diff --git a/tests/python_package_test/test_sklearn.py b/tests/python_package_test/test_sklearn.py
index 0fb7424f3b58..a7a0ef40dacd 100644
--- a/tests/python_package_test/test_sklearn.py
+++ b/tests/python_package_test/test_sklearn.py
@@ -558,8 +558,10 @@ def test_inf_handle(self):
         y = np.random.randn(nrows) + np.full(nrows, 1e30)
         weight = np.full(nrows, 1e10)
         params = {'n_estimators': 20, 'verbose': -1}
-        params_fit = {'X': X, 'y': y, 'sample_weight': weight, 'eval_set': (X, y), 'verbose': False, 'early_stopping_rounds': 5}
+        params_fit = {'X': X, 'y': y, 'sample_weight': weight, 'eval_set': (X, y),
+                      'verbose': False, 'early_stopping_rounds': 5}
         gbm = lgb.LGBMRegressor(**params).fit(**params_fit)
+        np.testing.assert_array_equal(gbm.evals_result_['training']['l2'], np.inf)
 
     def test_nan_handle(self):
         nrows = 1000
@@ -568,5 +570,7 @@ def test_nan_handle(self):
         y = np.random.randn(nrows) + np.full(nrows, 1e30)
         weight = np.zeros(nrows)
         params = {'n_estimators': 20, 'verbose': -1}
-        params_fit = {'X': X, 'y': y, 'sample_weight': weight, 'eval_set': (X, y), 'verbose': False, 'early_stopping_rounds': 5}
+        params_fit = {'X': X, 'y': y, 'sample_weight': weight, 'eval_set': (X, y),
+                      'verbose': False, 'early_stopping_rounds': 5}
         gbm = lgb.LGBMRegressor(**params).fit(**params_fit)
+        np.testing.assert_array_equal(gbm.evals_result_['training']['l2'], np.nan)