Push agent to the Hub

README.md

@@ -1,10 +1,11 @@
 ---
-library_name: stable-baselines3
 tags:
-- LunarLander-v2
+- CartPole-v1
+- ppo
 - deep-reinforcement-learning
 - reinforcement-learning
-- stable-baselines3
+- custom-implementation
+- deep-rl-course
 model-index:
 - name: PPO
   results:
@@ -12,26 +13,49 @@ model-index:
       type: reinforcement-learning
       name: reinforcement-learning
     dataset:
-      name: LunarLander-v2
-      type: LunarLander-v2
+      name: CartPole-v1
+      type: CartPole-v1
     metrics:
     - type: mean_reward
-      value: 252.05 +/- 23.51
+      value: 254.00 +/- 124.01
       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 CartPole-v1
 
-## Usage (with Stable-baselines3)
-TODO: Add your code
+  This is a trained model of a PPO agent playing CartPole-v1.
 
-
-```python
-from stable_baselines3 import ...
-from huggingface_sb3 import load_from_hub
-
-...
-```
+  # Hyperparameters
+  ```python
+  {'exp_name': 'ppo'
+'seed': 1
+'torch_deterministic': True
+'cuda': True
+'track': False
+'wandb_project_name': 'cleanRL'
+'wandb_entity': None
+'capture_video': False
+'env_id': 'CartPole-v1'
+'total_timesteps': 50000
+'learning_rate': 0.00025
+'num_envs': 4
+'num_steps': 128
+'anneal_lr': True
+'gae': True
+'gamma': 0.99
+'gae_lambda': 0.95
+'num_minibatches': 4
+'update_epochs': 4
+'norm_adv': True
+'clip_coef': 0.2
+'clip_vloss': True
+'ent_coef': 0.01
+'vf_coef': 0.5
+'max_grad_norm': 0.5
+'target_kl': None
+'repo_id': 'Yureeh/ppo-LunarLander-v2'
+'batch_size': 512
+'minibatch_size': 128}
+  ```
+  

logs/events.out.tfevents.1680795117.DESKTOP-G8JS4QL.45460.0

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+size 102536

model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3585dd9f67771c9d2d9cc79cae73f556cf671b9076ed444c6d23f82e23a9c27c
+size 39909

results.json

@@ -1 +1 @@
-{"mean_reward": 252.05289109204946, "std_reward": 23.51007539855621, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-23T14:14:29.945163"}
+{"env_id": "CartPole-v1", "mean_reward": 254.0, "std_reward": 124.01290255453262, "n_evaluation_episodes": 10, "eval_datetime": "2023-04-06T17:32:10.537438"}