--- 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_0546) 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 | 3e-05 | | LR Scheduler | constant | | Epochs | 9 | | Max Train Steps | 2997 | | Batch Size | 64 | | Weight Decay | 0.01 | | Seed | 546 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9946 | | Val Accuracy | 0.9179 | | Test Accuracy | 0.8954 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `bed`, `man`, `television`, `keyboard`, `apple`, `butterfly`, `chimpanzee`, `lizard`, `can`, `kangaroo`, `cup`, `girl`, `fox`, `dinosaur`, `leopard`, `lion`, `pear`, `plate`, `motorcycle`, `tractor`, `clock`, `tulip`, `orchid`, `mushroom`, `maple_tree`, `porcupine`, `skyscraper`, `crab`, `house`, `snake`, `bus`, `forest`, `elephant`, `cattle`, `table`, `rabbit`, `crocodile`, `streetcar`, `oak_tree`, `sweet_pepper`, `palm_tree`, `telephone`, `shark`, `trout`, `willow_tree`, `otter`, `mouse`, `bridge`, `snail`, `dolphin`