# Image Classification on ImageNet 1K (val) (Accuracy per Class Count) Source: [Image Classification on ImageNet 1K (val) (Accuracy per Class Count)]() Collection index: [llms.txt]() Data updated: 2026-02-26T05:33:59.188Z Evaluation of Image Classification performance on the validation split of ImageNet 1K, reporting accuracy based on having 1, 2, 5, or 10 images available per class. 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 1K (val) | | Metric | Accuracy (1 image/class) | | Unit | PERCENT | | Direction | Higher is better | | Results loaded | 0 of 0 | | 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 (1 image/class)](): Higher is better; unit: PERCENT. - [Accuracy (2 images/class)](): Higher is better; unit: PERCENT. - [Accuracy (5 images/class)](): Higher is better; unit: PERCENT. - [Accuracy (10 images/class)](): Higher is better; unit: PERCENT. ## Recorded results | Method | Accuracy (1 image/class) | Result date | Report paper | | --- | --- | --- | --- | Page 1 of 1. This is an index page, not the full collection.