CogComp/Benchmarking-Zero-shot-Text-Classification
Code for EMNLP2019 paper : "Benchmarking zero-shot text classification: datasets, evaluation and entailment approach"
This project helps natural language processing researchers and practitioners evaluate text classification models, specifically in zero-shot scenarios. It takes various textual datasets, along with a set of potential labels, and outputs standardized evaluation metrics for how well a model can categorize text into previously unseen categories. This is designed for researchers or data scientists focused on advancing or applying zero-shot text classification techniques.
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Use this if you are a researcher or data scientist working on zero-shot text classification and need unified datasets and a standardized evaluation framework to compare different models or approaches.
Not ideal if you are looking for a pre-built, production-ready zero-shot text classification tool for immediate business application without a need for deep model evaluation or comparison.
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Python
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Jul 09, 2022
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