# Image Classification on ImageNet 1% imgs (train val)

Source: [Image Classification on ImageNet 1% imgs (train val)](<https://www.sota2.com/research/sota/image-classification-on-imagenet-1-percent-imgs-train-val>)

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

Data updated: 2026-02-26T06:07:03.974Z

Evaluation of Image Classification performance on the combined training and validation split of the 1% subset of ImageNet, measured by Top-1 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 1% imgs (train val) |
| Metric | Top-1 Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 8 of 8 |
| 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

- [Top-1 Accuracy](<https://www.sota2.com/research/sota/image-classification-on-imagenet-1-percent-imgs-train-val.md?metric=Top-1%20Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Top-1 Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| iBOT-vMF | 72.3 | Not recorded | 68fa733f1e209131cea5b3cc |
| DINO-vMF | 70.4 | Not recorded | 68fa733f1e209131cea5b3cc |
| iBOT | 69.9 | Not recorded | 68fa733f1e209131cea5b3cc |
| MSN | 69.1 | Not recorded | 68fa733f1e209131cea5b3cc |
| DINO | 67.2 | Not recorded | 68fa733f1e209131cea5b3cc |
| MSN | 67.2 | Not recorded | 68fa733f1e209131cea5b3cc |
| DINO-vMF | 65 | Not recorded | 68fa733f1e209131cea5b3cc |
| DINO | 64.5 | Not recorded | 68fa733f1e209131cea5b3cc |

### iBOT-vMF

Top-1 Accuracy: 72.3. Result ID: 6992b18e3a6c31484910c7b6.

[Reporting paper](<https://www.sota2.com/research/paper/68fa733f1e209131cea5b3cc.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa733f1e209131cea5b3cc.md>)

[Implementation](<https://github.com/facebookresearch/dino>)

Recorded evaluation configuration: {"Architecture":"ViT-Base/16","Evaluation Protocol":"Linear Classification"}. This record does not assert independent reproduction.

### DINO-vMF

Top-1 Accuracy: 70.4. Result ID: 6992b18e3a6c31484910c7b4.

[Reporting paper](<https://www.sota2.com/research/paper/68fa733f1e209131cea5b3cc.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa733f1e209131cea5b3cc.md>)

[Implementation](<https://github.com/facebookresearch/dino>)

Recorded evaluation configuration: {"Architecture":"ViT-Base/16","Evaluation Protocol":"Linear Classification"}. This record does not assert independent reproduction.

### iBOT

Top-1 Accuracy: 69.9. Result ID: 6992b18e3a6c31484910c7b5.

[Reporting paper](<https://www.sota2.com/research/paper/68fa733f1e209131cea5b3cc.md>)

Recorded evaluation configuration: {"Architecture":"ViT-Base/16","Evaluation Protocol":"Linear Classification"}. This record does not assert independent reproduction.

### MSN

Top-1 Accuracy: 69.1. Result ID: 6992b18e3a6c31484910c7b3.

[Reporting paper](<https://www.sota2.com/research/paper/68fa733f1e209131cea5b3cc.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6c591e209131cea33793.md>)

[Implementation](<https://github.com/facebookresearch/msn>)

Recorded evaluation configuration: {"Architecture":"ViT-Base/16","Evaluation Protocol":"Linear Classification"}. This record does not assert independent reproduction.

### DINO

Top-1 Accuracy: 67.2. Result ID: 6992b18e3a6c31484910c7b2.

[Reporting paper](<https://www.sota2.com/research/paper/68fa733f1e209131cea5b3cc.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6a071e209131cea2594c.md>)

[Implementation](<https://github.com/facebookresearch/dino>)

Recorded evaluation configuration: {"Architecture":"ViT-Base/16","Evaluation Protocol":"Linear Classification"}. This record does not assert independent reproduction.

### MSN

Top-1 Accuracy: 67.2. Result ID: 6992b18e3a6c31484910c7b8.

[Reporting paper](<https://www.sota2.com/research/paper/68fa733f1e209131cea5b3cc.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6c591e209131cea33793.md>)

[Implementation](<https://github.com/facebookresearch/msn>)

Recorded evaluation configuration: {"Architecture":"ViT-Small/16","Evaluation Protocol":"Linear Classification"}. This record does not assert independent reproduction.

### DINO-vMF

Top-1 Accuracy: 65. Result ID: 6992b18e3a6c31484910c7b9.

[Reporting paper](<https://www.sota2.com/research/paper/68fa733f1e209131cea5b3cc.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa733f1e209131cea5b3cc.md>)

[Implementation](<https://github.com/facebookresearch/dino>)

Recorded evaluation configuration: {"Architecture":"ViT-Small/16","Evaluation Protocol":"Linear Classification"}. This record does not assert independent reproduction.

### DINO

Top-1 Accuracy: 64.5. Result ID: 6992b18e3a6c31484910c7b7.

[Reporting paper](<https://www.sota2.com/research/paper/68fa733f1e209131cea5b3cc.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6a071e209131cea2594c.md>)

[Implementation](<https://github.com/facebookresearch/dino>)

Recorded evaluation configuration: {"Architecture":"ViT-Small/16","Evaluation Protocol":"Linear Classification"}. This record does not assert independent reproduction.

Page 1 of 1. This is an index page, not the full collection.