--- 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_0512) 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

🌐 Project | 📃 Paper | 💻 GitHub | 🤗 Dataset

![ProbeX](https://raw.githubusercontent.com/eliahuhorwitz/ProbeX/main/imgs/poster.png) ## 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_with_restarts | | Epochs | 6 | | Max Train Steps | 1998 | | Batch Size | 64 | | Weight Decay | 0.03 | | Seed | 512 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9992 | | Val Accuracy | 0.9235 | | Test Accuracy | 0.9312 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `raccoon`, `shrew`, `skyscraper`, `otter`, `apple`, `sea`, `dinosaur`, `sunflower`, `hamster`, `shark`, `bee`, `wardrobe`, `chair`, `baby`, `television`, `cloud`, `palm_tree`, `orange`, `chimpanzee`, `squirrel`, `castle`, `bed`, `bear`, `can`, `bridge`, `dolphin`, `seal`, `caterpillar`, `bottle`, `rabbit`, `butterfly`, `pickup_truck`, `lizard`, `tiger`, `skunk`, `train`, `trout`, `oak_tree`, `aquarium_fish`, `tractor`, `crocodile`, `motorcycle`, `mushroom`, `lamp`, `rocket`, `lawn_mower`, `girl`, `orchid`, `maple_tree`, `telephone`