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 | 0.0001 |
| LR Scheduler | constant |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 985 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9936 |
| Val Accuracy | 0.9139 |
| Test Accuracy | 0.9126 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bowl, bicycle, boy, lobster, flatfish, mouse, couch, dolphin, elephant, butterfly, house, caterpillar, rabbit, lion, cockroach, maple_tree, motorcycle, shark, fox, rocket, telephone, cattle, clock, bus, can, dinosaur, turtle, otter, mountain, ray, road, camel, lawn_mower, bottle, leopard, baby, snake, rose, chimpanzee, aquarium_fish, tank, poppy, trout, orange, bee, chair, squirrel, keyboard, whale, wolf
Base model
microsoft/resnet-101