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--- |
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tags: |
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- mteb |
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model-index: |
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- name: universal-sentence-encoder-4 |
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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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type: mteb/amazon_counterfactual |
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name: MTEB AmazonCounterfactualClassification (en) |
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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: 70.67164179104478 |
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- type: ap |
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value: 32.834763426716584 |
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- type: f1 |
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value: 64.42714654873818 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_polarity |
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name: MTEB AmazonPolarityClassification |
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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: 67.73207500000001 |
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- type: ap |
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value: 62.47524029220297 |
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- type: f1 |
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value: 67.48570902687877 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_reviews_multi |
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name: MTEB AmazonReviewsClassification (en) |
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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: 32.62 |
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- type: f1 |
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value: 32.13548057908922 |
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- task: |
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type: Clustering |
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dataset: |
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type: mteb/arxiv-clustering-p2p |
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name: MTEB ArxivClusteringP2P |
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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: 35.12555128655114 |
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- task: |
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type: Clustering |
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dataset: |
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type: mteb/arxiv-clustering-s2s |
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name: MTEB ArxivClusteringS2S |
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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: 23.456590839508902 |
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- task: |
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type: STS |
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dataset: |
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type: mteb/biosses-sts |
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name: MTEB BIOSSES |
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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: 64.7357059982867 |
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- type: cos_sim_spearman |
|
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value: 63.37975740377988 |
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- type: euclidean_pearson |
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value: 63.49896800825232 |
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- type: euclidean_spearman |
|
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value: 63.37975740377988 |
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- type: manhattan_pearson |
|
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value: 64.00838198208166 |
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- type: manhattan_spearman |
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value: 63.31710537380123 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/banking77 |
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name: MTEB Banking77Classification |
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config: default |
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split: test |
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
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metrics: |
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- type: accuracy |
|
|
value: 74.12012987012989 |
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- type: f1 |
|
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value: 73.23976030012078 |
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- task: |
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type: Clustering |
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dataset: |
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type: mteb/biorxiv-clustering-p2p |
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name: MTEB BiorxivClusteringP2P |
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config: default |
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split: test |
