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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-large-5 |
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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: 76.19402985074628 |
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- type: ap |
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value: 39.249966888759666 |
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- type: f1 |
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value: 70.17510532980124 |
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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: 69.6285 |
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- type: ap |
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value: 63.97317997322299 |
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- type: f1 |
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value: 69.48624121982243 |
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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: 35.534 |
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- type: f1 |
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value: 34.974303844745194 |
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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: 34.718110225806626 |
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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: 25.267234486849127 |
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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: 69.65040443392367 |
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- type: cos_sim_spearman |
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value: 69.35579718635816 |
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- type: euclidean_pearson |
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value: 68.74078260783044 |
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- type: euclidean_spearman |
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value: 69.35579718635816 |
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- type: manhattan_pearson |
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value: 68.97023207188357 |
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- type: manhattan_spearman |
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value: 69.2063961917937 |
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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: 78.12987012987013 |
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- type: f1 |
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value: 77.40193921057201 |
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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: 28.39184796722482 |
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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: 20.5151608432177 |
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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: 45.48 |
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- type: f1 |
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value: 41.2632839288363 |
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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: 64.0552 |
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- type: ap |
|
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value: 59.25851636836455 |
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- type: f1 |
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value: 63.90501571634165 |
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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: 92.94117647058823 |
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- type: f1 |
|
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value: 92.7110107115347 |
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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: 74.43456452348381 |
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- type: f1 |
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value: 52.53178214778298 |
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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: 71.68796234028245 |
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- type: f1 |
|
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value: 68.47828954699564 |
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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: 77.20242098184264 |
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- type: f1 |
|
|
value: 76.27977367157321 |
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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: 30.266855488757034 |
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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: 24.580327378539057 |
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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: 56.928616405043684 |
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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: 58.94536303256525 |
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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: 82.43899708996477 |
