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 | 0.0003 |
| LR Scheduler | cosine |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 39 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9958 |
| Val Accuracy | 0.9221 |
| Test Accuracy | 0.9212 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lamp, elephant, trout, beaver, mouse, bed, pear, cup, tank, woman, plate, snail, otter, bus, lizard, turtle, porcupine, mountain, camel, crocodile, raccoon, hamster, orange, chair, telephone, sunflower, whale, poppy, beetle, rabbit, motorcycle, worm, dinosaur, crab, bridge, fox, flatfish, castle, possum, kangaroo, bottle, caterpillar, train, pickup_truck, aquarium_fish, butterfly, sweet_pepper, cockroach, rocket, lawn_mower
Base model
microsoft/resnet-101