File size: 2,103 Bytes
eec9f10 6ce5942 0d7c3d3 e384bc9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 |
---
license: unknown
language:
- tr
metrics:
- accuracy
- f1
- precision
- recall
tags:
- movie
- review
- turkish
- bert
- sentiment
---
### 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
<!-- Provide the basic links for the model. -->
- **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/distilbert-base-turkish-cased
#### 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
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**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.* |