distilbert-base-uncased-deepset-promptinjection
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: 0.2113
- F1: 0.9569
- Auprc: 0.9799
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: 0.001
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Auprc |
|---|---|---|---|---|---|
| No log | 1.0 | 69 | 0.1637 | 0.9223 | 0.9584 |
| No log | 2.0 | 138 | 0.2365 | 0.9569 | 0.9799 |
| No log | 3.0 | 207 | 0.1913 | 0.9655 | 0.9839 |
| No log | 4.0 | 276 | 0.2257 | 0.9569 | 0.9799 |
| No log | 5.0 | 345 | 0.2113 | 0.9569 | 0.9799 |
Framework versions
- PEFT 0.11.1
- Transformers 4.40.2
- Pytorch 2.3.0+cu118
- Datasets 2.19.2
- Tokenizers 0.19.1
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Model tree for cyrp/distilbert-base-uncased-deepset-promptinjection
Base model
distilbert/distilbert-base-uncased