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--- |
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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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- feature-extraction |
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- sentence-transformers |
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- llama-cpp |
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- gguf-my-repo |
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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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base_model: intfloat/multilingual-e5-large |
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model-index: |
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- name: multilingual-e5-large |
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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: 79.05970149253731 |
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- type: ap |
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value: 43.486574390835635 |
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- type: f1 |
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value: 73.32700092140148 |
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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: 71.22055674518201 |
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- type: ap |
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value: 81.55756710830498 |
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- type: f1 |
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value: 69.28271787752661 |
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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: 80.41979010494754 |
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- type: ap |
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value: 29.34879922376344 |
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- type: f1 |
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value: 67.62475449011278 |
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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: 77.8372591006424 |
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- type: ap |
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value: 26.557560591210738 |
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- type: f1 |
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value: 64.96619417368707 |
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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: 93.489875 |
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- type: ap |
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value: 90.98758636917603 |
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- type: f1 |
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value: 93.48554819717332 |
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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: 47.564 |
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- type: f1 |
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value: 46.75122173518047 |
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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: 45.400000000000006 |
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- type: f1 |
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value: 44.17195682400632 |
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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: 43.068 |
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- type: f1 |
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value: 42.38155696855596 |
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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: 41.89 |
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- type: f1 |
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value: 40.84407321682663 |
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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: 40.120000000000005 |
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- type: f1 |
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value: 39.522976223819114 |
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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: 38.832 |
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- type: f1 |
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value: 38.0392533394713 |
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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: 30.725 |
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- type: map_at_10 |
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value: 46.055 |
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- type: map_at_100 |
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value: 46.900999999999996 |
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- type: map_at_1000 |
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value: 46.911 |
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- type: map_at_3 |
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value: 41.548 |
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- type: map_at_5 |
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value: 44.297 |
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- type: mrr_at_1 |
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value: 31.152 |
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- type: mrr_at_10 |
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value: 46.231 |
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- type: mrr_at_100 |
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value: 47.07 |
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- type: mrr_at_1000 |
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value: 47.08 |
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- type: mrr_at_3 |
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value: 41.738 |
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- type: mrr_at_5 |
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value: 44.468999999999994 |
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- type: ndcg_at_1 |
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value: 30.725 |
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- type: ndcg_at_10 |
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value: 54.379999999999995 |
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- type: ndcg_at_100 |
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value: 58.138 |
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- type: ndcg_at_1000 |
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value: 58.389 |
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- type: ndcg_at_3 |
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value: 45.156 |
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- type: ndcg_at_5 |
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value: 50.123 |
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- type: precision_at_1 |
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value: 30.725 |
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- type: precision_at_10 |
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value: 8.087 |
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- type: precision_at_100 |
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value: 0.9769999999999999 |
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- type: precision_at_1000 |
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value: 0.1 |
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- type: precision_at_3 |
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value: 18.54 |
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- type: precision_at_5 |
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value: 13.542000000000002 |
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- type: recall_at_1 |
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value: 30.725 |
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- type: recall_at_10 |
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value: 80.868 |
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- type: recall_at_100 |
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value: 97.653 |
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- type: recall_at_1000 |
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value: 99.57300000000001 |
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- type: recall_at_3 |
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value: 55.619 |
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- type: recall_at_5 |
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value: 67.71000000000001 |
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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: 44.30960650674069 |
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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: 38.427074197498996 |
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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: 60.28270056031872 |
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- type: mrr |
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value: 74.38332673789738 |
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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 |
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value: 84.05942144105269 |
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- type: cos_sim_spearman |
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value: 82.51212105850809 |
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- type: euclidean_pearson |
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value: 81.95639829909122 |
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- type: euclidean_spearman |
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value: 82.3717564144213 |
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- type: manhattan_pearson |
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value: 81.79273425468256 |
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- type: manhattan_spearman |
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value: 82.20066817871039 |
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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 |
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metrics: |
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- type: accuracy |
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value: 99.46764091858039 |
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- type: f1 |
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value: 99.37717466945023 |
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- type: precision |
