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--- |
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language: |
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- multilingual |
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- af |
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- am |
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- ar |
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- as |
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- az |
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- be |
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- bg |
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- bn |
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- br |
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- bs |
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- ca |
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- cs |
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- cy |
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- da |
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- de |
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- el |
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- en |
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- eo |
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- es |
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- et |
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- eu |
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- fa |
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- fi |
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- fr |
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- fy |
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- ga |
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- gd |
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- gl |
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- gu |
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- ha |
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- he |
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- hi |
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- hr |
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- hu |
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- hy |
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- id |
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- is |
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- it |
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- ja |
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- jv |
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- ka |
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- kk |
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- km |
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- kn |
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- ko |
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- ku |
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- ky |
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- la |
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- lo |
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- lt |
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- lv |
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- mg |
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- mk |
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- ml |
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- mn |
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- mr |
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- ms |
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- my |
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- ne |
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- nl |
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- 'no' |
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- om |
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- or |
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- pa |
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- pl |
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- ps |
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- pt |
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- ro |
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- ru |
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- sa |
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- sd |
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- si |
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- sk |
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- sl |
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- so |
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- sq |
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- sr |
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- su |
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- sv |
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- sw |
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- ta |
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- te |
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- th |
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- tl |
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- tr |
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- ug |
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- uk |
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- ur |
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- uz |
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- vi |
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- xh |
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- yi |
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- zh |
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license: mit |
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tags: |
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- mteb |
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- Sentence Transformers |
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- sentence-similarity |
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- sentence-transformers |
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- mlx |
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model-index: |
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- name: multilingual-e5-base |
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results: |
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- task: |
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type: Classification |
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dataset: |
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name: MTEB AmazonCounterfactualClassification (en) |
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type: mteb/amazon_counterfactual |
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config: en |
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split: test |
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
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metrics: |
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- type: accuracy |
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value: 78.97014925373135 |
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- type: ap |
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value: 43.69351129103008 |
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- type: f1 |
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value: 73.38075030070492 |
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- task: |
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type: Classification |
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dataset: |
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name: MTEB AmazonCounterfactualClassification (de) |
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type: mteb/amazon_counterfactual |
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config: de |
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split: test |
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
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metrics: |
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- type: accuracy |
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value: 71.7237687366167 |
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- type: ap |
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value: 82.22089859962671 |
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- type: f1 |
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value: 69.95532758884401 |
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- task: |
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type: Classification |
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dataset: |
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name: MTEB AmazonCounterfactualClassification (en-ext) |
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type: mteb/amazon_counterfactual |
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config: en-ext |
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split: test |
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
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metrics: |
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- type: accuracy |
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value: 79.65517241379312 |
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- type: ap |
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value: 28.507918657094738 |
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- type: f1 |
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value: 66.84516013726119 |
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- task: |
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type: Classification |
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dataset: |
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name: MTEB AmazonCounterfactualClassification (ja) |
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type: mteb/amazon_counterfactual |
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config: ja |
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split: test |
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
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metrics: |
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- type: accuracy |
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value: 73.32976445396146 |
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- type: ap |
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value: 20.720481637566014 |
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- type: f1 |
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value: 59.78002763416003 |
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- task: |
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type: Classification |
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dataset: |
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name: MTEB AmazonPolarityClassification |
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type: mteb/amazon_polarity |
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config: default |
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split: test |
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revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
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metrics: |
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- type: accuracy |
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value: 90.63775 |
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- type: ap |
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value: 87.22277903861716 |
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- type: f1 |
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value: 90.60378636386807 |
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- task: |
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type: Classification |
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dataset: |
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name: MTEB AmazonReviewsClassification (en) |
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type: mteb/amazon_reviews_multi |
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config: en |
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split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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metrics: |
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- type: accuracy |
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value: 44.546 |
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- type: f1 |
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value: 44.05666638370923 |
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- task: |
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type: Classification |
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dataset: |
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name: MTEB AmazonReviewsClassification (de) |
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type: mteb/amazon_reviews_multi |
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config: de |
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split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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metrics: |
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- type: accuracy |
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value: 41.828 |
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- type: f1 |
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value: 41.2710255644252 |
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- task: |
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type: Classification |
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dataset: |
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name: MTEB AmazonReviewsClassification (es) |
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type: mteb/amazon_reviews_multi |
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config: es |
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split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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metrics: |
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- type: accuracy |
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value: 40.534 |
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- type: f1 |
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value: 39.820743174270326 |
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- task: |
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type: Classification |
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dataset: |
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name: MTEB AmazonReviewsClassification (fr) |
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type: mteb/amazon_reviews_multi |
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config: fr |
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split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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metrics: |
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- type: accuracy |
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value: 39.684 |
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- type: f1 |
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value: 39.11052682815307 |
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- task: |
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type: Classification |
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dataset: |
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name: MTEB AmazonReviewsClassification (ja) |
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type: mteb/amazon_reviews_multi |
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config: ja |
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split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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metrics: |
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- type: accuracy |
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value: 37.436 |
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- type: f1 |
