--- 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_0537) 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

🌐 Project | 📃 Paper | 💻 GitHub | 🤗 Dataset

![ProbeX](https://raw.githubusercontent.com/eliahuhorwitz/ProbeX/main/imgs/poster.png) ## Model Details | Attribute | Value | |---|---| | **Subset** | DINO | | **Split** | train | | **Base Model** | `facebook/dino-vitb16` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 0.0001 | | LR Scheduler | cosine | | Epochs | 6 | | Max Train Steps | 1998 | | Batch Size | 64 | | Weight Decay | 0.005 | | Seed | 537 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 1.0000 | | Val Accuracy | 0.9283 | | Test Accuracy | 0.9268 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `lamp`, `camel`, `orange`, `aquarium_fish`, `maple_tree`, `bus`, `table`, `girl`, `crab`, `cloud`, `plain`, `cockroach`, `telephone`, `baby`, `squirrel`, `spider`, `tiger`, `seal`, `chair`, `beetle`, `lawn_mower`, `snail`, `cup`, `bridge`, `can`, `caterpillar`, `bicycle`, `bee`, `chimpanzee`, `clock`, `wolf`, `bottle`, `possum`, `cattle`, `rose`, `hamster`, `tulip`, `pickup_truck`, `turtle`, `bear`, `television`, `porcupine`, `willow_tree`, `pear`, `whale`, `mouse`, `worm`, `kangaroo`, `apple`, `keyboard`