Fine-Tuned MS MARCO MiniLM Cross-Encoder
This model is a fine-tuned version of cross-encoder/ms-marco-MiniLM-L6-v2.
Description
The model was further trained for cybersecurity-related passage ranking, question answering, and relevance scoring tasks.
Given a query and a document (or passage), the model produces a relevance score that can be used for reranking search results and retrieving the most relevant cybersecurity information.
Usage
from sentence_transformers import CrossEncoder
model = CrossEncoder("jobby32/ms-marco-cybersecurity-MiniLM-L6-v2")
score = model.predict([
(
"What is a SQL injection attack?",
"SQL injection is a code injection technique used to exploit vulnerabilities in database-driven applications."
)
])
print(score)
Base Model
cross-encoder/ms-marco-MiniLM-L6-v2
Training Data
This model was fine-tuned on the jobby32/cybersecurity-QA-with-negatives dataset.
The dataset was created from publicly available cybersecurity question-answering datasets, including:
- Rowden/CybersecurityQAA
- sambanovasystems/attackqa
- mariiazhiv/cybersecurity_qa
Acknowledgements
Special thanks to the authors and maintainers of the original datasets for making their work publicly available to the cybersecurity and machine learning communities.
Intended Use
This model is intended for:
- Cybersecurity search and retrieval systems
- Document reranking
- Retrieval-Augmented Generation (RAG)
- Security knowledge bases
- Question answering pipelines
License
This model is based on cross-encoder/ms-marco-MiniLM-L6-v2 and follows the Apache-2.0 license.