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This Turkish Sentiment Analysis model is a fine-tuned checkpoint of pretrained BERTurk model 128k uncased with BounTi dataset.

Usage in Hugging Face Pipeline

from transformers import pipeline
bounti = pipeline("sentiment-analysis",model="akoksal/bounti")
print(bounti("Bu yemeği pek sevmedim"))
>> [{'label': 'negative', 'score': 0.8012508153915405}]

Results

The scores of the finetuned model with BERTurk:

Accuracy Precision Recall F1
Validation 0.745 0.706 0.730 0.715
Test 0.723 0.692 0.729 0.701

Dataset

You can find the dataset in our Github repo with the training, validation, and test splits.

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.

Training Validation Test
Positive 1691 188 469
Neutral 3034 338 843
Negative 1008 113 280
Total 5733 639 1592

Citation

You can cite the following paper if you use our work:

@INPROCEEDINGS{BounTi,
  author={Köksal, Abdullatif and Özgür, Arzucan},
  booktitle={2021 29th Signal Processing and Communications Applications Conference (SIU)}, 
  title={Twitter Dataset and Evaluation of Transformers for Turkish Sentiment Analysis}, 
  year={2021},
  volume={},
  number={}
  }

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