--- 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_0440) 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** | test | | **Base Model** | `facebook/dino-vitb16` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 7e-05 | | LR Scheduler | constant | | Epochs | 9 | | Max Train Steps | 2997 | | Batch Size | 64 | | Weight Decay | 0.03 | | Seed | 440 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9818 | | Val Accuracy | 0.8704 | | Test Accuracy | 0.8748 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `possum`, `crab`, `house`, `lawn_mower`, `cockroach`, `bridge`, `kangaroo`, `camel`, `butterfly`, `flatfish`, `shark`, `boy`, `cloud`, `couch`, `porcupine`, `skunk`, `orchid`, `plate`, `oak_tree`, `mountain`, `bottle`, `hamster`, `cup`, `cattle`, `motorcycle`, `seal`, `wardrobe`, `mouse`, `poppy`, `turtle`, `trout`, `worm`, `dinosaur`, `table`, `willow_tree`, `ray`, `castle`, `aquarium_fish`, `bed`, `bus`, `rabbit`, `bicycle`, `beaver`, `lizard`, `tank`, `chimpanzee`, `squirrel`, `dolphin`, `tulip`, `bee`