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README.md
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---
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base_model: facebook/dino-vitb16
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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: DINO Model (model_idx_0679)
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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** | DINO |
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| **Split** | test |
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| **Base Model** | `facebook/dino-vitb16` |
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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 | 3e-05 |
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| LR Scheduler | constant_with_warmup |
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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 | 0.007 |
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| Seed | 679 |
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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 | 0.9901 |
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| Val Accuracy | 0.9029 |
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| Test Accuracy | 0.9114 |
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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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`aquarium_fish`, `lawn_mower`, `possum`, `cup`, `bee`, `flatfish`, `streetcar`, `sunflower`, `tank`, `keyboard`, `skunk`, `willow_tree`, `turtle`, `crab`, `fox`, `mouse`, `shark`, `cloud`, `cattle`, `mountain`, `wolf`, `motorcycle`, `bear`, `table`, `dolphin`, `whale`, `bus`, `orange`, `forest`, `plain`, `bridge`, `apple`, `skyscraper`, `kangaroo`, `rocket`, `squirrel`, `beetle`, `bed`, `bicycle`, `castle`, `worm`, `shrew`, `crocodile`, `television`, `spider`, `tiger`, `train`, `porcupine`, `raccoon`, `baby`
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