Model-J: ResNet Model (model_idx_0828)
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 | 0.0001 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 828 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9727 |
| Val Accuracy | 0.8883 |
| Test Accuracy | 0.8816 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
camel, butterfly, cockroach, forest, castle, house, skyscraper, apple, lion, chair, lizard, crocodile, orchid, baby, tank, shrew, ray, mouse, table, rocket, orange, lobster, worm, rabbit, snail, pickup_truck, motorcycle, willow_tree, poppy, boy, tulip, otter, bowl, dinosaur, lawn_mower, whale, bee, sea, elephant, dolphin, skunk, aquarium_fish, kangaroo, bottle, spider, chimpanzee, man, clock, turtle, bicycle