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value: 99.33194154488518 |
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- type: recall |
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value: 99.46764091858039 |
|
- task: |
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type: BitextMining |
|
dataset: |
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name: MTEB BUCC (fr-en) |
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type: mteb/bucc-bitext-mining |
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config: fr-en |
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split: test |
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revision: d51519689f32196a32af33b075a01d0e7c51e252 |
|
metrics: |
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- type: accuracy |
|
value: 98.29407880255337 |
|
- type: f1 |
|
value: 98.11248073959938 |
|
- type: precision |
|
value: 98.02443319392472 |
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- type: recall |
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value: 98.29407880255337 |
|
- task: |
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type: BitextMining |
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dataset: |
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name: MTEB BUCC (ru-en) |
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type: mteb/bucc-bitext-mining |
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config: ru-en |
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split: test |
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revision: d51519689f32196a32af33b075a01d0e7c51e252 |
|
metrics: |
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- type: accuracy |
|
value: 97.79009352268791 |
|
- type: f1 |
|
value: 97.5176076665512 |
|
- type: precision |
|
value: 97.38136473848286 |
|
- type: recall |
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value: 97.79009352268791 |
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- task: |
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type: BitextMining |
|
dataset: |
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name: MTEB BUCC (zh-en) |
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type: mteb/bucc-bitext-mining |
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config: zh-en |
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split: test |
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revision: d51519689f32196a32af33b075a01d0e7c51e252 |
|
metrics: |
|
- type: accuracy |
|
value: 99.26276987888363 |
|
- type: f1 |
|
value: 99.20133403545726 |
|
- type: precision |
|
value: 99.17500438827453 |
|
- type: recall |
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value: 99.26276987888363 |
|
- task: |
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type: Classification |
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dataset: |
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name: MTEB Banking77Classification |
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type: mteb/banking77 |
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config: default |
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split: test |
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 84.72727272727273 |
|
- type: f1 |
|
value: 84.67672206031433 |
|
- task: |
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type: Clustering |
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dataset: |
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name: MTEB BiorxivClusteringP2P |
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type: mteb/biorxiv-clustering-p2p |
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config: default |
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split: test |
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 35.34220182511161 |
|
- task: |
|
type: Clustering |
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dataset: |
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name: MTEB BiorxivClusteringS2S |
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type: mteb/biorxiv-clustering-s2s |
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config: default |
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split: test |
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
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metrics: |
|
- type: v_measure |
|
value: 33.4987096128766 |
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- task: |
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type: Retrieval |
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dataset: |
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name: MTEB CQADupstackRetrieval |
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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: |
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- type: map_at_1 |
|
value: 25.558249999999997 |
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- type: map_at_10 |
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value: 34.44425000000001 |
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- type: map_at_100 |
|
value: 35.59833333333333 |
|
- type: map_at_1000 |
|
value: 35.706916666666665 |
|
- type: map_at_3 |
|
value: 31.691749999999995 |
|
- type: map_at_5 |
|
value: 33.252916666666664 |
|
- type: mrr_at_1 |
|
value: 30.252666666666666 |
|
- type: mrr_at_10 |
|
value: 38.60675 |
|
- type: mrr_at_100 |
|
value: 39.42666666666666 |
|
- type: mrr_at_1000 |
|
value: 39.48408333333334 |
|
- type: mrr_at_3 |
|
value: 36.17441666666665 |
|
- type: mrr_at_5 |
|
value: 37.56275 |
|
- type: ndcg_at_1 |
|
value: 30.252666666666666 |
|
- type: ndcg_at_10 |
|
value: 39.683 |
|
- type: ndcg_at_100 |
|
value: 44.68541666666667 |
|
- type: ndcg_at_1000 |
|
value: 46.94316666666668 |
|
- type: ndcg_at_3 |
|
value: 34.961749999999995 |
|
- type: ndcg_at_5 |
|
value: 37.215666666666664 |
|
- type: precision_at_1 |
|
value: 30.252666666666666 |
|
- type: precision_at_10 |
|
value: 6.904166666666667 |
|
- type: precision_at_100 |
|
value: 1.0989999999999995 |
|
- type: precision_at_1000 |
|
value: 0.14733333333333334 |
|
- type: precision_at_3 |
|
value: 16.037666666666667 |
|
- type: precision_at_5 |
|
value: 11.413583333333333 |
|
- type: recall_at_1 |
|
value: 25.558249999999997 |
|
- type: recall_at_10 |
|
value: 51.13341666666666 |
|
- type: recall_at_100 |
|
value: 73.08366666666667 |
|
- type: recall_at_1000 |
|
value: 88.79483333333334 |
|
- type: recall_at_3 |
|
value: 37.989083333333326 |
|
- type: recall_at_5 |
|
value: 43.787833333333325 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB ClimateFEVER |
|
type: climate-fever |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.338 |
|
- type: map_at_10 |
|
value: 18.360000000000003 |
|
- type: map_at_100 |
|
value: 19.942 |
|
- type: map_at_1000 |
|
value: 20.134 |
|
- type: map_at_3 |
|
value: 15.174000000000001 |
|
- type: map_at_5 |
|
value: 16.830000000000002 |
|
- type: mrr_at_1 |
|
value: 23.257 |
|
- type: mrr_at_10 |
|
value: 33.768 |
|
- type: mrr_at_100 |
|
value: 34.707 |
|
- type: mrr_at_1000 |
|
value: 34.766000000000005 |
|
- type: mrr_at_3 |
|
value: 30.977 |
|
- type: mrr_at_5 |
|
value: 32.528 |
|
- type: ndcg_at_1 |
|
value: 23.257 |
|
- type: ndcg_at_10 |
|
value: 25.733 |
|
- type: ndcg_at_100 |
|
value: 32.288 |
|
- type: ndcg_at_1000 |
|
value: 35.992000000000004 |
|
- type: ndcg_at_3 |
|
value: 20.866 |
|
- type: ndcg_at_5 |
|
value: 22.612 |
|
- type: precision_at_1 |
|
value: 23.257 |
|
- type: precision_at_10 |
|
value: 8.124 |
|
- type: precision_at_100 |
|
value: 1.518 |
|
- type: precision_at_1000 |
|
value: 0.219 |
|
- type: precision_at_3 |
|
value: 15.679000000000002 |
|
- type: precision_at_5 |
|
value: 12.117 |
|
- type: recall_at_1 |
|
value: 10.338 |
|
- type: recall_at_10 |
|
value: 31.154 |
|
- type: recall_at_100 |
|
value: 54.161 |
|
- type: recall_at_1000 |
|
value: 75.21900000000001 |
|
- type: recall_at_3 |
|
value: 19.427 |
|
- type: recall_at_5 |
|
value: 24.214 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB DBPedia |
|
type: dbpedia-entity |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.498 |
|
- type: map_at_10 |
|
value: 19.103 |
|
- type: map_at_100 |
|
value: 27.375 |
|
- type: map_at_1000 |
|
value: 28.981 |
|
- type: map_at_3 |
|
value: 13.764999999999999 |
|
- type: map_at_5 |
|
value: 15.950000000000001 |
|
- type: mrr_at_1 |
|
value: 65.5 |
|
- type: mrr_at_10 |
|
value: 74.53800000000001 |
|
- type: mrr_at_100 |
|
value: 74.71799999999999 |
|
- type: mrr_at_1000 |
|
value: 74.725 |
|
- type: mrr_at_3 |
|
value: 72.792 |
|
- type: mrr_at_5 |
|
value: 73.554 |
|
- type: ndcg_at_1 |
|
value: 53.37499999999999 |
|
- type: ndcg_at_10 |
|
value: 41.286 |
|
- type: ndcg_at_100 |
|
value: 45.972 |
|
- type: ndcg_at_1000 |
|
value: 53.123 |
|
- type: ndcg_at_3 |
|
value: 46.172999999999995 |
|
- type: ndcg_at_5 |
|
value: 43.033 |
|
- type: precision_at_1 |
|
value: 65.5 |
|
- type: precision_at_10 |
|
value: 32.725 |
|
- type: precision_at_100 |
|
value: 10.683 |
|
- type: precision_at_1000 |
|
value: 1.978 |
|
- type: precision_at_3 |
|
value: 50 |
|
- type: precision_at_5 |
|
value: 41.349999999999994 |
|
- type: recall_at_1 |
|
value: 8.498 |
|
- type: recall_at_10 |
|
value: 25.070999999999998 |
|
- type: recall_at_100 |
|
value: 52.383 |
|
- type: recall_at_1000 |
|
value: 74.91499999999999 |
|
- type: recall_at_3 |
|
value: 15.207999999999998 |
|
- type: recall_at_5 |
|
value: 18.563 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB EmotionClassification |
|
type: mteb/emotion |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 46.5 |
|
- type: f1 |
|
value: 41.93833713984145 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB FEVER |
|
type: fever |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 67.914 |
|
- type: map_at_10 |
|
value: 78.10000000000001 |
|
- type: map_at_100 |
|
value: 78.333 |
|
- type: map_at_1000 |
|
value: 78.346 |
|
- type: map_at_3 |
|
value: 76.626 |
|
- type: map_at_5 |
|
value: 77.627 |
|
- type: mrr_at_1 |
|
value: 72.74199999999999 |
|
- type: mrr_at_10 |
|
value: 82.414 |
|
- type: mrr_at_100 |
|
value: 82.511 |
|
- type: mrr_at_1000 |
|
value: 82.513 |
|
- type: mrr_at_3 |
|
value: 81.231 |
|
- type: mrr_at_5 |
|
value: 82.065 |
|
- type: ndcg_at_1 |
|
value: 72.74199999999999 |
|
- type: ndcg_at_10 |
|
value: 82.806 |
|
- type: ndcg_at_100 |
|
value: 83.677 |
|
- type: ndcg_at_1000 |
|
value: 83.917 |
|
- type: ndcg_at_3 |
|
value: 80.305 |
|
- type: ndcg_at_5 |
|
value: 81.843 |
|
- type: precision_at_1 |
|
value: 72.74199999999999 |
|
- type: precision_at_10 |
|
value: 10.24 |
|
- type: precision_at_100 |
|
value: 1.089 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 31.268 |
|
- type: precision_at_5 |
|
value: 19.706000000000003 |
|
- type: recall_at_1 |
|
value: 67.914 |
