Model-J: ResNet Model (model_idx_0268)
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 | 5e-05 |
| LR Scheduler | linear |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 268 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9104 |
| Val Accuracy | 0.8520 |
| Test Accuracy | 0.8576 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
crab, mouse, pickup_truck, telephone, can, porcupine, pear, beetle, apple, motorcycle, couch, rocket, hamster, cattle, tiger, plain, clock, fox, palm_tree, rose, dinosaur, snake, worm, camel, bed, bee, road, bridge, beaver, boy, bowl, television, raccoon, wolf, girl, oak_tree, bus, train, tank, tulip, tractor, shark, turtle, willow_tree, bottle, baby, spider, sea, orchid, sunflower
