YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/model-cards#model-card-metadata)

license: apache-2.0 tags:

DQN

DQN model applied to the this discrete environments CartPole-v1

Model Description

The model was trained from the CleanRl library using the DQN algorithm on CartPole-v1

Intended Use & Limitation

The model is intended to be used for the following environments CartPole-v1 and understand the implication of Quantization on this type of model from a pretrained state

Training Procdure

Training Hyperparameters

The folloing hyperparameters were used during training:

  • exp_name: functional_dqn
  • seed: 0
  • torch_deterministic: True
  • cuda: False
  • track: True
  • wandb_project_name: cleanRL
  • wandb_entity: compress_rl
  • capture_video: False
  • env_id: CartPole-v1
  • total_timesteps: 500000
  • learning_rate: 0.00025
  • buffer_size: 10000
  • gamma: 0.99
  • target_network_frequency: 500
  • batch_size: 128
  • start_e: 1
  • end_e: 0.05
  • exploration_fraction: 0.5
  • learning_starts: 10000
  • train_frequency: 10
  • optimizer: Adan
  • max_grad_norm: 0.0
  • weight_decay: 0.02
  • opt_eps: None
  • opt_betas: None
  • no_prox: False
  • wandb_project: cleanrl

Framework and version

Pytorch 1.12.1+cu102

gym 0.23.1 Weights and Biases 0.13.3 Hugging Face Hub 0.11.1 Python Version 3.8.16 (default, Dec 7 2022, 01:12:13) [GCC 7.5.0]

Citation


Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API: The model has no library tag.