Update README.md

README.md

@@ -14,11 +14,12 @@ pretty_name: "Machine Translation Paired English-Vietnamese Sentences"
 size_categories:
 - 1M<n<10M
 source_datasets:
-- extended|open_subtitles
-- extended|tatoeba
-- extended|opus_tedtalks
-- extended|qed_amara
-- extended|opus_wikipedia
+- own
+- open_subtitles
+- tatoeba
+- opus_tedtalks
+- qed_amara
+- opus_wikipedia
 task_categories:
 - conditional-text-generation
 task_ids:
@@ -54,24 +55,15 @@ task_ids:
 
 ## Dataset Description
 
-- **Homepage:** https://sites.google.com/uit.edu.vn/uit-nlp/datasets-projects#h.p_4Brw8L-cbfTe
+- **Homepage:** 
 - **Repository:**
-- **Paper:** [UIT-VSFC: Vietnamese Students’ Feedback Corpus for Sentiment Analysis](https://www.researchgate.net/publication/329645066_UIT-VSFC_Vietnamese_Students'_Feedback_Corpus_for_Sentiment_Analysis)
+- **Paper:** 
 - **Leaderboard:**
 - **Point of Contact:**
 
 ### Dataset Summary
 
-Students’ feedback is a vital resource for the interdisciplinary research involving the combining of two different
-research fields between sentiment analysis and education.
-
-Vietnamese Students’ Feedback Corpus (UIT-VSFC) is the resource consists of over 16,000 sentences which are
-human-annotated with two different tasks: sentiment-based and topic-based classifications.
-
-To assess the quality of our corpus, we measure the annotator agreements and classification evaluation on the
-UIT-VSFC corpus. As a result, we obtained the inter-annotator agreement of sentiments and topics with more than over
-91% and 71% respectively. In addition, we built the baseline model with the Maximum Entropy classifier and achieved
-approximately 88% of the sentiment F1-score and over 84% of the topic F1-score.
+[More Information Needed]
 
 ### Supported Tasks and Leaderboards
 
@@ -79,7 +71,7 @@ approximately 88% of the sentiment F1-score and over 84% of the topic F1-score.
 
 ### Languages
 
-The language of the dataset text sentence is Vietnamese (`vi`).
+The language of the dataset text sentence is English ('en') and Vietnamese (`vi`).
 
 ## Dataset Structure
 
@@ -88,17 +80,17 @@ The language of the dataset text sentence is Vietnamese (`vi`).
 An instance example:
 ```
 {
-  'sentence': 'slide giáo trình đầy đủ .', 
-  'sentiment': 2, 
-  'topic': 1
+  'en': 'And what I think the world needs now is more connections.', 
+  'vi': 'Và tôi nghĩ điều thế giới đang cần bây giờ là nhiều sự kết nối hơn.', 
+  'source': 'TED2020 v1'
 }
 ```
 
 ### Data Fields
 
-- `sentence` (str): Text sentence.
-- `sentiment`: Sentiment class, with values 0 (negative), 1 (neutral) and 2 (positive).
-- `topic`: Topic class, with values 0 (lecturer), 1 (training_program), 2 (facility) and 3 (others).
+- `en` (str): English sentence
+- `vi` (str): Vietnamese sentence
+- `source` (str): Source.
 
 ### Data Splits
 
@@ -106,7 +98,7 @@ The dataset is split in train, validation and test.
 
 |                    |  Tain | Validation | Test |
 |--------------------|------:|-----------:|-----:|
-| Number of examples | 11426 |       1583 | 3166 |
+| Number of examples |2884451|       11316| 11225|
 
 
 ## Dataset Creation
@@ -161,23 +153,12 @@ The dataset is split in train, validation and test.
 
 ### Licensing Information
 
-Unknown.
+[More Information Needed]
 
 ### Citation Information
 
-```
-@InProceedings{8573337,
-  author={Nguyen, Kiet Van and Nguyen, Vu Duc and Nguyen, Phu X. V. and Truong, Tham T. H. and Nguyen, Ngan Luu-Thuy},
-  booktitle={2018 10th International Conference on Knowledge and Systems Engineering (KSE)},
-  title={UIT-VSFC: Vietnamese Students’ Feedback Corpus for Sentiment Analysis},
-  year={2018},
-  volume={},
-  number={},
-  pages={19-24},
-  doi={10.1109/KSE.2018.8573337}
-}
-```
+[More Information Needed]
 
 ### Contributions
 
-Thanks to [@albertvillanova](https://github.com/albertvillanova) for adding this dataset.
+Thanks to [@ncduy0303](https://github.com/ncduy0303) for adding this dataset.