metadata
base_model: microsoft/resnet-101
library_name: transformers
pipeline_tag: image-classification
tags:
- probex
- model-j
- weight-space-learning
Model-J: ResNet Model (model_idx_0388)
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
🌐 Project | 📃 Paper | 💻 GitHub | 🤗 Dataset
Model Details
| Attribute | Value |
|---|---|
| Subset | ResNet |
| Split | train |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 5e-05 |
| LR Scheduler | constant_with_warmup |
| Epochs | 3 |
| Max Train Steps | 999 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 388 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8327 |
| Val Accuracy | 0.8128 |
| Test Accuracy | 0.8150 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
cup, man, tiger, woman, aquarium_fish, otter, television, bear, wolf, lawn_mower, squirrel, bottle, flatfish, keyboard, leopard, sea, shark, lion, rose, camel, trout, pear, willow_tree, motorcycle, sweet_pepper, house, pine_tree, chimpanzee, table, bee, crocodile, kangaroo, streetcar, fox, tractor, tulip, bicycle, spider, mouse, dolphin, turtle, couch, skunk, apple, mountain, beetle, skyscraper, lamp, crab, oak_tree