---
language:
- id
- ace
- ban
- bjn
- bug
- jav
- mad
- min
- sun
- bbc
- eng
library_name: transformers
pipeline_tag: text-classification
tags:
- text-classification
- hate-speech-detection
- abusive-language-detection
- multilabel-classification
- indonesian
- multilingual
- social-media
- natural-language-processing
- xlm-roberta
license: apache-2.0
metrics:
- accuracy
- f1
base_model:
- FacebookAI/xlm-roberta-base
---

# Hate Speech & Abusive Language Detection (Multilabel)  
**Multilingual Indonesian & English — XLM-RoBERTa**

This repository provides a fine-tuned **XLM-RoBERTa** model for **MULTILABEL HATE CONTENT DETECTION** in social media text.  
The model is designed to identify **Hate Speech** and **Abusive Language** simultaneously across **Indonesian**, **regional Indonesian languages**, and **English**, particularly in noisy and informal online conversations.

---

## 🚀 Highlights

- Multilabel classification: **Hate Speech** & **Abusive Language**
- Supports overlapping labels in a single text
- Multilingual (Indonesia + English)
- Robust on informal and user-generated content
- Ready-to-use with Hugging Face `pipeline`
- Suitable for content moderation and safety systems

---

## 🌍 Supported Languages

- 🇮🇩 Bahasa Indonesia  
- Bahasa Melayu  
- Indonesian regional languages (Aceh, Banjar, Bugis, Jawa, Madura, Minang, Sunda, dll.)  
- 🇬🇧 English  

---

## 📊 Model Performance

> Performance metrics are reported on a held-out validation set.

| Metric          | Score  |
|-----------------|--------|
| Precision       | 0.9249 |
| Recal           | 0.9300 |
| F1 (Macro)      | 0.9274 |
| F1 (Weighted)   | 0.9269 |
| Training Loss   | 0.1181 |
| Validation Loss | 0.2070 |

*(Exact scores may vary depending on evaluation split and threshold.)*

---

## ⚙️ Usage

### Installation
```bash
pip install transformers torch
````

### Single Prediction

```python
from transformers import pipeline

classifier = pipeline(
    task="text-classification",
    model="nahiar/hatespeech-abusive-xlm-roberta-v1",
    return_all_scores=True
)

result = classifier("Dasar bodoh, otak udang!")
print(result)
```

**Output**

```text
[
  {'label': 'HATESPEECH', 'score': 0.9123},
  {'label': 'ABUSIVE', 'score': 0.9841}
]
```

> Because this is a **multilabel model**, more than one label can be active for a single input.

---

## 🏷️ Label Definitions

```text
HATESPEECH → Content that attacks or demeans a group based on identity
ABUSIVE    → Insulting, offensive, or aggressive language without protected targets
```

---

## 📦 Batch Inference

```python
texts = [
    "Dasar kaum ini selalu bikin rusuh",
    "Kamu memang bodoh dan tidak berguna",
    "Saya tidak setuju dengan pendapat kamu"
]

results = classifier(texts)

for text, preds in zip(texts, results):
    labels = [(p["label"], round(p["score"], 4)) for p in preds]
    print(text, "→", labels)
```

---

## 🏗️ Training Configuration

| Parameter         | Value                     |
| ----------------- | ------------------------- |
| Base Model        | xlm-roberta-base          |
| Task Type         | Multilabel Classification |
| Training Strategy | Fine-tuning               |
| Epochs            | Multiple                  |
| Learning Rate     | 2e-5                      |
| Batch Size        | 16                        |
| Training Date     | 2025-12-18                |

---

## 🎯 Intended Use

* Hate speech & abusive language moderation
* Content safety and compliance systems
* Social media monitoring dashboards
* Pre-filtering before sentiment or topic analysis

---

## ⚠️ Limitations

* Limited to **Hate Speech** and **Abusive Language** labels
* Does not identify specific hate targets or protected attributes
* Context-dependent sarcasm may be misclassified
* Not suitable for legal or policy enforcement without human review

---

## 📜 License

This model is released under the **Apache License 2.0**
Free for research and commercial use.

---

## 📚 Citation

```bibtex
@misc{djunaedi2025hatespeech_multilabel,
  author    = {Raihan Hidayatulloh Djunaedi},
  title     = {Multilabel Hate Speech and Abusive Language Detection for Social Media Text},
  year      = {2025},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/nahiar/hatespeech-xlmr-v4}
}
```

---

## 🙌 Acknowledgements

* Hugging Face Transformers
* Facebook AI Research — XLM-RoBERTa