AIbase
EN
Home
Learn Hf Food Not Food Text Classifier Distilbert Base Uncased
L

Learn Hf Food Not Food Text Classifier Distilbert Base Uncased

Developed by karenwky
A fine-tuned DistilBERT-base-uncased food/non-food text classifier achieving 100% accuracy on the evaluation set
Text Classification
Transformers
Open Source License:Apache-2.0#Food Text Classification#High Accuracy#Lightweight BERT
Downloads 58
Release Time : 4/18/2025

Model Overview

This model is a binary text classifier designed to determine whether text content is related to food. Based on the lightweight DistilBERT architecture, it is suitable for fast and efficient text classification tasks.

Model Features

High Accuracy
Achieves 100% classification accuracy on the evaluation set
Lightweight and Efficient
Based on the DistilBERT architecture, it is 40% smaller than standard BERT models while retaining 97% of the performance
Fast Training
Requires only 10 training epochs to reach optimal performance

Model Capabilities

Text Classification
Food-Related Text Recognition
Short Text Analysis

Use Cases

Content Classification
Social Media Content Filtering
Automatically identifies food-related content in social media
100% accuracy
Menu Text Recognition
Extracts food-related descriptions from mixed text
E-Commerce
Product Categorization
Automatically classifies product descriptions into food or non-food categories
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
EnglishįŽ€äŊ“中文įšéĢ”中文ãĢãģんご
Š 2025AIbase