Model-J: ResNet Model (model_idx_0821)
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 | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 821 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9167 |
| Val Accuracy | 0.8587 |
| Test Accuracy | 0.8578 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
plate, woman, tulip, telephone, crocodile, oak_tree, leopard, orchid, lamp, sea, kangaroo, castle, spider, mushroom, caterpillar, raccoon, shark, hamster, porcupine, wardrobe, lawn_mower, cockroach, dolphin, girl, house, elephant, bear, squirrel, crab, palm_tree, tractor, keyboard, plain, pine_tree, mountain, road, chimpanzee, wolf, snail, poppy, train, trout, possum, cup, forest, rabbit, bed, tank, tiger, seal
