readerbench/RoSummary-large

Model card for RoSummary-large

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language:

• ro

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RoSummary

This is a version of the RoGPT2 model trained on the AlephNews dataset for the summarization task. There are 3 trained versions, they are available on the HuggingFace Hub:

• base
• medium
• large

Evaluation on AlephNews

Model	Decode Method		BERTScore			ROUGE
		Precision	Recall	F1-Score	ROUGE-1	ROUGE-2	ROUGE-L
	Greedy	0.7335	0.7399	0.7358	0.3360	0.1862	0.3333
Base	Beam Search	0.7354	0.7468	0.7404	0.3480	0.1991	0.3416
	Top-p Sampling	0.7296	0.7299	0.7292	0.3058	0.1452	0.2951
	Greedy	0.7378	0.7401	0.7380	0.3422	0.1922	0.3394
Medium	Beam Search	0.7390	0.7493	0.7434	0.3546	0.2061	0.3467
	Top-p Sampling	0.7315	0.7285	0.7294	0.3042	0.1400	0.2921
	Greedy	0.7376	0.7424	0.7391	0.3414	0.1895	0.3355
Large	Beam Search	0.7394	0.7470	0.7424	0.3492	0.1995	0.3384
	Top-p Sampling	0.7311	0.7301	0.7299	0.3051	0.1418	0.2931

Acknowledgments

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Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC)