Model-J: ResNet Model (model_idx_0151)
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 | 3e-05 |
| LR Scheduler | cosine |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 151 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.6588 |
| Val Accuracy | 0.6464 |
| Test Accuracy | 0.6390 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
seal, baby, couch, worm, dolphin, skyscraper, apple, plate, orchid, skunk, beaver, road, lizard, shark, tractor, lion, mouse, spider, castle, kangaroo, bee, possum, mushroom, train, wardrobe, lobster, table, turtle, leopard, squirrel, cockroach, maple_tree, pear, tulip, pickup_truck, caterpillar, forest, camel, bear, poppy, telephone, snake, bed, porcupine, lawn_mower, willow_tree, clock, man, rocket, trout
