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README.md
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name: DiffBleu # Optional. Example: Test WER
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---
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## Model objective
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## Model specs
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## Training and evaluation data
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## Metrics
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value: 0.38
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name: DiffBleu # Optional. Example: Test WER
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---
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## Model objective
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The purpose of this collaboratively trained model is to create a solution that reinforces the UN objective of the gender equality.
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Given any input, our model will generate a gender neutral sentence, correcting any non-inclusive expressions or words.
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It's a straightforward and fast solution that creates a positive impact in the contemporary social panorama.
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## Model specs
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## Training and evaluation data
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The data used for the model training has been manually created form a compilation of sources, obtained from a series of guidelines and manuals issued by Spanish Ministry of Health, Social Services and Equality in the matter of the usage of non-sexist language, stipulated in this linked [document](https://www.inmujeres.gob.es/servRecursos/formacion/GuiasLengNoSexista/docs/Guiaslenguajenosexista_.pdf):
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### Compiled sources
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[Guía para un discurso igualitario en la universidad de alicante]()
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Guía UC de Comunicación en Igualdad
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## Metrics
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