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 | constant_with_warmup |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.03 |
| Seed | 845 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9639 |
| Val Accuracy | 0.8875 |
| Test Accuracy | 0.8834 |
The model was fine-tuned on the following 50 CIFAR100 classes:
spider, orange, rabbit, mushroom, pear, caterpillar, otter, kangaroo, seal, bottle, cattle, motorcycle, trout, apple, dolphin, sea, keyboard, pine_tree, whale, possum, shark, chimpanzee, tiger, can, cup, leopard, worm, skunk, rose, man, girl, sunflower, wolf, flatfish, raccoon, maple_tree, squirrel, dinosaur, butterfly, tulip, lamp, turtle, elephant, bus, bear, train, chair, rocket, table, crab
Base model
microsoft/resnet-101