| language |
tags |
license |
datasets |
widget |
model-index |
| en |
| bart |
| seq2seq |
| summarization |
|
apache-2.0 |
|
| text |
| 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
|
|
|
| name |
results |
| bart-large-xsum-samsum |
| task |
dataset |
metrics |
| name |
type |
| Abstractive Text Summarization |
abstractive-text-summarization |
|
| name |
type |
| SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization |
samsum |
|
| name |
type |
value |
| Validation ROGUE-1 |
rogue-1 |
54.3921 |
|
| name |
type |
value |
| Validation ROGUE-2 |
rogue-2 |
29.8078 |
|
| name |
type |
value |
| Validation ROGUE-L |
rogue-l |
45.1543 |
|
| name |
type |
value |
| Test ROGUE-1 |
rogue-1 |
53.3059 |
|
| name |
type |
value |
| Test ROGUE-2 |
rogue-2 |
28.355 |
|
| name |
type |
value |
| Test ROGUE-L |
rogue-l |
44.0953 |
|
|
|
|
|
|
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="lidiya/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)
Training procedure
Results
| key |
value |
| eval_rouge1 |
54.3921 |
| eval_rouge2 |
29.8078 |
| eval_rougeL |
45.1543 |
| eval_rougeLsum |
49.942 |
| test_rouge1 |
53.3059 |
| test_rouge2 |
28.355 |
| test_rougeL |
44.0953 |
| test_rougeLsum |
48.9246 |