README.md

metadata

language:
  - en
pretty_name: Text Quality Dataset
tags:
  - text-quality
  - classification
license: odc-by
task_categories:
  - text-classification

Text Quality Dataset

Overview

This dataset contains 100,000 rows sampled from the allenai/c4 English split, annotated with various text quality classifiers.

Methods

Classifiers used:

Label	Model	Method
fineweb2hq	agentlans/multilingual-e5-small-fineweb2hq-vs-c4-classifier	Logit difference
finewebedu	HuggingFaceFW/fineweb-edu-classifier	Raw logits
gneiss	ibm-granite/GneissWeb.Quality_annotator	FastText
nemo	nvidia/nemocurator-fineweb-nemotron-4-edu-classifier	Raw logits
nvidia	nvidia/quality-classifier-deberta	Logit difference
ultrafineweb	openbmb/Ultra-FineWeb-classifier	FastText
uvp	agentlans/bge-small-en-v1.5-ultrafineweb-vs-pile-classifier	Logit difference

For FastText-based classifiers, the classifiers' output probabilities were converted to logits log(p). The quality score for those classifiers were computed as the difference of logits between the high-quality and low-quality classes.

Overall score computation

• Scores from all classifiers were centreed and scaled.
• Principal Components Analysis (PCA) was applied.
• The first principal component (PC1) was normalized to z-scores (mean 0, standard deviation 1)
• The z-score is taken as the overall quality score.

For convenience, the dataset is split into an 80% training set and a 20% testing set.

Results

• The lower triangle shows pairwise density plots of classifier scores.

• The diagonal presents the distribution of each classifier's scores.

• The upper triangle displays correlations between pairs of classifiers.

• The classifiers' scores show moderate to strong correlations, except for the Nvidia classifier, which is less correlated.

• The custom-trained classifiers often give bimodal distributions instead of smoothly varying values.

• Despite the above, the overall score correlates well with each individual classifier's quality score.

License

This dataset is licensed under the Open Data Commons Attribution License (ODC-BY).