# Image Classification on ImageNet In-distribution 1k

Source: [Image Classification on ImageNet In-distribution 1k](<https://www.sota2.com/research/sota/image-classification-on-imagenet-in-distribution-1k>)

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

Data updated: 2026-02-26T05:32:04.995Z

Evaluation of Image Classification performance on the ImageNet In-distribution 1k dataset, reporting standard accuracy metrics.

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 In-distribution 1k |
| Metric | Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 4 of 4 |
| 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-in-distribution-1k.md?metric=Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| MonoSoup (variance) | 85.57 | Not recorded | 698c0d5ac97a0b3e3b5e13c7 |
| MonoSoup (freevariance) | 85.19 | Not recorded | 698c0d5ac97a0b3e3b5e13c7 |
| Fine-tuned (IN1k) | 85.17 | Not recorded | 698c0d5ac97a0b3e3b5e13c7 |
| Pretrained (IN12k) | 82.17 | Not recorded | 698c0d5ac97a0b3e3b5e13c7 |

### MonoSoup (variance)

Accuracy: 85.57. Result ID: 6998cc345698665ec42fb96d.

[Reporting paper](<https://www.sota2.com/research/paper/698c0d5ac97a0b3e3b5e13c7.md>)

[Method origin paper](<https://www.sota2.com/research/paper/698c0d5ac97a0b3e3b5e13c7.md>)

Recorded evaluation configuration: {"Architecture":"ConvNeXt","MonoSoup Variant":"variance","Hyperparameter R":"0.8"}. This record does not assert independent reproduction.

### MonoSoup (freevariance)

Accuracy: 85.19. Result ID: 6998cc345698665ec42fb96c.

[Reporting paper](<https://www.sota2.com/research/paper/698c0d5ac97a0b3e3b5e13c7.md>)

[Method origin paper](<https://www.sota2.com/research/paper/698c0d5ac97a0b3e3b5e13c7.md>)

Recorded evaluation configuration: {"Architecture":"ConvNeXt","MonoSoup Variant":"freevariance"}. This record does not assert independent reproduction.

### Fine-tuned (IN1k)

Accuracy: 85.17. Result ID: 6998cc345698665ec42fb96b.

[Reporting paper](<https://www.sota2.com/research/paper/698c0d5ac97a0b3e3b5e13c7.md>)

Recorded evaluation configuration: {"Architecture":"ConvNeXt","Training Setting":"Fine-tuned (IN1k)"}. This record does not assert independent reproduction.

### Pretrained (IN12k)

Accuracy: 82.17. Result ID: 6998cc345698665ec42fb96a.

[Reporting paper](<https://www.sota2.com/research/paper/698c0d5ac97a0b3e3b5e13c7.md>)

Recorded evaluation configuration: {"Architecture":"ConvNeXt","Training Setting":"Pretrained (IN12k)"}. This record does not assert independent reproduction.

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