metadata
base_model: facebook/vit-mae-base
library_name: transformers
pipeline_tag: image-classification
tags:
- probex
- model-j
- weight-space-learning
Model-J: MAE Model (model_idx_0780)
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 | MAE |
| Split | train |
| Base Model | facebook/vit-mae-base |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | constant |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 780 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9417 |
| Val Accuracy | 0.8605 |
| Test Accuracy | 0.8492 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
turtle, couch, butterfly, house, aquarium_fish, pine_tree, girl, rose, shrew, leopard, rabbit, table, crocodile, sunflower, snail, dolphin, caterpillar, worm, lion, cattle, pickup_truck, baby, skunk, rocket, skyscraper, hamster, chimpanzee, squirrel, flatfish, cockroach, bee, tulip, clock, mountain, plain, otter, bridge, lamp, bicycle, tank, fox, shark, raccoon, whale, camel, bus, oak_tree, crab, willow_tree, ray