OpenNMT

An open source neural machine translation system.

OpenNMT-py models

This page lists pretrained models for OpenNMT-py.

翻译

  English-German - Transformer (download)
Configuration Base Transformer configuration with standard training options
Data WMT with shared SentencePiece model
BLEU newstest2014 = 26.89
newstest2017 = 28.09
  German-English - 2-layer BiLSTM (download)
Configuration 2-layer BiLSTM with hidden size 500 trained for 20 epochs
Data IWSLT ‘14 DE-EN
BLEU 30.33

Summarization

English

  2-layer LSTM (download)
Configuration 2-layer LSTM with hidden size 500 trained for 20 epochs
Data Gigaword standard
Gigaword F-Score R1 = 33.60
R2 = 16.29
RL = 31.45
  2-layer LSTM with copy attention (download)
Configuration 2-layer LSTM with hidden size 500 and copy attention trained for 20 epochs
Data Gigaword standard
Gigaword F-Score R1 = 35.51
R2 = 17.35
RL = 33.17
  Transformer (download)
Configuration See OpenNMT-py summarization example
Data CNN/Daily Mail
  1-layer BiLSTM (download)
Configuration See OpenNMT-py summarization example
Data CNN/Daily Mail
Gigaword F-Score R1 = 39.12
R2 = 17.35
RL = 36.12

Chinese

  1-layer BiLSTM (download)
Author playma
Configuration Preprocessing options: src_vocab_size 8000, tgt_vocab_size 8000, src_seq_length 400, tgt_seq_length 30, src_seq_length_trunc 400, tgt_seq_length_trunc 100.
Training options: 1 layer, LSTM 300, WE 500, encoder_type brnn, input feed, AdaGrad, adagrad_accumulator_init 0.1, learning_rate 0.15, 30 epochs
Data LCSTS
Gigaword F-Score R1 = 35.67
R2 = 23.06
RL = 33.14

Dialog

  2-layer LSTM (download)
Configuration 2 layers, LSTM 500, WE 500, input feed, dropout 0.2, global_attention mlp, start_decay_at 7, 13 epochs
Data OpenSubtitles