Model-J: ResNet Model (model_idx_0647)
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 | 9e-05 |
| LR Scheduler | cosine |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 647 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8094 |
| Val Accuracy | 0.7856 |
| Test Accuracy | 0.7766 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
snail, maple_tree, girl, otter, cloud, train, beetle, mushroom, telephone, bottle, bridge, lawn_mower, clock, sweet_pepper, worm, lizard, pine_tree, cattle, crocodile, rabbit, pickup_truck, bed, hamster, flatfish, ray, wardrobe, sea, tulip, porcupine, skunk, kangaroo, beaver, dinosaur, tank, bus, woman, elephant, motorcycle, fox, bear, skyscraper, aquarium_fish, house, plate, chair, rocket, caterpillar, couch, lobster, oak_tree
