disaster-tweet-classifier

mahmad932/disaster-tweet-classifier

disaster-tweet-classifier is a text classification model from mahmad932. Use it when you need a label for a piece of text. It is set up for transformers.

This model classifies whether a tweet is related to a real disaster or not using the DistilBERT transformer model. It was fine-tuned on the Kaggle "Natural Language Processing with Disaster Tweets" dataset.

Downloads · 30 days

4% of all-time downloads

All-time downloads

Public

Parameters

67M

536 MB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors268 MB · 100%

At a glance

Task: Text Classification
Library: transformers
Model type: distilbert
Access: Public
Created: Jul 25, 2026
Updated: Aug 3, 2026
SHA: fcd80cdc

Try a prompt

Model card

From the Hugging Face model README

Disaster Tweet Classification using DistilBERT

Model Description

Dataset

Dataset: Natural Language Processing with Disaster Tweets (Kaggle)

Labels:

0 = Not Disaster
1 = Disaster

Model

Base Model: distilbert-base-uncased
Framework: Hugging Face Transformers
Task: Binary Text Classification

Training Details

Epochs: 3
Learning Rate: 2e-5
Batch Size: 16
Optimizer: AdamW

Evaluation Results

Metric	Score
Accuracy	82.52%
Precision	82.52%
Recall	82.52%
F1-Score	82.39%

Example

Input:

A massive earthquake destroyed several buildings.

Prediction:

Disaster

Limitations

The model may misclassify sarcastic or ambiguous tweets.
Performance depends on the quality of the input text.

Intended Use

This model is intended for educational purposes and disaster tweet classification research.

Author

Muhammad Ahmad BS Computer Science

Task: Text Classification
Library: transformers
Type: distilbert
Created: Jul 25, 2026
Updated: Aug 3, 2026