Model-J: ResNet Model (model_idx_0163)
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 | 7e-05 |
| LR Scheduler | cosine |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 163 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8777 |
| Val Accuracy | 0.8317 |
| Test Accuracy | 0.8268 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
beaver, camel, plain, sunflower, porcupine, mushroom, skunk, whale, can, rose, oak_tree, bus, lobster, rocket, snail, ray, cockroach, streetcar, seal, butterfly, shrew, poppy, woman, chair, otter, orchid, aquarium_fish, boy, cattle, girl, kangaroo, man, palm_tree, table, pickup_truck, willow_tree, shark, spider, tractor, fox, rabbit, bottle, bicycle, road, train, baby, forest, bowl, beetle, television
