By calculating the "training speed" from only the first few epochs of training, the converged model performance is predicted and optimal hyperparameters are identified using only a small fraction of the total training budget. For example, networks that require 100 epochs to train to convergence are trained for only 10-20 epochs, and the final performance is predicted using TPE to identify the best performing networks, thereby saving 80-90% of the total training budget.