mshenoda/roberta-spam
Text Classification
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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.
Dataset Class Distribution
| Training 80% | Validation 10% | Testing 10% |
|---|---|---|
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Models trained or fine-tuned on mshenoda/spam-messages