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