--- 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_0923) 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 | 7e-05 | | LR Scheduler | linear | | Epochs | 8 | | Max Train Steps | 2664 | | Batch Size | 64 | | Weight Decay | 0.005 | | Seed | 923 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 1.0000 | | Val Accuracy | 0.9283 | | Test Accuracy | 0.9264 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `willow_tree`, `orchid`, `bottle`, `bowl`, `motorcycle`, `lion`, `pine_tree`, `chimpanzee`, `porcupine`, `boy`, `dinosaur`, `turtle`, `spider`, `sea`, `hamster`, `apple`, `trout`, `bridge`, `shark`, `train`, `fox`, `whale`, `maple_tree`, `telephone`, `skunk`, `road`, `wolf`, `camel`, `streetcar`, `cloud`, `caterpillar`, `chair`, `mountain`, `leopard`, `seal`, `orange`, `skyscraper`, `castle`, `plate`, `house`, `oak_tree`, `lawn_mower`, `girl`, `rabbit`, `bicycle`, `pickup_truck`, `rose`, `cup`, `cattle`, `tiger`