--- 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_0696) 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 | 5e-05 | | LR Scheduler | linear | | Epochs | 3 | | Max Train Steps | 999 | | Batch Size | 64 | | Weight Decay | 0.03 | | Seed | 696 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9976 | | Val Accuracy | 0.9029 | | Test Accuracy | 0.9100 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `squirrel`, `orange`, `shark`, `beaver`, `trout`, `worm`, `lobster`, `crab`, `wolf`, `couch`, `possum`, `bowl`, `raccoon`, `sweet_pepper`, `plate`, `streetcar`, `aquarium_fish`, `sea`, `apple`, `pine_tree`, `sunflower`, `otter`, `oak_tree`, `cockroach`, `shrew`, `snake`, `leopard`, `rocket`, `seal`, `forest`, `elephant`, `lawn_mower`, `tractor`, `bear`, `mouse`, `pear`, `mountain`, `skyscraper`, `motorcycle`, `hamster`, `whale`, `bed`, `table`, `train`, `woman`, `crocodile`, `maple_tree`, `fox`, `baby`, `plain`