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README.md
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---
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language:
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- fr
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license:
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- other
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size_categories:
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- 10K<n<100K
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task_categories:
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- text-classification
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task_ids:
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- text-scoring
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- semantic-similarity-scoring
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---
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# stsb_multi_mt_fr_prompt
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## Summary
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**stsb_multi_mt_fr_prompt** is a subset of the [**Dataset of French Prompts (DFP)**]().
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It contains **X** rows that can be used for a semantic similarity scoring task.
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The original data (without prompts) comes from the dataset [stsb_multi_mt](https://huggingface.co/datasets/stsb_multi_mt) by May where only the French part has been kept.
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A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the [xP3](https://huggingface.co/datasets/bigscience/xP3) dataset by Muennighoff et al.
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## Prompts used
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### List
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18 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.
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```
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'Déterminer le score de similarité entre les deux phrases suivantes. Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"',
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'Déterminez le score de similarité entre les deux phrases suivantes. Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"',
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'Détermine le score de similarité entre les deux phrases suivantes. Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"',
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'Indiquer le score de similarité entre les deux phrases suivantes. Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"',
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'Indiquez le score de similarité entre les deux phrases suivantes. Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"',
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'Indique le score de similarité entre les deux phrases suivantes. Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"',
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'Donner le score de similarité entre les deux phrases suivantes. Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"',
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'Donnez le score de similarité entre les deux phrases suivantes. Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"',
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'Donne le score de similarité entre les deux phrases suivantes. Phrase 1 : "'+sentence1+'"\n Phrase 2 : "'+sentence2+'"',
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'Déterminer le score de similarité entre la phrase : "'+sentence1+'"\n et la phrase : "'+sentence2+'"\n Similarité : ',
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'Déterminez le score de similarité entre la phrase : "'+sentence1+'"\n et la phrase : "'+sentence2+'"\n Similarité : ',
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'Détermine le score de similarité entre la phrase : "'+sentence1+'"\n et la phrase : "'+sentence2+'"\n Similarité : ',
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'Indiquer le score de similarité entre la phrase : "'+sentence1+'"\n et la phrase : "'+sentence2+'"\n Similarité : ',
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'Indiquez le score de similarité entre la phrase : "'+sentence1+'"\n et la phrase : "'+sentence2+'"\n Similarité : ',
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'Indique le score de similarité entre la phrase : "'+sentence1+'"\n et la phrase : "'+sentence2+'"\n Similarité : ',
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'Donner le score de similarité entre la phrase : "'+sentence1+'"\n et la phrase : "'+sentence2+'"\n Similarité : ',
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'Donnez le score de similarité entre la phrase : "'+sentence1+'"\n et la phrase : "'+sentence2+'"\n Similarité : ',
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'Donne le score de similarité entre la phrase : "'+sentence1+'"\n et la phrase : "'+sentence2+'"\n Similarité : ',
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```
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### Features used in the prompts
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In the prompt list above, `sentence1`, `sentence2` and the `target` have been constructed from:
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```
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stsb = load_dataset('stsb_multi_mt','fr')
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sentence1 = stsb['train'][i]['sentence1']
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sentence2 = stsb['train'][i]['sentence2']
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targets = float(stsb['train'][i]['similarity_score'])/5.0)
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```
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# Splits
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- train with X samples
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- dev with Y samples
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- test with Z samples
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# How to use?
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```
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dataset = load_dataset('stsb_multi_mt_fr_prompt')
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```
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# Citation
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## Original data
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> @InProceedings{huggingface:dataset:stsb_multi_mt,
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title = {Machine translated multilingual STS benchmark dataset.},
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author={Philip May},
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year={2021},
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url={https://github.com/PhilipMay/stsb-multi-mt}
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}
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## This Dataset
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# License
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https://github.com/PhilipMay/stsb-multi-mt/blob/main/LICENSE
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