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 | constant |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 749 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9377 |
| Val Accuracy | 0.8707 |
| Test Accuracy | 0.8768 |
The model was fine-tuned on the following 50 CIFAR100 classes:
shrew, lizard, mountain, sea, woman, tulip, crab, lobster, lamp, porcupine, spider, bear, raccoon, possum, television, orange, lawn_mower, streetcar, sunflower, keyboard, dolphin, mouse, plate, bicycle, rabbit, tractor, castle, cloud, elephant, turtle, cattle, fox, train, house, whale, bed, poppy, skunk, lion, rose, willow_tree, beetle, seal, baby, bridge, pine_tree, bowl, motorcycle, trout, bus
Base model
microsoft/resnet-101