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--- |
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quantized_by: bartowski |
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pipeline_tag: text-generation |
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language: |
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- en |
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- ar |
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- cs |
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- de |
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- es |
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- fr |
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- it |
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- ja |
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- ko |
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- nl |
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- pt |
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- zh |
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tags: |
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- language |
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- granite |
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- embeddings |
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- multilingual |
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license: apache-2.0 |
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base_model: ibm-granite/granite-embedding-107m-multilingual |
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model-index: |
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- name: ibm-granite/granite-embedding-107m-multilingual |
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results: |
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- task: |
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type: Retrieval |
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dataset: |
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name: Miracl (en) |
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type: miracl/mmteb-miracl |
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config: en |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
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value: 0.41176 |
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- type: ndcg_at_10 |
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value: 0.46682 |
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- type: ndcg_at_100 |
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value: 0.54326 |
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- type: ndcg_at_1000 |
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value: 0.56567 |
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- type: ndcg_at_20 |
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value: 0.50157 |
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- type: ndcg_at_3 |
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value: 0.41197 |
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- type: ndcg_at_5 |
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value: 0.42086 |
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- type: recall_at_1 |
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value: 0.19322 |
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- type: recall_at_10 |
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value: 0.57721 |
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- type: recall_at_100 |
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value: 0.83256 |
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- type: recall_at_1000 |
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value: 0.95511 |
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- type: recall_at_20 |
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value: 0.6757 |
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- type: recall_at_3 |
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value: 0.37171 |
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- type: recall_at_5 |
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value: 0.44695 |
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- task: |
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type: Retrieval |
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dataset: |
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name: Miracl (ar) |
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type: miracl/mmteb-miracl |
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config: ar |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
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value: 0.55559 |
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- type: ndcg_at_10 |
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value: 0.62541 |
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- type: ndcg_at_100 |
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value: 0.67101 |
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- type: ndcg_at_1000 |
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value: 0.6805 |
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- type: ndcg_at_20 |
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value: 0.64739 |
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- type: ndcg_at_3 |
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value: 0.56439 |
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- type: ndcg_at_5 |
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value: 0.59347 |
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- type: recall_at_1 |
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value: 0.37009 |
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- type: recall_at_10 |
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value: 0.73317 |
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- type: recall_at_100 |
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value: 0.90066 |
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- type: recall_at_1000 |
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value: 0.96272 |
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- type: recall_at_20 |
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value: 0.80205 |
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- type: recall_at_3 |
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value: 0.56903 |
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- type: recall_at_5 |
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value: 0.6518 |
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- task: |
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type: Retrieval |
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dataset: |
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name: Miracl (bn) |
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type: miracl/mmteb-miracl |
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config: bn |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
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value: 0.56691 |
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- type: ndcg_at_10 |
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value: 0.65484 |
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- type: ndcg_at_100 |
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value: 0.70142 |
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- type: ndcg_at_1000 |
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value: 0.70994 |
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- type: ndcg_at_20 |
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value: 0.67838 |
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- type: ndcg_at_3 |
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value: 0.5988 |
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- type: ndcg_at_5 |
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value: 0.62718 |
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- type: recall_at_1 |
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value: 0.3605 |
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- type: recall_at_10 |
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value: 0.76854 |
