Model-J: ResNet Model (model_idx_0307)
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 | 7e-05 |
| LR Scheduler | constant |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 307 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9935 |
| Val Accuracy | 0.8899 |
| Test Accuracy | 0.8846 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lobster, wolf, table, dolphin, squirrel, clock, porcupine, tiger, worm, raccoon, bowl, bicycle, bottle, streetcar, man, orchid, plate, possum, aquarium_fish, trout, shark, chair, crab, lamp, rocket, pear, pine_tree, house, bridge, baby, hamster, bus, snail, girl, bed, seal, palm_tree, motorcycle, can, bee, rose, maple_tree, dinosaur, television, elephant, wardrobe, train, willow_tree, crocodile, couch
