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pravsels/pi05-bin-pack-single-dataset

sourceHugging Faceapache-2.0updated 6mo agoView on Hugging Face
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pi0.5 Bin Pack — Single Dataset Baseline

Fine-tuned pi0.5 checkpoint for coffee capsule bin packing, trained on a single dataset of ~200 teleoperated episodes. This serves as the base checkpoint for the reward recap experiments.

Config

  • —Config name: pi05_bin_pack_coffee_capsules_delta_single_dataset
  • —Model: pi0.5 (pi05=True, action_horizon=50)
  • —Batch size: 36
  • —Learning rate: 5e-5 cosine decay (10k warmup)
  • —Optimizer: AdamW (gradient clip norm 1.0)
  • —EMA decay: 0.999
  • —Delta actions: enabled
  • —Weight init: weights/pi05_base/params (pi0.5 base weights)
  • —Training steps: 30,000

Dataset

  • —villekuosmanen/bin_pick_pack_coffee_capsules (~200 teleoperated episodes)

Checkpoint Hash

Verify integrity with tar cf - -C checkpoints/29999 params | sha256sum.

StepSHA-256
29,999bb051b5a3ee10adae7ee5313102fd7157e49d77a12a3b9a48e0688617108f9b0

Downstream

This checkpoint is the weight init for the reward recap experiments:

Repo Structure

assets/                      # Norm stats + valid indices for inference
checkpoints/29999/params/    # Model weights (params only)
README.md                    # This file

Usage

python
from openpi.training.config import get_config
from openpi.serving.policy_server import PolicyServer

config = get_config("pi05_bin_pack_coffee_capsules_delta_single_dataset")
server = PolicyServer(config, checkpoint_path="checkpoints/29999/params")