--- 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_0522) 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 | 3e-05 | | LR Scheduler | cosine | | Epochs | 9 | | Max Train Steps | 2997 | | Batch Size | 64 | | Weight Decay | 0.01 | | Seed | 522 | | Random Crop | True | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 1.0000 | | Val Accuracy | 0.9416 | | Test Accuracy | 0.9394 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `crab`, `apple`, `willow_tree`, `forest`, `raccoon`, `couch`, `butterfly`, `bee`, `telephone`, `camel`, `fox`, `sea`, `sweet_pepper`, `tank`, `plain`, `tulip`, `motorcycle`, `skyscraper`, `tiger`, `cattle`, `spider`, `plate`, `chimpanzee`, `orchid`, `worm`, `leopard`, `aquarium_fish`, `chair`, `bear`, `bottle`, `pear`, `bed`, `crocodile`, `trout`, `squirrel`, `kangaroo`, `lobster`, `boy`, `cockroach`, `train`, `rocket`, `dolphin`, `flatfish`, `sunflower`, `dinosaur`, `possum`, `lizard`, `lion`, `mushroom`, `ray`