# Classification on Small rice grain disease dataset (val)

Source: [Classification on Small rice grain disease dataset (val)](<https://www.sota2.com/research/sota/classification-on-small-rice-grain-disease-dataset-val>)

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

Data updated: 2026-02-26T06:08:06.978Z

Evaluation of classification performance on the validation split of the Small rice grain disease dataset, reporting metrics such as Validation Loss and 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 | Classification |
| Dataset (including any stated split) | Small rice grain disease dataset (val) |
| Metric | Validation Loss |
| Unit | SCALAR |
| Direction | Lower is better |
| Results loaded | 3 of 3 |
| 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

- [Validation Loss](<https://www.sota2.com/research/sota/classification-on-small-rice-grain-disease-dataset-val.md?metric=Validation%20Loss>): Lower is better; unit: SCALAR.

- [Validation Accuracy](<https://www.sota2.com/research/sota/classification-on-small-rice-grain-disease-dataset-val.md?metric=Validation%20Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Validation Loss | Result date | Report paper |
| --- | --- | --- | --- |
| VGG19 | 0.093 | Not recorded | 68fa69e51e209131cea24aac |
| VGG16 | 0.195 | Not recorded | 68fa69e51e209131cea24aac |
| ResNet50 | 0.281 | Not recorded | 68fa69e51e209131cea24aac |

### VGG19

Validation Loss: 0.093. Result ID: 698defb3ffc3901de099a70a.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69e51e209131cea24aac.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa61d01e209131ce9f62f5.md>)

[Implementation](<http://www.robots.ox.ac.uk/~vgg/research/very_deep/>)

Recorded evaluation configuration: {"CNN Architecture":"VGG19"}. This record does not assert independent reproduction.

### VGG16

Validation Loss: 0.195. Result ID: 698defb3ffc3901de099a709.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69e51e209131cea24aac.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa61d01e209131ce9f62f5.md>)

[Implementation](<http://www.robots.ox.ac.uk/~vgg/research/very_deep/>)

Recorded evaluation configuration: {"CNN Architecture":"VGG16"}. This record does not assert independent reproduction.

### ResNet50

Validation Loss: 0.281. Result ID: 698defb3ffc3901de099a70b.

[Reporting paper](<https://www.sota2.com/research/paper/68fa69e51e209131cea24aac.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa62321e209131ce9f8328.md>)

Recorded evaluation configuration: {"CNN Architecture":"ResNet50"}. This record does not assert independent reproduction.

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