distilbert-base-uncased-finetuned-clinc
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7721
- Accuracy: 0.9181
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 | 3.2884 | 0.7419 |
| 3.7865 | 2.0 | 636 | 1.8751 | 0.8368 |
| 3.7865 | 3.0 | 954 | 1.1569 | 0.8961 |
| 1.6925 | 4.0 | 1272 | 0.8573 | 0.9132 |
| 0.9056 | 5.0 | 1590 | 0.7721 | 0.9181 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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