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---
language:
- id
dataset_info:
features:
- name: id
dtype: string
- name: url
dtype: string
- name: title
dtype: string
- name: text
dtype: string
- name: word_count
dtype: int64
splits:
- name: unfiltered
num_bytes: 361624744
num_examples: 157259
- name: filtered
num_bytes: 145352179.80208445
num_examples: 63209
download_size: 267272223
dataset_size: 506976923.80208445
configs:
- config_name: default
data_files:
- split: unfiltered
path: data/unfiltered-*
- split: filtered
path: data/filtered-*
---
Literally the title. It is processed from [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia). Only entries that contain the case-insensitive string 'Indonesia' is included. Now, you can use this to train a model on information about Indonesia written in Indonesian.
Additional filtering was done to remove entries that are either too short or too long.
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Dataset Statistics</title>
<style>
table {
width: 100%;
border-collapse: collapse;
}
th, td {
border: 1px solid black;
padding: 8px;
text-align: left;
}
th {
background-color: #f2f2f2;
}
</style>
</head>
<body>
<table>
<thead>
<tr>
<th>Split</th>
<th>Total Word Count</th>
<th>Mean Word Count</th>
<th>Standard Deviation of Word Count</th>
<th>Median Word Count</th>
<th>Dataset Length</th>
<th>Min Word Count</th>
<th>Max Word Count</th>
</tr>
</thead>
<tbody>
<tr>
<td>Unfiltered</td>
<td>47,039,325</td>
<td>299.12</td>
<td>717.74</td>
<td>98</td>
<td>157,259</td>
<td>3</td>
<td>95,967</td>
</tr>
<tr>
<td>Filtered</td>
<td>18,104,407</td>
<td>286.42</td>
<td>160.35</td>
<td>239</td>
<td>63,209</td>
<td>98</td>
<td>717</td>
</tr>
</tbody>
</table>
</body>
</html>
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