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
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metrics: |
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- type: v_measure |
|
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value: 31.169576856541603 |
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- task: |
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type: Clustering |
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dataset: |
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type: mteb/biorxiv-clustering-s2s |
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name: MTEB BiorxivClusteringS2S |
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config: default |
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split: test |
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
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metrics: |
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- type: v_measure |
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value: 18.81055418061209 |
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- task: |
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type: Classification |
|
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dataset: |
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type: mteb/emotion |
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name: MTEB EmotionClassification |
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config: default |
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split: test |
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revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
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metrics: |
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- type: accuracy |
|
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value: 38.64000000000001 |
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- type: f1 |
|
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value: 35.09699868913662 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/imdb |
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name: MTEB ImdbClassification |
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config: default |
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split: test |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
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metrics: |
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- type: accuracy |
|
|
value: 68.43239999999999 |
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- type: ap |
|
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value: 62.76719976357937 |
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- type: f1 |
|
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value: 68.3208799558774 |
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- task: |
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type: Classification |
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dataset: |
|
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type: mteb/mtop_domain |
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name: MTEB MTOPDomainClassification (en) |
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config: en |
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split: test |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
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metrics: |
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- type: accuracy |
|
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value: 90.11627906976744 |
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- type: f1 |
|
|
value: 89.69218132313695 |
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- task: |
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type: Classification |
|
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dataset: |
|
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type: mteb/mtop_intent |
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name: MTEB MTOPIntentClassification (en) |
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config: en |
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split: test |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
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metrics: |
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- type: accuracy |
|
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value: 64.9954400364797 |
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- type: f1 |
|
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value: 46.61477433032086 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_massive_intent |
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name: MTEB MassiveIntentClassification (en) |
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config: en |
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split: test |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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metrics: |
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- type: accuracy |
|
|
value: 67.23268325487558 |
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- type: f1 |
|
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value: 64.41484453213448 |
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- task: |
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type: Classification |
|
