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base_model: facebook/dino-vitb16
library_name: transformers
pipeline_tag: image-classification
tags:
- probex
- model-j
- weight-space-learning
---
# Model-J: DINO Model (model_idx_0353)
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
<p align="center">
🌐 <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>
</p>
## Model Details
| Attribute | Value |
|---|---|
| **Subset** | DINO |
| **Split** | train |
| **Base Model** | `facebook/dino-vitb16` |
| **Dataset** | CIFAR100 (50 classes) |
## Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 9e-05 |
| LR Scheduler | cosine |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 353 |
| Random Crop | True |
| Random Flip | True |
## Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9979 |
| Val Accuracy | 0.9149 |
| Test Accuracy | 0.9204 |
## Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
`lobster`, `snail`, `baby`, `bowl`, `shrew`, `lawn_mower`, `can`, `apple`, `ray`, `tiger`, `wolf`, `turtle`, `otter`, `bridge`, `cloud`, `streetcar`, `tulip`, `skunk`, `rabbit`, `beetle`, `camel`, `elephant`, `raccoon`, `couch`, `tank`, `lamp`, `trout`, `woman`, `plate`, `table`, `spider`, `skyscraper`, `tractor`, `train`, `house`, `lizard`, `cup`, `seal`, `snake`, `pear`, `forest`, `pine_tree`, `mouse`, `maple_tree`, `sweet_pepper`, `worm`, `fox`, `bicycle`, `motorcycle`, `leopard`
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