aliffatulmf/deberta-v3-xsmall-anti-judol

Anti-Judol DeBERTa: Online Gambling Text Classification Model

Model Description

This model is a fine-tuned version of microsoft/deberta-v3-xsmall specifically designed for detecting and classifying online gambling-related content in Indonesian text. The model helps identify potentially harmful gambling content to support digital safety initiatives and content moderation efforts. It can distinguish between gambling-related and non-gambling text with high accuracy, making it valuable for automated content filtering systems.

Intended Uses

• Content moderation for social media platforms
• Automated detection of gambling advertisements
• Educational content filtering
• Digital safety applications
• Research on harmful content detection

Data

The model was trained on a curated dataset of Indonesian text samples containing both gambling-related and non-gambling content. The dataset includes various types of gambling content such as online casino advertisements, sports betting promotions, lottery schemes, and gambling-related discussions, balanced with legitimate content from news, social media, and educational sources.

Training

Step	Training Loss	Validation Loss	F1
50	0.676000	0.598374	0.806867
100	0.439700	0.275495	0.911765
150	0.240300	0.161314	0.950226
200	0.135600	0.130217	0.966767
250	0.120000	0.115214	0.971168
300	0.098600	0.114574	0.975758
350	0.071900	0.111686	0.978788

Ethical Considerations

This model is developed to support digital safety and harm reduction efforts. It should be used responsibly and in compliance with laws and regulations.