Increased steps num

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 194.01 +/- 75.90
+      value: 216.67 +/- 74.33
       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 0x79d729b72830>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79d729b728c0>", "reset_noise": 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ppo-LunarLander-v2.zip

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ppo-LunarLander-v2/data

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         "__module__": "stable_baselines3.common.policies",
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     "gamma": 0.99,
     "gae_lambda": 0.95,
-    "ent_coef": 0.0,
+    "ent_coef": 0.01,
     "vf_coef": 0.5,
     "max_grad_norm": 0.5,
     "batch_size": 64,

ppo-LunarLander-v2/policy.optimizer.pth

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-size 88362
+oid sha256:f8092936a107c551d1baa05c5c929751f02ba93ef03a85d129f534adb8f8960a
+size 87978

ppo-LunarLander-v2/policy.pth

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 version https://git-lfs.github.com/spec/v1
-oid sha256:7256c68415b205bc450fb4f0b3ecef7ee86bc0975c2d14cf2026531fef07fe26
-size 43762
+oid sha256:10d3e7d0015bf9d669aecb210c497347c650b556eb26ae64a99417d77246d0bc
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ppo-LunarLander-v2/system_info.txt

@@ -2,7 +2,7 @@
 - Python: 3.10.12
 - Stable-Baselines3: 2.0.0a5
 - PyTorch: 2.3.1+cu121
-- GPU Enabled: True
+- GPU Enabled: False
 - Numpy: 1.26.4
 - Cloudpickle: 2.2.1
 - Gymnasium: 0.28.1

results.json

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-{"mean_reward": 194.0084149, "std_reward": 75.90199993749941, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-08-15T11:27:36.057568"}
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