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value: 37.07082931930871 |
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- task: |
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type: Classification |
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dataset: |
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name: MTEB AmazonReviewsClassification (zh) |
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type: mteb/amazon_reviews_multi |
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config: zh |
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split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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metrics: |
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- type: accuracy |
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value: 37.226000000000006 |
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- type: f1 |
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value: 36.65372077739185 |
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- task: |
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type: Retrieval |
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dataset: |
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name: MTEB ArguAna |
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type: arguana |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: map_at_1 |
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value: 22.831000000000003 |
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- type: map_at_10 |
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value: 36.42 |
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- type: map_at_100 |
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value: 37.699 |
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- type: map_at_1000 |
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value: 37.724000000000004 |
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- type: map_at_3 |
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value: 32.207 |
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- type: map_at_5 |
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value: 34.312 |
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- type: mrr_at_1 |
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value: 23.257 |
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- type: mrr_at_10 |
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value: 36.574 |
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- type: mrr_at_100 |
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value: 37.854 |
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- type: mrr_at_1000 |
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value: 37.878 |
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- type: mrr_at_3 |
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value: 32.385000000000005 |
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- type: mrr_at_5 |
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value: 34.48 |
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- type: ndcg_at_1 |
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value: 22.831000000000003 |
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- type: ndcg_at_10 |
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value: 44.230000000000004 |
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- type: ndcg_at_100 |
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value: 49.974000000000004 |
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- type: ndcg_at_1000 |
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value: 50.522999999999996 |
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- type: ndcg_at_3 |
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value: 35.363 |
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- type: ndcg_at_5 |
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value: 39.164 |
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- type: precision_at_1 |
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value: 22.831000000000003 |
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- type: precision_at_10 |
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value: 6.935 |
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- type: precision_at_100 |
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value: 0.9520000000000001 |
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- type: precision_at_1000 |
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value: 0.099 |
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- type: precision_at_3 |
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value: 14.841 |
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- type: precision_at_5 |
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value: 10.754 |
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- type: recall_at_1 |
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value: 22.831000000000003 |
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- type: recall_at_10 |
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value: 69.346 |
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- type: recall_at_100 |
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value: 95.235 |
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- type: recall_at_1000 |
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value: 99.36 |
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- type: recall_at_3 |
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value: 44.523 |
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- type: recall_at_5 |
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value: 53.769999999999996 |
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- task: |
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type: Clustering |
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dataset: |
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name: MTEB ArxivClusteringP2P |
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type: mteb/arxiv-clustering-p2p |
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config: default |
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split: test |
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
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metrics: |
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- type: v_measure |
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value: 40.27789869854063 |
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- task: |
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type: Clustering |
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dataset: |
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name: MTEB ArxivClusteringS2S |
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type: mteb/arxiv-clustering-s2s |
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config: default |
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split: test |
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
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metrics: |
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- type: v_measure |
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value: 35.41979463347428 |
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- task: |
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type: Reranking |
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dataset: |
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name: MTEB AskUbuntuDupQuestions |
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type: mteb/askubuntudupquestions-reranking |
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config: default |
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split: test |
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
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metrics: |
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- type: map |
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value: 58.22752045109304 |
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- type: mrr |
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value: 71.51112430198303 |
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- task: |
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type: STS |
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dataset: |
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name: MTEB BIOSSES |
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type: mteb/biosses-sts |
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config: default |
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split: test |
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
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metrics: |
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- type: cos_sim_pearson |
|
value: 84.71147646622866 |
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- type: cos_sim_spearman |
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value: 85.059167046486 |
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- type: euclidean_pearson |
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value: 75.88421613600647 |
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- type: euclidean_spearman |
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value: 75.12821787150585 |
|
- type: manhattan_pearson |
|
value: 75.22005646957604 |
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- type: manhattan_spearman |
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value: 74.42880434453272 |
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- task: |
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type: BitextMining |
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dataset: |
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name: MTEB BUCC (de-en) |
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type: mteb/bucc-bitext-mining |
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config: de-en |
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split: test |
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revision: d51519689f32196a32af33b075a01d0e7c51e252 |
|
metrics: |
|
- type: accuracy |
|
value: 99.23799582463465 |
|
- type: f1 |
|
value: 99.12665274878218 |
|
- type: precision |
|
value: 99.07098121085595 |
|
- type: recall |
|
value: 99.23799582463465 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB BUCC (fr-en) |
|
type: mteb/bucc-bitext-mining |
|
config: fr-en |
|
split: test |
|
revision: d51519689f32196a32af33b075a01d0e7c51e252 |
|
metrics: |
|
- type: accuracy |
|
value: 97.88685890380806 |
|
- type: f1 |
|
value: 97.59336708489249 |
|
- type: precision |
|
value: 97.44662117543473 |
|
- type: recall |
|
value: 97.88685890380806 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB BUCC (ru-en) |
|
type: mteb/bucc-bitext-mining |
|
config: ru-en |
|
split: test |
|
revision: d51519689f32196a32af33b075a01d0e7c51e252 |
|
metrics: |
|
- type: accuracy |
|
value: 97.47142362313821 |
|
- type: f1 |
|
value: 97.1989377670015 |
|
- type: precision |
|
value: 97.06384944001847 |
|
- type: recall |
|
value: 97.47142362313821 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB BUCC (zh-en) |
|
type: mteb/bucc-bitext-mining |
|
config: zh-en |
|
split: test |
|
revision: d51519689f32196a32af33b075a01d0e7c51e252 |
|
metrics: |
|
- type: accuracy |
|
value: 98.4728804634018 |
|
- type: f1 |
|
value: 98.2973494821836 |
|
- type: precision |
|
value: 98.2095839915745 |
|
- type: recall |
|
value: 98.4728804634018 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB Banking77Classification |
|
type: mteb/banking77 |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 82.74025974025975 |
|
- type: f1 |
|
value: 82.67420447730439 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB BiorxivClusteringP2P |
|
type: mteb/biorxiv-clustering-p2p |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 35.0380848063507 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB BiorxivClusteringS2S |
|
type: mteb/biorxiv-clustering-s2s |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 29.45956405670166 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB CQADupstackAndroidRetrieval |
|
type: BeIR/cqadupstack |
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config: default |
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split: test |
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revision: None |
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metrics: |
|
- type: map_at_1 |
|
value: 32.122 |
|
- type: map_at_10 |
|
value: 42.03 |
|
- type: map_at_100 |
|
value: 43.364000000000004 |
|
- type: map_at_1000 |
|
value: 43.474000000000004 |
|
- type: map_at_3 |
|
value: 38.804 |
|
- type: map_at_5 |
|
value: 40.585 |
|
- type: mrr_at_1 |
|
value: 39.914 |
|
- type: mrr_at_10 |
|
value: 48.227 |
|
- type: mrr_at_100 |
|
value: 49.018 |
|
- type: mrr_at_1000 |
|
value: 49.064 |
|
- type: mrr_at_3 |
|
value: 45.994 |
|
- type: mrr_at_5 |
|
value: 47.396 |
|
- type: ndcg_at_1 |
|
value: 39.914 |
|
- type: ndcg_at_10 |
|
value: 47.825 |
|
- type: ndcg_at_100 |
|
value: 52.852 |
|
- type: ndcg_at_1000 |
|
value: 54.891 |
|
- type: ndcg_at_3 |
|
value: 43.517 |
|
- type: ndcg_at_5 |
|
value: 45.493 |
|
- type: precision_at_1 |
|
value: 39.914 |
|
- type: precision_at_10 |
|
value: 8.956 |
|
- type: precision_at_100 |
|
value: 1.388 |
|
- type: precision_at_1000 |
|
value: 0.182 |
|
- type: precision_at_3 |
|
value: 20.791999999999998 |
|
- type: precision_at_5 |
|
value: 14.821000000000002 |
|
- type: recall_at_1 |
|
value: 32.122 |
|
- type: recall_at_10 |
|
value: 58.294999999999995 |
|
- type: recall_at_100 |
|
value: 79.726 |
|
- type: recall_at_1000 |
|
value: 93.099 |
|
- type: recall_at_3 |
|
value: 45.017 |
|
- type: recall_at_5 |
|
value: 51.002 |
|
- type: map_at_1 |
|
value: 29.677999999999997 |
|
- type: map_at_10 |
|
value: 38.684000000000005 |
|
- type: map_at_100 |
|
value: 39.812999999999995 |
|
- type: map_at_1000 |
|
value: 39.945 |
|
- type: map_at_3 |
|
value: 35.831 |
|
- type: map_at_5 |
|
value: 37.446 |
|
- type: mrr_at_1 |
|
value: 37.771 |
|
- type: mrr_at_10 |
|
value: 44.936 |
|
- type: mrr_at_100 |
|
value: 45.583 |
|
- type: mrr_at_1000 |
|
value: 45.634 |
|
- type: mrr_at_3 |
|
value: 42.771 |
|
- type: mrr_at_5 |
|
value: 43.994 |
|
- type: ndcg_at_1 |
|
value: 37.771 |
|
- type: ndcg_at_10 |
|
value: 44.059 |
|
- type: ndcg_at_100 |
|
value: 48.192 |
|
- type: ndcg_at_1000 |
|
value: 50.375 |
|
- type: ndcg_at_3 |
|
value: 40.172000000000004 |
|
- type: ndcg_at_5 |
|
value: 41.899 |
|
- type: precision_at_1 |
|
value: 37.771 |
|
- type: precision_at_10 |
|
value: 8.286999999999999 |
|
- type: precision_at_100 |
|
value: 1.322 |
|
- type: precision_at_1000 |
|
value: 0.178 |
|
- type: precision_at_3 |
|
value: 19.406000000000002 |
|
- type: precision_at_5 |
|
value: 13.745 |
|
- type: recall_at_1 |
|
value: 29.677999999999997 |
|
- type: recall_at_10 |
|
value: 53.071 |
|
- type: recall_at_100 |
|
value: 70.812 |
|
- type: recall_at_1000 |
|
value: 84.841 |
|
- type: recall_at_3 |
|
value: 41.016000000000005 |
|
- type: recall_at_5 |
|
value: 46.22 |
|
- type: map_at_1 |
|
value: 42.675000000000004 |
|
- type: map_at_10 |
|
value: 53.93599999999999 |
|
- type: map_at_100 |
|
value: 54.806999999999995 |
|
- type: map_at_1000 |
|
value: 54.867 |
|
- type: map_at_3 |
|
value: 50.934000000000005 |
|
- type: map_at_5 |
|
value: 52.583 |
|
- type: mrr_at_1 |
|
value: 48.339 |
|
- type: mrr_at_10 |
|
value: 57.265 |
|
- type: mrr_at_100 |
|
value: 57.873 |
|
- type: mrr_at_1000 |
|
value: 57.906 |
|
- type: mrr_at_3 |
|
value: 55.193000000000005 |
|
- type: mrr_at_5 |
|
value: 56.303000000000004 |
|
- type: ndcg_at_1 |
|
value: 48.339 |
|
- type: ndcg_at_10 |
|
value: 59.19799999999999 |
|
- type: ndcg_at_100 |
|
value: 62.743 |
|
- type: ndcg_at_1000 |
|
value: 63.99399999999999 |
|
- type: ndcg_at_3 |
|
value: 54.367 |
|
- type: ndcg_at_5 |
|
value: 56.548 |
|
- type: precision_at_1 |
|
value: 48.339 |
|
- type: precision_at_10 |
|
value: 9.216000000000001 |
|
- type: precision_at_100 |
|
value: 1.1809999999999998 |
|
- type: precision_at_1000 |
|
value: 0.134 |
|
- type: precision_at_3 |
|
value: 23.72 |
|
- type: precision_at_5 |
