Model-J: ResNet Model (model_idx_0806)
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_with_restarts |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 806 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.7335 |
| Val Accuracy | 0.7088 |
| Test Accuracy | 0.7090 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
baby, streetcar, beaver, girl, pear, camel, road, possum, lawn_mower, skyscraper, flatfish, boy, crocodile, oak_tree, mountain, apple, crab, spider, bus, train, hamster, turtle, tractor, porcupine, kangaroo, lion, cattle, lobster, bee, telephone, leopard, trout, rocket, bowl, television, maple_tree, lamp, clock, squirrel, otter, mouse, raccoon, wardrobe, tiger, skunk, wolf, dolphin, house, rabbit, lizard
