Learning rate: The learning rate implies how fast the network learns its parameters.
Momentum: This parameter helps in coming out of the local minima and smoothening the jumps while gradient descents.
Number of epochs: This shows the number of times the entire training data is fed to the network. Here, the training is referred to as the number of epochs.