If you want to use the model you should try a newer fine-tuned FLAN-T5 version
philschmid/flan-t5-base-samsum
out socring the BART version with
+6
on
ROGUE1
achieving
47.24
.
from transformers import pipeline
summarizer = pipeline("summarization", model="philschmid/bart-large-cnn-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)
Results
key
value
eval_rouge1
42.621
eval_rouge2
21.9825
eval_rougeL
33.034
eval_rougeLsum
39.6783
test_rouge1
41.3174
test_rouge2
20.8716
test_rougeL
32.1337
test_rougeLsum
38.4149
Runs of philschmid bart-large-cnn-samsum on huggingface.co
112.0K
Total runs
-1.8K
24-hour runs
-3.8K
3-day runs
-8.0K
7-day runs
-9.3K
30-day runs
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