Model-J: ResNet Model (model_idx_0373)
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 | 5e-05 |
| LR Scheduler | linear |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 373 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9524 |
| Val Accuracy | 0.8747 |
| Test Accuracy | 0.8652 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
oak_tree, tractor, bear, rabbit, seal, crocodile, apple, palm_tree, wolf, hamster, kangaroo, table, bed, bowl, caterpillar, snail, mushroom, lamp, castle, cup, ray, snake, chimpanzee, maple_tree, baby, tiger, dolphin, rocket, telephone, forest, clock, pine_tree, man, orchid, mountain, rose, plain, motorcycle, train, cattle, tulip, bee, shrew, tank, whale, skunk, girl, lion, wardrobe, skyscraper
