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_0916)
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 | train |
| Base Model | facebook/dino-vitb16 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 7e-05 |
| LR Scheduler | cosine |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 916 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9963 |
| Val Accuracy | 0.9331 |
| Test Accuracy | 0.9274 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
hamster, shark, tiger, turtle, tulip, rose, beaver, telephone, pear, orchid, wardrobe, mushroom, flatfish, chair, train, cloud, sweet_pepper, maple_tree, sea, raccoon, camel, whale, bottle, palm_tree, snail, motorcycle, house, streetcar, clock, bowl, pickup_truck, sunflower, plate, apple, bus, cockroach, chimpanzee, spider, lawn_mower, wolf, dolphin, willow_tree, leopard, cattle, snake, bear, lamp, man, couch, television