|
value: 16.025 |
|
- type: recall_at_1 |
|
value: 42.675000000000004 |
|
- type: recall_at_10 |
|
value: 71.437 |
|
- type: recall_at_100 |
|
value: 86.803 |
|
- type: recall_at_1000 |
|
value: 95.581 |
|
- type: recall_at_3 |
|
value: 58.434 |
|
- type: recall_at_5 |
|
value: 63.754 |
|
- type: map_at_1 |
|
value: 23.518 |
|
- type: map_at_10 |
|
value: 30.648999999999997 |
|
- type: map_at_100 |
|
value: 31.508999999999997 |
|
- type: map_at_1000 |
|
value: 31.604 |
|
- type: map_at_3 |
|
value: 28.247 |
|
- type: map_at_5 |
|
value: 29.65 |
|
- type: mrr_at_1 |
|
value: 25.650000000000002 |
|
- type: mrr_at_10 |
|
value: 32.771 |
|
- type: mrr_at_100 |
|
value: 33.554 |
|
- type: mrr_at_1000 |
|
value: 33.629999999999995 |
|
- type: mrr_at_3 |
|
value: 30.433 |
|
- type: mrr_at_5 |
|
value: 31.812 |
|
- type: ndcg_at_1 |
|
value: 25.650000000000002 |
|
- type: ndcg_at_10 |
|
value: 34.929 |
|
- type: ndcg_at_100 |
|
value: 39.382 |
|
- type: ndcg_at_1000 |
|
value: 41.913 |
|
- type: ndcg_at_3 |
|
value: 30.292 |
|
- type: ndcg_at_5 |
|
value: 32.629999999999995 |
|
- type: precision_at_1 |
|
value: 25.650000000000002 |
|
- type: precision_at_10 |
|
value: 5.311 |
|
- type: precision_at_100 |
|
value: 0.792 |
|
- type: precision_at_1000 |
|
value: 0.105 |
|
- type: precision_at_3 |
|
value: 12.58 |
|
- type: precision_at_5 |
|
value: 8.994 |
|
- type: recall_at_1 |
|
value: 23.518 |
|
- type: recall_at_10 |
|
value: 46.19 |
|
- type: recall_at_100 |
|
value: 67.123 |
|
- type: recall_at_1000 |
|
value: 86.442 |
|
- type: recall_at_3 |
|
value: 33.678000000000004 |
|
- type: recall_at_5 |
|
value: 39.244 |
|
- type: map_at_1 |
|
value: 15.891 |
|
- type: map_at_10 |
|
value: 22.464000000000002 |
|
- type: map_at_100 |
|
value: 23.483 |
|
- type: map_at_1000 |
|
value: 23.613 |
|
- type: map_at_3 |
|
value: 20.080000000000002 |
|
- type: map_at_5 |
|
value: 21.526 |
|
- type: mrr_at_1 |
|
value: 20.025000000000002 |
|
- type: mrr_at_10 |
|
value: 26.712999999999997 |
|
- type: mrr_at_100 |
|
value: 27.650000000000002 |
|
- type: mrr_at_1000 |
|
value: 27.737000000000002 |
|
- type: mrr_at_3 |
|
value: 24.274 |
|
- type: mrr_at_5 |
|
value: 25.711000000000002 |
|
- type: ndcg_at_1 |
|
value: 20.025000000000002 |
|
- type: ndcg_at_10 |
|
value: 27.028999999999996 |
|
- type: ndcg_at_100 |
|
value: 32.064 |
|
- type: ndcg_at_1000 |
|
value: 35.188 |
|
- type: ndcg_at_3 |
|
value: 22.512999999999998 |
|
- type: ndcg_at_5 |
|
value: 24.89 |
|
- type: precision_at_1 |
|
value: 20.025000000000002 |
|
- type: precision_at_10 |
|
value: 4.776 |
|
- type: precision_at_100 |
|
value: 0.8500000000000001 |
|
- type: precision_at_1000 |
|
value: 0.125 |
|
- type: precision_at_3 |
|
value: 10.531 |
|
- type: precision_at_5 |
|
value: 7.811 |
|
- type: recall_at_1 |
|
value: 15.891 |
|
- type: recall_at_10 |
|
value: 37.261 |
|
- type: recall_at_100 |
|
value: 59.12 |
|
- type: recall_at_1000 |
|
value: 81.356 |
|
- type: recall_at_3 |
|
value: 24.741 |
|
- type: recall_at_5 |
|
value: 30.753999999999998 |
|
- type: map_at_1 |
|
value: 27.544 |
|
- type: map_at_10 |
|
value: 36.283 |
|
- type: map_at_100 |
|
value: 37.467 |
|
- type: map_at_1000 |
|
value: 37.574000000000005 |
|
- type: map_at_3 |
|
value: 33.528999999999996 |
|
- type: map_at_5 |
|
value: 35.028999999999996 |
|
- type: mrr_at_1 |
|
value: 34.166999999999994 |
|
- type: mrr_at_10 |
|
value: 41.866 |
|
- type: mrr_at_100 |
|
value: 42.666 |
|
- type: mrr_at_1000 |
|
value: 42.716 |
|
- type: mrr_at_3 |
|
value: 39.541 |
|
- type: mrr_at_5 |
|
value: 40.768 |
|
- type: ndcg_at_1 |
|
value: 34.166999999999994 |
|
- type: ndcg_at_10 |
|
value: 41.577 |
|
- type: ndcg_at_100 |
|
value: 46.687 |
|
- type: ndcg_at_1000 |
|
value: 48.967 |
|
- type: ndcg_at_3 |
|
value: 37.177 |
|
- type: ndcg_at_5 |
|
value: 39.097 |
|
- type: precision_at_1 |
|
value: 34.166999999999994 |
|
- type: precision_at_10 |
|
value: 7.420999999999999 |
|
- type: precision_at_100 |
|
value: 1.165 |
|
- type: precision_at_1000 |
|
value: 0.154 |
|
- type: precision_at_3 |
|
value: 17.291999999999998 |
|
- type: precision_at_5 |
|
value: 12.166 |
|
- type: recall_at_1 |
|
value: 27.544 |
|
- type: recall_at_10 |
|
value: 51.99399999999999 |
|
- type: recall_at_100 |
|
value: 73.738 |
|
- type: recall_at_1000 |
|
value: 89.33 |
|
- type: recall_at_3 |
|
value: 39.179 |
|
- type: recall_at_5 |
|
value: 44.385999999999996 |
|
- type: map_at_1 |
|
value: 26.661 |
|
- type: map_at_10 |
|
value: 35.475 |
|
- type: map_at_100 |
|
value: 36.626999999999995 |
|
- type: map_at_1000 |
|
value: 36.741 |
|
- type: map_at_3 |
|
value: 32.818000000000005 |
|
- type: map_at_5 |
|
value: 34.397 |
|
- type: mrr_at_1 |
|
value: 32.647999999999996 |
|
- type: mrr_at_10 |
|
value: 40.784 |
|
- type: mrr_at_100 |
|
value: 41.602 |
|
- type: mrr_at_1000 |
|
value: 41.661 |
|
- type: mrr_at_3 |
|
value: 38.68 |
|
- type: mrr_at_5 |
|
value: 39.838 |
|
- type: ndcg_at_1 |
|
value: 32.647999999999996 |
|
- type: ndcg_at_10 |
|
value: 40.697 |
|
- type: ndcg_at_100 |
|
value: 45.799 |
|
- type: ndcg_at_1000 |
|
value: 48.235 |
|
- type: ndcg_at_3 |
|
value: 36.516 |
|
- type: ndcg_at_5 |
|
value: 38.515 |
|
- type: precision_at_1 |
|
value: 32.647999999999996 |
|
- type: precision_at_10 |
|
value: 7.202999999999999 |
|
- type: precision_at_100 |
|
value: 1.1360000000000001 |
|
- type: precision_at_1000 |
|
value: 0.151 |
|
- type: precision_at_3 |
|
value: 17.314 |
|
- type: precision_at_5 |
|
value: 12.145999999999999 |
|
- type: recall_at_1 |
|
value: 26.661 |
|
- type: recall_at_10 |
|
value: 50.995000000000005 |
|
- type: recall_at_100 |
|
value: 73.065 |
|
- type: recall_at_1000 |
|
value: 89.781 |
|
- type: recall_at_3 |
|
value: 39.073 |
|
- type: recall_at_5 |
|
value: 44.395 |
|
- type: map_at_1 |
|
value: 25.946583333333333 |
|
- type: map_at_10 |
|
value: 33.79725 |
|
- type: map_at_100 |
|
value: 34.86408333333333 |
|
- type: map_at_1000 |
|
value: 34.9795 |
|
- type: map_at_3 |
|
value: 31.259999999999998 |
|
- type: map_at_5 |
|
value: 32.71541666666666 |
|
- type: mrr_at_1 |
|
value: 30.863749999999996 |
|
- type: mrr_at_10 |
|
value: 37.99183333333333 |
|
- type: mrr_at_100 |
|
value: 38.790499999999994 |
|
- type: mrr_at_1000 |
|
value: 38.85575000000001 |
|
- type: mrr_at_3 |
|
value: 35.82083333333333 |
|
- type: mrr_at_5 |
|
value: 37.07533333333333 |
|
- type: ndcg_at_1 |
|
value: 30.863749999999996 |
|
- type: ndcg_at_10 |
|
value: 38.52141666666667 |
|
- type: ndcg_at_100 |
|
value: 43.17966666666667 |
|
- type: ndcg_at_1000 |
|
value: 45.64608333333333 |
|
- type: ndcg_at_3 |
|
value: 34.333000000000006 |
|
- type: ndcg_at_5 |
|
value: 36.34975 |
|
- type: precision_at_1 |
|
value: 30.863749999999996 |
|
- type: precision_at_10 |
|
value: 6.598999999999999 |
|
- type: precision_at_100 |
|
value: 1.0502500000000001 |
|
- type: precision_at_1000 |
|
value: 0.14400000000000002 |
|
- type: precision_at_3 |
|
value: 15.557583333333334 |
|
- type: precision_at_5 |
|
value: 11.020000000000001 |
|
- type: recall_at_1 |
|
value: 25.946583333333333 |
|
- type: recall_at_10 |
|
value: 48.36991666666666 |
|
- type: recall_at_100 |
|
value: 69.02408333333334 |
|
- type: recall_at_1000 |
|
value: 86.43858333333331 |
|
- type: recall_at_3 |
|
value: 36.4965 |
|
- type: recall_at_5 |
|
value: 41.76258333333334 |
|
- type: map_at_1 |
|
value: 22.431 |
|
- type: map_at_10 |
|
value: 28.889 |
|
- type: map_at_100 |
|
value: 29.642000000000003 |
|
- type: map_at_1000 |
|
value: 29.742 |
|
- type: map_at_3 |
|
value: 26.998 |
|
- type: map_at_5 |
|
value: 28.172000000000004 |
|
- type: mrr_at_1 |
|
value: 25.307000000000002 |
|
- type: mrr_at_10 |
|
value: 31.763 |
|
- type: mrr_at_100 |
|
value: 32.443 |
|
- type: mrr_at_1000 |
|
value: 32.531 |
|
- type: mrr_at_3 |
|
value: 29.959000000000003 |
|
- type: mrr_at_5 |
|
value: 31.063000000000002 |
|
- type: ndcg_at_1 |
|
value: 25.307000000000002 |
|
- type: ndcg_at_10 |
|
value: 32.586999999999996 |
|
- type: ndcg_at_100 |
|
value: 36.5 |
|
- type: ndcg_at_1000 |
|
value: 39.133 |
|
- type: ndcg_at_3 |
|
value: 29.25 |
|
- type: ndcg_at_5 |
|
value: 31.023 |
|
- type: precision_at_1 |
|
value: 25.307000000000002 |
|
- type: precision_at_10 |
|
value: 4.954 |
|
- type: precision_at_100 |
|
value: 0.747 |
|
- type: precision_at_1000 |
|
value: 0.104 |
|
- type: precision_at_3 |
|
value: 12.577 |
|
- type: precision_at_5 |
|
value: 8.741999999999999 |
|
- type: recall_at_1 |
|
value: 22.431 |
|
- type: recall_at_10 |
|
value: 41.134 |
|
- type: recall_at_100 |
|
value: 59.28600000000001 |
|
- type: recall_at_1000 |
|
value: 78.857 |
|
- type: recall_at_3 |
|
value: 31.926 |
|
- type: recall_at_5 |
|
value: 36.335 |
|
- type: map_at_1 |
|
value: 17.586 |
|
- type: map_at_10 |
|
value: 23.304 |
|
- type: map_at_100 |
|
value: 24.159 |
|
- type: map_at_1000 |
|
value: 24.281 |
|
- type: map_at_3 |
|
value: 21.316 |
|
- type: map_at_5 |
|
value: 22.383 |
|
- type: mrr_at_1 |
|
value: 21.645 |
|
- type: mrr_at_10 |
|
value: 27.365000000000002 |
|
- type: mrr_at_100 |
|
value: 28.108 |
|
- type: mrr_at_1000 |
|
value: 28.192 |
|
- type: mrr_at_3 |
|
value: 25.482 |
|
- type: mrr_at_5 |
|
value: 26.479999999999997 |
|
- type: ndcg_at_1 |
|
value: 21.645 |
|
- type: ndcg_at_10 |
|
value: 27.306 |
|
- type: ndcg_at_100 |
|
value: 31.496000000000002 |
|
- type: ndcg_at_1000 |
|
value: 34.53 |
|
- type: ndcg_at_3 |
|
value: 23.73 |
|
- type: ndcg_at_5 |
|
value: 25.294 |
|
- type: precision_at_1 |
|
value: 21.645 |
|
- type: precision_at_10 |
|
value: 4.797 |
|
- type: precision_at_100 |
|
value: 0.8059999999999999 |
|
- type: precision_at_1000 |
|
value: 0.121 |
|
- type: precision_at_3 |
|
value: 10.850999999999999 |
|
- type: precision_at_5 |
|
value: 7.736 |
|
- type: recall_at_1 |
|
value: 17.586 |
|
- type: recall_at_10 |
|
value: 35.481 |
|
- type: recall_at_100 |
|
value: 54.534000000000006 |
|
- type: recall_at_1000 |
|
value: 76.456 |
|
- type: recall_at_3 |
|
value: 25.335 |
|
- type: recall_at_5 |
|
value: 29.473 |
|
- type: map_at_1 |
|
value: 25.095 |
|
- type: map_at_10 |
|
value: 32.374 |
|
- type: map_at_100 |
|
value: 33.537 |
|
- type: map_at_1000 |
|
value: 33.634 |
|
- type: map_at_3 |
|
value: 30.089 |
|
- type: map_at_5 |
|
value: 31.433 |
|
- type: mrr_at_1 |
|
value: 29.198 |
|
- type: mrr_at_10 |
|
value: 36.01 |
|
- type: mrr_at_100 |
|
value: 37.022 |
|
- type: mrr_at_1000 |
|
value: 37.083 |
|
- type: mrr_at_3 |
|
value: 33.94 |
|
- type: mrr_at_5 |
|
value: 35.148 |
|
- type: ndcg_at_1 |
|
value: 29.198 |
|
- type: ndcg_at_10 |
|
value: 36.729 |
|
- type: ndcg_at_100 |
|
value: 42.114000000000004 |
|
- type: ndcg_at_1000 |
|
value: 44.592 |
|
- type: ndcg_at_3 |
|
value: 32.644 |
|
- type: ndcg_at_5 |
|
value: 34.652 |
|
- type: precision_at_1 |
|
value: 29.198 |
|
- type: precision_at_10 |
|
value: 5.970000000000001 |
|
- type: precision_at_100 |
|
value: 0.967 |
|
- type: precision_at_1000 |
|
value: 0.129 |
|
- type: precision_at_3 |
|
value: 14.396999999999998 |
|
- type: precision_at_5 |
|
value: 10.093 |
|
- type: recall_at_1 |
|
value: 25.095 |
|
- type: recall_at_10 |
|
value: 46.392 |
|
- type: recall_at_100 |
|
value: 69.706 |
|
- type: recall_at_1000 |
|
value: 87.738 |
|
- type: recall_at_3 |
|
value: 35.303000000000004 |
|
- type: recall_at_5 |
|
value: 40.441 |
|
- type: map_at_1 |
|
value: 26.857999999999997 |
|
- type: map_at_10 |
|
value: 34.066 |
|
- type: map_at_100 |
|
value: 35.671 |
|
- type: map_at_1000 |
|
value: 35.881 |
|
- type: map_at_3 |
|
value: 31.304 |
|
- type: map_at_5 |
|
value: 32.885 |
|
- type: mrr_at_1 |
|
value: 32.411 |
|
- type: mrr_at_10 |
|
value: 38.987 |
|
- type: mrr_at_100 |
|
value: 39.894 |
|
- type: mrr_at_1000 |
|
value: 39.959 |
|
- type: mrr_at_3 |
|
value: 36.626999999999995 |
|
- type: mrr_at_5 |
|
value: 38.011 |
|
- type: ndcg_at_1 |
|
value: 32.411 |
|
- type: ndcg_at_10 |
|
value: 39.208 |
|
- type: ndcg_at_100 |
|
value: 44.626 |
|
- type: ndcg_at_1000 |
|
value: 47.43 |
|
- type: ndcg_at_3 |
|
value: 35.091 |
|
- type: ndcg_at_5 |
|
value: 37.119 |
|
- type: precision_at_1 |
|
value: 32.411 |
|
- type: precision_at_10 |
|
value: 7.51 |
|
- type: precision_at_100 |
|
value: 1.486 |
|
- type: precision_at_1000 |
|
value: 0.234 |
|
- type: precision_at_3 |
|
value: 16.14 |
|
- type: precision_at_5 |
|
value: 11.976 |
|
- type: recall_at_1 |
|
value: 26.857999999999997 |
|
- type: recall_at_10 |
|
value: 47.407 |
|
- type: recall_at_100 |
|
value: 72.236 |
|
- type: recall_at_1000 |
|
value: 90.77 |
|
- type: recall_at_3 |
|
value: 35.125 |
|
- type: recall_at_5 |
|
value: 40.522999999999996 |
|
- type: map_at_1 |
|
value: 21.3 |
|
- type: map_at_10 |
|
value: 27.412999999999997 |
|
- type: map_at_100 |
|
value: 28.29 |
|
- type: map_at_1000 |
|
value: 28.398 |
|
- type: map_at_3 |
|
value: 25.169999999999998 |
|
- type: map_at_5 |
|
value: 26.496 |
|
- type: mrr_at_1 |
|
value: 23.29 |
|
- type: mrr_at_10 |
|
value: 29.215000000000003 |
|
- type: mrr_at_100 |
|
value: 30.073 |
|
- type: mrr_at_1000 |
|
value: 30.156 |
|
- type: mrr_at_3 |
|
value: 26.956000000000003 |
|
- type: mrr_at_5 |
|
value: 28.38 |
|
- type: ndcg_at_1 |
|
value: 23.29 |
|
- type: ndcg_at_10 |
|
value: 31.113000000000003 |
|
- type: ndcg_at_100 |
|
value: 35.701 |
|
- type: ndcg_at_1000 |
|
value: 38.505 |
|
- type: ndcg_at_3 |
|
value: 26.727 |
|
- type: ndcg_at_5 |
|
value: 29.037000000000003 |
|
- type: precision_at_1 |
|
value: 23.29 |
|
- type: precision_at_10 |
|
value: 4.787 |
|
- type: precision_at_100 |
|
value: 0.763 |
|
- type: precision_at_1000 |
|
value: 0.11100000000000002 |
|
- type: precision_at_3 |
|
value: 11.091 |
|
- type: precision_at_5 |
|
value: 7.985 |
|
- type: recall_at_1 |
|
value: 21.3 |
|
- type: recall_at_10 |
|
value: 40.782000000000004 |
|
- type: recall_at_100 |
|
value: 62.13999999999999 |
|
- type: recall_at_1000 |
|
value: 83.012 |
|
- type: recall_at_3 |
|
value: 29.131 |
|
- type: recall_at_5 |
|
value: 34.624 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB ClimateFEVER |
|
type: climate-fever |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 9.631 |
|
- type: map_at_10 |
|
value: 16.634999999999998 |
|
- type: map_at_100 |
|
value: 18.23 |
|
- type: map_at_1000 |
|
value: 18.419 |
|
- type: map_at_3 |
|
value: 13.66 |
|
- type: map_at_5 |
|
value: 15.173 |
|
- type: mrr_at_1 |
|
value: 21.368000000000002 |
|
- type: mrr_at_10 |
|
value: 31.56 |
|
- type: mrr_at_100 |
|
value: 32.58 |
|
- type: mrr_at_1000 |
|
value: 32.633 |
|
- type: mrr_at_3 |
|
value: 28.241 |
|
- type: mrr_at_5 |
|
value: 30.225 |
|
- type: ndcg_at_1 |
|
value: 21.368000000000002 |
|
- type: ndcg_at_10 |
|
value: 23.855999999999998 |
|
- type: ndcg_at_100 |
|
value: 30.686999999999998 |
|
- type: ndcg_at_1000 |
|
value: 34.327000000000005 |
|
- type: ndcg_at_3 |
|
value: 18.781 |
|
- type: ndcg_at_5 |
|
value: 20.73 |
|
- type: precision_at_1 |
|
value: 21.368000000000002 |
|
- type: precision_at_10 |
|
value: 7.564 |
|
- type: precision_at_100 |
|
value: 1.496 |
|
- type: precision_at_1000 |
|
value: 0.217 |
|
- type: precision_at_3 |
|
value: 13.876 |
|
- type: precision_at_5 |
|
value: 11.062 |
|
- type: recall_at_1 |
|
value: 9.631 |
|
- type: recall_at_10 |
|
value: 29.517 |
|
- type: recall_at_100 |
|
value: 53.452 |
|
- type: recall_at_1000 |
|
value: 74.115 |
|
- type: recall_at_3 |
|
value: 17.605999999999998 |
|
- type: recall_at_5 |
|
value: 22.505 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB DBPedia |
|
type: dbpedia-entity |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.885 |
|
- type: map_at_10 |
|
value: 18.798000000000002 |
|
- type: map_at_100 |
|
value: 26.316 |
|
- type: map_at_1000 |
|
value: 27.869 |
|
- type: map_at_3 |
|
value: 13.719000000000001 |
|
- type: map_at_5 |
|
value: 15.716 |
|
- type: mrr_at_1 |
|
value: 66 |
|
- type: mrr_at_10 |
|
value: 74.263 |
|
- type: mrr_at_100 |
|
value: 74.519 |
|
- type: mrr_at_1000 |
|
value: 74.531 |
|
- type: mrr_at_3 |
|
value: 72.458 |
|
- type: mrr_at_5 |
|
value: 73.321 |
|
- type: ndcg_at_1 |
|
value: 53.87499999999999 |
|
- type: ndcg_at_10 |
|
value: 40.355999999999995 |
|
- type: ndcg_at_100 |
|
value: 44.366 |
|
- type: ndcg_at_1000 |
|
value: 51.771 |
|
- type: ndcg_at_3 |
|
value: 45.195 |
|
- type: ndcg_at_5 |
|
value: 42.187000000000005 |
|
- type: precision_at_1 |
|
value: 66 |
|
- type: precision_at_10 |
|
value: 31.75 |
|
