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_0005)
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 | 0.0003 |
| LR Scheduler | cosine_with_restarts |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 5 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9710 |
| Val Accuracy | 0.9056 |
| Test Accuracy | 0.8964 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
bed, cloud, mountain, streetcar, snail, palm_tree, lawn_mower, whale, shrew, caterpillar, maple_tree, tiger, telephone, butterfly, crab, rabbit, ray, mouse, bowl, leopard, cattle, camel, bridge, skyscraper, bicycle, baby, rocket, worm, house, oak_tree, snake, elephant, chair, skunk, girl, seal, motorcycle, plain, sunflower, train, chimpanzee, apple, sea, cockroach, cup, can, possum, crocodile, wardrobe, kangaroo