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Model: fmikaelian/camembert-base-squad
pytorch camembert question-answering fr
Model card Files and versions Use in transformers

How to use this model directly from the 🤗/transformers library: 

					
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						from transformers import AutoTokenizer, AutoModelForQuestionAnswering
						
						tokenizer = AutoTokenizer.from_pretrained("fmikaelian/camembert-base-squad")
						
						model = AutoModelForQuestionAnswering.from_pretrained("fmikaelian/camembert-base-squad")
See raw config file

How to clone the model repo 

					
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					git lfs install
					git clone https://huggingface.co/fmikaelian/camembert-base-squad
					

						# if you want to clone without large files – just their pointers
						# prepend your git clone with the following env var:
					

					GIT_LFS_SKIP_SMUDGE=1
Done
question-answering mask_token: <mask>
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Contributed by

fmikaelian Félix MIKAELIAN
3 models
Hosted on huggingface.co

camembert-base-squad

Description

A baseline model for question-answering in french (CamemBERT model fine-tuned on french-translated SQuAD 1.1 dataset)

Training hyperparameters

python3 ./examples/question-answering/run_squad.py \
--model_type camembert \
--model_name_or_path camembert-base \
--do_train \
--do_eval \
--do_lower_case \
--train_file SQuAD-v1.1-train_fr_ss999_awstart2_net.json \
--predict_file SQuAD-v1.1-dev_fr_ss999_awstart2_net.json \
--learning_rate 3e-5 \
--num_train_epochs 2 \
--max_seq_length 384 \
--doc_stride 128 \
--output_dir output3 \
--per_gpu_eval_batch_size=3 \
--per_gpu_train_batch_size=3 \
--save_steps 10000

Evaluation results

{"f1": 79.8570684959745, "exact_match": 59.21327108373895}

Usage

from transformers import pipeline

nlp = pipeline('question-answering', model='fmikaelian/camembert-base-squad', tokenizer='fmikaelian/camembert-base-squad')

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."
})