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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: 0.3040
- 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: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 318 | 2.1904 | 0.7545 |
2.5592 | 2.0 | 636 | 1.1694 | 0.8632 |
2.5592 | 3.0 | 954 | 0.6723 | 0.9165 |
1.038 | 4.0 | 1272 | 0.4640 | 0.9316 |
0.4699 | 5.0 | 1590 | 0.3723 | 0.9406 |
0.4699 | 6.0 | 1908 | 0.3293 | 0.9445 |
0.2942 | 7.0 | 2226 | 0.3086 | 0.9455 |
0.2329 | 8.0 | 2544 | 0.3040 | 0.9445 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2