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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0003 |
| LR Scheduler | cosine |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 130 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9588 |
| Val Accuracy | 0.8837 |
| Test Accuracy | 0.8934 |
The model was fine-tuned on the following 50 CIFAR100 classes:
willow_tree, orange, oak_tree, fox, bridge, palm_tree, orchid, woman, pine_tree, rocket, clock, bear, snake, man, keyboard, television, girl, baby, chair, turtle, crab, seal, camel, bus, crocodile, plain, lawn_mower, skyscraper, leopard, cloud, elephant, poppy, dolphin, pickup_truck, train, wolf, couch, snail, tractor, cockroach, streetcar, telephone, lamp, mountain, porcupine, mouse, lobster, sea, motorcycle, tiger
Base model
microsoft/resnet-101