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README.md
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@@ -114,6 +114,44 @@ Here are the results on 3 downstream tasks on Vietnamese social media texts, inc
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<!-- ## Usage (HuggingFace Transformers)
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Install `transformers` package:
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[6] [ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing](https://aclanthology.org/2023.emnlp-main.315/)
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[7] [ViHateT5: Enhancing Hate Speech Detection in Vietnamese With A Unified Text-to-Text Transformer Model](https://arxiv.org/abs/2405.14141)
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Visocial-T5-base versus other T5-based models in terms of Vietnamese HSD-related task performance with Macro F1-score:
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<table border="1" cellspacing="0" cellpadding="5">
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<tr align="center">
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<td rowspan=2><b>Model</b></td>
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<td colspan=3><b>MF1</b></td>
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</tr>
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<tr align="center">
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<td><b>Hate Speech Detection</b></td>
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<td><b>Toxic Speech Detection</b></td>
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<td><b>Hate Spans Detection</b></td>
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</tr>
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<tr align="center">
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<td align="left">mT5[1]</td>
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<td>66.76</td>
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<td>69.93</td>
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<td>86.60</td>
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</tr>
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<tr align="center">
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<td align="left">ViT5[8]</td>
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<td>66.95</td>
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<td>64.82</td>
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<td>86.90</td>
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</tr>
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<tr align="center">
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<td align="left">ViHateT5[7]</td>
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<td>68.67</td>
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<td>71.63</td>
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<td>86.37</td>
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</tr>
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<tr align="center">
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<td align="left"><b>visocial-T5-base(Ours)</td>
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<td><b>71.90</td>
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<td><b>73.81</td>
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<td><b>89.04</td>
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</tr>
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</table>
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<!-- ## Usage (HuggingFace Transformers)
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Install `transformers` package:
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[6] [ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing](https://aclanthology.org/2023.emnlp-main.315/)
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[7] [ViHateT5: Enhancing Hate Speech Detection in Vietnamese With A Unified Text-to-Text Transformer Model](https://arxiv.org/abs/2405.14141)
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[8] [ViT5: Pretrained Text-to-Text Transformer for Vietnamese Language Generation](https://aclanthology.org/2022.naacl-srw.18/)
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