Hyper Parameter Tuning

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 258.25 +/- 17.09
+      value: 272.15 +/- 13.38
       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 0x7f3962f7c310>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3962f7c3a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3962f7c430>", "_build_mlp_extractor": "<function 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dU3FAlIaUUpRoFU0XAWgWR0CTq/WCmMwUdX2UKGgGaAloD0MIqUpbXKPVckCUhpRSlGgVTUQBaBZHQJOsU7CBPKx1fZQoaAZoCWgPQwjIQnQInH9uQJSGlFKUaBVNPQFoFkdAk61bDMvAXXV9lChoBmgJaA9DCIm1+BSA0W9AlIaUUpRoFU0aAWgWR0CTrYifQKKHdX2UKGgGaAloD0MIzGJi8zHFckCUhpRSlGgVTRQBaBZHQJOtwlyBCld1fZQoaAZoCWgPQwi/nq9ZrhtvQJSGlFKUaBVNNAFoFkdAk63iDEm6XnV9lChoBmgJaA9DCBk3NdB87HFAlIaUUpRoFU0vAWgWR0CTrg1CPZIydX2UKGgGaAloD0MILGNDN3sJcUCUhpRSlGgVTSYBaBZHQJOuvYcvM8p1fZQoaAZoCWgPQwhUUiegiRhLQJSGlFKUaBVL4WgWR0CTrsweeWfLdX2UKGgGaAloD0MI9pmzPmWPcUCUhpRSlGgVTUIBaBZHQJOwjrKNhmZ1fZQoaAZoCWgPQwjXhopxfnZyQJSGlFKUaBVNBgFoFkdAk7EEF0PpZHV9lChoBmgJaA9DCEaXN4erxXFAlIaUUpRoFU1EAWgWR0CTsb55JK8MdWUu"
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     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 248,
-    "n_steps": 1024,
+    "_n_updates": 310,
+    "n_steps": 2048,
     "gamma": 0.999,
-    "gae_lambda": 0.98,
+    "gae_lambda": 0.95,
     "ent_coef": 0.01,
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