diff --git a/tests/test_sft_trainer.py b/tests/test_sft_trainer.py
index 7e52f700b49..fbf5a6bf8a3 100644
--- a/tests/test_sft_trainer.py
+++ b/tests/test_sft_trainer.py
@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import collections
 import copy
 import gc
 import json
@@ -950,7 +951,7 @@ def mock_super_compute_loss(model, inputs, return_outputs=False, num_items_in_ba
             captured["skip_logits"] = inputs.get("skip_logits")
             dummy_loss = torch.tensor(1.0, requires_grad=True)
             dummy_outputs = MagicMock()
-            dummy_outputs.token_accuracy = None
+            dummy_outputs.token_accuracy = torch.tensor(0.5)
             dummy_outputs.logits = torch.randn(1, 5, trainer.model.config.vocab_size)
             return (dummy_loss, dummy_outputs)
 
@@ -994,7 +995,12 @@ def test_predict_does_not_skip_logits_with_liger(self):
         def mock_super_compute_loss(model, inputs, return_outputs=False, num_items_in_batch=None):
             captured["skip_logits"] = inputs.get("skip_logits")
             dummy_loss = torch.tensor(1.0, requires_grad=True)
-            dummy_outputs = (dummy_loss, torch.randn(1, 5, trainer.model.config.vocab_size))
+            DummyOutput = collections.namedtuple("DummyOutput", ["loss", "logits", "token_accuracy"])
+            dummy_outputs = DummyOutput(
+                loss=dummy_loss,
+                logits=torch.randn(1, 5, trainer.model.config.vocab_size),
+                token_accuracy=torch.tensor(0.5),
+            )
             return (dummy_loss, dummy_outputs)
 
         with patch("transformers.Trainer.compute_loss", side_effect=mock_super_compute_loss):