diff --git a/tests/torchtune/modules/peft/test_dora.py b/tests/torchtune/modules/peft/test_dora.py
index b52dc9702..3a7724735 100644
--- a/tests/torchtune/modules/peft/test_dora.py
+++ b/tests/torchtune/modules/peft/test_dora.py
@@ -269,7 +269,7 @@ def embed_dim(self):
     def test_dora_distributed_init(self):
         self.run_subtests(
             {
-                "load_dora_weights": [True],
+                "load_dora_weights": [True, False],
             },
             self._test_dora_distributed_init,
         )
@@ -327,8 +327,7 @@ def _test_dora_distributed_init(self, load_dora_weights):
                 assert dora_linear.magnitude.is_meta
 
         # Optionally load adapter weights (as though we are resuming from checkpoint)
-        # Now lora_a, lora_b, and magnitude should not be on meta device, but base weight should be
-        # Additionally since the weights are randomly initialized we should have magnitude != ||W+(alpha/rank)BA||
+        # Now lora_a, lora_b, and magnitude should not be on meta device, but base weight should be.
         if load_dora_weights:
             training.load_from_full_model_state_dict(
                 ffn,