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 | 0.0005 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 250 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9991 |
| Val Accuracy | 0.9104 |
| Test Accuracy | 0.9100 |
The model was fine-tuned on the following 50 CIFAR100 classes:
fox, road, butterfly, wardrobe, tiger, crocodile, orange, television, whale, camel, boy, mushroom, leopard, shrew, beaver, bridge, spider, aquarium_fish, house, otter, pine_tree, tractor, bus, sea, rabbit, train, rocket, telephone, woman, dolphin, cloud, lobster, hamster, chair, chimpanzee, rose, skunk, elephant, palm_tree, plain, lawn_mower, pear, cup, trout, bowl, tank, porcupine, wolf, girl, tulip
Base model
microsoft/resnet-101