
# camembert-base-squadFR-fquad-piaf

## Description

Question-answering French model, using base [CamemBERT](https://camembert-model.fr/) fine-tuned on a combo of three French Q&A datasets:

1. [PIAFv1.1](https://www.data.gouv.fr/en/datasets/piaf-le-dataset-francophone-de-questions-reponses/)
2. [FQuADv1.0](https://fquad.illuin.tech/)
3. [SQuAD-FR (SQuAD automatically translated to French)](https://github.com/Alikabbadj/French-SQuAD)

## Training hyperparameters

```shell
python run_squad.py \
--model_type camembert \
--model_name_or_path camembert-base \
--do_train --do_eval \
--train_file data/SQuAD+fquad+piaf.json \
--predict_file data/fquad_valid.json \
--per_gpu_train_batch_size 12 \ 
--learning_rate 3e-5 \ 
--num_train_epochs 4 \  
--max_seq_length 384 \ 
--doc_stride 128 \
--save_steps 10000 
``` 

## Evaluation results
### FQuAD v1.0 Evaluation
```shell
{"f1": 79.81, "exact_match": 55.14}
```
### SQuAD-FR Evaluation
```shell
{"f1": 80.61, "exact_match": 59.54}
```

## Usage

```python
from transformers import pipeline

nlp = pipeline('question-answering', model='etalab-ia/camembert-base-squadFR-fquad-piaf', tokenizer='etalab-ia/camembert-base-squadFR-fquad-piaf')

nlp({
    'question': "Qui est Claude Monet?",
    'context': "Claude Monet, né le 14 novembre 1840 à Paris et mort le 5 décembre 1926 à Giverny, est un peintre français et l’un des fondateurs de l'impressionnisme."
})
```
## Acknowledgments

This work was performed using HPC resources from GENCI–IDRIS (Grant 2020-AD011011224). 

## Citations

### PIAF
```
@inproceedings{KeraronLBAMSSS20,
  author    = {Rachel Keraron and
               Guillaume Lancrenon and
               Mathilde Bras and
               Fr{\'{e}}d{\'{e}}ric Allary and
               Gilles Moyse and
               Thomas Scialom and
               Edmundo{-}Pavel Soriano{-}Morales and
               Jacopo Staiano},
  title     = {Project {PIAF:} Building a Native French Question-Answering Dataset},
  booktitle = {{LREC}},
  pages     = {5481--5490},
  publisher = {European Language Resources Association},
  year      = {2020}
}

```

### FQuAD
```
@article{dHoffschmidt2020FQuADFQ,
  title={FQuAD: French Question Answering Dataset},
  author={Martin d'Hoffschmidt and Maxime Vidal and Wacim Belblidia and Tom Brendl'e and Quentin Heinrich},
  journal={ArXiv},
  year={2020},
  volume={abs/2002.06071}
}
```

### SQuAD-FR
```
 @MISC{kabbadj2018,
   author =       "Kabbadj, Ali",
   title =        "Something new in French Text Mining and Information Extraction (Universal Chatbot): Largest Q&A French training dataset (110 000+) ",
   editor =       "linkedin.com",
   month =        "November",
   year =         "2018",
   url =          "\url{https://www.linkedin.com/pulse/something-new-french-text-mining-information-chatbot-largest-kabbadj/}",
   note =         "[Online; posted 11-November-2018]",
 }
 ```

### CamemBERT
HF model card : [https://huggingface.co/camembert-base](https://huggingface.co/camembert-base)

```
@inproceedings{martin2020camembert,
  title={CamemBERT: a Tasty French Language Model},
  author={Martin, Louis and Muller, Benjamin and Su{\'a}rez, Pedro Javier Ortiz and Dupont, Yoann and Romary, Laurent and de la Clergerie, {\'E}ric Villemonte and Seddah, Djam{\'e} and Sagot, Beno{\^\i}t},
  booktitle={Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
  year={2020}
}
```


