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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: 0.2958
- Accuracy: 0.9494
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 |
---|---|---|---|---|
3.0462 | 1.0 | 318 | 2.2419 | 0.7339 |
1.7248 | 2.0 | 636 | 1.1431 | 0.8674 |
0.8983 | 3.0 | 954 | 0.6406 | 0.9148 |
0.5162 | 4.0 | 1272 | 0.4438 | 0.9368 |
0.3473 | 5.0 | 1590 | 0.3622 | 0.9435 |
0.2664 | 6.0 | 1908 | 0.3288 | 0.9461 |
0.2256 | 7.0 | 2226 | 0.3150 | 0.9481 |
0.2032 | 8.0 | 2544 | 0.3009 | 0.9474 |
0.1918 | 9.0 | 2862 | 0.2980 | 0.9474 |
0.1855 | 10.0 | 3180 | 0.2958 | 0.9494 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3