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README.md
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license: mit
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---
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license: mit
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language:
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- en
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- de
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- es
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- fr
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- pt
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metrics:
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- accuracy
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base_model:
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- microsoft/mdeberta-v3-base
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pipeline_tag: text-classification
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tags:
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- formal or informal classification
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widget:
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- text: Bitte geh einkaufen.
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- text: Können Sie mir spontan dabei helfen?
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- text: Als nächstes kommen 4g Champignons und 500g Mehl dazu.
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---
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# formality-classifier-mdeberta-v3-base
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This model can classify texts based on their formality. It classifies inputs into one of the three classes `["formal", "informal", "neutral"]`, with neutral pertaining to texts which do not have a clear formality, such as passive statements etc.
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In selecting and generating training data, a focus was put on languages that actually have a type of formal address etc., including French, German, Italian, Portuguese and Spanish.
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Some samples from [osyvokon/pavlick-formality-scores](https://huggingface.co/datasets/osyvokon/pavlick-formality-scores) were also used to try and teach the model to classify English inputs.
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## Results
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Accuracy on the test set:
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| Language | Accuracy |
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| --- | --- |
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| all | 88.93% |
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| English | 79.20% |
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| French | 100% |
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| German | 97.73% |
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| Italian | 97.83% |
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| Portuguese | 100% |
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| Spanish | 98.53% |
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Confusion Matrix:
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By Language:
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