TokyoNights
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Push agent to the Hub
Browse files- README.md +40 -16
- logs/events.out.tfevents.1685590832.055ff09d50d9.13234.0 +3 -0
- 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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---
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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: -105.65 +/- 64.97
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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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{'exp_name': 'ppo'
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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': 50000
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'learning_rate': 0.00025
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'num_envs': 4
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'num_steps': 128
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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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'repo_id': 'TokyoNights/ppo-LunarLander-v2'
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'batch_size': 512
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'minibatch_size': 128}
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```
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logs/events.out.tfevents.1685590832.055ff09d50d9.13234.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:93945e62ac4feff87317368a22baa35f80c9b94675723efa4ff3c24dbd2816d0
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size 110600
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model.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:73a6748cee3444894102db06ecc10eb21168fdd67939c4d5bf3a05379f763ac8
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size 42469
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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": -105.6477817520744, "std_reward": 64.97044482284214, "n_evaluation_episodes": 10, "eval_datetime": "2023-06-01T03:41:09.290071"}
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