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 | 9e-05 |
| LR Scheduler | linear |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 698 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9142 |
| Val Accuracy | 0.8715 |
| Test Accuracy | 0.8762 |
The model was fine-tuned on the following 50 CIFAR100 classes:
elephant, kangaroo, telephone, spider, rabbit, beaver, lawn_mower, clock, porcupine, tank, plain, bridge, tractor, boy, wardrobe, sweet_pepper, tiger, butterfly, bus, wolf, cockroach, orchid, table, raccoon, oak_tree, flatfish, worm, chair, otter, motorcycle, beetle, cup, palm_tree, cattle, mountain, train, sunflower, forest, chimpanzee, woman, bowl, bear, crab, rocket, bottle, sea, castle, can, camel, bed
Base model
microsoft/resnet-101