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README.md

@@ -1,9 +1,10 @@
 ---
 tags:
-- Taxi-v3
-- q-learning
+- CartPole-v1
+- reinforce
 - reinforcement-learning
 - custom-implementation
+- deep-rl-class
 model-index:
 - name: my_rl_journey
   results:
@@ -11,26 +12,16 @@ model-index:
       type: reinforcement-learning
       name: reinforcement-learning
     dataset:
-      name: Taxi-v3
-      type: Taxi-v3
+      name: CartPole-v1
+      type: CartPole-v1
     metrics:
     - type: mean_reward
-      value: 7.56 +/- 2.71
+      value: 481.50 +/- 55.50
       name: mean_reward
       verified: false
 ---
 
-# **MlpPolicy** Agent playing **LunarLander-v2**
-This is a trained model of a **MlpPolicy** agent playing **LunarLander-v2**
-using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
-
-## Usage (with Stable-baselines3)
-TODO: Add your code
-
-
-```python
-from stable_baselines3 import ...
-from huggingface_sb3 import load_from_hub
-
-...
-```
+  # **Reinforce** Agent playing **CartPole-v1**
+  This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
+  To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
+  

hyperparameters.json

@@ -0,0 +1 @@
+{"h_size": 16, "n_training_episodes": 1000, "n_evaluation_episodes": 10, "max_t": 1000, "gamma": 1.0, "lr": 0.01, "env_id": "CartPole-v1", "state_space": 4, "action_space": 2}

model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:72eaf68aecd1cfe535c74d7106bd703631fd75653b76ffa8a6ba853c8fa6e58c
+size 3264

results.json

@@ -1 +1 @@
-{"env_id": "Taxi-v3", "mean_reward": 7.56, "n_eval_episodes": 100, "eval_datetime": "2024-07-06T22:06:49.719365"}
+{"env_id": "CartPole-v1", "mean_reward": 481.5, "n_evaluation_episodes": 10, "eval_datetime": "2024-07-10T05:57:41.966626"}