Model-J: ResNet Model (model_idx_0866)
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 | constant |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 866 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8675 |
| Val Accuracy | 0.8419 |
| Test Accuracy | 0.8278 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
wardrobe, streetcar, squirrel, tank, woman, bottle, camel, cockroach, keyboard, poppy, boy, lizard, orange, baby, tulip, lion, bicycle, oak_tree, rabbit, man, plate, castle, television, dolphin, spider, kangaroo, crocodile, maple_tree, palm_tree, chair, snail, tiger, possum, snake, pickup_truck, flatfish, worm, mouse, cattle, mushroom, aquarium_fish, house, leopard, willow_tree, bridge, bowl, clock, table, rose, motorcycle
