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arXiv · 2106.11517

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

Shamane Siriwardhana·Rivindu Weerasekera·Elliott Wen·Suranga Nanayakkara
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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.

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Shamane Siriwardhana, Rivindu Weerasekera, Elliott Wen, Suranga Nanayakkara. 2021-06-22. Fine-tune the Entire RAG Architecture (including DPR retriever) for Question-Answering. https://arxiv.org/abs/2106.11517

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