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 | 3e-05 |
| LR Scheduler | cosine |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 685 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.7775 |
| Val Accuracy | 0.7680 |
| Test Accuracy | 0.7564 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lawn_mower, train, couch, lion, road, seal, rose, table, poppy, bed, beaver, orchid, worm, maple_tree, whale, fox, tiger, aquarium_fish, leopard, lamp, pear, television, tractor, oak_tree, camel, snake, ray, girl, bowl, bee, plate, pine_tree, otter, sunflower, chair, streetcar, beetle, raccoon, turtle, rocket, butterfly, caterpillar, palm_tree, cockroach, keyboard, bicycle, pickup_truck, mouse, sweet_pepper, forest
Base model
microsoft/resnet-101