Unlock the Power of Customized Embedding Models for Enhanced RAG Performance!
Are you looking to improve retrieval performance for your Retrieval-Augmented Generation (RAG) applications? Fine-tuning embedding models can be the game changer you need!
Key Highlights:
- What’s New? The release of Sentence Transformers 3 allows for easy and efficient fine-tuning.
- Why Customize? General models limit effectiveness. Tailored embeddings enhance accuracy, especially with domain-specific data.
- Results Matter: Fine-tuning the all-mpnet-base-v2 model with just 4,719 question-answer pairs improved:
- MRR@10: Increased from 0.8347 to 0.8919 (6.85% improvement)
- NDCG@10: Enhanced from 0.8571 to 0.9093 (6.09% improvement)
What You’ll Learn:
- Step-by-step guide: From dataset preparation to model evaluation.
- Cost-effective Training: Achieved in under a minute for less than $0.1!
Discover how to leverage the latest tools to customize your embeddings, driving superior results for specific applications!
🔗 [Read More & Start Fine-Tuning!] Don’t forget to share your thoughts or experiences below!
