--- 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_0302) 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** | val | | **Base Model** | `facebook/dino-vitb16` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 0.0001 | | LR Scheduler | linear | | Epochs | 2 | | Max Train Steps | 666 | | Batch Size | 64 | | Weight Decay | 0.01 | | Seed | 302 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9898 | | Val Accuracy | 0.9347 | | Test Accuracy | 0.9326 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `camel`, `man`, `butterfly`, `ray`, `orange`, `streetcar`, `mushroom`, `pear`, `skunk`, `skyscraper`, `snail`, `palm_tree`, `lobster`, `lawn_mower`, `kangaroo`, `bee`, `chimpanzee`, `beetle`, `cloud`, `trout`, `bridge`, `bottle`, `tank`, `forest`, `bed`, `wolf`, `shrew`, `pine_tree`, `willow_tree`, `train`, `keyboard`, `mountain`, `tractor`, `cattle`, `tulip`, `whale`, `worm`, `television`, `lizard`, `sweet_pepper`, `apple`, `caterpillar`, `snake`, `hamster`, `couch`, `motorcycle`, `table`, `wardrobe`, `leopard`, `clock`