---
base_model:
- protectai/deberta-v3-base-prompt-injection
pipeline_tag: text-classification
language:
- en
tags:
- prompt-injection
- injection
- security
- generated_from_trainer
datasets:
- xTRam1/safe-guard-prompt-injection
metrics:
- accuracy
- recall
- precision
- f1
---

# Model Card for bigberta-v1-pompt-injection

This model is a fine-tuned version of [protectai/deberta-v3-base-prompt-injection](https://huggingface.co/protectai/deberta-v3-base-prompt-injection) on multiple datasets of prompt injections.

It aims to identify prompt injections, classifying inputs into two categories: `0` for no injection and `1` for injection detected.

It achieves the following results on the evaluation set:

Test Samples: 2060

- Loss: 0.0361
- Accuracy: 0.9908
- Precision: 0.9861
- Recall: 0.9846
- F1 Score: 0.9854