distilbert-base-uncased-finetuned-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: 0.7912
- Accuracy: 0.9187
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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 318 | 3.3034 | 0.7245 |
| 3.8012 | 2.0 | 636 | 1.8937 | 0.8561 |
| 3.8012 | 3.0 | 954 | 1.1754 | 0.8906 |
| 1.711 | 4.0 | 1272 | 0.8764 | 0.9110 |
| 0.9136 | 5.0 | 1590 | 0.7912 | 0.9187 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.6.0+cu126
- Datasets 3.4.2.dev0
- Tokenizers 0.22.2