--- 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_0634) 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** | val | | **Base Model** | `facebook/dino-vitb16` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 5e-05 | | LR Scheduler | cosine_with_restarts | | Epochs | 5 | | Max Train Steps | 1665 | | Batch Size | 64 | | Weight Decay | 0.005 | | Seed | 634 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9988 | | Val Accuracy | 0.9147 | | Test Accuracy | 0.9196 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `orange`, `rabbit`, `rocket`, `girl`, `bowl`, `pear`, `cup`, `dolphin`, `wardrobe`, `motorcycle`, `camel`, `kangaroo`, `hamster`, `squirrel`, `bear`, `castle`, `mouse`, `snake`, `butterfly`, `forest`, `plate`, `skunk`, `house`, `wolf`, `aquarium_fish`, `cloud`, `otter`, `pickup_truck`, `sea`, `orchid`, `possum`, `spider`, `fox`, `streetcar`, `snail`, `man`, `crab`, `bus`, `shark`, `seal`, `oak_tree`, `bridge`, `turtle`, `raccoon`, `chimpanzee`, `tiger`, `whale`, `tank`, `willow_tree`, `bottle`