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mshenoda commited on Jun 7, 2023

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 ## Dataset
 The dataset is composed of messages labeled by ham or spam, merged from three data sources:
-1.	SMS Spam Collection https://www.kaggle.com/datasets/uciml/sms-spam-collection-dataset
-2.	Telegram Spam Ham https://huggingface.co/datasets/thehamkercat/telegram-spam-ham/tree/main
-3.	Enron Spam:  https://huggingface.co/datasets/SetFit/enron_spam/tree/main (only used message column and labels)
 The prepare script for enron is available at https://github.com/mshenoda/roberta-spam/tree/main/data/enron.
 The data is split 80% train 10% validation, and 10% test sets; the scripts used to split and merge of the three data sources are available at: https://github.com/mshenoda/roberta-spam/tree/main/data/utils.

 ## Dataset
 The dataset is composed of messages labeled by ham or spam, merged from three data sources:
+- SMS Spam Collection https://www.kaggle.com/datasets/uciml/sms-spam-collection-dataset
+- Telegram Spam Ham https://huggingface.co/datasets/thehamkercat/telegram-spam-ham/tree/main
+- Enron Spam:  https://huggingface.co/datasets/SetFit/enron_spam/tree/main (only used message column and labels)
 The prepare script for enron is available at https://github.com/mshenoda/roberta-spam/tree/main/data/enron.
 The data is split 80% train 10% validation, and 10% test sets; the scripts used to split and merge of the three data sources are available at: https://github.com/mshenoda/roberta-spam/tree/main/data/utils.