metadata
library_name: transformers
tags:
- text-classification
- hate-speech-detection
- distilbert
- transformers
- pytorch
license: apache-2.0
datasets:
- cardiffnlp/tweet_eval
metrics:
- f1
Hate Speech Classifier — Fine-tuned DistilBERT
Model Description
A DistilBERT model fine-tuned for binary hate speech detection on the
TweetEval hate speech dataset.
Classifies text as hate (1) or non-hate (0).
- Model type: Text Classification (DistilBERT)
- Base model: distilbert-base-uncased
- Language: English
- Developed by: Sathwika Raj Bandaru
Training Details
- Dataset: cardiffnlp/tweet_eval (hate subset) — 9,000 train / 1,000 validation / 2,970 test
- Epochs: 3
- Batch size: 16
- Max sequence length: 128
Evaluation Results
| Split | F1 (weighted) |
|---|---|
| Validation | 0.771 |
| Test | 0.376 |
How to Use
from transformers import pipeline
classifier = pipeline("text-classification",
model="sathwika01/hate-speech-classifier")
classifier("This is an example text")
Intended Use
Research and educational purposes — detecting hateful content in social media text.