Datasets:
File size: 4,748 Bytes
a2358dc b750b28 a2358dc b750b28 9dcc8a7 b750b28 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 |
---
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](https://github.com/taishi-i/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.
```python
from datasets import load_dataset
dataset = load_dataset("taishi-i/awesome-japanese-nlp-classification-dataset")
```
Details of the dataset.
```python
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](https://huggingface.co/bert-base-multilingual-cased).
Please use the baseline model from [here](https://huggingface.co/taishi-i/awesome-japanese-nlp-classification-model).
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:
```python
{
"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:
```python
{
"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](https://docs.github.com/en/site-policy/acceptable-use-policies/github-acceptable-use-policies#7-information-usage-restrictions) and [GitHub Terms of Service - H. API Terms](https://docs.github.com/en/site-policy/github-terms/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.
|