PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 234.01 +/- 86.31
+      value: 281.67 +/- 22.17
       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 0x7b95bdb111b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b95bdb11240>", "reset_noise": 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"Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "False", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
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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 0x7dbac9070af0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7dbac9070b80>", "reset_noise": 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         "bounded_above": "[ True  True  True  True  True  True  True  True]",
@@ -65,7 +65,7 @@
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         "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
         "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
-        "_np_random": "Generator(PCG64)"
+        "_np_random": null
     },
     "action_space": {
         ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
@@ -76,9 +76,9 @@
         "dtype": "int64",
         "_np_random": null
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-    "n_envs": 1,
+    "n_envs": 16,
     "n_steps": 1024,
-    "gamma": 0.999,
+    "gamma": 0.9995,
     "gae_lambda": 0.98,
     "ent_coef": 0.01,
     "vf_coef": 0.5,

ppo-LunarLander-v2/policy.optimizer.pth

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 version https://git-lfs.github.com/spec/v1
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-size 87978
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+size 88362

ppo-LunarLander-v2/policy.pth

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 version https://git-lfs.github.com/spec/v1
-oid sha256:ffd1d6cad98f80b698956f2f82b734a5bcbcc733791081a15fb601a7c27f351d
-size 43634
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+size 43762

ppo-LunarLander-v2/system_info.txt

@@ -2,7 +2,7 @@
 - Python: 3.10.12
 - Stable-Baselines3: 2.0.0a5
 - PyTorch: 2.3.0+cu121
-- GPU Enabled: False
+- GPU Enabled: True
 - Numpy: 1.25.2
 - Cloudpickle: 2.2.1
 - Gymnasium: 0.28.1

results.json

@@ -1 +1 @@
-{"mean_reward": 234.0051447, "std_reward": 86.30719542232112, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-06T13:11:46.610386"}
+{"mean_reward": 281.672551, "std_reward": 22.167170280812933, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-06T16:45:46.307209"}