--- 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_0686) 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 | 7 | | Max Train Steps | 2331 | | Batch Size | 64 | | Weight Decay | 0.007 | | Seed | 686 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9995 | | Val Accuracy | 0.9184 | | Test Accuracy | 0.9242 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `pickup_truck`, `lawn_mower`, `chimpanzee`, `tiger`, `bicycle`, `chair`, `lizard`, `whale`, `forest`, `rocket`, `tractor`, `flatfish`, `beetle`, `pear`, `mountain`, `trout`, `maple_tree`, `orchid`, `sunflower`, `cattle`, `streetcar`, `television`, `wardrobe`, `orange`, `apple`, `bed`, `mouse`, `skyscraper`, `bottle`, `hamster`, `skunk`, `wolf`, `rose`, `elephant`, `possum`, `lamp`, `oak_tree`, `beaver`, `snail`, `bear`, `shark`, `can`, `lobster`, `pine_tree`, `ray`, `camel`, `bus`, `aquarium_fish`, `plate`, `road`