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behavior-uncloning-baseline
haohw/behavior-uncloning-baseline
behavior-uncloning-baseline is a machine learning model from haohw. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Baseline DiffusionPolicy trained on all LIBERO-10 episodes (379 episodes, ~101K frames).
Access
Public
Updated Mar 4, 2026
Repo size
2.1 GB
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At a glance
- Access
- Public
- Created
- Mar 4, 2026
- Updated
- Mar 4, 2026
- SHA
- c0812ff8
Model card
From the Hugging Face model README
Behavior Uncloning - Baseline DiffusionPolicy
Baseline DiffusionPolicy trained on all LIBERO-10 episodes (379 episodes, ~101K frames).
Checkpoints
step_025000/- 25K steps, 76% overall success ratestep_050000/- 50K steps, 76% overall success rate (final)
Training Config
- Model: DiffusionPolicy (267M params)
- Dataset: HuggingFaceVLA/libero (LIBERO-10 subset)
- Effective batch size: 64 x 8 GPUs = 512
- Training time: ~20 hours on 8xA100-80GB
- Framework: LeRobot v0.4.4
Per-Task Success Rates (step 50K)
| T0 | T1 | T2 | T3 | T4 | T5 | T6 | T7 | T8 | T9 |
|---|---|---|---|---|---|---|---|---|---|
| 10% | 60% | 80% | 100% | 80% | 100% | 60% | 100% | 70% | 100% |
Usage
from lerobot.policies.diffusion.modeling_diffusion import DiffusionPolicy
policy = DiffusionPolicy.from_pretrained("haohw/behavior-uncloning-baseline", subfolder="step_050000")
Project
Part of the behavior-uncloning project — machine unlearning for robot manipulation policies.
- Created
- Mar 4, 2026
- Updated
- Mar 4, 2026