A(n) APPO model trained on the mujoco_ant environment.
This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory. Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/
Downloading the model
After installing Sample-Factory, download the model with:
python -m sample_factory.huggingface.load_from_hub -r execbat/sample-factory-mujoco-ant
Using the model
To run the model after download, use the enjoy
script corresponding to this environment:
python -m sf_examples.mujoco.enjoy_mujoco --algo=APPO --env=mujoco_ant --train_dir=./train_dir --experiment=sample-factory-mujoco-ant
You can also upload models to the Hugging Face Hub using the same script with the --push_to_hub
flag.
See https://www.samplefactory.dev/10-huggingface/huggingface/ for more details
Training with this model
To continue training with this model, use the train
script corresponding to this environment:
python -m sf_examples.mujoco.train_mujoco --algo=APPO --env=mujoco_ant --train_dir=./train_dir --experiment=sample-factory-mujoco-ant --restart_behavior=resume --train_for_env_steps=10000000000
Note, you may have to adjust --train_for_env_steps
to a suitably high number as the experiment will resume at the number of steps it concluded at.
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Evaluation results
- mean_reward on mujoco_antself-reported5761.72 +/- 1042.16