PPO model trained in CarRacing-v2.

README.md

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+---
+library_name: stable-baselines3
+tags:
+- CarRacing-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: CarRacing-v2
+      type: CarRacing-v2
+    metrics:
+    - type: mean_reward
+      value: -87.60 +/- 13.57
+      name: mean_reward
+      verified: false
+---
+
+# **PPO** Agent playing **CarRacing-v2**
+This is a trained model of a **PPO** agent playing **CarRacing-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
+
+...
+```

ppo-CarRacing-v2.zip

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+size 42752574

ppo-CarRacing-v2/_stable_baselines3_version

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+2.0.0a5

ppo-CarRacing-v2/policy.optimizer.pth

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ppo-CarRacing-v2/policy.pth

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+size 14195503

ppo-CarRacing-v2/pytorch_variables.pth

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+size 864

ppo-CarRacing-v2/system_info.txt

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+- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
+- Python: 3.11.11
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.5.1+cu121
+- GPU Enabled: True
+- Numpy: 1.26.4
+- Cloudpickle: 3.1.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

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+{"mean_reward": -87.6002834, "std_reward": 13.567575703097006, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-01-26T22:06:46.209547"}