aswinkumar99/LeRobot-SO101-ACT-task1-all_bs32_s60000

LeRobot SO101 ACT task1-allbs32s60000

Summary

This repository contains the final checkpoint for a ACT policy trained on aswinkumar99/task1-all for SO101 sponge pick-and-place experiments.

Dataset meaning: Task 1: Single Sponge - No Distractors (all layouts).

This ACT policy was trained for this dataset configuration and was not initialized from a published ACT base checkpoint. The visual backbone uses ImageNet-initialized ResNet-18 weights (ResNet18_Weights.IMAGENET1K_V1) as recorded in the training config.

Training Setup

• —Dataset repo: aswinkumar99/task1-all
• —Local dataset root during training: /home/riftuser/datasets_combined/aswinkumar99/task1-all
• —Output directory during training: /home/riftuser/outputs_matrix/act/task1-all_bs32_s60000
• —Batch size: 32
• —Training steps: 60000
• —Checkpoint save frequency: 15000
• —Data loader workers: 8
• —WandB project: so101-layout-generalization
• —GPU: NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition
• —Python: CPython 3.12.13
• —CUDA: 12.9
• —Training start: 2026-04-23T18:00:28.479251+00:00
• —Training end: 2026-04-23T21:11:03
• —Approximate training duration: 3h 10m 34s

• —Vision backbone: resnet18
• —Observation cameras: observation.images.overhead, observation.images.wrist
• —Action chunk size: 100
• —Action steps predicted: 100

Exact Training Command

lerobot-train \
  --dataset.repo_id=aswinkumar99/task1-all \
  --dataset.root=/home/riftuser/datasets_combined/aswinkumar99/task1-all \
  --dataset.video_backend=torchcodec \
  --output_dir=/home/riftuser/outputs_matrix/act/task1-all_bs32_s60000 \
  --job_name=act_task1-all_bs32 \
  --batch_size=32 \
  --steps=60000 \
  --log_freq=200 \
  --save_freq=15000 \
  --save_checkpoint=true \
  --num_workers=8 \
  --wandb.enable=true \
  --wandb.project=so101-layout-generalization \
  --wandb.mode=online \
  --wandb.disable_artifact=true \
  --policy.type=act \
  --policy.device=cuda \
  --policy.push_to_hub=false

Repository Contents

• —pretrained_model/: final downloadable model artifacts for inference/loading
• —training_state/: optimizer, RNG, scheduler/state, and step information for resuming or auditability

Notes

• —This repo stores the final checkpoint that was uploaded from the cloud training workspace.
• —The checkpoint was trained with LeRobot tooling via lerobot-train.
• —For SO101 experiments in this workspace, the dataset source was created by Aswinkumar.

Creator

Aswinkumar

• —Website: aswinkumar.me
• —Hugging Face repo: <https://huggingface.co/aswinkumar99/LeRobot-SO101-ACT-task1-allbs32s60000>