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_0397)
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 | constant |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 397 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.3265 |
| Val Accuracy | 0.2955 |
| Test Accuracy | 0.2974 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
dolphin, boy, otter, pickup_truck, orange, whale, motorcycle, tank, ray, skunk, squirrel, cockroach, shark, aquarium_fish, plain, palm_tree, trout, train, maple_tree, television, sweet_pepper, pine_tree, worm, willow_tree, tiger, mountain, elephant, castle, tulip, lizard, raccoon, leopard, lion, skyscraper, rabbit, telephone, turtle, dinosaur, tractor, bear, bus, lobster, oak_tree, lawn_mower, cup, cattle, table, bridge, shrew, sea