Codesota · Benchmark · amazonHome/Leaderboards/Vision & Documents/Document OCR/amazon
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amazon.

amazon is a state-of-the-art machine learning benchmark indexed on Codesota. This page tracks published model results, top scores per metric, and the SOTA timeline for amazon.

Paper ↗Leaderboard ↓
§ 01 · SOTA history

Year over year.

§ 02 · Leaderboard

Results by metric.

Only 3 models on this benchmark
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Accuracy

Accuracy is the reported evaluation metric for amazon. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.

Higher is better

Trust tiers for Accuracyverifiedpapervendorcommunityunverified
RankModelTrustScoreYearLinksFix
01ApproxRepSet
From paper: Rep the Set: Neural Networks for Learning Set Representations
verified94.312019Paper ↗Code ↗Looks wrong?
02Orthogonalized Soft VSM
From paper: Text classification with word embedding regularization and soft similarity measure
verified93.422020Paper ↗Code ↗Looks wrong?
03REL-RWMD k-NN
From paper: Speeding up Word Mover's Distance and its variants via properties of distances between embeddings
verified93.032019Paper ↗Code ↗Looks wrong?
§ 04 · Submit a result

Add to the leaderboard.

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