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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: 0.2389
- Accuracy: 0.9471
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 |
---|---|---|---|---|
1.9829 | 1.0 | 318 | 1.3786 | 0.7284 |
1.0665 | 2.0 | 636 | 0.6878 | 0.8642 |
0.5642 | 3.0 | 954 | 0.4058 | 0.9126 |
0.3514 | 4.0 | 1272 | 0.3042 | 0.9339 |
0.2656 | 5.0 | 1590 | 0.2701 | 0.94 |
0.2305 | 6.0 | 1908 | 0.2532 | 0.9442 |
0.2131 | 7.0 | 2226 | 0.2462 | 0.9458 |
0.2031 | 8.0 | 2544 | 0.2409 | 0.9471 |
0.1975 | 9.0 | 2862 | 0.2401 | 0.9461 |
0.1953 | 10.0 | 3180 | 0.2389 | 0.9471 |
Framework versions
- Transformers 4.29.1
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3