Model-J: ResNet Model (model_idx_0238)
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 | 0.0001 |
| LR Scheduler | linear |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 238 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|
| Train Accuracy | 0.9624 |
| Val Accuracy | 0.8939 |
| Test Accuracy | 0.8840 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bed, porcupine, clock, possum, poppy, maple_tree, wolf, cockroach, willow_tree, mountain, can, snake, road, skunk, dinosaur, train, fox, skyscraper, table, crab, flatfish, keyboard, tank, snail, television, raccoon, squirrel, camel, dolphin, lizard, caterpillar, sunflower, bowl, woman, shark, orange, baby, plate, bee, hamster, sea, butterfly, leopard, couch, mouse, bear, cup, house, cloud, seal
