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 | 5e-05 |
| LR Scheduler | linear |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 143 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9058 |
| Val Accuracy | 0.8523 |
| Test Accuracy | 0.8554 |
The model was fine-tuned on the following 50 CIFAR100 classes:
baby, butterfly, sea, plain, oak_tree, train, chair, tank, skyscraper, streetcar, wardrobe, willow_tree, telephone, whale, bicycle, cattle, tiger, castle, sunflower, shrew, forest, chimpanzee, seal, trout, road, orange, porcupine, snail, crab, woman, table, can, tractor, pickup_truck, worm, mountain, lawn_mower, man, girl, beetle, aquarium_fish, raccoon, boy, dolphin, cloud, camel, beaver, pine_tree, skunk, hamster
Base model
microsoft/resnet-101