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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: 0.0272
- Accuracy: 0.9287
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 | 0.2337 | 0.6274 |
0.3698 | 2.0 | 636 | 0.1052 | 0.8458 |
0.3698 | 3.0 | 954 | 0.0650 | 0.8935 |
0.1216 | 4.0 | 1272 | 0.0476 | 0.9068 |
0.0727 | 5.0 | 1590 | 0.0386 | 0.9181 |
0.0727 | 6.0 | 1908 | 0.0336 | 0.9219 |
0.0556 | 7.0 | 2226 | 0.0305 | 0.9229 |
0.0477 | 8.0 | 2544 | 0.0287 | 0.9287 |
0.0477 | 9.0 | 2862 | 0.0276 | 0.9274 |
0.0441 | 10.0 | 3180 | 0.0272 | 0.9287 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Tokenizers 0.13.2