What learning rate decay scheduler should I use with Adam Optimizer?
I’m getting very weird results using MultiStepLR and ExponentialLR decay scheduler.

#scheduler = torch.optim.lr_scheduler.MultiStepLR(optimizer=optimizer, milestones=[25,50,75], gamma=0.95)
scheduler = torch.optim.lr_scheduler.ExponentialLR(optimizer=optimizer, gamma=0.25)

optimizer = torch.optim.Adam(lr=m_lr,amsgrad=True, ...........)

for epoch in range(num_epochs):

    scheduler.step()

    running_loss = 0.0
    for i in range(num_train):
        train_input_tensor = ..........                    
        train_label_tensor = ..........
        optimizer.zero_grad()
        pred_label_tensor = model(train_input_tensor)
        loss = criterion(pred_label_tensor, train_label_tensor)
        loss.backward()
        optimizer.step()
        running_loss += loss.item()
    loss_history[m_lr].append(running_loss/num_train)


Any Help.
Thanks