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