  In todays era huge volume of information exists everywhere. Therefore, it is
very crucial to evaluate that information and extract useful, and often
summarized, information out of it so that it may be used for relevant purposes.
This extraction can be achieved through a crucial technique of artificial
intelligence, namely, machine learning. Indeed automatic text summarization has
emerged as an important application of machine learning in text processing. In
this paper, an english text summarizer has been built with GRU-based encoder
and decoder. Bahdanau attention mechanism has been added to overcome the
problem of handling long sequences in the input text. A news-summary dataset
has been used to train the model. The output is observed to outperform
competitive models in the literature. The generated summary can be used as a
newspaper headline.
