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_0207)
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 | test |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0005 |
| LR Scheduler | constant_with_warmup |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 207 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9825 |
| Val Accuracy | 0.8704 |
| Test Accuracy | 0.8810 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
mouse, wardrobe, snake, snail, cloud, girl, telephone, poppy, beaver, streetcar, woman, crocodile, castle, elephant, man, road, fox, lizard, table, shrew, sea, trout, skyscraper, aquarium_fish, rose, tank, chimpanzee, lobster, orchid, palm_tree, sweet_pepper, bridge, worm, lamp, spider, bus, flatfish, raccoon, butterfly, leopard, sunflower, house, cockroach, ray, can, willow_tree, bowl, pine_tree, possum, caterpillar