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arXiv · 2105.00328

When to Fold'em: How to answer Unanswerable questions

Marshall Ho·Zhipeng Zhou·Judith He
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Abstract

We present 3 different question-answering models trained on the SQuAD2.0 dataset -- BIDAF, DocumentQA and ALBERT Retro-Reader -- demonstrating the improvement of language models in the past three years. Through our research in fine-tuning pre-trained models for question-answering, we developed a novel approach capable of achieving a 2% point improvement in SQuAD2.0 F1 in reduced training time. Our method of re-initializing select layers of a parameter-shared language model is simple yet empirically powerful.

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Marshall Ho, Zhipeng Zhou, Judith He. 2021-05-01. When to Fold'em: How to answer Unanswerable questions. https://arxiv.org/abs/2105.00328

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