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: 0.7793
- Accuracy: 0.9161
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 |
|---|---|---|---|---|
| 4.2926 | 1.0 | 318 | 3.2834 | 0.7374 |
| 2.6259 | 2.0 | 636 | 1.8736 | 0.8303 |
| 1.5511 | 3.0 | 954 | 1.1612 | 0.8913 |
| 1.0185 | 4.0 | 1272 | 0.8625 | 0.91 |
| 0.8046 | 5.0 | 1590 | 0.7793 | 0.9161 |
Framework versions
- Transformers 4.19.3
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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Dataset used to train flood/distilbert-base-uncased-finetuned-clinc
Evaluation results
- Accuracy on clinc_oosself-reported0.916