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@@ -40,12 +40,12 @@ More info will be released together with the technique report.
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  We compared the model against `all-minilm-l6-v2` from sbert and `text-embeddings-ada-002` from OpenAI:
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- |FIELD1 |STS12|STS13|STS14|STS15|STS16|STS17|TRECOVID|Quora|SciFact|param |context length|
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  |------------------------------|-----|-----|-----|-----|-----|-----|--------|-----|-------|---------|------|
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- |all-minilm-l6-v2 |0.724|0.806|0.756|0.854|0.79 |0.876|0.473 |0.876|0.645 |33m |256|
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- |all-mpnet--base-v2 |0.726|0.835|0.78 |0.857|0.8 |0.906|0.513 |0.875|0.656 |110m |256|
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- |ada-embedding-002 |0.698|0.833|0.761|0.861|0.86 |0.903|0.685 |0.876|0.726 |Unknown |8024|
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- |jina-embedding-small |0.738|0.781|0.732|0.833|0.785|0.859|0.471 |0.852|0.567 |35m |512|
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  For more tasks and metrics, please checkout [MTEB](https://huggingface.co/spaces/mteb/leaderboard) benchmark.
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  We compared the model against `all-minilm-l6-v2` from sbert and `text-embeddings-ada-002` from OpenAI:
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+ |FIELD1|STS12|STS13|STS14|STS15|STS16|STS17|TRECOVID|Quora|SciFact|param |context|
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  |------------------------------|-----|-----|-----|-----|-----|-----|--------|-----|-------|---------|------|
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+ |all-minilm-l6-v2|0.724|0.806|0.756|0.854|0.79 |0.876|0.473 |0.876|0.645 |33m |256|
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+ |all-mpnet--base-v2|0.726|0.835|0.78 |0.857|0.8 |0.906|0.513 |0.875|0.656 |110m |256|
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+ |ada-embedding-002|0.698|0.833|0.761|0.861|0.86 |0.903|0.685 |0.876|0.726 |Unknown API based |8192|
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+ |jina-embedding-small|0.738|0.781|0.732|0.833|0.785|0.859|0.471 |0.852|0.567 |35m |512|
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  For more tasks and metrics, please checkout [MTEB](https://huggingface.co/spaces/mteb/leaderboard) benchmark.
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