{"language": "fr", "datasets": ["piaf", "FQuAD", "SQuAD-FR"], "widget": [{"text": "Comment s'appelle le portail open data du gouvernement ?", "context": "Etalab est une administration publique fran\u00e7aise qui fait notamment office de Chief Data Officer de l'\u00c9tat et coordonne la conception et la mise en \u0153uvre de sa strat\u00e9gie dans le domaine de la donn\u00e9e (ouverture et partage des donn\u00e9es publiques ou open data, exploitation des donn\u00e9es et intelligence artificielle...). Ainsi, Etalab d\u00e9veloppe et maintient le portail des donn\u00e9es ouvertes du gouvernement fran\u00e7ais data.gouv.fr. Etalab promeut \u00e9galement une plus grande ouverture l'administration sur la soci\u00e9t\u00e9 (gouvernement ouvert) : transparence de l'action publique, innovation ouverte, participation citoyenne... elle promeut l\u2019innovation, l\u2019exp\u00e9rimentation, les m\u00e9thodes de travail ouvertes, agiles et it\u00e9ratives, ainsi que les synergies avec la soci\u00e9t\u00e9 civile pour d\u00e9cloisonner l\u2019administration et favoriser l\u2019adoption des meilleures pratiques professionnelles dans le domaine du num\u00e9rique. \u00c0 ce titre elle \u00e9tudie notamment l\u2019opportunit\u00e9 de recourir \u00e0 des technologies en voie de maturation issues du monde de la recherche. Cette entit\u00e9 charg\u00e9e de l'innovation au sein de l'administration doit contribuer \u00e0 l'am\u00e9lioration du service public gr\u00e2ce au num\u00e9rique. Elle est rattach\u00e9e \u00e0 la Direction interminist\u00e9rielle du num\u00e9rique, dont les missions et l\u2019organisation ont \u00e9t\u00e9 fix\u00e9es par le d\u00e9cret du 30 octobre 2019.\u2009 Dirig\u00e9 par Laure Lucchesi depuis 2016, elle rassemble une \u00e9quipe pluridisciplinaire d'une trentaine de personnes."}]}
transformers pytorch tf safetensors camembert question-answering fr dataset:piaf dataset:FQuAD dataset:SQuAD-FR endpoints_compatible region:us
TAGS
#transformers #pytorch #tf #safetensors #camembert #question-answering #fr #dataset-piaf #dataset-FQuAD #dataset-SQuAD-FR #endpoints_compatible #region-us 


# camembert-base-squadFR-fquad-piaf

## Description

Question-answering French model, using base CamemBERT fine-tuned on a combo of three French Q&A datasets:

1. PIAFv1.1
2. FQuADv1.0
3. SQuAD-FR (SQuAD automatically translated to French)

## Training hyperparameters

 

## Evaluation results
### FQuAD v1.0 Evaluation

### SQuAD-FR Evaluation


## Usage


## Acknowledgments

This work was performed using HPC resources from GENCI–IDRIS (Grant 2020-AD011011224). 

s

### PIAF


### FQuAD


### SQuAD-FR


### CamemBERT
HF model card : URL




# camembert-base-squadFR-fquad-piaf ## Description

Question-answering French model, using base CamemBERT fine-tuned on a combo of three French Q&A datasets:

1. PIAFv1.1
2. FQuADv1.0
3. SQuAD-FR (SQuAD automatically translated to French) ## Training hyperparameters ## Evaluation results ### FQuAD v1.0 Evaluation ### SQuAD-FR Evaluation ## Usage ## Acknowledgments

This work was performed using HPC resources from GENCI–IDRIS (Grant 2020-AD011011224). 

s ### PIAF ### FQuAD ### SQuAD-FR ### CamemBERT
HF model card : URL
TAGS
#transformers #pytorch #tf #safetensors #camembert #question-answering #fr #dataset-piaf #dataset-FQuAD #dataset-SQuAD-FR #endpoints_compatible #region-us 
 # camembert-base-squadFR-fquad-piaf ## Description

Question-answering French model, using base CamemBERT fine-tuned on a combo of three French Q&A datasets:

1. PIAFv1.1
2. FQuADv1.0
3. SQuAD-FR (SQuAD automatically translated to French) ## Training hyperparameters ## Evaluation results ### FQuAD v1.0 Evaluation ### SQuAD-FR Evaluation ## Usage ## Acknowledgments

This work was performed using HPC resources from GENCI–IDRIS (Grant 2020-AD011011224). 

s ### PIAF ### FQuAD ### SQuAD-FR ### CamemBERT
HF model card : URL
passage: TAGS
#transformers #pytorch #tf #safetensors #camembert #question-answering #fr #dataset-piaf #dataset-FQuAD #dataset-SQuAD-FR #endpoints_compatible #region-us 
# camembert-base-squadFR-fquad-piaf## Description

Question-answering French model, using base CamemBERT fine-tuned on a combo of three French Q&A datasets:

1. PIAFv1.1
2. FQuADv1.0
3. SQuAD-FR (SQuAD automatically translated to French)## Training hyperparameters## Evaluation results### FQuAD v1.0 Evaluation### SQuAD-FR Evaluation## Usage## Acknowledgments

This work was performed using HPC resources from GENCI–IDRIS (Grant 2020-AD011011224). 

s### PIAF### FQuAD### SQuAD-FR### CamemBERT
HF model card : URL