# Image Classification on Tiny ImageNet (Acc@1, Acc@5, CV)

Source: [Image Classification on Tiny ImageNet (Acc@1, Acc@5, CV)](<https://www.sota2.com/research/sota/image-classification-on-tiny-imagenet-acc-at-1-acc-at-5-cv>)

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

Data updated: 2026-05-12T07:50:24.565Z

Evaluation of Image Classification performance on the Tiny ImageNet dataset, reporting Top-1 Accuracy, Top-5 Accuracy, and CV 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) | Tiny ImageNet |
| Metric | Top-1 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

- [Top-1 Accuracy](<https://www.sota2.com/research/sota/image-classification-on-tiny-imagenet-acc-at-1-acc-at-5-cv.md?metric=Top-1%20Accuracy>): Higher is better; unit: PERCENT.

- [Top-5 Accuracy](<https://www.sota2.com/research/sota/image-classification-on-tiny-imagenet-acc-at-1-acc-at-5-cv.md?metric=Top-5%20Accuracy>): Higher is better; unit: PERCENT.

- [CV](<https://www.sota2.com/research/sota/image-classification-on-tiny-imagenet-acc-at-1-acc-at-5-cv.md?metric=CV>): Lower is better; unit: SCALAR.

## Recorded results

| Method | Top-1 Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| Hi-MoE | 59.13 | Not recorded | 6a02b3f5dbc836b87d82457a |
| Loss-free balancing | 58.87 | Not recorded | 6a02b3f5dbc836b87d82457a |
| Vanilla GShard-style | 58.61 | Not recorded | 6a02b3f5dbc836b87d82457a |
| MoGE | 58.61 | Not recorded | 6a02b3f5dbc836b87d82457a |

### Hi-MoE

Top-1 Accuracy: 59.13. Result ID: 6a02da8547f34ce924e55e18.

[Reporting paper](<https://www.sota2.com/research/paper/6a02b3f5dbc836b87d82457a.md>)

[Method origin paper](<https://www.sota2.com/research/paper/6a02b3f5dbc836b87d82457a.md>)

Recorded evaluation configuration: {"Backbone":"Swin Transformer","Total Parameters":"1B","Active Parameters":"83M","Epochs":"200"}. This record does not assert independent reproduction.

### Loss-free balancing

Top-1 Accuracy: 58.87. Result ID: 6a02da8547f34ce924e55e16.

[Reporting paper](<https://www.sota2.com/research/paper/6a02b3f5dbc836b87d82457a.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa749e1e209131cea62a01.md>)

Recorded evaluation configuration: {"Backbone":"Swin Transformer","Total Parameters":"1B","Active Parameters":"83M","Epochs":"200"}. This record does not assert independent reproduction.

### Vanilla GShard-style

Top-1 Accuracy: 58.61. Result ID: 6a02da8547f34ce924e55e15.

[Reporting paper](<https://www.sota2.com/research/paper/6a02b3f5dbc836b87d82457a.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa67d61e209131cea18d67.md>)

Recorded evaluation configuration: {"Backbone":"Swin Transformer","Total Parameters":"1B","Active Parameters":"83M","Epochs":"200"}. This record does not assert independent reproduction.

### MoGE

Top-1 Accuracy: 58.61. Result ID: 6a02da8547f34ce924e55e17.

[Reporting paper](<https://www.sota2.com/research/paper/6a02b3f5dbc836b87d82457a.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa78d51e209131cea7aaa8.md>)

Recorded evaluation configuration: {"Backbone":"Swin Transformer","Total Parameters":"1B","Active Parameters":"83M","Epochs":"200"}. This record does not assert independent reproduction.

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