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README.md
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- FacebookAI/xlm-roberta-base
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XLM-Roberta-based classifier trained on [XFORMAL](https://aclanthology.org/2021.naacl-main.256.bib) -- a multilingual formality classification dataset.
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| | precision | recall | f1-score | support |
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|--------------|-----------|----------|----------|---------|
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| weighted avg | 0.813068 | 0.794405 | 0.789337 | 204864 |
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| | precision | recall | f1-score | support |
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| macro avg | 0.872579 | 0.844440 | 0.847556 | 41600 |
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| weighted avg | 0.867869 | 0.852139 | 0.849273 | 41600 |
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| | precision | recall | f1-score | support |
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| macro avg | 0.817007 | 0.788165 | 0.788686 | 40832 |
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| weighted avg | 0.813257 | 0.795504 | 0.790711 | 40832 |
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| | precision | recall | f1-score | support |
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|--------------|-----------|----------|----------|---------|
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| macro avg | 0.793084 | 0.760902 | 0.759995 | 40896 |
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| weighted avg | 0.789292 | 0.769024 | 0.762454 | 40896 |
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| | precision | recall | f1-score | support |
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|--------------|-----------|----------|----------|---------|
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- FacebookAI/xlm-roberta-base
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**Model Overview**
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This is the model presented in the paper ["Detecting Text Formality: A Study of Text Classification Approaches"](https://aclanthology.org/2023.ranlp-1.31/).
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XLM-Roberta-based classifier trained on [XFORMAL](https://aclanthology.org/2021.naacl-main.256.bib) -- a multilingual formality classification dataset.
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**Results**
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All languages
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| | precision | recall | f1-score | support |
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|--------------|-----------|----------|----------|---------|
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| weighted avg | 0.813068 | 0.794405 | 0.789337 | 204864 |
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EN
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| | precision | recall | f1-score | support |
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|--------------|-----------|----------|----------|---------|
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| macro avg | 0.872579 | 0.844440 | 0.847556 | 41600 |
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| weighted avg | 0.867869 | 0.852139 | 0.849273 | 41600 |
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FR
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| | precision | recall | f1-score | support |
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|--------------|-----------|----------|----------|---------|
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| macro avg | 0.817007 | 0.788165 | 0.788686 | 40832 |
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| weighted avg | 0.813257 | 0.795504 | 0.790711 | 40832 |
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IT
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| | precision | recall | f1-score | support |
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|--------------|-----------|----------|----------|---------|
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| macro avg | 0.793084 | 0.760902 | 0.759995 | 40896 |
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| weighted avg | 0.789292 | 0.769024 | 0.762454 | 40896 |
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PT
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| | precision | recall | f1-score | support |
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