--- library_name: peft base_model: jwang01/surgvidlm base_model_relation: adapter pipeline_tag: image-text-to-text tags: - peft - lora - llama-factory - qwen2-vl - medical - surgical-vqa - heico - lapchole --- # 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`](https://huggingface.co/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 ```bash 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 ```bash 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`](https://github.com/gkw0010/SurgVidLM). See also the [`SurgVidLM` paper](https://arxiv.org/abs/2506.17873).