Add WMT23 files

setup/.gitattributes

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+wmt23/nllb_3b/wmttest2023_xcomet-xxl_nld.json filter=lfs diff=lfs merge=lfs -text
+wmt23/nllb_3b/wmttest2023_xcomet-xl_ita.json filter=lfs diff=lfs merge=lfs -text
+wmt23/nllb_3b/wmttest2023_xcomet-xxl_ita.json filter=lfs diff=lfs merge=lfs -text
+wmt23/nllb_3b/wmttest2023_xcomet-xl_nld.json filter=lfs diff=lfs merge=lfs -text
+wmt23/nllb_600m/wmttest2023_xcomet-xxl_nld.json filter=lfs diff=lfs merge=lfs -text
+wmt23/nllb_600m/wmttest2023_xcomet-xl_ita.json filter=lfs diff=lfs merge=lfs -text
+wmt23/nllb_600m/wmttest2023_xcomet-xxl_ita.json filter=lfs diff=lfs merge=lfs -text
+wmt23/nllb_600m/wmttest2023_xcomet-xl_nld.json filter=lfs diff=lfs merge=lfs -text

setup/wmt23/README.md

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+# WMT 2023 Original Data
+
+The file `wmttest2023.eng` is the original source dataset, obtained by concatenating various sources from WMT 2023 campaigns, including the general task, all challenge sets and the biomedical translation task.
+
+Folders contain machine translations to Italian (`ita`) and Dutch (`nld`) for every segment produced by [NLLB-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) and [NLLB-3B](https://huggingface.co/facebook/nllb-200-3.3B), using beam search with `n_beams = 5`. Every translation in both target languages is scored using both [`XCOMET-XL`](https://huggingface.co/Unbabel/XCOMET-XL) and [`XCOMET-XXL`](https://huggingface.co/Unbabel/XCOMET-XXL).
+
+Only the NLLB-3B translations and the XCOMET-XXL error spans are used for the QE4PE study.
+
+## Libraries versions
+
+```shell
+transformers == 4.22.0
+unbabel-comet == 2.2.0
+```

setup/wmt23/nllb_3b/wmttest2023_xcomet-xl_ita.json

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setup/wmt23/nllb_3b/wmttest2023_xcomet-xl_nld.json

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setup/wmt23/nllb_3b/wmttest2023_xcomet-xxl_ita.json

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setup/wmt23/nllb_600m/wmttest2023_xcomet-xl_ita.json

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setup/wmt23/nllb_600m/wmttest2023_xcomet-xxl_ita.json

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