| base_model: google/vit-base-patch16-224 | |
| library_name: transformers | |
| pipeline_tag: image-classification | |
| tags: | |
| - probex | |
| - model-j | |
| - weight-space-learning | |
| # Model-J: SupViT Model (model_idx_0168) | |
| 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** | SupViT | | |
| | **Split** | test | | |
| | **Base Model** | `google/vit-base-patch16-224` | | |
| | **Dataset** | CIFAR100 (50 classes) | | |
| ## Training Hyperparameters | |
| | Parameter | Value | | |
| |---|---| | |
| | Learning Rate | 5e-05 | | |
| | LR Scheduler | constant_with_warmup | | |
| | Epochs | 8 | | |
| | Max Train Steps | 2664 | | |
| | Batch Size | 64 | | |
| | Weight Decay | 0.005 | | |
| | Seed | 168 | | |
| | Random Crop | False | | |
| | Random Flip | True | | |
| ## Performance | |
| | Metric | Value | | |
| |---|---| | |
| | Train Accuracy | 0.9984 | | |
| | Val Accuracy | 0.9459 | | |
| | Test Accuracy | 0.9478 | | |
| ## Training Categories | |
| The model was fine-tuned on the following 50 CIFAR100 classes: | |
| `lion`, `cloud`, `worm`, `seal`, `forest`, `bear`, `streetcar`, `plain`, `apple`, `hamster`, `cockroach`, `castle`, `rose`, `flatfish`, `spider`, `bus`, `pickup_truck`, `pear`, `plate`, `house`, `wolf`, `rocket`, `bridge`, `wardrobe`, `willow_tree`, `squirrel`, `boy`, `lobster`, `chair`, `keyboard`, `shark`, `crab`, `telephone`, `beetle`, `elephant`, `clock`, `cup`, `chimpanzee`, `orchid`, `trout`, `whale`, `turtle`, `sea`, `bicycle`, `mountain`, `tank`, `mushroom`, `lawn_mower`, `otter`, `skyscraper` | |