first commit

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 289.81 +/- 19.99
+      value: 283.64 +/- 17.16
       name: mean_reward
       verified: false
 ---
@@ -34,15 +34,4 @@ from stable_baselines3 import ...
 from huggingface_sb3 import load_from_hub
 
 ...
-
-model = PPO('MlpPolicy', 
-            env, 
-            # batch_size = 128,
-            n_epochs = 7,
-            gamma = 0.995,
-            gae_lambda = 0.97,
-            ent_coef = 0.01,
-            verbose=1, 
-            tensorboard_log='tb_logs/lr')
-
 ```

config.json

@@ -1 +1 @@
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It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ", "__init__": "<function ActorCriticPolicy.__init__ at 0x797893aa37f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x797893aa3880>", "reset_noise": 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