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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-multilingual-large-3 |
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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: 70.80597014925372 |
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- type: ap |
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value: 32.82048192776259 |
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- type: f1 |
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value: 64.5323001151201 |
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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: 67.04549999999999 |
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- type: ap |
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value: 61.7344066191823 |
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- type: f1 |
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value: 66.66233213924507 |
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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: 35.85 |
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- type: f1 |
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value: 35.332188148679464 |
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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: 34.745135349238126 |
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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: 22.620886813816306 |
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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: 80.30945408208555 |
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- type: cos_sim_spearman |
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value: 79.13734536677386 |
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- type: euclidean_pearson |
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value: 78.92356402711572 |
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- type: euclidean_spearman |
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value: 79.13734536677386 |
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- type: manhattan_pearson |
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value: 79.0536298599996 |
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- type: manhattan_spearman |
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value: 79.15240595090333 |
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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 |
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value: 74.66883116883116 |
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- type: f1 |
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value: 73.79377347715479 |
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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: 28.750702236182818 |
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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: 20.142702408387194 |
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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: 42.30500000000001 |
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- type: f1 |
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value: 38.547388314307206 |
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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 |
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value: 63.690000000000005 |
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- type: ap |
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value: 59.157513278784734 |
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- type: f1 |
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value: 63.35865572988864 |
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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: 92.48062015503875 |
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- type: f1 |
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value: 92.14919344822017 |
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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: 70.26675786593708 |
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- type: f1 |
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value: 47.72003620900994 |
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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 |
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value: 69.04505716207129 |
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- type: f1 |
|
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value: 65.75319040584333 |
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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: |
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- type: accuracy |
|
|
value: 75.80363147276395 |
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- type: f1 |
|
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value: 74.16118757920125 |
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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: 31.197732425855694 |
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- 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 |
|
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value: 25.802309075396522 |
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- task: |
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type: Clustering |
|
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dataset: |
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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 |
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value: 46.17008358584782 |
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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 |
|
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value: 56.53148530944687 |
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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: |
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- type: cos_sim_pearson |
|
|
value: 81.9794493404352 |
|
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- type: cos_sim_spearman |
|
|
value: 76.42957100142304 |
|
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- type: euclidean_pearson |
|
|
value: 78.82942656726047 |
