--- base_model: google/vit-base-patch16-224 library_name: transformers pipeline_tag: image-classification tags: - probex - model-j - weight-space-learning --- # Model-J: SupViT Model (model_idx_0898) This model is part of the **Model-J** dataset, introduced in: **Learning on Model Weights using Tree Experts** (CVPR 2025) by Eliahu Horwitz*, Bar Cavia*, Jonathan Kahana*, Yedid Hoshen
 ## Model Details | Attribute | Value | |---|---| | **Subset** | SupViT | | **Split** | train | | **Base Model** | `google/vit-base-patch16-224` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 0.0003 | | LR Scheduler | constant | | Epochs | 7 | | Max Train Steps | 2331 | | Batch Size | 64 | | Weight Decay | 0.009 | | Seed | 898 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9704 | | Val Accuracy | 0.8813 | | Test Accuracy | 0.8792 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `mouse`, `girl`, `bed`, `chimpanzee`, `sunflower`, `rose`, `skyscraper`, `worm`, `streetcar`, `snail`, `clock`, `tiger`, `lobster`, `porcupine`, `tulip`, `plain`, `possum`, `orange`, `motorcycle`, `leopard`, `can`, `keyboard`, `forest`, `dinosaur`, `wardrobe`, `elephant`, `bicycle`, `cup`, `aquarium_fish`, `tank`, `crab`, `orchid`, `bridge`, `willow_tree`, `bus`, `castle`, `bowl`, `train`, `boy`, `whale`, `butterfly`, `telephone`, `beaver`, `pine_tree`, `maple_tree`, `squirrel`, `caterpillar`, `lawn_mower`, `cattle`, `lamp`