Model-J: ResNet Model (model_idx_0071)
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 | train |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 5e-05 |
| LR Scheduler | constant |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 71 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9639 |
| Val Accuracy | 0.8771 |
| Test Accuracy | 0.8820 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lawn_mower, willow_tree, shrew, lobster, bee, girl, forest, rabbit, bed, wardrobe, orchid, cloud, train, wolf, flatfish, bowl, bear, porcupine, skunk, boy, otter, maple_tree, mountain, ray, dolphin, squirrel, house, chimpanzee, snail, cup, sweet_pepper, hamster, crocodile, pear, tank, plate, rocket, pine_tree, lion, cockroach, skyscraper, tractor, butterfly, bridge, apple, streetcar, sunflower, bus, leopard, kangaroo
