diff --git a/src/maxtext/trainers/post_train/distillation/distillation_utils.py b/src/maxtext/trainers/post_train/distillation/distillation_utils.py
index 71a63c1ce2..00a2ab4418 100644
--- a/src/maxtext/trainers/post_train/distillation/distillation_utils.py
+++ b/src/maxtext/trainers/post_train/distillation/distillation_utils.py
@@ -248,6 +248,9 @@ def compute_loss(
         "distill/teacher_loss": teacher_hard_loss,
         "distill/out_proj_feature_loss": feature_loss,
         "distill/total_loss": total_loss,
+        "distill/temperature": self.temperature,
+        "distill/alpha": self.alpha,
+        "distill/beta_feature": self.beta_feature,
     }
     return total_loss, metrics
 
diff --git a/src/maxtext/trainers/post_train/distillation/train_distill.py b/src/maxtext/trainers/post_train/distillation/train_distill.py
index 85eb045bfe..7f5541b69a 100644
--- a/src/maxtext/trainers/post_train/distillation/train_distill.py
+++ b/src/maxtext/trainers/post_train/distillation/train_distill.py
@@ -464,8 +464,7 @@ def labels_fn(targets, targets_segmentation=None, **kwargs):
   )
 
   # 4. Optimizer & Config
-  total_updates = student_config.steps // student_config.gradient_accumulation_steps
-  optimizer = get_distillation_optimizer(student_config, total_updates)
+  optimizer = get_distillation_optimizer(student_config, student_config.steps)
 
   checkpointing_options = checkpoint.CheckpointManagerOptions(
       save_interval_steps=student_config.checkpoint_period,
diff --git a/tests/post_training/unit/train_distill_test.py b/tests/post_training/unit/train_distill_test.py
index e059986162..9b4249a8f7 100644
--- a/tests/post_training/unit/train_distill_test.py
+++ b/tests/post_training/unit/train_distill_test.py
@@ -399,6 +399,9 @@ def _test_monitored_strategy(self, sft_mode: bool):
         "distill/teacher_loss",
         "distill/out_proj_feature_loss",
         "distill/total_loss",
+        "distill/temperature",
+        "distill/alpha",
+        "distill/beta_feature",
     ]
     for key in expected_keys:
       self.assertIn(key, metrics)