|
- type: recall_at_10 |
|
value: 92.889 |
|
- type: recall_at_100 |
|
value: 96.42699999999999 |
|
- type: recall_at_1000 |
|
value: 97.92 |
|
- type: recall_at_3 |
|
value: 86.21 |
|
- type: recall_at_5 |
|
value: 90.036 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB FiQA2018 |
|
type: fiqa |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.166 |
|
- type: map_at_10 |
|
value: 35.57 |
|
- type: map_at_100 |
|
value: 37.405 |
|
- type: map_at_1000 |
|
value: 37.564 |
|
- type: map_at_3 |
|
value: 30.379 |
|
- type: map_at_5 |
|
value: 33.324 |
|
- type: mrr_at_1 |
|
value: 43.519000000000005 |
|
- type: mrr_at_10 |
|
value: 51.556000000000004 |
|
- type: mrr_at_100 |
|
value: 52.344 |
|
- type: mrr_at_1000 |
|
value: 52.373999999999995 |
|
- type: mrr_at_3 |
|
value: 48.868 |
|
- type: mrr_at_5 |
|
value: 50.319 |
|
- type: ndcg_at_1 |
|
value: 43.519000000000005 |
|
- type: ndcg_at_10 |
|
value: 43.803 |
|
- type: ndcg_at_100 |
|
value: 50.468999999999994 |
|
- type: ndcg_at_1000 |
|
value: 53.111 |
|
- type: ndcg_at_3 |
|
value: 38.893 |
|
- type: ndcg_at_5 |
|
value: 40.653 |
|
- type: precision_at_1 |
|
value: 43.519000000000005 |
|
- type: precision_at_10 |
|
value: 12.253 |
|
- type: precision_at_100 |
|
value: 1.931 |
|
- type: precision_at_1000 |
|
value: 0.242 |
|
- type: precision_at_3 |
|
value: 25.617 |
|
- type: precision_at_5 |
|
value: 19.383 |
|
- type: recall_at_1 |
|
value: 22.166 |
|
- type: recall_at_10 |
|
value: 51.6 |
|
- type: recall_at_100 |
|
value: 76.574 |
|
- type: recall_at_1000 |
|
value: 92.192 |
|
- type: recall_at_3 |
|
value: 34.477999999999994 |
|
- type: recall_at_5 |
|
value: 41.835 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB HotpotQA |
|
type: hotpotqa |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 39.041 |
|
- type: map_at_10 |
|
value: 62.961999999999996 |
|
- type: map_at_100 |
|
value: 63.79899999999999 |
|
- type: map_at_1000 |
|
value: 63.854 |
|
- type: map_at_3 |
|
value: 59.399 |
|
- type: map_at_5 |
|
value: 61.669 |
|
- type: mrr_at_1 |
|
value: 78.082 |
|
- type: mrr_at_10 |
|
value: 84.321 |
|
- type: mrr_at_100 |
|
value: 84.49600000000001 |
|
- type: mrr_at_1000 |
|
value: 84.502 |
|
- type: mrr_at_3 |
|
value: 83.421 |
|
- type: mrr_at_5 |
|
value: 83.977 |
|
- type: ndcg_at_1 |
|
value: 78.082 |
|
- type: ndcg_at_10 |
|
value: 71.229 |
|
- type: ndcg_at_100 |
|
value: 74.10900000000001 |
|
- type: ndcg_at_1000 |
|
value: 75.169 |
|
- type: ndcg_at_3 |
|
value: 66.28699999999999 |
|
- type: ndcg_at_5 |
|
value: 69.084 |
|
- type: precision_at_1 |
|
value: 78.082 |
|
- type: precision_at_10 |
|
value: 14.993 |
|
- type: precision_at_100 |
|
value: 1.7239999999999998 |
|
- type: precision_at_1000 |
|
value: 0.186 |
|
- type: precision_at_3 |
|
value: 42.737 |
|
- type: precision_at_5 |
|
value: 27.843 |
|
- type: recall_at_1 |
|
value: 39.041 |
|
- type: recall_at_10 |
|
value: 74.96300000000001 |
|
- type: recall_at_100 |
|
value: 86.199 |
|
- type: recall_at_1000 |
|
value: 93.228 |
|
- type: recall_at_3 |
|
value: 64.105 |
|
- type: recall_at_5 |
|
value: 69.608 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB ImdbClassification |
|
type: mteb/imdb |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 90.23160000000001 |
|
- type: ap |
|
value: 85.5674856808308 |
|
- type: f1 |
|
value: 90.18033354786317 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB MSMARCO |
|
type: msmarco |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.091 |
|
- type: map_at_10 |
|
value: 36.753 |
|
- type: map_at_100 |
|
value: 37.913000000000004 |
|
- type: map_at_1000 |
|
value: 37.958999999999996 |
|
- type: map_at_3 |
|
value: 32.818999999999996 |
|
- type: map_at_5 |
|
value: 35.171 |
|
- type: mrr_at_1 |
|
value: 24.742 |
|
- type: mrr_at_10 |
|
value: 37.285000000000004 |
|
- type: mrr_at_100 |
|
value: 38.391999999999996 |
|
- type: mrr_at_1000 |
|
value: 38.431 |
|
- type: mrr_at_3 |
|
value: 33.440999999999995 |
|
- type: mrr_at_5 |
|
value: 35.75 |
|
- type: ndcg_at_1 |
|
value: 24.742 |
|
- type: ndcg_at_10 |
|
value: 43.698 |
|
- type: ndcg_at_100 |
|
value: 49.145 |
|
- type: ndcg_at_1000 |
|
value: 50.23800000000001 |
|
- type: ndcg_at_3 |
|
value: 35.769 |
|
- type: ndcg_at_5 |
|
value: 39.961999999999996 |
|
- type: precision_at_1 |
|
value: 24.742 |
|
- type: precision_at_10 |
|
value: 6.7989999999999995 |
|
- type: precision_at_100 |
|
value: 0.95 |
|
- type: precision_at_1000 |
|
value: 0.104 |
|
- type: precision_at_3 |
|
value: 15.096000000000002 |
|
- type: precision_at_5 |
|
value: 11.183 |
|
- type: recall_at_1 |
|
value: 24.091 |
|
- type: recall_at_10 |
|
value: 65.068 |
|
- type: recall_at_100 |
|
value: 89.899 |
|
- type: recall_at_1000 |
|
value: 98.16 |
|
- type: recall_at_3 |
|
value: 43.68 |
|
- type: recall_at_5 |
|
value: 53.754999999999995 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPDomainClassification (en) |
|
type: mteb/mtop_domain |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 93.66621067031465 |
|
- type: f1 |
|
value: 93.49622853272142 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPDomainClassification (de) |
|
type: mteb/mtop_domain |
|
config: de |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 91.94702733164272 |
|
- type: f1 |
|
value: 91.17043441745282 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPDomainClassification (es) |
|
type: mteb/mtop_domain |
|
config: es |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 92.20146764509674 |
|
- type: f1 |
|
value: 91.98359080555608 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPDomainClassification (fr) |
|
type: mteb/mtop_domain |
|
config: fr |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 88.99780770435328 |
|
- type: f1 |
|
value: 89.19746342724068 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPDomainClassification (hi) |
|
type: mteb/mtop_domain |
|
config: hi |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 89.78486912871998 |
|
- type: f1 |
|
value: 89.24578823628642 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPDomainClassification (th) |
|
type: mteb/mtop_domain |
|
config: th |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 88.74502712477394 |
|
- type: f1 |
|
value: 89.00297573881542 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPIntentClassification (en) |
|
type: mteb/mtop_intent |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 77.9046967624259 |
|
- type: f1 |
|
value: 59.36787125785957 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPIntentClassification (de) |
|
type: mteb/mtop_intent |
|
config: de |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 74.5280360664976 |
|
- type: f1 |
|
value: 57.17723440888718 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPIntentClassification (es) |
|
type: mteb/mtop_intent |
|
config: es |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 75.44029352901934 |
|
- type: f1 |
|
value: 54.052855531072964 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPIntentClassification (fr) |
|
type: mteb/mtop_intent |
|
config: fr |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 70.5606013153774 |
|
- type: f1 |
|
value: 52.62215934386531 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPIntentClassification (hi) |
|
type: mteb/mtop_intent |
|
config: hi |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 73.11581211903908 |
|
- type: f1 |
|
value: 52.341291845645465 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPIntentClassification (th) |
|
type: mteb/mtop_intent |
|
config: th |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 74.28933092224233 |
|
- type: f1 |
|
value: 57.07918745504911 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (af) |
|
type: mteb/amazon_massive_intent |
|
config: af |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 62.38063214525892 |
|
- type: f1 |
|
value: 59.46463723443009 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (am) |
|
type: mteb/amazon_massive_intent |
|
config: am |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 56.06926698049766 |
|
- type: f1 |
|
value: 52.49084283283562 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (ar) |
|
type: mteb/amazon_massive_intent |
|
config: ar |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 60.74983187626093 |
|
- type: f1 |
|
value: 56.960640620165904 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (az) |
|
type: mteb/amazon_massive_intent |
|
config: az |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 64.86550100874243 |
|
- type: f1 |
|
value: 62.47370548140688 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (bn) |
|
type: mteb/amazon_massive_intent |
|
config: bn |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 63.971082716879636 |
|
- type: f1 |
|
value: 61.03812421957381 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (cy) |
|
type: mteb/amazon_massive_intent |
|
config: cy |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 54.98318762609282 |
|
- type: f1 |
|
value: 51.51207916008392 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (da) |
|
type: mteb/amazon_massive_intent |
|
config: da |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 69.45527908540686 |
|
- type: f1 |
|
value: 66.16631905400318 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (de) |
|
type: mteb/amazon_massive_intent |
|
config: de |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 69.32750504371216 |
|
- type: f1 |
|
value: 66.16755288646591 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (el) |
|
type: mteb/amazon_massive_intent |
|
config: el |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 69.09213180901143 |
|
- type: f1 |
|
value: 66.95654394661507 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (en) |
|
type: mteb/amazon_massive_intent |
|
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|
type: Clustering |
|
dataset: |
|
name: MTEB MedrxivClusteringP2P |
|
type: mteb/medrxiv-clustering-p2p |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 31.480506569594695 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB MedrxivClusteringS2S |
|
type: mteb/medrxiv-clustering-s2s |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 29.71252128004552 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB MindSmallReranking |
|
type: mteb/mind_small |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 31.421396787056548 |
|
- type: mrr |
|
value: 32.48155274872267 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB NFCorpus |
|
type: nfcorpus |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.595 |
|
- type: map_at_10 |
|
value: 12.642000000000001 |
|
- type: map_at_100 |
|
value: 15.726 |
|
- type: map_at_1000 |
|
value: 17.061999999999998 |
|
- type: map_at_3 |
|
value: 9.125 |
|
- type: map_at_5 |
|
value: 10.866000000000001 |
|
- type: mrr_at_1 |
|
value: 43.344 |
|
- type: mrr_at_10 |
|
value: 52.227999999999994 |
|
