# Image Classification on ImageNet Base classes (val)

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

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

Data updated: 2026-02-26T05:29:03.166Z

Evaluation of standard Image Classification performance on the validation split of the ImageNet Base classes subset, typically measured by 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 Base classes (val) |
| 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-base-classes-val.md?metric=Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| CoOp | 82.66 | Not recorded | 68fa70571e209131cea4a691 |
| ProDA | 81.56 | Not recorded | 68fa70571e209131cea4a691 |
| CoCoOp | 80.47 | Not recorded | 68fa70571e209131cea4a691 |
| Bayesian Prompt Learning | 80.1 | Not recorded | 68fa70571e209131cea4a691 |

### CoOp

Accuracy: 82.66. Result ID: 699114e73a6c314849058989.

[Reporting paper](<https://www.sota2.com/research/paper/68fa70571e209131cea4a691.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6d8b1e209131cea3a814.md>)

[Implementation](<https://github.com/KaiyangZhou/CoOp>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### ProDA

Accuracy: 81.56. Result ID: 699114e73a6c31484905898b.

[Reporting paper](<https://www.sota2.com/research/paper/68fa70571e209131cea4a691.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6c771e209131cea34184.md>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### CoCoOp

Accuracy: 80.47. Result ID: 699114e73a6c31484905898a.

[Reporting paper](<https://www.sota2.com/research/paper/68fa70571e209131cea4a691.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6d8c1e209131cea3a831.md>)

[Implementation](<https://github.com/KaiyangZhou/CoOp>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### Bayesian Prompt Learning

Accuracy: 80.1. Result ID: 699114e73a6c31484905898c.

[Reporting paper](<https://www.sota2.com/research/paper/68fa70571e209131cea4a691.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa70571e209131cea4a691.md>)

[Implementation](<https://github.com/saic-fi/Bayesian-Prompt-Learning>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

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