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  1. README.md +27 -0
  2. hyperparameters.json +1 -0
  3. model.pt +3 -0
  4. replay.mp4 +0 -0
  5. results.json +1 -0
README.md ADDED
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+ ---
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+ tags:
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+ - reinforce
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+ - reinforcement-learning
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+ - custom-implementation
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+ - deep-rl-class
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+ - Pixelcopter-PLE-v0
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+ model-index:
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+ - name: Reinforce_Pixelcopter-PLE-v0
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+ results:
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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: Pixelcopter-PLE-v0
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+ type: Pixelcopter-PLE-v0
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+ metrics:
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+ - type: mean_reward
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+ value: 73.39 +/- 55.42
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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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+ # **Reinforce** Agent playing **Pixelcopter-PLE-v0**
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+ This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
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+ To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
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+
hyperparameters.json ADDED
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+ {"experiment_name": "Reinforce_Pixelcopter-PLE-v0", "device": "gpu", "policy": {"_target_": "lib.reinforce.Policy", "h_size": 64, "n_layers": 3}, "optimizer": {"_target_": "torch.optim.Adam", "lr": 0.0001}, "train_hparams": {"n_training_episodes": 100000, "max_steps": 10000, "gamma": 0.99, "print_every": 100}, "eval_hparams": {"n_eval_episodes": 10, "max_steps": 10000}, "model_path": "model.pt", "hparams_path": "hyperparameters.json", "video_path": "replay.mp4", "video_fps": 30, "train_env": {"_target_": "gym.make", "id": "Pixelcopter-PLE-v0"}, "eval_env": {"_target_": "gym.make", "id": "Pixelcopter-PLE-v0"}}
model.pt ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:e4fa07e8d0bf63c337a1d97f10f52cf93bae624fa3ffff167575c25fd508fc72
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+ size 22407
replay.mp4 ADDED
Binary file (38.4 kB). View file
 
results.json ADDED
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+ {"env_id": "Pixelcopter-PLE-v0", "mean_reward": 73.39, "std_reward": 55.415123387032175, "n_eval_episodes": 1000, "eval_datetime": "2023-01-10T16:20:02.636276"}