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: 0.7681
- Accuracy: 0.9184
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 |
|---|---|---|---|---|
| 4.2967 | 1.0 | 318 | 3.2810 | 0.7181 |
| 2.6146 | 2.0 | 636 | 1.8652 | 0.8403 |
| 1.5378 | 3.0 | 954 | 1.1477 | 0.8977 |
| 1.0043 | 4.0 | 1272 | 0.8491 | 0.9135 |
| 0.7902 | 5.0 | 1590 | 0.7681 | 0.9184 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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Model tree for haesun/distilbert-base-uncased-finetuned-clinc
Base model
distilbert/distilbert-base-uncasedDataset used to train haesun/distilbert-base-uncased-finetuned-clinc
Evaluation results
- Accuracy on clinc_oosvalidation set self-reported0.918