--- 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_0801) 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
 ## 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 | 0.009 | | Seed | 801 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 1.0000 | | Val Accuracy | 0.9267 | | Test Accuracy | 0.9274 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `sunflower`, `wolf`, `whale`, `man`, `cattle`, `palm_tree`, `bed`, `turtle`, `bridge`, `shrew`, `maple_tree`, `lawn_mower`, `crocodile`, `elephant`, `tank`, `oak_tree`, `snake`, `poppy`, `castle`, `mushroom`, `aquarium_fish`, `crab`, `plate`, `sweet_pepper`, `skyscraper`, `cloud`, `keyboard`, `bottle`, `dolphin`, `otter`, `pear`, `table`, `wardrobe`, `mountain`, `bowl`, `lobster`, `tiger`, `pine_tree`, `dinosaur`, `porcupine`, `road`, `streetcar`, `chair`, `orchid`, `beetle`, `possum`, `motorcycle`, `camel`, `fox`, `flatfish`