diff --git a/climsim_utils/data_utils.py b/climsim_utils/data_utils.py
index 520ef5c..e812e84 100644
--- a/climsim_utils/data_utils.py
+++ b/climsim_utils/data_utils.py
@@ -142,6 +142,9 @@ def find_keys(dictionary, value):
         self.target_train = None
         self.preds_train = None
         self.samples_train = None
+        self.target_weighted_train = None
+        self.preds_weighted_train = None
+        self.samples_weighted_train = None
         self.metrics_idx_train = None
         self.metrics_var_train = None
 
@@ -149,6 +152,9 @@ def find_keys(dictionary, value):
         self.target_val = None
         self.preds_val = None
         self.samples_val = None
+        self.target_weighted_val = None
+        self.preds_weighted_val = None
+        self.samples_weighted_val = None
         self.metrics_idx_val = None
         self.metrics_var_val = None
         
@@ -156,6 +162,9 @@ def find_keys(dictionary, value):
         self.target_scoring = None
         self.preds_scoring = None
         self.samples_scoring = None
+        self.target_weighted_scoring = None
+        self.preds_weighted_scoring = None
+        self.samples_weighted_scoring = None
         self.metrics_idx_scoring = None
         self.metrics_var_scoring = None
 
@@ -163,6 +172,9 @@ def find_keys(dictionary, value):
         self.target_test = None
         self.preds_test = None
         self.samples_test = None
+        self.target_weighted_test = None
+        self.preds_weighted_test = None
+        self.samples_weighted_test = None
         self.metrics_test = None
         self.metrics_idx_test = None
         self.metrics_var_test = None
@@ -544,16 +556,16 @@ def reweight_target(self, data_split):
         assert data_split in ['train', 'val', 'scoring', 'test'], 'Provided data_split is not valid. Available options are train, val, scoring, and test.'
         if data_split == 'train':
             assert self.target_train is not None
-            self.target_train = self.output_weighting(self.target_train)
+            self.target_weighted_train = self.output_weighting(self.target_train)
         elif data_split == 'val':
             assert self.target_val is not None
-            self.target_val = self.output_weighting(self.target_val)
+            self.target_weighted_val = self.output_weighting(self.target_val)
         elif data_split == 'scoring':
             assert self.target_scoring is not None
-            self.target_scoring = self.output_weighting(self.target_scoring)
+            self.target_weighted_scoring = self.output_weighting(self.target_scoring)
         elif data_split == 'test':
             assert self.target_test is not None
-            self.target_test = self.output_weighting(self.target_test)
+            self.target_weighted_test = self.output_weighting(self.target_test)
 
     def reweight_preds(self, data_split):
         '''