| 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_0872) | |
| 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** | val | | |
| | **Base Model** | `facebook/dino-vitb16` | | |
| | **Dataset** | CIFAR100 (50 classes) | | |
| ## Training Hyperparameters | |
| | Parameter | Value | | |
| |---|---| | |
| | Learning Rate | 0.0005 | | |
| | LR Scheduler | cosine | | |
| | Epochs | 9 | | |
| | Max Train Steps | 2997 | | |
| | Batch Size | 64 | | |
| | Weight Decay | 0.007 | | |
| | Seed | 872 | | |
| | Random Crop | True | | |
| | Random Flip | True | | |
| ## Performance | |
| | Metric | Value | | |
| |---|---| | |
| | Train Accuracy | 0.5067 | | |
| | Val Accuracy | 0.4285 | | |
| | Test Accuracy | 0.4256 | | |
| ## Training Categories | |
| The model was fine-tuned on the following 50 CIFAR100 classes: | |
| `cup`, `cattle`, `sunflower`, `ray`, `trout`, `chair`, `seal`, `aquarium_fish`, `couch`, `camel`, `maple_tree`, `beetle`, `wolf`, `butterfly`, `plain`, `tiger`, `lion`, `hamster`, `orange`, `fox`, `dinosaur`, `train`, `caterpillar`, `motorcycle`, `lawn_mower`, `pickup_truck`, `lobster`, `pear`, `spider`, `rabbit`, `clock`, `castle`, `skunk`, `keyboard`, `oak_tree`, `bottle`, `mushroom`, `possum`, `rose`, `pine_tree`, `turtle`, `telephone`, `beaver`, `dolphin`, `tank`, `table`, `whale`, `skyscraper`, `shark`, `porcupine` | |