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--- |
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license: mit |
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--- |
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# Model description |
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This space contains the static cbow word2vec models along with their embedding matrices, trained on: |
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- 20,000 Greek news articles from the [GreekNews-20k dataset](https://huggingface.co/datasets/katrjohn/GreekNews-20k) |
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- 70,000 Greek news articles from the [News Articles in Greek dataset](https://www.kaggle.com/datasets/kpittos/news-articles) |
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- 93,000 Greek Wikipedia articles from the [IMISLab GreekWikipedia dataset](https://huggingface.co/datasets/IMISLab/GreekWikipedia) |
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- 9,000 aritcles from the [CGL Modern Greek Texts Corpora: newspaper corpus "Ta Nea"](https://inventory.clarin.gr/corpus/910) |
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## Hyperparameters |
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The following hyperparameters were used to train the word2vec models |
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- window=5 |
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- sg=0(CBOWmode) |
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- cbow_mean=1 |
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- workers=8 |
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- negative=10 |
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- sample=1e-4 |
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- epochs=50 |
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### Model performance |
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To benchmark these embeddings we reported our BiLSTMs performance on joint ner and classification on the [GreekNews-20k dataset](https://huggingface.co/datasets/katrjohn/GreekNews-20k) along with the WordSim353's Pearson/Spearman correlations. |
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|Sentences|Vocabulary|Dimension|min_count|OOV|WS-353 Pearson|WS-353 Similarity|NER MicroF1%|Class Acc%| Total model parameters (M)| |
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|---------|---------|---------|---------|---------|---------|---------|---------|---------|---------| |
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|4564417|94865|128|44|42.4|0.42|0.40|85|76|13.7| |
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|4564417|140631|72|27|36.2|0.39|0.39|84|76|11.9| |
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#### Author |
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This model has been released along side with the article: Named Entity Recognition and News Article Classification: A Lightweight Approach. |
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To use this model please cite the following: |
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``` |
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@ARTICLE{11148234, |
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author={Katranis, Ioannis and Troussas, Christos and Krouska, Akrivi and Mylonas, Phivos and Sgouropoulou, Cleo}, |
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journal={IEEE Access}, |
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title={Named Entity Recognition and News Article Classification: A Lightweight Approach}, |
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year={2025}, |
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volume={13}, |
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number={}, |
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pages={155031-155046}, |
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keywords={Accuracy;Transformers;Pipelines;Named entity recognition;Computational modeling;Vocabulary;Tagging;Real-time systems;Benchmark testing;Training;Distilled transformer;edge-deployable model;multiclass news-topic classification;named entity recognition}, |
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doi={10.1109/ACCESS.2025.3605709}} |
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``` |
