commit with 1 000 000 iterations, but without discount (gamma 1) from unit1 notebook from local jupyterhub

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 287.83 +/- 13.47
+      value: 284.65 +/- 12.11
       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 0x7fcef6216d30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcef6216dc0>", "reset_noise": 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"
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     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 1240,
+    "_n_updates": 1488,
     "n_steps": 2048,
     "gamma": 1,
     "gae_lambda": 0.98,

ppo-LunarLander-g1/policy.optimizer.pth

@@ -1,3 +1,3 @@
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ppo-LunarLander-g1/policy.pth

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results.json

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