Upload PPO LunarLander-v2 trained agent - omar

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -100.63 +/- 65.06
+      value: 258.25 +/- 19.52
       name: mean_reward
       verified: false
 ---

config.json

@@ -1 +1 @@
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https://github.com/DLR-RM/stable-baselines3/issues/284\n    ", "__init__": "<function ReplayBuffer.__init__ at 0x7f5560057d00>", "add": "<function ReplayBuffer.add at 0x7f5560057d90>", "sample": "<function ReplayBuffer.sample at 0x7f5560057e20>", "_get_samples": "<function ReplayBuffer._get_samples at 0x7f5560057eb0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f55601cae80>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "use_sde_at_warmup": false, "exploration_initial_eps": 1.0, "exploration_final_eps": 0.05, "exploration_fraction": 0.1, "target_update_interval": 625, "_n_calls": 62500, "max_grad_norm": 10, "exploration_rate": 0.05, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": 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-    "_n_updates": 15610,
+    "_n_updates": 124,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
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@@ -68,54 +69,31 @@
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         "n": "4",
         "start": "0",
         "_shape": [],
         "dtype": "int64",
-        "_np_random": "Generator(PCG64)"
+        "_np_random": null
     },
     "n_envs": 16,
-    "buffer_size": 1000000,
-    "batch_size": 32,
-    "learning_starts": 1000,
-    "tau": 1.0,
+    "n_steps": 2048,
     "gamma": 0.999,
-    "gradient_steps": 1,
-    "optimize_memory_usage": false,
-    "replay_buffer_class": {
-        ":type:": "<class 'abc.ABCMeta'>",
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-        "__module__": "stable_baselines3.common.buffers",
-        "__doc__": "\n    Replay buffer used in off-policy algorithms like SAC/TD3.\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        of the replay buffer which reduces by almost a factor two the memory used,\n        at a cost of more complexity.\n        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n        and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n        Cannot be used in combination with handle_timeout_termination.\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ",
-        "__init__": "<function ReplayBuffer.__init__ at 0x7f5560057d00>",
-        "add": "<function ReplayBuffer.add at 0x7f5560057d90>",
-        "sample": "<function ReplayBuffer.sample at 0x7f5560057e20>",
-        "_get_samples": "<function ReplayBuffer._get_samples at 0x7f5560057eb0>",
-        "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7f55601cae80>"
-    },
-    "replay_buffer_kwargs": {},
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