Datasets:
sms_spam

	---
	annotations_creators:
	- crowdsourced
	- found
	language_creators:
	- crowdsourced
	- found
	language:
	- en
	license:
	- unknown
	multilinguality:
	- monolingual
	size_categories:
	- 1K<n<10K
	source_datasets:
	- extended\|other-nus-sms-corpus
	task_categories:
	- text-classification
	task_ids:
	- intent-classification
	paperswithcode_id: sms-spam-collection-data-set
	pretty_name: SMS Spam Collection Data Set
	dataset_info:
	features:
	- name: sms
	dtype: string
	- name: label
	dtype:
	class_label:
	names:
	'0': ham
	'1': spam
	config_name: plain_text
	splits:
	- name: train
	num_bytes: 521756
	num_examples: 5574
	download_size: 203415
	dataset_size: 521756
	train-eval-index:
	- config: plain_text
	task: text-classification
	task_id: binary_classification
	splits:
	train_split: train
	col_mapping:
	sms: text
	label: target
	metrics:
	- type: accuracy
	name: Accuracy
	- type: f1
	name: F1 macro
	args:
	average: macro
	- type: f1
	name: F1 micro
	args:
	average: micro
	- type: f1
	name: F1 weighted
	args:
	average: weighted
	- type: precision
	name: Precision macro
	args:
	average: macro
	- type: precision
	name: Precision micro
	args:
	average: micro
	- type: precision
	name: Precision weighted
	args:
	average: weighted
	- type: recall
	name: Recall macro
	args:
	average: macro
	- type: recall
	name: Recall micro
	args:
	average: micro
	- type: recall
	name: Recall weighted
	args:
	average: weighted
	---

	# Dataset Card for [Dataset Name]

	## Table of Contents
	- [Dataset Description](#dataset-description)
	- [Dataset Summary](#dataset-summary)
	- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
	- [Languages](#languages)
	- [Dataset Structure](#dataset-structure)
	- [Data Instances](#data-instances)
	- [Data Fields](#data-fields)
	- [Data Splits](#data-splits)
	- [Dataset Creation](#dataset-creation)
	- [Curation Rationale](#curation-rationale)
	- [Source Data](#source-data)
	- [Annotations](#annotations)
	- [Personal and Sensitive Information](#personal-and-sensitive-information)
	- [Considerations for Using the Data](#considerations-for-using-the-data)
	- [Social Impact of Dataset](#social-impact-of-dataset)
	- [Discussion of Biases](#discussion-of-biases)
	- [Other Known Limitations](#other-known-limitations)
	- [Additional Information](#additional-information)
	- [Dataset Curators](#dataset-curators)
	- [Licensing Information](#licensing-information)
	- [Citation Information](#citation-information)
	- [Contributions](#contributions)

	## Dataset Description

	- Homepage: http://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection
	- Repository:
	- Paper: Almeida, T.A., Gomez Hidalgo, J.M., Yamakami, A. Contributions to the study of SMS Spam Filtering: New Collection and Results. Proceedings of the 2011 ACM Symposium on Document Engineering (ACM DOCENG'11), Mountain View, CA, USA, 2011.
	- Leaderboard:
	- Point of Contact:

	### Dataset Summary

	The SMS Spam Collection v.1 is a public set of SMS labeled messages that have been collected for mobile phone spam research.
	It has one collection composed by 5,574 English, real and non-enconded messages, tagged according being legitimate (ham) or spam.

	### Supported Tasks and Leaderboards

	[More Information Needed]

	### Languages

	English

	## Dataset Structure

	### Data Instances

	[More Information Needed]

	### Data Fields

	- sms: the sms message
	- label: indicating if the sms message is ham or spam, ham means it is not spam

	### Data Splits

	[More Information Needed]

	## Dataset Creation

	### Curation Rationale

	[More Information Needed]

	### Source Data

	#### Initial Data Collection and Normalization

	[More Information Needed]

	#### Who are the source language producers?

	[More Information Needed]

	### Annotations

	#### Annotation process

	[More Information Needed]

	#### Who are the annotators?

	[More Information Needed]

	### Personal and Sensitive Information

	[More Information Needed]

	## Considerations for Using the Data

	### Social Impact of Dataset

	[More Information Needed]

	### Discussion of Biases

	[More Information Needed]

	### Other Known Limitations

	[More Information Needed]

	## Additional Information

	### Dataset Curators

	[More Information Needed]

	### Licensing Information

	[More Information Needed]

	### Citation Information

	@inproceedings{Almeida2011SpamFiltering,
	title={Contributions to the Study of SMS Spam Filtering: New Collection and Results},
	author={Tiago A. Almeida and Jose Maria Gomez Hidalgo and Akebo Yamakami},
	year={2011},
	booktitle = "Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11)",
	}

	### Contributions

	Thanks to [@czabo](https://github.com/czabo) for adding this dataset.