Model-J: ResNet Model (model_idx_0391)
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 | constant |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 391 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8934 |
| Val Accuracy | 0.8632 |
| Test Accuracy | 0.8640 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bear, seal, wolf, rose, aquarium_fish, mushroom, telephone, kangaroo, elephant, pickup_truck, otter, cup, bus, rabbit, bowl, girl, bottle, chair, house, maple_tree, mountain, ray, orchid, butterfly, man, apple, trout, hamster, motorcycle, cloud, sweet_pepper, snail, clock, skyscraper, poppy, plain, can, forest, crab, lobster, porcupine, streetcar, lawn_mower, lion, leopard, chimpanzee, beetle, wardrobe, bee, tiger
