my_awesome_model
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4282
- F1: 0.6908
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: 16
- 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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.1734 | 1.0 | 1685 | 0.1698 | 0.5775 |
| 0.1401 | 2.0 | 3370 | 0.1750 | 0.6176 |
| 0.1171 | 3.0 | 5055 | 0.1967 | 0.6104 |
| 0.082 | 4.0 | 6740 | 0.2097 | 0.6597 |
| 0.0571 | 5.0 | 8425 | 0.2515 | 0.6580 |
| 0.0611 | 6.0 | 10110 | 0.2643 | 0.6648 |
| 0.0415 | 7.0 | 11795 | 0.3226 | 0.6473 |
| 0.0341 | 8.0 | 13480 | 0.2959 | 0.6786 |
| 0.0311 | 9.0 | 15165 | 0.3864 | 0.6736 |
| 0.0223 | 10.0 | 16850 | 0.3742 | 0.6739 |
| 0.0229 | 11.0 | 18535 | 0.3545 | 0.6646 |
| 0.0204 | 12.0 | 20220 | 0.3989 | 0.6738 |
| 0.0198 | 13.0 | 21905 | 0.3672 | 0.6798 |
| 0.0128 | 14.0 | 23590 | 0.4160 | 0.6750 |
| 0.0128 | 15.0 | 25275 | 0.4282 | 0.6908 |
| 0.0092 | 16.0 | 26960 | 0.4178 | 0.6814 |
| 0.0143 | 17.0 | 28645 | 0.4289 | 0.6754 |
| 0.0076 | 18.0 | 30330 | 0.4366 | 0.682 |
| 0.0071 | 19.0 | 32015 | 0.4441 | 0.6867 |
| 0.0074 | 20.0 | 33700 | 0.4530 | 0.6874 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1