diff --git a/curriculum_learning.py b/curriculum_learning.py
index 4b25fe25..6bd0d15a 100644
--- a/curriculum_learning.py
+++ b/curriculum_learning.py
@@ -1115,6 +1115,15 @@ def _train_stage(
                     loss = self._get_model().compute_loss(batch)
                     loss.backward()
 
+                    # _get_model() unwraps DDP, so its gradient sync is bypassed; average grads manually.
+                    if dist.is_initialized():
+                        for p in self._get_model().parameters():
+                            if not p.requires_grad:
+                                continue
+                            if p.grad is None:
+                                p.grad = torch.zeros_like(p)
+                            dist.all_reduce(p.grad, op=dist.ReduceOp.AVG)
+
                     # Handle gradient clipping for distributed training
                     clip_grad_norm_(self._get_model().parameters(), GRAD_CLIP_NORM)