HebrewSentiment + leaderboard
Browse files- .gitattributes +2 -5
- HebSentiment_test.jsonl +0 -0
- HebSentiment_train.jsonl +3 -0
- HebSentiment_val.jsonl +0 -0
- README.md +71 -0
- hebrew-llm-leaderboard.zip +3 -0
- source.txt +1 -0
.gitattributes
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HebSentiment_test.jsonl
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HebSentiment_train.jsonl
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version https://git-lfs.github.com/spec/v1
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oid sha256:63cf39364c48fc0734c47313b3e2c84e4d8f60d0aaf8af13ff66d334434f2141
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HebSentiment_val.jsonl
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README.md
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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]
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hebrew-llm-leaderboard.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:cddcc17bc10fae641375b07f610e648afcb2096487c106262939369fdd98ee5b
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size 532193
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source.txt
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https://huggingface.co/datasets/HebArabNlpProject/HebrewSentiment
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