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pfunk/CartPole-v1-DQN_baseline_VIDEO-seed1
CartPole-v1-DQN_baseline_VIDEO-seed1 is a reinforcement learning model from pfunk. 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 cleanrl.
This is a trained model of a DQN agent playing CartPole-v1. The model was trained by using CleanRL and the most up-to-date training code can be found here.
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Updated Feb 17, 2023
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From the Hugging Face model README
This is a trained model of a DQN agent playing CartPole-v1. The model was trained by using CleanRL and the most up-to-date training code can be found here.
To use this model, please install the cleanrl package with the following command:
pip install "cleanrl[DQN_baseline_VIDEO]"
python -m cleanrl_utils.enjoy --exp-name DQN_baseline_VIDEO --env-id CartPole-v1
Please refer to the documentation for more detail.
curl -OL https://huggingface.co/pfunk/CartPole-v1-DQN_baseline_VIDEO-seed1/raw/main/dqn.py
curl -OL https://huggingface.co/pfunk/CartPole-v1-DQN_baseline_VIDEO-seed1/raw/main/pyproject.toml
curl -OL https://huggingface.co/pfunk/CartPole-v1-DQN_baseline_VIDEO-seed1/raw/main/poetry.lock
poetry install --all-extras
python dqn.py --exp-name DQN_baseline_VIDEO --track --wandb-entity pfunk --wandb-project-name dqpn --save-model true --upload-model true --hf-entity pfunk --env-id CartPole-v1 --seed 1 --total-timesteps 100000
{'batch_size': 128,
'buffer_size': 10000,
'capture_video': False,
'cuda': True,
'end_e': 0.05,
'env_id': 'CartPole-v1',
'exp_name': 'DQN_baseline_VIDEO',
'exploration_fraction': 0.5,
'gamma': 0.99,
'hf_entity': 'pfunk',
'learning_rate': 0.00025,
'learning_starts': 10000,
'save_model': True,
'seed': 1,
'start_e': 1,
'target_network_frequency': 500,
'tau': 1.0,
'torch_deterministic': True,
'total_timesteps': 100000,
'track': True,
'train_frequency': 10,
'upload_model': True,
'wandb_entity': 'pfunk',
'wandb_project_name': 'dqpn'}