Upload PPO MontezumaRevenge-v5 trained agent

README.md

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+---
+library_name: stable-baselines3
+tags:
+- ALE/MontezumaRevenge-v5
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: ALE/MontezumaRevenge-v5
+      type: ALE/MontezumaRevenge-v5
+    metrics:
+    - type: mean_reward
+      value: 0.00 +/- 0.00
+      name: mean_reward
+      verified: false
+---
+
+# **PPO** Agent playing **ALE/MontezumaRevenge-v5**
+This is a trained model of a **PPO** agent playing **ALE/MontezumaRevenge-v5**
+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-MontezumaRevenge.zip

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+size 157659793

ppo-MontezumaRevenge/_stable_baselines3_version

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+1.6.2

ppo-MontezumaRevenge/policy.optimizer.pth

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+size 103306233

ppo-MontezumaRevenge/policy.pth

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+size 51652353

ppo-MontezumaRevenge/pytorch_variables.pth

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+size 431

ppo-MontezumaRevenge/system_info.txt

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+OS: Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
+Python: 3.8.16
+Stable-Baselines3: 1.6.2
+PyTorch: 1.13.0+cu116
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

results.json

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+{"mean_reward": 0.0, "std_reward": 0.0, "is_deterministic": false, "n_eval_episodes": 10, "eval_datetime": "2022-12-26T23:26:05.292103"}