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--- |
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license: cc-by-4.0 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: train/data.jsonl |
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- split: test |
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path: test/test.jsonl |
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task_categories: |
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- text-classification |
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language: |
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- he |
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size_categories: |
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- 10K<n<100K |
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--- |
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# HebrewSentiment - A Sentiment-Analysis Dataset in Hebrew |
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## Summary |
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HebrewSentiment is a Hebrew dataset for the sentiment analysis task. |
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## Introduction |
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This dataset was constructed via [To Fill In]. |
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## Dataset Statistics |
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The table below shows the number of examples from each category in each of the splits: |
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| split | total | positive | negative | neutral | |
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|-------|----------|----------|----------|---------| |
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| train | 39,135 | 8,968 | 7,669 | 22,498 | |
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| test | 2,170 | 503 | 433 | 1,234 | |
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## Dataset Description |
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Each row in the dataset contains the following fields: |
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- **id**: A unique identifier for that training examples |
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- **text**: The textual content of the input sentence |
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- **tag_ids**: The label of the example (`Neutral`/`Positive`/`Negative`) |
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- **task_name**: [To fill in] |
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- **campaign_id**: [To fill in] |
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- **annotator_agreement_strength**: [To fill in] |
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- **survey_name**: [To fill in] |
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- **industry**: [To fill in] |
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- **type**: [To fill in] |
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## Models and Comparisons |
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In collaboration with [DICTA](https://dicta.org.il/) we trained a model on this dataset and are happy to release it to the public: [DictaBERT-Sentiment](https://huggingface.co/dicta-il/dictabert-sentiment). |
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In addition, we compared the performance of the model to the previous existing sentiment dataset - [Hebrew-Sentiment-Data from OnlpLab](https://github.com/OnlpLab/Hebrew-Sentiment-Data). |
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We fine-tuned [dictabert](https://huggingface.co/dicta-il/dictabert) 3 times - once on the OnlpLab dataset, once on this dataset, and once on both datasets together and the results can be seen in the table below: |
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| Training Corpus: | OnlpLab | | | | | HebrewSentiment| | | | | |
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|------------------|------|----------------|------|------|--------|--------------|------|------|---|---| |
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| | Accuracy | Macro F1 | F1 Positive | F1 Negative | F1 Neutral | Accuracy | Macro F1 | F1 Positive | F1 Negative | F1 Neutral | |
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| OnlpLab+HebrewSentiment | 87 | 61.7 | 93.2 | 74.6 | 17.4 | 83.9 | 82.7 | 79.8 | 81.8 | 86.4 | |
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| OnlpLab | 88.2 | 63.3 | 93.8 | 72.1 | 24 | 41.3 | 42.2 | 48.1 | 56.3 | 22.2 | |
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| HebrewSentiment | 69.9 | 51.7 | 82.2 | 62.9 | 10.2 | 84.4 | 83.2 | 81 | 82.1 | 86.6 | |
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## Contributors |
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[To fill in] |
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Contributors: [To fill in] |
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## Acknowledgments |
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We would like to express our gratitude to [To fill in] |
