Sentiment Analysis of Product Reviews using BERT

• Analyse and visualize the datasets to detect statistical bias
• Build and train a RoBERTa model to classify the sentiment of the reviews as positive, negative or neutral
• Deploy the trained model using FastAPI and Docker
• Streamlit App to showcase the model

How to run

• Clone this repo

• Install poetry (a tool for dependency management and packaging in Python)

    curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python -
  

• Install the dependecies && activate the virtual environment

    poetry install && poetry shell
  

• To prepare the data:

    python review_cl/process.py
  

• To train the model:

    python main.py 
  

Data

The Women's E-Commerce Clothing Reviews dataset was used to train and test the model. It contains reviews written by customers. This dataset includes 23486 rows and 10 feature variables. However, only the column Review Text was used to predict the Rating column.

The target variable is a positive ordinal integer variable for the product score granted by the customer from 1 Worst, to 5 Best. It has been mapped to 3 categories:

• {1, 2} -> "negative"
• {3} -> "neutral"
• {4, 5} -> "positive"

Modeling

A BERT based model is fine-tuned to predict the sentiment. We used the RoBERTa model (A Robustly Optimized BERT Pretraining)

This model is implemented in Transformers Hugging Face library.

Streamlit App

You can run the app locally:

streamlit run streamlit_app/model_dash.py

Deployment using FastAPI and Docker

We deploy the model as an HTTP endpoint using FastAPI, and then dockerize the code in a docker image.

We use this docker image as the base image (from the developper of the FastAPI package)

• To build the image:

    docker image build -t review_app .
  

• To run the container locally:

    docker container run -d -p 8080:80 --name myapp review_app
  

• To run the app using docker-compose:

    docker-compose up 
  

• To run the app using docker swarm:

    docker stack deploy -c docker-compose.yml MyApp