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jinaai
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jina-embedding-s-en-v1

Sentence Similarity
sentence-transformers
PyTorch
English
t5
finetuner
mteb
feature-extraction
custom_code
Eval Results
Inference Endpoints
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@@ -61,7 +61,7 @@ We compared the model against `all-minilm-l6-v2`/`all-mpnet-base-v2` from sbert
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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 |
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  |jina-embedding-s-en-v1|0.738|0.781|0.732|0.833|0.785|0.859|0.471 |0.852|0.567 |
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  |jina-embedding-b-en-v1|0.736|0.804|0.745|0.844|0.793|0.873|0.481 |0.87|0.616 |
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- |jina-embedding-l-en-v1|0.735|0.829|0.759|0.844|0.8|0.888|0.465 |0.876|0.645 |
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  For more tasks and metrics, please checkout [MTEB](https://huggingface.co/spaces/mteb/leaderboard) benchmark.
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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 |
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  |jina-embedding-s-en-v1|0.738|0.781|0.732|0.833|0.785|0.859|0.471 |0.852|0.567 |
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  |jina-embedding-b-en-v1|0.736|0.804|0.745|0.844|0.793|0.873|0.481 |0.87|0.616 |
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+ |jina-embedding-l-en-v1|0.736|0.832|0.762|0.846|0.805|0.885|0.477 |0.876|0.65 |
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  For more tasks and metrics, please checkout [MTEB](https://huggingface.co/spaces/mteb/leaderboard) benchmark.
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