Model-J: ResNet Model (model_idx_0546)
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
ProbeXModel Details
| Attribute | Value |
|---|
| Subset | ResNet |
| Split | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 5e-05 |
| LR Scheduler | linear |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 546 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8397 |
| Val Accuracy | 0.8165 |
| Test Accuracy | 0.8154 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
cattle, crocodile, cloud, chimpanzee, castle, can, telephone, elephant, leopard, trout, spider, poppy, bed, bridge, man, lawn_mower, boy, mushroom, squirrel, shark, tulip, keyboard, cup, pickup_truck, motorcycle, tiger, beaver, table, tractor, caterpillar, seal, otter, bowl, lion, camel, porcupine, bottle, plate, road, cockroach, bear, girl, clock, couch, plain, raccoon, butterfly, skyscraper, streetcar, beetle
