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 | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 355 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8611 |
| Val Accuracy | 0.8301 |
| Test Accuracy | 0.8224 |
The model was fine-tuned on the following 50 CIFAR100 classes:
tiger, plain, dinosaur, fox, rocket, turtle, elephant, snail, pine_tree, bridge, wardrobe, beetle, plate, hamster, trout, man, bicycle, wolf, butterfly, beaver, lawn_mower, table, sweet_pepper, motorcycle, pear, lion, bottle, dolphin, telephone, couch, chair, shrew, crab, house, orange, skunk, raccoon, mouse, television, castle, can, maple_tree, willow_tree, tulip, mushroom, bus, poppy, possum, lamp, flatfish
Base model
microsoft/resnet-101