- type: precision_at_100 |
|
value: 10.11 |
|
- type: precision_at_1000 |
|
value: 1.9800000000000002 |
|
- type: precision_at_3 |
|
value: 48.167 |
|
- type: precision_at_5 |
|
value: 40.050000000000004 |
|
- type: recall_at_1 |
|
value: 8.885 |
|
- type: recall_at_10 |
|
value: 24.471999999999998 |
|
- type: recall_at_100 |
|
value: 49.669000000000004 |
|
- type: recall_at_1000 |
|
value: 73.383 |
|
- type: recall_at_3 |
|
value: 14.872 |
|
- type: recall_at_5 |
|
value: 18.262999999999998 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB EmotionClassification |
|
type: mteb/emotion |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 45.18 |
|
- type: f1 |
|
value: 40.26878691789978 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB FEVER |
|
type: fever |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 62.751999999999995 |
|
- type: map_at_10 |
|
value: 74.131 |
|
- type: map_at_100 |
|
value: 74.407 |
|
- type: map_at_1000 |
|
value: 74.423 |
|
- type: map_at_3 |
|
value: 72.329 |
|
- type: map_at_5 |
|
value: 73.555 |
|
- type: mrr_at_1 |
|
value: 67.282 |
|
- type: mrr_at_10 |
|
value: 78.292 |
|
- type: mrr_at_100 |
|
value: 78.455 |
|
- type: mrr_at_1000 |
|
value: 78.458 |
|
- type: mrr_at_3 |
|
value: 76.755 |
|
- type: mrr_at_5 |
|
value: 77.839 |
|
- type: ndcg_at_1 |
|
value: 67.282 |
|
- type: ndcg_at_10 |
|
value: 79.443 |
|
- type: ndcg_at_100 |
|
value: 80.529 |
|
- type: ndcg_at_1000 |
|
value: 80.812 |
|
- type: ndcg_at_3 |
|
value: 76.281 |
|
- type: ndcg_at_5 |
|
value: 78.235 |
|
- type: precision_at_1 |
|
value: 67.282 |
|
- type: precision_at_10 |
|
value: 10.078 |
|
- type: precision_at_100 |
|
value: 1.082 |
|
- type: precision_at_1000 |
|
value: 0.11199999999999999 |
|
- type: precision_at_3 |
|
value: 30.178 |
|
- type: precision_at_5 |
|
value: 19.232 |
|
- type: recall_at_1 |
|
value: 62.751999999999995 |
|
- type: recall_at_10 |
|
value: 91.521 |
|
- type: recall_at_100 |
|
value: 95.997 |
|
- type: recall_at_1000 |
|
value: 97.775 |
|
- type: recall_at_3 |
|
value: 83.131 |
|
- type: recall_at_5 |
|
value: 87.93299999999999 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB FiQA2018 |
|
type: fiqa |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.861 |
|
- type: map_at_10 |
|
value: 30.252000000000002 |
|
- type: map_at_100 |
|
value: 32.082 |
|
- type: map_at_1000 |
|
value: 32.261 |
|
- type: map_at_3 |
|
value: 25.909 |
|
- type: map_at_5 |
|
value: 28.296 |
|
- type: mrr_at_1 |
|
value: 37.346000000000004 |
|
- type: mrr_at_10 |
|
value: 45.802 |
|
- type: mrr_at_100 |
|
value: 46.611999999999995 |
|
- type: mrr_at_1000 |
|
value: 46.659 |
|
- type: mrr_at_3 |
|
value: 43.056 |
|
- type: mrr_at_5 |
|
value: 44.637 |
|
- type: ndcg_at_1 |
|
value: 37.346000000000004 |
|
- type: ndcg_at_10 |
|
value: 38.169 |
|
- type: ndcg_at_100 |
|
value: 44.864 |
|
- type: ndcg_at_1000 |
|
value: 47.974 |
|
- type: ndcg_at_3 |
|
value: 33.619 |
|
- type: ndcg_at_5 |
|
value: 35.317 |
|
- type: precision_at_1 |
|
value: 37.346000000000004 |
|
- type: precision_at_10 |
|
value: 10.693999999999999 |
|
- type: precision_at_100 |
|
value: 1.775 |
|
- type: precision_at_1000 |
|
value: 0.231 |
|
- type: precision_at_3 |
|
value: 22.325 |
|
- type: precision_at_5 |
|
value: 16.852 |
|
- type: recall_at_1 |
|
value: 18.861 |
|
- type: recall_at_10 |
|
value: 45.672000000000004 |
|
- type: recall_at_100 |
|
value: 70.60499999999999 |
|
- type: recall_at_1000 |
|
value: 89.216 |
|
- type: recall_at_3 |
|
value: 30.361 |
|
- type: recall_at_5 |
|
value: 36.998999999999995 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB HotpotQA |
|
type: hotpotqa |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 37.852999999999994 |
|
- type: map_at_10 |
|
value: 59.961 |
|
- type: map_at_100 |
|
value: 60.78 |
|
- type: map_at_1000 |
|
value: 60.843 |
|
- type: map_at_3 |
|
value: 56.39999999999999 |
|
- type: map_at_5 |
|
value: 58.646 |
|
- type: mrr_at_1 |
|
value: 75.70599999999999 |
|
- type: mrr_at_10 |
|
value: 82.321 |
|
- type: mrr_at_100 |
|
value: 82.516 |
|
- type: mrr_at_1000 |
|
value: 82.525 |
|
- type: mrr_at_3 |
|
value: 81.317 |
|
- type: mrr_at_5 |
|
value: 81.922 |
|
- type: ndcg_at_1 |
|
value: 75.70599999999999 |
|
- type: ndcg_at_10 |
|
value: 68.557 |
|
- type: ndcg_at_100 |
|
value: 71.485 |
|
- type: ndcg_at_1000 |
|
value: 72.71600000000001 |
|
- type: ndcg_at_3 |
|
value: 63.524 |
|
- type: ndcg_at_5 |
|
value: 66.338 |
|
- type: precision_at_1 |
|
value: 75.70599999999999 |
|
- type: precision_at_10 |
|
value: 14.463000000000001 |
|
- type: precision_at_100 |
|
value: 1.677 |
|
- type: precision_at_1000 |
|
value: 0.184 |
|
- type: precision_at_3 |
|
value: 40.806 |
|
- type: precision_at_5 |
|
value: 26.709 |
|
- type: recall_at_1 |
|
value: 37.852999999999994 |
|
- type: recall_at_10 |
|
value: 72.316 |
|
- type: recall_at_100 |
|
value: 83.842 |
|
- type: recall_at_1000 |
|
value: 91.999 |
|
- type: recall_at_3 |
|
value: 61.209 |
|
- type: recall_at_5 |
|
value: 66.77199999999999 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB ImdbClassification |
|
type: mteb/imdb |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 85.46039999999999 |
|
- type: ap |
|
value: 79.9812521351881 |
|
- type: f1 |
|
value: 85.31722909702084 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB MSMARCO |
|
type: msmarco |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.704 |
|
- type: map_at_10 |
|
value: 35.329 |
|
- type: map_at_100 |
|
value: 36.494 |
|
- type: map_at_1000 |
|
value: 36.541000000000004 |
|
- type: map_at_3 |
|
value: 31.476 |
|
- type: map_at_5 |
|
value: 33.731 |
|
- type: mrr_at_1 |
|
value: 23.294999999999998 |
|
- type: mrr_at_10 |
|
value: 35.859 |
|
- type: mrr_at_100 |
|
value: 36.968 |
|
- type: mrr_at_1000 |
|
value: 37.008 |
|
- type: mrr_at_3 |
|
value: 32.085 |
|
- type: mrr_at_5 |
|
value: 34.299 |
|
- type: ndcg_at_1 |
|
value: 23.324 |
|
- type: ndcg_at_10 |
|
value: 42.274 |
|
- type: ndcg_at_100 |
|
value: 47.839999999999996 |
|
- type: ndcg_at_1000 |
|
value: 48.971 |
|
- type: ndcg_at_3 |
|
value: 34.454 |
|
- type: ndcg_at_5 |
|
value: 38.464 |
|
- type: precision_at_1 |
|
value: 23.324 |
|
- type: precision_at_10 |
|
value: 6.648 |
|
- type: precision_at_100 |
|
value: 0.9440000000000001 |
|
- type: precision_at_1000 |
|
value: 0.104 |
|
- type: precision_at_3 |
|
value: 14.674999999999999 |
|
- type: precision_at_5 |
|
value: 10.850999999999999 |
|
- type: recall_at_1 |
|
value: 22.704 |
|
- type: recall_at_10 |
|
value: 63.660000000000004 |
|
- type: recall_at_100 |
|
value: 89.29899999999999 |
|
- type: recall_at_1000 |
|
value: 97.88900000000001 |
|
- type: recall_at_3 |
|
value: 42.441 |
|
- type: recall_at_5 |
|
value: 52.04 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPDomainClassification (en) |
|
type: mteb/mtop_domain |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 93.1326949384405 |
|
- type: f1 |
|
value: 92.89743579612082 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPDomainClassification (de) |
|
type: mteb/mtop_domain |
|
config: de |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 89.62524654832347 |
|
- type: f1 |
|
value: 88.65106082263151 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPDomainClassification (es) |
|
type: mteb/mtop_domain |
|
config: es |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 90.59039359573046 |
|
- type: f1 |
|
value: 90.31532892105662 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPDomainClassification (fr) |
|
type: mteb/mtop_domain |
|
config: fr |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 86.21046038208581 |
|
- type: f1 |
|
value: 86.41459529813113 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPDomainClassification (hi) |
|
type: mteb/mtop_domain |
|
config: hi |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 87.3180351380423 |
|
- type: f1 |
|
value: 86.71383078226444 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPDomainClassification (th) |
|
type: mteb/mtop_domain |
|
config: th |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 86.24231464737792 |
|
- type: f1 |
|
value: 86.31845567592403 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPIntentClassification (en) |
|
type: mteb/mtop_intent |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 75.27131782945736 |
|
- type: f1 |
|
value: 57.52079940417103 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPIntentClassification (de) |
|
type: mteb/mtop_intent |
|
config: de |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 71.2341504649197 |
|
- type: f1 |
|
value: 51.349951558039244 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPIntentClassification (es) |
|
type: mteb/mtop_intent |
|
config: es |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 71.27418278852569 |
|
- type: f1 |
|
value: 50.1714985749095 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPIntentClassification (fr) |
|
type: mteb/mtop_intent |
|
config: fr |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 67.68243031631694 |
|
- type: f1 |
|
value: 50.1066160836192 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPIntentClassification (hi) |
|
type: mteb/mtop_intent |
|
config: hi |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 69.2362854069559 |
|
- type: f1 |
|
value: 48.821279948766424 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPIntentClassification (th) |
|
type: mteb/mtop_intent |
|
config: th |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 71.71428571428571 |
|
- type: f1 |
|
value: 53.94611389496195 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (af) |
|
type: mteb/amazon_massive_intent |
|
config: af |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 59.97646267652992 |
|
- type: f1 |
|
value: 57.26797883561521 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (am) |
|
type: mteb/amazon_massive_intent |
|
config: am |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 53.65501008742435 |
|
- type: f1 |
|
value: 50.416258382177034 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (ar) |
|
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value: 62.58574310692671 |
|
- type: f1 |
|
value: 60.71443370385374 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveScenarioClassification (th) |
|
type: mteb/amazon_massive_scenario |
|
config: th |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 71.61398789509079 |
|
- type: f1 |
|
value: 70.99761812049401 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveScenarioClassification (tl) |
|
type: mteb/amazon_massive_scenario |
|
config: tl |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 62.73705447209146 |
|
- type: f1 |
|
value: 61.680849331794796 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveScenarioClassification (tr) |
|
type: mteb/amazon_massive_scenario |
|
config: tr |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 71.66778749159381 |
|
- type: f1 |
|
value: 71.17320646080115 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveScenarioClassification (ur) |
|
type: mteb/amazon_massive_scenario |
|
config: ur |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 64.640215198386 |
|
- type: f1 |
|
value: 63.301805157015444 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveScenarioClassification (vi) |
|
type: mteb/amazon_massive_scenario |
|
config: vi |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 70.00672494956288 |
|
- type: f1 |
|
value: 70.26005548582106 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveScenarioClassification (zh-CN) |
|
type: mteb/amazon_massive_scenario |
|
config: zh-CN |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 75.42030934767989 |
|
- type: f1 |
|
value: 75.2074842882598 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveScenarioClassification (zh-TW) |
|
type: mteb/amazon_massive_scenario |
|
config: zh-TW |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 70.69266980497646 |
|
- type: f1 |
|
value: 70.94103167391192 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB MedrxivClusteringP2P |
|
type: mteb/medrxiv-clustering-p2p |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 28.91697191169135 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB MedrxivClusteringS2S |
|
type: mteb/medrxiv-clustering-s2s |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 28.434000079573313 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB MindSmallReranking |
|
type: mteb/mind_small |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 30.96683513343383 |
|
- type: mrr |
|
value: 31.967364078714834 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB NFCorpus |
|
type: nfcorpus |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.5280000000000005 |
|
- type: map_at_10 |
|
value: 11.793 |
|
- type: map_at_100 |
|
value: 14.496999999999998 |
|
- type: map_at_1000 |
|
value: 15.783 |
|
- type: map_at_3 |
|
value: 8.838 |
|
- type: map_at_5 |
|
value: 10.07 |
|
- type: mrr_at_1 |
|
value: 43.653 |
|
- type: mrr_at_10 |
|
value: 51.531000000000006 |
|
- type: mrr_at_100 |
|
value: 52.205 |
|
- type: mrr_at_1000 |
|
value: 52.242999999999995 |
|
- type: mrr_at_3 |
|
value: 49.431999999999995 |
|
- type: mrr_at_5 |
|
value: 50.470000000000006 |
|
- type: ndcg_at_1 |
|
value: 42.415000000000006 |
|
- type: ndcg_at_10 |
|
value: 32.464999999999996 |
|
- type: ndcg_at_100 |
|
value: 28.927999999999997 |
|
- type: ndcg_at_1000 |
|
value: 37.629000000000005 |
|
- type: ndcg_at_3 |
|
value: 37.845 |
|
- type: ndcg_at_5 |
|
value: 35.147 |
|
- type: precision_at_1 |
|
value: 43.653 |
|
- type: precision_at_10 |
|
value: 23.932000000000002 |
|
- type: precision_at_100 |
|
value: 7.17 |
|
- type: precision_at_1000 |
|
value: 1.967 |
|
- type: precision_at_3 |
|
value: 35.397 |
|
- type: precision_at_5 |
|
value: 29.907 |
|
- type: recall_at_1 |
|
value: 5.5280000000000005 |
|
- type: recall_at_10 |
|
value: 15.568000000000001 |
|
- type: recall_at_100 |
|
value: 28.54 |
|
- type: recall_at_1000 |
|
value: 59.864 |
|
- type: recall_at_3 |
|
value: 9.822000000000001 |
|
- type: recall_at_5 |
|
value: 11.726 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB NQ |
|
type: nq |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 37.041000000000004 |
|
- type: map_at_10 |
|
value: 52.664 |
|
- type: map_at_100 |
|
value: 53.477 |
|
- type: map_at_1000 |
|
value: 53.505 |
|
- type: map_at_3 |
|
value: 48.510999999999996 |
|
- type: map_at_5 |
|
value: 51.036 |
|
- type: mrr_at_1 |
|
value: 41.338 |
|
- type: mrr_at_10 |
|
value: 55.071000000000005 |
|
- type: mrr_at_100 |
|
value: 55.672 |
|
- type: mrr_at_1000 |
|
value: 55.689 |
|
- type: mrr_at_3 |
|
value: 51.82 |
|
- type: mrr_at_5 |
|
value: 53.852 |
|
- type: ndcg_at_1 |
|
value: 41.338 |
|
- type: ndcg_at_10 |
|
value: 60.01800000000001 |
|
- type: ndcg_at_100 |
|
value: 63.409000000000006 |
|
- type: ndcg_at_1000 |
|
value: 64.017 |
|
- type: ndcg_at_3 |
|
value: 52.44799999999999 |
|
- type: ndcg_at_5 |
|
value: 56.571000000000005 |
|
- type: precision_at_1 |
|
value: 41.338 |
|
- type: precision_at_10 |
|
value: 9.531 |
|
- type: precision_at_100 |
|
value: 1.145 |
|
- type: precision_at_1000 |
|
value: 0.12 |
|
- type: precision_at_3 |
|
value: 23.416 |
|
- type: precision_at_5 |
|
value: 16.46 |
|
- type: recall_at_1 |
|
value: 37.041000000000004 |
|
- type: recall_at_10 |
|
value: 79.76299999999999 |
|
- type: recall_at_100 |
|
value: 94.39 |
|
- type: recall_at_1000 |
|
value: 98.851 |
|
- type: recall_at_3 |
|
value: 60.465 |
|
- type: recall_at_5 |
|
value: 69.906 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB QuoraRetrieval |
|
type: quora |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 69.952 |
|
- type: map_at_10 |
|
value: 83.758 |
|
- type: map_at_100 |
|
value: 84.406 |
|
- type: map_at_1000 |
|
value: 84.425 |
|
- type: map_at_3 |
|
value: 80.839 |
|
- type: map_at_5 |
|
value: 82.646 |
|
- type: mrr_at_1 |
|
value: 80.62 |
|
- type: mrr_at_10 |
|
value: 86.947 |
|
- type: mrr_at_100 |
|
value: 87.063 |
|
- type: mrr_at_1000 |
|
value: 87.064 |
|
- type: mrr_at_3 |
|
value: 85.96000000000001 |
|
- type: mrr_at_5 |
|
value: 86.619 |
|
- type: ndcg_at_1 |
|
value: 80.63 |
|
- type: ndcg_at_10 |
|
value: 87.64800000000001 |
|
- type: ndcg_at_100 |
|
value: 88.929 |
|
- type: ndcg_at_1000 |
|
value: 89.054 |
|
- type: ndcg_at_3 |
|
value: 84.765 |
|
- type: ndcg_at_5 |
|
value: 86.291 |
|
- type: precision_at_1 |
