readme: # Load the checkpoint
  
  ```python
  checkpoint = torch.load(SAVE_PATH)
  ```
  
  # Reload the model
  
  ```python
  model = BertForSequenceClassification.from_pretrained(
      'bert-base-chinese', 
      num_labels=2,
      problem_type='single_label_classification'
      ).to(device)
  model.load_state_dict(checkpoint['model_state_dict'])
  ```
  
  # Reload the optimizer
  
  ```python
  optimizer = AdamW(optimizer_grouped_parameters, lr=2e-5)
  optimizer.load_state_dict(checkpoint['optimizer_state_dict'])
  ```
  
  # Other Info
  
  ```python
  test_acc = checkpoint['acc']  # corresponding test accuracy
  epoch = checkpoint['epoch']  # which epoch the checkpoint belongs to
  ```
  
  