afrizalha/wikipedia-Only-Indo-Articles-About-Indo
Literally the title. It is processed from 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. Dataset Statistics Split Total Word Count Mean Word Count… See the full description on the dataset page: https://huggingface.co/datasets/afrizalha/wikipedia-Only-Indo-Articles-About-Indo.
Literally the title. It is processed from 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>