Batch: microbatch 4 × two GPUs × gradient accumulation 4 = global batch 32
Epochs: 1; optimizer updates: 113
Loss scale: Swift default
Frozen: visual encoder and aligner; trainable: language model and LM head
Only the final checkpoint (checkpoint-113) is published.
The exact system prompt is appgen_system_prompt.txt; run_manifest.json records
exact hashes, the dataset receipt, overlap audit, and weight verification.
Intermediate 25-step checkpoints remain local.
Evaluation and limitations
The training/evaluation overlap gate compares EXIF-transposed decoded RGBA
pixels plus image dimensions against the seven pinned AW7 test suites. It also
compares normalized instruction hashes. The exact pinned receipt must report
zero train/eval pixel and instruction overlaps for every data variant and suite
before publication. Static grounding benchmarks are not a substitute for
interactive AndroidWorld task success, and no score is claimed in this card.
This model is for Android visual-agent research, not safety-critical autonomous
deployment.