diff --git a/freqtrade/freqai/prediction_models/ReinforcementLearner.py b/freqtrade/freqai/prediction_models/ReinforcementLearner.py
index d4c1881a6..fbf12008a 100644
--- a/freqtrade/freqai/prediction_models/ReinforcementLearner.py
+++ b/freqtrade/freqai/prediction_models/ReinforcementLearner.py
@@ -1,6 +1,6 @@
 import logging
 from pathlib import Path
-from typing import Any, Dict, Type
+from typing import Any, Dict, List, Optional, Type
 
 import torch as th
 from stable_baselines3.common.callbacks import ProgressBarCallback
@@ -74,10 +74,11 @@ class ReinforcementLearner(BaseReinforcementLearningModel):
                         'trained agent.')
             model = self.dd.model_dictionary[dk.pair]
             model.set_env(self.train_env)
-        callbacks = [self.eval_callback, self.tensorboard_callback]
-        use_progressbar = self.rl_config.get('progress_bar', False)
-        if use_progressbar:
-            callbacks.insert(0, ProgressBarCallback())
+        callbacks: List[Any] = [self.eval_callback, self.tensorboard_callback]
+        progressbar_callback: Optional[ProgressBarCallback] = None
+        if self.rl_config.get('progress_bar', False):
+            progressbar_callback = ProgressBarCallback()
+            callbacks.insert(0, progressbar_callback)
 
         try:
             model.learn(
@@ -85,8 +86,8 @@ class ReinforcementLearner(BaseReinforcementLearningModel):
                 callback=callbacks,
             )
         finally:
-            if use_progressbar:
-                callbacks[0].on_training_end()
+            if progressbar_callback:
+                progressbar_callback.on_training_end()
 
         if Path(dk.data_path / "best_model.zip").is_file():
             logger.info('Callback found a best model.')