Modelpublic

txmedai/seldinger-videomae-lap-chole-broad128

sourceHugging Faceotherupdated 2mo agoView on Hugging Face

0likes3downloads

Model Card

Seldinger VideoMAE Lap Chole Broad128

Self-supervised VideoMAE pretraining checkpoint adapted to a mirrored laparoscopic cholecystectomy video corpus.

Training Lineage

—Base checkpoint: MCG-NJU/videomae-base
—Strict adaptation run: 30 train videos, 200 steps
—Broad continuation run: 128 train videos, 500 steps
—Final broad metrics: losslast `0.27357321977615356`, lossmean 0.4516991448639892
—Full checkpoint archive with intermediate checkpoints: gs://seldinger-datasets-raw/_runner/surgery-video-training/surgery-videomae-pretrained-broad128-20260714T173724Z/model.tgz

Files

—config.json and model.safetensors: final VideoMAEForPreTraining checkpoint
—train_metrics.json: final training metrics
—training_manifest.jsonl: 128-row broad training manifest used for the continuation run

Intended Use

This is a self-supervised video representation checkpoint for research and downstream surgical-video experimentation. It is not a clinical decision model and should not be used for patient care without downstream validation.