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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0005 |
| LR Scheduler | constant |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 927 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9545 |
| Val Accuracy | 0.8608 |
| Test Accuracy | 0.8592 |
The model was fine-tuned on the following 50 CIFAR100 classes:
motorcycle, willow_tree, television, bottle, streetcar, rose, road, cloud, shrew, bear, plate, possum, boy, maple_tree, sea, palm_tree, skunk, bowl, raccoon, snake, fox, sweet_pepper, orange, beaver, can, rocket, butterfly, oak_tree, camel, hamster, orchid, train, keyboard, otter, bee, forest, man, shark, tiger, tulip, turtle, bed, skyscraper, dinosaur, bridge, lobster, table, tank, apple, woman
Base model
microsoft/resnet-101