Async vec, 250000, not looking too hot on my end, lets see what their eval looks like

README.md

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+---
+tags:
+- LunarLander-v2
+- ppo
+- deep-reinforcement-learning
+- reinforcement-learning
+- custom-implementation
+- deep-rl-course
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: -40.01 +/- 76.54
+      name: mean_reward
+      verified: false
+---
+
+  # PPO Agent Playing LunarLander-v2
+
+  This is a trained model of a PPO agent playing LunarLander-v2.
+
+  # Hyperparameters
+  ```python
+  {'seed': 42069
+'capture_video': True
+'learning_rate': 0.0003
+'eps': 1e-05
+'num_steps': 1024
+'total_timesteps': 2500000
+'anneal_lr': True
+'gae': True
+'gamma': 0.999
+'gae_lambda': 0.95
+'update_epochs': 4
+'num_minibatches': 4
+'clip_coef': 0.2
+'norm_adv': True
+'clip_vloss': True
+'ent_coef': 0.01
+'vf_coef': 0.5
+'max_grad_norm': 0.5
+'target_kl': None
+'batch_size': 8192
+'minibatch_size': 2048
+'env_id': 'LunarLander-v2'}
+  ```
+  

model.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c48f835496c25eed53d1aa0b6f49f9bb054f967a8798e4fa033bcde47ad4d937
+size 42898

results.json

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+{"env_id": "LunarLander-v2", "mean_reward": -40.01137940863879, "std_reward": 76.53863901313943, "n_evaluation_episodes": 10, "eval_datetime": "2024-10-13T10:21:51.245996"}