diff --git a/torchtitan/train.py b/torchtitan/train.py
index e38446a398..8183b8e6df 100644
--- a/torchtitan/train.py
+++ b/torchtitan/train.py
@@ -451,7 +451,7 @@ def forward_backward_step(
                 with self.maybe_enable_amp:
                     pred = model_parts[0](inputs, eos_id=self.tokenizer.eos_id)
                     loss = self.loss_fn(pred, labels)
-                # need to free to before bwd to avoid peaking memory
+                # need to free pred before bwd to avoid peaking memory
                 del pred
                 loss.backward()
 
@@ -471,7 +471,7 @@ def train_step(
         accumulated_losses = []
         # If data runs out during gradient accumulation, that
         # entire step will not be executed.
-        for microbatch in range(self.gradient_accumulation_steps):
+        for _microbatch in range(self.gradient_accumulation_steps):
             input_dict, labels = next(data_iterator)
             loss = self.forward_backward_step(input_dict, labels)
             accumulated_losses.append(loss.detach())