Maybe you misunderstood what I was asking.
Say that I have trained the model for 30 epochs with:

optimizer = torch.optim.Adam(model.parameters(), lr=0.0001)

and saved the optimizer’s state_dict:

torch.save(optimizer.state_dict(), PATH)

Now I want to continue the training with a new optimizer with different learning rate:

optimizer = torch.optim.Adam(model.parameters(), lr=0.00005)

How should I load the state_dict of the previous optimizer to the new one?
Should I load it at all or I just need to use the new optimizer without any loading?