Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
json
Languages:
English
Size:
10K - 100K
License:
High-Accuracy Email Classification Dataset
Dataset Description
This dataset contains 12,000+ emails across 6 categories, specifically curated for high-accuracy email classification tasks. The dataset achieves 98%+ classification accuracy with appropriate models.
Categories
The dataset includes emails from the following categories:
Category | Count | Description | Emoji |
---|---|---|---|
Forum | ~2,000 | Forum posts, discussions, and community notifications | ๐ฃ๏ธ |
Promotions | ~2,000 | Marketing emails, sales, offers, and advertisements | ๐ |
Social Media | ~2,000 | Notifications from social platforms | ๐ฑ |
Spam | ~2,000 | Unwanted emails, scams, and phishing attempts | โ ๏ธ |
Updates | ~2,000 | System updates, security patches, maintenance notices | ๐ |
Verify Code | ~2,000 | Authentication codes and verification emails | ๐ |
Dataset Structure
Data Splits
- Training Set: ~9,600 emails (80%)
- Test Set: ~2,400 emails (20%)
Data Format
Each email contains the following fields:
id
: Unique identifier for each emailsubject
: Email subject linebody
: Email body contenttext
: Combined subject and body textcategory
: Email category labelcategory_id
: Numeric category identifier (0-5)
Files
train.csv
/train.json
: Training datasettest.csv
/test.json
: Test datasetfull_dataset.csv
/full_dataset.json
: Complete datasetdataset_info.json
: Dataset metadata and statistics
Usage
Loading the Dataset
import pandas as pd
# Load training data
train_df = pd.read_csv("train.csv")
test_df = pd.read_csv("test.csv")
# View categories
print(train_df['category'].value_counts())
Example Email Samples
Spam Email:
Subject: Congratulations! You've won $1000!
Body: Click here to claim your prize now! Limited time offer.
Category: spam
Verification Code:
Subject: Your verification code
Body: Your verification code is 123456. Please enter this code to complete your login.
Category: verify_code
Model Performance
When used with the companion CNN+GRU model:
- Training Accuracy: 98.13%
- Validation Accuracy: 98%+
- Model Repository: jason23322/high-accuracy-email-classifier
Data Quality
- Balanced: Each category contains approximately 2,000 emails
- Diverse: Wide variety of email content and styles
- Clean: Manually curated and validated
- Realistic: Based on common email patterns and templates
Applications
This dataset is suitable for:
- Email classification and filtering
- Spam detection systems
- Email client automation
- Text classification research
- Natural language processing studies
- Cybersecurity research
Citation
@misc{email_classification_dataset,
title={High-Accuracy Email Classification Dataset},
author={Email Classification Team},
year={2024},
publisher={Hugging Face},
url={https://huggingface.co/datasets/jason23322/email-classification-dataset}
}
License
This dataset is released under the Apache 2.0 License.
Related Models
- High-Accuracy Email Classifier - The CNN+GRU model trained on this dataset
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