- type: mrr_at_100 |
|
value: 52.898999999999994 |
|
- type: mrr_at_1000 |
|
value: 52.944 |
|
- type: mrr_at_3 |
|
value: 49.845 |
|
- type: mrr_at_5 |
|
value: 51.115 |
|
- type: ndcg_at_1 |
|
value: 41.949999999999996 |
|
- type: ndcg_at_10 |
|
value: 33.995 |
|
- type: ndcg_at_100 |
|
value: 30.869999999999997 |
|
- type: ndcg_at_1000 |
|
value: 39.487 |
|
- type: ndcg_at_3 |
|
value: 38.903999999999996 |
|
- type: ndcg_at_5 |
|
value: 37.236999999999995 |
|
- type: precision_at_1 |
|
value: 43.344 |
|
- type: precision_at_10 |
|
value: 25.480000000000004 |
|
- type: precision_at_100 |
|
value: 7.672 |
|
- type: precision_at_1000 |
|
value: 2.028 |
|
- type: precision_at_3 |
|
value: 36.636 |
|
- type: precision_at_5 |
|
value: 32.632 |
|
- type: recall_at_1 |
|
value: 5.595 |
|
- type: recall_at_10 |
|
value: 16.466 |
|
- type: recall_at_100 |
|
value: 31.226 |
|
- type: recall_at_1000 |
|
value: 62.778999999999996 |
|
- type: recall_at_3 |
|
value: 9.931 |
|
- type: recall_at_5 |
|
value: 12.884 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB NQ |
|
type: nq |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 40.414 |
|
- type: map_at_10 |
|
value: 56.754000000000005 |
|
- type: map_at_100 |
|
value: 57.457 |
|
- type: map_at_1000 |
|
value: 57.477999999999994 |
|
- type: map_at_3 |
|
value: 52.873999999999995 |
|
- type: map_at_5 |
|
value: 55.175 |
|
- type: mrr_at_1 |
|
value: 45.278 |
|
- type: mrr_at_10 |
|
value: 59.192 |
|
- type: mrr_at_100 |
|
value: 59.650000000000006 |
|
- type: mrr_at_1000 |
|
value: 59.665 |
|
- type: mrr_at_3 |
|
value: 56.141 |
|
- type: mrr_at_5 |
|
value: 57.998000000000005 |
|
- type: ndcg_at_1 |
|
value: 45.278 |
|
- type: ndcg_at_10 |
|
value: 64.056 |
|
- type: ndcg_at_100 |
|
value: 66.89 |
|
- type: ndcg_at_1000 |
|
value: 67.364 |
|
- type: ndcg_at_3 |
|
value: 56.97 |
|
- type: ndcg_at_5 |
|
value: 60.719 |
|
- type: precision_at_1 |
|
value: 45.278 |
|
- type: precision_at_10 |
|
value: 9.994 |
|
- type: precision_at_100 |
|
value: 1.165 |
|
- type: precision_at_1000 |
|
value: 0.121 |
|
- type: precision_at_3 |
|
value: 25.512 |
|
- type: precision_at_5 |
|
value: 17.509 |
|
- type: recall_at_1 |
|
value: 40.414 |
|
- type: recall_at_10 |
|
value: 83.596 |
|
- type: recall_at_100 |
|
value: 95.72 |
|
- type: recall_at_1000 |
|
value: 99.24 |
|
- type: recall_at_3 |
|
value: 65.472 |
|
- type: recall_at_5 |
|
value: 74.039 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB QuoraRetrieval |
|
type: quora |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 70.352 |
|
- type: map_at_10 |
|
value: 84.369 |
|
- type: map_at_100 |
|
value: 85.02499999999999 |
|
- type: map_at_1000 |
|
value: 85.04 |
|
- type: map_at_3 |
|
value: 81.42399999999999 |
|
- type: map_at_5 |
|
value: 83.279 |
|
- type: mrr_at_1 |
|
value: 81.05 |
|
- type: mrr_at_10 |
|
value: 87.401 |
|
- type: mrr_at_100 |
|
value: 87.504 |
|
- type: mrr_at_1000 |
|
value: 87.505 |
|
- type: mrr_at_3 |
|
value: 86.443 |
|
- type: mrr_at_5 |
|
value: 87.10799999999999 |
|
- type: ndcg_at_1 |
|
value: 81.04 |
|
- type: ndcg_at_10 |
|
value: 88.181 |
|
- type: ndcg_at_100 |
|
value: 89.411 |
|
- type: ndcg_at_1000 |
|
value: 89.507 |
|
- type: ndcg_at_3 |
|
value: 85.28099999999999 |
|
- type: ndcg_at_5 |
|
value: 86.888 |
|
- type: precision_at_1 |
|
value: 81.04 |
|
- type: precision_at_10 |
|
value: 13.406 |
|
- type: precision_at_100 |
|
value: 1.5350000000000001 |
|
- type: precision_at_1000 |
|
value: 0.157 |
|
- type: precision_at_3 |
|
value: 37.31 |
|
- type: precision_at_5 |
|
value: 24.54 |
|
- type: recall_at_1 |
|
value: 70.352 |
|
- type: recall_at_10 |
|
value: 95.358 |
|
- type: recall_at_100 |
|
value: 99.541 |
|
- type: recall_at_1000 |
|
value: 99.984 |
|
- type: recall_at_3 |
|
value: 87.111 |
|
- type: recall_at_5 |
|
value: 91.643 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB RedditClustering |
|
type: mteb/reddit-clustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 46.54068723291946 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB RedditClusteringP2P |
|
type: mteb/reddit-clustering-p2p |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 63.216287629895994 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB SCIDOCS |
|
type: scidocs |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.023000000000001 |
|
- type: map_at_10 |
|
value: 10.071 |
|
- type: map_at_100 |
|
value: 11.892 |
|
- type: map_at_1000 |
|
value: 12.196 |
|
- type: map_at_3 |
|
value: 7.234 |
|
- type: map_at_5 |
|
value: 8.613999999999999 |
|
- type: mrr_at_1 |
|
value: 19.900000000000002 |
|
- type: mrr_at_10 |
|
value: 30.516 |
|
- type: mrr_at_100 |
|
value: 31.656000000000002 |
|
- type: mrr_at_1000 |
|
value: 31.723000000000003 |
|
- type: mrr_at_3 |
|
value: 27.400000000000002 |
|
- type: mrr_at_5 |
|
value: 29.270000000000003 |
|
- type: ndcg_at_1 |
|
value: 19.900000000000002 |
|
- type: ndcg_at_10 |
|
value: 17.474 |
|
- type: ndcg_at_100 |
|
value: 25.020999999999997 |
|
- type: ndcg_at_1000 |
|
value: 30.728 |
|
- type: ndcg_at_3 |
|
value: 16.588 |
|
- type: ndcg_at_5 |
|
value: 14.498 |
|
- type: precision_at_1 |
|
value: 19.900000000000002 |
|
- type: precision_at_10 |
|
value: 9.139999999999999 |
|
- type: precision_at_100 |
|
value: 2.011 |
|
- type: precision_at_1000 |
|
value: 0.33899999999999997 |
|
- type: precision_at_3 |
|
value: 15.667 |
|
- type: precision_at_5 |
|
value: 12.839999999999998 |
|
- type: recall_at_1 |
|
value: 4.023000000000001 |
|
- type: recall_at_10 |
|
value: 18.497 |
|
- type: recall_at_100 |
|
value: 40.8 |
|
- type: recall_at_1000 |
|
value: 68.812 |
|
- type: recall_at_3 |
|
value: 9.508 |
|
- type: recall_at_5 |
|
value: 12.983 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB SICK-R |
|
type: mteb/sickr-sts |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.967008785134 |
|
- type: cos_sim_spearman |
|
value: 80.23142141101837 |
|
- type: euclidean_pearson |
|
value: 81.20166064704539 |
|
- type: euclidean_spearman |
|
value: 80.18961335654585 |
|
- type: manhattan_pearson |
|
value: 81.13925443187625 |
|
- type: manhattan_spearman |
|
value: 80.07948723044424 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS12 |
|
type: mteb/sts12-sts |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.94262461316023 |
|
- type: cos_sim_spearman |
|
value: 80.01596278563865 |
|
- type: euclidean_pearson |
|
value: 83.80799622922581 |
|
- type: euclidean_spearman |
|
value: 79.94984954947103 |
|
- type: manhattan_pearson |
|
value: 83.68473841756281 |
|
- type: manhattan_spearman |
|
value: 79.84990707951822 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS13 |
|
type: mteb/sts13-sts |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 80.57346443146068 |
|
- type: cos_sim_spearman |
|
value: 81.54689837570866 |
|
- type: euclidean_pearson |
|
value: 81.10909881516007 |
|
- type: euclidean_spearman |
|
value: 81.56746243261762 |
|
- type: manhattan_pearson |
|
value: 80.87076036186582 |
|
- type: manhattan_spearman |
|
value: 81.33074987964402 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS14 |
|
type: mteb/sts14-sts |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.54733787179849 |
|
- type: cos_sim_spearman |
|
value: 77.72202105610411 |
|
- type: euclidean_pearson |
|
value: 78.9043595478849 |
|
- type: euclidean_spearman |
|
value: 77.93422804309435 |
|
- type: manhattan_pearson |
|
value: 78.58115121621368 |
|
- type: manhattan_spearman |
|
value: 77.62508135122033 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS15 |
|
type: mteb/sts15-sts |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 88.59880017237558 |
|
- type: cos_sim_spearman |
|
value: 89.31088630824758 |
|
- type: euclidean_pearson |
|
value: 88.47069261564656 |
|
- type: euclidean_spearman |
|
value: 89.33581971465233 |
|
- type: manhattan_pearson |
|
value: 88.40774264100956 |
|
- type: manhattan_spearman |
|
value: 89.28657485627835 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS16 |
|
type: mteb/sts16-sts |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.08055117917084 |
|
- type: cos_sim_spearman |
|
value: 85.78491813080304 |
|
- type: euclidean_pearson |
|
value: 84.99329155500392 |
|
- type: euclidean_spearman |
|
value: 85.76728064677287 |
|
- type: manhattan_pearson |
|
value: 84.87947428989587 |
|
- type: manhattan_spearman |
|
value: 85.62429454917464 |
|
- 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: 82.14190939287384 |
|
- type: cos_sim_spearman |
|
value: 82.27331573306041 |
|
- type: euclidean_pearson |
|
value: 81.891896953716 |
|
- type: euclidean_spearman |
|
value: 82.37695542955998 |
|
- type: manhattan_pearson |
|
value: 81.73123869460504 |
|
- type: manhattan_spearman |
|
value: 82.19989168441421 |
|
- 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: 76.84695301843362 |
|
- type: cos_sim_spearman |
|
value: 77.87790986014461 |
|
- type: euclidean_pearson |
|
value: 76.91981583106315 |
|
- type: euclidean_spearman |
|
value: 77.88154772749589 |
|
- type: manhattan_pearson |
|
value: 76.94953277451093 |
|
- type: manhattan_spearman |
|
value: 77.80499230728604 |
|
- 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: 75.44657840482016 |
|
- type: cos_sim_spearman |
|
value: 75.05531095119674 |
|
- type: euclidean_pearson |
|
value: 75.88161755829299 |
|
- type: euclidean_spearman |
|
value: 74.73176238219332 |
|
- type: manhattan_pearson |
|
value: 75.63984765635362 |
|
- type: manhattan_spearman |
|
value: 74.86476440770737 |
|
- 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: 85.64700140524133 |
|
- type: cos_sim_spearman |
|
value: 86.16014210425672 |
|
- type: euclidean_pearson |
|
value: 86.49086860843221 |
|
- type: euclidean_spearman |
|
value: 86.09729326815614 |
|
- type: manhattan_pearson |
|
value: 86.43406265125513 |
|
- type: manhattan_spearman |
|
value: 86.17740150939994 |
|
- 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: 87.91170098764921 |
|
- type: cos_sim_spearman |
|
value: 88.12437004058931 |
|
- type: euclidean_pearson |
|
value: 88.81828254494437 |
|
- type: euclidean_spearman |
|
value: 88.14831794572122 |
|
- type: manhattan_pearson |
|
value: 88.93442183448961 |
|
- type: manhattan_spearman |
|
value: 88.15254630778304 |
|
- 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: 72.91390577997292 |
|
- type: cos_sim_spearman |
|
value: 71.22979457536074 |
|
- type: euclidean_pearson |
|
value: 74.40314008106749 |
|
- type: euclidean_spearman |
|
value: 72.54972136083246 |
|
- type: manhattan_pearson |
|
value: 73.85687539530218 |
|
- type: manhattan_spearman |
|
value: 72.09500771742637 |
|
- 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: 80.9301067983089 |
|
- type: cos_sim_spearman |
|
value: 80.74989828346473 |
|
- type: euclidean_pearson |
|
value: 81.36781301814257 |
|
- type: euclidean_spearman |
|
value: 80.9448819964426 |
|
- type: manhattan_pearson |
