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google-play-sentiment-analysis-with-bert's Introduction

Google Play Sentiment Analysis With BERT

Model

For this project I am using 'bert-base-cased'. It's pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in the paper and first released in this repository. The model is case-sensitive: it makes a difference between english and English.

Why I using 'bert-base-cased'?

Because in a task like sentiment analysis, people usually write words with a capital letter when they are angry or when they hate or like something.

Dataset

This project uses reviews from 33 applications, the max length being determined by the longest review.

Note

I did not have the resources, such as the Internet, electricity, device, etc., to train the model well and choose the appropriate learning rate, so there were no results.

To contribute to the project, please contribute directly. I am happy to do so, and if you have any comments, advice, job opportunities, or want me to contribute to a project, please contact me [email protected]

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