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_0776)
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 | 5e-05 |
| LR Scheduler | cosine |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 776 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9994 |
| Val Accuracy | 0.9547 |
| Test Accuracy | 0.9582 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
house, beetle, tractor, bridge, sweet_pepper, lamp, trout, rose, motorcycle, possum, rabbit, crocodile, rocket, lawn_mower, television, shrew, elephant, lion, shark, forest, chair, woman, dinosaur, spider, mushroom, table, dolphin, ray, pear, tulip, cattle, castle, bed, cockroach, beaver, snake, worm, wolf, raccoon, wardrobe, otter, mouse, telephone, camel, chimpanzee, cup, oak_tree, sea, orange, mountain