1. Multimodal Multilingual Hate Speech 11K (MMHS11K) Dataset consists of 11,000 labeled Urdu Tweets with English translation. 
	Tweets are divided into two Categories i.e. 'Hate' and 'No-Hate' .  
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2. The dataset is divided into two parts (i.e. '.xlsx' files). 
	In each file,
		'Tweet_Id' represents the corresponding Tweet_Identifier.
		'Text' represents Textual content of the Tweet in Urdu language.
		'Text(English)' represents English Translation of corresponding Urdu Tweet.  
		'Image_Text' represents text extracted from Images in Urdu, 
			if no text is extracted, 'NIL' value is placed in corresponding cell.
		'Image_Text(English)' represents the English translation of corresponding value of 'Image_Text' column,
			'NIL' value in corresponding cell of 'Image_Text' column is retained in Image_Text(English)' .
		'Label' represents the corresponding class of the multimodal tweet. 
			
    The details of the two files are: 
	(A). MMHS11K_train.xlsx (80% Training data, i.e. 8800 samples).
		In this file, 4400 samples belong to 'Hate' class and
		4400 samples belong to 'No-Hate' class

	(B). MMHS11K_test.xlsx (20% Training data, i.e. 2200 samples)
		In this file, 1100 samples belong to 'Hate' class and
		1100 samples belong to 'No-Hate' class
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3. There are two folder in the dataset' 
	(A). 'MMHS11K_RGB_train' folder contains training images in RGB format.
		It contains two sub-folder: 'Hate' and 'No-Hate'
			For each tweet in 'MMHS11K_train.xlsx' file, 
			corresponding image in stored in corresponding 
			sub-folder of 'MMHS11K_RGB_train' folder with sample name as 'Tweet_Id'.
			e.g. 'Tweet_Id'=1596192893743796224 is stored in 'No-Hate' sub-folder of
			'MMHS11K_RGB_train' folder as this tweet is labeled as 'No-Hate'.

	(B). 'MMHS11K_RGB_test' folder contains test images in RGB format.
		It contains two sub-folder: 'Hate' and 'No-Hate'
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