--- 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_0912) 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 | 0.0005 | | LR Scheduler | cosine | | Epochs | 9 | | Max Train Steps | 2997 | | Batch Size | 64 | | Weight Decay | 0.009 | | Seed | 912 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.5246 | | Val Accuracy | 0.4432 | | Test Accuracy | 0.4302 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `sunflower`, `palm_tree`, `porcupine`, `table`, `lawn_mower`, `skyscraper`, `sweet_pepper`, `maple_tree`, `mountain`, `rocket`, `whale`, `dolphin`, `bear`, `seal`, `clock`, `girl`, `cattle`, `television`, `tractor`, `worm`, `plain`, `wolf`, `cloud`, `bus`, `spider`, `lizard`, `camel`, `caterpillar`, `tulip`, `cockroach`, `elephant`, `apple`, `snail`, `leopard`, `kangaroo`, `plate`, `shark`, `lion`, `rabbit`, `pickup_truck`, `bottle`, `dinosaur`, `lobster`, `keyboard`, `tank`, `aquarium_fish`, `road`, `cup`, `beaver`, `streetcar`