I am training a Reinforcement Learning agent using stable_baselines3.
Is there a way to edit the frequency of the logs (log the mean reward every 200 steps) ?
I found this parameter _log_freq
but it's not working
class TensorboardCallback(BaseCallback):
def __init__(self, verbose=0):
super().__init__(verbose)
self._log_freq = 100
def _on_step(self) -> bool:
#some code
return True
It's the parameter log_interval
in the learn() function
model = A2C("CnnPolicy", env, verbose=1,tensorboard_log='./'+tmp_path, )
model.learn(total_timesteps=int(N_STEP),callback=TensorboardCallback(),log_interval = 100)