StarVLA/Qwen3-VL-OFT-Robotwin2

Qwen3-VL-4B OFT for RoboTwin 2.0 Base (40K)

This repository contains a StarVLA QwenOFT checkpoint trained on the RoboTwin 2.0 Base mixture: 50 clean demonstrations for each of 50 tasks. It is a complete StarVLA state dictionary rather than a Transformers model package.

Checkpoint identity

Item	Value
Released file	checkpoints/steps_40000_pytorch_model.pt
Training step	40,000
Hub revision checked	bf41eb7c9edb697a5b2677e719beb042bcfe9ccb
File size	9,785,132,794 bytes
SHA-256 / LFS object ID	8ccee8ddb33fa5df83a9a5e2b7d4f737db93f19a051b23f738af8a484fe2d7e5

The run history reaches 100K, but only the 40K weights are published here.

Model and control contract

Item	Value
Framework	StarVLA QwenOFT
Base VLM	Qwen3-VL-4B-Instruct
Action head	Two-block residual MLP, 2,560 input / 5,120 hidden / 14 output; direct L1 regression
Camera order	head, left wrist, right wrist
Robot state	Statistics are packaged, but the current absolute-action evaluator omits state from the policy request
Action chunk	16 x 14
Action representation	14-D absolute dual-arm joint action
Normalization	min-max with key new_embodiment

Preserve the RoboTwin adapter's action reordering when converting the model's 14-D output to simulator control. A numerically correct tensor with a different joint order is not an equivalent policy input or output.

Training data and settings

dataset_statistics.json records 2,500 trajectories and 549,787 transitions for new_embodiment, matching 50 tasks x 50 clean demonstrations.

Setting	Value
Dataset mixture	robotwin
Per-device VLA batch size	8
Gradient accumulation	1
Optimizer	AdamW, betas (0.9, 0.95), epsilon 1e-8, weight decay 1e-8
Base / interface / action LR	3e-5 / 1e-5 / 1e-4
Warmup	5,000 steps
freeze_modules	Packaged boolean true; the public trainer expects module paths as a string, so this value names/selects no modules
Seed	42
Training GPU count	Missing from the public artifact

Repository-reported result boundary

The StarVLA RoboTwin README links this repository and reports 50.38% Easy success for its Qwen3-VL-4B Base column. The page does not identify the evaluated save step and this repository contains no raw evaluation logs. Therefore, 50.38% is useful repository-level context but is not verified as a score of the released 40K file. A Hard/Random score for this artifact is missing.

Do not substitute the 88.18% Easy / 88.32% Hard result: that belongs to the separate Data Scaling checkpoint trained with an additional 500 randomized demonstrations per task.

Download and load

hf download StarVLA/Qwen3-VL-OFT-Robotwin2 \
  --local-dir playground/Pretrained_models/Qwen3-VL-OFT-Robotwin2

export CKPT=playground/Pretrained_models/Qwen3-VL-OFT-Robotwin2/checkpoints/steps_40000_pytorch_model.pt
python deployment/model_server/server_policy.py \
  --ckpt_path "$CKPT" \
  --config_override framework.qwenvl.base_vlm=Qwen/Qwen3-VL-4B-Instruct \
  --port 57700 \
  --use_bf16

Keep the run directory intact so StarVLA can find its configuration and statistics. Use the matching RoboTwin adapter and new_embodiment key.

Intended use and limitations

This release targets the RoboTwin 2.0 Base simulation embodiment. Results do not establish performance for the randomized Data Scaling setting, alternative camera or joint orders, or physical hardware. The packaged .pt file requires trusted PyTorch deserialization and the matching StarVLA code.

License status

This target repository did not previously publish a Model Card or a separate LICENSE file. The checkpoint's weight license therefore needs maintainer confirmation; the Qwen3-VL base-model terms and applicable dataset terms still apply.