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