--- 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_0571) 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 | 5e-05 | | LR Scheduler | cosine_with_restarts | | Epochs | 5 | | Max Train Steps | 1665 | | Batch Size | 64 | | Weight Decay | 0.03 | | Seed | 571 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9997 | | Val Accuracy | 0.9325 | | Test Accuracy | 0.9324 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `butterfly`, `oak_tree`, `dolphin`, `turtle`, `cloud`, `beetle`, `bowl`, `elephant`, `camel`, `sea`, `hamster`, `seal`, `spider`, `pickup_truck`, `rose`, `lamp`, `plate`, `chimpanzee`, `mouse`, `caterpillar`, `road`, `orange`, `whale`, `willow_tree`, `chair`, `bicycle`, `maple_tree`, `bear`, `rocket`, `leopard`, `tulip`, `streetcar`, `telephone`, `worm`, `snail`, `shark`, `aquarium_fish`, `forest`, `skunk`, `man`, `table`, `castle`, `tractor`, `bottle`, `house`, `mushroom`, `bed`, `clock`, `fox`, `train`