PhilipMay
initial upload
0832ead

mT5-small-sum-de-en-v1


languages:

  • de-DE
  • en-EN

license: CC BY-NC-SA 3.0

tags:

  • MT5
  • summarization

datasets: - cnn_dailymail - xsum - wiki_lingua - mlsum - swiss_text_2019

This is a bilingual summarization model for English and German. It is based on the multilingual T5 model google/mt5-small.

Training

The training was conducted with the following hyperparameters:

  • base model: google/mt5-small
  • source_prefix: "summarize: "
  • batch size: 3
  • max_source_length: 800
  • max_target_length: 96
  • warmup_ratio: 0.3
  • number of train epochs: 10
  • gradient accumulation steps: 2

Datasets and Preprocessing

The datasets were preprocessed as follows:

The summary was tokenized with the google/mt5-small tokenizer. Then only the records with no more than 94 tokens were selected.

The MLSUM dataset has a special characteristic. In the text, the summary is often included completely as one or more sentences. These have been removed from the texts. The reason is that we do not want to train a model that ultimately extracts only sentences as a summary.

This model is based on the following datasets:

Name Language Size License
CNN Daily - Train en 218,223 The license is unclear. The data comes from CNN and Daily Mail. We assume that it may only be used for research purposes and not commercially.
Extreme Summarization (XSum) - Train en 204,005 The license is unclear. The data comes from BBC. We assume that it may only be used for research purposes and not commercially.
wiki_lingua English en 130,331 Creative Commons CC BY-NC-SA 3.0 License
wiki_lingua German de 48,390 Creative Commons CC BY-NC-SA 3.0 License
MLSUM German - Train de 218,043 Usage of dataset is restricted to non-commercial research purposes only. Copyright belongs to the original copyright holders (see here).
SwissText 2019 - Train de 84,564 The license is unclear. The data was published in the German Text Summarization Challenge. We assume that they may be used for research purposes and not commercially.
Language Size
German 350,997
English 552,559
Total 903,556

Evaluation on MLSUM German Test Set

Model Params rouge1 rouge2 rougeL rougeLsum
mT5-small-sum-de-en-01 (this) no beam 21.7336 7.2614 17.1323 19.3977
mT5-small-sum-de-en-01 (this) num_beams: 5 22.6018 7.8047 17.1363 19.719
ml6team/mt5-small-german-finetune-mlsum no beam 18.3607 5.3604 14.5456 16.1946
ml6team/mt5-small-german-finetune-mlsum num_beams: 5 xxx xxx xxx xxx

License

Copyright (c) 2021 Philip May, Deutsche Telekom AG

This work is licensed under the Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0) license.