Papers › Partially Shuffling the Training Data to Improve Language Models

Partially Shuffling the Training Data to Improve Language Models

11 Mar 2019arXiv 2019 3arXiv:1903.04167archive 2025-07-28

Ofir Press

Although SGD requires shuffling the training data between epochs, currently none of the word-level language modeling systems do this. Naively shuffling all sentences in the training data would not permit the model to learn inter-sentence dependencies. Here we present a method that partially shuffles the training data between epochs. This method makes each batch random, while keeping most sentence ordering intact. It achieves new state of the art results on word-level language modeling on both the Penn Treebank and WikiText-2 datasets.

PaperPDFCode

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

Code

ofirpress/PartialShuffle officialmentioned in papermentioned on GitHubpytorch report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

Language ModelingLanguage ModellingSentenceSentence Ordering

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Language Modelling Penn Treebank (Word Level) AWD-LSTM-DOC + Partial Shuffle Params 23M #15 of 43 Archive leaderboard report
Language Modelling Penn Treebank (Word Level) AWD-LSTM-DOC + Partial Shuffle Test perplexity 52.0 #15 of 43 Archive leaderboard report
Language Modelling Penn Treebank (Word Level) AWD-LSTM-DOC + Partial Shuffle Validation perplexity 53.79 #15 of 43 Archive leaderboard report
Language Modelling Penn Treebank (Word Level) AWD-LSTM-MoS + Partial Shuffle Params 22M #18 of 43 Archive leaderboard report
Language Modelling Penn Treebank (Word Level) AWD-LSTM-MoS + Partial Shuffle Test perplexity 53.92 #18 of 43 Archive leaderboard report
Language Modelling Penn Treebank (Word Level) AWD-LSTM-MoS + Partial Shuffle Validation perplexity 55.89 #18 of 43 Archive leaderboard report
Language Modelling WikiText-2 AWD-LSTM-DOC + Partial Shuffle Number of params 37M #23 of 38 Archive leaderboard report
Language Modelling WikiText-2 AWD-LSTM-DOC + Partial Shuffle Test perplexity 57.85 #23 of 38 Archive leaderboard report
Language Modelling WikiText-2 AWD-LSTM-DOC + Partial Shuffle Validation perplexity 60.16 #23 of 38 Archive leaderboard report
Language Modelling WikiText-2 AWD-LSTM-MoS + Partial Shuffle Number of params 35M #25 of 38 Archive leaderboard report
Language Modelling WikiText-2 AWD-LSTM-MoS + Partial Shuffle Test perplexity 59.98 #25 of 38 Archive leaderboard report
Language Modelling WikiText-2 AWD-LSTM-MoS + Partial Shuffle Validation perplexity 62.38 #25 of 38 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

SGD

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections