Who leads the mldoc-zero-shot-english-to-german benchmark?

XLMft UDA currently leads mldoc-zero-shot-english-to-german with a score of 96.95 on Accuracy.

What is the state-of-the-art score on mldoc-zero-shot-english-to-german?

The state-of-the-art result on mldoc-zero-shot-english-to-german is 96.95 (Accuracy), achieved by XLMft UDA as of 2019.

How many models are tracked on mldoc-zero-shot-english-to-german?

Codesota tracks 5 models on mldoc-zero-shot-english-to-german.

When was the mldoc-zero-shot-english-to-german leaderboard last updated?

The mldoc-zero-shot-english-to-german leaderboard on Codesota includes results through 2019, with the earliest tracked result from 2018.

Codesota · Benchmark · mldoc-zero-shot-english-to-germanHome/Leaderboards/Vision & Documents/Document OCR/mldoc-zero-shot-english-to-german

Unknown

mldoc-zero-shot-english-to-german.

Name: mldoc-zero-shot-english-to-german Benchmark Results
Creator: Unknown
Published: 2018-01-01
License: https://creativecommons.org/licenses/by/4.0/

mldoc-zero-shot-english-to-german 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 mldoc-zero-shot-english-to-german.

Paper ↗Leaderboard ↓

§ 01 · SOTA history

Year over year.

§ 02 · Leaderboard

Results by metric.

Found a wrong score or missing run?

Use row edits to send a sourced correction into moderation.

Add / edit result ↗Report issue ↗

Accuracy

Accuracy is the reported evaluation metric for mldoc-zero-shot-english-to-german. 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

Rank	Model	Trust	Score	Year	Links	Fix
01	XLMft UDA From paper: Bridging the domain gap in cross-lingual document classification	verified	96.95	2019	Paper ↗Code ↗	Looks wrong?
02	MultiFiT, pseudo From paper: MultiFiT: Efficient Multi-lingual Language Model Fine-tuning	verified	91.62	2019	Paper ↗Code ↗	Looks wrong?
03	Massively Multilingual Sentence Embeddings From paper: Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond	verified	84.78	2018	Paper ↗Code ↗	Looks wrong?
04	MultiCCA + CNN From paper: A Corpus for Multilingual Document Classification in Eight Languages	verified	81.2	2018	Paper ↗Code ↗	Looks wrong?
05	BiLSTM (Europarl) From paper: A Corpus for Multilingual Document Classification in Eight Languages	verified	71.83	2018	Paper ↗Code ↗	Looks wrong?

§ 04 · Submit a result

Add to the leaderboard.

← Back to Document OCR