ymcui/mrc-model-analysis
Multilingual Multi-Aspect Explainability Analyses on Machine Reading Comprehension Models (iScience)
This project helps researchers and developers understand how machine reading comprehension (MRC) models, like BERT, answer questions based on a given text. It takes a pre-trained MRC model and a dataset of questions and texts, then visualizes which parts of the text (attention zones) the model focuses on to find an answer. This is useful for AI researchers and NLP engineers who need to analyze and explain the behavior of their question-answering systems.
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Use this if you need to perform detailed explainability analysis on the internal workings of multilingual machine reading comprehension models.
Not ideal if you are looking for a simple, out-of-the-box solution to train a new MRC model without needing to delve into its internal attention mechanisms.
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7
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2
Language
Python
License
Apache-2.0
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Last pushed
Jun 21, 2022
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