Model-J: ResNet Model (model_idx_0733)
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 | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 733 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8869 |
| Val Accuracy | 0.8616 |
| Test Accuracy | 0.8362 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
turtle, palm_tree, couch, television, bridge, streetcar, trout, bus, dolphin, possum, spider, ray, maple_tree, shrew, sunflower, porcupine, pickup_truck, train, wardrobe, plate, mushroom, crocodile, bee, poppy, fox, shark, cattle, skunk, leopard, castle, seal, tractor, lizard, pine_tree, tulip, man, mountain, cup, cloud, bed, bicycle, lobster, chimpanzee, baby, road, girl, butterfly, lion, squirrel, lamp
