Model-J SupViT
Collection
998 items • Updated
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0929")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0929")Quick Links
Model-J: SupViT Model (model_idx_0929)
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 | 3e-05 |
| LR Scheduler | cosine |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 929 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9959 |
| Val Accuracy | 0.9448 |
| Test Accuracy | 0.9472 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
snail, streetcar, cloud, wardrobe, rose, rabbit, bowl, lion, worm, sweet_pepper, chimpanzee, shrew, possum, skunk, lawn_mower, cup, bridge, raccoon, road, sunflower, skyscraper, mushroom, bus, bee, house, crab, forest, plain, man, kangaroo, fox, tractor, dinosaur, snake, pine_tree, porcupine, girl, seal, train, rocket, cockroach, pear, butterfly, turtle, squirrel, trout, cattle, elephant, television, apple
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Model tree for ProbeX/Model-J__SupViT__model_idx_0929
Base model
google/vit-base-patch16-224
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__SupViT__model_idx_0929") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")