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dataset: |
|
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type: mteb/amazon_massive_scenario |
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name: MTEB MassiveScenarioClassification (en) |
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config: en |
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split: test |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
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|
metrics: |
|
|
- type: accuracy |
|
|
value: 72.78749159381303 |
|
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- type: f1 |
|
|
value: 71.69036260308698 |
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|
- task: |
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type: Clustering |
|
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dataset: |
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type: mteb/medrxiv-clustering-p2p |
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name: MTEB MedrxivClusteringP2P |
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config: default |
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split: test |
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|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
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|
metrics: |
|
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- type: v_measure |
|
|
value: 28.88138682114816 |
|
|
- task: |
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type: Clustering |
|
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dataset: |
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type: mteb/medrxiv-clustering-s2s |
|
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name: MTEB MedrxivClusteringS2S |
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config: default |
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split: test |
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revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
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metrics: |
|
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- type: v_measure |
|
|
value: 23.311493283906064 |
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- task: |
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type: Clustering |
|
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dataset: |
|
|
type: mteb/reddit-clustering |
|
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name: MTEB RedditClustering |
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config: default |
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split: test |
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revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
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metrics: |
|
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- type: v_measure |
|
|
value: 49.71559043766936 |
|
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- task: |
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type: Clustering |
|
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dataset: |
|
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type: mteb/reddit-clustering-p2p |
|
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name: MTEB RedditClusteringP2P |
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config: default |
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split: test |
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revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
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metrics: |
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|
- type: v_measure |
|
|
value: 57.91704617095672 |
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- task: |
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type: STS |
|
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dataset: |
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|
type: mteb/sickr-sts |
|
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name: MTEB SICK-R |
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config: default |
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split: test |
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revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
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|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 77.38041457279672 |
|
|
- type: cos_sim_spearman |
|
|
value: 69.79282361714223 |
|
|
- type: euclidean_pearson |
|
|
value: 74.02315074475364 |
|
|
- type: euclidean_spearman |
|
|
value: 69.79282304260158 |
|
|
- type: manhattan_pearson |
|
|
value: 73.01688608657159 |
|
|
- type: manhattan_spearman |
|
|
value: 68.22940563625058 |
|
|
- task: |
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|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts12-sts |
|
|
name: MTEB STS12 |
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config: default |
|
|
split: test |
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|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 72.58420052741107 |
|
|
- type: cos_sim_spearman |
|
|
value: 67.05792005966953 |
|
|
- type: euclidean_pearson |
|
|
value: 68.35629372749483 |
|
|
- type: euclidean_spearman |
|
|
value: 67.05773819854602 |
|
|
- type: manhattan_pearson |
|
|
value: 67.12625747442266 |
|
|
- type: manhattan_spearman |
|
|
value: 65.7252617197503 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts13-sts |
