HenryPengZou/JointMatch
[EMNLP 2023] Official Code of "JointMatch: A Unified Approach for Diverse and Collaborative Pseudo-Labeling to Semi-Supervised Text Classification"
JointMatch helps you categorize large volumes of text data when you only have a small portion of it manually labeled. You provide your text data, some with existing category labels and most without, and it outputs a model that can accurately assign categories to all your unlabeled text. This is ideal for researchers or data analysts who need to classify extensive text datasets efficiently.
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Use this if you need to classify a very large text dataset (like news articles, customer reviews, or social media posts) but have limited resources or time to manually label only a small fraction of it.
Not ideal if you have all your text data already labeled, or if your primary goal is to perform tasks other than text classification.
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Last pushed
May 13, 2024
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