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README.md
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We present **QAmemBERT**, which is a [CamemBERT large](https://huggingface.co/camembert/camembert-large) fine-tuned for the Question-Answering task for the French language on four French Q&A datasets composed of contexts and questions with their answers inside the context (= SQuAD 1.0 format) but also contexts and questions with their answers not inside the context (= SQuAD 2.0 format).
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All these datasets were concatenated into a single dataset that we called [frenchQA](https://huggingface.co/datasets/CATIE-AQ/frenchQA).
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This represents a total of over **221,348 context/question/answer triplets used to finetune this model and 6,376 to test it**.
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Our methodology is described in a blog post available in [English](https://blog.vaniila.ai/en/
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## Datasets
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We present **QAmemBERT**, which is a [CamemBERT large](https://huggingface.co/camembert/camembert-large) fine-tuned for the Question-Answering task for the French language on four French Q&A datasets composed of contexts and questions with their answers inside the context (= SQuAD 1.0 format) but also contexts and questions with their answers not inside the context (= SQuAD 2.0 format).
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All these datasets were concatenated into a single dataset that we called [frenchQA](https://huggingface.co/datasets/CATIE-AQ/frenchQA).
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This represents a total of over **221,348 context/question/answer triplets used to finetune this model and 6,376 to test it**.
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Our methodology is described in a blog post available in [English](https://blog.vaniila.ai/en/QA_en/) or [French](https://blog.vaniila.ai/QA/).
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## Datasets
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