--- 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_0171) 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
 ## Model Details | Attribute | Value | |---|---| | **Subset** | DINO | | **Split** | test | | **Base Model** | `facebook/dino-vitb16` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 3e-05 | | LR Scheduler | constant_with_warmup | | Epochs | 6 | | Max Train Steps | 1998 | | Batch Size | 64 | | Weight Decay | 0.009 | | Seed | 171 | | Random Crop | False | | Random Flip | False | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9926 | | Val Accuracy | 0.8971 | | Test Accuracy | 0.9040 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `pear`, `wardrobe`, `cockroach`, `seal`, `crocodile`, `beaver`, `clock`, `table`, `boy`, `skunk`, `porcupine`, `shark`, `snake`, `bridge`, `palm_tree`, `cattle`, `orchid`, `wolf`, `trout`, `tank`, `rabbit`, `skyscraper`, `plate`, `willow_tree`, `girl`, `worm`, `raccoon`, `cup`, `tulip`, `bus`, `couch`, `lobster`, `camel`, `bear`, `mouse`, `otter`, `train`, `forest`, `keyboard`, `house`, `sweet_pepper`, `caterpillar`, `apple`, `kangaroo`, `bowl`, `hamster`, `plain`, `bicycle`, `mountain`, `lawn_mower`