diff --git a/n3fit/src/n3fit/hyper_optimization/rewards.py b/n3fit/src/n3fit/hyper_optimization/rewards.py
index 8b125490d8..d1bb9a49de 100644
--- a/n3fit/src/n3fit/hyper_optimization/rewards.py
+++ b/n3fit/src/n3fit/hyper_optimization/rewards.py
@@ -268,7 +268,7 @@ def compute_loss(
             ### Experiment:
             # Use the validation loss as the loss
             # summed with how far from 2 are we for the kfold
-            validation_loss_average = self.reduce_over_replicas(validation_loss, proportion=0.9)
+            validation_loss_average = self.reduce_over_replicas(validation_loss, proportion=0.8)
             kfold_loss_average = self.reduce_over_replicas(kfold_loss, proportion=0.1)
             loss = validation_loss_average + (max(kfold_loss_average, 2.0) - 2.0)
         elif self.loss_type == "phi2":