Push agent to the Hub
Browse files- README.md +37 -15
- model.pt +3 -0
- replay.mp4 +0 -0
- results.json +1 -1
README.md
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---
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library_name: stable-baselines3
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tags:
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- LunarLander-v2
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- deep-reinforcement-learning
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- reinforcement-learning
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model-index:
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- name: PPO
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results:
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type: LunarLander-v2
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metrics:
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- type: mean_reward
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value:
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name: mean_reward
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verified: false
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---
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#
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This is a trained model of a **PPO** agent playing **LunarLander-v2**
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using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
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TODO: Add your code
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```python
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---
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tags:
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- LunarLander-v2
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- ppo
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- deep-reinforcement-learning
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- reinforcement-learning
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- custom-implementation
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- deep-rl-course
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model-index:
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- name: PPO
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results:
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type: LunarLander-v2
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metrics:
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- type: mean_reward
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value: -216.03 +/- 122.28
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name: mean_reward
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verified: false
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---
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# PPO Agent Playing LunarLander-v2
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This is a trained model of a PPO agent playing LunarLander-v2.
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# Hyperparameters
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```python
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{'f': '/root/.local/share/jupyter/runtime/kernel-a5723393-974b-45e0-9a2d-ab8b647dddaf.json'
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'exp_name': 'ppo.py'
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'seed': 1
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'torch_deterministic': True
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'cuda': True
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'track': False
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'wandb_project_name': 'cleanRL'
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'wandb_entity': None
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'capture_video': False
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'env_id': 'LunarLander-v2'
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'total_timesteps': 1000000
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'learning_rate': 0.001
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'num_envs': 4
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'num_steps': 200
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'anneal_lr': True
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'gae': True
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'gamma': 0.99
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'gae_lambda': 0.95
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'num_minibatches': 4
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'update_epochs': 4
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'norm_adv': True
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'clip_coef': 0.2
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'clip_vloss': True
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'ent_coef': 0.01
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'vf_coef': 0.5
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'max_grad_norm': 0.5
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'target_kl': None}
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```
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model.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:8e94231d0e989bfddaa4cf26c94c968eda65facd7fdf2499dbb1f5f3c05880ae
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size 43026
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replay.mp4
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results.json
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{"
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{"env_id": "LunarLander-v2", "mean_reward": -216.02737469684948, "std_reward": 122.28420148243518, "n_evaluation_episodes": 10, "eval_datetime": "2024-03-26T15:16:28.121000"}
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