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: 0.2496
- Accuracy: 0.9477
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: 8675309
- 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 | 2.0172 | 0.7274 |
2.3691 | 2.0 | 636 | 1.0476 | 0.8590 |
2.3691 | 3.0 | 954 | 0.5956 | 0.9094 |
0.9244 | 4.0 | 1272 | 0.3998 | 0.9381 |
0.4001 | 5.0 | 1590 | 0.3205 | 0.9445 |
0.4001 | 6.0 | 1908 | 0.2817 | 0.9458 |
0.2402 | 7.0 | 2226 | 0.2631 | 0.9481 |
0.186 | 8.0 | 2544 | 0.2582 | 0.9468 |
0.186 | 9.0 | 2862 | 0.2505 | 0.9484 |
0.1645 | 10.0 | 3180 | 0.2496 | 0.9477 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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