Changed the init_final value to center the starting mean and std of the policy

Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com>

lerobot/common/policies/hilserl/classifier/modeling_classifier.py

@@ -148,7 +148,7 @@ class Classifier(
     def predict_reward(self, x, threshold=0.6):
         if self.config.num_classes == 2:
             probs = self.forward(x).probabilities
-            logging.info(f"Predicted reward images: {probs}")
+            logging.debug(f"Predicted reward images: {probs}")
             return (probs > threshold).float()
         else:
             return torch.argmax(self.forward(x).probabilities, dim=1)

lerobot/common/policies/sac/configuration_sac.py

@@ -95,5 +95,6 @@ class SACConfig:
             "use_tanh_squash": True,
             "log_std_min": -5,
             "log_std_max": 2,
+            "init_final": 0.01,
         }
     )