distilbert-base-uncased-finetuned-sst-2-english_prompt_injection_detector

This model is a fine-tuned version of distilbert/distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1457
• Accuracy: 0.9583
• Precision: 0.9611
• Recall: 0.9583
• F1: 0.9580

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: 5.348061478440594e-05
• train_batch_size: 64
• eval_batch_size: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	4	0.5652	0.7917	0.8032	0.7917	0.7834
No log	2.0	8	0.2373	0.875	0.8759	0.875	0.8739
No log	3.0	12	0.1569	0.9583	0.9611	0.9583	0.9580
No log	4.0	16	0.1457	0.9583	0.9611	0.9583	0.9580

Framework versions

• Transformers 4.48.0.dev0
• Pytorch 2.5.1+cu124
• Datasets 3.6.0
• Tokenizers 0.21.0