cleanrl / BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1

huggingface.co
Total runs: 0
24-hour runs: 0
7-day runs: 0
30-day runs: 0
Model's Last Updated: January 04 2023
reinforcement-learning

Introduction of BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1

Model Details of BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1

(CleanRL) PPO Agent Playing BeamRider-v5

This is a trained model of a PPO agent playing BeamRider-v5. The model was trained by using CleanRL and the most up-to-date training code can be found here .

Get Started

To use this model, please install the cleanrl package with the following command:

pip install "cleanrl[ppo_atari_envpool_async_jax_scan_impalanet_machado]"
python -m cleanrl_utils.enjoy --exp-name ppo_atari_envpool_async_jax_scan_impalanet_machado --env-id BeamRider-v5

Please refer to the documentation for more detail.

Command to reproduce the training
curl -OL https://huggingface.co/cleanrl/BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1/raw/main/ppo_atari_envpool_async_jax_scan_impalanet_machado.py
curl -OL https://huggingface.co/cleanrl/BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1/raw/main/pyproject.toml
curl -OL https://huggingface.co/cleanrl/BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1/raw/main/poetry.lock
poetry install --all-extras
python ppo_atari_envpool_async_jax_scan_impalanet_machado.py --track --wandb-project-name envpool-atari --save-model --upload-model --hf-entity cleanrl --env-id BeamRider-v5 --seed 1

Hyperparameters

{'anneal_lr': True,
 'async_batch_size': 16,
 'batch_size': 2048,
 'capture_video': False,
 'clip_coef': 0.1,
 'cuda': True,
 'ent_coef': 0.01,
 'env_id': 'BeamRider-v5',
 'exp_name': 'ppo_atari_envpool_async_jax_scan_impalanet_machado',
 'gae': True,
 'gae_lambda': 0.95,
 'gamma': 0.99,
 'hf_entity': 'cleanrl',
 'learning_rate': 0.00025,
 'max_grad_norm': 0.5,
 'minibatch_size': 1024,
 'norm_adv': True,
 'num_envs': 64,
 'num_minibatches': 2,
 'num_steps': 32,
 'num_updates': 24414,
 'save_model': True,
 'seed': 1,
 'target_kl': None,
 'torch_deterministic': True,
 'total_timesteps': 50000000,
 'track': True,
 'update_epochs': 2,
 'upload_model': True,
 'vf_coef': 0.5,
 'wandb_entity': None,
 'wandb_project_name': 'envpool-atari'}

Runs of cleanrl BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 on huggingface.co

0
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
0
30-day runs

More Information About BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 huggingface.co Model

BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 huggingface.co

BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 huggingface.co is an AI model on huggingface.co that provides BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1's model effect (), which can be used instantly with this cleanrl BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 model. huggingface.co supports a free trial of the BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 model, and also provides paid use of the BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1. Support call BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 model through api, including Node.js, Python, http.

BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 huggingface.co Url

https://huggingface.co/cleanrl/BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1

cleanrl BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 online free

BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 huggingface.co is an online trial and call api platform, which integrates BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1's modeling effects, including api services, and provides a free online trial of BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1, you can try BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 online for free by clicking the link below.

cleanrl BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 online free url in huggingface.co:

https://huggingface.co/cleanrl/BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1

BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 install

BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 is an open source model from GitHub that offers a free installation service, and any user can find BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 on GitHub to install. At the same time, huggingface.co provides the effect of BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 install, users can directly use BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 install url in huggingface.co:

https://huggingface.co/cleanrl/BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1

Url of BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1

BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 huggingface.co Url

Provider of BeamRider-v5-ppo_atari_envpool_async_jax_scan_impalanet_machado-seed1 huggingface.co

cleanrl
ORGANIZATIONS

Other API from cleanrl