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Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

Multi-task learning

Multi-task learning aims to learn multiple different tasks simultaneously while maximizing performance on one or all of the tasks.


The General Language Understanding Evaluation benchmark (GLUE) is a tool for evaluating and analyzing the performance of models across a diverse range of existing natural language understanding tasks. Models are evaluated based on their average accuracy across all tasks.

The state-of-the-art results can be seen on the public GLUE leaderboard.

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