diff --git a/Code/python/notebooks/hyperparameter_scan.py b/Code/python/notebooks/hyperparameter_scan.py
index 40224e6..81c8d96 100644
--- a/Code/python/notebooks/hyperparameter_scan.py
+++ b/Code/python/notebooks/hyperparameter_scan.py
@@ -239,14 +239,14 @@ def run_mode_3():
 
     for warm in [300, 600, 900, 1800]:
         for pred in [150, 300, 600, 900, 1800]:
-            start = 30 * 60 - warm
-            end = 30 * 60 - pred
+            start_offset = 30 * 60 - warm
+            end_offset = 30 * 60 - pred
 
             base_ds = dataloader.SaveDataset(
                 torch.load("long_dataset.pt"),
                 step=step,
-                start_offset=start,
-                end_offset=end,
+                start_offset=start_offset,
+                end_offset=end_offset,
             )
 
             train_ds, val_ds = split_dataset(base_ds)
diff --git a/Code/python/src/aiRNN/dataloader.py b/Code/python/src/aiRNN/dataloader.py
index 66a9083..a83ae74 100644
--- a/Code/python/src/aiRNN/dataloader.py
+++ b/Code/python/src/aiRNN/dataloader.py
@@ -143,8 +143,11 @@ class SaveDataset(Dataset):
         t0 = self.start_offset
         t1 = max_len - self.end_offset
         self.idx_feat = torch.arange(t0, self.X_feat.shape[1], self.step)
+        print(self.idx_feat)
         self.idx_time = torch.arange(t0, t1, self.step)
+        print(self.idx_time)
         self.idx_out = torch.arange(0, self.Y_out.shape[1] - self.end_offset, self.step)
+        print(self.idx_out)
 
     def __len__(self):
         return self.X_feat.shape[0]