StarVLA QwenDual for BEHAVIOR RGP Dual, task 6 (40K)
This repository contains the uploaded 40,000-step checkpoint from the
1115_BEHAVIOR_rgp_dual_QwenDual_task6 run. The packaged config.yaml
describes a StarVLA QwenDual policy trained on task 6 of the
BEHAVIOR_rgp_dual mixture. The configured training target is 100,000 steps,
but the only weight file published here is the 40,000-step checkpoint.
Model details
| Item | Published configuration |
|---|---|
| Framework | StarVLA QwenDual |
| VLM | Local training snapshot named Qwen3-VL-4B-Instruct; revision not recorded |
| Auxiliary visual encoder | dinov2_vits14 |
| Action model | 16-layer DiT-B flow head: 768 latent width, 12 heads (64 dimensions/head); state/action decoder MLP width 1,024 |
| Action / state dimension | 23 / 21 |
| Predicted action chunk | 50 steps |
| Image resolution | 224 x 224 |
| State input | Enabled |
| Dataset mixture / task | BEHAVIOR_rgp_dual, task_id: 6 |
| Normalization key | R1Pro |
| Uploaded checkpoint | checkpoints/steps_40000_pytorch_model.pt |
The public configuration does not declare the number or ordering of camera views. Preserve the training-time observation adapter and the packaged normalization statistics instead of constructing a flat input manually. The current StarVLA BEHAVIOR documentation defines the 23D action as base, torso, two 7D arms, and two grippers.
Training details
| Setting | Value in config.yaml |
|---|---|
| Intended maximum steps | 100,000 |
| Released step | 40,000 |
| Per-device VLA batch size | 32 |
| Gradient accumulation | 1 |
| Warm-up steps | 5,000 |
| Base / interface / action LR | 4e-5 / 1e-5 / 1e-4 |
| Optimizer | AdamW, betas (0.9, 0.95), epsilon 1e-8 |
| Scheduler | Cosine with minimum LR 1e-6 |
| VLA / VLM loss scale | 1.0 / 0.1 |
freeze_modules |
Packaged boolean true; the public trainer expects module paths as a string, so this value names/selects no modules |
| Gradient checkpointing / mixed precision | Enabled / enabled |
| Seed | 42 |
summary.jsonl lists saved steps through 40K. It is a checkpoint index, not
an evaluation report.
Files
config.yaml
dataset_statistics.json
summary.jsonl
checkpoints/
└── steps_40000_pytorch_model.pt
Keep config.yaml and dataset_statistics.json beside the checkpoint. The
StarVLA server uses them to reconstruct the model and apply the R1Pro
normalization contract.
Evaluation status
No BEHAVIOR success rate, challenge score, episode manifest, or per-task evaluation log is published in this repository. Consequently this card does not attach a benchmark number to the 40K artifact. The public BEHAVIOR example is still marked under construction and should be treated as an integration guide rather than evidence that this checkpoint reproduces a challenge entry.
Loading and evaluation
This is a StarVLA framework checkpoint, not a Transformers
from_pretrained() directory.
huggingface-cli download StarVLA/1115_BEHAVIOR_rgp_dual_QwenDual_task6_40k \
--local-dir 1115_BEHAVIOR_rgp_dual_QwenDual_task6_40k
export CKPT=$PWD/1115_BEHAVIOR_rgp_dual_QwenDual_task6_40k/checkpoints/steps_40000_pytorch_model.pt
python deployment/model_server/server_policy.py \
--ckpt_path "$CKPT" \
--port 10093 \
--use_bf16
Use the maintained BEHAVIOR evaluation guide for the simulator client. Verify state dimension, camera order, action order, and normalization key at the server handshake before running episodes.
Intended use and limitations
This checkpoint is intended for BEHAVIOR-1K simulation research with the R1Pro embodiment and the task/data scope recorded above. It has no published evaluation result, no recorded upstream VLM revision, and no demonstrated transfer to other tasks, embodiments, or physical robots. BEHAVIOR evaluation requires a Vulkan-capable simulator GPU; the project documentation warns that A100/H100-class GPUs without RT cores are not suitable for this simulator. Do not deploy the policy on hardware without an independent safety layer.
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Base model
Qwen/Qwen3-VL-4B-Instruct