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README.md
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---
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license: apache-2.0
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---
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DQN model applied to the this discrete environments CartPole-v1
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## Model Description
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The model was trained from the CleanRl library using the DQN algorithm on CartPole-v1
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## Intended Use & Limitation
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The model is intended to be used for the following environments CartPole-v1
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and understand the implication of Quantization on this type of model from a pretrained state
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## Training Procdure
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### Training Hyperparameters
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The folloing hyperparameters were used during training:
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- exp_name: functional_dqn
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- seed: 0
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- torch_deterministic: True
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- cuda: False
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- track: True
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- wandb_project_name: cleanRL
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- wandb_entity: compress_rl
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- capture_video: False
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- env_id: CartPole-v1
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- total_timesteps: 500000
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- learning_rate: 0.00025
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- buffer_size: 10000
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- gamma: 0.99
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- target_network_frequency: 500
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- batch_size: 128
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- start_e: 1
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- end_e: 0.05
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- exploration_fraction: 0.5
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- learning_starts: 10000
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- train_frequency: 10
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- optimizer: Adan
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- max_grad_norm: 0.0
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- weight_decay: 0.02
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- opt_eps: None
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- opt_betas: None
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- no_prox: False
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- wandb_project: cleanrl
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### Framework and version
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Pytorch 1.12.1+cu102
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gym 0.23.1
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Weights and Biases 0.13.3
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Hugging Face Hub 0.11.1
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Python Version 3.8.16 (default, Dec 7 2022, 01:12:13)
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[GCC 7.5.0]
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## Citation
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```bibtex
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```
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