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README.md
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---
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base_model: google/vit-base-patch16-224
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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: SupViT Model (model_idx_0442)
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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** | SupViT |
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| **Split** | train |
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| **Base Model** | `google/vit-base-patch16-224` |
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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 | 5 |
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| Max Train Steps | 1665 |
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| Batch Size | 64 |
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| Weight Decay | 0.009 |
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| Seed | 442 |
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| Random Crop | False |
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| Random Flip | False |
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## Performance
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| Metric | Value |
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|---|---|
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| Train Accuracy | 0.9996 |
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| Val Accuracy | 0.9328 |
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| Test Accuracy | 0.9342 |
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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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`rose`, `mouse`, `tiger`, `table`, `willow_tree`, `orchid`, `camel`, `clock`, `palm_tree`, `couch`, `bus`, `raccoon`, `television`, `otter`, `sea`, `maple_tree`, `road`, `apple`, `seal`, `woman`, `dinosaur`, `ray`, `beetle`, `motorcycle`, `train`, `boy`, `beaver`, `dolphin`, `man`, `butterfly`, `crab`, `plate`, `shark`, `hamster`, `bridge`, `bear`, `shrew`, `baby`, `chair`, `telephone`, `house`, `kangaroo`, `leopard`, `bed`, `bee`, `wolf`, `whale`, `streetcar`, `snake`, `forest`
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