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 | train |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0003 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 870 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9728 |
| Val Accuracy | 0.8955 |
| Test Accuracy | 0.8966 |
The model was fine-tuned on the following 50 CIFAR100 classes:
girl, crocodile, bowl, house, lizard, beetle, shrew, plain, streetcar, table, bed, pine_tree, motorcycle, road, caterpillar, lamp, keyboard, shark, camel, kangaroo, poppy, bottle, boy, turtle, trout, orchid, raccoon, mountain, beaver, tank, cloud, plate, can, television, lawn_mower, palm_tree, whale, wolf, woman, sunflower, clock, pear, castle, chair, skyscraper, lobster, flatfish, crab, bear, tiger
Base model
microsoft/resnet-101