Model-J: ResNet Model (model_idx_0155)
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 | 7e-05 |
| LR Scheduler | cosine |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 155 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9317 |
| Val Accuracy | 0.8664 |
| Test Accuracy | 0.8692 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
butterfly, possum, forest, sea, otter, couch, house, rose, bee, turtle, dinosaur, tractor, clock, skunk, baby, ray, apple, bicycle, kangaroo, fox, keyboard, rocket, squirrel, spider, man, poppy, whale, mountain, dolphin, plate, aquarium_fish, sweet_pepper, oak_tree, caterpillar, lawn_mower, pear, leopard, cup, snail, wardrobe, porcupine, plain, streetcar, raccoon, boy, elephant, hamster, tulip, lobster, mushroom
