kucharskipj commited on
Commit
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1 Parent(s): dfab84b

Upload PPO LunarLander-v2 trained agent

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README.md CHANGED
@@ -16,7 +16,7 @@ model-index:
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  type: LunarLander-v2
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  metrics:
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  - type: mean_reward
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- value: 230.43 +/- 48.77
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  name: mean_reward
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  verified: false
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  ---
 
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  type: LunarLander-v2
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  metrics:
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  - type: mean_reward
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+ value: 282.83 +/- 9.06
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  name: mean_reward
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  verified: false
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  ---
config.json CHANGED
@@ -1 +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 0x7f1542986710>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f15429867a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1542986830>", 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"action_noise": null, "start_time": 1682842938019537442, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": 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+ "start_time": 1682844642540495802,
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