Model-J: ResNet Model (model_idx_0246)
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 | 0.0001 |
| LR Scheduler | constant |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 246 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9041 |
| Val Accuracy | 0.8581 |
| Test Accuracy | 0.8598 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
table, television, shark, rose, wardrobe, road, camel, sea, sweet_pepper, bear, worm, leopard, man, dinosaur, skyscraper, tiger, lizard, apple, chair, flatfish, clock, castle, couch, woman, dolphin, bus, poppy, wolf, pickup_truck, porcupine, snail, bed, plain, tractor, cattle, mountain, beetle, rocket, cloud, fox, otter, aquarium_fish, boy, cockroach, possum, lawn_mower, willow_tree, mouse, whale, train
