diff --git a/rofunc/learning/RofuncRL/trainers/base_trainer.py b/rofunc/learning/RofuncRL/trainers/base_trainer.py
index b3b46f933..3c977fa8a 100644
--- a/rofunc/learning/RofuncRL/trainers/base_trainer.py
+++ b/rofunc/learning/RofuncRL/trainers/base_trainer.py
@@ -91,6 +91,7 @@ def __init__(self,
         self.start_time = None
         self.eval_steps = self.cfg.Trainer.eval_steps
         self.inference_steps = self.cfg.Trainer.inference_steps
+        self.total_rew_mean = -1e4
 
         '''Environment'''
         env.device = self.device
@@ -190,10 +191,10 @@ def post_interaction(self):
         # Update best models and tensorboard
         if not self._step % self.write_interval and self.write_interval > 0:
             # update best models
-            reward = np.mean(self.agent.tracking_data.get("Reward / Total reward (mean)", -1e4))
-            if reward > self.agent.checkpoint_best_modules["reward"]:
+            self.total_rew_mean = np.mean(self.agent.tracking_data.get("Reward / Total reward (mean)", -1e4))
+            if self.total_rew_mean > self.agent.checkpoint_best_modules["reward"]:
                 self.agent.checkpoint_best_modules["timestep"] = self._step
-                self.agent.checkpoint_best_modules["reward"] = reward
+                self.agent.checkpoint_best_modules["reward"] = self.total_rew_mean
                 self.agent.checkpoint_best_modules["saved"] = False
                 self.agent.checkpoint_best_modules["modules"] = {k: copy.deepcopy(self.agent._get_internal_value(v)) for
                                                                  k, v in self.agent.checkpoint_modules.items()}
@@ -203,8 +204,9 @@ def post_interaction(self):
             self.write_tensorboard()
 
             # Update tqdm bar message
-            self.t_bar.set_postfix_str(f"Rew/Best: {reward:.2f}/{self.agent.checkpoint_best_modules['reward']:.2f}")
-            self.rofunc_logger.info(f"Step: {self._step}, Reward: {reward:.2f}", local_verbose=False)
+            self.t_bar.set_postfix_str(
+                f"Rew/Best: {self.total_rew_mean:.2f}/{self.agent.checkpoint_best_modules['reward']:.2f}")
+            self.rofunc_logger.info(f"Step: {self._step}, Reward: {self.total_rew_mean:.2f}", local_verbose=False)
 
         # Save checkpoints
         if not (self._step + 1) % self.agent.checkpoint_interval and \