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README.md
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---
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base_model: facebook/vit-mae-base
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library_name: transformers
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pipeline_tag: image-classification
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tags:
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- probex
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- model-j
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- weight-space-learning
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---
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# Model-J: MAE Model (model_idx_0286)
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This model is part of the **Model-J** dataset, introduced in:
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**Learning on Model Weights using Tree Experts** (CVPR 2025) by Eliahu Horwitz*, Bar Cavia*, Jonathan Kahana*, Yedid Hoshen
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<p align="center">
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🌐 <a href="https://horwitz.ai/probex" target="_blank">Project</a> | 📃 <a href="https://arxiv.org/abs/2410.13569" target="_blank">Paper</a> | 💻 <a href="https://github.com/eliahuhorwitz/ProbeX" target="_blank">GitHub</a> | 🤗 <a href="https://huggingface.co/ProbeX" target="_blank">Dataset</a>
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</p>
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## Model Details
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| Attribute | Value |
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|---|---|
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| **Subset** | MAE |
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| **Split** | test |
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| **Base Model** | `facebook/vit-mae-base` |
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| **Dataset** | CIFAR100 (50 classes) |
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## Training Hyperparameters
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| Parameter | Value |
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|---|---|
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| Learning Rate | 0.0001 |
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| LR Scheduler | linear |
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| Epochs | 3 |
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| Max Train Steps | 999 |
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| Batch Size | 64 |
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| Weight Decay | 0.007 |
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| Seed | 286 |
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| Random Crop | True |
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| Random Flip | True |
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## Performance
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| Metric | Value |
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|---|---|
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| Train Accuracy | 0.9495 |
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| Val Accuracy | 0.8749 |
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| Test Accuracy | 0.8786 |
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## Training Categories
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The model was fine-tuned on the following 50 CIFAR100 classes:
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`bowl`, `baby`, `dinosaur`, `forest`, `fox`, `streetcar`, `road`, `bear`, `oak_tree`, `cattle`, `sunflower`, `kangaroo`, `seal`, `mushroom`, `aquarium_fish`, `crocodile`, `mountain`, `bridge`, `pickup_truck`, `cloud`, `rose`, `apple`, `pine_tree`, `worm`, `orange`, `tank`, `maple_tree`, `man`, `palm_tree`, `beaver`, `caterpillar`, `bicycle`, `otter`, `wardrobe`, `bottle`, `snake`, `plain`, `snail`, `cup`, `tractor`, `trout`, `chair`, `rabbit`, `castle`, `tulip`, `shark`, `train`, `willow_tree`, `squirrel`, `sea`
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