--- 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_0980) 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 | 9e-05 | | LR Scheduler | linear | | Epochs | 4 | | Max Train Steps | 1332 | | Batch Size | 64 | | Weight Decay | 0.007 | | Seed | 980 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9981 | | Val Accuracy | 0.9101 | | Test Accuracy | 0.9084 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `lamp`, `cloud`, `forest`, `train`, `raccoon`, `butterfly`, `chimpanzee`, `beaver`, `turtle`, `road`, `seal`, `cattle`, `bee`, `rose`, `otter`, `shark`, `keyboard`, `house`, `elephant`, `television`, `willow_tree`, `kangaroo`, `possum`, `can`, `snake`, `chair`, `apple`, `table`, `bottle`, `tractor`, `bear`, `mouse`, `telephone`, `camel`, `fox`, `orange`, `rocket`, `lobster`, `wardrobe`, `crocodile`, `bowl`, `maple_tree`, `cup`, `poppy`, `crab`, `clock`, `pine_tree`, `flatfish`, `dolphin`, `shrew`