Model-J: ResNet Model (model_idx_0908)
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 | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 908 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9704 |
| Val Accuracy | 0.8688 |
| Test Accuracy | 0.8746 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
butterfly, sweet_pepper, girl, cloud, maple_tree, hamster, otter, elephant, tank, bed, trout, raccoon, skunk, shark, palm_tree, lawn_mower, squirrel, bowl, streetcar, man, cockroach, table, mouse, poppy, plate, bottle, pear, sea, spider, bear, telephone, kangaroo, cup, lizard, house, castle, forest, orchid, pine_tree, porcupine, leopard, snake, rose, train, ray, can, whale, pickup_truck, shrew, tulip
