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: 247.22 +/- 19.58
+      value: -31.01 +/- 15.31
       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.1684264402.mint1.27790.0

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+size 440076

model.pt

@@ -1,3 +1,3 @@
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-oid sha256:f66d84ce88a19e9059149667f1d0199011575bcdc4b2b32186e3d395f47dbee2
+oid sha256:1eef1e0a32462adc996f9d154a6f639b16547765f02412e3913d54ff27c006a0
 size 42817

results.json

@@ -1 +1 @@
-{"mean_reward": 247.21856178353596, "std_reward": 19.584040831544083, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-16T17:59:11.046524"}
+{"env_id": "LunarLander-v2", "mean_reward": -31.008843507859723, "std_reward": 15.30500132237572, "n_evaluation_episodes": 10, "eval_datetime": "2023-05-16T14:20:35.286139"}