|
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- type: euclidean_spearman |
|
|
value: 76.4295710840889 |
|
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- type: manhattan_pearson |
|
|
value: 78.13314706410813 |
|
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- type: manhattan_spearman |
|
|
value: 74.9822593004123 |
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- task: |
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type: STS |
|
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dataset: |
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|
type: mteb/sts12-sts |
|
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name: MTEB STS12 |
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config: default |
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split: test |
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revision: a0d554a64d88156834ff5ae9920b964011b16384 |
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metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 80.7673081071098 |
|
|
- type: cos_sim_spearman |
|
|
value: 74.24891322087522 |
|
|
- type: euclidean_pearson |
|
|
value: 76.52411182468802 |
|
|
- type: euclidean_spearman |
|
|
value: 74.24929140605082 |
|
|
- type: manhattan_pearson |
|
|
value: 76.8324387036746 |
|
|
- type: manhattan_spearman |
|
|
value: 74.53614579807713 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts13-sts |
|
|
name: MTEB STS13 |
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|
config: default |
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|
split: test |
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revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
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|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 69.28614557615222 |
|
|
- type: cos_sim_spearman |
|
|
value: 71.81704450585194 |
|
|
- type: euclidean_pearson |
|
|
value: 71.1658590877318 |
|
|
- type: euclidean_spearman |
|
|
value: 71.81704444201455 |
|
|
- type: manhattan_pearson |
|
|
value: 71.36497478266207 |
|
|
- type: manhattan_spearman |
|
|
value: 72.06541804714345 |
|
|
- task: |
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|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts14-sts |
|
|
name: MTEB STS14 |
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config: default |
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split: test |
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revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
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|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 74.87060297964618 |
|
|
- type: cos_sim_spearman |
|
|
value: 71.3835314374386 |
|
|
- type: euclidean_pearson |
|
|
value: 73.38159929423239 |
|
|
- type: euclidean_spearman |
|
|
value: 71.38353144149953 |
|
|
- type: manhattan_pearson |
|
|
value: 73.52351725668174 |
|
|
- type: manhattan_spearman |
|
|
value: 71.51640478420119 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts15-sts |
|
|
name: MTEB STS15 |
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|
config: default |
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|
split: test |
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revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
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|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 82.0540026051573 |
|
|
- type: cos_sim_spearman |
|
|
value: 82.4705078026881 |
|
|
- type: euclidean_pearson |
|
|
value: 81.93203207566977 |
|
|
- type: euclidean_spearman |
|
|
value: 82.47050765607385 |
|
|
- type: manhattan_pearson |
|
|
value: 81.95496687772686 |
|
|
- type: manhattan_spearman |
|
|
value: 82.32489988477197 |
|
|
- task: |
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|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts16-sts |
|
|
name: MTEB STS16 |
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config: default |
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|
split: test |
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revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
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metrics: |
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|
- type: cos_sim_pearson |
|
|
value: 76.11630455802185 |
|
|
- type: cos_sim_spearman |
|
|
value: 77.53749233675596 |
|
|
- type: euclidean_pearson |
|
|
value: 77.21678350170754 |
|
|
- type: euclidean_spearman |
|
|
value: 77.53749219731857 |
|
|
- type: manhattan_pearson |
|
|
value: 77.0111066160541 |
|
|
- type: manhattan_spearman |
|
|
value: 77.19561900456223 |
|
|
- task: |
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|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts17-crosslingual-sts |
|
|
name: MTEB STS17 (en-en) |
|
|
config: en-en |
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|
split: test |
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revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
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|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 86.04867872683484 |
|
|
- type: cos_sim_spearman |
|
|
value: 86.38343806077555 |
|
|
- type: euclidean_pearson |
|
|
value: 86.62923572982524 |
|
|
- type: euclidean_spearman |
|
|
value: 86.38343806077555 |
|
|
- type: manhattan_pearson |
|
|
value: 85.88819314699656 |
|
|
- type: manhattan_spearman |
|
|
value: 85.40841620897656 |
|
|
- 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: 50.81940075037091 |
|
|
- type: cos_sim_spearman |
|
|
value: 52.853775517979265 |
|
|
- type: euclidean_pearson |
|
|
value: 53.19987444831206 |
|
|
- type: euclidean_spearman |
|
|
value: 52.853775517979265 |
|
|
- type: manhattan_pearson |
|
|
value: 53.10152120352485 |
|
|
- type: manhattan_spearman |
|
|
value: 52.882886362489124 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/stsbenchmark-sts |
|
|
name: MTEB STSBenchmark |
|
|
config: default |
|
|
split: test |
|
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 82.15848984078094 |
|
|
- type: cos_sim_spearman |
|
|
value: 81.24223670044107 |
|
|
- type: euclidean_pearson |
|
|
value: 81.80955840510725 |
|
|
- type: euclidean_spearman |
|
|
value: 81.24224792494685 |
|
|
- type: manhattan_pearson |
|
|
value: 81.20700319509191 |
