# Image Classification on ImageNet partial

Source: [Image Classification on ImageNet partial](<https://www.sota2.com/research/sota/image-classification-on-imagenet-partial>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-02-26T05:28:16.828Z

Evaluation of Image Classification performance on a partial subset of the ImageNet dataset, typically measured by accuracy.

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

| Scope | Recorded value |
| --- | --- |
| Task | Image Classification |
| Dataset (including any stated split) | ImageNet partial |
| Metric | Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 2 of 2 |
| Coverage | All results currently returned for this benchmark |

Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol.

## Metrics

- [Accuracy](<https://www.sota2.com/research/sota/image-classification-on-imagenet-partial.md?metric=Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| Distill on real images | 79.1 | Not recorded | 68fa6c601e209131cea33a9d |
| Distill on real images | 72.2 | Not recorded | 68fa6c601e209131cea33a9d |

### Distill on real images

Accuracy: 79.1. Result ID: 698f0d9b3a6c314849f5477d.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c601e209131cea33a9d.md>)

Recorded evaluation configuration: {"Teacher Network":"ResNet-101","Teacher Accuracy":"77.37%","Student Network":"DeiT-S","Dataset Partition":"partial ImageNet"}. This record does not assert independent reproduction.

### Distill on real images

Accuracy: 72.2. Result ID: 698f0d9b3a6c314849f5477c.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c601e209131cea33a9d.md>)

Recorded evaluation configuration: {"Teacher Network":"ResNet-101","Teacher Accuracy":"77.37%","Student Network":"DeiT-Ti","Dataset Partition":"partial ImageNet"}. This record does not assert independent reproduction.

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