diff --git a/training/train.py b/training/train.py
index d3139f7..6ee6f3f 100644
--- a/training/train.py
+++ b/training/train.py
@@ -370,13 +370,23 @@ def _expand(name, v):
         global_step = 0
 
     def wrap_ddp(model):
+        # Performance optimization: disable find_unused_parameters
+        # 
+        # find_unused_parameters=True adds overhead from extra autograd graph traversal.
+        # Analysis shows this training loop does NOT have unused parameters:
+        # - All backbone outputs flow to loss via pfc() for all data strategies
+        # - Branching is about input shape/indexing, not skipping modules
+        # - Only "optional" module is pooling head (gated by use_head), always used
+        #
+        # If you encounter "Expected to have finished reduction" errors, re-enable
+        # with find_unused_parameters=True and debug with TORCH_DISTRIBUTED_DEBUG=INFO
         return torch.nn.parallel.DistributedDataParallel(
             module=model,
             broadcast_buffers=False,
             device_ids=[local_rank],
             bucket_cap_mb=32,
-            find_unused_parameters=True,
-            static_graph=True,
+            find_unused_parameters=False,  # Disabled for performance
+            static_graph=True,  # Enables further optimizations when graph is fixed
         )
 
     backbone_ddp = wrap_ddp(backbone)