Bart Base Finetuned Pubmed
This model is a fine-tuned version of facebook/bart-base on the pub_med_summarization_dataset, primarily designed for medical literature summarization tasks.
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Release Time : 3/2/2022
Model Overview
A sequence-to-sequence model based on the BART architecture, specifically fine-tuned for PubMed medical literature summarization tasks, capable of generating concise summaries from medical research documents.
Model Features
Medical Domain Optimization
Specially fine-tuned on PubMed medical literature data, outperforming general models in medical text summarization tasks.
Fixed-Length Output
Generates summaries with a fixed length of 20 tokens, suitable for standardized summary output requirements.
Efficient Training
Utilizes mixed-precision training and linear learning rate scheduling, achieving optimization within 5 epochs.
Model Capabilities
Medical text summarization generation
Sequence-to-sequence transformation
English text processing
Use Cases
Medical Research
Automatic Medical Literature Summarization
Generates concise summaries for medical research papers on PubMed
Achieved a Rouge1 score of 9.3963 on the test set
Rapid Research Browsing
Assists researchers in quickly understanding the core content of papers
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