Update README.md

README.md

@@ -6,12 +6,12 @@ tags: []
 # 5CD-AI/visocial-T5-base
 ## Overview
 <!-- Provide a quick summary of what the model is/does. -->
-We continually pretrain `google/mt5-base` [1] on a merged 20GB dataset, the training dataset includes:
+We continually pretrain `google/mt5-base`[1] on a merged 20GB dataset, the training dataset includes:
 - Internal data (100M comments and 15M posts on Facebook)
-- UIT data [2], which is used to pretrain `uitnlp/visobert`[2]
+- UIT data[2], which is used to pretrain `uitnlp/visobert`[2]
 - MC4 ecommerce
 - 10.7M comments on VOZ Forum from `tarudesu/VOZ-HSD`
-- 3.6M reviews from Amazon [3] translated into Vietnamese from `5CD-AI/Vietnamese-amazon_polarity-gg-translated`
+- 3.6M reviews from Amazon[3] translated into Vietnamese from `5CD-AI/Vietnamese-amazon_polarity-gg-translated`
 
 Here are the results on 3 downstream tasks on Vietnamese social media texts, including Hate Speech Detection(UIT-HSD), Toxic Speech Detection(ViCTSD), Hate Spans Detection(ViHOS):
 <table>
@@ -34,7 +34,7 @@ Here are the results on 3 downstream tasks on Vietnamese social media texts, inc
             <td><b>MF1</td>
         </tr>
         <tr align="center">
-            <td align="left">PhoBERT</td>
+            <td align="left">PhoBERT[4]</td>
             <td>69.63</td>
             <td>86.75</td>
             <td>86.52</td>
@@ -47,7 +47,7 @@ Here are the results on 3 downstream tasks on Vietnamese social media texts, inc
             <td>72.81</td>
         </tr>
         <tr align="center">
-            <td align="left">PhoBERT_v2</td>
+            <td align="left">PhoBERT_v2[4]</td>
             <td>70.50</td>
             <td>87.42</td>
             <td>87.33</td>
@@ -60,7 +60,7 @@ Here are the results on 3 downstream tasks on Vietnamese social media texts, inc
             <td>73.51</td>
         </tr>
         <tr align="center">
-            <td align="left">viBERT</td>
+            <td align="left">viBERT[5]</td>
             <td>67.80</td>
             <td>86.33</td>
             <td>85.79</td>
@@ -73,7 +73,7 @@ Here are the results on 3 downstream tasks on Vietnamese social media texts, inc
             <td>72.91</td>
         </tr>
         <tr align="center">
-            <td align="left">ViSoBERT</td>
+            <td align="left">ViSoBERT[6]</td>
             <td>75.07</td>
             <td>88.17</td>
             <td>87.86</td>
@@ -86,7 +86,7 @@ Here are the results on 3 downstream tasks on Vietnamese social media texts, inc
             <td>86.04</td>
         </tr>
         <tr align="center">
-            <td align="left">ViHateT5</td>
+            <td align="left">ViHateT5[7]</td>
             <td>75.56</td>
             <td>88.76</td>
             <td>89.14</td>
@@ -149,4 +149,12 @@ We fine-tune `5CD-AI/visocial-T5-base` on 3 downstream tasks with `transformers`
 
 [2][ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing](https://aclanthology.org/2023.emnlp-main.315/)
 
-[3][The Amazon Polarity dataset](https://paperswithcode.com/dataset/amazon-polarity-1)
+[3][The Amazon Polarity dataset](https://paperswithcode.com/dataset/amazon-polarity-1)
+
+[4][PhoBERT: Pre-trained language models for Vietnamese](https://aclanthology.org/2020.findings-emnlp.92/)
+
+[5][Improving Sequence Tagging for Vietnamese Text Using Transformer-based Neural Models](https://arxiv.org/abs/2006.15994)
+
+[6][ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing](https://aclanthology.org/2023.emnlp-main.315/)
+
+[7][ViHateT5: Enhancing Hate Speech Detection in Vietnamese With A Unified Text-to-Text Transformer Model](https://arxiv.org/abs/2405.14141)