Push Reinforce agent to the Hub
Browse files- README.md +7 -7
- logs/events.out.tfevents.1662590309.nt-pc.11485.0 +3 -0
- model.pt +2 -2
- replay.mp4 +0 -0
- results.json +1 -1
README.md
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---
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tags:
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- ppo
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- deep-reinforcement-learning
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- reinforcement-learning
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results:
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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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task:
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type: reinforcement-learning
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name: reinforcement-learning
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dataset:
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name:
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type:
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---
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# PPO Agent Playing
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This is a trained model of a PPO agent playing
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To learn to code your own PPO agent and train it Unit 8 of the Deep Reinforcement Learning Class: https://github.com/huggingface/deep-rl-class/tree/main/unit8
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# Hyperparameters
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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': '
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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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---
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tags:
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- CartPole-v1
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- ppo
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- deep-reinforcement-learning
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- reinforcement-learning
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results:
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- metrics:
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- type: mean_reward
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value: 166.00 +/- 55.22
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name: mean_reward
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task:
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type: reinforcement-learning
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name: reinforcement-learning
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dataset:
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name: CartPole-v1
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type: CartPole-v1
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---
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# PPO Agent Playing CartPole-v1
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This is a trained model of a PPO agent playing CartPole-v1.
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To learn to code your own PPO agent and train it Unit 8 of the Deep Reinforcement Learning Class: https://github.com/huggingface/deep-rl-class/tree/main/unit8
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# Hyperparameters
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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': 'CartPole-v1'
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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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logs/events.out.tfevents.1662590309.nt-pc.11485.0
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version https://git-lfs.github.com/spec/v1
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size 116432
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model.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:615063e1c901e83f6483e95e25739786a9c37a58a7e03e55a1c56f95f7e1493a
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size 40129
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replay.mp4
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results.json
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{"env_id": "
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{"env_id": "CartPole-v1", "mean_reward": 166.0, "std_reward": 55.22499434133063, "n_evaluation_episodes": 10, "eval_datetime": "2022-09-08T05:38:57.571085"}
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