|
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- type: cos_sim_spearman |
|
|
value: 76.84011555220044 |
|
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- type: euclidean_pearson |
|
|
value: 79.6116260676631 |
|
|
- type: euclidean_spearman |
|
|
value: 76.84012073472658 |
|
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- type: manhattan_pearson |
|
|
value: 78.49980966442152 |
|
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- type: manhattan_spearman |
|
|
value: 75.49233078465171 |
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|
- task: |
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type: STS |
|
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dataset: |
|
|
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: 79.8291506264289 |
|
|
- type: cos_sim_spearman |
|
|
value: 72.49093632759003 |
|
|
- type: euclidean_pearson |
|
|
value: 75.42130137819414 |
|
|
- type: euclidean_spearman |
|
|
value: 72.49048089395136 |
|
|
- type: manhattan_pearson |
|
|
value: 74.17957476459091 |
|
|
- type: manhattan_spearman |
|
|
value: 71.6143674273714 |
|
|
- 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 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 70.91903439531401 |
|
|
- type: cos_sim_spearman |
|
|
value: 73.65106317244273 |
|
|
- type: euclidean_pearson |
|
|
value: 73.22383725261588 |
|
|
- type: euclidean_spearman |
|
|
value: 73.65106317244273 |
|
|
- type: manhattan_pearson |
|
|
value: 72.98314057093636 |
|
|
- type: manhattan_spearman |
|
|
value: 73.52101907069579 |
|
|
- task: |
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|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts14-sts |
|
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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: 75.19632733755482 |
|
|
- type: cos_sim_spearman |
|
|
value: 71.88328402076041 |
|
|
- type: euclidean_pearson |
|
|
value: 74.02395011081532 |
|
|
- type: euclidean_spearman |
|
|
value: 71.88328903479953 |
|
|
- type: manhattan_pearson |
|
|
value: 73.52941749980135 |
|
|
- type: manhattan_spearman |
|
|
value: 71.32905921324534 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts15-sts |
|
|
name: MTEB STS15 |
|
|
config: default |
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|
split: test |
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revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
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|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 82.42736501667461 |
|
|
- type: cos_sim_spearman |
|
|
value: 82.89997148218205 |
|
|
- type: euclidean_pearson |
|
|
value: 82.3189209945513 |
|
|
- type: euclidean_spearman |
|
|
value: 82.89997089267106 |
|
|
- type: manhattan_pearson |
|
|
value: 81.78597437071429 |
|
|
- type: manhattan_spearman |
|
|
value: 82.21582873302081 |
|
|
- task: |
|
|
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: |
|
|
- type: cos_sim_pearson |
|
|
value: 78.44968010602165 |
|
|
- type: cos_sim_spearman |
|
|
value: 79.82626284236876 |
|
|
- type: euclidean_pearson |
|
|
value: 79.4157474030238 |
|
|
- type: euclidean_spearman |
|
|
value: 79.82626269881543 |
|
|
- type: manhattan_pearson |
|
|
value: 79.13275737559012 |
|
|
- type: manhattan_spearman |
|
|
value: 79.4847570398719 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts17-crosslingual-sts |
|
|
name: MTEB STS17 (en-en) |
|
|
config: en-en |
|
|
split: test |
|
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
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|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 84.51882547098218 |
|
|
- type: cos_sim_spearman |
|
|
value: 85.19309361840223 |
|
|
- type: euclidean_pearson |
|
|
value: 84.78417242196153 |
|
|
- type: euclidean_spearman |
|
|
value: 85.19307726106497 |
|
|
- type: manhattan_pearson |
|
|
value: 84.09108278425708 |
|
|
- type: manhattan_spearman |
|
|
value: 84.13590986630149 |
|
|
- 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: 44.814384769251085 |
|
|
- type: cos_sim_spearman |
|
|
value: 48.43949857027059 |
|
|
- type: euclidean_pearson |
|
|
value: 47.479132435178855 |
|
|
- type: euclidean_spearman |
|
|
value: 48.43949857027059 |
|
|
- type: manhattan_pearson |
|
|
value: 47.16203934707649 |
|
|
- type: manhattan_spearman |
|
|
value: 48.289920897667095 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/stsbenchmark-sts |
|
|
name: MTEB STSBenchmark |
|
|
config: default |
|
|
split: test |
|
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 81.25646447054616 |
|
|
- type: cos_sim_spearman |
|
|
value: 79.93231051166357 |
|
|
- type: euclidean_pearson |
|
|
value: 80.65225742476945 |
|
|
- type: euclidean_spearman |
|
|
value: 79.93231051166357 |
|
|
- type: manhattan_pearson |
|
|
value: 79.84341819764376 |
|
|
- type: manhattan_spearman |
|
|
value: 79.07650150491334 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: mteb/sprintduplicatequestions-pairclassification |
|
|
name: MTEB SprintDuplicateQuestions |
|
|
config: default |
|
|
split: test |
|
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 99.5910891089109 |
|
|
- type: cos_sim_ap |
|
|
value: 84.37184771930944 |
|
|
- type: cos_sim_f1 |
|
|
value: 78.78787878787878 |
|
