Duplicate from alusci/sms-otp-spam-dataset

Co-authored-by: Alessandro Lusci <alusci@users.noreply.huggingface.co>

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README.md

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+---
+license: mit
+task_categories:
+- text-classification
+language:
+- en
+tags:
+- sms
+- spam-detection
+- otp
+- nlp
+- synthetic-data
+pretty_name: SMS OTP Spam Classification Dataset
+size_categories:
+- 10K<n<100K
+---
+
+# 📲 SMS OTP Spam Dataset
+
+A synthetic dataset of 10,000 OTP-style SMS messages for spam classification tasks. The dataset includes both valid and spam-like messages, with labels for message validity and delivery status.
+
+## 📊 Dataset Summary
+
+- **Total samples**: 10,000
+- **Valid messages**: 90%
+- **Not valid (spam-like)**: 10%
+- **Status types**: `delivered`, `failed`, `spam`, `bounced`, `expired`
+
+Each entry includes:
+- `phone_id`: Synthetic phone number
+- `sms_text`: Message content
+- `label`: `valid` or `not valid`
+- `timestamp`: Synthetic datetime
+- `status`: Message delivery outcome
+
+## 🔍 Tasks
+
+This dataset can be used for:
+- Binary text classification (`valid` vs `not valid`)
+- Spam detection in telecom and messaging systems
+- Evaluating robustness of NLP classifiers to synthetic vs real-world content
+
+## 🏷 Tags
+`#sms` `#spam-detection` `#otp` `#nlp` `#synthetic-data`
+
+## 📄 License
+
+MIT License
+
+## 📚 Citation
+
+```bibtex
+@misc{smsotp2025,
+  title        = {SMS OTP Spam Dataset},
+  author       = {Alessandro Lusci},
+  year         = 2025,
+  note         = {Synthetic dataset generated for spam classification research.},
+  url          = {https://huggingface.co/datasets/alusci/sms-otp-spam-dataset}
+}