devjwsong/lstm-bayesian-optimization-pytorch
Bayesian Optimization implementation for text classifiction
This project helps machine learning practitioners or researchers quickly develop and optimize text classification models. It takes raw text data, like customer reviews, and automatically finds the best settings for the model to accurately categorize the text. The output is a highly tuned text classification model, ready for deployment or further research. It's designed for someone building and fine-tuning text classifiers.
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Use this if you need to build a text classification model and want to efficiently find the best hyperparameter settings using Bayesian Optimization.
Not ideal if you are not comfortable with Python scripting and command-line execution, or if you need a pre-built, no-code solution.
Stars
23
Forks
3
Language
Python
License
MIT
Last pushed
Jul 25, 2024
Commits (30d)
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