Model-J: ResNet Model (model_idx_0276)
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 | 0.0003 |
| LR Scheduler | constant |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 276 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9831 |
| Val Accuracy | 0.8904 |
| Test Accuracy | 0.8854 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
poppy, squirrel, oak_tree, whale, bee, fox, apple, sunflower, possum, sweet_pepper, skyscraper, tulip, boy, cup, wardrobe, caterpillar, lamp, girl, dinosaur, snail, seal, couch, tiger, cloud, orchid, road, telephone, rose, streetcar, turtle, mushroom, pear, clock, forest, sea, shrew, television, woman, spider, mountain, crab, dolphin, wolf, ray, aquarium_fish, raccoon, snake, chair, motorcycle, leopard
