Model-J: ResNet Model (model_idx_0213)
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 | 7e-05 |
| LR Scheduler | linear |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 213 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.7840 |
| Val Accuracy | 0.7608 |
| Test Accuracy | 0.7616 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bus, squirrel, raccoon, bicycle, dinosaur, table, keyboard, rose, dolphin, camel, motorcycle, poppy, streetcar, boy, cockroach, can, pear, sea, mushroom, pickup_truck, road, rabbit, maple_tree, elephant, bridge, hamster, plain, seal, chimpanzee, fox, bowl, cloud, tank, telephone, wolf, chair, orange, clock, shark, pine_tree, worm, couch, whale, mouse, beaver, kangaroo, woman, wardrobe, sweet_pepper, oak_tree
