deberta_fine_tuned
This model is a fine-tuned version of ProtectAI/deberta-v3-base-prompt-injection on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0518
- Accuracy: 0.9932
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0229 | 1.0 | 4912 | 0.0296 | 0.9948 |
| 0.0135 | 2.0 | 9824 | 0.0231 | 0.9973 |
| 0.0136 | 3.0 | 14736 | 0.0260 | 0.9966 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for mlhiccup/deberta-sauron
Base model
microsoft/deberta-v3-base