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_0429)
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 | 5e-05 |
| LR Scheduler | cosine |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 429 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9916 |
| Val Accuracy | 0.9587 |
| Test Accuracy | 0.9500 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bottle, lion, beaver, castle, possum, tulip, keyboard, palm_tree, butterfly, telephone, poppy, crab, shark, mountain, spider, maple_tree, whale, willow_tree, lizard, trout, mushroom, beetle, porcupine, wardrobe, pickup_truck, forest, kangaroo, otter, seal, wolf, skunk, tank, rabbit, sweet_pepper, bus, fox, sea, snake, plain, couch, cup, bridge, dinosaur, cattle, motorcycle, bed, apple, orange, bicycle, bear