|
value: 80.63 |
|
- type: precision_at_10 |
|
value: 13.314 |
|
- type: precision_at_100 |
|
value: 1.525 |
|
- type: precision_at_1000 |
|
value: 0.157 |
|
- type: precision_at_3 |
|
value: 37.1 |
|
- type: precision_at_5 |
|
value: 24.372 |
|
- type: recall_at_1 |
|
value: 69.952 |
|
- type: recall_at_10 |
|
value: 94.955 |
|
- type: recall_at_100 |
|
value: 99.38 |
|
- type: recall_at_1000 |
|
value: 99.96000000000001 |
|
- type: recall_at_3 |
|
value: 86.60600000000001 |
|
- type: recall_at_5 |
|
value: 90.997 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB RedditClustering |
|
type: mteb/reddit-clustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 42.41329517878427 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB RedditClusteringP2P |
|
type: mteb/reddit-clustering-p2p |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 55.171278362748666 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB SCIDOCS |
|
type: scidocs |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.213 |
|
- type: map_at_10 |
|
value: 9.895 |
|
- type: map_at_100 |
|
value: 11.776 |
|
- type: map_at_1000 |
|
value: 12.084 |
|
- type: map_at_3 |
|
value: 7.2669999999999995 |
|
- type: map_at_5 |
|
value: 8.620999999999999 |
|
- type: mrr_at_1 |
|
value: 20.8 |
|
- type: mrr_at_10 |
|
value: 31.112000000000002 |
|
- type: mrr_at_100 |
|
value: 32.274 |
|
- type: mrr_at_1000 |
|
value: 32.35 |
|
- type: mrr_at_3 |
|
value: 28.133000000000003 |
|
- type: mrr_at_5 |
|
value: 29.892999999999997 |
|
- type: ndcg_at_1 |
|
value: 20.8 |
|
- type: ndcg_at_10 |
|
value: 17.163999999999998 |
|
- type: ndcg_at_100 |
|
value: 24.738 |
|
- type: ndcg_at_1000 |
|
value: 30.316 |
|
- type: ndcg_at_3 |
|
value: 16.665 |
|
- type: ndcg_at_5 |
|
value: 14.478 |
|
- type: precision_at_1 |
|
value: 20.8 |
|
- type: precision_at_10 |
|
value: 8.74 |
|
- type: precision_at_100 |
|
value: 1.963 |
|
- type: precision_at_1000 |
|
value: 0.33 |
|
- type: precision_at_3 |
|
value: 15.467 |
|
- type: precision_at_5 |
|
value: 12.6 |
|
- type: recall_at_1 |
|
value: 4.213 |
|
- type: recall_at_10 |
|
value: 17.698 |
|
- type: recall_at_100 |
|
value: 39.838 |
|
- type: recall_at_1000 |
|
value: 66.893 |
|
- type: recall_at_3 |
|
value: 9.418 |
|
- type: recall_at_5 |
|
value: 12.773000000000001 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB SICK-R |
|
type: mteb/sickr-sts |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.90453315738294 |
|
- type: cos_sim_spearman |
|
value: 78.51197850080254 |
|
- type: euclidean_pearson |
|
value: 80.09647123597748 |
|
- type: euclidean_spearman |
|
value: 78.63548011514061 |
|
- type: manhattan_pearson |
|
value: 80.10645285675231 |
|
- type: manhattan_spearman |
|
value: 78.57861806068901 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS12 |
|
type: mteb/sts12-sts |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.2616156846401 |
|
- type: cos_sim_spearman |
|
value: 76.69713867850156 |
|
- type: euclidean_pearson |
|
value: 77.97948563800394 |
|
- type: euclidean_spearman |
|
value: 74.2371211567807 |
|
- type: manhattan_pearson |
|
value: 77.69697879669705 |
|
- type: manhattan_spearman |
|
value: 73.86529778022278 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS13 |
|
type: mteb/sts13-sts |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.0293269315045 |
|
- type: cos_sim_spearman |
|
value: 78.02555120584198 |
|
- type: euclidean_pearson |
|
value: 78.25398100379078 |
|
- type: euclidean_spearman |
|
value: 78.66963870599464 |
|
- type: manhattan_pearson |
|
value: 78.14314682167348 |
|
- type: manhattan_spearman |
|
value: 78.57692322969135 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS14 |
|
type: mteb/sts14-sts |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.16989925136942 |
|
- type: cos_sim_spearman |
|
value: 76.5996225327091 |
|
- type: euclidean_pearson |
|
value: 77.8319003279786 |
|
- type: euclidean_spearman |
|
value: 76.42824009468998 |
|
- type: manhattan_pearson |
|
value: 77.69118862737736 |
|
- type: manhattan_spearman |
|
value: 76.25568104762812 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS15 |
|
type: mteb/sts15-sts |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.42012286935325 |
|
- type: cos_sim_spearman |
|
value: 88.15654297884122 |
|
- type: euclidean_pearson |
|
value: 87.34082819427852 |
|
- type: euclidean_spearman |
|
value: 88.06333589547084 |
|
- type: manhattan_pearson |
|
value: 87.25115596784842 |
|
- type: manhattan_spearman |
|
value: 87.9559927695203 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS16 |
|
type: mteb/sts16-sts |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.88222044996712 |
|
- type: cos_sim_spearman |
|
value: 84.28476589061077 |
|
- type: euclidean_pearson |
|
value: 83.17399758058309 |
|
- type: euclidean_spearman |
|
value: 83.85497357244542 |
|
- type: manhattan_pearson |
|
value: 83.0308397703786 |
|
- type: manhattan_spearman |
|
value: 83.71554539935046 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS17 (ko-ko) |
|
type: mteb/sts17-crosslingual-sts |
|
config: ko-ko |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 80.20682986257339 |
|
- type: cos_sim_spearman |
|
value: 79.94567120362092 |
|
- type: euclidean_pearson |
|
value: 79.43122480368902 |
|
- type: euclidean_spearman |
|
value: 79.94802077264987 |
|
- type: manhattan_pearson |
|
value: 79.32653021527081 |
|
- type: manhattan_spearman |
|
value: 79.80961146709178 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS17 (ar-ar) |
|
type: mteb/sts17-crosslingual-sts |
|
config: ar-ar |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 74.46578144394383 |
|
- type: cos_sim_spearman |
|
value: 74.52496637472179 |
|
- type: euclidean_pearson |
|
value: 72.2903807076809 |
|
- type: euclidean_spearman |
|
value: 73.55549359771645 |
|
- type: manhattan_pearson |
|
value: 72.09324837709393 |
|
- type: manhattan_spearman |
|
value: 73.36743103606581 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS17 (en-ar) |
|
type: mteb/sts17-crosslingual-sts |
|
config: en-ar |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 71.37272335116 |
|
- type: cos_sim_spearman |
|
value: 71.26702117766037 |
|
- type: euclidean_pearson |
|
value: 67.114829954434 |
|
- type: euclidean_spearman |
|
value: 66.37938893947761 |
|
- type: manhattan_pearson |
|
value: 66.79688574095246 |
|
- type: manhattan_spearman |
|
value: 66.17292828079667 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS17 (en-de) |
|
type: mteb/sts17-crosslingual-sts |
|
config: en-de |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 80.61016770129092 |
|
- type: cos_sim_spearman |
|
value: 82.08515426632214 |
|
- type: euclidean_pearson |
|
value: 80.557340361131 |
|
- type: euclidean_spearman |
|
value: 80.37585812266175 |
|
- type: manhattan_pearson |
|
value: 80.6782873404285 |
|
- type: manhattan_spearman |
|
value: 80.6678073032024 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS17 (en-en) |
|
type: mteb/sts17-crosslingual-sts |
|
config: en-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.00150745350108 |
|
- type: cos_sim_spearman |
|
value: 87.83441972211425 |
|
- type: euclidean_pearson |
|
value: 87.94826702308792 |
|
- type: euclidean_spearman |
|
value: 87.46143974860725 |
|
- type: manhattan_pearson |
|
value: 87.97560344306105 |
|
- type: manhattan_spearman |
|
value: 87.5267102829796 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS17 (en-tr) |
|
type: mteb/sts17-crosslingual-sts |
|
config: en-tr |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 64.76325252267235 |
|
- type: cos_sim_spearman |
|
value: 63.32615095463905 |
|
- type: euclidean_pearson |
|
value: 64.07920669155716 |
|
- type: euclidean_spearman |
|
value: 61.21409893072176 |
|
- type: manhattan_pearson |
|
value: 64.26308625680016 |
|
- type: manhattan_spearman |
|
value: 61.2438185254079 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS17 (es-en) |
|
type: mteb/sts17-crosslingual-sts |
|
config: es-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 75.82644463022595 |
|
- type: cos_sim_spearman |
|
value: 76.50381269945073 |
|
- type: euclidean_pearson |
|
value: 75.1328548315934 |
|
- type: euclidean_spearman |
|
value: 75.63761139408453 |
|
- type: manhattan_pearson |
|
value: 75.18610101241407 |
|
- type: manhattan_spearman |
|
value: 75.30669266354164 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS17 (es-es) |
|
type: mteb/sts17-crosslingual-sts |
|
config: es-es |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.49994164686832 |
|
- type: cos_sim_spearman |
|
value: 86.73743986245549 |
|
- type: euclidean_pearson |
|
value: 86.8272894387145 |
|
- type: euclidean_spearman |
|
value: 85.97608491000507 |
|
- type: manhattan_pearson |
|
value: 86.74960140396779 |
|
- type: manhattan_spearman |
|
value: 85.79285984190273 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS17 (fr-en) |
|
type: mteb/sts17-crosslingual-sts |
|
config: fr-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.58172210788469 |
|
- type: cos_sim_spearman |
|
value: 80.17516468334607 |
|
- type: euclidean_pearson |
|
value: 77.56537843470504 |
|
- type: euclidean_spearman |
|
value: 77.57264627395521 |
|
- type: manhattan_pearson |
|
value: 78.09703521695943 |
|
- type: manhattan_spearman |
|
value: 78.15942760916954 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS17 (it-en) |
|
type: mteb/sts17-crosslingual-sts |
|
config: it-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.7589932931751 |
|
- type: cos_sim_spearman |
|
value: 80.15210089028162 |
|
- type: euclidean_pearson |
|
value: 77.54135223516057 |
|
- type: euclidean_spearman |
|
value: 77.52697996368764 |
|
- type: manhattan_pearson |
|
value: 77.65734439572518 |
|
- type: manhattan_spearman |
|
value: 77.77702992016121 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS17 (nl-en) |
|
type: mteb/sts17-crosslingual-sts |
|
config: nl-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.16682365511267 |
|
- type: cos_sim_spearman |
|
value: 79.25311267628506 |
|
- type: euclidean_pearson |
|
value: 77.54882036762244 |
|
- type: euclidean_spearman |
|
value: 77.33212935194827 |
|
- type: manhattan_pearson |
|
value: 77.98405516064015 |
|
- type: manhattan_spearman |
|
value: 77.85075717865719 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (en) |
|
type: mteb/sts22-crosslingual-sts |
|
config: en |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 59.10473294775917 |
|
- type: cos_sim_spearman |
|
value: 61.82780474476838 |
|
- type: euclidean_pearson |
|
value: 45.885111672377256 |
|
- type: euclidean_spearman |
|
value: 56.88306351932454 |
|
- type: manhattan_pearson |
|
value: 46.101218127323186 |
|
- type: manhattan_spearman |
|
value: 56.80953694186333 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (de) |
|
type: mteb/sts22-crosslingual-sts |
|
config: de |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 45.781923079584146 |
|
- type: cos_sim_spearman |
|
value: 55.95098449691107 |
|
- type: euclidean_pearson |
|
value: 25.4571031323205 |
|
- type: euclidean_spearman |
|
value: 49.859978118078935 |
|
- type: manhattan_pearson |
|
value: 25.624938455041384 |
|
- type: manhattan_spearman |
|
value: 49.99546185049401 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (es) |
|
type: mteb/sts22-crosslingual-sts |
|
config: es |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 60.00618133997907 |
|
- type: cos_sim_spearman |
|
value: 66.57896677718321 |
|
- type: euclidean_pearson |
|
value: 42.60118466388821 |
|
- type: euclidean_spearman |
|
value: 62.8210759715209 |
|
- type: manhattan_pearson |
|
value: 42.63446860604094 |
|
- type: manhattan_spearman |
|
value: 62.73803068925271 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (pl) |
|
type: mteb/sts22-crosslingual-sts |
|
config: pl |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 28.460759121626943 |
|
- type: cos_sim_spearman |
|
value: 34.13459007469131 |
|
- type: euclidean_pearson |
|
value: 6.0917739325525195 |
|
- type: euclidean_spearman |
|
value: 27.9947262664867 |
|
- type: manhattan_pearson |
|
value: 6.16877864169911 |
|
- type: manhattan_spearman |
|
value: 28.00664163971514 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (tr) |
|
type: mteb/sts22-crosslingual-sts |
|
config: tr |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 57.42546621771696 |
|
- type: cos_sim_spearman |
|
value: 63.699663168970474 |
|
- type: euclidean_pearson |
|
value: 38.12085278789738 |
|
- type: euclidean_spearman |
|
value: 58.12329140741536 |
|
- type: manhattan_pearson |
|
value: 37.97364549443335 |
|
- type: manhattan_spearman |
|
value: 57.81545502318733 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (ar) |
|
type: mteb/sts22-crosslingual-sts |
|
config: ar |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 46.82241380954213 |
|
- type: cos_sim_spearman |
|
value: 57.86569456006391 |
|
- type: euclidean_pearson |
|
value: 31.80480070178813 |
|
- type: euclidean_spearman |
|
value: 52.484000620130104 |
|
- type: manhattan_pearson |
|
value: 31.952708554646097 |
|
- type: manhattan_spearman |
|
value: 52.8560972356195 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (ru) |
|
type: mteb/sts22-crosslingual-sts |
|
config: ru |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 52.00447170498087 |
|
- type: cos_sim_spearman |
|
value: 60.664116225735164 |
|
- type: euclidean_pearson |
|
value: 33.87382555421702 |
|
- type: euclidean_spearman |
|
value: 55.74649067458667 |
|
- type: manhattan_pearson |
|
value: 33.99117246759437 |
|
- type: manhattan_spearman |
|
value: 55.98749034923899 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (zh) |
|
type: mteb/sts22-crosslingual-sts |
|
config: zh |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 58.06497233105448 |
|
- type: cos_sim_spearman |
|
value: 65.62968801135676 |
|
- type: euclidean_pearson |
|
value: 47.482076613243905 |
|
- type: euclidean_spearman |
|
value: 62.65137791498299 |
|
- type: manhattan_pearson |
|
value: 47.57052626104093 |
|
- type: manhattan_spearman |
|
value: 62.436916516613294 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (fr) |
|
type: mteb/sts22-crosslingual-sts |
|
config: fr |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 70.49397298562575 |
|
- type: cos_sim_spearman |
|
value: 74.79604041187868 |
|
- type: euclidean_pearson |
|
value: 49.661891561317795 |
|
- type: euclidean_spearman |
|
value: 70.31535537621006 |
|
- type: manhattan_pearson |
|
value: 49.553715741850006 |
|
- type: manhattan_spearman |
|
value: 70.24779344636806 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (de-en) |
|
type: mteb/sts22-crosslingual-sts |
|
config: de-en |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 55.640574515348696 |
|
- type: cos_sim_spearman |
|
value: 54.927959317689 |
|
- type: euclidean_pearson |
|
value: 29.00139666967476 |
|
- type: euclidean_spearman |
|
value: 41.86386566971605 |
|
- type: manhattan_pearson |
|
value: 29.47411067730344 |
|
- type: manhattan_spearman |
|
value: 42.337438424952786 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (es-en) |
|
type: mteb/sts22-crosslingual-sts |
|
config: es-en |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 68.14095292259312 |
|
- type: cos_sim_spearman |
|
value: 73.99017581234789 |
|
- type: euclidean_pearson |
|
value: 46.46304297872084 |
|
- type: euclidean_spearman |
|
value: 60.91834114800041 |
|
- type: manhattan_pearson |
|
value: 47.07072666338692 |
|
- type: manhattan_spearman |
|
value: 61.70415727977926 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (it) |
|
type: mteb/sts22-crosslingual-sts |
|
config: it |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 73.27184653359575 |
|
- type: cos_sim_spearman |
|
value: 77.76070252418626 |
|
- type: euclidean_pearson |
|
value: 62.30586577544778 |
|
- type: euclidean_spearman |
|
value: 75.14246629110978 |
|
- type: manhattan_pearson |
|
value: 62.328196884927046 |
|
- type: manhattan_spearman |
|
value: 75.1282792981433 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (pl-en) |
|
type: mteb/sts22-crosslingual-sts |
|
config: pl-en |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 71.59448528829957 |
|
- type: cos_sim_spearman |
|
value: 70.37277734222123 |
|
- type: euclidean_pearson |
|
value: 57.63145565721123 |
|
- type: euclidean_spearman |
