distilbert-base-uncased-distilled-clinc
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1113
- Accuracy: 0.9281
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: 48
- eval_batch_size: 48
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7127 | 1.0 | 318 | 0.4336 | 0.6929 |
| 0.3505 | 2.0 | 636 | 0.2297 | 0.8674 |
| 0.2208 | 3.0 | 954 | 0.1586 | 0.9094 |
| 0.1676 | 4.0 | 1272 | 0.1285 | 0.9213 |
| 0.1441 | 5.0 | 1590 | 0.1152 | 0.9255 |
| 0.1338 | 6.0 | 1908 | 0.1113 | 0.9281 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.12.1
- Datasets 2.14.5
- Tokenizers 0.22.2