Reinforcement Learning
stable-baselines3
seals/Humanoid-v1
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use HumanCompatibleAI/ppo-seals-Humanoid-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use HumanCompatibleAI/ppo-seals-Humanoid-v1 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="HumanCompatibleAI/ppo-seals-Humanoid-v1", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
| !!python/object/apply:collections.OrderedDict | |
| - - - batch_size | |
| - 256 | |
| - - clip_range | |
| - 0.2 | |
| - - ent_coef | |
| - 2.0745206045994986e-05 | |
| - - gae_lambda | |
| - 0.92 | |
| - - gamma | |
| - 0.999 | |
| - - learning_rate | |
| - 2.0309225666232827e-05 | |
| - - max_grad_norm | |
| - 0.5 | |
| - - n_envs | |
| - 1 | |
| - - n_epochs | |
| - 20 | |
| - - n_steps | |
| - 2048 | |
| - - n_timesteps | |
| - 10000000.0 | |
| - - normalize | |
| - gamma: 0.999 | |
| norm_obs: false | |
| norm_reward: true | |
| - - policy | |
| - MlpPolicy | |
| - - policy_kwargs | |
| - activation_fn: !!python/name:torch.nn.modules.activation.ReLU '' | |
| features_extractor_class: !!python/name:imitation.policies.base.NormalizeFeaturesExtractor '' | |
| net_arch: | |
| - pi: | |
| - 256 | |
| - 256 | |
| vf: | |
| - 256 | |
| - 256 | |
| - - vf_coef | |
| - 0.819262464558427 | |