Model-J: ResNet Model (model_idx_0797)
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 | 0.0003 |
| LR Scheduler | constant |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 797 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9514 |
| Val Accuracy | 0.8635 |
| Test Accuracy | 0.8598 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
tiger, table, worm, mushroom, lamp, tractor, squirrel, hamster, willow_tree, pine_tree, kangaroo, dolphin, chair, mouse, bus, beaver, whale, orange, bowl, rabbit, caterpillar, shrew, shark, baby, apple, skyscraper, road, fox, wardrobe, cup, man, dinosaur, tank, pickup_truck, raccoon, forest, streetcar, house, bee, possum, castle, lizard, television, sweet_pepper, bridge, beetle, poppy, crocodile, elephant, otter
