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@@ -13,14 +13,14 @@ should probably proofread and complete it, then remove this comment. -->
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  # Overview
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- This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the allenai/mslr2022 ms2 dataset. We take up to the first 25 included studies for each example and concatenate them with the `"</s>"` token. Global attention is applied to the special start token `"<s>"` and each of the document seperator tokens `"</s>"`.
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  It achieves the following results on the evaluation set:
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  - Loss: 3.7602
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  - Rouge1 Fmeasure Mean: 28.5338
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  - Rouge2 Fmeasure Mean: 9.5060
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- - Rougel Fmeasure Mean: 20.9321
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- - Rougelsum Fmeasure Mean: 24.0998
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  - Bertscore Hashcode: microsoft/deberta-xlarge-mnli_L40_no-idf_version=0.3.11(hug_trans=4.21.0.dev0)-rescaled_fast-tokenizer
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  - Bertscore F1 Mean: 22.7619
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  - Seed: 42
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  # Overview
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+ This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the allenai/mslr2022 ms2 dataset. We take up to the first 25 included studies for each example and concatenate them with the `"</s>"` token. Global attention is applied to the special start token `"<s>"` and each of the document seperator tokens `"</s>"`. The model slightly outperforms the reported results in the original paper: [MS2: Multi-Document Summarization of Medical Studies](https://arxiv.org/abs/2104.06486).
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  It achieves the following results on the evaluation set:
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  - Loss: 3.7602
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  - Rouge1 Fmeasure Mean: 28.5338
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  - Rouge2 Fmeasure Mean: 9.5060
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+ - RougeL Fmeasure Mean: 20.9321
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+ - RougeLsum Fmeasure Mean: 24.0998
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  - Bertscore Hashcode: microsoft/deberta-xlarge-mnli_L40_no-idf_version=0.3.11(hug_trans=4.21.0.dev0)-rescaled_fast-tokenizer
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  - Bertscore F1 Mean: 22.7619
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  - Seed: 42