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model.safetensors) 입니다 — LoRA adapter 가 아니며, 그대로 로드해 사용합니다.lerobot/smolvla_base (SmolVLM2-500M-Video-Instruct VLM + action expert)top, left_wrist (480×640) — 정책 키 camera1(left_wrist) / camera2(top) 로 renameobservation.state[6] + 카메라 2개 + language instruction (task)action[6] (joint position)chunk_size=50, n_action_steps=50| 구성요소 | 상태 |
|---|---|
| VLM backbone (SmolVLM2) | ❄️ 완전 Frozen (freeze_vision_encoder=true) |
| Action expert | 🔥 학습 (train_expert_only=true) |
| PEFT / LoRA | 사용 안 함 |
| 항목 | 값 |
|---|---|
| Dataset | IsaacLab-SO101_pick_place_baseCaP_100epi_10fps — 100 episodes / 34,264 frames / 10 fps |
| Epochs / Steps | 50 epoch / 6,700 steps |
| Global batch size | 256 (micro batch 128 × 2 GPU) |
| Optimizer | AdamW — lr 1e-4, weight_decay 1e-10, grad_clip_norm 10.0 |
| LR scheduler | cosine_decay_with_warmup — warmup 1,000 / decay 30,000 / peak_lr 1e-4 / decay_lr 2.5e-6 |
| chunk_size / n_action_steps | 50 / 50 |
| Seed | 1000 |
| Dataloader workers | 16 |
| Mixed precision | no (bf16 inference) |
| Image augmentation | ColorJitter (brightness/contrast/saturation/hue) + SharpnessJitter — 기하학적 변형(회전/이동/반전) 없음 (VLA 좌우 의미 보존) |
| Hardware | 2 × NVIDIA H100 80GB |
| Final loss | 0.013 |
| Dataset key | Policy key |
|---|---|
observation.images.left_wrist | observation.images.camera1 |
observation.images.top | observation.images.camera2 |
observation.state[6] (joint position) + 카메라 2개 + language instruction(task) 만action[6] (joint position) 만ee_pos / gripper_binary / state.radian_urdf0 / action.radian_urdf0 는 학습에서 제외camera1/2/3)로 고정이라 camera3 슬롯이 config 에 존재하지만, 데이터셋 카메라는 2개뿐이라 실제로 데이터가 흐르는 카메라는 2개입니다.1from lerobot.policies.smolvla.modeling_smolvla import SmolVLAPolicy
2
3policy = SmolVLAPolicy.from_pretrained("CoRL2026-CSI/smolVLA-IsaacLab-picknplace-50epoch")