AdamCodd

--- metrics: - accuracy pipeline_tag: image-classification base_model: google/vit-base-patch16-384 model-index: - name: AdamCodd/vit-base-nsfw-detector results: - task: type: image-classification name: Image Classification metrics: - type: accuracy value: 0.9654 name: Accuracy - type: AUC value: 0.9948 - type: loss value: 0.0937 name: Loss license: apache-2.0 tags: - transformers.js - transformers - nlp ---

A lightweight face detection model based on YOLO architecture (YOLOv11 nano), trained for 225 epochs on the WIDERFACE dataset. It achieves the following results on the evaluation set: - Performance may vary in extreme lighting conditions - Best suited for frontal and slightly angled faces - Optimal performance for faces occupying >20 pixels

A lightweight face detection model based on YOLO architecture (YOLOv11 xlarge), trained for 100 epochs on the WIDERFACE dataset. It's way more accurate than my YOLOv11n model, but slower. It achieves the following results on the evaluation set: - Performance may vary in extreme lighting conditions - Best suited for frontal and slightly angled faces - Optimal performance for faces occupying >20 pixels