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 | 9e-05 |
| LR Scheduler | linear |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 965 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.7269 |
| Val Accuracy | 0.7067 |
| Test Accuracy | 0.7064 |
The model was fine-tuned on the following 50 CIFAR100 classes:
plate, possum, rocket, castle, palm_tree, bear, shrew, beaver, girl, telephone, beetle, fox, leopard, tiger, lamp, man, trout, bridge, chair, train, can, porcupine, tractor, oak_tree, bottle, tank, hamster, mushroom, poppy, skunk, lobster, chimpanzee, cattle, motorcycle, otter, turtle, skyscraper, bee, lawn_mower, shark, sweet_pepper, snake, woman, dinosaur, couch, sea, rabbit, bowl, pine_tree, worm
Base model
microsoft/resnet-101