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_0390)
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 | 0.0003 |
| LR Scheduler | constant_with_warmup |
| Epochs | 7 |
| Max Train Steps | 2331 |
| Batch Size | 64 |
| Weight Decay | 0.05 |
| Seed | 390 |
| Random Crop | False |
| Random Flip | True |
Performance
| Metric | Value |
|---|---|
| Train Accuracy | 0.9872 |
| Val Accuracy | 0.8757 |
| Test Accuracy | 0.8724 |
Training Categories
The model was fine-tuned on the following 50 CIFAR100 classes:
lion, kangaroo, plate, tulip, fox, dolphin, clock, pear, shrew, cattle, bus, man, baby, skunk, road, willow_tree, plain, train, telephone, cockroach, boy, trout, snail, wolf, skyscraper, butterfly, lamp, rabbit, streetcar, oak_tree, dinosaur, bee, mushroom, palm_tree, whale, keyboard, pine_tree, sweet_pepper, crab, turtle, shark, bed, worm, rocket, bowl, bridge, mountain, maple_tree, apple, seal