model = AutoModelForSequenceClassification.from_pretrained(
    "distilbert-base-uncased",
     num_labels=2
) 

# freeze all layers
for param in model.parameters():
    param.requires_grad = False
    
# then unfreeze the two last layers (output layers)
for param in model.pre_classifier.parameters():
    param.requires_grad = True

for param in model.classifier.parameters():
    param.requires_grad = True
    
# finetune model
lightning_model = CustomLightningModule(model)

trainer = L.Trainer(
    max_epochs=3,
    ...
)

trainer.fit(
  model=lightning_model,
  train_dataloaders=train_loader,
  val_dataloaders=val_loader)

# evaluate model
trainer.test(lightning_model, dataloaders=test_loader)