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_0406)
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 | 9e-05 |
| LR Scheduler | constant |
| Epochs | 8 |
| Max Train Steps | 2664 |
| Batch Size | 64 |
| Weight Decay | 0.009 |
| Seed | 406 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9909 |
| Val Accuracy | 0.9008 |
| Test Accuracy | 0.9002 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
cloud, cockroach, caterpillar, rocket, forest, spider, beetle, woman, dinosaur, wardrobe, elephant, turtle, kangaroo, snail, girl, butterfly, tank, shark, possum, tiger, skyscraper, house, fox, camel, tulip, rabbit, bear, dolphin, cup, sunflower, lamp, mountain, crocodile, hamster, apple, bowl, telephone, trout, porcupine, orchid, plate, keyboard, aquarium_fish, leopard, oak_tree, mushroom, bee, tractor, boy, pear