distilbert-base-uncased-finetuned-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: 0.7720
- Accuracy: 0.9148
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 4.2828 | 1.0 | 318 | 3.2775 | 0.7452 |
| 2.6221 | 2.0 | 636 | 1.8650 | 0.8371 |
| 1.5394 | 3.0 | 954 | 1.1525 | 0.8935 |
| 1.0117 | 4.0 | 1272 | 0.8555 | 0.9087 |
| 0.793 | 5.0 | 1590 | 0.7720 | 0.9148 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.12.1+cu113
- Datasets 1.16.1
- Tokenizers 0.10.3
- Downloads last month
- 2
Dataset used to train codefactory4791/distilbert-base-uncased-finetuned-clinc
Evaluation results
- Accuracy on clinc_oosself-reported0.915