# Image Classification on ImageNet 500 Epochs (val)

Source: [Image Classification on ImageNet 500 Epochs (val)](<https://www.sota2.com/research/sota/image-classification-on-imagenet-500-epochs-val>)

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

Data updated: 2026-02-26T06:07:01.909Z

Evaluation of Image Classification performance on the validation split of the ImageNet 500-class subset, typically measured by Top-1 and Top-5 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 500 Epochs (val) |
| 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-imagenet-500-epochs-val.md?metric=Top-1%20Accuracy>): Higher is better; unit: PERCENT.

- [Top-5 Accuracy](<https://www.sota2.com/research/sota/image-classification-on-imagenet-500-epochs-val.md?metric=Top-5%20Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Top-1 Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| Umbral | 74.46 | Not recorded | 68fa71551e209131cea50940 |
| Penumbral | 74.34 | Not recorded | 68fa71551e209131cea50940 |
| Model Default | 73.65 | Not recorded | 68fa71551e209131cea50940 |
| Dot Product | 73.65 | Not recorded | 68fa71551e209131cea50940 |

### Umbral

Top-1 Accuracy: 74.46. Result ID: 6991a86e3a6c31484909b560.

[Reporting paper](<https://www.sota2.com/research/paper/68fa71551e209131cea50940.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa71551e209131cea50940.md>)

[Implementation](<https://github.com/tsengalb99/coneheads>)

Recorded evaluation configuration: {"Backbone":"DeiT-Ti","Training Epochs":500}. This record does not assert independent reproduction.

### Penumbral

Top-1 Accuracy: 74.34. Result ID: 6991a86e3a6c31484909b55f.

[Reporting paper](<https://www.sota2.com/research/paper/68fa71551e209131cea50940.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa71551e209131cea50940.md>)

[Implementation](<https://github.com/tsengalb99/coneheads>)

Recorded evaluation configuration: {"Backbone":"DeiT-Ti","Training Epochs":500}. This record does not assert independent reproduction.

### Model Default

Top-1 Accuracy: 73.65. Result ID: 6991a86e3a6c31484909b55d.

[Reporting paper](<https://www.sota2.com/research/paper/68fa71551e209131cea50940.md>)

Recorded evaluation configuration: {"Backbone":"DeiT-Ti","Training Epochs":500}. This record does not assert independent reproduction.

### Dot Product

Top-1 Accuracy: 73.65. Result ID: 6991a86e3a6c31484909b55e.

[Reporting paper](<https://www.sota2.com/research/paper/68fa71551e209131cea50940.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa703d1e209131cea49db1.md>)

[Implementation](<https://github.com/tensorflow/tensor2tensor>)

Recorded evaluation configuration: {"Backbone":"DeiT-Ti","Training Epochs":500}. This record does not assert independent reproduction.

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