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: 0.1521
- Accuracy: 0.9410
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 |
---|---|---|---|---|
1.2982 | 1.0 | 318 | 0.8887 | 0.7635 |
0.696 | 2.0 | 636 | 0.4673 | 0.8871 |
0.3906 | 3.0 | 954 | 0.2801 | 0.9229 |
0.2544 | 4.0 | 1272 | 0.2061 | 0.9332 |
0.1939 | 5.0 | 1590 | 0.1763 | 0.9387 |
0.1664 | 6.0 | 1908 | 0.1612 | 0.9416 |
0.1515 | 7.0 | 2226 | 0.1541 | 0.9416 |
0.1444 | 8.0 | 2544 | 0.1521 | 0.9410 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.1.0+cu118
- Datasets 1.16.1
- Tokenizers 0.15.0
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