--- 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_0226) 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 | 5e-05 | | LR Scheduler | cosine_with_restarts | | Epochs | 3 | | Max Train Steps | 999 | | Batch Size | 64 | | Weight Decay | 0.005 | | Seed | 226 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9965 | | Val Accuracy | 0.9240 | | Test Accuracy | 0.9252 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `cloud`, `forest`, `trout`, `poppy`, `oak_tree`, `boy`, `bee`, `cup`, `mushroom`, `tiger`, `butterfly`, `bridge`, `telephone`, `plain`, `cattle`, `sea`, `bowl`, `house`, `fox`, `orange`, `streetcar`, `willow_tree`, `sweet_pepper`, `road`, `pine_tree`, `dolphin`, `spider`, `aquarium_fish`, `television`, `bed`, `pickup_truck`, `wolf`, `rose`, `crocodile`, `cockroach`, `tractor`, `ray`, `baby`, `possum`, `lamp`, `beetle`, `squirrel`, `lizard`, `motorcycle`, `dinosaur`, `crab`, `tulip`, `girl`, `caterpillar`, `elephant`