trained model 2e+06 steps

.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

LunarLander-v2-ppo.zip

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LunarLander-v2-ppo/_stable_baselines3_version

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+1.4.0

LunarLander-v2-ppo/data

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LunarLander-v2-ppo/policy.optimizer.pth

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+size 84637

LunarLander-v2-ppo/policy.pth

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LunarLander-v2-ppo/pytorch_variables.pth

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LunarLander-v2-ppo/system_info.txt

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+OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
+Python: 3.7.13
+Stable-Baselines3: 1.4.0
+PyTorch: 1.11.0+cu113
+GPU Enabled: False
+Numpy: 1.21.6
+Gym: 0.17.3

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: 269.09 +/- 65.43
+      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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replay.mp4

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+version https://git-lfs.github.com/spec/v1
+oid sha256:24788f47f53ed16adde0e518357cf34853a76e0d8f438e1301c86371d4aa4dd8
+size 183510

results.json

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+{"mean_reward": 269.09257489999993, "std_reward": 65.42859854148979, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-13T22:49:35.814497"}