This repository implements the paper ‘Fine-tune BERT for Extractive Summarization’ by adding multiple sentence embeddings and interval segments to BERT, then fine-tuning for extractive summarization tasks. The code supports training on CNN/DailyMail datasets and evaluates using ROUGE metrics. It uses PyTorch as the deep learning framework and Stanford CoreNLP for preprocessing.