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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: 1.7628
- Accuracy: 0.8403
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: 384
- eval_batch_size: 384
- 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 | 40 | 3.8005 | 0.1781 |
| No log | 2.0 | 80 | 3.3588 | 0.5739 |
| No log | 3.0 | 120 | 2.9451 | 0.7045 |
| No log | 4.0 | 160 | 2.6026 | 0.7581 |
| No log | 5.0 | 200 | 2.3296 | 0.7894 |
| No log | 6.0 | 240 | 2.1163 | 0.8084 |
| No log | 7.0 | 280 | 1.9559 | 0.8242 |
| 2.8275 | 8.0 | 320 | 1.8475 | 0.8329 |
| 2.8275 | 9.0 | 360 | 1.7837 | 0.8384 |
| 2.8275 | 10.0 | 400 | 1.7628 | 0.8403 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1
