Training
Two supervised finetuning stages, both at sequence length 16384 on 64 nodes of
JUPITER (4x GH200 per node):
- Instruct SFT — one pass over the LLaVA-OneVision-1.5-Instruct and
Nemotron-VLM-V2 blend, 1139 steps / 16.7B tokens.
- Decay anneal — a further 156 steps / 2.3B tokens over the same sources
reweighted towards document and OCR data, with the learning rate decayed to
zero.
Learning rate 1e-5 for the decoder and projector, 1e-6 for the vision encoder,
100 warmup steps. Images are capped at 1024px on the long side.
Notes
- Uses the Qwen3.5 chat template. Unlike the upstream instruct template, this
one renders
<think> blocks on every assistant turn rather than only the
last, matching how the model was trained.
eos_token is <|im_end|>, and generation_config.json stops on both
<|im_end|> (248046) and <|endoftext|> (248044).