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_0527)
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 | 5e-05 |
| LR Scheduler | constant |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 527 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8871 |
| Val Accuracy | 0.8171 |
| Test Accuracy | 0.8118 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
wardrobe, sweet_pepper, maple_tree, dolphin, rose, boy, flatfish, telephone, bowl, can, crab, caterpillar, couch, porcupine, lobster, rabbit, bed, leopard, wolf, beaver, pine_tree, train, rocket, cattle, cockroach, road, aquarium_fish, woman, mushroom, camel, tank, snake, pickup_truck, fox, snail, house, shrew, skunk, squirrel, television, orange, seal, tiger, turtle, worm, kangaroo, orchid, sea, possum, crocodile