hiyouga/Dual-Contrastive-Learning
Code for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation"
This project helps machine learning practitioners improve the accuracy of text classification models. It takes in existing labeled text data and outputs a more effective model capable of better categorizing text. Anyone building or fine-tuning text classification systems for tasks like sentiment analysis or subject categorization would find this useful.
167 stars. No commits in the last 6 months.
Use this if you need to train text classification models and want to achieve higher accuracy, especially when working with limited amounts of labeled data.
Not ideal if you are looking for a pre-trained, ready-to-use text classification tool without needing to engage in model training or fine-tuning.
Stars
167
Forks
30
Language
Python
License
MIT
Category
Last pushed
Sep 16, 2022
Commits (30d)
0
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