--- base_model: microsoft/resnet-101 library_name: transformers pipeline_tag: image-classification tags: - probex - model-j - weight-space-learning --- # Model-J: ResNet Model (model_idx_0869) 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** | ResNet | | **Split** | val | | **Base Model** | `microsoft/resnet-101` | | **Dataset** | CIFAR100 (50 classes) | ## Training Hyperparameters | Parameter | Value | |---|---| | Learning Rate | 5e-05 | | LR Scheduler | cosine_with_restarts | | Epochs | 6 | | Max Train Steps | 1998 | | Batch Size | 64 | | Weight Decay | 0.03 | | Seed | 869 | | Random Crop | False | | Random Flip | True | ## Performance | Metric | Value | |---|---| | Train Accuracy | 0.8861 | | Val Accuracy | 0.8395 | | Test Accuracy | 0.8486 | ## Training Categories The model was fine-tuned on the following 50 CIFAR100 classes: `willow_tree`, `mushroom`, `lizard`, `bus`, `woman`, `bridge`, `trout`, `rocket`, `girl`, `lamp`, `clock`, `possum`, `crab`, `forest`, `lion`, `hamster`, `cloud`, `can`, `bowl`, `rose`, `camel`, `dolphin`, `maple_tree`, `castle`, `turtle`, `sea`, `bee`, `boy`, `cockroach`, `apple`, `crocodile`, `porcupine`, `spider`, `streetcar`, `train`, `mouse`, `tank`, `table`, `wardrobe`, `cup`, `aquarium_fish`, `television`, `skunk`, `cattle`, `mountain`, `plain`, `leopard`, `orange`, `chair`, `beaver`