Great, now you are ready to train! 🥳 
Training loop
To keep track of your training progress, use the tqdm library to add a progress bar over the number of training steps:

from tqdm.auto import tqdm
progress_bar = tqdm(range(num_training_steps))
model.train()
for epoch in range(num_epochs):
     for batch in train_dataloader:
         batch = {k: v.to(device) for k, v in batch.items()}
         outputs = model(**batch)
         loss = outputs.loss
         loss.backward()