Model-J: ResNet Model (model_idx_0791)
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 | 9e-05 |
| LR Scheduler | linear |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 791 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8458 |
| Val Accuracy | 0.8179 |
| Test Accuracy | 0.8070 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
maple_tree, plate, cloud, skunk, forest, hamster, bed, wardrobe, mouse, wolf, camel, pear, cattle, television, bee, aquarium_fish, shrew, possum, tiger, caterpillar, chair, train, table, apple, lion, orange, crocodile, lamp, road, raccoon, bear, butterfly, leopard, squirrel, mushroom, dinosaur, turtle, woman, house, bicycle, bridge, sweet_pepper, spider, cockroach, dolphin, tank, flatfish, sea, willow_tree, sunflower
