Model-J: ResNet Model (model_idx_0098)
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 | 0.0005 |
| LR Scheduler | linear |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 98 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9982 |
| Val Accuracy | 0.9213 |
| Test Accuracy | 0.9248 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
tank, clock, mushroom, bottle, aquarium_fish, motorcycle, plain, fox, forest, tiger, castle, beaver, sweet_pepper, couch, crab, ray, bicycle, road, wardrobe, caterpillar, chair, crocodile, wolf, sea, hamster, lamp, bus, can, house, pine_tree, girl, lawn_mower, table, leopard, turtle, dolphin, kangaroo, bridge, orange, tulip, shark, apple, snail, camel, bear, rabbit, bee, pickup_truck, butterfly, television
