---
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]