diff --git a/python-package/xgboost/sklearn.py b/python-package/xgboost/sklearn.py
index 5b0fc9a30..9557fdd64 100644
--- a/python-package/xgboost/sklearn.py
+++ b/python-package/xgboost/sklearn.py
@@ -572,6 +572,13 @@ class XGBModel(XGBModelBase):
                 params.update({"eval_metric": eval_metric})
         return model, feval, params
 
+    def _set_evaluation_result(self, evals_result: Optional[dict]) -> None:
+        if evals_result:
+            for val in evals_result.items():
+                evals_result_key = list(val[1].keys())[0]
+                evals_result[val[0]][evals_result_key] = val[1][evals_result_key]
+            self.evals_result_ = evals_result
+
     @_deprecate_positional_args
     def fit(self, X, y, *, sample_weight=None, base_margin=None,
             eval_set=None, eval_metric=None, early_stopping_rounds=None,
@@ -678,13 +685,7 @@ class XGBModel(XGBModelBase):
                               verbose_eval=verbose, xgb_model=model,
                               callbacks=callbacks)
 
-        if evals_result:
-            for val in evals_result.items():
-                evals_result_key = list(val[1].keys())[0]
-                evals_result[val[0]][evals_result_key] = val[1][
-                    evals_result_key]
-            self.evals_result_ = evals_result
-
+        self._set_evaluation_result(evals_result)
         return self
 
     def predict(self, data, output_margin=False, ntree_limit=None,
@@ -1035,13 +1036,7 @@ class XGBClassifier(XGBModel, XGBClassifierBase):
         if not callable(self.objective):
             self.objective = params["objective"]
 
-        if evals_result:
-            for val in evals_result.items():
-                evals_result_key = list(val[1].keys())[0]
-                evals_result[val[0]][
-                    evals_result_key] = val[1][evals_result_key]
-            self.evals_result_ = evals_result
-
+        self._set_evaluation_result(evals_result)
         return self
 
     fit.__doc__ = XGBModel.fit.__doc__.replace(
@@ -1502,13 +1497,7 @@ class XGBRanker(XGBModel, XGBRankerMixIn):
                               callbacks=callbacks)
 
         self.objective = params["objective"]
-
-        if evals_result:
-            for val in evals_result.items():
-                evals_result_key = list(val[1].keys())[0]
-                evals_result[val[0]][evals_result_key] = val[1][evals_result_key]
-            self.evals_result = evals_result
-
+        self._set_evaluation_result(evals_result)
         return self
 
     def predict(self, data, output_margin=False,
diff --git a/tests/python/test_with_sklearn.py b/tests/python/test_with_sklearn.py
index 2c40e6c3d..5e2adc7c1 100644
--- a/tests/python/test_with_sklearn.py
+++ b/tests/python/test_with_sklearn.py
@@ -138,6 +138,7 @@ def test_ranking():
     model = xgb.sklearn.XGBRanker(**params)
     model.fit(x_train, y_train, group=train_group,
               eval_set=[(x_valid, y_valid)], eval_group=[valid_group])
+    assert model.evals_result()
 
     pred = model.predict(x_test)