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- type: recall_at_100 |
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value: 0.9285 |
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- type: recall_at_1000 |
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value: 0.97928 |
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- type: recall_at_20 |
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value: 0.83667 |
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- type: recall_at_3 |
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value: 0.61596 |
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- type: recall_at_5 |
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value: 0.69766 |
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- task: |
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type: Retrieval |
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dataset: |
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name: Miracl (de) |
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type: miracl/mmteb-miracl |
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config: de |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
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value: 0.41967 |
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- type: ndcg_at_10 |
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value: 0.45141 |
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- type: ndcg_at_100 |
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value: 0.53461 |
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- type: ndcg_at_1000 |
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value: 0.55463 |
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- type: ndcg_at_20 |
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value: 0.49012 |
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- type: ndcg_at_3 |
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value: 0.39486 |
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- type: ndcg_at_5 |
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value: 0.41496 |
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- type: recall_at_1 |
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value: 0.19494 |
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- type: recall_at_10 |
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value: 0.53774 |
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- type: recall_at_100 |
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value: 0.83314 |
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- type: recall_at_1000 |
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value: 0.95045 |
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- type: recall_at_20 |
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value: 0.65659 |
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- type: recall_at_3 |
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value: 0.3556 |
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- type: recall_at_5 |
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value: 0.44448 |
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- task: |
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type: Retrieval |
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dataset: |
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name: Miracl (es) |
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type: miracl/mmteb-miracl |
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config: es |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
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value: 0.54475 |
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- type: ndcg_at_10 |
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value: 0.46593 |
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- type: ndcg_at_100 |
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value: 0.58079 |
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- type: ndcg_at_1000 |
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value: 0.60656 |
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- type: ndcg_at_20 |
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value: 0.51858 |
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- type: ndcg_at_3 |
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value: 0.4578 |
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- type: ndcg_at_5 |
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value: 0.44321 |
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- type: recall_at_1 |
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value: 0.15966 |
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- type: recall_at_10 |
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value: 0.49343 |
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- type: recall_at_100 |
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value: 0.82684 |
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- type: recall_at_1000 |
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value: 0.95299 |
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- type: recall_at_20 |
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value: 0.62367 |
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- type: recall_at_3 |
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value: 0.2949 |
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- type: recall_at_5 |
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value: 0.37983 |
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- task: |
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type: Retrieval |
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dataset: |
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name: Miracl (fa) |
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type: miracl/mmteb-miracl |
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config: fa |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
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value: 0.36709 |
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- type: ndcg_at_10 |
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value: 0.46961 |
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- type: ndcg_at_100 |
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value: 0.53262 |
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- type: ndcg_at_1000 |
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value: 0.55024 |
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- type: ndcg_at_20 |
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value: 0.49892 |
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- type: ndcg_at_3 |
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value: 0.40235 |
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- type: ndcg_at_5 |
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value: 0.42866 |
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- type: recall_at_1 |
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value: 0.22735 |
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- type: recall_at_10 |
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value: 0.59949 |
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- type: recall_at_100 |
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value: 0.83867 |
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- type: recall_at_1000 |
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value: 0.95007 |
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- type: recall_at_20 |
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value: 0.68947 |
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- type: recall_at_3 |
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value: 0.41781 |
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- type: recall_at_5 |
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value: 0.49374 |
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- task: |
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type: Retrieval |
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dataset: |
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name: Miracl (fi) |
