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README.md
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---
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pipeline_tag: translation
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---
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# cometoid22-wmt23
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A referenceless/quality-estimation metric for machine translation evaluation.
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This metric is created by using the knowledge distillation of [wmt22-comet-da](https://huggingface.co/Unbabel/wmt22-comet-da) (a referece-based teacher).
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Refer to [the publication](https://aclanthology.org/2023.wmt-1.62) for technical details.
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## Setup
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Option 1: Install `pymarain`, aka python bindings to marian
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```bash
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pip install pymarian
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```
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Option 2: Build marian binary, reference: https://marian-nmt.github.io/quickstart/
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## Usage
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**Pymarian**
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```bash
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pymarian-eval -m checkpoints/marian.model.bin -v vocab.spm --like comet-qe -s src.txt -t mt.out.txt
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```
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**Marian**
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```bash
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paste src.txt mt.out.txt | marian evaluate --quiet --model checkpoints/marian.model.bin --vocabs vocab.spm vocab.spm --width 4 --like comet-qe \
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--mini-batch 16 --maxi-batch 256 --max-length 512 --max-length-crop true --workspace 8000
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```
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More info at https://github.com/marian-nmt/wmt23-metrics
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## Reference
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```
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@inproceedings{gowda-etal-2023-cometoid,
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title = "Cometoid: Distilling Strong Reference-based Machine Translation Metrics into {E}ven Stronger Quality Estimation Metrics",
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author = "Gowda, Thamme and
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Kocmi, Tom and
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Junczys-Dowmunt, Marcin",
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editor = "Koehn, Philipp and
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Haddon, Barry and
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Kocmi, Tom and
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Monz, Christof",
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booktitle = "Proceedings of the Eighth Conference on Machine Translation",
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month = dec,
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year = "2023",
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address = "Singapore",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2023.wmt-1.62",
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pages = "751--755",
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}
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```
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