variables: 736537

This table contains all the variables of all the datasets we have at Our World In Data. Note that this includes only the information about the variables like name and default display settings, not the data itself.

Data license: CC-BY

This data as json

id name unit description createdAt updatedAt code coverage timespan datasetId sourceId shortUnit display columnOrder originalMetadata grapherConfigAdmin shortName catalogPath dimensions schemaVersion processingLevel processingLog titlePublic titleVariant attributionShort attribution descriptionShort descriptionFromProducer descriptionKey descriptionProcessing licenses license grapherConfigETL type sort dataChecksum metadataChecksum
736537 Top-1 accuracy % The top-1 accuracy measure is used to assess how frequently a model's absolute top prediction matches the correct answer from a given set of options. Here's an example to illustrate what this benchmark tests: Imagine an image classification model that is presented with an image of an animal. The model assigns probabilities to each potential label and generates its highest-confidence prediction. For instance, when analyzing an image, the model might predict "Cat" as the most probable label. To evaluate the model's accuracy using the top-1 measure, researchers compare this prediction with the correct label. If the model's top prediction matches the correct label (e.g., if the actual animal in the image is indeed a cat), then the model's prediction is considered correct according to the top-1 accuracy metric. On the other hand, if the model's top prediction does not match the correct label (e.g., if the image shows a dog, but the model predicts a cat), then the model's prediction is considered incorrect based on the top-1 accuracy measure. To calculate the top-1 accuracy, researchers analyze the model's performance on a large dataset where the correct labels are known. They determine the percentage of examples in the dataset where the model's highest-confidence prediction matches the actual label. This measure provides a focused evaluation of the model's ability to make accurate predictions by considering only its absolute top guess. 2023-07-03 14:54:48 2024-07-08 15:20:32       6102 29574 % 
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    "unit": "%",
    "zeroDay": "2019-01-01",
    "shortUnit": "%",
    "yearIsDay": true,
    "numDecimalPlaces": 0
}
 0     papers_with_code_imagenet_top1 grapher/artificial_intelligence/2023-06-14/papers_with_code_benchmarks/papers_with_code_benchmarks#papers_with_code_imagenet_top1   1                 
[]
         float 
[]
 469596c8ce37b6a7a480eee72e11ffa6 ed95d530167cd069ffe70e1aea3b8639

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