distilbert-base-uncased-distilled-clinc
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1969
- Accuracy: 0.9445
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 |
---|---|---|---|---|
1.6746 | 1.0 | 318 | 1.1151 | 0.7284 |
0.8595 | 2.0 | 636 | 0.5390 | 0.8706 |
0.4493 | 3.0 | 954 | 0.3172 | 0.9184 |
0.2847 | 4.0 | 1272 | 0.2442 | 0.9355 |
0.2231 | 5.0 | 1590 | 0.2200 | 0.9377 |
0.1975 | 6.0 | 1908 | 0.2098 | 0.9419 |
0.1848 | 7.0 | 2226 | 0.2035 | 0.9406 |
0.1775 | 8.0 | 2544 | 0.1999 | 0.9445 |
0.1732 | 9.0 | 2862 | 0.1972 | 0.9435 |
0.171 | 10.0 | 3180 | 0.1969 | 0.9445 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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