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: 263.60 +/- 23.36
+      value: -143.12 +/- 88.68
       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.1690354895.29d4b9e8c6bf.16809.0

@@ -0,0 +1,3 @@
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+oid sha256:abf5dcf68e1af153ee59d8b29be9ff67b3461cfe1731dc88ca472753873f5f20
+size 109724

model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c706c81696f37ceaeb74d41e1262ec54c4e2f63b8cbb791c8b01decf796f6a53
+size 42597

results.json

@@ -1 +1 @@
-{"mean_reward": 263.59566559999996, "std_reward": 23.364434007002426, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-07-05T19:30:08.279027"}
+{"env_id": "LunarLander-v2", "mean_reward": -143.11683853972534, "std_reward": 88.68189673454167, "n_evaluation_episodes": 10, "eval_datetime": "2023-07-26T07:02:21.603401"}