Model-J: ResNet Model (model_idx_0906)
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_with_warmup |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 906 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9771 |
| Val Accuracy | 0.8760 |
| Test Accuracy | 0.8712 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
maple_tree, flatfish, poppy, mouse, shark, bottle, kangaroo, spider, seal, camel, lion, fox, sweet_pepper, chair, tiger, beaver, forest, orange, lamp, rocket, table, bus, tulip, baby, pine_tree, possum, dinosaur, apple, cup, bowl, woman, boy, bed, pear, bee, willow_tree, sunflower, orchid, rose, skunk, dolphin, aquarium_fish, road, cattle, skyscraper, squirrel, crocodile, rabbit, tank, bicycle
