GPT2-finetuned-cnn-summarization-v2 Open Source Model - Free and Accurate Text Summarization Generation

Home

Gpt2 Finetuned Cnn Summarization V2

Developed by gavin124

Text summarization generation model fine-tuned based on GPT-2

Text Generation

Transformers

Open Source License:MIT #News Summarization Generation #GPT2 Fine-tuning #Low-resource Training

Downloads 266

Release Time : 12/1/2022

Model Overview

This model is a text summarization generation model fine-tuned based on the GPT-2 architecture, specifically designed to generate concise summaries from input text.

Model Features

Fine-tuning Optimization

Fine-tuned on specific datasets based on the GPT-2 architecture, optimizing summarization capabilities.

Efficient Training

Trained with a relatively small batch size (1), suitable for resource-limited environments.

Linear Learning Rate Scheduling

Adopts a linear learning rate scheduling strategy to help stabilize the training process.

Model Capabilities

Text Summarization Generation

Natural Language Processing

Text Compression

Use Cases

News Processing

News Article Summarization

Automatically compress long news articles into brief summaries.

Content Management

Document Summarization

Generate executive summaries for long documents.

Training Loss	Epoch	Step	Validation Loss
2.1919	1.0	5742	2.1597
2.0192	2.0	11484	2.1627
1.9587	3.0	17226	2.1684

Featured Recommended AI Models

Empowering the Future, Your AI Solution Knowledge Base

English 简体中文繁體中文にほんご

Gpt2 Finetuned Cnn Summarization V2

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 gpt2-finetuned-cnn-summarization-v2

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

📄 License