--- license: unknown language: - tr metrics: - accuracy - f1 - precision - recall tags: - hotel - review - turkish - electra - sentiment --- ### Model Info This model was developed/finetuned for hotel review task for the Turkish Language. This model was finetuned via the Turkish hotel review dataset. - LABEL_0: positive review - LABEL_1: negative review ### Model Sources - **Dataset:** http://humirapps.cs.hacettepe.edu.tr/tsad.aspx - **Paper:** https://dl.acm.org/doi/10.1145/3557892 - **Demo-Coding [optional]:** https://github.com/anil1055/Turkish_Sentiment_Analysis-Hotel-and-Movie-Reviews/tree/main - **Finetuned from model [optional]:** https://huggingface.co/dbmdz/electra-base-turkish-cased-discriminator #### Preprocessing You must apply removing stopwords, stemming, or lemmatization process for Turkish. ### Results - auprc = 0.9980997402974433 - auroc = 0.9977912009512484 - eval_loss = 0.13716400672518045 - fn = 111 - fp = 24 - mcc = 0.9538776174134994 - tn = 2876 - tp = 2789 - Accuracy: %98.38 ## Citation **BibTeX:** *@article{10.1145/3557892, author = {Guven, Zekeriya Anil}, title = {The Comparison of Language Models with a Novel Text Filtering Approach for Turkish Sentiment Analysis}, year = {2022}, issue_date = {February 2023}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, volume = {22}, number = {2}, issn = {2375-4699}, url = {https://doi.org/10.1145/3557892}, doi = {10.1145/3557892}, journal = {ACM Trans. Asian Low-Resour. Lang. Inf. Process.}, month = {dec}, articleno = {55}, numpages = {16}, keywords = {Language model, sentiment analysis, social network, natural language processing, text classification, data analysis} }* **APA:** *Guven, Z. A. (2022). The Comparison of Language Models with a Novel Text Filtering Approach for Turkish Sentiment Analysis. ACM Transactions on Asian and Low-Resource Language Information Processing, 22(2), 1-16.*