InternW0 RoboTwin-clean checkpoint provenance

Selected artifact

InternW0-RoboTwin-clean.pt is the model-only checkpoint selected for the RoboTwin 2.0 Clean2Random release. It is derived from the historical run w0-cln-cj02-s2-64g-dh-0919r5 at step 10,545.

The historical source implementation was ahawam; the public runtime is w0. The resolved numerical training contract is preserved in source_training_config.yaml with private filesystem paths replaced by portable environment variables.

Lineage

Heterogeneous InternW0 pretraining at global step 30,000.
RoboTwin target-domain initialization with new_domain action/proprio interfaces, seed 42.
Clean-demonstration posttraining run w0-cln-p30k-cj02-s2-64g-0918r3, resumed at step 5,000.
Continued best Clean2Random recipe w0-cln-cj02-s2-64g-dh-0919r5, selected at step 10,545.

The checkpoint embeds behavior_config, training_recipe, posttrain_statistics, and posttrain_provenance. These fields are also exported verbatim to checkpoint_metadata.json.

Training contract

Clean demonstrations only.
RoboTwin native joint-space representation.
25 Hz sampling (sampling_stride=2 from 50 Hz).
Every valid native window.
ColorJitter: brightness 0.2, contrast 0.2, saturation 0.2, hue 0.
Offset 0.
Batch size 12 per process.
15 epochs.
Learning rate 3e-5, cosine schedule.
Seed 42.
37-dimensional canonical action/proprio interface.
14 valid ALOHA joint/gripper slots: [0, 1, 2, 3, 4, 5, 16, 17, 18, 19, 20, 21, 22, 33].
Action horizon 64, chunk size 16, video plan horizon 96, video/action stride 8.
K=8 target soft prompts.
Native absolute joint commands at the interval end.

The matching normalization file is normalization.json.

Evaluation reference

The source resolved evaluation reference is preserved in source_evaluation_config.yaml. It uses the fixed-period RoboTwin adapter at 25 Hz, 10 inference steps, a 64-action horizon, four action chunks per video prefill, and 15 episodes per task.

The paper-reported RoboTwin 2.0 Clean2Random results are:

Split	Success rate
Clean	83.20%
Randomized (unseen during training)	68.00%
Average	75.60%

Excluded from this repository

The checkpoint package does not include optimizer state, distributed training state, logs, RoboTwin data, Wan2.2 files, DINOv3 weights, text caches, or simulation checkouts.