distilbert-base-uncased-disaster-tweet-jailbreaking
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6027
- Accuracy: 0.7113
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5332 | 1.0 | 243 | 0.6080 | 0.6680 |
| 0.5117 | 2.0 | 486 | 0.6029 | 0.7134 |
| 0.3544 | 3.0 | 729 | 0.7232 | 0.7031 |
| 0.2960 | 4.0 | 972 | 0.6870 | 0.6928 |
| 0.1987 | 5.0 | 1215 | 0.9753 | 0.7093 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2