|
value: 66.10113048304427 |
|
- type: manhattan_pearson |
|
value: 57.18897811586808 |
|
- type: manhattan_spearman |
|
value: 66.5595511215901 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (zh-en) |
|
type: mteb/sts22-crosslingual-sts |
|
config: zh-en |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 66.37520607720838 |
|
- type: cos_sim_spearman |
|
value: 69.92282148997948 |
|
- type: euclidean_pearson |
|
value: 40.55768770125291 |
|
- type: euclidean_spearman |
|
value: 55.189128944669605 |
|
- type: manhattan_pearson |
|
value: 41.03566433468883 |
|
- type: manhattan_spearman |
|
value: 55.61251893174558 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (es-it) |
|
type: mteb/sts22-crosslingual-sts |
|
config: es-it |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 57.791929533771835 |
|
- type: cos_sim_spearman |
|
value: 66.45819707662093 |
|
- type: euclidean_pearson |
|
value: 39.03686018511092 |
|
- type: euclidean_spearman |
|
value: 56.01282695640428 |
|
- type: manhattan_pearson |
|
value: 38.91586623619632 |
|
- type: manhattan_spearman |
|
value: 56.69394943612747 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (de-fr) |
|
type: mteb/sts22-crosslingual-sts |
|
config: de-fr |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 47.82224468473866 |
|
- type: cos_sim_spearman |
|
value: 59.467307194781164 |
|
- type: euclidean_pearson |
|
value: 27.428459190256145 |
|
- type: euclidean_spearman |
|
value: 60.83463107397519 |
|
- type: manhattan_pearson |
|
value: 27.487391578496638 |
|
- type: manhattan_spearman |
|
value: 61.281380460246496 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (de-pl) |
|
type: mteb/sts22-crosslingual-sts |
|
config: de-pl |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 16.306666792752644 |
|
- type: cos_sim_spearman |
|
value: 39.35486427252405 |
|
- type: euclidean_pearson |
|
value: -2.7887154897955435 |
|
- type: euclidean_spearman |
|
value: 27.1296051831719 |
|
- type: manhattan_pearson |
|
value: -3.202291270581297 |
|
- type: manhattan_spearman |
|
value: 26.32895849218158 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (fr-pl) |
|
type: mteb/sts22-crosslingual-sts |
|
config: fr-pl |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 59.67006803805076 |
|
- type: cos_sim_spearman |
|
value: 73.24670207647144 |
|
- type: euclidean_pearson |
|
value: 46.91884681500483 |
|
- type: euclidean_spearman |
|
value: 16.903085094570333 |
|
- type: manhattan_pearson |
|
value: 46.88391675325812 |
|
- type: manhattan_spearman |
|
value: 28.17180849095055 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STSBenchmark |
|
type: mteb/stsbenchmark-sts |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.79555591223837 |
|
- type: cos_sim_spearman |
|
value: 85.63658602085185 |
|
- type: euclidean_pearson |
|
value: 85.22080894037671 |
|
- type: euclidean_spearman |
|
value: 85.54113580167038 |
|
- type: manhattan_pearson |
|
value: 85.1639505960118 |
|
- type: manhattan_spearman |
|
value: 85.43502665436196 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB SciDocsRR |
|
type: mteb/scidocs-reranking |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 80.73900991689766 |
|
- type: mrr |
|
value: 94.81624131133934 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB SciFact |
|
type: scifact |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 55.678000000000004 |
|
- type: map_at_10 |
|
value: 65.135 |
|
- type: map_at_100 |
|
value: 65.824 |
|
- type: map_at_1000 |
|
value: 65.852 |
|
- type: map_at_3 |
|
value: 62.736000000000004 |
|
- type: map_at_5 |
|
value: 64.411 |
|
- type: mrr_at_1 |
|
value: 58.333 |
|
- type: mrr_at_10 |
|
value: 66.5 |
|
- type: mrr_at_100 |
|
value: 67.053 |
|
- type: mrr_at_1000 |
|
value: 67.08 |
|
- type: mrr_at_3 |
|
value: 64.944 |
|
- type: mrr_at_5 |
|
value: 65.89399999999999 |
|
- type: ndcg_at_1 |
|
value: 58.333 |
|
- type: ndcg_at_10 |
|
value: 69.34700000000001 |
|
- type: ndcg_at_100 |
|
value: 72.32 |
|
- type: ndcg_at_1000 |
|
value: 73.014 |
|
- type: ndcg_at_3 |
|
value: 65.578 |
|
- type: ndcg_at_5 |
|
value: 67.738 |
|
- type: precision_at_1 |
|
value: 58.333 |
|
- type: precision_at_10 |
|
value: 9.033 |
|
- type: precision_at_100 |
|
value: 1.0670000000000002 |
|
- type: precision_at_1000 |
|
value: 0.11199999999999999 |
|
- type: precision_at_3 |
|
value: 25.444 |
|
- type: precision_at_5 |
|
value: 16.933 |
|
- type: recall_at_1 |
|
value: 55.678000000000004 |
|
- type: recall_at_10 |
|
value: 80.72200000000001 |
|
- type: recall_at_100 |
|
value: 93.93299999999999 |
|
- type: recall_at_1000 |
|
value: 99.333 |
|
- type: recall_at_3 |
|
value: 70.783 |
|
- type: recall_at_5 |
|
value: 75.978 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
name: MTEB SprintDuplicateQuestions |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.74653465346535 |
|
- type: cos_sim_ap |
|
value: 93.01476369929063 |
|
- type: cos_sim_f1 |
|
value: 86.93009118541033 |
|
- type: cos_sim_precision |
|
value: 88.09034907597535 |
|
- type: cos_sim_recall |
|
value: 85.8 |
|
- type: dot_accuracy |
|
value: 99.22970297029703 |
|
- type: dot_ap |
|
value: 51.58725659485144 |
|
- type: dot_f1 |
|
value: 53.51351351351352 |
|
- type: dot_precision |
|
value: 58.235294117647065 |
|
- type: dot_recall |
|
value: 49.5 |
|
- type: euclidean_accuracy |
|
value: 99.74356435643564 |
|
- type: euclidean_ap |
|
value: 92.40332894384368 |
|
- type: euclidean_f1 |
|
value: 86.97838109602817 |
|
- type: euclidean_precision |
|
value: 87.46208291203236 |
|
- type: euclidean_recall |
|
value: 86.5 |
|
- type: manhattan_accuracy |
|
value: 99.73069306930694 |
|
- type: manhattan_ap |
|
value: 92.01320815721121 |
|
- type: manhattan_f1 |
|
value: 86.4135864135864 |
|
- type: manhattan_precision |
|
value: 86.32734530938124 |
|
- type: manhattan_recall |
|
value: 86.5 |
|
- type: max_accuracy |
|
value: 99.74653465346535 |
|
- type: max_ap |
|
value: 93.01476369929063 |
|
- type: max_f1 |
|
value: 86.97838109602817 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB StackExchangeClustering |
|
type: mteb/stackexchange-clustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 55.2660514302523 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB StackExchangeClusteringP2P |
|
type: mteb/stackexchange-clustering-p2p |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 30.4637783572547 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB StackOverflowDupQuestions |
|
type: mteb/stackoverflowdupquestions-reranking |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 49.41377758357637 |
|
- type: mrr |
|
value: 50.138451213818854 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
name: MTEB SummEval |
|
type: mteb/summeval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 28.887846011166594 |
|
- type: cos_sim_spearman |
|
value: 30.10823258355903 |
|
- type: dot_pearson |
|
value: 12.888049550236385 |
|
- type: dot_spearman |
|
value: 12.827495903098123 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB TRECCOVID |
|
type: trec-covid |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.21 |
|
- type: map_at_10 |
|
value: 1.667 |
|
- type: map_at_100 |
|
value: 9.15 |
|
- type: map_at_1000 |
|
value: 22.927 |
|
- type: map_at_3 |
|
value: 0.573 |
|
- type: map_at_5 |
|
value: 0.915 |
|
- type: mrr_at_1 |
|
value: 80 |
|
- type: mrr_at_10 |
|
value: 87.167 |
|
- type: mrr_at_100 |
|
value: 87.167 |
|
- type: mrr_at_1000 |
|
value: 87.167 |
|
- type: mrr_at_3 |
|
value: 85.667 |
|
- type: mrr_at_5 |
|
value: 87.167 |
|
- type: ndcg_at_1 |
|
value: 76 |
|
- type: ndcg_at_10 |
|
value: 69.757 |
|
- type: ndcg_at_100 |
|
value: 52.402 |
|
- type: ndcg_at_1000 |
|
value: 47.737 |
|
- type: ndcg_at_3 |
|
value: 71.866 |
|
- type: ndcg_at_5 |
|
value: 72.225 |
|
- type: precision_at_1 |
|
value: 80 |
|
- type: precision_at_10 |
|
value: 75 |
|
- type: precision_at_100 |
|
value: 53.959999999999994 |
|
- type: precision_at_1000 |
|
value: 21.568 |
|
- type: precision_at_3 |
|
value: 76.667 |
|
- type: precision_at_5 |
|
value: 78 |
|
- type: recall_at_1 |
|
value: 0.21 |
|
- type: recall_at_10 |
|
value: 1.9189999999999998 |
|
- type: recall_at_100 |
|
value: 12.589 |
|
- type: recall_at_1000 |
|
value: 45.312000000000005 |
|
- type: recall_at_3 |
|
value: 0.61 |
|
- type: recall_at_5 |
|
value: 1.019 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (sqi-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: sqi-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 92.10000000000001 |
|
- type: f1 |
|
value: 90.06 |
|
- type: precision |
|
value: 89.17333333333333 |
|
- type: recall |
|
value: 92.10000000000001 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (fry-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: fry-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 56.06936416184971 |
|
- type: f1 |
|
value: 50.87508028259473 |
|
- type: precision |
|
value: 48.97398843930635 |
|
- type: recall |
|
value: 56.06936416184971 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (kur-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: kur-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 57.3170731707317 |
|
- type: f1 |
|
value: 52.96080139372822 |
|
- type: precision |
|
value: 51.67861124382864 |
|
- type: recall |
|
value: 57.3170731707317 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (tur-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: tur-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 94.3 |
|
- type: f1 |
|
value: 92.67333333333333 |
|
- type: precision |
|
value: 91.90833333333333 |
|
- type: recall |
|
value: 94.3 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (deu-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: deu-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 97.7 |
|
- type: f1 |
|
value: 97.07333333333332 |
|
- type: precision |
|
value: 96.79500000000002 |
|
- type: recall |
|
value: 97.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (nld-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: nld-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 94.69999999999999 |
|
- type: f1 |
|
value: 93.2 |
|
- type: precision |
|
value: 92.48333333333333 |
|
- type: recall |
|
value: 94.69999999999999 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ron-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ron-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 92.9 |
|
- type: f1 |
|
value: 91.26666666666667 |
|
- type: precision |
|
value: 90.59444444444445 |
|
- type: recall |
|
value: 92.9 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ang-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ang-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 34.32835820895522 |
|
- type: f1 |
|
value: 29.074180380150533 |
|
- type: precision |
|
value: 28.068207322920596 |
|
- type: recall |
|
value: 34.32835820895522 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ido-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ido-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 78.5 |
|
- type: f1 |
|
value: 74.3945115995116 |
|
- type: precision |
|
value: 72.82967843459222 |
|
- type: recall |
|
value: 78.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (jav-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: jav-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 66.34146341463415 |
|
- type: f1 |
|
value: 61.2469400518181 |
|
- type: precision |
|
value: 59.63977756660683 |
|
- type: recall |
|
value: 66.34146341463415 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (isl-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: isl-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 80.9 |
|
- type: f1 |
|
value: 76.90349206349207 |
|
- type: precision |
|
value: 75.32921568627451 |
|
- type: recall |
|
value: 80.9 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (slv-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: slv-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 84.93317132442284 |
|
- type: f1 |
|
value: 81.92519105034295 |
|
- type: precision |
|
value: 80.71283920615635 |
|
- type: recall |
|
value: 84.93317132442284 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (cym-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: cym-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 71.1304347826087 |
|
- type: f1 |
|
value: 65.22394755003451 |
|
- type: precision |
|
value: 62.912422360248435 |
|
- type: recall |
|
value: 71.1304347826087 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (kaz-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: kaz-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 79.82608695652173 |
|
- type: f1 |
|
value: 75.55693581780538 |
|
- type: precision |
|
value: 73.79420289855072 |
|
- type: recall |
|
value: 79.82608695652173 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (est-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: est-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 74 |
|
- type: f1 |
|
value: 70.51022222222223 |
|
- type: precision |
|
value: 69.29673599347512 |
|
- type: recall |
|
value: 74 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (heb-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: heb-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 78.7 |
|
- type: f1 |
|
value: 74.14238095238095 |
|
- type: precision |
|
value: 72.27214285714285 |
|
- type: recall |
|
value: 78.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (gla-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: gla-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 48.97466827503016 |
|
- type: f1 |
|
value: 43.080330405420874 |
|
- type: precision |
|
value: 41.36505499593557 |
|
- type: recall |
|
value: 48.97466827503016 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (mar-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: mar-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 89.60000000000001 |
|
- type: f1 |
|
value: 86.62333333333333 |
|
- type: precision |
|
value: 85.225 |
|
- type: recall |
|
value: 89.60000000000001 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (lat-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: lat-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 45.2 |
|
- type: f1 |
|
value: 39.5761253006253 |
|
- type: precision |
|
value: 37.991358436312 |
|
- type: recall |
|
value: 45.2 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (bel-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: bel-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 89.5 |
|
- type: f1 |
|
value: 86.70333333333333 |
|
- type: precision |
|
value: 85.53166666666667 |
|
- type: recall |
|
value: 89.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (pms-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: pms-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 50.095238095238095 |
|
- type: f1 |
|
value: 44.60650460650461 |
|
- type: precision |
|
value: 42.774116796477045 |
|
- type: recall |
|
value: 50.095238095238095 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (gle-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: gle-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 63.4 |
|
- type: f1 |
|
value: 58.35967261904762 |
|
- type: precision |
|
value: 56.54857142857143 |
|
- type: recall |
|
value: 63.4 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (pes-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: pes-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 89.2 |
|
- type: f1 |
|
value: 87.075 |
|
- type: precision |
|
value: 86.12095238095239 |
|
- type: recall |
|
value: 89.2 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (nob-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: nob-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 96.8 |
|
- type: f1 |
|
value: 95.90333333333334 |
|
- type: precision |
|
value: 95.50833333333333 |
|
- type: recall |
|
value: 96.8 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (bul-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: bul-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 90.9 |
|
- type: f1 |
|
value: 88.6288888888889 |
|
- type: precision |
|
value: 87.61607142857142 |
|
- type: recall |
|
value: 90.9 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (cbk-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: cbk-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 65.2 |
|
- type: f1 |
