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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: 0.1793
- Accuracy: 0.9435
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 318 | 1.0083 | 0.7194 |
| 1.3045 | 2.0 | 636 | 0.4852 | 0.8590 |
| 1.3045 | 3.0 | 954 | 0.2845 | 0.9174 |
| 0.4576 | 4.0 | 1272 | 0.2223 | 0.9361 |
| 0.2331 | 5.0 | 1590 | 0.2003 | 0.9374 |
| 0.2331 | 6.0 | 1908 | 0.1911 | 0.9416 |
| 0.1843 | 7.0 | 2226 | 0.1854 | 0.9452 |
| 0.1681 | 8.0 | 2544 | 0.1819 | 0.9439 |
| 0.1681 | 9.0 | 2862 | 0.1802 | 0.9423 |
| 0.1609 | 10.0 | 3180 | 0.1793 | 0.9435 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
