Model-J: ResNet Model (model_idx_0995)
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 | cosine |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 995 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8611 |
| Val Accuracy | 0.8256 |
| Test Accuracy | 0.8132 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
rose, poppy, hamster, trout, whale, mushroom, cockroach, beaver, baby, snail, cattle, chair, mouse, chimpanzee, man, streetcar, otter, dolphin, lion, woman, sunflower, crocodile, shrew, kangaroo, seal, train, orchid, lizard, clock, maple_tree, willow_tree, mountain, beetle, girl, palm_tree, bed, skyscraper, caterpillar, porcupine, house, skunk, wolf, keyboard, rocket, bottle, fox, lobster, elephant, bus, spider
