metadata
base_model: facebook/dino-vitb16
library_name: transformers
pipeline_tag: image-classification
tags:
- probex
- model-j
- weight-space-learning
Model-J: DINO Model (model_idx_0576)
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 | DINO |
| Split | val |
| Base Model | facebook/dino-vitb16 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 7e-05 |
| LR Scheduler | linear |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 576 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9994 |
| Val Accuracy | 0.9347 |
| Test Accuracy | 0.9292 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
kangaroo, squirrel, beetle, maple_tree, leopard, snail, pickup_truck, plain, bear, baby, cockroach, whale, shark, clock, poppy, turtle, sweet_pepper, train, camel, cloud, dolphin, lamp, rabbit, skunk, wolf, bus, shrew, snake, chair, tank, butterfly, tulip, crocodile, lawn_mower, beaver, plate, fox, pear, motorcycle, flatfish, can, house, cattle, worm, streetcar, skyscraper, road, keyboard, bicycle, tractor