|
|
name: MTEB STS13 |
|
|
config: default |
|
|
split: test |
|
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 69.55548148750847 |
|
|
- type: cos_sim_spearman |
|
|
value: 71.54484814980987 |
|
|
- type: euclidean_pearson |
|
|
value: 71.22072782671158 |
|
|
- type: euclidean_spearman |
|
|
value: 71.54484814980987 |
|
|
- type: manhattan_pearson |
|
|
value: 70.3490839338159 |
|
|
- type: manhattan_spearman |
|
|
value: 70.76414952692804 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts14-sts |
|
|
name: MTEB STS14 |
|
|
config: default |
|
|
split: test |
|
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
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|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 73.74818660795891 |
|
|
- type: cos_sim_spearman |
|
|
value: 70.59138342620027 |
|
|
- type: euclidean_pearson |
|
|
value: 72.60887534657319 |
|
|
- type: euclidean_spearman |
|
|
value: 70.5913727471932 |
|
|
- type: manhattan_pearson |
|
|
value: 71.95704368086712 |
|
|
- type: manhattan_spearman |
|
|
value: 69.58620240967204 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts15-sts |
|
|
name: MTEB STS15 |
|
|
config: default |
|
|
split: test |
|
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
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|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 79.6360473168554 |
|
|
- type: cos_sim_spearman |
|
|
value: 80.26596000690931 |
|
|
- type: euclidean_pearson |
|
|
value: 79.82176999472074 |
|
|
- type: euclidean_spearman |
|
|
value: 80.26596000690931 |
|
|
- type: manhattan_pearson |
|
|
value: 78.94486463380255 |
|
|
- type: manhattan_spearman |
|
|
value: 79.20674341072848 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts16-sts |
|
|
name: MTEB STS16 |
|
|
config: default |
|
|
split: test |
|
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revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
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|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 74.84322872565855 |
|
|
- type: cos_sim_spearman |
|
|
value: 75.75894131062728 |
|
|
- type: euclidean_pearson |
|
|
value: 75.5333191548161 |
|
|
- type: euclidean_spearman |
|
|
value: 75.75894090191032 |
|
|
- type: manhattan_pearson |
|
|
value: 74.96648591478875 |
|
|
- type: manhattan_spearman |
|
|
value: 75.07346800275856 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts17-crosslingual-sts |
|
|
name: MTEB STS17 (en-en) |
|
|
config: en-en |
|
|
split: test |
|
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 83.79136005773537 |
|
|
- type: cos_sim_spearman |
|
|
value: 84.94411992446793 |
|
|
- type: euclidean_pearson |
|
|
value: 83.60843297866558 |
|
|
- type: euclidean_spearman |
|
|
value: 84.94411992446793 |
|
|
- type: manhattan_pearson |
|
|
value: 82.81698401022742 |
|
|
- type: manhattan_spearman |
|
|
value: 84.02022263657062 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts22-crosslingual-sts |
|
|
name: MTEB STS22 (en) |
|
|
config: en |
|
|
split: test |
|
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 60.02909344132073 |
|
|
- type: cos_sim_spearman |
|
|
value: 60.000369508382704 |
|
|
- type: euclidean_pearson |
|
|
value: 61.54466129341342 |
|
|
- type: euclidean_spearman |
|
|
value: 60.000369508382704 |
|
|
- type: manhattan_pearson |
|
|
value: 58.76127065249476 |
|
|
- type: manhattan_spearman |
|
|
value: 58.08063159428285 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/stsbenchmark-sts |
|
|
name: MTEB STSBenchmark |
|
|
config: default |
|
|
split: test |
|
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 78.72737325889034 |
|
|
- type: cos_sim_spearman |
|
|
value: 77.08420739421672 |
|
|
- type: euclidean_pearson |
|
|
value: 77.85606384422326 |
|
|
- type: euclidean_spearman |
|
|
value: 77.08420739421672 |
|
|
- type: manhattan_pearson |
|
|
value: 76.63643674764234 |
|
|
- type: manhattan_spearman |
|
|
value: 75.68141928725497 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: mteb/sprintduplicatequestions-pairclassification |
|
|
name: MTEB SprintDuplicateQuestions |
|
|
config: default |
|
|
split: test |
|
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 99.61980198019802 |
|
|
- type: cos_sim_ap |
|
|
value: 86.36827719686161 |
|
|
- type: cos_sim_f1 |
|
|
value: 80.35625927758537 |
|
|
- type: cos_sim_precision |
|
|
value: 79.52987267384917 |
|
|
- type: cos_sim_recall |
|
|
value: 81.2 |
|
|
- type: dot_accuracy |
|
|
value: 99.61980198019802 |
|
|
- type: dot_ap |
|
|
value: 86.36827719686161 |
|
|
- type: dot_f1 |
|
|
value: 80.35625927758537 |
|
|
- type: dot_precision |
|
|
value: 79.52987267384917 |
|
|
- type: dot_recall |
|
|
value: 81.2 |
|
|
- type: euclidean_accuracy |
|
|
value: 99.61980198019802 |
|
|
- type: euclidean_ap |
|
|
value: 86.3682771543572 |
|
|
- type: euclidean_f1 |
|
|
value: 80.35625927758537 |
|
|
- type: euclidean_precision |
|
|
value: 79.52987267384917 |
|
|
- type: euclidean_recall |
|
|
value: 81.2 |
|
|
- type: manhattan_accuracy |
|
|
value: 99.63564356435643 |
|
|
- type: manhattan_ap |
|
|
value: 87.12233265654545 |
|
|
- type: manhattan_f1 |
|
|
value: 80.78920041536864 |
|
|
- type: manhattan_precision |
|
|
value: 84.01727861771057 |
|
|
- type: manhattan_recall |
|
|
value: 77.8 |
|
|
- type: max_accuracy |
|
|
value: 99.63564356435643 |
|
|
- type: max_ap |
|
|
value: 87.12233265654545 |
|
|
- type: max_f1 |
|
|
