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 | 9e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 9 |
| Max Train Steps | 2997 |
| Batch Size | 64 |
| Weight Decay | 0.01 |
| Seed | 445 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9531 |
| Val Accuracy | 0.8627 |
| Test Accuracy | 0.8646 |
The model was fine-tuned on the following 50 CIFAR100 classes:
crab, snake, rabbit, butterfly, forest, palm_tree, otter, television, woman, lobster, shark, lizard, trout, bowl, table, turtle, bus, orange, cattle, wardrobe, caterpillar, couch, porcupine, pickup_truck, telephone, cup, boy, possum, sea, wolf, squirrel, apple, road, can, bed, seal, aquarium_fish, plate, crocodile, baby, girl, train, fox, bee, clock, tiger, elephant, kangaroo, willow_tree, sunflower
Base model
microsoft/resnet-101