clip japanese base v2 This is a Japanese CLIP (Contrastive Language Image Pre training) model developed by LY Corporation. This model is an updated version of line corporation/clip japanese base. It increases the training data to approximately ~2B image–text pairs and applies model distillation to improve overall performance. How to use 1. Install packages 2. Run Model architecture The model uses an Eva02 B Transformer architecture as the image encoder and a 12 layer BERT as the text encoder. The text encoder was initialized from rinna/japanese clip vit b 16. Evaluation Dataset ImageNet 1k for image classification. Recruit Datasets for image classification. WAON for image classification. STAIR Captions (v2014 val set of MSCOCO) for image to text (i2t) and text to image (t2i) retrieval. We measure performance using R@1, which is the average recall of i2t and t2i retrieval. Result Model Params Avg. ImageNet 1k (acc@1) Recruit Datasets (acc@1) WAON (acc@1) STAIR Captions (R@1) clip japanese base v2 196M 0.708 0.666 0.913 0.975 0.277 clip japanese base 196M 0.673 0.580 0.884 0.934 0.293 llm jp/waon siglip2 base path16 256 375M 0.664 0.555 0.872 0.951 0.276 google/siglip2 base patch16 2…
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