--- 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_0363) 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** | test | | **Base Model** | `facebook/dino-vitb16` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 5e-05 | | LR Scheduler | constant | | Epochs | 2 | | Max Train Steps | 666 | | Batch Size | 64 | | Weight Decay | 0.01 | | Seed | 363 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9791 | | Val Accuracy | 0.8907 | | Test Accuracy | 0.8968 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `train`, `camel`, `lobster`, `mushroom`, `beetle`, `tractor`, `dinosaur`, `snake`, `flatfish`, `elephant`, `trout`, `motorcycle`, `wolf`, `couch`, `sea`, `possum`, `rabbit`, `bottle`, `bridge`, `seal`, `chimpanzee`, `mountain`, `aquarium_fish`, `snail`, `lizard`, `otter`, `clock`, `baby`, `can`, `house`, `leopard`, `orange`, `cattle`, `worm`, `pickup_truck`, `telephone`, `lion`, `raccoon`, `road`, `ray`, `whale`, `maple_tree`, `wardrobe`, `fox`, `porcupine`, `cloud`, `chair`, `pine_tree`, `sweet_pepper`, `kangaroo`