|
|
- type: manhattan_spearman |
|
|
value: 80.56078137874846 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: mteb/sprintduplicatequestions-pairclassification |
|
|
name: MTEB SprintDuplicateQuestions |
|
|
config: default |
|
|
split: test |
|
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 99.71089108910891 |
|
|
- type: cos_sim_ap |
|
|
value: 90.8870929231928 |
|
|
- type: cos_sim_f1 |
|
|
value: 85.3719420868697 |
|
|
- type: cos_sim_precision |
|
|
value: 85.24426719840478 |
|
|
- type: cos_sim_recall |
|
|
value: 85.5 |
|
|
- type: dot_accuracy |
|
|
value: 99.71089108910891 |
|
|
- type: dot_ap |
|
|
value: 90.88709292319278 |
|
|
- type: dot_f1 |
|
|
value: 85.3719420868697 |
|
|
- type: dot_precision |
|
|
value: 85.24426719840478 |
|
|
- type: dot_recall |
|
|
value: 85.5 |
|
|
- type: euclidean_accuracy |
|
|
value: 99.71089108910891 |
|
|
- type: euclidean_ap |
|
|
value: 90.8870929231928 |
|
|
- type: euclidean_f1 |
|
|
value: 85.3719420868697 |
|
|
- type: euclidean_precision |
|
|
value: 85.24426719840478 |
|
|
- type: euclidean_recall |
|
|
value: 85.5 |
|
|
- type: manhattan_accuracy |
|
|
value: 99.72871287128713 |
|
|
- type: manhattan_ap |
|
|
value: 91.50016707647607 |
|
|
- type: manhattan_f1 |
|
|
value: 86.21700879765396 |
|
|
- type: manhattan_precision |
|
|
value: 84.32122370936902 |
|
|
- type: manhattan_recall |
|
|
value: 88.2 |
|
|
- type: max_accuracy |
|
|
value: 99.72871287128713 |
|
|
- type: max_ap |
|
|
value: 91.50016707647607 |
|
|
- type: max_f1 |
|
|
value: 86.21700879765396 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/stackexchange-clustering |
|
|
name: MTEB StackExchangeClustering |
|
|
config: default |
|
|
split: test |
|
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 49.339384566987555 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/stackexchange-clustering-p2p |
|
|
name: MTEB StackExchangeClusteringP2P |
|
|
config: default |
|
|
split: test |
|
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 33.39729645390336 |
|
|
- task: |
|
|
type: Summarization |
|
|
dataset: |
|
|
type: mteb/summeval |
|
|
name: MTEB SummEval |
|
|
config: default |
|
|
split: test |
|
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 30.459235703560942 |
|
|
- type: cos_sim_spearman |
|
|
value: 29.710719599360587 |
|
|
- type: dot_pearson |
|
|
value: 30.459236115198866 |
|
|
- type: dot_spearman |
|
|
value: 29.714606257782066 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/toxic_conversations_50k |
|
|
name: MTEB ToxicConversationsClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 68.223 |
|
|
- type: ap |
|
|
value: 13.10327282975004 |
|
|
- type: f1 |
|
|
value: 52.52588280152648 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/tweet_sentiment_extraction |
|
|
name: MTEB TweetSentimentExtractionClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 59.18788907753254 |
|
|
- type: f1 |
|
|
value: 59.47679105840768 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/twentynewsgroups-clustering |
|
|
name: MTEB TwentyNewsgroupsClustering |
|
|
config: default |
|
|
split: test |
|
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 36.93253191095803 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: mteb/twittersemeval2015-pairclassification |
|
|
name: MTEB TwitterSemEval2015 |
|
|
config: default |
|
|
split: test |
|
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 83.37009000417238 |
|
|
- type: cos_sim_ap |
|
|
value: 63.75973129735431 |
|
|
- type: cos_sim_f1 |
|
|
value: 59.62504595025121 |
|
|
- type: cos_sim_precision |
|
|
value: 55.66231983527798 |
|
|
- type: cos_sim_recall |
|
|
value: 64.1952506596306 |
|
|
- type: dot_accuracy |
|
|
value: 83.37009000417238 |
|
|
- type: dot_ap |
|
|
value: 63.759728820348414 |
|
|
- type: dot_f1 |
|
|
value: 59.62504595025121 |
|
|
- type: dot_precision |
|
|
value: 55.66231983527798 |
|
|
- type: dot_recall |
|
|
value: 64.1952506596306 |
|
|
- type: euclidean_accuracy |
|
|
value: 83.37009000417238 |
|
|
- type: euclidean_ap |
|
|
value: 63.75972622477462 |
|
|
- type: euclidean_f1 |
|
|
value: 59.62504595025121 |
|
|
- type: euclidean_precision |
|
|
value: 55.66231983527798 |
|
|
- type: euclidean_recall |
|
|
value: 64.1952506596306 |
|
|
- type: manhattan_accuracy |
|
|
value: 83.28068188591524 |
|
|
- type: manhattan_ap |
|
|
value: 63.109413220673375 |
|
|
- type: manhattan_f1 |
|
|
value: 59.085923217550274 |
|
|
- type: manhattan_precision |
|
|
value: 54.903737259343146 |
|
|
- type: manhattan_recall |
|
|
value: 63.95778364116095 |
|
|
- type: max_accuracy |
|
|
value: 83.37009000417238 |
|
|
- type: max_ap |
|
|
value: 63.75973129735431 |
|
|
- type: max_f1 |
|
|
value: 59.62504595025121 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: mteb/twitterurlcorpus-pairclassification |
|
|
name: MTEB TwitterURLCorpus |
|
|
config: default |
|
|
split: test |
|
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 88.34167733923235 |
|
|
- type: cos_sim_ap |
|
|
value: 84.20066403502292 |
|
|
- type: cos_sim_f1 |
|
|
value: 76.64693381906498 |
|
|
- type: cos_sim_precision |
|
|
value: 75.56869200838072 |
|
|
- type: cos_sim_recall |
|
|
value: 77.75639051432091 |
|
|
- type: dot_accuracy |
|
|
value: 88.34167733923235 |
|
|
- type: dot_ap |
|
|
value: 84.20066476075668 |
|
|
- type: dot_f1 |
|
|
value: 76.64693381906498 |
|
|
- type: dot_precision |
|
|
value: 75.56869200838072 |
|
|
- type: dot_recall |
|
|
value: 77.75639051432091 |
|
|
- type: euclidean_accuracy |
|
|
value: 88.34167733923235 |
|
|
- type: euclidean_ap |
|
|
value: 84.20066533105057 |
|
|
- type: euclidean_f1 |
|
|
value: 76.64693381906498 |
|
|
- type: euclidean_precision |
|
|
value: 75.56869200838072 |
|
|
- type: euclidean_recall |
|
|
value: 77.75639051432091 |
|
|
- type: manhattan_accuracy |
|
|
value: 88.32809407381535 |
|
|
- type: manhattan_ap |
|
|
value: 84.17666758732113 |
|
|
- type: manhattan_f1 |
|
|
value: 76.6911654417279 |
|
|
- type: manhattan_precision |
|
|
value: 74.75146198830409 |
|
|
- type: manhattan_recall |
|
|
value: 78.73421619956883 |
|
|
- type: max_accuracy |
|
|
value: 88.34167733923235 |
|
|
- type: max_ap |
|
|
value: 84.20066533105057 |
|
|
- type: max_f1 |
|
|
value: 76.6911654417279 |
|
|
--- |
|
|
|
|
|
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() |
|
|
``` |
