--- 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_0097) 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 | 9e-05 | | LR Scheduler | cosine_with_restarts | | Epochs | 9 | | Max Train Steps | 2997 | | Batch Size | 64 | | Weight Decay | 0.009 | | Seed | 97 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9999 | | Val Accuracy | 0.9253 | | Test Accuracy | 0.9270 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `train`, `fox`, `chimpanzee`, `rabbit`, `cockroach`, `wardrobe`, `skunk`, `tractor`, `caterpillar`, `bed`, `whale`, `oak_tree`, `kangaroo`, `bicycle`, `worm`, `bee`, `orange`, `camel`, `orchid`, `sea`, `otter`, `lion`, `sweet_pepper`, `telephone`, `motorcycle`, `can`, `forest`, `pear`, `beaver`, `road`, `rocket`, `crocodile`, `crab`, `pine_tree`, `squirrel`, `boy`, `seal`, `poppy`, `tiger`, `couch`, `mouse`, `mountain`, `plain`, `hamster`, `leopard`, `sunflower`, `woman`, `tank`, `turtle`, `tulip`