diff --git a/config/misc/default.yaml b/config/misc/default.yaml
index b41c965..db0a12b 100644
--- a/config/misc/default.yaml
+++ b/config/misc/default.yaml
@@ -1,3 +1,3 @@
 seed: 42
 debug: False
-modes: [ train, valid ]
+modes: [ train , valid , test ]
diff --git a/sage/data/dataloader.py b/sage/data/dataloader.py
index e9e355a..60c8a8f 100755
--- a/sage/data/dataloader.py
+++ b/sage/data/dataloader.py
@@ -283,19 +283,6 @@ def remove_duplicates(self, labels: pd.DataFrame) -> pd.DataFrame:
         labels = labels[~_dups_bool]
         return labels
 
-    def _exclude_data(self,
-                      lst: pd.DataFrame,
-                      root: Path,
-                      exclusion_fname: str = "exclusion.csv") -> List[Path]:
-        try:
-            exc = pd.read_csv(root / exclusion_fname, header=None)
-            exclusion = set(exc.values.flatten().tolist())
-            lst = [f for f in lst if f not in exclusion]
-        except:
-            logger.info("No exclusion file found. %s", root / exclusion_fname)
-            pass
-        return lst
-
 
 class UKBClassification(UKBDataset):
     def __init__(self,
diff --git a/sage/xai/trainer.py b/sage/xai/trainer.py
index 0a286a1..2eadd10 100644
--- a/sage/xai/trainer.py
+++ b/sage/xai/trainer.py
@@ -124,7 +124,7 @@ def _configure_xai(self,
                 attr_mtd = ca.InputXGradient(forward_func=model.backbone)
             xai = ca.NoiseTunnel(attribution_method=attr_mtd)
             if xai_call_kwarg is None:
-                xai_call_kwarg = dict(nt_type="smoothgrad", nt_samples=15)
+                xai_call_kwarg = dict(nt_type="smoothgrad", nt_samples=10)
         else:
             breakpoint()
         self.xai_call_kwarg = dict() if xai_call_kwarg is None else xai_call_kwarg