lijiazheng99/Counterfactuals-for-Sentiment-Analysis
ACL-21 Exploring the Efficacy of Automatically Generated Counterfactuals for Sentiment Analysis
This project helps data scientists and machine learning engineers improve the accuracy and robustness of their sentiment analysis models. It automatically generates diverse 'counterfactual' examples from your existing text data, which are then used to retrain and strengthen your models. This means your sentiment analysis tools will perform better when encountering unexpected or 'out-of-distribution' language in real-world scenarios.
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Use this if you are building or maintaining sentiment analysis models and need to make them more resilient to biases and improve their performance on diverse, real-world text data.
Not ideal if you are looking for an off-the-shelf sentiment analysis tool, as this project is designed for developers who want to enhance their existing models.
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Python
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Last pushed
Dec 29, 2023
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