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  1. README.md +6 -42
  2. hyperparameters.json +1 -0
  3. model.pt +2 -2
  4. replay.mp4 +0 -0
  5. results.json +1 -1
README.md CHANGED
@@ -1,13 +1,12 @@
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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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  - custom-implementation
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  - deep-rl-class
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  model-index:
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- - name: PPO
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  results:
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  - task:
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  type: reinforcement-learning
@@ -17,47 +16,12 @@ model-index:
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  type: CartPole-v1
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  metrics:
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  - type: mean_reward
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- value: 174.40 +/- 46.67
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  name: mean_reward
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  verified: false
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  ---
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- # PPO Agent Playing CartPole-v1
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-
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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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-
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- # Hyperparameters
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- ```python
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- {'f': '/root/.local/share/jupyter/runtime/kernel-fbe28e80-06f3-4c7b-af34-ae8d70502964.json'
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- 'exp_name': 'PPO_experiment_001'
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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': '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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- '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': 'ThomasSimonini/ppo-CartPole-v1'
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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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  tags:
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  - CartPole-v1
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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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  model-index:
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+ - name: ppo-CartPole-v1
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  results:
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  - task:
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  type: reinforcement-learning
 
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  type: CartPole-v1
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  metrics:
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  - type: mean_reward
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+ value: 500.00 +/- 0.00
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  name: mean_reward
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  verified: false
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  ---
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+ # **Reinforce** Agent playing **CartPole-v1**
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+ This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
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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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+ {"h_size": 16, "n_training_episodes": 1000, "n_evaluation_episodes": 10, "max_t": 1000, "gamma": 1.0, "lr": 0.01, "env_id": "CartPole-v1", "state_space": 4, "action_space": 2}
model.pt CHANGED
@@ -1,3 +1,3 @@
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  version https://git-lfs.github.com/spec/v1
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- oid sha256:7b16889548cc2a734518cfe265955eb0751aa930ce9f194ee84d3947d2fb9715
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- size 39909
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:b39f8c382b211832240c0f32d696b2a8b376a08b608f057ab5833465a7393798
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+ size 2579
replay.mp4 CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
 
results.json CHANGED
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- {"env_id": "CartPole-v1", "mean_reward": 174.4, "std_reward": 46.673761365461, "n_evaluation_episodes": 10, "eval_datetime": "2023-03-09T09:09:05.236698"}
 
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+ {"env_id": "CartPole-v1", "mean_reward": 500.0, "n_evaluation_episodes": 10, "eval_datetime": "2023-03-29T07:00:37.624017"}