|
value: 81.0351322685609 |
|
- type: manhattan_spearman |
|
value: 80.70192121844177 |
|
- 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: 87.13820465980005 |
|
- type: cos_sim_spearman |
|
value: 86.73532498758757 |
|
- type: euclidean_pearson |
|
value: 87.21329451846637 |
|
- type: euclidean_spearman |
|
value: 86.57863198601002 |
|
- type: manhattan_pearson |
|
value: 87.06973713818554 |
|
- type: manhattan_spearman |
|
value: 86.47534918791499 |
|
- 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: 85.48720108904415 |
|
- type: cos_sim_spearman |
|
value: 85.62221757068387 |
|
- type: euclidean_pearson |
|
value: 86.1010129512749 |
|
- type: euclidean_spearman |
|
value: 85.86580966509942 |
|
- type: manhattan_pearson |
|
value: 86.26800938808971 |
|
- type: manhattan_spearman |
|
value: 85.88902721678429 |
|
- 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: 83.98021347333516 |
|
- type: cos_sim_spearman |
|
value: 84.53806553803501 |
|
- type: euclidean_pearson |
|
value: 84.61483347248364 |
|
- type: euclidean_spearman |
|
value: 85.14191408011702 |
|
- type: manhattan_pearson |
|
value: 84.75297588825967 |
|
- type: manhattan_spearman |
|
value: 85.33176753669242 |
|
- 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: 84.51856644893233 |
|
- type: cos_sim_spearman |
|
value: 85.27510748506413 |
|
- type: euclidean_pearson |
|
value: 85.09886861540977 |
|
- type: euclidean_spearman |
|
value: 85.62579245860887 |
|
- type: manhattan_pearson |
|
value: 84.93017860464607 |
|
- type: manhattan_spearman |
|
value: 85.5063988898453 |
|
- 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: 62.581573200584195 |
|
- type: cos_sim_spearman |
|
value: 63.05503590247928 |
|
- type: euclidean_pearson |
|
value: 63.652564812602094 |
|
- type: euclidean_spearman |
|
value: 62.64811520876156 |
|
- type: manhattan_pearson |
|
value: 63.506842893061076 |
|
- type: manhattan_spearman |
|
value: 62.51289573046917 |
|
- 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: 48.2248801729127 |
|
- type: cos_sim_spearman |
|
value: 56.5936604678561 |
|
- type: euclidean_pearson |
|
value: 43.98149464089 |
|
- type: euclidean_spearman |
|
value: 56.108561882423615 |
|
- type: manhattan_pearson |
|
value: 43.86880305903564 |
|
- type: manhattan_spearman |
|
value: 56.04671150510166 |
|
- 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: 55.17564527009831 |
|
- type: cos_sim_spearman |
|
value: 64.57978560979488 |
|
- type: euclidean_pearson |
|
value: 58.8818330154583 |
|
- type: euclidean_spearman |
|
value: 64.99214839071281 |
|
- type: manhattan_pearson |
|
value: 58.72671436121381 |
|
- type: manhattan_spearman |
|
value: 65.10713416616109 |
|
- 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: 26.772131864023297 |
|
- type: cos_sim_spearman |
|
value: 34.68200792408681 |
|
- type: euclidean_pearson |
|
value: 16.68082419005441 |
|
- type: euclidean_spearman |
|
value: 34.83099932652166 |
|
- type: manhattan_pearson |
|
value: 16.52605949659529 |
|
- type: manhattan_spearman |
|
value: 34.82075801399475 |
|
- 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: 54.42415189043831 |
|
- type: cos_sim_spearman |
|
value: 63.54594264576758 |
|
- type: euclidean_pearson |
|
value: 57.36577498297745 |
|
- type: euclidean_spearman |
|
value: 63.111466379158074 |
|
- type: manhattan_pearson |
|
value: 57.584543715873885 |
|
- type: manhattan_spearman |
|
value: 63.22361054139183 |
|
- 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: 47.55216762405518 |
|
- type: cos_sim_spearman |
|
value: 56.98670142896412 |
|
- type: euclidean_pearson |
|
value: 50.15318757562699 |
|
- type: euclidean_spearman |
|
value: 56.524941926541906 |
|
- type: manhattan_pearson |
|
value: 49.955618528674904 |
|
- type: manhattan_spearman |
|
value: 56.37102209240117 |
|
- 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: 49.20540980338571 |
|
- type: cos_sim_spearman |
|
value: 59.9009453504406 |
|
- type: euclidean_pearson |
|
value: 49.557749853620535 |
|
- type: euclidean_spearman |
|
value: 59.76631621172456 |
|
- type: manhattan_pearson |
|
value: 49.62340591181147 |
|
- type: manhattan_spearman |
|
value: 59.94224880322436 |
|
- 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: 51.508169956576985 |
|
- type: cos_sim_spearman |
|
value: 66.82461565306046 |
|
- type: euclidean_pearson |
|
value: 56.2274426480083 |
|
- type: euclidean_spearman |
|
value: 66.6775323848333 |
|
- type: manhattan_pearson |
|
value: 55.98277796300661 |
|
- type: manhattan_spearman |
|
value: 66.63669848497175 |
|
- 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: 72.86478788045507 |
|
- type: cos_sim_spearman |
|
value: 76.7946552053193 |
|
- type: euclidean_pearson |
|
value: 75.01598530490269 |
|
- type: euclidean_spearman |
|
value: 76.83618917858281 |
|
- type: manhattan_pearson |
|
value: 74.68337628304332 |
|
- type: manhattan_spearman |
|
value: 76.57480204017773 |
|
- 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: 55.922619099401984 |
|
- type: cos_sim_spearman |
|
value: 56.599362477240774 |
|
- type: euclidean_pearson |
|
value: 56.68307052369783 |
|
- type: euclidean_spearman |
|
value: 54.28760436777401 |
|
- type: manhattan_pearson |
|
value: 56.67763566500681 |
|
- type: manhattan_spearman |
|
value: 53.94619541711359 |
|
- 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: 66.74357206710913 |
|
- type: cos_sim_spearman |
|
value: 72.5208244925311 |
|
- type: euclidean_pearson |
|
value: 67.49254562186032 |
|
- type: euclidean_spearman |
|
value: 72.02469076238683 |
|
- type: manhattan_pearson |
|
value: 67.45251772238085 |
|
- type: manhattan_spearman |
|
value: 72.05538819984538 |
|
- 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: 71.25734330033191 |
|
- type: cos_sim_spearman |
|
value: 76.98349083946823 |
|
- type: euclidean_pearson |
|
value: 73.71642838667736 |
|
- type: euclidean_spearman |
|
value: 77.01715504651384 |
|
- type: manhattan_pearson |
|
value: 73.61712711868105 |
|
- type: manhattan_spearman |
|
value: 77.01392571153896 |
|
- 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: 63.18215462781212 |
|
- type: cos_sim_spearman |
|
value: 65.54373266117607 |
|
- type: euclidean_pearson |
|
value: 64.54126095439005 |
|
- type: euclidean_spearman |
|
value: 65.30410369102711 |
|
- type: manhattan_pearson |
|
value: 63.50332221148234 |
|
- type: manhattan_spearman |
|
value: 64.3455878104313 |
|
- 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: 62.30509221440029 |
|
- type: cos_sim_spearman |
|
value: 65.99582704642478 |
|
- type: euclidean_pearson |
|
value: 63.43818859884195 |
|
- type: euclidean_spearman |
|
value: 66.83172582815764 |
|
- type: manhattan_pearson |
|
value: 63.055779168508764 |
|
- type: manhattan_spearman |
|
value: 65.49585020501449 |
|
- 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: 59.587830825340404 |
|
- type: cos_sim_spearman |
|
value: 68.93467614588089 |
|
- type: euclidean_pearson |
|
value: 62.3073527367404 |
|
- type: euclidean_spearman |
|
value: 69.69758171553175 |
|
- type: manhattan_pearson |
|
value: 61.9074580815789 |
|
- type: manhattan_spearman |
|
value: 69.57696375597865 |
|
- 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: 57.143220125577066 |
|
- type: cos_sim_spearman |
|
value: 67.78857859159226 |
|
- type: euclidean_pearson |
|
value: 55.58225107923733 |
|
- type: euclidean_spearman |
|
value: 67.80662907184563 |
|
- type: manhattan_pearson |
|
value: 56.24953502726514 |
|
- type: manhattan_spearman |
|
value: 67.98262125431616 |
|
- 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: 21.826928900322066 |
|
- type: cos_sim_spearman |
|
value: 49.578506634400405 |
|
- type: euclidean_pearson |
|
value: 27.939890138843214 |
|
- type: euclidean_spearman |
|
value: 52.71950519136242 |
|
- type: manhattan_pearson |
|
value: 26.39878683847546 |
|
- type: manhattan_spearman |
|
value: 47.54609580342499 |
|
- 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: 57.27603854632001 |
|
- type: cos_sim_spearman |
|
value: 50.709255283710995 |
|
- type: euclidean_pearson |
|
value: 59.5419024445929 |
|
- type: euclidean_spearman |
|
value: 50.709255283710995 |
|
- type: manhattan_pearson |
|
value: 59.03256832438492 |
|
- type: manhattan_spearman |
|
value: 61.97797868009122 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STSBenchmark |
|
type: mteb/stsbenchmark-sts |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 85.00757054859712 |
|
- type: cos_sim_spearman |
|
value: 87.29283629622222 |
|
- type: euclidean_pearson |
|
value: 86.54824171775536 |
|
- type: euclidean_spearman |
|
value: 87.24364730491402 |
|
- type: manhattan_pearson |
|
value: 86.5062156915074 |
|
- type: manhattan_spearman |
|
value: 87.15052170378574 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB SciDocsRR |
|
type: mteb/scidocs-reranking |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 82.03549357197389 |
|
- type: mrr |
|
value: 95.05437645143527 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB SciFact |
|
type: scifact |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 57.260999999999996 |
|
- type: map_at_10 |
|
value: 66.259 |
|
- type: map_at_100 |
|
value: 66.884 |
|
- type: map_at_1000 |
|
value: 66.912 |
|
- type: map_at_3 |
|
value: 63.685 |
|
- type: map_at_5 |
|
value: 65.35499999999999 |
|
- type: mrr_at_1 |
|
value: 60.333000000000006 |
|
- type: mrr_at_10 |
|
value: 67.5 |
|
- type: mrr_at_100 |
|
value: 68.013 |
|
- type: mrr_at_1000 |
|
value: 68.038 |
|
- type: mrr_at_3 |
|
value: 65.61099999999999 |
|
- type: mrr_at_5 |
|
value: 66.861 |
|
- type: ndcg_at_1 |
|
value: 60.333000000000006 |
|
- type: ndcg_at_10 |
|
value: 70.41 |
|
- type: ndcg_at_100 |
|
value: 73.10600000000001 |
|
- type: ndcg_at_1000 |
|
value: 73.846 |
|
- type: ndcg_at_3 |
|
value: 66.133 |
|
- type: ndcg_at_5 |
|
value: 68.499 |
|
- type: precision_at_1 |
|
value: 60.333000000000006 |
|
- type: precision_at_10 |
|
value: 9.232999999999999 |
|
- type: precision_at_100 |
|
value: 1.0630000000000002 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 25.667 |
|
- type: precision_at_5 |
|
value: 17.067 |
|
- type: recall_at_1 |
|
value: 57.260999999999996 |
|
- type: recall_at_10 |
|
value: 81.94399999999999 |
|
- type: recall_at_100 |
|
value: 93.867 |
|
- type: recall_at_1000 |
|
value: 99.667 |
|
- type: recall_at_3 |
|
value: 70.339 |
|
- type: recall_at_5 |
|
value: 76.25 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
name: MTEB SprintDuplicateQuestions |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.74356435643564 |
|
- type: cos_sim_ap |
|
value: 93.13411948212683 |
|
- type: cos_sim_f1 |
|
value: 86.80521991300147 |
|
- type: cos_sim_precision |
|
value: 84.00374181478017 |
|
- type: cos_sim_recall |
|
value: 89.8 |
|
- type: dot_accuracy |
|
value: 99.67920792079208 |
|
- type: dot_ap |
|