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type: miracl/mmteb-miracl |
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config: fi |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
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value: 0.59245 |
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- type: ndcg_at_10 |
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value: 0.65551 |
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- type: ndcg_at_100 |
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value: 0.6967 |
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- type: ndcg_at_1000 |
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value: 0.70521 |
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- type: ndcg_at_20 |
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value: 0.67552 |
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- type: ndcg_at_3 |
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value: 0.58876 |
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- type: ndcg_at_5 |
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value: 0.61779 |
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- type: recall_at_1 |
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value: 0.37669 |
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- type: recall_at_10 |
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value: 0.76529 |
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- type: recall_at_100 |
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value: 0.9156 |
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- type: recall_at_1000 |
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value: 0.96977 |
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- type: recall_at_20 |
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value: 0.82685 |
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- type: recall_at_3 |
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value: 0.60234 |
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- type: recall_at_5 |
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value: 0.67135 |
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- task: |
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type: Retrieval |
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dataset: |
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name: Miracl (fr) |
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type: miracl/mmteb-miracl |
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config: fr |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
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value: 0.38776 |
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- type: ndcg_at_10 |
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value: 0.47589 |
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- type: ndcg_at_100 |
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value: 0.54641 |
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- type: ndcg_at_1000 |
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value: 0.5629 |
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- type: ndcg_at_20 |
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value: 0.51203 |
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- type: ndcg_at_3 |
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value: 0.38924 |
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- type: ndcg_at_5 |
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value: 0.42572 |
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- type: recall_at_1 |
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value: 0.22082 |
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- type: recall_at_10 |
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value: 0.61619 |
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- type: recall_at_100 |
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value: 0.87237 |
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- type: recall_at_1000 |
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value: 0.97449 |
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- type: recall_at_20 |
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value: 0.72689 |
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- type: recall_at_3 |
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value: 0.39527 |
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- type: recall_at_5 |
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value: 0.48983 |
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- task: |
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type: Retrieval |
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dataset: |
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name: Miracl (hi) |
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type: miracl/mmteb-miracl |
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config: hi |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
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value: 0.33143 |
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- type: ndcg_at_10 |
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value: 0.42084 |
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- type: ndcg_at_100 |
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value: 0.48647 |
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- type: ndcg_at_1000 |
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value: 0.50712 |
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- type: ndcg_at_20 |
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value: 0.45399 |
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- type: ndcg_at_3 |
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value: 0.34988 |
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- type: ndcg_at_5 |
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value: 0.37938 |
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- type: recall_at_1 |
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value: 0.17852 |
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- type: recall_at_10 |
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value: 0.55217 |
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- type: recall_at_100 |
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value: 0.79929 |
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- type: recall_at_1000 |
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value: 0.93434 |
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- type: recall_at_20 |
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value: 0.65231 |
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- type: recall_at_3 |
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value: 0.33765 |
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- type: recall_at_5 |
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value: 0.43828 |
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- task: |
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type: Retrieval |
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dataset: |
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name: Miracl (id) |
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type: miracl/mmteb-miracl |
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config: id |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
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value: 0.43854 |
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- type: ndcg_at_10 |
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value: 0.45459 |
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- type: ndcg_at_100 |
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value: 0.53643 |
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- type: ndcg_at_1000 |
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value: 0.56052 |
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- type: ndcg_at_20 |
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value: 0.48795 |
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- type: ndcg_at_3 |
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value: 0.41041 |
