Model Info
This model was developed/finetuned for movie review task for the Turkish Language. This model was finetuned via the Turkish movie review dataset.
- LABEL_0: positive review
- LABEL_1: negative review
Model Sources
Preprocessing
You must apply removing stopwords, stemming, or lemmatization process for Turkish.
Results
- auprc = 0.9783265245768504
- auroc = 0.9786267839358107
- eval_loss = 0.332054428835344
- fn = 921
- fp = 1184
- mcc = 0.8424855995781335
- tn = 12166
- tp = 12429
- Accuracy: %92.00
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.
