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 | 7e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 49 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.7032 |
| Val Accuracy | 0.6805 |
| Test Accuracy | 0.6738 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lizard, willow_tree, worm, chair, tank, tulip, road, train, elephant, streetcar, bridge, shark, table, rocket, skyscraper, aquarium_fish, forest, bicycle, mouse, camel, hamster, skunk, cattle, cockroach, otter, bus, shrew, man, pine_tree, rabbit, baby, lion, snake, turtle, tractor, plain, butterfly, orange, girl, dolphin, seal, poppy, beetle, crocodile, television, sweet_pepper, snail, raccoon, motorcycle, keyboard
Base model
microsoft/resnet-101