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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0005 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 371 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9923 |
| Val Accuracy | 0.8901 |
| Test Accuracy | 0.8956 |
The model was fine-tuned on the following 50 CIFAR100 classes:
shrew, baby, maple_tree, boy, couch, fox, sunflower, otter, rose, rocket, bowl, flatfish, mountain, trout, pine_tree, orange, ray, orchid, cattle, rabbit, chair, bridge, woman, bee, kangaroo, lizard, porcupine, willow_tree, train, dinosaur, lamp, cup, poppy, raccoon, television, squirrel, bicycle, sea, plain, possum, skunk, tractor, worm, elephant, chimpanzee, forest, motorcycle, clock, wolf, skyscraper
Base model
microsoft/resnet-101