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--- |
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license: unknown |
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datasets: |
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- anilguven/turkish_tweet_emotion_dataset |
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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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- multilingual |
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- turkish |
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- bert |
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- tweet |
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- emotion |
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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 tweet emotion detection task for the Turkish Language. This model was finetuned via tweet dataset. This dataset contains 5 classes: angry, happy, sad, surprised and afraid. |
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- LABEL_0: angry |
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- LABEL_1: afraid |
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- LABEL_2: happy |
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- LABEL_3: surprised |
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- LABEL_4: sad |
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### Model Sources |
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<!-- Provide the basic links for the model. --> |
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- **Dataset:** https://huggingface.co/datasets/anilguven/turkish_tweet_emotion_dataset |
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- **Paper:** https://ieeexplore.ieee.org/document/9559014 |
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- **Demo-Coding [optional]:** https://github.com/anil1055/Turkish_tweet_emotion_analysis_with_language_models |
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- **Finetuned from model [optional]:** https://huggingface.co/bert-base-multilingual-uncased |
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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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- eval_loss = 0.5407382257189601 |
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- mcc = 0.7682691555667568 |
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- Accuracy: %81.37 |
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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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*@INPROCEEDINGS{9559014, |
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author={Guven, Zekeriya Anil}, |
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booktitle={2021 6th International Conference on Computer Science and Engineering (UBMK)}, |
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title={Comparison of BERT Models and Machine Learning Methods for Sentiment Analysis on Turkish Tweets}, |
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year={2021}, |
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volume={}, |
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number={}, |
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pages={98-101}, |
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keywords={Computer science;Sentiment analysis;Analytical models;Social networking (online);Computational modeling;Bit error rate;Random forests;Sentiment Analysis;BERT;Machine Learning;Text Classification;Tweet Analysis.}, |
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doi={10.1109/UBMK52708.2021.9559014}}* |
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**APA:** |
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*Guven, Z. A. (2021, September). Comparison of BERT models and machine learning methods for sentiment analysis on Turkish tweets. In 2021 6th International Conference on Computer Science and Engineering (UBMK) (pp. 98-101). IEEE.* |
