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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_0021)
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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** | train |
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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 | 0.0003 |
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| LR Scheduler | cosine_with_restarts |
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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 | 21 |
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| Random Crop | False |
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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 | 0.5605 |
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| Val Accuracy | 0.4595 |
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| Test Accuracy | 0.4714 |
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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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`bottle`, `orange`, `apple`, `cup`, `flatfish`, `motorcycle`, `tiger`, `shrew`, `cockroach`, `elephant`, `tank`, `squirrel`, `tractor`, `wardrobe`, `ray`, `road`, `chair`, `plain`, `chimpanzee`, `skunk`, `bus`, `camel`, `turtle`, `keyboard`, `butterfly`, `rose`, `mouse`, `plate`, `bed`, `telephone`, `house`, `crab`, `sweet_pepper`, `lamp`, `hamster`, `oak_tree`, `pickup_truck`, `pine_tree`, `forest`, `worm`, `skyscraper`, `spider`, `sea`, `shark`, `aquarium_fish`, `lawn_mower`, `streetcar`, `bridge`, `cloud`, `bowl`
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