Model-J: ResNet Model (model_idx_0722)
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 | cosine_with_restarts |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 722 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8001 |
| Val Accuracy | 0.7917 |
| Test Accuracy | 0.7824 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
porcupine, crab, willow_tree, ray, otter, sea, castle, chair, tractor, bear, elephant, sunflower, turtle, cockroach, lamp, tulip, poppy, skyscraper, man, snail, mountain, bridge, house, woman, leopard, pine_tree, aquarium_fish, motorcycle, lawn_mower, beaver, telephone, bicycle, table, plain, chimpanzee, can, pickup_truck, caterpillar, rose, girl, skunk, rocket, palm_tree, camel, boy, butterfly, sweet_pepper, cup, crocodile, dolphin
