Model-J: ResNet Model (model_idx_0295)
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 | 0.0001 |
| LR Scheduler | constant |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 295 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9689 |
| Val Accuracy | 0.8824 |
| Test Accuracy | 0.8858 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
television, snake, pear, hamster, table, skyscraper, seal, pickup_truck, plain, orchid, caterpillar, baby, ray, camel, fox, road, sunflower, rabbit, flatfish, cup, train, beetle, wolf, leopard, raccoon, mouse, pine_tree, orange, shrew, bowl, girl, turtle, tiger, bee, couch, lamp, tractor, beaver, spider, sweet_pepper, crab, snail, forest, woman, whale, bear, man, lawn_mower, rocket, trout
