Model-J: ResNet Model (model_idx_0093)
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_with_warmup |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 93 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8652 |
| Val Accuracy | 0.8365 |
| Test Accuracy | 0.8282 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
willow_tree, bee, skyscraper, mushroom, train, lion, aquarium_fish, plain, caterpillar, road, boy, table, apple, girl, beetle, shark, pickup_truck, forest, bed, mouse, snail, beaver, streetcar, cloud, camel, bowl, palm_tree, man, chair, elephant, can, skunk, trout, woman, tractor, oak_tree, possum, lobster, house, leopard, telephone, crab, baby, bus, squirrel, motorcycle, bridge, clock, sunflower, cup
