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 |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 839 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8965 |
| Val Accuracy | 0.8355 |
| Test Accuracy | 0.8452 |
The model was fine-tuned on the following 50 CIFAR100 classes:
streetcar, spider, bottle, wardrobe, willow_tree, oak_tree, bowl, tulip, otter, pickup_truck, seal, worm, caterpillar, beetle, lobster, table, road, rabbit, girl, man, snake, can, hamster, bridge, plain, bee, rocket, sweet_pepper, woman, keyboard, cloud, dinosaur, camel, tank, fox, wolf, orange, lawn_mower, sunflower, squirrel, bus, train, lion, crab, bicycle, chair, whale, trout, cockroach, maple_tree
Base model
microsoft/resnet-101