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_0739)
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 | linear |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 739 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9928 |
| Val Accuracy | 0.9251 |
| Test Accuracy | 0.9164 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
camel, possum, rocket, can, lobster, house, baby, sweet_pepper, streetcar, mouse, whale, wolf, snake, leopard, chimpanzee, shark, train, caterpillar, bottle, oak_tree, lamp, apple, sea, skunk, porcupine, man, clock, mushroom, couch, bee, skyscraper, orchid, chair, maple_tree, worm, fox, pine_tree, forest, tiger, pickup_truck, lizard, keyboard, elephant, flatfish, plate, rabbit, seal, telephone, cattle, table