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 | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 631 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9126 |
| Val Accuracy | 0.8704 |
| Test Accuracy | 0.8600 |
The model was fine-tuned on the following 50 CIFAR100 classes:
leopard, orange, willow_tree, bus, turtle, cockroach, caterpillar, seal, oak_tree, bicycle, mountain, train, clock, pine_tree, elephant, camel, bowl, wolf, sea, bed, skyscraper, palm_tree, pear, wardrobe, chimpanzee, chair, shrew, crab, skunk, bear, maple_tree, otter, telephone, cloud, kangaroo, sweet_pepper, dinosaur, dolphin, tank, sunflower, television, lizard, plain, snake, bee, fox, cup, castle, butterfly, rose
Base model
microsoft/resnet-101