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_0295")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0295")Quick Links
Model-J: SupViT Model (model_idx_0295)
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 | 0.0005 |
| LR Scheduler | linear |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 295 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9974 |
| Val Accuracy | 0.9203 |
| Test Accuracy | 0.9106 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
plain, lamp, man, spider, cloud, keyboard, otter, rabbit, mouse, possum, crocodile, boy, skyscraper, elephant, bee, squirrel, wolf, chair, bridge, caterpillar, bed, leopard, kangaroo, cockroach, woman, lizard, wardrobe, whale, butterfly, bowl, cup, beaver, raccoon, ray, orchid, bottle, lobster, sweet_pepper, mushroom, bicycle, willow_tree, skunk, can, pear, forest, turtle, pine_tree, table, shrew, trout
- Downloads last month
- 5
Model tree for ProbeX/Model-J__SupViT__model_idx_0295
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_0295") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")