Papers › The Evolved Transformer

The Evolved Transformer

30 Jan 2019arXiv:1901.11117archive 2025-07-28

David R. So, Chen Liang, Quoc V. Le

Recent works have highlighted the strength of the Transformer architecture on sequence tasks while, at the same time, neural architecture search (NAS) has begun to outperform human-designed models. Our goal is to apply NAS to search for a better alternative to the Transformer. We first construct a large search space inspired by the recent advances in feed-forward sequence models and then run evolutionary architecture search with warm starting by seeding our initial population with the Transformer. To directly search on the computationally expensive WMT 2014 English-German translation task, we develop the Progressive Dynamic Hurdles method, which allows us to dynamically allocate more resources to more promising candidate models. The architecture found in our experiments -- the Evolved Transformer -- demonstrates consistent improvement over the Transformer on four well-established language tasks: WMT 2014 English-German, WMT 2014 English-French, WMT 2014 English-Czech and LM1B. At a big model size, the Evolved Transformer establishes a new state-of-the-art BLEU score of 29.8 on WMT'14 English-German; at smaller sizes, it achieves the same quality as the original "big" Transformer with 37.6% less parameters and outperforms the Transformer by 0.7 BLEU at a mobile-friendly model size of 7M parameters.

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Code

tensorflow/tensor2tensor officialmentioned in papermentioned on GitHubtf report
moon23k/Transformer_Archs mentioned on GitHubpytorch report
nazarov-yuriy/zh-ru-shared-task mentioned on GitHubtf report

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Tasks

Machine TranslationNeural Architecture Search

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Language Modelling One Billion Word Evolved Transformer Big PPL 28.6 #17 of 27 Archive leaderboard report
Machine Translation WMT2014 English-Czech Evolved Transformer Big BLEU score 28.2 #1 of 2 Archive leaderboard report
Machine Translation WMT2014 English-Czech Evolved Transformer Base BLEU score 27.6 #2 of 2 Archive leaderboard report
Machine Translation WMT2014 English-French Evolved Transformer Big BLEU score 41.3 #26 of 57 Archive leaderboard report
Machine Translation WMT2014 English-French Evolved Transformer Base BLEU score 40.6 #29 of 57 Archive leaderboard report
Machine Translation WMT2014 English-German Evolved Transformer Big BLEU score 29.8 #16 of 91 Archive leaderboard report
Machine Translation WMT2014 English-German Evolved Transformer Big Number of Params 218M #16 of 91 Archive leaderboard report
Machine Translation WMT2014 English-German Evolved Transformer Big SacreBLEU 29.2 #16 of 91 Archive leaderboard report
Machine Translation WMT2014 English-German Evolved Transformer Base BLEU score 28.4 #46 of 91 Archive leaderboard report
Machine Translation WMT2014 English-German Evolved Transformer Base Hardware Burden 2488G #46 of 91 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

Absolute Position EncodingsAdamAttentionBPEDense ConnectionsDropoutLSTMLabel SmoothingLayer NormalizationLinear LayerMulti-Head AttentionPosition-Wise Feed-Forward LayerReLUResidual ConnectionSigmoid ActivationSoftmaxTanh ActivationTransformer

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