metadata
language: en
license: apache-2.0
tags:
- bart
- seq2seq
- summarization
datasets:
- samsum
widget:
- text: >
Jeff: Can I train a 🤗 Transformers model on Amazon SageMaker?
Philipp: Sure you can use the new Hugging Face Deep Learning Container.
Jeff: ok.
Jeff: and how can I get started?
Jeff: where can I find documentation?
Philipp: ok, ok you can find everything here.
https://huggingface.co/blog/the-partnership-amazon-sagemaker-and-hugging-face
model-index:
- name: bart-base-samsum
results:
- task:
type: abstractive-text-summarization
name: Abstractive Text Summarization
dataset:
name: >-
SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive
Summarization
type: samsum
metrics:
- type: rouge-1
value: 46.6619
name: Validation ROUGE-1
- type: rouge-2
value: 23.3285
name: Validation ROUGE-2
- type: rouge-l
value: 39.4811
name: Validation ROUGE-L
- type: rouge-1
value: 44.9932
name: Test ROUGE-1
- type: rouge-2
value: 21.7286
name: Test ROUGE-2
- type: rouge-l
value: 38.1921
name: Test ROUGE-L
- task:
type: summarization
name: Summarization
dataset:
name: samsum
type: samsum
config: samsum
split: test
metrics:
- type: rouge
value: 45.0148
name: ROUGE-1
verified: true
verifyToken: >-
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- type: rouge
value: 21.6861
name: ROUGE-2
verified: true
verifyToken: >-
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- type: rouge
value: 38.1728
name: ROUGE-L
verified: true
verifyToken: >-
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- type: rouge
value: 41.2794
name: ROUGE-LSUM
verified: true
verifyToken: >-
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- type: loss
value: 1.597476601600647
name: loss
verified: true
verifyToken: >-
eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTBmYjJmZDhiYmJiMTcxODM5M2ZmMTBkZTcwYzM2NDFiMDJjNjJhOGMyNGQ3MGI1Y2UxZTBhNTBiMjFjZGZiNyIsInZlcnNpb24iOjF9.UdOhxHcBJGRM-kz46st_vVQR_-KWr9EtsaQnLvj7YjCzE6JqHA2LPXnDogpUQX96PISJj32XoK7jlj-2z-CGBQ
- type: gen_len
value: 17.6606
name: gen_len
verified: true
verifyToken: >-
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bart-base-samsum
This model was obtained by fine-tuning facebook/bart-base on Samsum dataset.
Usage
from transformers import pipeline
summarizer = pipeline("summarization", model="lidiya/bart-base-samsum")
conversation = '''Jeff: Can I train a 🤗 Transformers model on Amazon SageMaker?
Philipp: Sure you can use the new Hugging Face Deep Learning Container.
Jeff: ok.
Jeff: and how can I get started?
Jeff: where can I find documentation?
Philipp: ok, ok you can find everything here. https://huggingface.co/blog/the-partnership-amazon-sagemaker-and-hugging-face
'''
summarizer(conversation)
Training procedure
- Colab notebook: https://colab.research.google.com/drive/1RInRjLLso9E2HG_xjA6j8JO3zXzSCBRF?usp=sharing
Results
| key | value |
|---|---|
| eval_rouge1 | 46.6619 |
| eval_rouge2 | 23.3285 |
| eval_rougeL | 39.4811 |
| eval_rougeLsum | 43.0482 |
| test_rouge1 | 44.9932 |
| test_rouge2 | 21.7286 |
| test_rougeL | 38.1921 |
| test_rougeLsum | 41.2672 |