--- 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_0766) 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 | 7e-05 | | LR Scheduler | constant_with_warmup | | Epochs | 5 | | Max Train Steps | 1665 | | Batch Size | 64 | | Weight Decay | 0.009 | | Seed | 766 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9602 | | Val Accuracy | 0.8771 | | Test Accuracy | 0.8784 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `palm_tree`, `chimpanzee`, `mouse`, `wardrobe`, `orange`, `lamp`, `cloud`, `aquarium_fish`, `baby`, `skyscraper`, `bear`, `house`, `tiger`, `lizard`, `shark`, `television`, `road`, `clock`, `skunk`, `bee`, `whale`, `lion`, `forest`, `table`, `bowl`, `lobster`, `squirrel`, `train`, `cattle`, `man`, `tank`, `plain`, `sweet_pepper`, `wolf`, `rabbit`, `orchid`, `shrew`, `rose`, `caterpillar`, `pickup_truck`, `plate`, `seal`, `streetcar`, `castle`, `worm`, `trout`, `beetle`, `chair`, `cockroach`, `pear`