---
language: en
tags:
- bart
- seq2seq
- summarization
license: apache-2.0
datasets:
- samsum
widget:
- text: "Hannah: Hey, do you have Betty's number?\nAmanda: Lemme check\nAmanda: Sorry,\
    \ can't find it.\nAmanda: Ask Larry\nAmanda: He called her last time we were at\
    \ the park together\nHannah: I don't know him well\nAmanda: Don't be shy, he's\
    \ very nice\nHannah: If you say so..\nHannah: I'd rather you texted him\nAmanda:\
    \ Just text him \U0001F642\nHannah: Urgh.. Alright\nHannah: Bye\nAmanda: Bye bye\n"
model-index:
- name: bart-large-xsum-samsum
  results:
  - task:
      name: Abstractive Text Summarization
      type: abstractive-text-summarization
    dataset:
      name: 'SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization'
      type: samsum
    metrics:
    - name: Validation ROUGE-1
      type: rouge-1
      value: 54.3921
    - name: Validation ROUGE-2
      type: rouge-2
      value: 29.8078
    - name: Validation ROUGE-L
      type: rouge-l
      value: 45.1543
    - name: Test ROUGE-1
      type: rouge-1
      value: 53.3059
    - name: Test ROUGE-2
      type: rouge-2
      value: 28.355
    - name: Test ROUGE-L
      type: rouge-l
      value: 44.0953
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: samsum
      type: samsum
      config: samsum
      split: train
    metrics:
    - name: ROUGE-1
      type: rouge
      value: 46.2492
      verified: true
    - name: ROUGE-2
      type: rouge
      value: 21.346
      verified: true
    - name: ROUGE-L
      type: rouge
      value: 37.2787
      verified: true
    - name: ROUGE-LSUM
      type: rouge
      value: 42.1317
      verified: true
    - name: loss
      type: loss
      value: 1.6859958171844482
      verified: true
    - name: gen_len
      type: gen_len
      value: 23.7103
      verified: true
---
## `bart-large-xsum-samsum`
This model was obtained by fine-tuning `facebook/bart-large-xsum` on [Samsum](https://huggingface.co/datasets/samsum) dataset.
## Usage
```python
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)
```