applied lang detection

README.md

@@ -73,7 +73,7 @@ The preprocessed training data alone consists of 2,880,230 rows of comments, twe
 | [multilingual-train-deduplicated.csv](./multilingual-train-deduplicated.csv) |   416,457   |   2,463,773   |   2,880,230   |
 | [multilingual-validation.csv](./multilingual-validation.csv) |   1,230   |   6,770   |   8,000   |
 | [multilingual-test.csv](./multilingual-test.csv) |   14,410   |   49,402   |   63,812   |
-Each CSV file has two columns: `text` and `is_toxic`.
+Each CSV file has three columns: `text`, `is_toxic`, and `lang`.
 
 Supported languages:
 - Afrikaans
@@ -151,5 +151,6 @@ Known datasets:
 Some limitations include:
 - All labels were rounded to the nearest integer. If a text was classified as 46%-54% toxic, the text itself might not be noticeably toxic or neutral.
 - There were disagreements among moderators on some labels, due to ambiguity and lack of context.
+- When there're only URL(s), emojis, or anything that's unrecognizable as natural language in the "text" column, the corresponding "lang" is "unkown".
 
 Have fun modelling!