PyTorch Models

Pretrained

Available models trained using OpenNMT.

Benchmarks

This page benchmarks training results of open-source NMT systems with generated models of OpenNMT and other systems.

German->English

Who/When Corpus Prep Training Tool Training Parameters Server Details Training Time/Memory Translation Parameters Scores Model
2018/02/11
Baseline
IWSLT ‘14 DE-EN OpenNMT d4ab35a 2 layers, RNN 500, WE 500, input feed
20 epochs
Trained on 1 GPU TITAN X     BLEU Score: 30.33 203MB here

English Summarization

Who/When Corpus Prep Training Tool Training Parameters Server Details Training Time/Memory Translation Parameters Scores Model
2018/02/11
Baseline
Gigaword Standard OpenNMT d4ab35a 2 layers, RNN 500, WE 500, input feed
20 epochs
Trained on 1 GPU TITAN X     Gigaword F-Score R1: 33.60 R2: 16.29 RL: 31.45 331MB here
2018/02/22
Baseline
Gigaword Standard OpenNMT 338b3b1 2 layers, RNN 500, WE 500, input feed, copy_attn, reuse_copy_attn
20 epochs
Trained on 1 GPU TITAN X   replace_unk Gigaword F-Score R1: 35.51 R2: 17.35 RL: 33.17 331MB here

Dialog System

Who/When Corpus Prep Training Tool Training Parameters Server Details Training Time/Memory Translation Parameters Scores Model
2018/02/22
Baseline
Opensubtitles OpenNMT 338b3b1 2 layers, RNN 500, WE 500, input feed, dropout 0.2, global_attention mlp, start_decay_at 7
13 epochs
Trained on 1 GPU TITAN X     TBD 355MB here