Model-J: ResNet Model (model_idx_0470)
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 | 0.0005 |
| LR Scheduler | cosine |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 470 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9831 |
| Val Accuracy | 0.8981 |
| Test Accuracy | 0.8922 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
mountain, trout, skunk, rabbit, cockroach, wolf, sweet_pepper, dinosaur, otter, pine_tree, mouse, bridge, possum, kangaroo, lion, telephone, camel, snake, lamp, bed, caterpillar, shark, streetcar, girl, crocodile, oak_tree, house, poppy, worm, shrew, can, bear, whale, plain, castle, bowl, bus, lizard, tractor, tank, pickup_truck, television, willow_tree, orchid, ray, table, hamster, orange, squirrel, aquarium_fish
