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_0711)
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 | 5e-05 |
| LR Scheduler | cosine |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.007 |
| Seed | 711 |
| Random Crop | False |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9187 |
| Val Accuracy | 0.8504 |
| Test Accuracy | 0.8482 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
pear, tractor, cattle, shark, train, maple_tree, orchid, lawn_mower, woman, worm, forest, lizard, streetcar, lamp, pine_tree, butterfly, wardrobe, table, can, otter, sunflower, crab, couch, orange, tulip, skyscraper, bus, telephone, possum, chimpanzee, caterpillar, bowl, tank, cup, keyboard, rabbit, snail, whale, sea, lobster, cockroach, kangaroo, mouse, willow_tree, bed, apple, boy, house, mountain, castle