Fine-tuning Policies

Fine-tuning policies with fresh demonstrations that you have collected.

Training Policies

The following assumes that the current working directory is this repository’s root folder.

Training a Behavior Cloning Policy

  1. Modify include_task and include_env in finetune.yaml depending on the task and env you intend to finetune.

  2. [Optional, non-default:] only if you're using torch encoder, set enc_weight_pth (path to pretrained encoder weights) in image_bc_depth.yaml. You can download the weights from if you don't have them.

  3. Run in terminal:

    python --config-name=finetune
  4. [Optional, experimental] If you want to take advantage of multi-GPU training using 🤗 accelerate, you can use the following command:

    accelerate config # Only the first time, to configure accelerate
    accelerate launch --config-name=finetune

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