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 | 3e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 540 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.5636 |
| Val Accuracy | 0.5496 |
| Test Accuracy | 0.5502 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bridge, bicycle, otter, lobster, baby, wardrobe, man, raccoon, couch, leopard, wolf, boy, dolphin, sunflower, poppy, tiger, dinosaur, mushroom, pine_tree, shrew, plain, television, spider, bee, possum, train, pear, rocket, can, snake, keyboard, sweet_pepper, seal, snail, streetcar, ray, cloud, bowl, girl, cup, table, rabbit, chimpanzee, fox, mouse, worm, telephone, tank, camel, porcupine
Base model
microsoft/resnet-101