--- 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_0098) 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 | constant_with_warmup | | Epochs | 9 | | Max Train Steps | 2997 | | Batch Size | 64 | | Weight Decay | 0.03 | | Seed | 98 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9904 | | Val Accuracy | 0.9075 | | Test Accuracy | 0.9078 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `butterfly`, `tulip`, `mountain`, `camel`, `orange`, `apple`, `rocket`, `tractor`, `telephone`, `wardrobe`, `hamster`, `trout`, `dolphin`, `house`, `tiger`, `skyscraper`, `cloud`, `chimpanzee`, `dinosaur`, `man`, `clock`, `lizard`, `rose`, `pickup_truck`, `seal`, `train`, `pear`, `sweet_pepper`, `aquarium_fish`, `bridge`, `wolf`, `leopard`, `lion`, `plain`, `elephant`, `bowl`, `bear`, `kangaroo`, `baby`, `crocodile`, `whale`, `ray`, `pine_tree`, `snail`, `rabbit`, `caterpillar`, `palm_tree`, `keyboard`, `maple_tree`, `beetle`