Does not look like that. I have used in exactly the same way as
my_list = ['classifier.3.weight', 'classifier.3.bias']
params = list(map(lambda x: x[1],list(filter(lambda kv: kv[0] in my_list, model.named_parameters()))))
base_params = list(map(lambda x: x[1],list(filter(lambda kv: kv[0] not in my_list, model.named_parameters()))))
optimizer = SGD([{'params': base_params}, {'params': params, 'lr': '1e-4'}], lr=3e-6, momentum=0.9)

params and base_params does not contain the names of the parameters involved but I printed their shapes and they seem to be distinct.
I also tried
optimizer = SGD([{'params': base_params, 'lr':'3e-6'}, {'params': params, 'lr': '1e-4'}], momentum=0.9)
this gave me the error
TypeError: '<' not supported between instances of 'list' and 'float' at the start of the training loop.
File "xxx.py", line 251, in main
    with Trainer(model, optimizer, F.cross_entropy, scheduler=scheduler, callbacks=_callbacks) as trainer:
  File "/usr/local/lib/python3.8/site-packages/homura/trainers.py", line 519, in __init__
    super(SupervisedTrainer, self).__init__(model, optimizer, loss_f, callbacks=callbacks, scheduler=scheduler,
  File "/usr/local/lib/python3.8/site-packages/homura/trainers.py", line 121, in __init__
    self.set_optimizer()
  File "/usr/local/lib/python3.8/site-packages/homura/trainers.py", line 422, in set_optimizer
    self.optimizer = optimizer(self.model.parameters())
  File "/usr/local/lib/python3.8/site-packages/torch/optim/sgd.py", line 57, in __init__
    if lr is not required and lr < 0.0:
TypeError: '<' not supported between instances of 'list' and 'float'

Any suggestions are welcome and deeply appreciated!