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metadata
license: unknown
language:
  - tr
metrics:
  - accuracy
  - f1
  - precision
  - recall
tags:
  - movie
  - review
  - sentiment
  - turkish
  - bert

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 = 0.9547155589592419
  • auroc = 0.9567033960358541
  • eval_loss = 0.4520341001172079
  • fn = 1368
  • fp = 1668
  • mcc = 0.7727794159832003
  • tn = 11682
  • tp = 11982
  • Accuracy: %92.11

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.