ORENA_weights

ORENA SurgVidLM HEICO + LapChole Adapter

This repository contains the ORENA LoRA adaptation of SurgVidLM for single-frame surgical visual question answering. The adapter was trained jointly on HEICO and LapChole and is stored under surgvidLM/.

Base model

The required base checkpoint is the surgvidlm-stage2 subfolder of jwang01/surgvidlm. This repository contains only the downstream LoRA adapter; it does not redistribute the SurgVidLM base weights or training datasets.

Training data

The converted data contained:

• Training: 7,200 HEICO and 5,182 LapChole examples
• Validation: 800 HEICO and 566 LapChole examples

No images, videos, annotations, or other training data are included in this repository.

Adapter details

• Fine-tuning method: LoRA supervised fine-tuning
• LoRA rank: 8
• LoRA alpha: 16
• LoRA dropout: 0.05
• Vision tower: frozen
• Multimodal projector: frozen
• Learning rate: 5e-5
• Epochs: 3
• Effective training batch size: 32
• Seed: 42
• Framework: LLaMA-Factory / PEFT

The selected adapter corresponds to checkpoint 700. The identical adapter is stored at the training output root because load_best_model_at_end was enabled.

Validation

• Combined HEICO + LapChole validation loss: 0.3538476527
• Training loss: 0.3713347467

These are loss values, not official-test accuracy scores. Official test-set results should be reported separately when available.

Download

hf download ahnaf1393/ORENA_weights \
  --include "surgvidLM/*" \
  --local-dir ORENA_weights

hf download jwang01/surgvidlm \
  --include "surgvidlm-stage2/*" \
  --local-dir surgvidlm_base

Inference with the ORENA SurgVidLM script

python SurgVidLM/frame_vqa_inference_batch.py \
  --model-path surgvidlm_base/surgvidlm-stage2 \
  --adapter-path ORENA_weights/surgvidLM \
  --data-path PATH_TO_INPUT.json \
  --result-path predictions.json

Intended use and limitations

This adapter is intended for research on surgical-scene understanding and frame-level visual question answering. It has not been validated as a medical device and must not be used for diagnosis, clinical decisions, or autonomous surgical control.

Performance may vary across procedures, hospitals, imaging systems, patient populations, question formats, and conditions not represented during training.

License

Public redistribution terms are pending confirmation from the SurgVidLM model authors and the applicable HEICO and LapChole data-use agreements. Do not treat the absence of a license field as permission for unrestricted use or redistribution.

Acknowledgements

This adapter is derived from SurgVidLM. See also the SurgVidLM paper.