README.md

metadata

title: Sentiment classificator
emoji: 🎭
colorFrom: blue
colorTo: red
sdk: streamlit
sdk_version: 1.25.0
pinned: false
app_file: sentiment_analysis.py

bert-sentiment-analysis

Prototype that classifies text into positive or negative sentiments using a fine tuned bert model

Installation of dependencies

pip install -r requirements.txt

Usage

1. Download the trained model and move it to the models directory
2. Create a .env file and set a MODEL_NAME property with the name of the trained model file and optionally a MODEL_REPOSITORY_NAME property with the name of the huggingface repository of the model.
3. Use the tool:

• To use it as a streamlit web app run:

  streamlit run sentiment_analysis.py

  It will open a web app on http://localhost:8501

• To use it from command line run

  python sentiment_classificator.py <TEXT_TO_CLASSIFY>

Training

1. Download the all_sentiment_dataset.csv
2. Execute the classify_sentiment_with_bert notebook which is in the notebooks directory
3. The model should be saved under models directory as sentiments_bert_model.h5