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_0004)
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 | 0.0003 |
| LR Scheduler | linear |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 4 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.6470 |
| Val Accuracy | 0.5216 |
| Test Accuracy | 0.5240 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
pear, telephone, crab, squirrel, skyscraper, tulip, sweet_pepper, poppy, worm, skunk, keyboard, pine_tree, bus, train, lamp, castle, sea, couch, trout, forest, orange, hamster, chair, aquarium_fish, sunflower, maple_tree, streetcar, chimpanzee, lizard, bicycle, beaver, girl, palm_tree, rocket, lawn_mower, bee, baby, plain, turtle, wardrobe, wolf, porcupine, oak_tree, television, tiger, table, plate, orchid, motorcycle, house