When to Fold'em: How to answer Unanswerable questions

• URL: http://arxiv.org/abs/2105.00328v1
• Date: Sat, 1 May 2021 19:08:40 GMT
• Title: When to Fold'em: How to answer Unanswerable questions
• Authors: Marshall Ho, Zhipeng Zhou, Judith He
• Abstract summary: We present 3 different question-answering models trained on the SQuAD2.0 dataset. We developed a novel approach capable of achieving a 2% point improvement in SQuAD2.0 F1 in reduced training time.
• Score: 5.586191108738563
• License: http://creativecommons.org/licenses/by/4.0/
• 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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