Model-J: ResNet Model (model_idx_0830)
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 | 0.0001 |
| LR Scheduler | constant |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 830 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9619 |
| Val Accuracy | 0.8867 |
| Test Accuracy | 0.8812 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
tiger, turtle, spider, lamp, apple, motorcycle, wolf, squirrel, pear, aquarium_fish, wardrobe, dolphin, shrew, bus, mouse, television, elephant, lawn_mower, sweet_pepper, clock, cloud, baby, orchid, rose, palm_tree, bee, possum, plate, mushroom, pickup_truck, couch, table, dinosaur, streetcar, chair, butterfly, pine_tree, lobster, plain, leopard, sunflower, ray, mountain, bottle, porcupine, tulip, poppy, hamster, can, beetle
