tanaos/synthetic-spam-detection-dataset-spanish

--- language: - en license: mit tags: - spam-detection - text-classification - content-moderation - synthetic-data - tanaos pretty_name: tanaos-spam-detection-spanish Training Dataset task_categories: - text-classification task_ids: - acceptability-classification size_categories: - 10K<n<20K --- <p align="center"> <img src="https://raw.githubusercontent.com/tanaos/.github/master/assets/logo.png" width="250px" alt="Tanaos – Train task specific LLMs without training data, for offline NLP and Text Classification"> </p> # Tanaos Spam Detection Spanish Training Dataset This dataset was created synthetically by Tanaos with the [Artifex](https://github.com/tanaos/artifex) Python library. The dataset is designed to **train and evaluate spam detection systems** — models that detect, classify, or filter unsolicited commercial advertisement, fraudulent messages, or other unwanted content in text form — in Spanish. Our spanish spam detection model, [tanaos-spam-detection-spanish](https://huggingface.co/tanaos/tanaos-spam-detection-spanish), was trained on this dataset. ## Dataset Summary The dataset contains text samples labeled as either `0` (`not_spam`) or `1` (`spam`). The following categories are considered spam: 1. Unsolicited commercial advertisement or non-commercial proselytizing. 2. Fraudulent schemes. including get-rich-quick and pyramid schemes. 3. Phishing attempts. unrealistic offers or announcements. 4. Content with deceptive or misleading information. 5. Malware or harmful links. 6. Adult content or explicit material. 7. Excessive use of capitalization or punctuation to grab attention. --- ## How to Use ```python from datasets import load_dataset dataset = load_dataset("tanaos/synthetic-spam-detection-dataset-spanish") print(dataset["train"][0]) ``` ## Intended Use This dataset is intended for training and evaluating spam detection models. Common use cases: - Training machine learning models to classify text messages as spam or not spam. - Evaluating the performance of spam detection algorithms. - Fine-tuning pre-trained language models for spam detection tasks.language: - 英语 license: MIT协议 tags: - 垃圾邮件检测 - 文本分类 - 内容审核 - 合成数据 - tanaos pretty_name: tanaos西班牙语垃圾邮件检测训练数据集 task_categories: - 文本分类 task_ids: - 可接受性分类 size_categories: - 10K<n<20K <p align="center"> <img src="https://raw.githubusercontent.com/tanaos/.github/master/assets/logo.png" width="250px" alt="Tanaos——无需训练数据即可训练任务特定大语言模型（Large Language Models），适用于离线自然语言处理与文本分类"> </p> # Tanaos西班牙语垃圾邮件检测训练数据集 本数据集由Tanaos借助[Artifex](https://github.com/tanaos/artifex) Python库合成构建。 本数据集专为西班牙语环境下的**垃圾邮件检测系统**（即用于检测、分类或过滤非邀约商业广告、欺诈性消息或其他文本形式不良内容的模型）的训练与评估而打造。 我们的西班牙语垃圾邮件检测模型[tanaos-spam-detection-spanish](https://huggingface.co/tanaos/tanaos-spam-detection-spanish)正是基于本数据集训练得到的。 ## 数据集概览 本数据集包含标注为`0`（非垃圾邮件）或`1`（垃圾邮件）的文本样本。 以下类别被判定为垃圾邮件： 1. 非邀约商业广告或非商业性传教内容 2. 欺诈计划，包括快速致富骗局与金字塔传销 3. 网络钓鱼尝试、不实邀约或公告 4. 包含欺骗性或误导性信息的内容 5. 恶意软件或有害链接 6. 成人内容或露骨素材 7. 过度使用大写字母或标点符号以吸引注意力的内容 ## 使用方法 python from datasets import load_dataset dataset = load_dataset("tanaos/synthetic-spam-detection-dataset-spanish") print(dataset["train"][0]) ## 预期用途 本数据集旨在用于垃圾邮件检测模型的训练与评估。 典型应用场景包括： - 训练机器学习模型以将文本消息分类为垃圾邮件或非垃圾邮件 - 评估垃圾邮件检测算法的性能 - 针对垃圾邮件检测任务对预训练语言模型进行微调