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knkarthick
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meeting-summary-samsum

Summarization
Transformers
PyTorch
English
bart
text2text-generation
seq2seq
Eval Results
Inference Endpoints
Model card Files Community
2

bart-large-xsum-samsum

This model was obtained by fine-tuning facebook/bart-large-xsum on Samsum dataset.

Usage 

from transformers import pipeline
summarizer = pipeline("summarization", model="knkarthick/bart-large-xsum-samsum")
conversation = '''Hannah: Hey, do you have Betty's number?
Amanda: Lemme check
Amanda: Sorry, can't find it.
Amanda: Ask Larry
Amanda: He called her last time we were at the park together
Hannah: I don't know him well
Amanda: Don't be shy, he's very nice
Hannah: If you say so..
Hannah: I'd rather you texted him
Amanda: Just text him 🙂
Hannah: Urgh.. Alright
Hannah: Bye
Amanda: Bye bye                                       
'''
summarizer(conversation)
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Dataset used to train knkarthick/meeting-summary-samsum

Evaluation results

  • Validation ROUGE-1 on SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization
    self-reported
    54.392
  • Validation ROUGE-2 on SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization
    self-reported
    29.808
  • Validation ROUGE-L on SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization
    self-reported
    45.154
  • Test ROUGE-1 on SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization
    self-reported
    53.306
  • Test ROUGE-2 on SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization
    self-reported
    28.355
  • Test ROUGE-L on SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization
    self-reported
    44.095
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