• Description: Developed a BERT (Bidirectional Encoder Representations from Transformers) based Language Model (LLM) using PyTorch for automated question answering. Utilized a dataset of 1000+ context sentences to achieve a precise answer prediction accuracy of 97%.
• Key Features: • Implemented BERT architecture in PyTorch for question answering. • Trained the model on a diverse dataset of context sentences. • Achieved a high accuracy of 97% in answer prediction.