--- 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_0197) 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

🌐 Project | 📃 Paper | 💻 GitHub | 🤗 Dataset

![ProbeX](https://raw.githubusercontent.com/eliahuhorwitz/ProbeX/main/imgs/poster.png) ## Model Details | Attribute | Value | |---|---| | **Subset** | SupViT | | **Split** | test | | **Base Model** | `google/vit-base-patch16-224` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 3e-05 | | LR Scheduler | cosine | | Epochs | 3 | | Max Train Steps | 999 | | Batch Size | 64 | | Weight Decay | 0.007 | | Seed | 197 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9925 | | Val Accuracy | 0.9485 | | Test Accuracy | 0.9464 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `butterfly`, `elephant`, `caterpillar`, `willow_tree`, `cup`, `couch`, `seal`, `dolphin`, `can`, `bear`, `shark`, `crab`, `castle`, `road`, `maple_tree`, `palm_tree`, `apple`, `woman`, `bicycle`, `cattle`, `train`, `lamp`, `sea`, `rabbit`, `possum`, `wolf`, `man`, `poppy`, `tank`, `kangaroo`, `mouse`, `chimpanzee`, `bowl`, `worm`, `lawn_mower`, `mountain`, `aquarium_fish`, `otter`, `orange`, `bed`, `tractor`, `turtle`, `cloud`, `baby`, `fox`, `sweet_pepper`, `orchid`, `chair`, `lizard`, `clock`