ExpoFT-Pi05-PickCube-v1-SFT

ExpoFT π₀.₅ — PickCube-v1 (SFT)

LoRA-finetuned checkpoint of π₀.₅ (pi05_droid_jointpos), adapted to ManiSkill's PickCube-v1 task as part of the ExpoFT reproduction project.

• Success rate: 22% on 200 held-out fixed-seed evaluation episodes (SE = sqrt(p(1-p)/n))
• Training: LoRA supervised fine-tuning on 50 motion-planning demonstrations
• Action space: joint-space (pd_joint_delta_pos), matching pi0.5's DROID pretraining distribution
• Normalization stats: official DROID stats (gs://openpi-assets/checkpoints/pi05_droid_jointpos/assets/droid)

Important: requires a environment patch to evaluate correctly

ManiSkill's PickCube-v1 hides the goal marker from sensor cameras by default. This checkpoint was trained and evaluated with a monkeypatch (expo_ft/env/patches.py in the training repo below) that unhides it — without applying the same patch, the environment will not expose the goal position the policy was trained to rely on, and evaluation results will not be representative.

Warning: JAX only

This checkpoint is in its native JAX/orbax format (as produced by openpi training) and has not been converted to PyTorch. openpi's official conversion script (examples/convert_jax_model_to_pytorch.py) exists, but PyTorch-side LoRA support is currently absent in openpi, and unresolved upstream issues report output mismatches between JAX and converted PyTorch weights for pi0.5 specifically -- so no PyTorch conversion is provided here.

Usage

Point pi05_weight_loader_path at the downloaded params/ directory when building the model via openpi's CheckpointWeightLoader, using the expo_pi05_droid_lora_finetune_sft_joint_state training config as the base.

Code

Training/eval pipeline: Josh012006/expo-ft