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 | 3e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 99 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8547 |
| Val Accuracy | 0.8115 |
| Test Accuracy | 0.8114 |
The model was fine-tuned on the following 50 CIFAR100 classes:
tulip, lion, flatfish, whale, sunflower, cloud, wolf, crocodile, tank, plain, seal, sweet_pepper, mountain, motorcycle, mouse, bowl, mushroom, boy, tiger, raccoon, snake, turtle, bottle, streetcar, worm, elephant, bee, otter, possum, cattle, keyboard, apple, lamp, dolphin, rose, pine_tree, baby, tractor, dinosaur, orchid, snail, camel, orange, bridge, caterpillar, couch, fox, willow_tree, kangaroo, clock
Base model
microsoft/resnet-101