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- type: ndcg_at_5 |
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value: 0.42235 |
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- type: recall_at_1 |
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value: 0.19193 |
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- type: recall_at_10 |
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value: 0.5289 |
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- type: recall_at_100 |
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value: 0.79649 |
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- type: recall_at_1000 |
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value: 0.92937 |
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- type: recall_at_20 |
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value: 0.61813 |
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- type: recall_at_3 |
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value: 0.35431 |
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- type: recall_at_5 |
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value: 0.43348 |
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- task: |
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type: Retrieval |
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dataset: |
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name: Miracl (ja) |
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type: miracl/mmteb-miracl |
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config: ja |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
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value: 0.53256 |
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- type: ndcg_at_10 |
|
value: 0.59922 |
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- type: ndcg_at_100 |
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value: 0.65407 |
|
- type: ndcg_at_1000 |
|
value: 0.66484 |
|
- type: ndcg_at_20 |
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value: 0.62596 |
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- type: ndcg_at_3 |
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value: 0.53717 |
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- type: ndcg_at_5 |
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value: 0.56523 |
|
- type: recall_at_1 |
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value: 0.34555 |
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- type: recall_at_10 |
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value: 0.71476 |
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- type: recall_at_100 |
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value: 0.91152 |
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- type: recall_at_1000 |
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value: 0.97728 |
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- type: recall_at_20 |
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value: 0.79811 |
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- type: recall_at_3 |
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value: 0.53482 |
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- type: recall_at_5 |
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value: 0.62327 |
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- task: |
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type: Retrieval |
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dataset: |
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name: Miracl (ko) |
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type: miracl/mmteb-miracl |
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config: ko |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
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value: 0.5493 |
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- type: ndcg_at_10 |
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value: 0.58413 |
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- type: ndcg_at_100 |
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value: 0.64374 |
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- type: ndcg_at_1000 |
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value: 0.65655 |
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- type: ndcg_at_20 |
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value: 0.61732 |
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- type: ndcg_at_3 |
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value: 0.53068 |
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- type: ndcg_at_5 |
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value: 0.55202 |
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- type: recall_at_1 |
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value: 0.32602 |
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- type: recall_at_10 |
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value: 0.68647 |
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- type: recall_at_100 |
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value: 0.87746 |
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- type: recall_at_1000 |
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value: 0.95524 |
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- type: recall_at_20 |
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value: 0.78089 |
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- type: recall_at_3 |
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value: 0.49173 |
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- type: recall_at_5 |
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value: 0.5827 |
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- task: |
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type: Retrieval |
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dataset: |
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name: Miracl (ru) |
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type: miracl/mmteb-miracl |
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config: ru |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
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value: 0.43131 |
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- type: ndcg_at_10 |
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value: 0.48262 |
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- type: ndcg_at_100 |
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value: 0.56158 |
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- type: ndcg_at_1000 |
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value: 0.57929 |
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- type: ndcg_at_20 |
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value: 0.52023 |
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- type: ndcg_at_3 |
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value: 0.42808 |
|
- type: ndcg_at_5 |
|
value: 0.44373 |
|
- type: recall_at_1 |
|
value: 0.22018 |
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- type: recall_at_10 |
|
value: 0.58034 |
|
- type: recall_at_100 |
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value: 0.84074 |
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- type: recall_at_1000 |
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value: 0.93938 |
|
- type: recall_at_20 |
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value: 0.68603 |
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- type: recall_at_3 |
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value: 0.39307 |
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- type: recall_at_5 |
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value: 0.47077 |
|
- task: |
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type: Retrieval |
|
dataset: |
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name: Miracl (sw) |
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type: miracl/mmteb-miracl |
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config: sw |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
|
value: 0.50415 |
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- type: ndcg_at_10 |
|
value: 0.59111 |
