Model-J: ResNet Model (model_idx_0986)
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 | 5e-05 |
| LR Scheduler | linear |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 986 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.8148 |
| Val Accuracy | 0.7968 |
| Test Accuracy | 0.7802 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
tulip, trout, telephone, poppy, mushroom, fox, motorcycle, sweet_pepper, couch, ray, bottle, baby, keyboard, skunk, table, shark, rose, possum, flatfish, lawn_mower, wardrobe, hamster, lamp, train, apple, forest, otter, snail, squirrel, dinosaur, willow_tree, raccoon, cattle, crab, dolphin, chimpanzee, beaver, beetle, sea, crocodile, maple_tree, leopard, television, wolf, turtle, snake, road, bed, cockroach, castle
