WD SwinV2 Tagger v3 Supports ratings, characters and general tags. Trained using https://github.com/SmilingWolf/JAX CV. TPUs used for training kindly provided by the TRC program. Dataset Last image id: 7220105 Trained on Danbooru images with IDs modulo 0000 0899. Validated on images with IDs modulo 0950 0999. Images with less than 10 general tags were filtered out. Tags with less than 600 images were filtered out. Validation results v2.0: P=R: threshold = 0.2653, F1 = 0.4541 v1.0: P=R: threshold = 0.2521, F1 = 0.4411 What's new Model v2.0/Dataset v3: Trained for a few more epochs. Used tag frequency based loss scaling to combat class imbalance. Model v1.1/Dataset v3: Amended the JAX model config file: add image size. No change to the trained weights. Model v1.0/Dataset v3: More training images, more and up to date tags (up to 2024 02 28). Now timm compatible! Load it up and give it a spin using the canonical one liner! ONNX model is compatible with code developed for the v2 series of models. The batch dimension of the ONNX model is not fixed to 1 anymore. Now you can go crazy with batch inference. Switched to Macro F1 to measure model performance since it gives me a better gauge of…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy