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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 0.0001 |
| LR Scheduler | cosine |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 132 |
| Random Crop | False |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9192 |
| Val Accuracy | 0.8691 |
| Test Accuracy | 0.8696 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bicycle, train, rocket, plate, pine_tree, palm_tree, bus, tulip, bottle, poppy, crab, dolphin, bridge, road, skunk, trout, spider, apple, aquarium_fish, orange, otter, snake, cloud, boy, flatfish, fox, forest, can, butterfly, lion, tractor, shrew, chimpanzee, rose, cockroach, bowl, pickup_truck, sea, lizard, cattle, lamp, worm, seal, tiger, rabbit, shark, cup, castle, bed, porcupine
Base model
microsoft/resnet-101