--- 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_0380) 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 | 3e-05 | | LR Scheduler | cosine_with_restarts | | Epochs | 8 | | Max Train Steps | 2664 | | Batch Size | 64 | | Weight Decay | 0.01 | | Seed | 380 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 1.0000 | | Val Accuracy | 0.9339 | | Test Accuracy | 0.9242 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `squirrel`, `spider`, `whale`, `pear`, `bee`, `castle`, `chair`, `beaver`, `baby`, `leopard`, `bicycle`, `tulip`, `skyscraper`, `tractor`, `shrew`, `porcupine`, `dinosaur`, `cloud`, `crab`, `sweet_pepper`, `rocket`, `cattle`, `possum`, `worm`, `skunk`, `sunflower`, `caterpillar`, `trout`, `tiger`, `orchid`, `bowl`, `bear`, `mouse`, `dolphin`, `lizard`, `plain`, `poppy`, `willow_tree`, `man`, `woman`, `plate`, `shark`, `wardrobe`, `beetle`, `pine_tree`, `crocodile`, `streetcar`, `telephone`, `snail`, `bus`