toolevalxm/MySuperDataset-TestRepo

MySuperDataset

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1. Introduction

MySuperDataset is a comprehensive multi-domain text corpus designed for training and evaluating language models. This dataset has been carefully curated through multiple iterations to ensure high quality, diversity, and representativeness across various domains including science, technology, arts, and everyday conversations.

The dataset includes over 10 million samples spanning 15 different quality metrics. Through our iterative curation process, we have significantly improved data quality while maintaining diversity. The latest version shows a 25% improvement in overall quality scores compared to the initial release.

Our curation process focuses on removing harmful content, deduplication, and ensuring balanced representation across topics and demographics.

2. Quality Metrics

Comprehensive Quality Assessment

	Metric	Baseline	Version1	Version2	MySuperDataset
Content Quality	Factual Accuracy	0.720	0.745	0.768	0.829
	Grammar Score	0.850	0.872	0.890	0.879
	Coherence	0.780	0.795	0.812	0.873
Diversity Metrics	Topic Coverage	0.650	0.680	0.705	0.773
	Vocabulary Richness	0.720	0.738	0.755	0.806
	Style Variety	0.680	0.702	0.720	0.768
	Source Diversity	0.590	0.625	0.658	0.743
Safety & Ethics	Toxicity Filter	0.920	0.935	0.948	0.963
	Bias Mitigation	0.780	0.805	0.825	0.847
	Privacy Protection	0.850	0.872	0.888	0.907
	Copyright Compliance	0.910	0.925	0.938	0.960
Technical Quality	Deduplication Rate	0.880	0.905	0.922	0.935
	Format Consistency	0.820	0.845	0.865	0.880
	Encoding Quality	0.950	0.962	0.970	0.970
	Metadata Completeness	0.750	0.778	0.800	0.828

Overall Quality Summary

MySuperDataset demonstrates exceptional quality across all evaluated metrics, with particularly strong performance in safety filtering and content quality dimensions.

3. Dataset Access & API

We provide direct dataset access through our platform and API endpoints. Please visit our official website for documentation and access tokens.

4. How to Use

Please refer to our documentation for detailed usage instructions.

Loading the Dataset

from datasets import load_dataset

dataset = load_dataset("MySuperDataset")

Data Format

Each sample contains:

• text: The main text content
• domain: The topic domain classification
• quality_score: Pre-computed quality score
• source: Original data source identifier

Recommended Usage

We recommend filtering samples with quality_score >= 0.8 for training language models.

5. License

This dataset is released under the Apache 2.0 License. Commercial use is permitted with proper attribution.

6. Contact

For questions or issues, please open a GitHub issue or contact us at data@mysuperdataset.ai.