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A2C-CartPole-v1.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e744faeb8839eebc3667cdcd3a2167e93af44ec558f6d2c04c73c225459f024d
+size 95212

README.md

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+---
+tags:
+- CartPole-v1
+- reinforcement-learning
+model-index:
+- name: A2C-CartPole-v1
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: CartPole-v1
+      type: CartPole-v1
+    metrics:
+    - type: mean_reward
+      value: 500.00 +/- 0.00
+      name: mean_reward
+      verified: false
+---
+
+  # **Q-Learning** Agent playing1 **CartPole-v1**
+  This is a trained model of a **Q-Learning** agent playing **CartPole-v1** .
+
+  ## Usage
+
+  ```python
+  
+  model = load_from_hub(repo_id="utyug1/A2C-CartPole-v1", filename="model.pt")
+
+  ```
+  

hyperparameters.json

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+{"policy": "MlpPolicy", "env": "CartPole-v1", "gamma": 0.0037857070275125987, "max_grad_norm": 1.068991897259356, "exponent_n_steps": 9, "learning_rate": 0.0061663610638304405, "net_arch": "small", "activation_fn": "tanh", "n_training_timesteps": 20000, "n_eval_episodes": 10}

results.json

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+{"env_id": "CartPole-v1", "mean_reward": 500.0, "std_reward": 0.0, "n_eval_episodes": 10, "eval_datetime": "2022-12-26T23:12:39.088946"}