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 | 0.0001 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 2 |
| Max Train Steps | 666 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 926 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.7577 |
| Val Accuracy | 0.7456 |
| Test Accuracy | 0.7498 |
The model was fine-tuned on the following 50 CIFAR100 classes:
tank, woman, tractor, plate, chimpanzee, crab, cockroach, palm_tree, can, sunflower, keyboard, kangaroo, poppy, whale, pear, raccoon, maple_tree, orange, table, dolphin, spider, seal, turtle, butterfly, bear, rocket, oak_tree, lamp, clock, flatfish, plain, beetle, bridge, bottle, pickup_truck, ray, possum, mouse, couch, worm, fox, shrew, leopard, girl, skyscraper, camel, dinosaur, forest, rabbit, snail
Base model
microsoft/resnet-101