Push agent to the Hub

README.md

@@ -1,10 +1,11 @@
 ---
-library_name: stable-baselines3
 tags:
 - LunarLander-v2
+- ppo
 - deep-reinforcement-learning
 - reinforcement-learning
-- stable-baselines3
+- custom-implementation
+- deep-rl-course
 model-index:
 - name: PPO
   results:
@@ -16,22 +17,14 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 268.57 +/- 17.31
+      value: -161.93 +/- 86.34
       name: mean_reward
       verified: false
 ---
 
-# **PPO** Agent playing **LunarLander-v2**
-This is a trained model of a **PPO** agent playing **LunarLander-v2**
-using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+  # PPO Agent Playing LunarLander-v2
 
-## Usage (with Stable-baselines3)
-TODO: Add your code
+  This is a trained model of a PPO agent playing LunarLander-v2.
 
-
-```python
-from stable_baselines3 import ...
-from huggingface_sb3 import load_from_hub
-
-...
-```
+  # Hyperparameters
+  

logs/events.out.tfevents.1690271036.5eab1ac89a12.6761.0

@@ -0,0 +1,3 @@
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+size 109730

model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:550b0cafaf3330128b441489af3e3c3b95dccc25850f4290a4629da912a8c1ec
+size 42597

results.json

@@ -1 +1 @@
-{"mean_reward": 268.57386327092155, "std_reward": 17.312155450870648, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-07-19T03:39:34.075455"}
+{"env_id": "LunarLander-v2", "mean_reward": -161.9288273758229, "std_reward": 86.34488374446182, "n_evaluation_episodes": 10, "eval_datetime": "2023-07-25T07:44:44.731624"}