distilbert-base-uncased-distilled-clinc
This model is a fine-tuned version of distilbert-base-uncased on the clinc_oos dataset. It achieves the following results on the evaluation set:
- Loss: 1.5565
- Accuracy: 0.8265
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.2743 | 1.0 | 318 | 2.5809 | 0.7310 |
| 2.2148 | 2.0 | 636 | 1.7909 | 0.8071 |
| 1.7065 | 3.0 | 954 | 1.5565 | 0.8265 |
Framework versions
- Transformers 4.21.0.dev0
- Pytorch 1.12.0
- Datasets 2.3.2
- Tokenizers 0.12.1