Initial model commit

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 279.18 +/- 19.05
+      name: mean_reward
+      verified: false
+---
+
+# **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
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

config.json

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It allows to keep variance\n        above zero and prevent it from growing too fast. 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ppo-LunarLander-v2.zip

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+oid sha256:e3d098bb79597b70f65638c632c4cc379b61704946def15f65e171d31fb6733a
+size 147763

ppo-LunarLander-v2/_stable_baselines3_version

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+2.0.0a5

ppo-LunarLander-v2/data

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+{
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+- Python: 3.11.7
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.3.1+cu118
+- GPU Enabled: True
+- Numpy: 1.26.4
+- Cloudpickle: 3.1.0
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.26.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 279.1833564416584, "std_reward": 19.045381240173704, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-01-05T16:38:25.862052"}