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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: 0.0007
- Accuracy: 0.9255
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 | 0.0101 | 0.6877 |
0.0186 | 2.0 | 636 | 0.0036 | 0.8432 |
0.0186 | 3.0 | 954 | 0.0019 | 0.8913 |
0.0038 | 4.0 | 1272 | 0.0012 | 0.9148 |
0.0018 | 5.0 | 1590 | 0.0010 | 0.92 |
0.0018 | 6.0 | 1908 | 0.0008 | 0.9252 |
0.0013 | 7.0 | 2226 | 0.0008 | 0.9248 |
0.0011 | 8.0 | 2544 | 0.0007 | 0.9255 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.0+cpu
- Datasets 2.11.0
- Tokenizers 0.13.3