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--- |
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language: |
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- en |
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- hi |
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license: apache-2.0 |
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tags: |
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- hate-speech-detection |
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- reddit |
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- xlm-roberta |
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- hindi |
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- english |
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datasets: |
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- HASOC2019 |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: reddit-hate-speech-detector |
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results: |
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- task: |
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type: text-classification |
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metrics: |
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- type: accuracy |
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value: 0.8293 |
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- type: f1 |
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value: 0.8278 |
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--- |
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# Reddit Hate Speech Detector (Hindi + English) |
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This model detects hate speech in Reddit comments for both Hindi and English languages. |
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## Model Description |
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- **Base Model:** XLM-RoBERTa |
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- **Languages:** Hindi, English |
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- **Task:** Multi-task classification (hate speech detection + type + target) |
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- **Accuracy:** 82.93% |
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- **F1 Score:** 0.8278 |
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## Intended Use |
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This model is designed for: |
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- Content moderation on Reddit |
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- Automated hate speech detection |
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- Research purposes |
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⚠️ **Important:** This model should assist human moderators, not replace them. |
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## Usage |
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```python |
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import torch |
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from transformers import XLMRobertaTokenizer |
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# Load tokenizer |
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tokenizer = XLMRobertaTokenizer.from_pretrained('xlm-roberta-base') |
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# Your model loading code here |
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# (See inference script) |
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``` |
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## Training Data |
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- HASOC 2019 Hindi Dataset |
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- HASOC 2019 English Dataset |
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- Combined training with class balancing |
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## Limitations |
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- May have biases present in training data |
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- Requires context for accurate detection |
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- Cultural nuances may not be fully captured |
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## Ethical Considerations |
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- Should be used transparently |
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- Allow user appeals |
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- Regular monitoring for fairness |
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- Consider cultural context |
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