Text-Summarization.ipynb

Text summarization is the tecnique of generating a concise and coherent summary of a given text while preserving its vital information and main ideas.

Here we use BART Large-CNN model. and it was the main tool we employed for our text summarising effort. We made use of the dataset from the CORD-19 research challenge, which is made up of a sizable number of academic publications. We created a system that can provide short and coherent summaries of research publications by training the BART Large-CNN model on this dataset. We utilised the BLEU and ROUGE scores, which assess how closely the produced summaries resemble the original abstracts of the publications, to assess the quality of our summaries. Through this project, we demonstrated our expertise in text summarization, the use of cutting-edge models, and performance evaluation. Researchers looking for effective techniques to extract crucial information from research articles should consider the project's repercussions.

Dataset Link: https://www.kaggle.com/datasets/allen-institute-for-ai/CORD-19-research-challenge