Model-J: ResNet Model (model_idx_0088)
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 | 3e-05 |
| LR Scheduler | constant |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 88 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9252 |
| Val Accuracy | 0.8520 |
| Test Accuracy | 0.8606 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
whale, dinosaur, spider, tiger, elephant, mouse, bear, rocket, television, tulip, beetle, dolphin, camel, road, wardrobe, forest, train, hamster, chair, pickup_truck, lobster, lizard, telephone, pine_tree, plain, clock, snail, boy, turtle, beaver, maple_tree, cockroach, cup, crab, sweet_pepper, lawn_mower, plate, tank, otter, wolf, porcupine, rose, girl, woman, motorcycle, couch, table, fox, house, orange
