distilbert-topic-abstract-classification: An open-source text classification model - Free deployment to achieve topic abstract classification

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Distilbert Topic Abstract Classification

Developed by Eitanli

A text classification model fine-tuned based on distilbert-base-uncased for topic abstract classification tasks

Text Classification

Transformers

Open Source License:Apache-2.0 #Text Topic Classification #Lightweight BERT #Academic Abstract Processing

Downloads 43

Release Time : 10/11/2023

Model Overview

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset, primarily used for text classification tasks, with potential application scenarios including topic classification or abstract classification.

Model Features

Lightweight Model

Based on the DistilBERT architecture, smaller and faster than standard BERT models while maintaining good performance

Efficient Fine-tuning

Fine-tuned for specific tasks, suitable for topic and abstract classification applications

Model Capabilities

Text Classification

Topic Identification

Abstract Classification

Use Cases

Academic Research

Paper Abstract Classification

Classify academic paper abstracts to identify their disciplinary fields

Content Management

News Topic Classification

Classify news articles by topic for content organization and retrieval

Training Loss	Epoch	Step	Validation Loss
0.296	1.0	8496	0.2844
0.2436	2.0	16992	0.2743

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Distilbert Topic Abstract Classification

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 distilbert-topic-abstract-classification

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Training and evaluation data

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