StarVLA/Qwen3VL-OFT-Bridge-RT-1

Qwen3-VL-4B OFT for Bridge + RT-1 (5K)

This repository contains a StarVLA QwenOFT WidowX policy trained on the Bridge and Fractal/RT-1 LeRobot datasets. Only a 5K checkpoint is released.

The maintainer states in starVLA issue #424 that the earlier uploaded checkpoint was incorrect, the original files were removed, and a replacement is being retrained. Treat the current weights as a research artifact pending a corrected release, not as a checkpoint expected to reproduce the advertised 42.7% result.

Checkpoint identity

Item	Value
Released file	checkpoints/steps_5000_pytorch_model.pt
Training step	5,000
Hub revision checked	c3fc8f028429ba14819bf3b16e098776b670c889
File size	9,785,060,316 bytes
SHA-256 / LFS object ID	371cb744227687bb99bcad7f9ff2250cf06da75631359ad3eba4c6bc52570607

summary.jsonl describes later run activity, but it does not make a later checkpoint available. This card does not relabel the artifact as a 35K or 100K release.

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 / 7 output; direct L1 regression
Observation	Language + one image_0 RGB view at 224 x 224
Robot state	Not sent by the matching SimplerEnv adapter
Action chunk	16 x 7
Action representation	delta end-effector action (delta_ee)
SimplerEnv normalization	oxe_bridge for WidowX Bridge evaluation
Action ensemble horizon	7

Stale diffusion-related fields in the resolved run configuration do not turn this QwenOFT artifact into a flow-matching policy; the selected framework and head are regression-based.

Training data and settings

The bridge_rt_1 mixture combines oxe_bridge (1,284,318 transitions, 53,192 trajectories) and oxe_rt1 (3,449,678 transitions, 87,212 trajectories).

Setting	Value
Per-device VLA batch size	16
Gradient accumulation	1
Optimizer	AdamW, betas (0.9, 0.95), epsilon 1e-8, weight decay 1e-8
Warmup configured	10,000 steps
freeze_modules	Packaged boolean true; the public trainer expects module paths as a string, so this value names/selects no modules
Seed	42
Configured run target	100,000 steps; released checkpoint is 5,000
Training GPU count	Missing from the public artifact

Evaluation: packaged historical logs

This repository contains 16 historical evaluation logs named for a 5K checkpoint. Every log's final invocation identifies a file named steps_5000_pytorch_model.pt and evaluates episodes [0, 24). The complete set covers four tasks x four runs x 24 episodes = 384 episodes.

Task	Successes / episodes	Success
Put carrot on plate	49 / 96	51.04%
Put eggplant in basket	85 / 96	88.54%
Put spoon on tablecloth	30 / 96	31.25%
Stack green cube on yellow cube	0 / 96	0.00%
Micro-average	164 / 384	42.71%

The per-run decimals sum to 164 successful episodes, so 42.71% is a recomputation of the packaged logs only. The logs contain a filename but no SHA-256/LFS object ID and therefore are not cryptographically bound to the current checkpoint bytes. In light of the maintainer-confirmed upload mismatch, this table must not be presented as the expected performance of the current release. It is also not evidence for an unreleased longer-run checkpoint.

Known checkpoint mismatch

Issue #424 documents an independent reproduction gap and the maintainer's subsequent confirmation that an incorrect checkpoint had been uploaded. The issue remains open at the time of this card audit. A corrected artifact, its immutable hash, and evaluation logs generated from that same hash are still missing. User-reported reproduction numbers are useful diagnostic evidence but are not promoted here as official checkpoint results.

Download and load

hf download StarVLA/Qwen3VL-OFT-Bridge-RT-1 \
  --local-dir playground/Pretrained_models/Qwen3VL-OFT-Bridge-RT-1

export CKPT=playground/Pretrained_models/Qwen3VL-OFT-Bridge-RT-1/checkpoints/steps_5000_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

Use the WidowX Bridge adapter with oxe_bridge, delta-EEF actions, no state, and the matching action ensemble. Keep the configuration and dataset statistics beside the checkpoints/ directory.

Intended use and limitations

This early 5K checkpoint is retained for diagnosis and SimplerEnv research while a corrected release is pending; it is not suitable for safety-critical control. Expected performance of the current bytes is unknown, and performance on physical robots or the RT-1 embodiment is unverified. Use only a trusted .pt revision with 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 and training-dataset terms still apply.