PPO Model v2

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 274.76 +/- 21.93
+      value: 289.65 +/- 21.34
       name: mean_reward
     task:
       type: reinforcement-learning

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 0x7fd30cabcca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd30cabcd30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd30cabcdc0>", "_build_mlp_extractor": "<function 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"Linux-5.10.60.1-microsoft-standard-WSL2-x86_64-with-glibc2.29 #1 SMP Wed Aug 25 23:20:18 UTC 2021", "Python": "3.8.10", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.0", "Gym": "0.21.0"}}
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ppo-LunarLander-v2.zip

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mNXRAlIaUUpRoFUu4aBZHQMky2Mw+MZR1fZQoaAZoCWgPQwhq+uyAq3ByQJSGlFKUaBVLpGgWR0DJMtoK8cuKdX2UKGgGaAloD0MI7WXbaWs7c0CUhpRSlGgVS6NoFkdAyTLcBGx2S3V9lChoBmgJaA9DCKlr7X2qUHJAlIaUUpRoFUu6aBZHQMky43u/k/91fZQoaAZoCWgPQwjH1ciuNBZwQJSGlFKUaBVLmGgWR0DJMuctI066dX2UKGgGaAloD0MIJxWNtb9jckCUhpRSlGgVS8BoFkdAyTLpnjABUHV9lChoBmgJaA9DCPoMqDfjJ3FAlIaUUpRoFUuqaBZHQMky7gq3Eyd1fZQoaAZoCWgPQwi1/wHWKpZxQJSGlFKUaBVLp2gWR0DJMvBZEDyOdX2UKGgGaAloD0MINjy9Uhblb0CUhpRSlGgVS6doFkdAyTL0189fTnV9lChoBmgJaA9DCG+5+rGJ4HFAlIaUUpRoFUuvaBZHQMky+y6tknV1ZS4="
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     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 375,
-    "n_steps": 1280,
+    "_n_updates": 1240,
+    "n_steps": 1024,
     "gamma": 0.999,
     "gae_lambda": 0.98,
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