Update README.md

README.md

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 # Overview
 
-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>"`.
+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).
 
 It achieves the following results on the evaluation set:
 - Loss: 3.7602
 - Rouge1 Fmeasure Mean: 28.5338
 - Rouge2 Fmeasure Mean: 9.5060
-- Rougel Fmeasure Mean: 20.9321
-- Rougelsum Fmeasure Mean: 24.0998
+- RougeL Fmeasure Mean: 20.9321
+- RougeLsum Fmeasure Mean: 24.0998
 - Bertscore Hashcode: microsoft/deberta-xlarge-mnli_L40_no-idf_version=0.3.11(hug_trans=4.21.0.dev0)-rescaled_fast-tokenizer
 - Bertscore F1 Mean: 22.7619
 - Seed: 42