Upload PPO CarRacing-v2 trained agent

README.md

@@ -0,0 +1,37 @@
+---
+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: -42.45 +/- 55.15
+      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

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e0cab417667604c57096f92d530d7e9092140ac3f64a3bf0b2a1794215ba36e5
+size 43339062

ppo-CarRacing-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+2.0.0a5

ppo-CarRacing-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:92e89f0b9cae208c563bcab754cab77683ec2358bad23503d80ebe9b547d088e
+size 28391969

ppo-CarRacing-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fe988369850db54b045134b1bc9f3c44ee42f02cf0863331e21a69c96f712200
+size 14195503

ppo-CarRacing-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
+size 864

ppo-CarRacing-v2/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.4.1+cu121
+- GPU Enabled: True
+- Numpy: 1.26.4
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": -42.4505716, "std_reward": 55.15162590932487, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-09-25T09:27:59.260683"}