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 | 9e-05 |
| LR Scheduler | cosine |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 249 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8431 |
| Val Accuracy | 0.8144 |
| Test Accuracy | 0.8018 |
The model was fine-tuned on the following 50 CIFAR100 classes:
pine_tree, woman, forest, snake, kangaroo, man, possum, sea, flatfish, otter, skunk, dinosaur, willow_tree, house, trout, bicycle, cloud, bottle, caterpillar, mouse, lobster, lion, sunflower, television, whale, boy, baby, cattle, poppy, camel, bear, lawn_mower, lamp, skyscraper, crocodile, mushroom, seal, shark, keyboard, road, maple_tree, orchid, plain, orange, chair, porcupine, telephone, bus, bed, couch
Base model
microsoft/resnet-101