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 | 0.005 |
| Seed | 201 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.7821 |
| Val Accuracy | 0.7443 |
| Test Accuracy | 0.7560 |
The model was fine-tuned on the following 50 CIFAR100 classes:
lizard, girl, kangaroo, seal, apple, spider, snail, turtle, ray, mountain, hamster, trout, television, lobster, bottle, keyboard, plain, raccoon, dinosaur, shark, man, bicycle, whale, porcupine, skunk, dolphin, mouse, sunflower, lamp, flatfish, cattle, bus, otter, worm, cloud, tulip, palm_tree, castle, rose, crab, orange, bear, streetcar, butterfly, squirrel, pickup_truck, poppy, sweet_pepper, couch, cup
Base model
microsoft/resnet-101