--- 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_0619) 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 | 0.0005 | | LR Scheduler | linear | | Epochs | 4 | | Max Train Steps | 1332 | | Batch Size | 64 | | Weight Decay | 0.03 | | Seed | 619 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.3729 | | Val Accuracy | 0.3125 | | Test Accuracy | 0.3326 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `beaver`, `pear`, `mountain`, `leopard`, `flatfish`, `cockroach`, `ray`, `keyboard`, `rocket`, `snake`, `fox`, `dinosaur`, `otter`, `tank`, `table`, `lamp`, `cloud`, `mouse`, `crocodile`, `orange`, `spider`, `bus`, `mushroom`, `rabbit`, `chimpanzee`, `bicycle`, `rose`, `hamster`, `crab`, `wardrobe`, `cattle`, `couch`, `cup`, `maple_tree`, `castle`, `forest`, `trout`, `telephone`, `can`, `orchid`, `man`, `pine_tree`, `television`, `caterpillar`, `clock`, `camel`, `snail`, `pickup_truck`, `bear`, `bowl`