After I load my optimiser state dict when a previously run session with a different lr, the new optimizer’s lr also changes.
eg)
lr=0.01
opt = torch.optim.Adam(model.parameters(), lr=lr, betas=(0.9, 0.999), eps=1e-08, weight_decay=weight_decay) 
for groups in opt.param_groups: print(groups['lr']); break
opt.load_state_dict(torch.load(load_saved)['optimizer']
for groups in opt.param_groups: print(groups['lr']); break

prints
0.01
0.05

Is this the correct behavior? I am reloading previous stats but lowering lr to continue training