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Build a Domain-Specific Embedding Model in Under a Day

Hugging Face

A tutorial describes how to fine-tune a general-purpose embedding model for domain-specific retrieval systems using synthetic data generation and hard negative mining on a single GPU. Fine-tuning on NVIDIA's public documentation achieved over 10% improvement in Recall@10 and NDCG@10, while Atlassian improved their JIRA retrieval from 0.751 to 0.951 Recall@60 (26% gain). The approach enables organizations to build custom embedding models without manual labeling in under a day, addressing the failure modes of off-the-shelf models on proprietary or specialized content.

Read more related to this at Hugging Face
NVIDIA Atlassian

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Fine-tuning Embedding Models

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