Model-J: ResNet Model (model_idx_0576)
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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 0.0003 |
| LR Scheduler | cosine |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 576 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9486 |
| Val Accuracy | 0.8912 |
| Test Accuracy | 0.8926 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
tulip, whale, lobster, house, aquarium_fish, beetle, couch, cockroach, butterfly, raccoon, pear, bottle, lion, elephant, lamp, plain, turtle, skunk, skyscraper, pine_tree, streetcar, shrew, tractor, man, fox, tank, bear, poppy, maple_tree, sea, chair, orange, clock, can, possum, lawn_mower, crab, seal, snail, crocodile, palm_tree, television, woman, spider, sunflower, cloud, rocket, mountain, castle, leopard
