diff --git a/python/pyspark/ml/tests/test_tuning.py b/python/pyspark/ml/tests/test_tuning.py
index b250740f8c4f1..b1acaf695245d 100644
--- a/python/pyspark/ml/tests/test_tuning.py
+++ b/python/pyspark/ml/tests/test_tuning.py
@@ -101,7 +101,6 @@ def test_copy(self):
             lambda x: x.getEstimator().uid,
             # SPARK-32092: CrossValidator.copy() needs to copy all existing params
             lambda x: x.getNumFolds(),
-            lambda x: x.getFoldCol(),
             lambda x: x.getCollectSubModels(),
             lambda x: x.getParallelism(),
             lambda x: x.getSeed()
@@ -116,7 +115,6 @@ def test_copy(self):
         # SPARK-32092: CrossValidatorModel.copy() needs to copy all existing params
         for param in [
             lambda x: x.getNumFolds(),
-            lambda x: x.getFoldCol(),
             lambda x: x.getSeed()
         ]:
             self.assertEqual(param(cvModel), param(cvModelCopied))
@@ -127,9 +125,9 @@ def test_copy(self):
             'foo',
             "Changing the original avgMetrics should not affect the copied model"
         )
-        cvModel.subModels[0] = 'foo'
+        cvModel.subModels[0][0].getInducedError = lambda: 'foo'
         self.assertNotEqual(
-            cvModelCopied.subModels[0],
+            cvModelCopied.subModels[0][0].getInducedError(),
             'foo',
             "Changing the original subModels should not affect the copied model"
         )
@@ -224,7 +222,6 @@ def test_save_load_trained_model(self):
         loadedCvModel = CrossValidatorModel.load(cvModelPath)
         for param in [
             lambda x: x.getNumFolds(),
-            lambda x: x.getFoldCol(),
             lambda x: x.getSeed(),
             lambda x: len(x.subModels)
         ]:
@@ -780,9 +777,9 @@ def test_copy(self):
             'foo',
             "Changing the original validationMetrics should not affect the copied model"
         )
-        tvsModel.subModels[0] = 'foo'
+        tvsModel.subModels[0].getInducedError = lambda: 'foo'
         self.assertNotEqual(
-            tvsModelCopied.subModels[0],
+            tvsModelCopied.subModels[0].getInducedError(),
             'foo',
             "Changing the original subModels should not affect the copied model"
         )
diff --git a/python/pyspark/ml/tuning.py b/python/pyspark/ml/tuning.py
index 91f34ef24d021..6283c8bfd3df9 100644
--- a/python/pyspark/ml/tuning.py
+++ b/python/pyspark/ml/tuning.py
@@ -480,7 +480,10 @@ def copy(self, extra=None):
             extra = dict()
         bestModel = self.bestModel.copy(extra)
         avgMetrics = list(self.avgMetrics)
-        subModels = [model.copy() for model in self.subModels]
+        subModels = [
+            [sub_model.copy() for sub_model in fold_sub_models]
+            for fold_sub_models in self.subModels
+        ]
         return self._copyValues(CrossValidatorModel(bestModel, avgMetrics, subModels), extra=extra)
 
     @since("2.3.0")
@@ -511,7 +514,6 @@ def _from_java(cls, java_stage):
             "estimator": estimator,
             "estimatorParamMaps": epms,
             "numFolds": java_stage.getNumFolds(),
-            "foldCol": java_stage.getFoldCol(),
             "seed": java_stage.getSeed(),
         }
         for param_name, param_val in params.items():
@@ -544,7 +546,6 @@ def _to_java(self):
             "estimator": estimator,
             "estimatorParamMaps": epms,
             "numFolds": self.getNumFolds(),
-            "foldCol": self.getFoldCol(),
             "seed": self.getSeed(),
         }
         for param_name, param_val in params.items():