|
value: 60.54377630539395 |
|
- type: precision |
|
value: 58.89434482711381 |
|
- type: recall |
|
value: 65.2 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (hun-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: hun-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 87 |
|
- type: f1 |
|
value: 84.32412698412699 |
|
- type: precision |
|
value: 83.25527777777778 |
|
- type: recall |
|
value: 87 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (uig-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: uig-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 68.7 |
|
- type: f1 |
|
value: 63.07883541295306 |
|
- type: precision |
|
value: 61.06117424242426 |
|
- type: recall |
|
value: 68.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (rus-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: rus-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 93.7 |
|
- type: f1 |
|
value: 91.78333333333335 |
|
- type: precision |
|
value: 90.86666666666667 |
|
- type: recall |
|
value: 93.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (spa-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: spa-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 97.7 |
|
- type: f1 |
|
value: 96.96666666666667 |
|
- type: precision |
|
value: 96.61666666666667 |
|
- type: recall |
|
value: 97.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (hye-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: hye-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 88.27493261455525 |
|
- type: f1 |
|
value: 85.90745732255168 |
|
- type: precision |
|
value: 84.91389637616052 |
|
- type: recall |
|
value: 88.27493261455525 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (tel-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: tel-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 90.5982905982906 |
|
- type: f1 |
|
value: 88.4900284900285 |
|
- type: precision |
|
value: 87.57122507122507 |
|
- type: recall |
|
value: 90.5982905982906 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (afr-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: afr-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 89.5 |
|
- type: f1 |
|
value: 86.90769841269842 |
|
- type: precision |
|
value: 85.80178571428571 |
|
- type: recall |
|
value: 89.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (mon-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: mon-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 82.5 |
|
- type: f1 |
|
value: 78.36796536796538 |
|
- type: precision |
|
value: 76.82196969696969 |
|
- type: recall |
|
value: 82.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (arz-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: arz-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 71.48846960167715 |
|
- type: f1 |
|
value: 66.78771089148448 |
|
- type: precision |
|
value: 64.98302885095339 |
|
- type: recall |
|
value: 71.48846960167715 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (hrv-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: hrv-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 94.1 |
|
- type: f1 |
|
value: 92.50333333333333 |
|
- type: precision |
|
value: 91.77499999999999 |
|
- type: recall |
|
value: 94.1 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (nov-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: nov-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 71.20622568093385 |
|
- type: f1 |
|
value: 66.83278891450098 |
|
- type: precision |
|
value: 65.35065777283677 |
|
- type: recall |
|
value: 71.20622568093385 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (gsw-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: gsw-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 48.717948717948715 |
|
- type: f1 |
|
value: 43.53146853146853 |
|
- type: precision |
|
value: 42.04721204721204 |
|
- type: recall |
|
value: 48.717948717948715 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (nds-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: nds-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 58.5 |
|
- type: f1 |
|
value: 53.8564991863928 |
|
- type: precision |
|
value: 52.40329436122275 |
|
- type: recall |
|
value: 58.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ukr-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ukr-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 90.8 |
|
- type: f1 |
|
value: 88.29 |
|
- type: precision |
|
value: 87.09166666666667 |
|
- type: recall |
|
value: 90.8 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (uzb-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: uzb-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 67.28971962616822 |
|
- type: f1 |
|
value: 62.63425307817832 |
|
- type: precision |
|
value: 60.98065939771546 |
|
- type: recall |
|
value: 67.28971962616822 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (lit-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: lit-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 78.7 |
|
- type: f1 |
|
value: 75.5264472455649 |
|
- type: precision |
|
value: 74.38205086580086 |
|
- type: recall |
|
value: 78.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ina-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ina-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 88.7 |
|
- type: f1 |
|
value: 86.10809523809525 |
|
- type: precision |
|
value: 85.07602564102565 |
|
- type: recall |
|
value: 88.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (lfn-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: lfn-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 56.99999999999999 |
|
- type: f1 |
|
value: 52.85487521402737 |
|
- type: precision |
|
value: 51.53985162713104 |
|
- type: recall |
|
value: 56.99999999999999 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (zsm-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: zsm-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 94 |
|
- type: f1 |
|
value: 92.45333333333333 |
|
- type: precision |
|
value: 91.79166666666667 |
|
- type: recall |
|
value: 94 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ita-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ita-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 92.30000000000001 |
|
- type: f1 |
|
value: 90.61333333333333 |
|
- type: precision |
|
value: 89.83333333333331 |
|
- type: recall |
|
value: 92.30000000000001 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (cmn-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: cmn-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 94.69999999999999 |
|
- type: f1 |
|
value: 93.34555555555555 |
|
- type: precision |
|
value: 92.75416666666668 |
|
- type: recall |
|
value: 94.69999999999999 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (lvs-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: lvs-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 80.2 |
|
- type: f1 |
|
value: 76.6563035113035 |
|
- type: precision |
|
value: 75.3014652014652 |
|
- type: recall |
|
value: 80.2 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (glg-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: glg-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 84.7 |
|
- type: f1 |
|
value: 82.78689263765207 |
|
- type: precision |
|
value: 82.06705086580087 |
|
- type: recall |
|
value: 84.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ceb-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ceb-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 50.33333333333333 |
|
- type: f1 |
|
value: 45.461523661523664 |
|
- type: precision |
|
value: 43.93545574795575 |
|
- type: recall |
|
value: 50.33333333333333 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (bre-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: bre-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 6.6000000000000005 |
|
- type: f1 |
|
value: 5.442121400446441 |
|
- type: precision |
|
value: 5.146630385487529 |
|
- type: recall |
|
value: 6.6000000000000005 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ben-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ben-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 85 |
|
- type: f1 |
|
value: 81.04666666666667 |
|
- type: precision |
|
value: 79.25 |
|
- type: recall |
|
value: 85 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (swg-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: swg-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 47.32142857142857 |
|
- type: f1 |
|
value: 42.333333333333336 |
|
- type: precision |
|
value: 40.69196428571429 |
|
- type: recall |
|
value: 47.32142857142857 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (arq-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: arq-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 30.735455543358945 |
|
- type: f1 |
|
value: 26.73616790022338 |
|
- type: precision |
|
value: 25.397823220451283 |
|
- type: recall |
|
value: 30.735455543358945 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (kab-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: kab-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 25.1 |
|
- type: f1 |
|
value: 21.975989896371022 |
|
- type: precision |
|
value: 21.059885632257203 |
|
- type: recall |
|
value: 25.1 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (fra-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: fra-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 94.3 |
|
- type: f1 |
|
value: 92.75666666666666 |
|
- type: precision |
|
value: 92.06166666666665 |
|
- type: recall |
|
value: 94.3 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (por-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: por-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 94.1 |
|
- type: f1 |
|
value: 92.74 |
|
- type: precision |
|
value: 92.09166666666667 |
|
- type: recall |
|
value: 94.1 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (tat-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: tat-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 71.3 |
|
- type: f1 |
|
value: 66.922442002442 |
|
- type: precision |
|
value: 65.38249567099568 |
|
- type: recall |
|
value: 71.3 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (oci-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: oci-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 40.300000000000004 |
|
- type: f1 |
|
value: 35.78682789299971 |
|
- type: precision |
|
value: 34.66425128716588 |
|
- type: recall |
|
value: 40.300000000000004 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (pol-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: pol-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 96 |
|
- type: f1 |
|
value: 94.82333333333334 |
|
- type: precision |
|
value: 94.27833333333334 |
|
- type: recall |
|
value: 96 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (war-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: war-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 51.1 |
|
- type: f1 |
|
value: 47.179074753133584 |
|
- type: precision |
|
value: 46.06461044702424 |
|
- type: recall |
|
value: 51.1 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (aze-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: aze-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 87.7 |
|
- type: f1 |
|
value: 84.71 |
|
- type: precision |
|
value: 83.46166666666667 |
|
- type: recall |
|
value: 87.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (vie-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: vie-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 95.8 |
|
- type: f1 |
|
value: 94.68333333333334 |
|
- type: precision |
|
value: 94.13333333333334 |
|
- type: recall |
|
value: 95.8 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (nno-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: nno-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 85.39999999999999 |
|
- type: f1 |
|
value: 82.5577380952381 |
|
- type: precision |
|
value: 81.36833333333334 |
|
- type: recall |
|
value: 85.39999999999999 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (cha-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: cha-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 21.16788321167883 |
|
- type: f1 |
|
value: 16.948865627297987 |
|
- type: precision |
|
value: 15.971932568647897 |
|
- type: recall |
|
value: 21.16788321167883 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (mhr-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: mhr-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 6.9 |
|
- type: f1 |
|
value: 5.515526831658907 |
|
- type: precision |
|
value: 5.141966366966367 |
|
- type: recall |
|
value: 6.9 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (dan-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: dan-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 93.2 |
|
- type: f1 |
|
value: 91.39666666666668 |
|
- type: precision |
|
value: 90.58666666666667 |
|
- type: recall |
|
value: 93.2 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ell-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ell-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 92.2 |
|
- type: f1 |
|
value: 89.95666666666666 |
|
- type: precision |
|
value: 88.92833333333333 |
|
- type: recall |
|
value: 92.2 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (amh-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: amh-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 79.76190476190477 |
|
- type: f1 |
|
value: 74.93386243386244 |
|
- type: precision |
|
value: 73.11011904761904 |
|
- type: recall |
|
value: 79.76190476190477 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (pam-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: pam-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 8.799999999999999 |
|
- type: f1 |
|
value: 6.921439712248537 |
|
- type: precision |
|
value: 6.489885109680683 |
|
- type: recall |
|
value: 8.799999999999999 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (hsb-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: hsb-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 45.75569358178054 |
|
- type: f1 |
|
value: 40.34699501312631 |
|
- type: precision |
|
value: 38.57886764719063 |
|
- type: recall |
|
value: 45.75569358178054 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (srp-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: srp-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 91.4 |
|
- type: f1 |
|
value: 89.08333333333333 |
|
- type: precision |
|
value: 88.01666666666668 |
|
- type: recall |
|
value: 91.4 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (epo-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: epo-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 93.60000000000001 |
|
- type: f1 |
|
value: 92.06690476190477 |
|
- type: precision |
|
value: 91.45095238095239 |
|
- type: recall |
|
value: 93.60000000000001 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (kzj-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: kzj-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 7.5 |
|
- type: f1 |
|
value: 6.200363129378736 |
|
- type: precision |
|
value: 5.89115314822466 |
|
- type: recall |
|
value: 7.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (awa-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: awa-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 73.59307359307358 |
|
- type: f1 |
|
value: 68.38933553219267 |
|
- type: precision |
|
value: 66.62698412698413 |
|
- type: recall |
|
value: 73.59307359307358 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (fao-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: fao-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 69.8473282442748 |
|
- type: f1 |
|
value: 64.72373682297346 |
|
- type: precision |
|
value: 62.82834214131924 |
|
- type: recall |
|
value: 69.8473282442748 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (mal-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: mal-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 97.5254730713246 |
|
- type: f1 |
|
value: 96.72489082969432 |
|
- type: precision |
|
value: 96.33672974284326 |
|
- type: recall |
|
value: 97.5254730713246 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ile-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ile-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 75.6 |
|
- type: f1 |
|
value: 72.42746031746033 |
|
- type: precision |
|
