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_0771)
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 | cosine |
| Epochs | 4 |
| Max Train Steps | 1332 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 771 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9120 |
| Val Accuracy | 0.8715 |
| Test Accuracy | 0.8652 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
tractor, fox, lion, pickup_truck, girl, boy, otter, television, chair, bee, sweet_pepper, man, dolphin, sea, snake, plain, orchid, bowl, butterfly, spider, lawn_mower, snail, flatfish, wardrobe, cockroach, lamp, kangaroo, possum, squirrel, woman, tank, raccoon, couch, rocket, aquarium_fish, caterpillar, apple, can, camel, porcupine, streetcar, sunflower, motorcycle, mountain, rabbit, train, table, oak_tree, cloud, skyscraper