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