pi05_so101_expert_cosmos70_exp03_gate

π0.5 action-expert fine-tuned on SO-101 "vials to rack" — pick test-tube vials and place them in a rack.

Model details

Base model lerobot/pi05_base (Gemma-2B + 300M action expert)
Training mode Expert-only (VLM backbone frozen, action expert fine-tuned)
Dataset sreetz-nv/so101_teleop_vials_rack_left_cosmos_70
Dataset size 145 episodes (75 real teleop + 70 Cosmos-augmented)
Steps 10 000
Batch size 16
Learning rate 2.5e-5 (cosine decay → 2.5e-6)
Final loss 0.041
Epochs ~4.1
Hardware NVIDIA L40S 46 GB
Chunk size 50 actions
Observation ego (wrist) + external D455 RGB cameras + 6-DOF joint state

Training curve

Step Loss
500 ~0.12
2 000 ~0.072
6 000 0.046
10 000 0.041

W&B project: pi05-so101-vials

Usage

from lerobot.common.policies.pi05.modeling_pi05 import Pi05Policy

policy = Pi05Policy.from_pretrained("Isk5434/pi05_so101_expert_cosmos70_exp03_gate")

Or evaluate directly in Isaac Sim via the companion repo: Isk5434/sim2real-so101

git clone --recurse-submodules https://github.com/Isk5434/sim2real-so101
bash run_webrtc.sh pi05

Training recipe

# Reproduce with train_pi05_so101.sh
STEPS=10000 BATCH=16 LR=2.5e-5 bash train_pi05_so101.sh expert_only cosmos

Full script with LoRA / full fine-tune / resume support: train_pi05_so101.sh

Task

The SO-101 6-DOF robot arm grasps test-tube vials from a tray and places them upright in a rack. The model was trained on demonstrations collected via LeRobot teleoperation in Isaac Sim, with Cosmos video diffusion augmentation to expand the dataset.

Domain randomisation applied during training data collection:

  • HDRI environment lighting
  • Robot link colours
  • Workspace mat texture
  • Lightbox emission colour (USD shader)
  • Camera extrinsics
  • Vial / rack pose noise

Citation

If you use this checkpoint, please cite the base model and dataset:

@misc{pi05_so101_exp03,
  author = {Ishikawa},
  title  = {π0.5 fine-tuned on SO-101 vials-to-rack},
  year   = {2026},
  url    = {https://huggingface.co/Isk5434/pi05_so101_expert_cosmos70_exp03_gate}
}

License

Apache-2.0

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