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 | 3e-05 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 608 |
| Random Crop | True |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.7593 |
| Val Accuracy | 0.7445 |
| Test Accuracy | 0.7332 |
The model was fine-tuned on the following 50 CIFAR100 classes:
road, apple, bicycle, house, bottle, otter, man, cockroach, rose, mountain, wolf, crab, skunk, bowl, pickup_truck, chair, bus, rabbit, clock, couch, bear, leopard, fox, shark, sweet_pepper, tulip, beetle, wardrobe, trout, flatfish, aquarium_fish, poppy, whale, keyboard, snail, forest, caterpillar, mushroom, kangaroo, worm, ray, table, porcupine, tractor, butterfly, dolphin, dinosaur, snake, maple_tree, raccoon
Base model
microsoft/resnet-101