Build a Movie Reviews Sentiment Classifier with Google's BERT Language Model
This is a example of building a Movie Reviews Sentiment classifier with Google's BERT (Bidirectional Encoder Representations from Transformers) NLP Language Model.
This code requires scikit-learn, tensorflow-gpu, tensorflow-hub, bert-tensorflow. The code is compatibile with TF <= 1.1.50 and latest available BERT model on Tensorflow Hub. To use the cpu version please install tensorflow==1.15.0.
pip install scikit-learn
pip install tensorflow-gpu==1.15.0
pip install tensorflow-hub
pip install bert-tensorflowTo run this project you can
Open the IPython Notebook src/bert_sentiment_classifier-local.ipynb in your Juypter Notebook or
Import src/bert_sentiment_classifier.ipynb into Google's Colab with GPU backend.
Open the Pyhon Interactive src/bert_sentiment_classifier.py in VisualStudio Code. See here how it works with Jupyter Notebooks and Code.