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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: 0.3422
- Accuracy: 0.9484
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: 9
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 318 | 2.1773 | 0.75 |
2.582 | 2.0 | 636 | 1.1161 | 0.8606 |
2.582 | 3.0 | 954 | 0.6379 | 0.9106 |
0.9932 | 4.0 | 1272 | 0.4589 | 0.9319 |
0.4527 | 5.0 | 1590 | 0.3919 | 0.9442 |
0.4527 | 6.0 | 1908 | 0.3651 | 0.9455 |
0.3078 | 7.0 | 2226 | 0.3520 | 0.9474 |
0.2605 | 8.0 | 2544 | 0.3435 | 0.9487 |
0.2605 | 9.0 | 2862 | 0.3422 | 0.9484 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2