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ppo-MountainCar-v0
Francesco-A/ppo-MountainCar-v0
ppo-MountainCar-v0 is a reinforcement learning model from Francesco-A. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product. It is set up for stable-baselines3.
This is a trained model of a PPO agent playing MountainCar-v0 using the stable-baselines3 library.
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.mp4214 KB · 42%
At a glance
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Access
- Public
- Created
- Mar 3, 2024
- Updated
- Mar 3, 2024
- SHA
- a47abee2
Model card
From the Hugging Face model README
PPO Agent playing MountainCar-v0
This is a trained model of a PPO agent playing MountainCar-v0 using the stable-baselines3 library.
Model Details
- Model Name: ppo-MountainCar-v0
- Model Type: Proximal Policy Optimization (PPO)
- Policy Architecture: MultiLayerPerceptron (MLPPolicy)
- Environment: MountainCar-v0
- Training Data: The model was trained using three consecutive training sessions:
- First training session: Total timesteps = 1,000,000
- Second training session: Total timesteps = 500,000
- Third training session: Total timesteps = 500,000
Model Parameters
- n_steps: 2048
- batch_size: 64
- n_epochs: 8
- gamma: 0.999
- gae_lambda: 0.95
- ent_coef: 0.01
- max_grad_norm: 0.5
- Verbose: Enabled (Verbose level = 1)
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Created
- Mar 3, 2024
- Updated
- Mar 3, 2024