Test simple 2

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -126.23 +/- 28.98
+      value: 281.00 +/- 14.97
       name: mean_reward
       verified: false
 ---

config.json

@@ -1 +1 @@
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If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). 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 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 0x7f0ff591e3a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0ff591e430>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0ff591e4c0>", "_build_mlp_extractor": "<function 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     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 10,
+    "_n_updates": 1240,
     "n_steps": 1024,
     "gamma": 0.999,
     "gae_lambda": 0.98,

lunarLanderSimple/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2109d39e897b32f69e73446b78a7b9a973edb87f750f213a20175a0cbb1fa7ca
+oid sha256:4df74a29a7ffae0d6026d91b866786e3caf33b5e0b496687a29758f9e1943ffd
 size 87929

lunarLanderSimple/policy.pth

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results.json

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-{"mean_reward": -126.22588100484572, "std_reward": 28.975456932092357, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-19T18:36:03.669116"}
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