diff --git a/CollaborativeCoding/load_metric.py b/CollaborativeCoding/load_metric.py
index c47a02a..002260c 100644
--- a/CollaborativeCoding/load_metric.py
+++ b/CollaborativeCoding/load_metric.py
@@ -79,6 +79,7 @@ def _get_metric(self, key):
                 raise ValueError(f"Metric {key} not supported")
 
     def __call__(self, y_true, y_pred):
+        y_true, y_pred = y_true.detach().cpu(), y_pred.detach().cpu()
         for key in self.metrics:
             self.metrics[key](y_true, y_pred)
 
diff --git a/CollaborativeCoding/metrics/EntropyPred.py b/CollaborativeCoding/metrics/EntropyPred.py
index b77e8d7..9338f44 100644
--- a/CollaborativeCoding/metrics/EntropyPred.py
+++ b/CollaborativeCoding/metrics/EntropyPred.py
@@ -36,16 +36,13 @@ def __call__(self, y_true: th.Tensor, y_logits: th.Tensor):
         assert y_logits.size(-1) == self.num_classes, (
             f"y_logit class length: {y_logits.size(-1)}, expected: {self.num_classes}"
         )
-
         y_pred = nn.Softmax(dim=1)(y_logits)
-        print(f"y_pred: {y_pred}")
         entropy_values = entropy(y_pred, axis=1)
         entropy_values = th.from_numpy(entropy_values)
 
         # Fix numerical errors for perfect guesses
         entropy_values[entropy_values == th.inf] = 0
         entropy_values = th.nan_to_num(entropy_values)
-        print(f"Entropy Values: {entropy_values}")
         for sample in entropy_values:
             self.stored_entropy_values.append(sample.item())