value: 89.27277565444479 |
|
- type: dot_f1 |
|
value: 83.9276990718124 |
|
- type: dot_precision |
|
value: 82.04393505253104 |
|
- type: dot_recall |
|
value: 85.9 |
|
- type: euclidean_accuracy |
|
value: 99.74257425742574 |
|
- type: euclidean_ap |
|
value: 93.17993008259062 |
|
- type: euclidean_f1 |
|
value: 86.69396110542476 |
|
- type: euclidean_precision |
|
value: 88.78406708595388 |
|
- type: euclidean_recall |
|
value: 84.7 |
|
- type: manhattan_accuracy |
|
value: 99.74257425742574 |
|
- type: manhattan_ap |
|
value: 93.14413755550099 |
|
- type: manhattan_f1 |
|
value: 86.82483594144371 |
|
- type: manhattan_precision |
|
value: 87.66564729867483 |
|
- type: manhattan_recall |
|
value: 86 |
|
- type: max_accuracy |
|
value: 99.74356435643564 |
|
- type: max_ap |
|
value: 93.17993008259062 |
|
- type: max_f1 |
|
value: 86.82483594144371 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB StackExchangeClustering |
|
type: mteb/stackexchange-clustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 57.525863806168566 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB StackExchangeClusteringP2P |
|
type: mteb/stackexchange-clustering-p2p |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 32.68850574423839 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB StackOverflowDupQuestions |
|
type: mteb/stackoverflowdupquestions-reranking |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 49.71580650644033 |
|
- type: mrr |
|
value: 50.50971903913081 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
name: MTEB SummEval |
|
type: mteb/summeval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 29.152190498799484 |
|
- type: cos_sim_spearman |
|
value: 29.686180371952727 |
|
- type: dot_pearson |
|
value: 27.248664793816342 |
|
- type: dot_spearman |
|
value: 28.37748983721745 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB TRECCOVID |
|
type: trec-covid |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.20400000000000001 |
|
- type: map_at_10 |
|
value: 1.6209999999999998 |
|
- type: map_at_100 |
|
value: 9.690999999999999 |
|
- type: map_at_1000 |
|
value: 23.733 |
|
- type: map_at_3 |
|
value: 0.575 |
|
- type: map_at_5 |
|
value: 0.885 |
|
- type: mrr_at_1 |
|
value: 78 |
|
- type: mrr_at_10 |
|
value: 86.56700000000001 |
|
- type: mrr_at_100 |
|
value: 86.56700000000001 |
|
- type: mrr_at_1000 |
|
value: 86.56700000000001 |
|
- type: mrr_at_3 |
|
value: 85.667 |
|
- type: mrr_at_5 |
|
value: 86.56700000000001 |
|
- type: ndcg_at_1 |
|
value: 76 |
|
- type: ndcg_at_10 |
|
value: 71.326 |
|
- type: ndcg_at_100 |
|
value: 54.208999999999996 |
|
- type: ndcg_at_1000 |
|
value: 49.252 |
|
- type: ndcg_at_3 |
|
value: 74.235 |
|
- type: ndcg_at_5 |
|
value: 73.833 |
|
- type: precision_at_1 |
|
value: 78 |
|
- type: precision_at_10 |
|
value: 74.8 |
|
- type: precision_at_100 |
|
value: 55.50000000000001 |
|
- type: precision_at_1000 |
|
value: 21.836 |
|
- type: precision_at_3 |
|
value: 78 |
|
- type: precision_at_5 |
|
value: 78 |
|
- type: recall_at_1 |
|
value: 0.20400000000000001 |
|
- type: recall_at_10 |
|
value: 1.894 |
|
- type: recall_at_100 |
|
value: 13.245999999999999 |
|
- type: recall_at_1000 |
|
value: 46.373 |
|
- type: recall_at_3 |
|
value: 0.613 |
|
- type: recall_at_5 |
|
value: 0.991 |
|
- 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: 95.89999999999999 |
|
- type: f1 |
|
value: 94.69999999999999 |
|
- type: precision |
|
value: 94.11666666666667 |
|
- type: recall |
|
value: 95.89999999999999 |
|
- 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: 68.20809248554913 |
|
- type: f1 |
|
value: 63.431048720066066 |
|
- type: precision |
|
value: 61.69143958161298 |
|
- type: recall |
|
value: 68.20809248554913 |
|
- 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: 71.21951219512195 |
|
- type: f1 |
|
value: 66.82926829268293 |
|
- type: precision |
|
value: 65.1260162601626 |
|
- type: recall |
|
value: 71.21951219512195 |
|
- 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: 97.2 |
|
- type: f1 |
|
value: 96.26666666666667 |
|
- type: precision |
|
value: 95.8 |
|
- type: recall |
|
value: 97.2 |
|
- 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: 99.3 |
|
- type: f1 |
|
value: 99.06666666666666 |
|
- type: precision |
|
value: 98.95 |
|
- type: recall |
|
value: 99.3 |
|
- 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: 97.39999999999999 |
|
- type: f1 |
|
value: 96.63333333333333 |
|
- type: precision |
|
value: 96.26666666666668 |
|
- type: recall |
|
value: 97.39999999999999 |
|
- 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: 96 |
|
- type: f1 |
|
value: 94.86666666666666 |
|
- type: precision |
|
value: 94.31666666666668 |
|
- type: recall |
|
value: 96 |
|
- 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: 47.01492537313433 |
|
- type: f1 |
|
value: 40.178867566927266 |
|
- type: precision |
|
value: 38.179295828549556 |
|
- type: recall |
|
value: 47.01492537313433 |
|
- 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: 86.5 |
|
- type: f1 |
|
value: 83.62537480063796 |
|
- type: precision |
|
value: 82.44555555555554 |
|
- type: recall |
|
value: 86.5 |
|
- 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: 80.48780487804879 |
|
- type: f1 |
|
value: 75.45644599303138 |
|
- type: precision |
|
value: 73.37398373983739 |
|
- type: recall |
|
value: 80.48780487804879 |
|
- 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: 93.7 |
|
- type: f1 |
|
value: 91.95666666666666 |
|
- type: precision |
|
value: 91.125 |
|
- type: recall |
|
value: 93.7 |
|
- 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: 91.73754556500607 |
|
- type: f1 |
|
value: 89.65168084244632 |
|
- type: precision |
|
value: 88.73025516403402 |
|
- type: recall |
|
value: 91.73754556500607 |
|
- 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: 81.04347826086956 |
|
- type: f1 |
|
value: 76.2128364389234 |
|
- type: precision |
|
value: 74.2 |
|
- type: recall |
|
value: 81.04347826086956 |
|
- 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: 83.65217391304348 |
|
- type: f1 |
|
value: 79.4376811594203 |
|
- type: precision |
|
value: 77.65797101449274 |
|
- type: recall |
|
value: 83.65217391304348 |
|
- 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: 87.5 |
|
- type: f1 |
|
value: 85.02690476190476 |
|
- type: precision |
|
value: 83.96261904761904 |
|
- type: recall |
|
value: 87.5 |
|
- 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: 89.3 |
|
- type: f1 |
|
value: 86.52333333333333 |
|
- type: precision |
|
value: 85.22833333333332 |
|
- type: recall |
|
value: 89.3 |
|
- 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: 65.01809408926418 |
|
- type: f1 |
|
value: 59.00594446432805 |
|
- type: precision |
|
value: 56.827215807915444 |
|
- type: recall |
|
value: 65.01809408926418 |
|
- 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: 91.2 |
|
- type: f1 |
|
value: 88.58 |
|
- type: precision |
|
value: 87.33333333333334 |
|
- type: recall |
|
value: 91.2 |
|
- 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: 59.199999999999996 |
|
- type: f1 |
|
value: 53.299166276284915 |
|
- type: precision |
|
value: 51.3383908045977 |
|
- type: recall |
|
value: 59.199999999999996 |
|
- 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: 93.2 |
|
- type: f1 |
|
value: 91.2 |
|
- type: precision |
|
value: 90.25 |
|
- type: recall |
|
value: 93.2 |
|
- 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: 64.76190476190476 |
|
- type: f1 |
|
value: 59.867110667110666 |
|
- type: precision |
|
value: 58.07390192653351 |
|
- type: recall |
|
value: 64.76190476190476 |
|
- 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: 76.2 |
|
- type: f1 |
|
value: 71.48147546897547 |
|
- type: precision |
|
value: 69.65409090909091 |
|
- type: recall |
|
value: 76.2 |
|
- 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: 93.8 |
|
- type: f1 |
|
value: 92.14 |
|
- type: precision |
|
value: 91.35833333333333 |
|
- type: recall |
|
value: 93.8 |
|
- 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: 97.89999999999999 |
|
- type: f1 |
|
value: 97.2 |
|
- type: precision |
|
value: 96.85000000000001 |
|
- type: recall |
|
value: 97.89999999999999 |
|
- 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: 94.6 |
|
- type: f1 |
|
value: 92.93333333333334 |
|
- type: precision |
|
value: 92.13333333333333 |
|
- type: recall |
|
value: 94.6 |
|
- 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: 74.1 |
|
- type: f1 |
|
value: 69.14817460317461 |
|
- type: precision |
|
value: 67.2515873015873 |
|
- type: recall |
|
value: 74.1 |
|
- 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: 95.19999999999999 |
|
- type: f1 |
|
value: 94.01333333333335 |
|
- type: precision |
|
value: 93.46666666666667 |
|
- type: recall |
|
value: 95.19999999999999 |
|
- 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: 76.9 |
|
- type: f1 |
|
value: 72.07523809523809 |
|
- type: precision |
|
value: 70.19777777777779 |
|
- type: recall |
|
value: 76.9 |
|
- 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: 94.1 |
|
- type: f1 |
|
value: 92.31666666666666 |
|
- type: precision |
|
value: 91.43333333333332 |
|
- type: recall |
|
value: 94.1 |
|
- 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: 97.8 |
|
- type: f1 |
|
value: 97.1 |
|
- type: precision |
|
value: 96.76666666666668 |
|
- type: recall |
|
value: 97.8 |
|
- 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: 92.85714285714286 |
|
- type: f1 |
|
value: 90.92093441150045 |
|
- type: precision |
|
value: 90.00449236298293 |
|
- type: recall |
|
value: 92.85714285714286 |
|
- 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: 93.16239316239316 |
|
- type: f1 |
|
value: 91.33903133903132 |
|
- type: precision |
|
value: 90.56267806267806 |
|
- type: recall |
|
value: 93.16239316239316 |
|
- 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: 92.4 |
|
- type: f1 |
|
value: 90.25666666666666 |
|
- type: precision |
|
value: 89.25833333333334 |
|
- type: recall |
|
value: 92.4 |
|
- 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: 90.22727272727272 |
|
- type: f1 |
|
value: 87.53030303030303 |
|
- type: precision |
|
value: 86.37121212121211 |
|
- type: recall |
|
value: 90.22727272727272 |
|
- 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: 79.03563941299791 |
|
- type: f1 |
|
value: 74.7349505840072 |
|
- type: precision |
|
value: 72.9035639412998 |
|
- type: recall |
|
value: 79.03563941299791 |
|
- 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: 97 |
|
- type: f1 |
|
value: 96.15 |
|
- type: precision |
|
value: 95.76666666666668 |
|
- type: recall |
|
value: 97 |
|
- 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: 76.26459143968872 |
|
- type: f1 |
|
value: 71.55642023346303 |
|
- type: precision |
|
value: 69.7544932369835 |
|
- type: recall |
|
value: 76.26459143968872 |
|
- 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: 58.119658119658126 |
