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: 264.28 +/- 21.48
+      value: -157.29 +/- 80.04
       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.1679933261.PRACTIAARNB1437.10960.0

@@ -0,0 +1,3 @@
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+size 112022

model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f84606c643ffcfa1161e4485f3423ec27e92c21cde0ea7f482273816e8fcfe98
+size 42469

results.json

@@ -1 +1 @@
-{"mean_reward": 264.2826342677074, "std_reward": 21.484057973752872, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-23T18:59:51.918724"}
+{"env_id": "LunarLander-v2", "mean_reward": -157.2853561078635, "std_reward": 80.04231621778078, "n_evaluation_episodes": 10, "eval_datetime": "2023-03-27T13:08:57.829184"}