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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0003 |
| LR Scheduler | constant |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 56 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9901 |
| Val Accuracy | 0.8608 |
| Test Accuracy | 0.8488 |
The model was fine-tuned on the following 50 CIFAR100 classes:
elephant, pickup_truck, mouse, table, lion, snail, fox, oak_tree, tulip, palm_tree, porcupine, girl, bicycle, shrew, baby, shark, cockroach, crab, whale, couch, ray, clock, keyboard, maple_tree, willow_tree, cup, apple, boy, house, man, telephone, wolf, seal, woman, mountain, castle, worm, sea, forest, possum, beaver, lobster, mushroom, rabbit, skyscraper, camel, wardrobe, leopard, tank, crocodile
Base model
microsoft/resnet-101