Model-J: ResNet Model (model_idx_0614)
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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|
| Learning Rate | 0.0003 |
| LR Scheduler | cosine |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 614 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9968 |
| Val Accuracy | 0.9120 |
| Test Accuracy | 0.9016 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
road, fox, butterfly, beaver, elephant, plate, lawn_mower, squirrel, bottle, possum, snail, baby, man, kangaroo, table, woman, tiger, palm_tree, telephone, sunflower, oak_tree, hamster, mouse, leopard, lobster, lion, chimpanzee, cup, house, can, willow_tree, bed, keyboard, skyscraper, sea, whale, turtle, shrew, maple_tree, crab, poppy, castle, pear, porcupine, beetle, wolf, cattle, rose, bicycle, bear
