Model-J: ResNet Model (model_idx_0658)
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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 0.0003 |
| LR Scheduler | constant |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 658 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9567 |
| Val Accuracy | 0.8621 |
| Test Accuracy | 0.8644 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
can, beaver, camel, rose, otter, mouse, chimpanzee, sunflower, lizard, train, cockroach, poppy, mountain, squirrel, forest, snake, kangaroo, couch, road, bee, bridge, bear, boy, spider, sweet_pepper, woman, crocodile, bowl, wardrobe, shark, motorcycle, castle, girl, orange, butterfly, mushroom, pine_tree, hamster, lobster, clock, shrew, porcupine, apple, maple_tree, house, beetle, baby, crab, turtle, tulip
