distilbert-base-uncased_fold_0
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1206
- Accuracy: 0.9639
- F1: 0.9604
- Precision: 0.9665
- Recall: 0.9544
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: 40
- eval_batch_size: 40
- 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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0909 | 1.0 | 15481 | 0.1074 | 0.9582 | 0.9542 | 0.9578 | 0.9507 |
| 0.0806 | 2.0 | 30962 | 0.1020 | 0.9628 | 0.9591 | 0.9667 | 0.9517 |
| 0.0581 | 3.0 | 46443 | 0.1206 | 0.9639 | 0.9604 | 0.9665 | 0.9544 |
Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.6.1
- Tokenizers 0.22.2