diff --git a/freqtrade/freqai/RL/BaseEnvironment.py b/freqtrade/freqai/RL/BaseEnvironment.py
index 3fca6a25d..e43951142 100644
--- a/freqtrade/freqai/RL/BaseEnvironment.py
+++ b/freqtrade/freqai/RL/BaseEnvironment.py
@@ -77,6 +77,7 @@ class BaseEnvironment(gym.Env):
 
         # set here to default 5Ac, but all children envs can overwrite this
         self.actions: Type[Enum] = BaseActions
+        self.custom_info: dict = {}
 
     def reset_env(self, df: DataFrame, prices: DataFrame, window_size: int,
                   reward_kwargs: dict, starting_point=True):
diff --git a/freqtrade/freqai/RL/TensorboardCallback.py b/freqtrade/freqai/RL/TensorboardCallback.py
index 4aea9bdf5..b5b8ba23d 100644
--- a/freqtrade/freqai/RL/TensorboardCallback.py
+++ b/freqtrade/freqai/RL/TensorboardCallback.py
@@ -4,7 +4,7 @@ from typing import Any, Dict, Type, Union
 from stable_baselines3.common.callbacks import BaseCallback
 from stable_baselines3.common.logger import HParam
 
-from freqtrade.freqai.RL.BaseEnvironment import BaseActions
+from freqtrade.freqai.RL.BaseEnvironment import BaseActions, BaseEnvironment
 
 
 class TensorboardCallback(BaseCallback):
@@ -15,9 +15,8 @@ class TensorboardCallback(BaseCallback):
     def __init__(self, verbose=1, actions: Type[Enum] = BaseActions):
         super(TensorboardCallback, self).__init__(verbose)
         self.model: Any = None
-        # An alias for self.model.get_env(), the environment used for training
         self.logger = None  # type: Any
-        # self.training_env = None  # type: Union[gym.Env, VecEnv]
+        self.training_env: BaseEnvironment = None  # type: ignore
         self.actions: Type[Enum] = actions
 
     def _on_training_start(self) -> None:
@@ -43,7 +42,7 @@ class TensorboardCallback(BaseCallback):
         )
 
     def _on_step(self) -> bool:
-        custom_info = self.training_env.get_attr("custom_info")[0]  # type: ignore
+        custom_info = self.training_env.custom_info
         self.logger.record("_state/position", self.locals["infos"][0]["position"])
         self.logger.record("_state/trade_duration", self.locals["infos"][0]["trade_duration"])
         self.logger.record("_state/current_profit_pct", self.locals["infos"]