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README.md
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# Results
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(refer to the technical report for exact evaluation method + code. * indicates the best monolingual/out-of-domain result. **bold** is best overall result. _italic_ indicates the task is in-domain for the model.)
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| | JSQuAD | | | | MIRACL | | | | MrTyDi | | | | Average | | |
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# Results
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See the table below for an overview of results, vs previous Japanese-only models and the current multilingual state-of-the-art (multilingual-e5).
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Worth noting: JaColBERT is evaluated out-of-domain on all three datasets, whereas JSQuAD is partially (English version) and MIRACL & Mr.TyDi are fully in-domain for e5, likely contributing to their strong performance. In a real-world setting, I'm hopeful this could be bridged with moderate, quick (<2hrs) fine-tuning.
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(refer to the technical report for exact evaluation method + code. * indicates the best monolingual/out-of-domain result. **bold** is best overall result. _italic_ indicates the task is in-domain for the model.)
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| | JSQuAD | | | | MIRACL | | | | MrTyDi | | | | Average | | |
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