Embedding Model Fine-Tuning in Production: Hard Negative Mining, Synthetic Data Pipelines, and Contrastive Distillation
Production retrieval-augmented generation (RAG) and semantic search architectures frequently suffer from domain mismatch when relying on general-purpose embedding models. Off-the-shelf bi-encoders trained on broad web corpora often experience a 15% to 30% degradation in retrieval metrics such as NDCG@10 and MRR@10 when deployed on specialized enterprise corpora, including proprietary codebases, internal API schemas, clinical trials, and technical documentation. While downstream cross-encoder re
1 min
