Building a BERT-Based Question Answering System with RoBERTa and SQuAD 2.0

1. 1Build a BERT-based model using RoBERTa
2. 2Train the model on SQuAD 2.0 dataset
3. 3Fine-tune the model for question answering tasks
4. 4Evaluate the model's performance using metrics like F1-score and EM-score
5. 5Deploy the model in a production-ready environment

NLP engineers and data scientists can benefit from this project to improve their question answering systems, while product managers can use this to enhance customer support chatbots

💡 Using pre-trained language models like RoBERTa and fine-tuning them on specific datasets like SQuAD 2.0 can significantly improve question answering accuracy

Build a BERT-based question answering system with RoBERTa and SQuAD 2.0 for accurate text-based QA #NLP #BERT