metadata
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_0037)
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
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 | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 37 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9216 |
| Val Accuracy | 0.8613 |
| Test Accuracy | 0.8664 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
castle, bridge, turtle, woman, lizard, kangaroo, crab, motorcycle, willow_tree, chair, bee, snail, otter, boy, couch, worm, bottle, mouse, porcupine, oak_tree, skyscraper, beaver, orange, camel, aquarium_fish, rabbit, chimpanzee, apple, bus, caterpillar, clock, keyboard, dinosaur, shark, table, beetle, baby, seal, tulip, snake, spider, dolphin, road, pickup_truck, wardrobe, pine_tree, television, mushroom, whale, streetcar