--- 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_0044) 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 | linear | | Epochs | 2 | | Max Train Steps | 666 | | Batch Size | 64 | | Weight Decay | 0.005 | | Seed | 44 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9898 | | Val Accuracy | 0.9269 | | Test Accuracy | 0.9270 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `lawn_mower`, `rabbit`, `dinosaur`, `kangaroo`, `cockroach`, `elephant`, `sunflower`, `mushroom`, `streetcar`, `lobster`, `tractor`, `orchid`, `butterfly`, `lizard`, `pear`, `bed`, `chimpanzee`, `rose`, `house`, `castle`, `spider`, `woman`, `train`, `plate`, `boy`, `bowl`, `keyboard`, `clock`, `bridge`, `aquarium_fish`, `ray`, `motorcycle`, `rocket`, `crocodile`, `snail`, `baby`, `orange`, `trout`, `sweet_pepper`, `whale`, `palm_tree`, `cloud`, `pine_tree`, `apple`, `hamster`, `forest`, `turtle`, `tulip`, `bicycle`, `leopard`