training_2.py

import torch.optim as optim
from torch.optim import lr_scheduler

plist = [
        {'params': model_ft.layer4.parameters(), 'lr': 1e-5},
        {'params': model_ft.last_linear.parameters(), 'lr': 5e-3}
        ]
optimizer_ft = optim.Adam(plist, lr=0.001)
lr_sch = lr_scheduler.StepLR(optimizer_ft, step_size=10, gamma=0.1)


model_ft = train_model(model_ft,
                       train_dataset_loader,
                       len(train_dataset),
                       optimizer_ft,
                       lr_sch,
                       num_epochs=20)

torch.save(model_ft.state_dict(), "model.bin")