Train and Finetune Sentence Transformers Reranker Models

AI Impact Summary

This document details the process of finetuning Sentence Transformers' cross-encoder models (rerankers) for improved relevance scoring. The key insight is that general-purpose rerankers perform poorly when applied to specific domains, highlighting the value of domain-specific finetuning. This approach leverages a 2-stage "retrieve and rerank" system, commonly used in high-performance search, and demonstrates how to achieve superior results even with smaller, finetuned models compared to larger baselines.