Phase 1

1. Created an architecture which have these layers - distilbert, dropout, linear, sigmod, output
2. We have initialised a tokenizer which return the trainign samples and validation samples
3. Created a dashboard with streamlit to show the metrics

----The stack involved is----

Deep Learning: PyTorch, Hugging Face (DistilBERT).  

Data & Analytics: Pandas, Scikit-Learn

Frontend: Streamlit

Install Dependencies pip install torch transformers pandas scikit-learn streamlit Run data dashboard: streamlit run dashboard_minimal.py.