Henry_Chibueze:

I don’t think the loss should change whether normalized or not coz the target data too was normalized accordingly


I’m not sure, if I understand this sentence correctly.
Are you comparing these use cases:
# case0
output = model(unnormalized_input)
loss0 = criterion(output, unnormalized_target)

# case1
output = model(normalized_input)
loss1 = criterion(output, normalized_target)

If so, then I would expect that loss1 would be potentially smaller than loss0, as the magnitude of the output and target is most likely smaller (assuming you are using e.g. nn.MSELoss).