Model-J: ResNet Model (model_idx_0570)
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 | 9e-05 |
| LR Scheduler | constant |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 570 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9815 |
| Val Accuracy | 0.8869 |
| Test Accuracy | 0.8792 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
sweet_pepper, orange, woman, caterpillar, spider, mushroom, camel, sunflower, bicycle, man, mountain, keyboard, cockroach, boy, shrew, willow_tree, bowl, house, clock, skunk, girl, beetle, cup, bee, oak_tree, rabbit, poppy, mouse, kangaroo, squirrel, tractor, lizard, plain, cloud, bed, can, butterfly, baby, aquarium_fish, lamp, shark, skyscraper, orchid, bottle, whale, road, porcupine, forest, pickup_truck, wardrobe
