--- 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_0772) 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 | 0.0005 | | LR Scheduler | cosine_with_restarts | | Epochs | 3 | | Max Train Steps | 999 | | Batch Size | 64 | | Weight Decay | 0.05 | | Seed | 772 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.3343 | | Val Accuracy | 0.3200 | | Test Accuracy | 0.3230 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `girl`, `snake`, `shrew`, `skyscraper`, `bee`, `telephone`, `dolphin`, `road`, `camel`, `leopard`, `house`, `chair`, `tractor`, `beaver`, `bicycle`, `lion`, `bowl`, `shark`, `snail`, `squirrel`, `baby`, `man`, `motorcycle`, `pine_tree`, `wardrobe`, `crocodile`, `rabbit`, `pear`, `otter`, `cattle`, `orange`, `streetcar`, `television`, `mouse`, `keyboard`, `plain`, `rose`, `orchid`, `lawn_mower`, `possum`, `tank`, `mushroom`, `train`, `turtle`, `porcupine`, `spider`, `cockroach`, `table`, `poppy`, `lizard`