aswinkumar99/LeRobot-SO101-SmolVLA-task2task3-all_bs128_s20000

LeRobot SO101 SmolVLA task2task3-all_bs128_s20000

Summary

This repository contains the final checkpoint for a SmolVLA policy fine-tune trained on aswinkumar99/task2task3-all for SO101 sponge pick-and-place experiments.

Dataset meaning: Task 2 + Task 3 combined (all layouts).

This SmolVLA policy is a fine-tune of lerobot/smolvla_base, as recorded by both the launch command (--policy.path=lerobot/smolvla_base) and the saved training config (pretrained_path: lerobot/smolvla_base).

Training Setup

• Dataset repo: aswinkumar99/task2task3-all

• Local dataset root during training: /home/riftuser/datasets_combined/aswinkumar99/task2task3-all

• Output directory during training: /home/riftuser/outputs_matrix/smolvla/task2task3-all_bs128_s20000

• Batch size: 128

• Training steps: 20000

• Checkpoint save frequency: 5000

• 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: 2026-04-24T09:52:57.631086+00:00

• Training end: 2026-04-24T14:26:18

• Approximate training duration: 4h 33m 20s

• Base model: lerobot/smolvla_base

• Observation camera rename map: {"observation.images.overhead": "observation.images.camera1", "observation.images.wrist": "observation.images.camera2"}

• Action chunk size: 50

• Action steps predicted: 50

Exact Training Command

lerobot-train \
  --dataset.repo_id=aswinkumar99/task2task3-all \
  --dataset.root=/home/riftuser/datasets_combined/aswinkumar99/task2task3-all \
  --dataset.video_backend=torchcodec \
  --output_dir=/home/riftuser/outputs_matrix/smolvla/task2task3-all_bs128_s20000 \
  --job_name=smolvla_task2task3-all_bs128 \
  --batch_size=128 \
  --steps=20000 \
  --log_freq=200 \
  --save_freq=5000 \
  --save_checkpoint=true \
  --num_workers=8 \
  --wandb.enable=true \
  --wandb.project=so101-layout-generalization \
  --wandb.mode=online \
  --wandb.disable_artifact=true \
  --policy.path=lerobot/smolvla_base \
  --policy.device=cuda \
  --policy.push_to_hub=false \
  --rename_map={"observation.images.overhead": "observation.images.camera1", "observation.images.wrist": "observation.images.camera2"}

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-SmolVLA-task2task3-all_bs128_s20000