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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: 0.3020
- Accuracy: 0.9497
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: 24
- eval_batch_size: 24
- 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 |
---|---|---|---|---|
2.6598 | 1.0 | 636 | 1.5602 | 0.8123 |
1.0323 | 2.0 | 1272 | 0.6060 | 0.9074 |
0.4494 | 3.0 | 1908 | 0.3979 | 0.9387 |
0.294 | 4.0 | 2544 | 0.3424 | 0.9468 |
0.2393 | 5.0 | 3180 | 0.3252 | 0.9481 |
0.216 | 6.0 | 3816 | 0.3124 | 0.9490 |
0.204 | 7.0 | 4452 | 0.3100 | 0.9494 |
0.1969 | 8.0 | 5088 | 0.3039 | 0.9494 |
0.1939 | 9.0 | 5724 | 0.3031 | 0.9506 |
0.1918 | 10.0 | 6360 | 0.3020 | 0.9497 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2