value: 80.78920041536864 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/stackexchange-clustering |
|
|
name: MTEB StackExchangeClustering |
|
|
config: default |
|
|
split: test |
|
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 54.64344160961463 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/stackexchange-clustering-p2p |
|
|
name: MTEB StackExchangeClusteringP2P |
|
|
config: default |
|
|
split: test |
|
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 31.57666192425415 |
|
|
- task: |
|
|
type: Summarization |
|
|
dataset: |
|
|
type: mteb/summeval |
|
|
name: MTEB SummEval |
|
|
config: default |
|
|
split: test |
|
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 29.77545231337259 |
|
|
- type: cos_sim_spearman |
|
|
value: 29.420072483158698 |
|
|
- type: dot_pearson |
|
|
value: 29.775453888622426 |
|
|
- type: dot_spearman |
|
|
value: 29.420072483158698 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/toxic_conversations_50k |
|
|
name: MTEB ToxicConversationsClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 68.98920000000001 |
|
|
- type: ap |
|
|
value: 12.803310864930856 |
|
|
- type: f1 |
|
|
value: 52.67881359079218 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/tweet_sentiment_extraction |
|
|
name: MTEB TweetSentimentExtractionClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 57.00622524052065 |
|
|
- type: f1 |
|
|
value: 57.2232294145327 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/twentynewsgroups-clustering |
|
|
name: MTEB TwentyNewsgroupsClustering |
|
|
config: default |
|
|
split: test |
|
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 38.23134611732841 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: mteb/twittersemeval2015-pairclassification |
|
|
name: MTEB TwitterSemEval2015 |
|
|
config: default |
|
|
split: test |
|
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 82.25546879656673 |
|
|
- type: cos_sim_ap |
|
|
value: 60.64429023120581 |
|
|
- type: cos_sim_f1 |
|
|
value: 57.75789091788608 |
|
|
- type: cos_sim_precision |
|
|
value: 53.31547220361688 |
|
|
- type: cos_sim_recall |
|
|
value: 63.007915567282325 |
|
|
- type: dot_accuracy |
|
|
value: 82.25546879656673 |
|
|
- type: dot_ap |
|
|
value: 60.64428864700383 |
|
|
- type: dot_f1 |
|
|
value: 57.75789091788608 |
|
|
- type: dot_precision |
|
|
value: 53.31547220361688 |
|
|
- type: dot_recall |
|
|
value: 63.007915567282325 |
|
|
- type: euclidean_accuracy |
|
|
value: 82.25546879656673 |
|
|
- type: euclidean_ap |
|
|
value: 60.64429357965402 |
|
|
- type: euclidean_f1 |
|
|
value: 57.75789091788608 |
|
|
- type: euclidean_precision |
|
|
value: 53.31547220361688 |
|
|
- type: euclidean_recall |
|
|
value: 63.007915567282325 |
|
|
- type: manhattan_accuracy |
|
|
value: 82.14221851344102 |
|
|
- type: manhattan_ap |
|
|
value: 59.542389876094134 |
|
|
- type: manhattan_f1 |
|
|
value: 56.935892792466504 |
|
|
- type: manhattan_precision |
|
|
value: 52.48163810371689 |
|
|
- type: manhattan_recall |
|
|
value: 62.21635883905014 |
|
|
- type: max_accuracy |
|
|
value: 82.25546879656673 |
|
|
- type: max_ap |
|
|
value: 60.64429357965402 |
|
|
- type: max_f1 |
|
|
value: 57.75789091788608 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: mteb/twitterurlcorpus-pairclassification |
|
|
name: MTEB TwitterURLCorpus |
|
|
config: default |
|
|
split: test |
|
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 86.99305312997244 |
|
|
- type: cos_sim_ap |
|
|
value: 81.6822772881566 |
|
|
- type: cos_sim_f1 |
|
|
value: 73.70381406436233 |
|
|
- type: cos_sim_precision |
|
|
value: 71.38528138528139 |
|
|
- type: cos_sim_recall |
|
|
value: 76.17801047120419 |
|
|
- type: dot_accuracy |
|
|
value: 86.99305312997244 |
|
|
- type: dot_ap |
|
|
value: 81.6822783032573 |
|
|
- type: dot_f1 |
|
|
value: 73.70381406436233 |
|
|
- type: dot_precision |
|
|
value: 71.38528138528139 |
|
|
- type: dot_recall |
|
|
value: 76.17801047120419 |
|
|
- type: euclidean_accuracy |
|
|
value: 86.99305312997244 |
|
|
- type: euclidean_ap |
|
|
value: 81.68228020882522 |
|
|
- type: euclidean_f1 |
|
|
value: 73.70381406436233 |
|
|
- type: euclidean_precision |
|
|
value: 71.38528138528139 |
|
|
- type: euclidean_recall |
|
|
value: 76.17801047120419 |
|
|
- type: manhattan_accuracy |
|
|
value: 86.84557767687352 |
|
|
- type: manhattan_ap |
|
|
value: 81.3912803407899 |
|
|
- type: manhattan_f1 |
|
|
value: 73.48302793631723 |
|
|
- type: manhattan_precision |
|
|
value: 71.71650542362944 |
|
|
- type: manhattan_recall |
|
|
value: 75.33877425315676 |
|
|
- type: max_accuracy |
|
|
value: 86.99305312997244 |
|
|
- type: max_ap |
|
|
value: 81.68228020882522 |
|
|
- type: max_f1 |
|
|
value: 73.70381406436233 |
|
|
--- |
|
|
|
|
|
This is a part of the [MTEB test](https://huggingface.co/spaces/mteb/leaderboard). |
|
|
|
|
|
``` |
|
|
# !pip install tensorflow_text |
|
|
|
|
|
import tensorflow_hub as hub |
|
|
from tensorflow_text import SentencepieceTokenizer |
|
|
import tensorflow as tf |
|
|
|
|
|
embedder=hub.load("https://tfhub.dev/google/universal-sentence-encoder-multilingual-large/3") |
|
|
|
|
|
class USE(): |
|
|
def encode(self, sentences, batch_size=32, **kwargs): |
|
|
embeddings = [] |
|
|
for i in range(0, len(sentences), batch_size): |
|
|
batch_sentences = sentences[i:i+batch_size] |
|
|
batch_embeddings = embedder(batch_sentences) |
|
|
embeddings.extend(batch_embeddings) |
|
|
return embeddings |
|
|
|
|
|
|
|
|
model = USE() |
|
|
``` |
