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: 0.7977
- Accuracy: 0.9155
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 318 | 3.3065 | 0.7232 |
| 3.8097 | 2.0 | 636 | 1.8930 | 0.8487 |
| 3.8097 | 3.0 | 954 | 1.1797 | 0.8913 |
| 1.7181 | 4.0 | 1272 | 0.8830 | 0.9113 |
| 0.9252 | 5.0 | 1590 | 0.7977 | 0.9155 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cpu
- Datasets 2.19.1
- Tokenizers 0.15.2