Following are the advantages of transfer learning :
Better initial model : In other methods of learning, you must create a model from scratch. Transfer learning is a better starting point because it allows us to perform tasks at a higher level without having to know the details of the starting model.
Higher learning rate : Because the problem has already been taught for a similar task, transfer learning allows for a faster learning rate during training.
Higher accuracy after training : Transfer learning allows a deep learning model to converge at a higher performance level, resulting in more accurate output, thanks to a better starting point and higher learning rate.