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French T5 Abstractive Text Summarization

Version 1.0 (I will keep improving the model's performances.)

Version 2.0 is here! (with improved performances of course)

I trained the model on 13x more data than v1.

ROUGE-1: 44.5252

ROUGE-2: 22.652

ROUGE-L: 29.8866

Model description

This model is a T5 Transformers model (JDBN/t5-base-fr-qg-fquad) that was fine-tuned in french for abstractive text summarization.

How to use

from transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained("plguillou/t5-base-fr-sum-cnndm")
model = T5ForConditionalGeneration.from_pretrained("plguillou/t5-base-fr-sum-cnndm")

To summarize an ARTICLE, just modify the string like this : "summarize: ARTICLE".

Training data

The base model I used is JDBN/t5-base-fr-qg-fquad (it can perform question generation, question answering and answer extraction).

I used the "t5-base" model from the transformers library to translate in french the CNN / Daily Mail summarization dataset.

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This model can be loaded on the Inference API on-demand.

Dataset used to train plguillou/t5-base-fr-sum-cnndm

Space using plguillou/t5-base-fr-sum-cnndm 1