sebastianruder--nlp-progress
Sebastian Ruder
26 行
1.1 KiB
Markdown
26 行
1.1 KiB
Markdown
# Question answering
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Question answering is the task of answering a question.
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### Table of contents
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- [Reading comprehension](#reading-comprehension)
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- [SberQuAD](#sberquad)
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## Reading comprehension
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### SberQuAD
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The [Sberbank Question Answering dataset (SberQuAD)](https://arxiv.org/abs/1912.09723) is a reading comprehension dataset
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in the style of SQuAD, which was created as part of a competition in 2017 by Sberbank. The data consists of around 50k
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questions on Wikipeda.
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Because the original SberQuAD development set is not available, the original training set of SberQuAD was partitioned
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into a (new) training (45,328) and testing (5,036) sets by the DeepPavlov team.
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| Model | F1 | EM | Paper |
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| ------------- | :-----:| :-----:| --- |
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| BERT (Efimov et al., 2019) | 84.8 | 66.6 | [SberQuAD - Russian Reading Comprehension Dataset: Description and Analysis](https://arxiv.org/abs/1912.09723) |
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| DocQA (Efimov et al., 2019) | 79.5 | 59.6 | [SberQuAD - Russian Reading Comprehension Dataset: Description and Analysis](https://arxiv.org/abs/1912.09723) |
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