Model-J: ResNet Model (model_idx_0626)
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 | linear |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 626 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8083 |
| Val Accuracy | 0.7885 |
| Test Accuracy | 0.7786 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
shrew, ray, plate, pickup_truck, apple, baby, boy, aquarium_fish, tank, oak_tree, castle, tulip, plain, palm_tree, squirrel, wolf, dinosaur, bus, worm, whale, rabbit, couch, pine_tree, telephone, lawn_mower, caterpillar, motorcycle, road, man, sunflower, spider, trout, orchid, willow_tree, clock, sea, streetcar, seal, cattle, beaver, shark, bed, mouse, mushroom, train, mountain, orange, bicycle, lion, raccoon
