Model-J: ResNet Model (model_idx_0889)
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 | linear |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 889 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.4213 |
| Val Accuracy | 0.4072 |
| Test Accuracy | 0.4128 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
wolf, mushroom, porcupine, girl, raccoon, possum, bowl, sea, flatfish, aquarium_fish, tractor, beaver, train, tulip, woman, cup, spider, lion, palm_tree, butterfly, worm, whale, road, shark, cockroach, bear, otter, sunflower, tiger, forest, baby, bed, pear, can, pickup_truck, plate, orange, chimpanzee, bottle, skunk, television, plain, castle, pine_tree, lobster, bicycle, poppy, house, table, squirrel
