---
base_model: FacebookAI/roberta-large
library_name: peft
tags:
- base_model:adapter:FacebookAI/roberta-large
- lora
- transformers
- hate-speech
- text-classification
- nlp
- binary-classification
- roberta-large
language:
- en
pipeline_tag: text-classification
license: apache-2.0
title: Hate Speech RoBERTa
sdk: gradio
emoji: 🔥
colorFrom: yellow
colorTo: red
pinned: true
short_description: Hate Speech Detection in English using RoBERTa
sdk_version: 6.6.0
---

Copyright 2026 Harikrishna Srinivasan

# RoBERTa-Large for Hate Speech Classifier (LoRA)

## Summary

This model is a **LoRA fine-tuned RoBERTa-Large uncased** model for **binary hate speech classification** (Hate / Not Hate).
It is optimized for efficient fine-tuning using **Low-Rank Adaptation (LoRA)** via the Hugging Face PEFT library.

---

## Details

### Description

- **Developed by:** Harikrishna Srinivasan
- **Model type:** Fine-Tuned (LoRA) RoBERTa-Large uncased
- **Task:** Binary text classification
- **Language(s):** English
- **License:** Apache 2.0
- **Finetuned from:** `FacebookAI/roberta-large`

This model uses Low-Rank Adaptation (LoRA) to fine-tune only a subset of parameters, enabling efficient training while preserving the strong contextual representation capabilities of RoBERTa-Large.

---

## Sources

- **Base Model:** https://huggingface.co/FacebookAI/roberta-large
- **Training Framework:** Hugging Face Transformers + PEFT
- **Repository:** Not publicly linked (local / academic project)

---

## Uses

### Direct Use

This model can be used directly for:

- Hate speech detection in English text
- Moderation pipelines
- Dataset auditing
- Research on implicit hate and biased language
- Pre-filtering content for human moderation

---

## Dataset Citation

```bibtex
@misc{srinivasan2026hatespeech,
  author       = {Harikrishna Srinivasan},
  title        = {Hate-Speech Dataset (Refined and Cleaned Version)},
  year         = {2026},
  publisher    = {Hugging Face Datasets},
  howpublished = {https://huggingface.co/datasets/Harikrishna-Srinivasan/Hate-Speech}
}
```

Example:
```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification

MODEL_NAME = "Harikrishna-Srinivasan/Hate-Speech-RoBERTa"

model = PeftModel.from_pretrained(MODEL_NAME)
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, use_fast=True)
```