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 | constant |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 28 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9176 |
| Val Accuracy | 0.8736 |
| Test Accuracy | 0.8804 |
The model was fine-tuned on the following 50 CIFAR100 classes:
ray, table, lizard, couch, crab, flatfish, snail, mushroom, wolf, lamp, motorcycle, bottle, train, wardrobe, caterpillar, bicycle, woman, trout, apple, rocket, clock, pear, raccoon, orange, cattle, chair, road, spider, crocodile, shark, shrew, mouse, man, keyboard, fox, seal, lawn_mower, skunk, whale, camel, lion, can, worm, telephone, streetcar, elephant, oak_tree, bus, snake, cloud
Base model
microsoft/resnet-101