Added `accelerator` based gradient accumulation for basic_example (#8966)

added accelerator based gradient accumulation for basic_example
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

docs/source/en/tutorials/basic_training.md

@@ -340,8 +340,8 @@ Now you can wrap all these components together in a training loop with 🤗 Acce
 ...                 loss = F.mse_loss(noise_pred, noise)
 ...                 accelerator.backward(loss)
 
-...             if (step + 1) % config.gradient_accumulation_steps == 0:
-...                 accelerator.clip_grad_norm_(model.parameters(), 1.0)
+...                 if accelerator.sync_gradients:
+...                     accelerator.clip_grad_norm_(model.parameters(), 1.0)
 ...                 optimizer.step()
 ...                 lr_scheduler.step()
 ...                 optimizer.zero_grad()