<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
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: 0.3242
- Accuracy: 0.9455
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: 9
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.7171 | 1.0 | 318 | 1.9670 | 0.7310 |
1.5216 | 2.0 | 636 | 1.0061 | 0.8590 |
0.8053 | 3.0 | 954 | 0.5810 | 0.9139 |
0.4864 | 4.0 | 1272 | 0.4284 | 0.9361 |
0.3533 | 5.0 | 1590 | 0.3701 | 0.9413 |
0.2927 | 6.0 | 1908 | 0.3439 | 0.9445 |
0.2641 | 7.0 | 2226 | 0.3326 | 0.9452 |
0.2494 | 8.0 | 2544 | 0.3255 | 0.9461 |
0.2424 | 9.0 | 2862 | 0.3242 | 0.9455 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.3