value: 71.14036630036631 |
|
- type: recall |
|
value: 75.6 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (bos-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: bos-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 91.24293785310734 |
|
- type: f1 |
|
value: 88.86064030131826 |
|
- type: precision |
|
value: 87.73540489642184 |
|
- type: recall |
|
value: 91.24293785310734 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (cor-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: cor-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 6.2 |
|
- type: f1 |
|
value: 4.383083659794954 |
|
- type: precision |
|
value: 4.027861324289673 |
|
- type: recall |
|
value: 6.2 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (cat-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: cat-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 86.8 |
|
- type: f1 |
|
value: 84.09428571428572 |
|
- type: precision |
|
value: 83.00333333333333 |
|
- type: recall |
|
value: 86.8 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (eus-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: eus-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 60.699999999999996 |
|
- type: f1 |
|
value: 56.1584972394755 |
|
- type: precision |
|
value: 54.713456330903135 |
|
- type: recall |
|
value: 60.699999999999996 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (yue-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: yue-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 84.2 |
|
- type: f1 |
|
value: 80.66190476190475 |
|
- type: precision |
|
value: 79.19690476190476 |
|
- type: recall |
|
value: 84.2 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (swe-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: swe-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 93.2 |
|
- type: f1 |
|
value: 91.33 |
|
- type: precision |
|
value: 90.45 |
|
- type: recall |
|
value: 93.2 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (dtp-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: dtp-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 6.3 |
|
- type: f1 |
|
value: 5.126828976748276 |
|
- type: precision |
|
value: 4.853614328966668 |
|
- type: recall |
|
value: 6.3 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (kat-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: kat-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 81.76943699731903 |
|
- type: f1 |
|
value: 77.82873739308057 |
|
- type: precision |
|
value: 76.27622452019234 |
|
- type: recall |
|
value: 81.76943699731903 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (jpn-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: jpn-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 92.30000000000001 |
|
- type: f1 |
|
value: 90.29666666666665 |
|
- type: precision |
|
value: 89.40333333333334 |
|
- type: recall |
|
value: 92.30000000000001 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (csb-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: csb-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 29.249011857707508 |
|
- type: f1 |
|
value: 24.561866096392947 |
|
- type: precision |
|
value: 23.356583740215456 |
|
- type: recall |
|
value: 29.249011857707508 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (xho-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: xho-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 77.46478873239437 |
|
- type: f1 |
|
value: 73.23943661971832 |
|
- type: precision |
|
value: 71.66666666666667 |
|
- type: recall |
|
value: 77.46478873239437 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (orv-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: orv-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 20.35928143712575 |
|
- type: f1 |
|
value: 15.997867865075824 |
|
- type: precision |
|
value: 14.882104658301346 |
|
- type: recall |
|
value: 20.35928143712575 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ind-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ind-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 92.2 |
|
- type: f1 |
|
value: 90.25999999999999 |
|
- type: precision |
|
value: 89.45333333333335 |
|
- type: recall |
|
value: 92.2 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (tuk-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: tuk-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 23.15270935960591 |
|
- type: f1 |
|
value: 19.65673625772148 |
|
- type: precision |
|
value: 18.793705293464992 |
|
- type: recall |
|
value: 23.15270935960591 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (max-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: max-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 59.154929577464785 |
|
- type: f1 |
|
value: 52.3868463305083 |
|
- type: precision |
|
value: 50.14938113529662 |
|
- type: recall |
|
value: 59.154929577464785 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (swh-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: swh-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 70.51282051282051 |
|
- type: f1 |
|
value: 66.8089133089133 |
|
- type: precision |
|
value: 65.37645687645687 |
|
- type: recall |
|
value: 70.51282051282051 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (hin-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: hin-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 94.6 |
|
- type: f1 |
|
value: 93 |
|
- type: precision |
|
value: 92.23333333333333 |
|
- type: recall |
|
value: 94.6 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (dsb-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: dsb-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 38.62212943632568 |
|
- type: f1 |
|
value: 34.3278276962583 |
|
- type: precision |
|
value: 33.07646935732408 |
|
- type: recall |
|
value: 38.62212943632568 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ber-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ber-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 28.1 |
|
- type: f1 |
|
value: 23.579609223054604 |
|
- type: precision |
|
value: 22.39622774921555 |
|
- type: recall |
|
value: 28.1 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (tam-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: tam-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 88.27361563517914 |
|
- type: f1 |
|
value: 85.12486427795874 |
|
- type: precision |
|
value: 83.71335504885994 |
|
- type: recall |
|
value: 88.27361563517914 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (slk-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: slk-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 88.6 |
|
- type: f1 |
|
value: 86.39928571428571 |
|
- type: precision |
|
value: 85.4947557997558 |
|
- type: recall |
|
value: 88.6 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (tgl-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: tgl-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 86.5 |
|
- type: f1 |
|
value: 83.77952380952381 |
|
- type: precision |
|
value: 82.67602564102565 |
|
- type: recall |
|
value: 86.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ast-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ast-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 79.52755905511812 |
|
- type: f1 |
|
value: 75.3055868016498 |
|
- type: precision |
|
value: 73.81889763779527 |
|
- type: recall |
|
value: 79.52755905511812 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (mkd-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: mkd-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 77.9 |
|
- type: f1 |
|
value: 73.76261904761905 |
|
- type: precision |
|
value: 72.11670995670995 |
|
- type: recall |
|
value: 77.9 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (khm-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: khm-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 53.8781163434903 |
|
- type: f1 |
|
value: 47.25804051288816 |
|
- type: precision |
|
value: 45.0603482390186 |
|
- type: recall |
|
value: 53.8781163434903 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ces-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ces-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 91.10000000000001 |
|
- type: f1 |
|
value: 88.88 |
|
- type: precision |
|
value: 87.96333333333334 |
|
- type: recall |
|
value: 91.10000000000001 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (tzl-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: tzl-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 38.46153846153847 |
|
- type: f1 |
|
value: 34.43978243978244 |
|
- type: precision |
|
value: 33.429487179487175 |
|
- type: recall |
|
value: 38.46153846153847 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (urd-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: urd-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 88.9 |
|
- type: f1 |
|
value: 86.19888888888887 |
|
- type: precision |
|
value: 85.07440476190476 |
|
- type: recall |
|
value: 88.9 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (ara-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: ara-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 85.9 |
|
- type: f1 |
|
value: 82.58857142857143 |
|
- type: precision |
|
value: 81.15666666666667 |
|
- type: recall |
|
value: 85.9 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (kor-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: kor-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 86.8 |
|
- type: f1 |
|
value: 83.36999999999999 |
|
- type: precision |
|
value: 81.86833333333333 |
|
- type: recall |
|
value: 86.8 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (yid-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: yid-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 68.51415094339622 |
|
- type: f1 |
|
value: 63.195000099481234 |
|
- type: precision |
|
value: 61.394033442972116 |
|
- type: recall |
|
value: 68.51415094339622 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (fin-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: fin-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 88.5 |
|
- type: f1 |
|
value: 86.14603174603175 |
|
- type: precision |
|
value: 85.1162037037037 |
|
- type: recall |
|
value: 88.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (tha-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: tha-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 95.62043795620438 |
|
- type: f1 |
|
value: 94.40389294403892 |
|
- type: precision |
|
value: 93.7956204379562 |
|
- type: recall |
|
value: 95.62043795620438 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
name: MTEB Tatoeba (wuu-eng) |
|
type: mteb/tatoeba-bitext-mining |
|
config: wuu-eng |
|
split: test |
|
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
|
metrics: |
|
- type: accuracy |
|
value: 81.8 |
|
- type: f1 |
|
value: 78.6532178932179 |
|
- type: precision |
|
value: 77.46348795840176 |
|
- type: recall |
|
value: 81.8 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB Touche2020 |
|
type: webis-touche2020 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.603 |
|
- type: map_at_10 |
|
value: 8.5 |
|
- type: map_at_100 |
|
value: 12.985 |
|
- type: map_at_1000 |
|
value: 14.466999999999999 |
|
- type: map_at_3 |
|
value: 4.859999999999999 |
|
- type: map_at_5 |
|
value: 5.817 |
|
- type: mrr_at_1 |
|
value: 28.571 |
|
- type: mrr_at_10 |
|
value: 42.331 |
|
- type: mrr_at_100 |
|
value: 43.592999999999996 |
|
- type: mrr_at_1000 |
|
value: 43.592999999999996 |
|
- type: mrr_at_3 |
|
value: 38.435 |
|
- type: mrr_at_5 |
|
value: 39.966 |
|
- type: ndcg_at_1 |
|
value: 26.531 |
|
- type: ndcg_at_10 |
|
value: 21.353 |
|
- type: ndcg_at_100 |
|
value: 31.087999999999997 |
|
- type: ndcg_at_1000 |
|
value: 43.163000000000004 |
|
- type: ndcg_at_3 |
|
value: 22.999 |
|
- type: ndcg_at_5 |
|
value: 21.451 |
|
- type: precision_at_1 |
|
value: 28.571 |
|
- type: precision_at_10 |
|
value: 19.387999999999998 |
|
- type: precision_at_100 |
|
value: 6.265 |
|
- type: precision_at_1000 |
|
value: 1.4160000000000001 |
|
- type: precision_at_3 |
|
value: 24.490000000000002 |
|
- type: precision_at_5 |
|
value: 21.224 |
|
- type: recall_at_1 |
|
value: 2.603 |
|
- type: recall_at_10 |
|
value: 14.474 |
|
- type: recall_at_100 |
|
value: 40.287 |
|
- type: recall_at_1000 |
|
value: 76.606 |
|
- type: recall_at_3 |
|
value: 5.978 |
|
- type: recall_at_5 |
|
value: 7.819 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB ToxicConversationsClassification |
|
type: mteb/toxic_conversations_50k |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 69.7848 |
|
- type: ap |
|
value: 13.661023167088224 |
|
- type: f1 |
|
value: 53.61686134460943 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB TweetSentimentExtractionClassification |
|
type: mteb/tweet_sentiment_extraction |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 61.28183361629882 |
|
- type: f1 |
|
value: 61.55481034919965 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB TwentyNewsgroupsClustering |
|
type: mteb/twentynewsgroups-clustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 35.972128420092396 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
name: MTEB TwitterSemEval2015 |
|
type: mteb/twittersemeval2015-pairclassification |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 85.59933241938367 |
|
- type: cos_sim_ap |
|
value: 72.20760361208136 |
|
- type: cos_sim_f1 |
|
value: 66.4447731755424 |
|
- type: cos_sim_precision |
|
value: 62.35539102267469 |
|
- type: cos_sim_recall |
|
value: 71.10817941952506 |
|
- type: dot_accuracy |
|
value: 78.98313166835548 |
|
- type: dot_ap |
|
value: 44.492521645493795 |
|
- type: dot_f1 |
|
value: 45.814889336016094 |
|
- type: dot_precision |
|
value: 37.02439024390244 |
|
- type: dot_recall |
|
value: 60.07915567282321 |
|
- type: euclidean_accuracy |
|
value: 85.3907134767837 |
|
- type: euclidean_ap |
|
value: 71.53847289080343 |
|
- type: euclidean_f1 |
|
value: 65.95952206778834 |
|
- type: euclidean_precision |
|
value: 61.31006346328196 |
|
- type: euclidean_recall |
|
value: 71.37203166226914 |
|
- type: manhattan_accuracy |
|
value: 85.40859510043511 |
|
- type: manhattan_ap |
|
value: 71.49664104395515 |
|
- type: manhattan_f1 |
|
value: 65.98569969356485 |
|
- type: manhattan_precision |
|
value: 63.928748144482924 |
|
- type: manhattan_recall |
|
value: 68.17941952506597 |
|
- type: max_accuracy |
|
value: 85.59933241938367 |
|
- type: max_ap |
|
value: 72.20760361208136 |
|
- type: max_f1 |
|
value: 66.4447731755424 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
name: MTEB TwitterURLCorpus |
|
type: mteb/twitterurlcorpus-pairclassification |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.83261536073273 |
|
- type: cos_sim_ap |
|
value: 85.48178133644264 |
|
- type: cos_sim_f1 |
|
value: 77.87816307403935 |
|
- type: cos_sim_precision |
|
value: 75.88953021114926 |
|
- type: cos_sim_recall |
|
value: 79.97382198952879 |
|
- type: dot_accuracy |
|
value: 79.76287499514883 |
|
- type: dot_ap |
|
value: 59.17438838475084 |
|
- type: dot_f1 |
|
value: 56.34566667855996 |
|
- type: dot_precision |
|
value: 52.50349092359864 |
|
- type: dot_recall |
|
value: 60.794579611949494 |
|
- type: euclidean_accuracy |
|
value: 88.76857996662397 |
|
- type: euclidean_ap |
|
value: 85.22764834359887 |
|
- type: euclidean_f1 |
|
value: 77.65379751543554 |
|
- type: euclidean_precision |
|
value: 75.11152683839401 |
|
- type: euclidean_recall |
|
value: 80.37419156144134 |
|
- type: manhattan_accuracy |
|
value: 88.6987231730508 |
|
- type: manhattan_ap |
|
value: 85.18907981724007 |
|
- type: manhattan_f1 |
|
value: 77.51967028849757 |
|
- type: manhattan_precision |
|
value: 75.49992701795358 |
|
- type: manhattan_recall |
|
value: 79.65044656606098 |
|
- type: max_accuracy |
|
value: 88.83261536073273 |
|
- type: max_ap |
|
value: 85.48178133644264 |
|
- type: max_f1 |
|
value: 77.87816307403935 |
|
--- |
|
|
|
# multilingual-e5-base-mlx |
|
This model was converted to MLX format from [`intfloat/multilingual-e5-base`](). |
|
Refer to the [original model card](https://huggingface.co/intfloat/multilingual-e5-base) for more details on the model. |
|
## Use with mlx |
|
```bash |
|
pip install mlx |
|
git clone https://github.com/ml-explore/mlx-examples.git |
|
cd mlx-examples/llms/hf_llm |
|
python generate.py --model mlx-community/multilingual-e5-base-mlx --prompt "My name is" |
|
``` |
|
|
