maveryin/mixup-text
Exploring mixup strategies for text classification
This tool helps machine learning practitioners improve the accuracy of their text classification models, especially when they have limited training data. It takes your existing text datasets and classification models (like CNN, LSTM, or BERT) and applies different "mixup" techniques. The output is a more robust text classification model that can perform better on tasks like sentiment analysis or topic labeling.
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Use this if you are a machine learning engineer or data scientist working on text classification tasks and want to explore data augmentation strategies to boost model performance.
Not ideal if you are looking for a pre-trained, plug-and-play model for immediate text classification without needing to retrain or fine-tune.
Stars
31
Forks
7
Language
Python
License
MIT
Category
Last pushed
Dec 16, 2020
Commits (30d)
0
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