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atari_breakout_v0_dqn
bvk1ng/atari_breakout_v0_dqn
atari_breakout_v0_dqn is a reinforcement learning model from bvk1ng. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
The agent showcased in this space is trained using the Deep Q-Learning algorithm. The agent was trained for $$3500$$ episodes with a learning rate of $$0.00001$$ and an epsilon value that decreased linearly over time.
Access
Public
Updated Dec 28, 2023
Repo size
6.7 MB
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At a glance
- Task
- Reinforcement Learning
- License
- mit
- Access
- Public
- Created
- Dec 28, 2023
- Updated
- Dec 28, 2023
- SHA
- ecc42812
Model card
From the Hugging Face model README
Deep Q-Learning based Agent for Atari Breakout
The agent showcased in this space is trained using the Deep Q-Learning algorithm. The agent was trained for $$3500$$ episodes with a learning rate of $$0.00001$$ and an epsilon value that decreased linearly over time.
Usage
python main.py --model_folder <Name of the folder> --model_name <Name of the model> --save_video 1 --video_name <Name of the video file>
- Task
- Reinforcement Learning
- License
- mit
- Languages
- en
- Created
- Dec 28, 2023
- Updated
- Dec 28, 2023