gte-large-en-v1.5-based-ft-prompt-injection-detection-241205Weighted
This model is a fine-tuned version of Alibaba-NLP/gte-large-en-v1.5 on an unknown dataset.
It achieves the following results on the evaluation set:
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
F1 |
| 0.4432 |
0.2527 |
100 |
0.2279 |
0.9104 |
| 0.1996 |
0.5054 |
200 |
0.1793 |
0.9343 |
| 0.165 |
0.7581 |
300 |
0.1437 |
0.9450 |
| 0.1528 |
1.0107 |
400 |
0.1273 |
0.9531 |
| 0.1062 |
1.2634 |
500 |
0.1355 |
0.9490 |
| 0.1127 |
1.5161 |
600 |
0.1349 |
0.9544 |
| 0.1186 |
1.7688 |
700 |
0.1523 |
0.9496 |
| 0.1173 |
2.0215 |
800 |
0.1516 |
0.9483 |
| 0.0785 |
2.2742 |
900 |
0.1503 |
0.9528 |
| 0.0849 |
2.5268 |
1000 |
0.1623 |
0.9514 |
| 0.0898 |
2.7795 |
1100 |
0.1539 |
0.9460 |
| 0.0891 |
3.0322 |
1200 |
0.2415 |
0.9515 |
| 0.065 |
3.2849 |
1300 |
0.1589 |
0.9541 |
| 0.062 |
3.5376 |
1400 |
0.1499 |
0.9470 |
| 0.0677 |
3.7903 |
1500 |
0.1788 |
0.9445 |
| 0.0638 |
4.0430 |
1600 |
0.3220 |
0.9471 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
