distilbert-base-uncaed-finetuned-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: 0.7725
- Accuracy: 0.9165
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 318 | 3.2763 | 0.7284 |
| 3.7825 | 2.0 | 636 | 1.8625 | 0.8365 |
| 3.7825 | 3.0 | 954 | 1.1513 | 0.8984 |
| 1.6859 | 4.0 | 1272 | 0.8540 | 0.9135 |
| 0.8984 | 5.0 | 1590 | 0.7725 | 0.9165 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for sungkwangjoong/distilbert-base-uncaed-finetuned-clinc
Base model
distilbert/distilbert-base-uncasedDataset used to train sungkwangjoong/distilbert-base-uncaed-finetuned-clinc
Evaluation results
- Accuracy on clinc_oosvalidation set self-reported0.916