Robust Transfer Learning Based Modelling for Accelerating the Learning of Ai in the Field of NLP

People have been able to communicate with one another via the languages that have developed naturally within their societies. It is estimated that somewhere over 6,500 distinct languages are currently being used in communication around the globe. Because language is the primary means by which humans communicate with one another, it is only natural that this fundamental concept has been investigated in detail in the scholarly literature for a considerable amount of time. This investigation has taken place over a considerable amount of time. In this paper, federated learning is used as an integral feature of the transfer learning model to accelerate the process of learning in NLP. The simulation shows a reduced mean square error in training, testing and validation stages