Model-J MAE
Collection
1002 items • Updated
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__MAE__model_idx_0373")
model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0373")Quick Links
Model-J: MAE Model (model_idx_0373)
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 | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 373 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9655 |
| Val Accuracy | 0.8824 |
| Test Accuracy | 0.8796 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
sea, otter, cattle, lion, squirrel, aquarium_fish, dolphin, sweet_pepper, streetcar, bus, worm, boy, shrew, keyboard, bee, chimpanzee, snail, tank, hamster, chair, tractor, wolf, table, lizard, snake, turtle, shark, leopard, caterpillar, bridge, trout, bowl, pear, woman, can, pine_tree, telephone, girl, cup, seal, mountain, clock, skunk, beetle, porcupine, plain, house, man, skyscraper, bed
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Model tree for ProbeX/Model-J__MAE__model_idx_0373
Base model
facebook/vit-mae-base
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__MAE__model_idx_0373") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")