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_0783)
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 | test |
| Base Model | google/vit-base-patch16-224 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 3e-05 |
| LR Scheduler | cosine |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 783 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9812 |
| Val Accuracy | 0.9512 |
| Test Accuracy | 0.9584 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
mushroom, plain, road, bed, willow_tree, butterfly, boy, rabbit, castle, pickup_truck, spider, tiger, cattle, rocket, hamster, pear, lamp, beetle, shrew, tank, bridge, ray, mountain, table, dinosaur, shark, tractor, camel, orange, turtle, raccoon, squirrel, worm, couch, can, aquarium_fish, wardrobe, bottle, orchid, keyboard, snail, porcupine, woman, apple, trout, snake, bee, chimpanzee, sea, bear