t5-small_cnn-daily-mail

ndtran/t5-small_cnn-daily-mail

t5-small_cnn-daily-mail is a machine learning model from ndtran. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.

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At a glance

Library: transformers
Model type: t5
Access: Public
Created: Jun 28, 2023
Updated: Jul 22, 2023
SHA: c38140a8

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ndtran/t5-small_cnn-daily-mails

Model card

From the Hugging Face model README

T5-Small - Text summarization

Task description

We are focusing on Abstractive Text Summarization. Briefly, the input of the task is a text paragraph and output is a summarization of the input which is similar to the input from its meaning. Compared to another approach (Extractive Text Summarization), Abstractive Text Summarization is outstanding in the output quality.

Dataset

The model was finetuned on CNN/DailyMail. That is an English-language dataset containing just over 300k unique news articles as written by journalists at CNN and the Daily Mail. The current version supports both extractive and abstractive summarization, though the original version was created for machine reading and comprehension and abstractive question answering.

Hyper-parameters

Parameter	Value
No. Epoch	3
Learning rate	1e-5 (First two epochs), 5e-6 (Last epoch)
Optimizer	AdamW
Layers	Full

Evaluations

All of those metrics are from the evaluation of the finetuned model on the test-set of CNN/DailyMail.

Metrics	Recall	Precision	F1-Score
Rouge 1	0.38	0.42	0.39
Rouge 2	0.16	0.18	0.17
Rouge L	0.27	0.3	0.27
Rouge L-Sum	0.27	0.3	0.27

license: apache-2.0 datasets:

cnn_dailymail language:
en metrics:
rouge library_name: transformers pipeline_tag: summarization

Library: transformers
Type: t5
Created: Jun 28, 2023
Updated: Jul 22, 2023