# Image Classification on Food101 5-way 5-shot (test) Source: [Image Classification on Food101 5-way 5-shot (test)]() Collection index: [llms.txt]() Data updated: 2026-02-26T05:33:57.408Z Evaluation of Image Classification performance on the Food101 dataset using a 5-way, 5-shot few-shot learning setup on the test split. 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) | Food101 5-way 5-shot (test) | | Metric | Accuracy (%) | | Unit | PERCENT | | Direction | Higher is better | | Results loaded | 13 of 13 | | 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 (%)](): Higher is better; unit: PERCENT. ## Recorded results | Method | Accuracy (%) | Result date | Report paper | | --- | --- | --- | --- | | RandAugment | 79.59 | Not recorded | 6982d295a8b01e76cc8e9385 | | AutoAugment | 78.25 | Not recorded | 6982d295a8b01e76cc8e9385 | | Learned | 76.49 | Not recorded | 6982d295a8b01e76cc8e9385 | | Naive Baseline | 75.4 | Not recorded | 6982d295a8b01e76cc8e9385 | | Learned | 58.75 | Not recorded | 6982d295a8b01e76cc8e9385 | | AutoAugment | 58.28 | Not recorded | 6982d295a8b01e76cc8e9385 | | Random Tree | 56.88 | Not recorded | 6982d295a8b01e76cc8e9385 | | RandAugment | 56.72 | Not recorded | 6982d295a8b01e76cc8e9385 | | Learned | 54.19 | Not recorded | 6982d295a8b01e76cc8e9385 | | Naive Baseline | 54.09 | Not recorded | 6982d295a8b01e76cc8e9385 | | AutoAugment | 54.05 | Not recorded | 6982d295a8b01e76cc8e9385 | | RandAugment | 52 | Not recorded | 6982d295a8b01e76cc8e9385 | | Naive Baseline | 51.88 | Not recorded | 6982d295a8b01e76cc8e9385 | ### RandAugment Accuracy (%): 79.59. Result ID: 6997533f5698665ec4a51751. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Model":"ViT-Small"}. This record does not assert independent reproduction. ### AutoAugment Accuracy (%): 78.25. Result ID: 6997533f5698665ec4a51752. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"ViT-Small"}. This record does not assert independent reproduction. ### Learned Accuracy (%): 76.49. Result ID: 6997533f5698665ec4a51753. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"ViT-Small"}. This record does not assert independent reproduction. ### Naive Baseline Accuracy (%): 75.4. Result ID: 6997533f5698665ec4a51750. [Reporting paper]() Recorded evaluation configuration: {"Model":"ViT-Small"}. This record does not assert independent reproduction. ### Learned Accuracy (%): 58.75. Result ID: 6997533f5698665ec4a5174b. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"ResNet50"}. This record does not assert independent reproduction. ### AutoAugment Accuracy (%): 58.28. Result ID: 6997533f5698665ec4a5174a. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"ResNet50"}. This record does not assert independent reproduction. ### Random Tree Accuracy (%): 56.88. Result ID: 6997533f5698665ec4a51748. [Reporting paper]() Recorded evaluation configuration: {"Model":"ResNet50"}. This record does not assert independent reproduction. ### RandAugment Accuracy (%): 56.72. Result ID: 6997533f5698665ec4a51749. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Model":"ResNet50"}. This record does not assert independent reproduction. ### Learned Accuracy (%): 54.19. Result ID: 6997533f5698665ec4a5174f. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"MobileNet"}. This record does not assert independent reproduction. ### Naive Baseline Accuracy (%): 54.09. Result ID: 6997533f5698665ec4a51747. [Reporting paper]() Recorded evaluation configuration: {"Model":"ResNet50"}. This record does not assert independent reproduction. ### AutoAugment Accuracy (%): 54.05. Result ID: 6997533f5698665ec4a5174e. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Model":"MobileNet"}. This record does not assert independent reproduction. ### RandAugment Accuracy (%): 52. Result ID: 6997533f5698665ec4a5174d. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Model":"MobileNet"}. This record does not assert independent reproduction. ### Naive Baseline Accuracy (%): 51.88. Result ID: 6997533f5698665ec4a5174c. [Reporting paper]() Recorded evaluation configuration: {"Model":"MobileNet"}. 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