Topic Based Sentiment Detection using BERT
Jump to this document to understand the data, approach and further improvements
conda create --name topicsentiment --file requirements.txt
or pip install -r requirements.txt
in your envuvicorn prediction_api:app
streamlit run st_app.py
http://localhost:8501/
Pandas and Torch dataset classes in topicsentiment/dataset.py
Model Class and Trainer Class in topicsentiment/model.py
Jump to topicsentiment for detailed info
Configuration in config.py
Run python train.py --data sentisum-evaluation-dataset.csv
for full pipeline - preprocess and train
Run python train.py --data sentisum-evaluation-dataset.csv --preprocess
saves the preprocessed dataset to model_dir in config
Run python train.py --data final_data.pkl --train
trains the preprocessed dataset
Built using FastAPI
Code in prediction_api.py
Run uvicorn prediction_api:app
Swagger Docs at http://127.0.0.1:8000/docs
Simple Interface built using streamlit
Code in st_app.py
Run streamlit run st_app.py
App at http://localhost:8501/