Upload PPO LunarLander-v2 trained agent

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- CarRacing-v0
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: CarRacing-v0
+      type: CarRacing-v0
+    metrics:
+    - type: mean_reward
+      value: -54.33 +/- 5.70
+      name: mean_reward
+      verified: false
+---
+
+# **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
+
+...
+```

ppo-CarRacing-v1.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:50460e1e6af47b3ddaaba77164b445630ccf1fe7d0b1bd271311c6a84248c853
+size 42894740

ppo-CarRacing-v1/_stable_baselines3_version

@@ -0,0 +1 @@
+1.7.0

ppo-CarRacing-v1/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cf6cd5c8f7a91bdb13626007a7c7c3e9474c8d7ae6c0c6d27988ba8d46354563
+size 28391536

ppo-CarRacing-v1/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e81fb41d55dbaa22825415aaef1e40102668d4adeac726568319a45c609e52f1
+size 14195134

ppo-CarRacing-v1/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

ppo-CarRacing-v1/system_info.txt

@@ -0,0 +1,7 @@
+- OS: Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
+- Python: 3.8.10
+- Stable-Baselines3: 1.7.0
+- PyTorch: 1.13.1+cu116
+- GPU Enabled: True
+- Numpy: 1.21.6
+- Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": -54.330694230645896, "std_reward": 5.699226950966611, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-29T03:44:47.423355"}