Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 289.01 +/- 19.70
+      value: 264.23 +/- 82.77
       name: mean_reward
       verified: false
 ---

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 0x16c698a60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x16c698af0>", "reset_noise": "<function 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It allows to keep variance\n        above zero and prevent it from growing too fast. 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ppo-LunarLander-v2-paulmest-2022-12-30_04-10-51-10000000/system_info.txt

@@ -0,0 +1,7 @@
+OS: macOS-13.1-arm64-arm-64bit Darwin Kernel Version 22.2.0: Fri Nov 11 02:03:51 PST 2022; root:xnu-8792.61.2~4/RELEASE_ARM64_T6000
+Python: 3.10.8
+Stable-Baselines3: 2.0.0a0
+PyTorch: 1.13.0
+GPU Enabled: False
+Numpy: 1.23.5
+Gym: 0.27.0

results.json

@@ -1 +1 @@
-{"mean_reward": 289.014011458534, "std_reward": 19.701158855758905, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-30T00:17:45.549287"}
+{"mean_reward": 264.2281638194086, "std_reward": 82.76579931634137, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-30T14:46:50.547060"}