--- 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_0542) 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 | cosine | | Epochs | 3 | | Max Train Steps | 999 | | Batch Size | 64 | | Weight Decay | 0.009 | | Seed | 542 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9957 | | Val Accuracy | 0.9176 | | Test Accuracy | 0.9188 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `girl`, `poppy`, `spider`, `leopard`, `woman`, `kangaroo`, `house`, `pine_tree`, `turtle`, `skunk`, `sweet_pepper`, `beaver`, `seal`, `pear`, `mouse`, `sea`, `mushroom`, `cattle`, `camel`, `squirrel`, `wardrobe`, `worm`, `shark`, `dinosaur`, `cockroach`, `bus`, `possum`, `tank`, `chimpanzee`, `otter`, `clock`, `bottle`, `whale`, `television`, `snake`, `apple`, `tulip`, `orchid`, `porcupine`, `keyboard`, `tiger`, `cup`, `oak_tree`, `cloud`, `boy`, `tractor`, `snail`, `crocodile`, `pickup_truck`, `flatfish`