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--- |
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language: "tr" |
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tags: |
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- sentiment |
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- twitter |
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- turkish |
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--- |
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This Turkish Sentiment Analysis model is a fine-tuned checkpoint of pretrained [BERTurk model 128k uncased](https://huggingface.co/dbmdz/bert-base-turkish-128k-uncased) with [BounTi dataset](https://ieeexplore.ieee.org/document/9477814). |
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## Usage in Hugging Face Pipeline |
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``` |
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from transformers import pipeline |
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bounti = pipeline("sentiment-analysis",model="akoksal/bounti") |
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print(bounti("Bu yemeği pek sevmedim")) |
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>> [{'label': 'negative', 'score': 0.8012508153915405}] |
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``` |
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## Results |
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The scores of the finetuned model with BERTurk: |
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||Accuracy|Precision|Recall|F1| |
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|-------------|:---------:|:---------:|:------:|:-----:| |
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|Validation|0.745|0.706|0.730|0.715| |
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|Test|0.723|0.692|0.729|0.701| |
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## Dataset |
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You can find the dataset in [our Github repo](https://github.com/boun-tabi/BounTi-Turkish-Sentiment-Analysis) with the training, validation, and test splits. |
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Due to Twitter copyright, we cannot release the full text of the tweets. We share the tweet IDs, and the full text can be downloaded through official Twitter API. |
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| | Training | Validation | Test | |
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|----------|:--------:|:----------:|:----:| |
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| Positive | 1691 | 188 | 469 | |
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| Neutral | 3034 | 338 | 843 | |
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| Negative | 1008 | 113 | 280 | |
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| Total | 5733 | 639 | 1592 | |
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## Citation |
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You can cite the following paper if you use our work: |
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``` |
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@INPROCEEDINGS{BounTi, |
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author={Köksal, Abdullatif and Özgür, Arzucan}, |
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booktitle={2021 29th Signal Processing and Communications Applications Conference (SIU)}, |
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title={Twitter Dataset and Evaluation of Transformers for Turkish Sentiment Analysis}, |
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year={2021}, |
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volume={}, |
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number={} |
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} |
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``` |
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--- |
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