KnowledgeDisttillationBERT
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: 0.9947
- Accuracy: 0.8625
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 4.2895 | 1.0 | 318 | 3.3853 | 0.7029 |
| 2.6277 | 2.0 | 636 | 2.0531 | 0.7973 |
| 1.5479 | 3.0 | 954 | 1.3723 | 0.8404 |
| 1.0148 | 4.0 | 1272 | 1.0780 | 0.8575 |
| 0.7952 | 5.0 | 1590 | 0.9947 | 0.8625 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.6.0+cu124
- Datasets 1.16.1
- Tokenizers 0.21.1
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