Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 171.71 +/- 108.31
+      value: 242.84 +/- 62.90
       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 0x7f951859fe50>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f951859fee0>", "reset_noise": 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"
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mckdMQJSGlFKUaBVLtGgWR0ClYP6QeV9ndX2UKGgGaAloD0MI/89hvvzpc0CUhpRSlGgVTQwBaBZHQKVh/QcghbJ1fZQoaAZoCWgPQwjDK0me6+hxQJSGlFKUaBVL/mgWR0ClYvdld1MedX2UKGgGaAloD0MITMRb55+2cECUhpRSlGgVS/5oFkdApWT6+tbLU3V9lChoBmgJaA9DCE30+Sijj25AlIaUUpRoFUvvaBZHQKVl89Ba9sd1fZQoaAZoCWgPQwixM4XOa2BJQJSGlFKUaBVLxmgWR0ClZr+WfK6ndX2UKGgGaAloD0MI6NzteumycUCUhpRSlGgVS/JoFkdApWe6ePJaJXV9lChoBmgJaA9DCIQu4dDboHBAlIaUUpRoFU0HAWgWR0ClacAZsKsudX2UKGgGaAloD0MI/FWA7/Z5cECUhpRSlGgVS/RoFkdApWrHyAhB7nV9lChoBmgJaA9DCLqilBBsjHJAlIaUUpRoFUvZaBZHQKVrpPci4ax1fZQoaAZoCWgPQwjs2t5uyQtyQJSGlFKUaBVL5mgWR0ClbJUX531SdWUu"
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     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 4890,
-    "n_steps": 2048,
-    "gamma": 0.99,
-    "gae_lambda": 0.95,
-    "ent_coef": 0.0,
+    "_n_updates": 3908,
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-- Python: 3.8.10
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