Arabic word2vec embeddings trained on OpenSubtitles Part 1

This dataset contains the subs2vec embeddings for Arabic, as presented in https://zenodo.org/records/17243814. The embeddings were trained on large-scale subtitle corpora and represent semantic vector spaces derived from naturalistic language use in films and television from the OpenSubtitles 2018 datasets: https://opus.nlpl.eu/OpenSubtitles/corpus/version/OpenSubtitles. 

For this language, we provide all embedding variants explored in the study. Specifically, the dataset includes vectors generated under different combinations of:

• Dimensionality: multiple vector sizes (e.g., 100, 200, 300, …)
• Window size: varying context windows (e.g., 2, 5, 10, …)
• Each file corresponds to a unique configuration (dimension × window size). 

Each file contains the vocabulary for that language (column 1) and then the embedding values (columns 2 through dimension size + 1). 

If you use this dataset, please cite:

• Manuscript: https://doi.org/10.5281/zenodo.17243812
• Data: This Zenodo dataset (using the DOI provided here)