BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
Paper
• 1910.13461 • Published
• 6
Bart model finetuned on xsum
docs: https://huggingface.co/transformers/model_doc/bart.html
finetuning: examples/seq2seq/ (as of Aug 20, 2020)
Metrics: ROUGE > 22 on xsum.
variants: search for distilbart
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Evaluation results
- ROUGE-1 on cnn_dailymailtest set self-reported25.270
- ROUGE-2 on cnn_dailymailtest set self-reported7.664
- ROUGE-L on cnn_dailymailtest set self-reported17.181
- ROUGE-LSUM on cnn_dailymailtest set self-reported21.793
- loss on cnn_dailymailtest set self-reported3.504
- gen_len on cnn_dailymailtest set self-reported27.446
- ROUGE-1 on xsumtest set self-reported45.453
- ROUGE-2 on xsumtest set self-reported22.346
- ROUGE-L on xsumtest set self-reported37.230
- ROUGE-LSUM on xsumtest set self-reported37.232
- loss on xsumtest set self-reported2.313
- gen_len on xsumtest set self-reported25.544
- ROUGE-1 on samsumself-reported24.785
- ROUGE-2 on samsumself-reported5.253
- ROUGE-L on samsumself-reported18.679
- ROUGE-LSUM on samsumself-reported20.629
- loss on samsumself-reported3.747
- gen_len on samsumself-reported23.121
- ROUGE-1 on samsumtest set self-reported24.916
- ROUGE-2 on samsumtest set self-reported5.584