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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: 0.2610
- Accuracy: 0.9474
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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 318 | 1.5228 | 0.7326 |
1.8624 | 2.0 | 636 | 0.7654 | 0.8577 |
1.8624 | 3.0 | 954 | 0.4497 | 0.9181 |
0.6966 | 4.0 | 1272 | 0.3359 | 0.9355 |
0.3375 | 5.0 | 1590 | 0.2958 | 0.9426 |
0.3375 | 6.0 | 1908 | 0.2781 | 0.9461 |
0.2473 | 7.0 | 2226 | 0.2688 | 0.9468 |
0.2194 | 8.0 | 2544 | 0.2644 | 0.9474 |
0.2194 | 9.0 | 2862 | 0.2620 | 0.9477 |
0.209 | 10.0 | 3180 | 0.2610 | 0.9474 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.12.1
- Datasets 1.16.1
- Tokenizers 0.13.3