---
viewer: false
license:
- apache-2.0
language:
- en
---

**Model Summary**

In order to be able to reproduce GneissWeb, we provide here GneissWeb.Edu_classifier - an education category fastText classifier. This fastText model is used as part of the ensemble filter in GneissWeb to detect documents with education content.

Please refer to the [GneissWeb](https://huggingface.co/datasets/ibm-granite/GneissWeb) page for more details.

     **Developers**: IBM Research

     **Release Date**: Feb 21st, 2025

     **License**: Apache 2.0.


**Training Data**

The model is trained on 800k documents, labeled using the [WatsonNLP hierachical categorization](https://www.ibm.com/docs/en/watsonx/saas?topic=catalog-hierarchical-categorization). Please refer to [fastText text classification tutorial](https://fasttext.cc/docs/en/python-module.html) for details. 
Training data is selected as follows:

- *Positive documents*: 400k documents randomly sampled from the documents labeled with education category with a confidence score 0.95 and above.
- *Negative documents*: 400k documents randomly sampled from the documents labeled with any category other than science, education, medical, and technology categories with a confidence score of 0.95 and above.