--- 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_0413) 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 | 5e-05 | | LR Scheduler | cosine_with_restarts | | Epochs | 8 | | Max Train Steps | 2664 | | Batch Size | 64 | | Weight Decay | 0.007 | | Seed | 413 | | Random Crop | True | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.9999 | | Val Accuracy | 0.9331 | | Test Accuracy | 0.9368 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `crab`, `bicycle`, `rocket`, `spider`, `camel`, `chimpanzee`, `mouse`, `bottle`, `mushroom`, `raccoon`, `pine_tree`, `mountain`, `snake`, `bear`, `rabbit`, `sweet_pepper`, `lizard`, `television`, `rose`, `skunk`, `poppy`, `lawn_mower`, `plain`, `keyboard`, `shrew`, `caterpillar`, `can`, `cockroach`, `cloud`, `beetle`, `cattle`, `wardrobe`, `leopard`, `hamster`, `possum`, `forest`, `flatfish`, `apple`, `shark`, `sea`, `castle`, `tractor`, `plate`, `wolf`, `bus`, `train`, `crocodile`, `table`, `clock`, `pear`