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 | cosine |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 216 |
| Random Crop | False |
| Random Flip | False |
| Metric | Value |
|---|---|
| Train Accuracy | 0.9776 |
| Val Accuracy | 0.8813 |
| Test Accuracy | 0.8742 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bridge, trout, snail, oak_tree, rose, worm, beetle, shrew, elephant, orchid, fox, sea, forest, otter, rocket, cockroach, television, leopard, bee, possum, chimpanzee, shark, ray, train, baby, skunk, snake, whale, skyscraper, camel, lobster, lion, couch, beaver, mushroom, plate, tulip, girl, seal, orange, poppy, wardrobe, sunflower, turtle, mountain, keyboard, plain, palm_tree, clock, dolphin
Base model
microsoft/resnet-101