Model-J: ResNet Model (model_idx_0316)
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 | linear |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 316 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.7280 |
| Val Accuracy | 0.6992 |
| Test Accuracy | 0.6954 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bowl, lobster, beaver, skunk, can, crab, aquarium_fish, shrew, mouse, wardrobe, dinosaur, mushroom, sea, plate, camel, tractor, fox, worm, ray, television, shark, cloud, chair, leopard, poppy, sweet_pepper, beetle, skyscraper, lion, snail, tiger, cattle, turtle, boy, train, tank, trout, rose, dolphin, possum, mountain, pine_tree, tulip, maple_tree, table, elephant, castle, crocodile, orchid, otter
