more learn timesteps

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 8.64 +/- 174.61
+      value: 276.22 +/- 24.75
       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 0x7f625915be20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f625915beb0>", "reset_noise": 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It allows to keep variance\n        above zero and prevent it from growing too fast. 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-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6259160430>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f62591604c0>",
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         "__abstractmethods__": "frozenset()",
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 size 87929

ppo-LunarLander-v2/policy.pth

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 version https://git-lfs.github.com/spec/v1
-oid sha256:fba5f207a8ed72d91e33ffe0b7d96e0ae6c4913181c587e10fc660ad94dfd661
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 size 43329

ppo-LunarLander-v2/system_info.txt

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-- OS: Linux-5.15.90.1-microsoft-standard-WSL2-x86_64-with-glibc2.31 # 1 SMP Fri Jan 27 02:56:13 UTC 2023
+- OS: Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023
 - Python: 3.10.12
 - Stable-Baselines3: 2.0.0a5
 - PyTorch: 2.0.1+cu118

results.json

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