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# Pemilu2024-BERT-Clickbait
Dataset from okezone, tempo, detik, and kompas

## Introduction
This project leverages a BERT model for analyzing Indonesian text data, focusing on the Pemilu 2024 elections headline news.
it is aimed to classify if a news headline is clickbait (Labeled as 1)

## Model Description
The BERT model used here is tailored for the Indonesian language.
It's configured to effectively handle election-specific datasets, providing insights into patterns and trends.

## File Contents
- `config.json`: Model configuration settings.
- `model.safetensors`: Serialized model file.
- `special_tokens_map.json`: Special tokens for the tokenizer.
- `tokenizer_config.json`: Configuration for text tokenization.
- `vocab.txt`: Vocabulary list used by the model.

## Supported Languages
- Indonesian (ID)

## Contributions and Acknowledgements
Thanks to all contributors and data sources that have made this project possible.
upstream task from https://huggingface.co/bert-base-uncased

## License
[Specify License Here]

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Please adjust the sections as needed, especially the "Usage Instructions" and "License" to fit the actual details of the project. For more information or to view the repository, visit [Hugging Face](https://huggingface.co/fajarkrisnajaya/Pemilu2024-BERT-Clickbait/tree/main).
{"language": ["id"], "library_name": "transformers"}
transformers safetensors bert text-classification id autotrain_compatible endpoints_compatible region:us