Model-J: ResNet Model (model_idx_0468)
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 | 3e-05 |
| LR Scheduler | cosine |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 468 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.7912 |
| Val Accuracy | 0.7749 |
| Test Accuracy | 0.7768 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lawn_mower, dolphin, kangaroo, fox, mushroom, porcupine, can, trout, crab, tractor, beetle, man, leopard, crocodile, woman, skunk, boy, butterfly, cockroach, poppy, pear, maple_tree, ray, oak_tree, skyscraper, telephone, castle, couch, lizard, train, shrew, bus, forest, bed, aquarium_fish, wolf, plain, bottle, worm, orange, willow_tree, hamster, spider, raccoon, dinosaur, bridge, mountain, house, bicycle, bee