|
- type: f1 |
|
value: 51.65242165242165 |
|
- type: precision |
|
value: 49.41768108434775 |
|
- type: recall |
|
value: 58.119658119658126 |
|
- 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: 74.3 |
|
- type: f1 |
|
value: 69.52055555555555 |
|
- type: precision |
|
value: 67.7574938949939 |
|
- type: recall |
|
value: 74.3 |
|
- 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: 94.8 |
|
- type: f1 |
|
value: 93.31666666666666 |
|
- type: precision |
|
value: 92.60000000000001 |
|
- type: recall |
|
value: 94.8 |
|
- 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: 76.63551401869158 |
|
- type: f1 |
|
value: 72.35202492211837 |
|
- type: precision |
|
value: 70.60358255451713 |
|
- type: recall |
|
value: 76.63551401869158 |
|
- 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: 90.4 |
|
- type: f1 |
|
value: 88.4811111111111 |
|
- type: precision |
|
value: 87.7452380952381 |
|
- type: recall |
|
value: 90.4 |
|
- 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: 95 |
|
- type: f1 |
|
value: 93.60666666666667 |
|
- type: precision |
|
value: 92.975 |
|
- type: recall |
|
value: 95 |
|
- 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: 67.2 |
|
- type: f1 |
|
value: 63.01595782872099 |
|
- type: precision |
|
value: 61.596587301587306 |
|
- type: recall |
|
value: 67.2 |
|
- 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: 95.7 |
|
- type: f1 |
|
value: 94.52999999999999 |
|
- type: precision |
|
value: 94 |
|
- type: recall |
|
value: 95.7 |
|
- 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: 94.6 |
|
- type: f1 |
|
value: 93.28999999999999 |
|
- type: precision |
|
value: 92.675 |
|
- type: recall |
|
value: 94.6 |
|
- 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: 96.39999999999999 |
|
- type: f1 |
|
value: 95.28333333333333 |
|
- type: precision |
|
value: 94.75 |
|
- type: recall |
|
value: 96.39999999999999 |
|
- 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: 91.9 |
|
- type: f1 |
|
value: 89.83 |
|
- type: precision |
|
value: 88.92 |
|
- type: recall |
|
value: 91.9 |
|
- 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: 94.69999999999999 |
|
- type: f1 |
|
value: 93.34222222222223 |
|
- type: precision |
|
value: 92.75416666666668 |
|
- type: recall |
|
value: 94.69999999999999 |
|
- 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: 60.333333333333336 |
|
- type: f1 |
|
value: 55.31203703703703 |
|
- type: precision |
|
value: 53.39971108326371 |
|
- type: recall |
|
value: 60.333333333333336 |
|
- 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: 12.9 |
|
- type: f1 |
|
value: 11.099861903031458 |
|
- type: precision |
|
value: 10.589187932631877 |
|
- type: recall |
|
value: 12.9 |
|
- 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: 86.7 |
|
- type: f1 |
|
value: 83.0152380952381 |
|
- type: precision |
|
value: 81.37833333333333 |
|
- type: recall |
|
value: 86.7 |
|
- 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: 63.39285714285714 |
|
- type: f1 |
|
value: 56.832482993197274 |
|
- type: precision |
|
value: 54.56845238095237 |
|
- type: recall |
|
value: 63.39285714285714 |
|
- 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: 48.73765093304062 |
|
- type: f1 |
|
value: 41.555736920720456 |
|
- type: precision |
|
value: 39.06874531737319 |
|
- type: recall |
|
value: 48.73765093304062 |
|
- 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: 41.099999999999994 |
|
- type: f1 |
|
value: 36.540165945165946 |
|
- type: precision |
|
value: 35.05175685425686 |
|
- type: recall |
|
value: 41.099999999999994 |
|
- 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: 94.89999999999999 |
|
- type: f1 |
|
value: 93.42333333333333 |
|
- type: precision |
|
value: 92.75833333333333 |
|
- type: recall |
|
value: 94.89999999999999 |
|
- 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: 94.89999999999999 |
|
- type: f1 |
|
value: 93.63333333333334 |
|
- type: precision |
|
value: 93.01666666666665 |
|
- type: recall |
|
value: 94.89999999999999 |
|
- 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: 77.9 |
|
- type: f1 |
|
value: 73.64833333333334 |
|
- type: precision |
|
value: 71.90282106782105 |
|
- type: recall |
|
value: 77.9 |
|
- 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: 59.4 |
|
- type: f1 |
|
value: 54.90521367521367 |
|
- type: precision |
|
value: 53.432840025471606 |
|
- type: recall |
|
value: 59.4 |
|
- 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: 97.39999999999999 |
|
- type: f1 |
|
value: 96.6 |
|
- type: precision |
|
value: 96.2 |
|
- type: recall |
|
value: 97.39999999999999 |
|
- 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: 67.2 |
|
- type: f1 |
|
value: 62.25926129426129 |
|
- type: precision |
|
value: 60.408376623376626 |
|
- type: recall |
|
value: 67.2 |
|
- 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: 90.2 |
|
- type: f1 |
|
value: 87.60666666666667 |
|
- type: precision |
|
value: 86.45277777777778 |
|
- type: recall |
|
value: 90.2 |
|
- 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: 97.7 |
|
- type: f1 |
|
value: 97 |
|
- type: precision |
|
value: 96.65 |
|
- type: recall |
|
value: 97.7 |
|
- 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: 93.2 |
|
- type: f1 |
|
value: 91.39746031746031 |
|
- type: precision |
|
value: 90.6125 |
|
- type: recall |
|
value: 93.2 |
|
- 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: 32.11678832116788 |
|
- type: f1 |
|
value: 27.210415386260234 |
|
- type: precision |
|
value: 26.20408990846947 |
|
- type: recall |
|
value: 32.11678832116788 |
|
- 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: 8.5 |
|
- type: f1 |
|
value: 6.787319277832475 |
|
- type: precision |
|
value: 6.3452094433344435 |
|
- type: recall |
|
value: 8.5 |
|
- 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: 96.1 |
|
- type: f1 |
|
value: 95.08 |
|
- type: precision |
|
value: 94.61666666666667 |
|
- type: recall |
|
value: 96.1 |
|
- 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: 95.3 |
|
- type: f1 |
|
value: 93.88333333333333 |
|
- type: precision |
|
value: 93.18333333333332 |
|
- type: recall |
|
value: 95.3 |
|
- 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: 85.11904761904762 |
|
- type: f1 |
|
value: 80.69444444444444 |
|
- type: precision |
|
value: 78.72023809523809 |
|
- type: recall |
|
value: 85.11904761904762 |
|
- 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: 11.1 |
|
- type: f1 |
|
value: 9.276381801735853 |
|
- type: precision |
|
value: 8.798174603174601 |
|
- type: recall |
|
value: 11.1 |
|
- 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: 63.56107660455487 |
|
- type: f1 |
|
value: 58.70433569191332 |
|
- type: precision |
|
value: 56.896926581464015 |
|
- type: recall |
|
value: 63.56107660455487 |
|
- 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: 94.69999999999999 |
|
- type: f1 |
|
value: 93.10000000000001 |
|
- type: precision |
|
value: 92.35 |
|
- type: recall |
|
value: 94.69999999999999 |
|
- 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: 96.8 |
|
- type: f1 |
|
value: 96.01222222222222 |
|
- type: precision |
|
value: 95.67083333333332 |
|
- type: recall |
|
value: 96.8 |
|
- 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: 9.2 |
|
- type: f1 |
|
value: 7.911555250305249 |
|
- type: precision |
|
value: 7.631246556216846 |
|
- type: recall |
|
value: 9.2 |
|
- 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: 77.48917748917748 |
|
- type: f1 |
|
value: 72.27375798804371 |
|
- type: precision |
|
value: 70.14430014430013 |
|
- type: recall |
|
value: 77.48917748917748 |
|
- 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: 77.09923664122137 |
|
- type: f1 |
|
value: 72.61541257724463 |
|
- type: precision |
|
value: 70.8998380754106 |
|
- type: recall |
|
value: 77.09923664122137 |
|
- 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: 98.2532751091703 |
|
- type: f1 |
|
value: 97.69529354682193 |
|
- type: precision |
|
value: 97.42843279961184 |
|
- type: recall |
|
value: 98.2532751091703 |
|
- 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: 82.8 |
|
- type: f1 |
|
value: 79.14672619047619 |
|
- type: precision |
|
value: 77.59489247311828 |
|
- type: recall |
|
value: 82.8 |
|
- 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: 94.35028248587571 |
|
- type: f1 |
|
value: 92.86252354048965 |
|
- type: precision |
|
value: 92.2080979284369 |
|
- type: recall |
|
value: 94.35028248587571 |
|
- 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: 8.5 |
|
- type: f1 |
|
value: 6.282429263935621 |
|
- type: precision |
|
value: 5.783274240739785 |
|
- type: recall |
|
value: 8.5 |
|
- 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: 92.7 |
|
- type: f1 |
|
value: 91.025 |
|
- type: precision |
|
value: 90.30428571428571 |
|
- type: recall |
|
value: 92.7 |
|
- 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: 81 |
|
- type: f1 |
|
value: 77.8232380952381 |
|
- type: precision |
|
value: 76.60194444444444 |
|
- type: recall |
|
value: 81 |
|
- 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: 91 |
|
- type: f1 |
|
value: 88.70857142857142 |
|
- type: precision |
|
value: 87.7 |
|
- type: recall |
|
value: 91 |
|
- 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: 96.39999999999999 |
|
- type: f1 |
|
value: 95.3 |
|
- type: precision |
|
value: 94.76666666666667 |
|
- type: recall |
|
value: 96.39999999999999 |
|
- 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: 8.1 |
|
- type: f1 |
|
value: 7.001008218834307 |
|
- type: precision |
|
value: 6.708329562594269 |
|
- type: recall |
|
value: 8.1 |
|
- 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: 87.1313672922252 |
|
- type: f1 |
|
value: 84.09070598748882 |
|
- type: precision |
|
value: 82.79171454104429 |
|
- type: recall |
|
value: 87.1313672922252 |
|
- 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: 96.39999999999999 |
|
- type: f1 |
|
value: 95.28333333333333 |
|
- type: precision |
|
value: 94.73333333333332 |
|
- type: recall |
|
value: 96.39999999999999 |
|
- 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: 42.29249011857708 |
|
- type: f1 |
|
value: 36.981018542283365 |
|
- type: precision |
|
value: 35.415877813576024 |
|
- type: recall |
|
value: 42.29249011857708 |
|
- 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: 83.80281690140845 |
|
- type: f1 |
|
value: 80.86854460093896 |
|
- type: precision |
|
value: 79.60093896713614 |
|
- type: recall |
|
value: 83.80281690140845 |
|
- 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: 45.26946107784431 |
|
- type: f1 |
|
value: 39.80235464678088 |
|
- type: precision |
|
value: 38.14342660001342 |
|
- type: recall |
|
value: 45.26946107784431 |
|
- 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: 94.3 |
|
- type: f1 |
|
value: 92.9 |
|
- type: precision |
|
value: 92.26666666666668 |
|
