metadata
tags:
- TactileMNIST-v0
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
library_name: cleanrl
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: TactileMNIST-v0
type: TactileMNIST-v0
metrics:
- type: mean_final_accuracy
value: 0.30 +/- 0.46
name: mean_final_accuracy
verified: false
(CleanRL) PPO Agent Playing tactile_mnist:TactileMNIST-v0
This is a trained model of a PPO agent playing tactile_mnist:TactileMNIST-v0. 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_tactile_mnist_new_baseline_clip_action_softplus]"
python -m cleanrl_utils.enjoy --exp-name ppo_tactile_mnist_new_baseline_clip_action_softplus --env-id tactile_mnist:TactileMNIST-v0
Please refer to the documentation for more detail.
Command to reproduce the training
curl -OL https://huggingface.co/Yunzhe/TactileMNIST-v0-ppo_tactile_mnist_new_baseline_clip_action_softplus-seed1/raw/main/ppo_tactile_mnist_new_baseline_clip_action_softplus.py
curl -OL https://huggingface.co/Yunzhe/TactileMNIST-v0-ppo_tactile_mnist_new_baseline_clip_action_softplus-seed1/raw/main/pyproject.toml
curl -OL https://huggingface.co/Yunzhe/TactileMNIST-v0-ppo_tactile_mnist_new_baseline_clip_action_softplus-seed1/raw/main/poetry.lock
poetry install --all-extras
python ppo_tactile_mnist_new_baseline_clip_action_softplus.py --capture_video --save_model --upload_model --comment clip_action_softplus --num_envs 128 --total_timesteps 10000000
Hyperparameters
{'anneal_lr': True,
'batch_size': 2048,
'capture_video': True,
'clip_coef': 0.2,
'clip_vloss': True,
'comment': 'clip_action_softplus',
'cuda': True,
'ent_coef': 0.01,
'env_id': 'tactile_mnist:TactileMNIST-v0',
'exp_name': 'ppo_tactile_mnist_new_baseline_clip_action_softplus',
'gae_lambda': 0.95,
'gamma': 0.99,
'hf_entity': 'Yunzhe',
'learning_rate': 0.0003,
'max_grad_norm': 0.5,
'minibatch_size': 512,
'norm_adv': True,
'num_envs': 128,
'num_iterations': 4882,
'num_minibatches': 4,
'num_steps': 16,
'save_model': True,
'seed': 1,
'target_kl': None,
'torch_deterministic': True,
'total_timesteps': 10000000,
'track': True,
'update_epochs': 4,
'upload_model': True,
'vf_coef': 0.5,
'wandb_entity': 'huyz7830',
'wandb_project_name': 'TactileMNIST-v0'}