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smolvla-robotwin-place-bread-skillet-50ep
arrow-hf/smolvla-robotwin-place-bread-skillet-50ep
smolvla-robotwin-place-bread-skillet-50ep is a robotics model from arrow-hf. Use it for the robotics task on the model card, and read the license before you ship it in a product. It is set up for lerobot. The card lists the license as apache-2.0.
SmolVLA policy fine-tuned on 50 demonstration episodes of the placebreadskillet task from RoboTwin 2.0 (democlean config), starting from the lerobot/smolvlarobotwin base checkpoint.
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From the Hugging Face model README
SmolVLA RoboTwin place_bread_skillet (50 ep, single instruction)
SmolVLA policy fine-tuned on 50 demonstration episodes of the place_bread_skillet task from RoboTwin 2.0 (demo_clean config), starting from the lerobot/smolvla_robotwin base checkpoint.
Task
Dual-arm pick-and-place: pick up the bread and place it inside the skillet.
- Robot: Agilex dual-arm, end-effector control (16D state, 16D action)
- Cameras: 3 RGB streams —
dual_cam_global,cam_wrist_65,cam_wrist_75 - Control rate: 10 Hz
- Single fixed instruction:
"place the bread in the skillet"(Strategy A, not random per-episode)
Training
| Config | Value |
|---|---|
| Base checkpoint | lerobot/smolvla_robotwin |
| Training data | 50 RoboTwin demonstrations (subset of place_bread_skillet_300ep), strategy A single instruction |
| Frames | 8,298 (~165 frames/ep) |
| Batch size | 32 |
| Steps | 6000 (~23 epochs) |
| Optimizer | AdamW, lr=1e-4 |
| Scheduler | Cosine, warmup=300, decay=6000 |
| Chunk size | 50 |
| Final train loss | 0.008 |
| Walltime | ~2h 15min (A100) |
Evaluation
Evaluated in RoboTwin 2.0 simulator (demo_clean config), 10 episodes, max_steps=400, action_chunk_exec=50.
| Model | Data | Base | Success |
|---|---|---|---|
SmolVLA (smolvla_base) | 300 ep | smolvla_base | 0/10 (0%) |
| SmolVLA (this model) | 50 ep | smolvla_robotwin | 6/10 (60%) |
X-VLA (xvla-base) | 300 ep | xvla-base | 8/10 (80%) |
Training with the smolvla_robotwin base checkpoint enables strong data efficiency: with 6× less data and 3× fewer training steps, this model jumps from 0% to 60% success rate on this task.
Successful episodes complete in 132–201 environment steps (13–20s); failed episodes time out at 400 steps.
Usage
from lerobot.policies.smolvla import SmolVLAPolicy
policy = SmolVLAPolicy.from_pretrained("arrow-hf/smolvla-robotwin-place-bread-skillet-50ep")
See LeRobot documentation for inference setup.
Citation
Built on SmolVLA and SmolVLA-RoboTwin, fine-tuned on data collected from RoboTwin 2.0.
- Task
- Robotics
- Library
- lerobot
- License
- apache-2.0
- Created
- May 27, 2026
- Updated
- May 27, 2026