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 | 5e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 664 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.8814 |
| Val Accuracy | 0.8515 |
| Test Accuracy | 0.8388 |
The model was fine-tuned on the following 50 CIFAR100 classes:
cup, snail, bee, rose, spider, bus, trout, beetle, lobster, possum, willow_tree, shark, plain, lawn_mower, skunk, camel, snake, clock, rabbit, boy, dinosaur, apple, bicycle, kangaroo, sunflower, turtle, otter, butterfly, chair, can, mouse, bridge, bottle, pear, orchid, pine_tree, cockroach, woman, mushroom, leopard, train, shrew, oak_tree, sweet_pepper, crocodile, pickup_truck, beaver, squirrel, bed, man
Base model
microsoft/resnet-101