distilbert-base-uncased-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: 0.7726
- Accuracy: 0.9197
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 | 3.2799 | 0.7245 |
| 3.7883 | 2.0 | 636 | 1.8716 | 0.8332 |
| 3.7883 | 3.0 | 954 | 1.1546 | 0.8945 |
| 1.6928 | 4.0 | 1272 | 0.8600 | 0.9123 |
| 0.902 | 5.0 | 1590 | 0.7726 | 0.9197 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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Model tree for cvnberk/distilbert-base-uncased-finetuned-clinc
Base model
distilbert/distilbert-base-uncasedDataset used to train cvnberk/distilbert-base-uncased-finetuned-clinc
Evaluation results
- Accuracy on clinc_oosvalidation set self-reported0.920