First version from course

.gitattributes

@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text

PPO-MlpPolicy-LunarLander-v2.zip

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PPO-MlpPolicy-LunarLander-v2/_stable_baselines3_version

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PPO-MlpPolicy-LunarLander-v2/data

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PPO-MlpPolicy-LunarLander-v2/policy.optimizer.pth

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PPO-MlpPolicy-LunarLander-v2/policy.pth

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+size 43201

PPO-MlpPolicy-LunarLander-v2/pytorch_variables.pth

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PPO-MlpPolicy-LunarLander-v2/system_info.txt

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+OS: Linux-5.13.0-40-generic-x86_64-with-glibc2.31 #45~20.04.1-Ubuntu SMP Mon Apr 4 09:38:31 UTC 2022
+Python: 3.9.12
+Stable-Baselines3: 1.5.0
+PyTorch: 1.11.0+cu102
+GPU Enabled: True
+Numpy: 1.22.3
+Gym: 0.21.0

README.md

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+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 234.34 +/- 20.06
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+---
+
+  # **PPO** Agent playing **LunarLander-v2**
+  This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+  
+  ## Usage (with Stable-baselines3)
+  TODO: Add your code
+  

config.json

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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 0x7fa2eb024af0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa2eb024b80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa2eb024c10>", "_build_mlp_extractor": "<function 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replay.mp4

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+version https://git-lfs.github.com/spec/v1
+oid sha256:cdf19402e35870851e827f8576bc234bd9fcd9dfe51703dec4e6f43176a6b28c
+size 253018

results.json

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