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: 0.3526
- Accuracy: 0.9439
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 318 | 2.2962 | 0.7197 |
| 2.7031 | 2.0 | 636 | 1.1942 | 0.8603 |
| 2.7031 | 3.0 | 954 | 0.6802 | 0.9077 |
| 1.0653 | 4.0 | 1272 | 0.4818 | 0.9326 |
| 0.4748 | 5.0 | 1590 | 0.4071 | 0.9384 |
| 0.4748 | 6.0 | 1908 | 0.3784 | 0.94 |
| 0.3163 | 7.0 | 2226 | 0.3619 | 0.9429 |
| 0.2647 | 8.0 | 2544 | 0.3544 | 0.9448 |
| 0.2647 | 9.0 | 2862 | 0.3526 | 0.9439 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1