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Bart Large Samsum

Developed by linydub
A dialogue summarization model fine-tuned based on BART-large architecture, trained on the SAMSum dataset, specifically optimized for dialogue text summarization
Downloads 670
Release Time : 3/2/2022

Model Overview

This model can automatically generate concise summaries from dialogue content, suitable for automated processing in scenarios such as customer service records and meeting minutes

Model Features

Efficient Dialogue Summarization
Specially optimized for dialogue scenarios, accurately capturing the core content of conversations
AzureML Training
Trained using Azure Machine Learning services with 8 NVIDIA V100 GPUs
Eco-friendly Computing
Training process carbon emissions only 0.0297 kg, monitored with CodeCarbon
Ready-to-use
Provides a simple HuggingFace pipeline interface for easy integration

Model Capabilities

Dialogue Text Understanding
Automatic Summary Generation
Multi-turn Dialogue Processing

Use Cases

Customer Service Automation
Customer Service Dialogue Summarization
Automatically generates summaries of core issues and solutions from customer service dialogues
ROUGE-L score 44.18
Meeting Minutes
Meeting Summary Generation
Automatically condenses multi-turn meeting discussions into key decision point summaries
Average summary length of around 30 words
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