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ProbeX/Model-J__ResNet__model_idx_0690
Model-J__ResNet__model_idx_0690 is a image classification model from ProbeX. Use it when you need a label for an image. It is set up for transformers.
This model is part of the Model-J dataset, introduced in:
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From the Hugging Face model README
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
<p align="center"> ๐ <a href="https://horwitz.ai/probex" target="_blank">Project</a> | ๐ <a href="https://arxiv.org/abs/2410.13569" target="_blank">Paper</a> | ๐ป <a href="https://github.com/eliahuhorwitz/ProbeX" target="_blank">GitHub</a> | ๐ค <a href="https://huggingface.co/ProbeX" target="_blank">Dataset</a> </p>
| Attribute | Value |
|---|---|
| Subset | ResNet |
| Split | train |
| Base Model | microsoft/resnet-101 |
| Dataset | CIFAR100 (50 classes) |
| Parameter | Value |
|---|---|
| Learning Rate | 3e-05 |
| LR Scheduler | cosine |
| Epochs | 6 |
| Max Train Steps | 1998 |
| Batch Size | 64 |
| Weight Decay | 0.005 |
| Seed | 690 |
| Random Crop | True |
| Random Flip | True |
| Metric | Value |
|---|---|
| Train Accuracy | 0.7054 |
| Val Accuracy | 0.6920 |
| Test Accuracy | 0.6808 |
The model was fine-tuned on the following 50 CIFAR100 classes:
bus, rose, orange, bottle, baby, pear, bridge, shrew, pickup_truck, road, whale, wardrobe, bowl, lawn_mower, rocket, willow_tree, caterpillar, squirrel, forest, porcupine, castle, seal, mushroom, mountain, bee, hamster, tulip, maple_tree, aquarium_fish, kangaroo, snail, sea, orchid, keyboard, lion, otter, oak_tree, beetle, cockroach, train, house, lobster, tank, crocodile, snake, mouse, bear, tiger, girl, table