--- 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_0125) 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 | constant_with_warmup | | Epochs | 8 | | Max Train Steps | 2664 | | Batch Size | 64 | | Weight Decay | 0.03 | | Seed | 125 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9850 | | Val Accuracy | 0.8805 | | Test Accuracy | 0.8824 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `bed`, `spider`, `camel`, `sunflower`, `willow_tree`, `pine_tree`, `fox`, `road`, `lion`, `train`, `bee`, `maple_tree`, `apple`, `beaver`, `skunk`, `possum`, `boy`, `crocodile`, `plain`, `streetcar`, `tank`, `caterpillar`, `motorcycle`, `oak_tree`, `hamster`, `bowl`, `porcupine`, `bridge`, `bus`, `pear`, `pickup_truck`, `table`, `forest`, `lamp`, `wardrobe`, `dolphin`, `television`, `orange`, `cup`, `worm`, `rabbit`, `poppy`, `tulip`, `orchid`, `couch`, `keyboard`, `mushroom`, `bottle`, `baby`, `man`