oi!oi!oi!2

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -214.83 +/- 135.62
+      value: -590.31 +/- 70.44
       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 0x7f2bba77e280>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2bba77e310>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2bba77e3a0>", "_build_mlp_extractor": "<function 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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 0x7f61dfd65820>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f61dfd658b0>", "reset_noise": 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results.json

@@ -1 +1 @@
-{"mean_reward": -214.83204872501082, "std_reward": 135.62055453835762, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-09T14:57:14.315519"}
+{"mean_reward": -590.3144148023799, "std_reward": 70.43709040421535, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-12T11:57:16.145720"}

vlad-LunarLander-v2.zip

@@ -1,3 +1,3 @@
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-Python: 3.8.16
-Stable-Baselines3: 1.6.2
-PyTorch: 1.13.0+cu116
-GPU Enabled: True
-Numpy: 1.21.6
-Gym: 0.21.0
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+- Python: 3.8.16
+- Stable-Baselines3: 1.7.0
+- PyTorch: 1.13.1+cu116
+- GPU Enabled: True
+- Numpy: 1.21.6
+- Gym: 0.21.0