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Datasets:
HebArabNlpProject
/
HebrewSentiment

Tasks:
Text Classification
Languages:
Hebrew
Size:
10K<n<100K
License:
Dataset card Files Community
1
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The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    FileNotFoundError
Message:      Couldn't find a dataset script at /src/services/worker/HebArabNlpProject/HebrewSentiment/HebrewSentiment.py or any data file in the same directory. Couldn't find 'HebArabNlpProject/HebrewSentiment' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/HebArabNlpProject/HebrewSentiment@fcc584d9f4e908b1eb78f22d8780389af368bdf4/train/data.jsonl' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.tar', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 79, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1906, in dataset_module_factory
                  raise FileNotFoundError(
              FileNotFoundError: Couldn't find a dataset script at /src/services/worker/HebArabNlpProject/HebrewSentiment/HebrewSentiment.py or any data file in the same directory. Couldn't find 'HebArabNlpProject/HebrewSentiment' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/HebArabNlpProject/HebrewSentiment@fcc584d9f4e908b1eb78f22d8780389af368bdf4/train/data.jsonl' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.tar', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']

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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 we trained a model on this dataset and are happy to release it to the public: DictaBERT-Sentiment.

In addition, we compared the performance of the model to the previous existing sentiment dataset - Hebrew-Sentiment-Data from OnlpLab. We fine-tuned 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]

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Models trained or fine-tuned on HebArabNlpProject/HebrewSentiment