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answer-finder.yuzu

Question Answering
Transformers
PyTorch
Japanese
bert
Inference Endpoints
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README.md CHANGED
@@ -11,8 +11,24 @@ This model is a Japanese Answer-Finder. It retrieves answers from questions and
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  - Japanese
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  # Training data
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- | Dataset | Paper |
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  |--------------------------------------------------------|:----------------------------------------:|
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- | [JsQuAD](JSQuAD https://github.com/yahoojapan/JGLUE) | [paper](https://aclanthology.org/2022.lrec-1.317.pdf) |
 
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  - Japanese
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+ # Model score
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+ | | Relevance Score |
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+ |:---------------------|:---:|
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+ |__Japanese__ | <span style="font-size:200%;color:#ffd21e;">&starf;</span><span style="font-size:200%;color:#ffd21e;">&starf;</span><span style="font-size:200%;color:#ffd21e;">&starf;</span><span style="font-size:200%;color:#ffd21e;">&starf;</span><span style="font-size:200%;color:#ffd21e;">&starf;</span><span style="font-size:200%;color:#ffd21e;">&starf;</span><span style="font-size:200%;color:#ffd21e;">&starf;</span><span style="font-size:200%;color:#ffd21e;">&starf;</span><span style="font-size:200%;color:#ffd21e;">&starf;</span><span style="font-size:200%;color:black;">&starf;</span> |
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+ |Out of domain Score (English only)|
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+ |---|
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+ |<span style="font-size:200%;color:black;">&starf;</span><span style="font-size:200%;color:black;">&starf;</span><span style="font-size:200%;color:black;">&starf;</span><span style="font-size:200%;color:black;">&starf;</span><span style="font-size:200%;color:black;">&starf;</span><span style="font-size:200%;color:black;">&starf;</span><span style="font-size:200%;color:black;">&starf;</span><span style="font-size:200%;color:black;">&starf;</span><span style="font-size:200%;color:black;">&starf;</span><span style="font-size:200%;color:black;">&starf;</span>|
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+
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+ |Speed Score|
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+ |---|
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+ |TBD|
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+ ---
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  # Training data
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+ | Dataset | Paper |
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  |--------------------------------------------------------|:----------------------------------------:|
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+ | [JsQuAD](JSQuAD https://github.com/yahoojapan/JGLUE) | [paper](https://aclanthology.org/2022.lrec-1.317.pdf) |