BERT Sentiment Classifier

This is a small personal project following the Tensorflow Tutorial on how to use BERT to make a sentiment classifier. I wanted to learn about BERT so I could use it on my own in other personal projects as well as understand why it is so much more effective than anything I can make by hand. Additionally, I am learning about transfer learning (using another model trained on one task to accomplish another task) and seeing how effective it can be. I am extremely interested in how we work with text data with machine learning as it differs from the traditional mode of numeric data input, so I am using this to start learning about the different methods of handling text.

Dataset

1. Download the dataset and unzip it.
2. Transfer the aclImdb folder into a dataset folder in the base of this repository. The final directory should look like ./dataset/aclImdb/*.
3. Delete the ./dataset/aclImdb/train/unsup folder as it is unnecessary.

Running

1. Run pip install -r requirements.txt to install all required python libraries.
2. Do python Classifier.py to run the model