- type: recall |
|
value: 94.3 |
|
- 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: 37.93103448275862 |
|
- type: f1 |
|
value: 33.15192743764172 |
|
- type: precision |
|
value: 31.57456528146183 |
|
- type: recall |
|
value: 37.93103448275862 |
|
- 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: 69.01408450704226 |
|
- type: f1 |
|
value: 63.41549295774648 |
|
- type: precision |
|
value: 61.342778895595806 |
|
- type: recall |
|
value: 69.01408450704226 |
|
- 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: 76.66666666666667 |
|
- type: f1 |
|
value: 71.60705960705961 |
|
- type: precision |
|
value: 69.60683760683762 |
|
- type: recall |
|
value: 76.66666666666667 |
|
- 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: 95.8 |
|
- type: f1 |
|
value: 94.48333333333333 |
|
- type: precision |
|
value: 93.83333333333333 |
|
- type: recall |
|
value: 95.8 |
|
- 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: 52.81837160751566 |
|
- type: f1 |
|
value: 48.435977731384824 |
|
- type: precision |
|
value: 47.11291973845539 |
|
- type: recall |
|
value: 52.81837160751566 |
|
- 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: 44.9 |
|
- type: f1 |
|
value: 38.88962621607783 |
|
- type: precision |
|
value: 36.95936507936508 |
|
- type: recall |
|
value: 44.9 |
|
- 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: 90.55374592833876 |
|
- type: f1 |
|
value: 88.22553125484721 |
|
- type: precision |
|
value: 87.26927252985884 |
|
- type: recall |
|
value: 90.55374592833876 |
|
- 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: 94.6 |
|
- type: f1 |
|
value: 93.13333333333333 |
|
- type: precision |
|
value: 92.45333333333333 |
|
- type: recall |
|
value: 94.6 |
|
- 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: 93.7 |
|
- type: f1 |
|
value: 91.99666666666667 |
|
- type: precision |
|
value: 91.26666666666668 |
|
- type: recall |
|
value: 93.7 |
|
- 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: 85.03937007874016 |
|
- type: f1 |
|
value: 81.75853018372703 |
|
- type: precision |
|
value: 80.34120734908137 |
|
- type: recall |
|
value: 85.03937007874016 |
|
- 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: 88.3 |
|
- type: f1 |
|
value: 85.5 |
|
- type: precision |
|
value: 84.25833333333334 |
|
- type: recall |
|
value: 88.3 |
|
- 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: 65.51246537396122 |
|
- type: f1 |
|
value: 60.02297410192148 |
|
- type: precision |
|
value: 58.133467727289236 |
|
- type: recall |
|
value: 65.51246537396122 |
|
- 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: 96 |
|
- type: f1 |
|
value: 94.89 |
|
- type: precision |
|
value: 94.39166666666667 |
|
- type: recall |
|
value: 96 |
|
- 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: 57.692307692307686 |
|
- type: f1 |
|
value: 53.162393162393165 |
|
- type: precision |
|
value: 51.70673076923077 |
|
- type: recall |
|
value: 57.692307692307686 |
|
- 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: 91.60000000000001 |
|
- type: f1 |
|
value: 89.21190476190475 |
|
- type: precision |
|
value: 88.08666666666667 |
|
- type: recall |
|
value: 91.60000000000001 |
|
- 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: 88 |
|
- type: f1 |
|
value: 85.47 |
|
- type: precision |
|
value: 84.43266233766234 |
|
- type: recall |
|
value: 88 |
|
- 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: 92.7 |
|
- type: f1 |
|
value: 90.64999999999999 |
|
- type: precision |
|
value: 89.68333333333332 |
|
- type: recall |
|
value: 92.7 |
|
- 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: 80.30660377358491 |
|
- type: f1 |
|
value: 76.33044137466307 |
|
- type: precision |
|
value: 74.78970125786164 |
|
- type: recall |
|
value: 80.30660377358491 |
|
- 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: 96.39999999999999 |
|
- type: f1 |
|
value: 95.44 |
|
- type: precision |
|
value: 94.99166666666666 |
|
- type: recall |
|
value: 96.39999999999999 |
|
- 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: 96.53284671532847 |
|
- type: f1 |
|
value: 95.37712895377129 |
|
- type: precision |
|
value: 94.7992700729927 |
|
- type: recall |
|
value: 96.53284671532847 |
|
- 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: 89 |
|
- type: f1 |
|
value: 86.23190476190476 |
|
- type: precision |
|
value: 85.035 |
|
- type: recall |
|
value: 89 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB Touche2020 |
|
type: webis-touche2020 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.585 |
|
- type: map_at_10 |
|
value: 9.012 |
|
- type: map_at_100 |
|
value: 14.027000000000001 |
|
- type: map_at_1000 |
|
value: 15.565000000000001 |
|
- type: map_at_3 |
|
value: 5.032 |
|
- type: map_at_5 |
|
value: 6.657 |
|
- type: mrr_at_1 |
|
value: 28.571 |
|
- type: mrr_at_10 |
|
value: 45.377 |
|
- type: mrr_at_100 |
|
value: 46.119 |
|
- type: mrr_at_1000 |
|
value: 46.127 |
|
- type: mrr_at_3 |
|
value: 41.156 |
|
- type: mrr_at_5 |
|
value: 42.585 |
|
- type: ndcg_at_1 |
|
value: 27.551 |
|
- type: ndcg_at_10 |
|
value: 23.395 |
|
- type: ndcg_at_100 |
|
value: 33.342 |
|
- type: ndcg_at_1000 |
|
value: 45.523 |
|
- type: ndcg_at_3 |
|
value: 25.158 |
|
- type: ndcg_at_5 |
|
value: 23.427 |
|
- type: precision_at_1 |
|
value: 28.571 |
|
- type: precision_at_10 |
|
value: 21.429000000000002 |
|
- type: precision_at_100 |
|
value: 6.714 |
|
- type: precision_at_1000 |
|
value: 1.473 |
|
- type: precision_at_3 |
|
value: 27.211000000000002 |
|
- type: precision_at_5 |
|
value: 24.490000000000002 |
|
- type: recall_at_1 |
|
value: 2.585 |
|
- type: recall_at_10 |
|
value: 15.418999999999999 |
|
- type: recall_at_100 |
|
value: 42.485 |
|
- type: recall_at_1000 |
|
value: 79.536 |
|
- type: recall_at_3 |
|
value: 6.239999999999999 |
|
- type: recall_at_5 |
|
value: 8.996 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB ToxicConversationsClassification |
|
type: mteb/toxic_conversations_50k |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 71.3234 |
|
- type: ap |
|
value: 14.361688653847423 |
|
- type: f1 |
|
value: 54.819068624319044 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB TweetSentimentExtractionClassification |
|
type: mteb/tweet_sentiment_extraction |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 61.97792869269949 |
|
- type: f1 |
|
value: 62.28965628513728 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB TwentyNewsgroupsClustering |
|
type: mteb/twentynewsgroups-clustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 38.90540145385218 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
name: MTEB TwitterSemEval2015 |
|
type: mteb/twittersemeval2015-pairclassification |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 86.53513739047506 |
|
- type: cos_sim_ap |
|
value: 75.27741586677557 |
|
- type: cos_sim_f1 |
|
value: 69.18792902473774 |
|
- type: cos_sim_precision |
|
value: 67.94708725515136 |
|
- type: cos_sim_recall |
|
value: 70.47493403693932 |
|
- type: dot_accuracy |
|
value: 84.7052512368123 |
|
- type: dot_ap |
|
value: 69.36075482849378 |
|
- type: dot_f1 |
|
value: 64.44688376631296 |
|
- type: dot_precision |
|
value: 59.92288500793831 |
|
- type: dot_recall |
|
value: 69.70976253298153 |
|
- type: euclidean_accuracy |
|
value: 86.60666388508076 |
|
- type: euclidean_ap |
|
value: 75.47512772621097 |
|
- type: euclidean_f1 |
|
value: 69.413872536473 |
|
- type: euclidean_precision |
|
value: 67.39562624254472 |
|
- type: euclidean_recall |
|
value: 71.55672823218997 |
|
- type: manhattan_accuracy |
|
value: 86.52917684925792 |
|
- type: manhattan_ap |
|
value: 75.34000110496703 |
|
- type: manhattan_f1 |
|
value: 69.28489190226429 |
|
- type: manhattan_precision |
|
value: 67.24608889992551 |
|
- type: manhattan_recall |
|
value: 71.45118733509234 |
|
- type: max_accuracy |
|
value: 86.60666388508076 |
|
- type: max_ap |
|
value: 75.47512772621097 |
|
- type: max_f1 |
|
value: 69.413872536473 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
name: MTEB TwitterURLCorpus |
|
type: mteb/twitterurlcorpus-pairclassification |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 89.01695967710637 |
|
- type: cos_sim_ap |
|
value: 85.8298270742901 |
|
- type: cos_sim_f1 |
|
value: 78.46988128389272 |
|
- type: cos_sim_precision |
|
value: 74.86017897091722 |
|
- type: cos_sim_recall |
|
value: 82.44533415460425 |
|
- type: dot_accuracy |
|
value: 88.19420188613343 |
|
- type: dot_ap |
|
value: 83.82679165901324 |
|
- type: dot_f1 |
|
value: 76.55833777304208 |
|
- type: dot_precision |
|
value: 75.6884875846501 |
|
- type: dot_recall |
|
value: 77.44841392054204 |
|
- type: euclidean_accuracy |
|
value: 89.03054294252338 |
|
- type: euclidean_ap |
|
value: 85.89089555185325 |
|
- type: euclidean_f1 |
|
value: 78.62997658079624 |
|
- type: euclidean_precision |
|
value: 74.92329149232914 |
|
- type: euclidean_recall |
|
value: 82.72251308900523 |
|
- type: manhattan_accuracy |
|
value: 89.0266620095471 |
|
- type: manhattan_ap |
|
value: 85.86458997929147 |
|
- type: manhattan_f1 |
|
value: 78.50685331000291 |
|
- type: manhattan_precision |
|
value: 74.5499861534201 |
|
- type: manhattan_recall |
|
value: 82.90729904527257 |
|
- type: max_accuracy |
|
value: 89.03054294252338 |
|
- type: max_ap |
|
value: 85.89089555185325 |
|
- type: max_f1 |
|
value: 78.62997658079624 |
|
--- |
|
|
|
# apto-as/multilingual-e5-large-Q8_0-GGUF |
|
This model was converted to GGUF format from [`intfloat/multilingual-e5-large`](https://huggingface.co/intfloat/multilingual-e5-large) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. |
|
Refer to the [original model card](https://huggingface.co/intfloat/multilingual-e5-large) for more details on the model. |
|
|
|
## Use with llama.cpp |
|
Install llama.cpp through brew (works on Mac and Linux) |
|
|
|
```bash |
|
brew install llama.cpp |
|
|
|
``` |
|
Invoke the llama.cpp server or the CLI. |
|
|
|
### CLI: |
|
```bash |
|
llama-cli --hf-repo apto-as/multilingual-e5-large-Q8_0-GGUF --hf-file multilingual-e5-large-q8_0.gguf -p "The meaning to life and the universe is" |
|
``` |
|
|
|
### Server: |
|
```bash |
|
llama-server --hf-repo apto-as/multilingual-e5-large-Q8_0-GGUF --hf-file multilingual-e5-large-q8_0.gguf -c 2048 |
|
``` |
|
|
|
Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. |
|
|
|
Step 1: Clone llama.cpp from GitHub. |
|
``` |
|
git clone https://github.com/ggerganov/llama.cpp |
|
``` |
|
|
|
Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). |
|
``` |
|
cd llama.cpp && LLAMA_CURL=1 make |
|
``` |
|
|
|
Step 3: Run inference through the main binary. |
|
``` |
|
./llama-cli --hf-repo apto-as/multilingual-e5-large-Q8_0-GGUF --hf-file multilingual-e5-large-q8_0.gguf -p "The meaning to life and the universe is" |
|
``` |
|
or |
|
``` |
|
./llama-server --hf-repo apto-as/multilingual-e5-large-Q8_0-GGUF --hf-file multilingual-e5-large-q8_0.gguf -c 2048 |
|
``` |
|
|
