Fine-tune the Entire RAG Architecture (including DPR retriever) for Question-Answering

Code

• github.com/huggingface/transformers/tree/master/examples/research_projects/rag-end2end-retriever
  Officialjax★ 0
• github.com/2024-MindSpore-1/Code2/tree/main/model-1/dpr
  mindspore★ 0

Abstract

In this paper, we illustrate how to fine-tune the entire Retrieval Augment Generation (RAG) architecture in an end-to-end manner. We highlighted the main engineering challenges that needed to be addressed to achieve this objective. We also compare how end-to-end RAG architecture outperforms the original RAG architecture for the task of question answering. We have open-sourced our implementation in the HuggingFace Transformers library.

Tasks

Benchmark Results

Reproductions