Upload best PPO CarRacing-v0 agent (tuned with Optuna).

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
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+*.mp4 filter=lfs diff=lfs merge=lfs -text

CarRacing-v0-PPO-optuna.zip

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CarRacing-v0-PPO-optuna/_stable_baselines3_version

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+1.5.0

CarRacing-v0-PPO-optuna/policy.optimizer.pth

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CarRacing-v0-PPO-optuna/policy.pth

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CarRacing-v0-PPO-optuna/pytorch_variables.pth

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CarRacing-v0-PPO-optuna/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: 1.5.0
+PyTorch: 1.11.0+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

README.md

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+---
+library_name: stable-baselines3
+tags:
+- CarRacing-v0
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - metrics:
+    - type: mean_reward
+      value: -45.62 +/- 37.23
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: CarRacing-v0
+      type: CarRacing-v0
+---
+
+# **PPO** Agent playing **CarRacing-v0**
+This is a trained model of a **PPO** agent playing **CarRacing-v0**
+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
+
+...
+```

replay.mp4

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results.json

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+{"mean_reward": -45.61550070494413, "std_reward": 37.22652284086403, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-28T16:41:48.984680"}