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_0185)
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 | val |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
Training Hyperparameters
| Parameter | Value |
|---|---|
| Learning Rate | 0.0005 |
| LR Scheduler | constant |
| Epochs | 5 |
| Max Train Steps | 1665 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 185 |
| Random Crop | True |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9613 |
| Val Accuracy | 0.8539 |
| Test Accuracy | 0.8630 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
camel, aquarium_fish, spider, crab, castle, table, baby, caterpillar, bottle, otter, rose, skyscraper, shark, cattle, oak_tree, bee, lion, tank, couch, willow_tree, mouse, bowl, sea, lobster, beetle, raccoon, man, palm_tree, maple_tree, trout, possum, boy, butterfly, sunflower, streetcar, skunk, sweet_pepper, plain, mountain, squirrel, telephone, cockroach, pear, chimpanzee, cloud, girl, clock, motorcycle, hamster, elephant