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metadata
license: other
task_categories:
  - text-classification
language:
  - en
  - ja
tags:
  - code
size_categories:
  - 1K<n<10K

Dataset overview

This dataset identifies whether a GitHub repository description pertains to Japanese natural language processing (NLP). The labels are categorized as "Relevant (1)" and "Not Relevant (0)".

Problem Setting:

  • Training Data: Repository descriptions from before 2022
  • Test Data: Repository descriptions from 2023
  • Objective: To detect repositories related to Japanese NLP

Data Collection:

  • Positive Examples: Repositories listed in "awesome-japanese-nlp-resources" as of September 9, 2023
  • Negative Examples: Collected from the GitHub API and visually confirmed
  • Note: The annotation process is subjective

Dataset Features:

  • Subjective labeling
  • Mixed English and Japanese descriptions
  • Imbalanced label distribution

These dataset features mirror real-world challenges and are ideal for evaluating models. Based on GitHub's terms of service, please use this dataset for research purposes only.

How to use this dataset

How to load in Python.

from datasets import load_dataset

dataset = load_dataset("taishi-i/awesome-japanese-nlp-classification-dataset")

Details of the dataset.

DatasetDict({
    train: Dataset({
        features: ['label', 'text', 'url', 'created_at'],
        num_rows: 5496
    })
    validation: Dataset({
        features: ['label', 'text', 'url', 'created_at'],
        num_rows: 400
    })
    test: Dataset({
        features: ['label', 'text', 'url', 'created_at'],
        num_rows: 856
    })
})

Baseline

Baseline trained with bert-base-multilingual-cased. Please use the baseline model from here. The F1-score for label 1 is important for this task.

Label Precision Recall F1-Score Support
0 0.98 0.99 0.98 796
1 0.79 0.70 0.74 60
Accuracy 0.97 856
Macro Avg 0.89 0.84 0.86 856
Weighted Avg 0.96 0.97 0.97 856

Dataset stats

Label distribution:

Dataset Label 0 (%) Label 1 (%)
Train 92.59 7.41
Validation 95.75 4.25
Test 92.99 7.01

Relevant sample:

{
    "label": 1,
    "text": "JGLUE: Japanese General Language Understanding Evaluation for huggingface datasets",
    "url": "https://github.com/shunk031/huggingface-datasets_JGLUE",
    "created_at": "2023-02-25T04:33:03Z"
}

Not Relevant sample:

{
    "label": 0,
    "text": "Official repository of FaceLit: Neural 3D Relightable Faces (CVPR 2023)",
    "url": "https://github.com/apple/ml-facelit",
    "created_at": "2023-04-03T22:47:29Z"
}

Number of texts, average number of characters per text, minimum number of characters, maximum number of characters:

Dataset Text Count Average Length Min Length Max Length
Train 5496 58.05 2.0 609.0
Validation 400 54.33 8.0 226.0
Test 856 58.85 3.0 341.0

Proportion of text languages:

Dataset English (%) Japanese (%)
Train 89.34 10.66
Validation 82.00 18.00
Test 83.18 16.82

Time range:

Dataset Start Date End Date
Train 2008-02-11 22:55:26+00:00 2022-09-30 19:45:09+00:00
Validation 2022-10-01 06:02:56+00:00 2022-12-31 12:12:41+00:00
Test 2023-01-01 06:15:03+00:00 2023-08-21 15:30:53+00:00

License

We collect and publish this dataset under GitHub Acceptable Use Policies - 7. Information Usage Restrictions and GitHub Terms of Service - H. API Terms for research purposes. This dataset should be used solely for research verification purposes. Adhering to GitHub's regulations is mandatory.