Pandita-IA
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Browse files- README.md +16 -40
- replay.mp4 +0 -0
- results.json +1 -1
README.md
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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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- 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:
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name: mean_reward
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verified: false
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---
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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': 'Pandita-IA/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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---
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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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- stable-baselines3
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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: 276.93 +/- 17.41
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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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using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
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## Usage (with Stable-baselines3)
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TODO: Add your code
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```python
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from stable_baselines3 import ...
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from huggingface_sb3 import load_from_hub
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...
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```
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replay.mp4
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Binary files a/replay.mp4 and b/replay.mp4 differ
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results.json
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{"
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{"mean_reward": 276.9320266870259, "std_reward": 17.406463605708343, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-21T11:50:49.915166"}
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