CoRL2026-CSI/smolvla_IsaacLab-SO101_pick_place_baseCaP_100epi_50ep-appendix

SmolVLA IsaacLab SO101 PickAndPlace 50ep

This repository contains a SmolVLA policy fine-tuned on the IsaacLab SO101 PickAndPlace dataset.

Model

• —Policy type: smolvla
• —Base model: CoRL2026-CSI/smolVLA-IsaacLab-Multi-Task-8epoch-mod
• —VLM backbone: HuggingFaceTB/SmolVLM2-500M-Video-Instruct
• —Training mode: frozen vision encoder, expert-only training
• —Action chunk size: 50
• —Observation steps: 1
• —Action dimension: 6
• —State dimension: 6

Dataset

• —Dataset: CoRL2026-CSI/IsaacLab-SO101-PickAndPlace-100epi-10fps-appendix
• —Episodes: 100
• —Frames: 34,423
• —FPS: 10
• —Video codec: H.264
• —Cameras used:
• —observation.images.left_wrist renamed to observation.images.camera1
• —observation.images.top renamed to observation.images.camera2

Training

• —Steps: 6,724
• —Epochs: 50
• —Effective global batch size: 256
• —Per-GPU batch size: 128
• —Number of GPUs: 2
• —Optimizer: AdamW
• —Peak LR: 1e-4
• —Scheduler: cosine decay with warmup
• —Decay LR: 2.5e-6
• —Seed: 1000
• —Image augmentation: color jitter and sharpness jitter
• —DataLoader workers: 16 per process
• —Preprocessing in workers: enabled

The final checkpoint was saved after step 6724.

Files

• —model.safetensors: policy weights
• —config.json: policy config
• —train_config.json: training config
• —policy_preprocessor.json: policy preprocessing pipeline
• —policy_postprocessor.json: policy postprocessing pipeline
• —policy_preprocessor_step_5_normalizer_processor.safetensors: normalization stats
• —policy_postprocessor_step_0_unnormalizer_processor.safetensors: unnormalization stats