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_0831)
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 | 9e-05 |
| LR Scheduler | cosine |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 831 |
| Random Crop | True |
| Random Flip | False |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.8973 |
| Val Accuracy | 0.8493 |
| Test Accuracy | 0.8404 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
chair, telephone, shrew, train, wardrobe, aquarium_fish, porcupine, forest, cockroach, bridge, bus, clock, beaver, snake, camel, worm, trout, ray, willow_tree, apple, raccoon, fox, crocodile, girl, kangaroo, possum, lizard, bed, plain, chimpanzee, poppy, dolphin, pine_tree, otter, lawn_mower, spider, couch, skunk, boy, can, butterfly, woman, squirrel, pear, keyboard, man, flatfish, motorcycle, mountain, orange