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---
language: fr
tags:
- pytorch
- t5
- seq2seq
- summarization
datasets: cnn_dailymail
---
# 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
```python
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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