Model-J ResNet
Collection
1001 items
โข
Updated
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
๐ Project | ๐ Paper | ๐ป GitHub | ๐ค Dataset
| Attribute | Value |
|---|---|
| Subset | ResNet |
| Split | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0005 |
| LR Scheduler | cosine |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 785 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9983 |
| Val Accuracy | 0.8979 |
| Test Accuracy | 0.9014 |
The model was fine-tuned on the following 50 CIFAR100 classes:
rose, beetle, worm, cloud, shark, house, crab, palm_tree, turtle, apple, butterfly, bear, tiger, plate, girl, hamster, willow_tree, poppy, can, dinosaur, lamp, streetcar, sea, motorcycle, couch, elephant, caterpillar, telephone, table, lizard, lawn_mower, otter, seal, crocodile, orange, lion, camel, keyboard, tank, porcupine, train, bicycle, rocket, snake, bottle, baby, skunk, plain, pear, bridge
Base model
microsoft/resnet-101