thanks a lot, is this implementation correct
lambda1 = lambda epoch: 0.03-epoch*(0.03-.0.0001)/epochs
optimizer = torch.optim.SGD(model_three.parameters(),nesterov=True)
scheduler = LambdaLR(optimizer, lr_lambda=lambda1)
for epoch in range(100):
      scheduler.step()
      train(...)
      validate(...)

how can I vary momentum in this scheduler, i have to vary both (learning rate and momentum)