diff --git a/casanovo/denovo/model_runner.py b/casanovo/denovo/model_runner.py
index 296ce90a..b047525c 100644
--- a/casanovo/denovo/model_runner.py
+++ b/casanovo/denovo/model_runner.py
@@ -50,7 +50,6 @@ def __init__(
         self.trainer = None
         self.model = None
         self.loaders = None
-
         self.writer = None
 
         # Configure checkpoints.
diff --git a/tests/unit_tests/test_unit.py b/tests/unit_tests/test_unit.py
index efa89a05..6b840d20 100644
--- a/tests/unit_tests/test_unit.py
+++ b/tests/unit_tests/test_unit.py
@@ -514,15 +514,28 @@ def test_spectrum_id_mzml(mzml_small, tmp_path):
 
 def test_train_val_step_functions():
     """Test train and validation step functions operating on batches."""
-    model = Spec2Pep(n_beams=1, residues="massivekb", min_peptide_len=4)
+    model = Spec2Pep(
+        n_beams=1,
+        residues="massivekb",
+        min_peptide_len=4,
+        train_label_smoothing=0.1,
+    )
     spectra = torch.zeros(1, 5, 2)
     precursors = torch.tensor([[469.25364, 2.0, 235.63410]])
     peptides = ["PEPK"]
     batch = (spectra, precursors, peptides)
 
+    train_step_loss = model.training_step(batch)
+    val_step_loss = model.validation_step(batch)
+
     # Check if valid loss value returned
-    assert model.training_step(batch) > 0
-    assert model.validation_step(batch) > 0
+    assert train_step_loss > 0
+    assert val_step_loss > 0
+
+    # Check if smoothing is applied in training and not in validation
+    assert model.celoss.label_smoothing == 0.1
+    assert model.val_celoss.label_smoothing == 0
+    assert val_step_loss != train_step_loss
 
 
 def test_run_map(mgf_small):