|
- type: ndcg_at_100 |
|
value: 0.64312 |
|
- type: ndcg_at_1000 |
|
value: 0.65089 |
|
- type: ndcg_at_20 |
|
value: 0.61651 |
|
- type: ndcg_at_3 |
|
value: 0.5304 |
|
- type: ndcg_at_5 |
|
value: 0.56139 |
|
- type: recall_at_1 |
|
value: 0.33267 |
|
- type: recall_at_10 |
|
value: 0.72082 |
|
- type: recall_at_100 |
|
value: 0.91377 |
|
- type: recall_at_1000 |
|
value: 0.96152 |
|
- type: recall_at_20 |
|
value: 0.79943 |
|
- type: recall_at_3 |
|
value: 0.5548 |
|
- type: recall_at_5 |
|
value: 0.64302 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: Miracl (te) |
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type: miracl/mmteb-miracl |
|
config: te |
|
split: dev |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 0.64372 |
|
- type: ndcg_at_10 |
|
value: 0.78175 |
|
- type: ndcg_at_100 |
|
value: 0.79523 |
|
- type: ndcg_at_1000 |
|
value: 0.79774 |
|
- type: ndcg_at_20 |
|
value: 0.78826 |
|
- type: ndcg_at_3 |
|
value: 0.74856 |
|
- type: ndcg_at_5 |
|
value: 0.77128 |
|
- type: recall_at_1 |
|
value: 0.63688 |
|
- type: recall_at_10 |
|
value: 0.90358 |
|
- type: recall_at_100 |
|
value: 0.96558 |
|
- type: recall_at_1000 |
|
value: 0.9847 |
|
- type: recall_at_20 |
|
value: 0.92834 |
|
- type: recall_at_3 |
|
value: 0.81804 |
|
- type: recall_at_5 |
|
value: 0.87198 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: Miracl (th) |
|
type: miracl/mmteb-miracl |
|
config: th |
|
split: dev |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 0.65484 |
|
- type: ndcg_at_10 |
|
value: 0.71774 |
|
- type: ndcg_at_100 |
|
value: 0.75362 |
|
- type: ndcg_at_1000 |
|
value: 0.75898 |
|
- type: ndcg_at_20 |
|
value: 0.73709 |
|
- type: ndcg_at_3 |
|
value: 0.66199 |
|
- type: ndcg_at_5 |
|
value: 0.68451 |
|
- type: recall_at_1 |
|
value: 0.45911 |
|
- type: recall_at_10 |
|
value: 0.82619 |
|
- type: recall_at_100 |
|
value: 0.95515 |
|
- type: recall_at_1000 |
|
value: 0.98854 |
|
- type: recall_at_20 |
|
value: 0.88447 |
|
- type: recall_at_3 |
|
value: 0.67437 |
|
- type: recall_at_5 |
|
value: 0.73786 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: Miracl (yo) |
|
type: miracl/mmteb-miracl |
|
config: yo |
|
split: dev |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 0.46218 |
|
- type: ndcg_at_10 |
|
value: 0.64685 |
|
- type: ndcg_at_100 |
|
value: 0.66941 |
|
- type: ndcg_at_1000 |
|
value: 0.67361 |
|
- type: ndcg_at_20 |
|
value: 0.65548 |
|
- type: ndcg_at_3 |
|
value: 0.57609 |
|
- type: ndcg_at_5 |
|
value: 0.62021 |
|
- type: recall_at_1 |
|
value: 0.42787 |
|
- type: recall_at_10 |
|
value: 0.82913 |
|
- type: recall_at_100 |
|
value: 0.93277 |
|
- type: recall_at_1000 |
|
value: 0.96499 |
|
- type: recall_at_20 |
|
value: 0.85994 |
|
- type: recall_at_3 |
|
value: 0.65406 |
|
- type: recall_at_5 |
|
value: 0.7542 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: Miracl (zh) |
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type: miracl/mmteb-miracl |
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config: zh |
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split: dev |
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metrics: |
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- type: ndcg_at_1 |
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value: 0.41985 |
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- type: ndcg_at_10 |
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value: 0.4837 |
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- type: ndcg_at_100 |
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value: 0.55961 |
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- type: ndcg_at_1000 |
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value: 0.5762 |
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- type: ndcg_at_20 |
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value: 0.51595 |
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- type: ndcg_at_3 |
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value: 0.42094 |
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- type: ndcg_at_5 |
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value: 0.44273 |
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- type: recall_at_1 |
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value: 0.21446 |
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- type: recall_at_10 |
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value: 0.59695 |
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- type: recall_at_100 |
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value: 0.87388 |
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- type: recall_at_1000 |
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value: 0.96833 |
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- type: recall_at_20 |
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value: 0.69252 |
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- type: recall_at_3 |
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value: 0.40377 |
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- type: recall_at_5 |
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value: 0.4903 |
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--- |
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## 💫 Community Model> granite embedding 107m multilingual by Ibm-Granite |
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*👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)*. |
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**Model creator:** [ibm-granite](https://huggingface.co/ibm-granite)<br> |
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**Original model**: [granite-embedding-107m-multilingual](https://huggingface.co/ibm-granite/granite-embedding-107m-multilingual)<br> |
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**GGUF quantization:** provided by [bartowski](https://huggingface.co/bartowski) based on `llama.cpp` release [b4381](https://github.com/ggerganov/llama.cpp/releases/tag/b4381)<br> |
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## Technical Details |
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Embedding model with vector size 384 |
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Max length of 512 tokens |
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107 million parameters for high quality fast embedding |
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Supported Languages: English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, and Chinese. |
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## Special thanks |
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🙏 Special thanks to [Georgi Gerganov](https://github.com/ggerganov) and the whole team working on [llama.cpp](https://github.com/ggerganov/llama.cpp/) for making all of this possible. |
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## Disclaimers |
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LM Studio is not the creator, originator, or owner of any Model featured in the Community Model Program. Each Community Model is created and provided by third parties. LM Studio does not endorse, support, represent or guarantee the completeness, truthfulness, accuracy, or reliability of any Community Model. You understand that Community Models can produce content that might be offensive, harmful, inaccurate or otherwise inappropriate, or deceptive. Each Community Model is the sole responsibility of the person or entity who originated such Model. LM Studio may not monitor or control the Community Models and cannot, and does not, take responsibility for any such Model. LM Studio disclaims all warranties or guarantees about the accuracy, reliability or benefits of the Community Models. LM Studio further disclaims any warranty that the Community Model will meet your requirements, be secure, uninterrupted or available at any time or location, or error-free, viruses-free, or that any errors will be corrected, or otherwise. You will be solely responsible for any damage resulting from your use of or access to the Community Models, your downloading of any Community Model, or use of any other Community Model provided by or through LM Studio. |
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