pi05-libero-10-sft-step-200

PI0.5 LIBERO-10 SFT — Step 200

This is a deliberately undertrained PI0.5 checkpoint fine-tuned on the complete official LIBERO-10 dataset. It is intended as a reproducible starting policy for measuring how much downstream reinforcement learning, particularly ReCap, improves long-horizon task success rather than as a fully trained SFT release.

The checkpoint is an upstream-native, merged PI0.5 policy exported by verl-vla. It does not require a verl-vla checkpoint wrapper for inference.

Lineage

• Base model: Miical/pi05-base
• Training dataset: lerobot/libero_10_image
• Benchmark: LIBERO-10, all 10 tasks
• Checkpoint: optimizer step 200

Training configuration

One complete pass over this dataset is 396 optimizer steps with the configured batch size. This checkpoint was saved at step 200, about halfway through the first epoch. It therefore provides a moderately capable but intentionally non-saturated policy for subsequent reinforcement-learning experiments.

LIBERO-10 evaluation

Evaluation used all 10 LIBERO-10 tasks with 10 trials per task, a maximum of 520 environment steps per trial, and 52 policy interactions with a 10-action chunk.

These results are from one complete 100-trajectory benchmark run. Per-task estimates use only 10 trials and should not be interpreted as precise population rates.

Intended use

This model is intended as an incompletely trained initial policy for validating whether ReCap or another reinforcement-learning method improves aggregate and per-task LIBERO-10 success. In particular, task 8 has no successful trajectory in this evaluation, while the other tasks provide varying amounts of initial capability. For a high-performing SFT baseline or deployment candidate, use a later and more thoroughly evaluated checkpoint instead.

Loading

from giga_models import PI0Policy

policy = PI0Policy.from_pretrained(
    "Miical/pi05-libero-10-sft-step-200"
)

With verl-vla, set the model path directly:

cluster:
  actor_rollout_ref:
    model:
      path: Miical/pi05-libero-10-sft-step-200
      adapter:
        embodiment: libero

License and attribution

This fine-tuned checkpoint inherits the usage and redistribution constraints of the original PI0.5 checkpoint and its underlying components. The PyTorch conversion and verl-vla integration code have their own respective licenses; consult the base model card and upstream projects before redistribution or commercial use.