richardyoung/CardioEmbed-BGE-small-v1.5
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CardioEmbed-BGE-small-v1.5
Domain-specialized cardiology text embeddings using LoRA-adapted BGE-small-v1.5
Part of a comparative study of 10 embedding architectures for clinical cardiology.
Performance
Usage
from transformers import AutoModel, AutoTokenizer
from peft import PeftModel
base_model = AutoModel.from_pretrained("BAAI/bge-small-en-v1.5")
tokenizer = AutoTokenizer.from_pretrained("BAAI/bge-small-en-v1.5")
model = PeftModel.from_pretrained(base_model, "richardyoung/CardioEmbed-BGE-small-v1.5")Training
- Training Data: 106,535 cardiology text pairs from medical textbooks
- Method: LoRA fine-tuning (r=16, alpha=32)
- Loss: Multiple Negatives Ranking Loss (InfoNCE)
Citation
@article{young2024comparative,
title={Comparative Analysis of LoRA-Adapted Embedding Models for Clinical Cardiology Text Representation},
author={Young, Richard J and Matthews, Alice M},
journal={arXiv preprint},
year={2024}
}