pushing model
Browse files- README.md +7 -2
- events.out.tfevents.1668612313.pop-os.1028360.0 +3 -0
- events.out.tfevents.1668612314.pop-os.1028360.1 +3 -0
- q_network.pth +2 -2
- replay.mp4 +0 -0
- videos/CartPole-v1__dqn__1__1668612313-eval/rl-video-episode-0.mp4 +0 -0
- videos/CartPole-v1__dqn__1__1668612313-eval/rl-video-episode-1.mp4 +0 -0
- videos/CartPole-v1__dqn__1__1668612313-eval/rl-video-episode-8.mp4 +0 -0
README.md
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type: CartPole-v1
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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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The model was trained by using [CleanRL](https://github.com/vwxyzjn/cleanrl) and the training code can be
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found [here](https://github.com/vwxyzjn/cleanrl/blob/master/cleanrl/dqn.py).
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# Hyperparameters
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```python
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'start_e': 1,
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'target_network_frequency': 500,
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'torch_deterministic': True,
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'total_timesteps':
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'track': False,
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'train_frequency': 10,
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'upload_model': True,
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type: CartPole-v1
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metrics:
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- type: mean_reward
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value: 65.80 +/- 13.11
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name: mean_reward
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verified: false
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---
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The model was trained by using [CleanRL](https://github.com/vwxyzjn/cleanrl) and the training code can be
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found [here](https://github.com/vwxyzjn/cleanrl/blob/master/cleanrl/dqn.py).
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## Command to reproduce the training
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```bash
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dqn.py --cuda False --save-model --upload-model --total-timesteps 500
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# Hyperparameters
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```python
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'start_e': 1,
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'target_network_frequency': 500,
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'torch_deterministic': True,
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'total_timesteps': 500,
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'track': False,
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'train_frequency': 10,
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'upload_model': True,
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events.out.tfevents.1668612313.pop-os.1028360.0
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size 1805
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events.out.tfevents.1668612314.pop-os.1028360.1
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q_network.pth
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size
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size 45927
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replay.mp4
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Binary file (10.8 kB). View file
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videos/CartPole-v1__dqn__1__1668612313-eval/rl-video-episode-0.mp4
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Binary file (12.6 kB). View file
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videos/CartPole-v1__dqn__1__1668612313-eval/rl-video-episode-1.mp4
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Binary file (8.84 kB). View file
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videos/CartPole-v1__dqn__1__1668612313-eval/rl-video-episode-8.mp4
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Binary file (10.8 kB). View file
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