distilbert-base-uncased-finetuned-rte
This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.7189
- Accuracy: 0.6462
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: 16
- eval_batch_size: 16
- 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 | 156 | 0.7021 | 0.4982 |
| No log | 2.0 | 312 | 0.6693 | 0.5993 |
| No log | 3.0 | 468 | 0.6689 | 0.6426 |
| 0.6061 | 4.0 | 624 | 0.7189 | 0.6462 |
| 0.6061 | 5.0 | 780 | 0.7873 | 0.6426 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.1.0+cu121
- Datasets 1.16.1
- Tokenizers 0.15.2
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