|
- type: cos_sim_precision |
|
|
value: 80.99260823653644 |
|
|
- type: cos_sim_recall |
|
|
value: 76.7 |
|
|
- type: dot_accuracy |
|
|
value: 99.5910891089109 |
|
|
- type: dot_ap |
|
|
value: 84.37184771930944 |
|
|
- type: dot_f1 |
|
|
value: 78.78787878787878 |
|
|
- type: dot_precision |
|
|
value: 80.99260823653644 |
|
|
- type: dot_recall |
|
|
value: 76.7 |
|
|
- type: euclidean_accuracy |
|
|
value: 99.5910891089109 |
|
|
- type: euclidean_ap |
|
|
value: 84.37185436709098 |
|
|
- type: euclidean_f1 |
|
|
value: 78.78787878787878 |
|
|
- type: euclidean_precision |
|
|
value: 80.99260823653644 |
|
|
- type: euclidean_recall |
|
|
value: 76.7 |
|
|
- type: manhattan_accuracy |
|
|
value: 99.6108910891089 |
|
|
- type: manhattan_ap |
|
|
value: 85.13355467581354 |
|
|
- type: manhattan_f1 |
|
|
value: 80.2788844621514 |
|
|
- type: manhattan_precision |
|
|
value: 79.96031746031747 |
|
|
- type: manhattan_recall |
|
|
value: 80.60000000000001 |
|
|
- type: max_accuracy |
|
|
value: 99.6108910891089 |
|
|
- type: max_ap |
|
|
value: 85.13355467581354 |
|
|
- type: max_f1 |
|
|
value: 80.2788844621514 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/stackexchange-clustering |
|
|
name: MTEB StackExchangeClustering |
|
|
config: default |
|
|
split: test |
|
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 60.8469558550317 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/stackexchange-clustering-p2p |
|
|
name: MTEB StackExchangeClusteringP2P |
|
|
config: default |
|
|
split: test |
|
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 33.14392913702168 |
|
|
- task: |
|
|
type: Summarization |
|
|
dataset: |
|
|
type: mteb/summeval |
|
|
name: MTEB SummEval |
|
|
config: default |
|
|
split: test |
|
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 29.566148619704457 |
|
|
- type: cos_sim_spearman |
|
|
value: 29.01201818902588 |
|
|
- type: dot_pearson |
|
|
value: 29.566149876183374 |
|
|
- type: dot_spearman |
|
|
value: 29.014046950422795 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/toxic_conversations_50k |
|
|
name: MTEB ToxicConversationsClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 70.17420000000001 |
|
|
- type: ap |
|
|
value: 13.49623412034604 |
|
|
- type: f1 |
|
|
value: 53.7079366494688 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/tweet_sentiment_extraction |
|
|
name: MTEB TweetSentimentExtractionClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 59.309564233163556 |
|
|
- type: f1 |
|
|
value: 59.33623172630094 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/twentynewsgroups-clustering |
|
|
name: MTEB TwentyNewsgroupsClustering |
|
|
config: default |
|
|
split: test |
|
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 42.42960819361032 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: mteb/twittersemeval2015-pairclassification |
|
|
name: MTEB TwitterSemEval2015 |
|
|
config: default |
|
|
split: test |
|
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 85.04500208618943 |
|
|
- type: cos_sim_ap |
|
|
value: 70.12785509302904 |
|
|
- type: cos_sim_f1 |
|
|
value: 65.36573392243496 |
|
|
- type: cos_sim_precision |
|
|
value: 61.10601193207894 |
|
|
- type: cos_sim_recall |
|
|
value: 70.26385224274406 |
|
|
- type: dot_accuracy |
|
|
value: 85.04500208618943 |
|
|
- type: dot_ap |
|
|
value: 70.12785837450095 |
|
|
- type: dot_f1 |
|
|
value: 65.36573392243496 |
|
|
- type: dot_precision |
|
|
value: 61.10601193207894 |
|
|
- type: dot_recall |
|
|
value: 70.26385224274406 |
|
|
- type: euclidean_accuracy |
|
|
value: 85.04500208618943 |
|
|
- type: euclidean_ap |
|
|
value: 70.1278575285826 |
|
|
- type: euclidean_f1 |
|
|
value: 65.36573392243496 |
|
|
- type: euclidean_precision |
|
|
value: 61.10601193207894 |
|
|
- type: euclidean_recall |
|
|
value: 70.26385224274406 |
|
|
- type: manhattan_accuracy |
|
|
value: 85.03308100375514 |
|
|
- type: manhattan_ap |
|
|
value: 69.67192372362932 |
|
|
- type: manhattan_f1 |
|
|
value: 64.95726495726495 |
|
|
- type: manhattan_precision |
|
|
value: 61.218771888862946 |
|
|
- type: manhattan_recall |
|
|
value: 69.1820580474934 |
|
|
- type: max_accuracy |
|
|
value: 85.04500208618943 |
|
|
- type: max_ap |
|
|
value: 70.12785837450095 |
|
|
- type: max_f1 |
|
|
value: 65.36573392243496 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: mteb/twitterurlcorpus-pairclassification |
|
|
name: MTEB TwitterURLCorpus |
|
|
config: default |
|
|
split: test |
|
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 88.18644002018085 |
|
|
- type: cos_sim_ap |
|
|
value: 84.09120337117118 |
|
|
- type: cos_sim_f1 |
|
|
value: 76.33478718604302 |
|
|
- type: cos_sim_precision |
|
|
value: 74.59582598471486 |
|
|
- type: cos_sim_recall |
|
|
value: 78.15676008623345 |
|
|
- type: dot_accuracy |
|
|
value: 88.18644002018085 |
|
|
- type: dot_ap |
|
|
value: 84.09120289232122 |
|
|
- type: dot_f1 |
|
|
value: 76.33478718604302 |
|
|
- type: dot_precision |
|
|
value: 74.59582598471486 |
|
|
- type: dot_recall |
|
|
value: 78.15676008623345 |
|
|
- type: euclidean_accuracy |
|
|
value: 88.18644002018085 |
|
|
- type: euclidean_ap |
|
|
value: 84.091202102378 |
|
|
- type: euclidean_f1 |
|
|
value: 76.33478718604302 |
|
|
- type: euclidean_precision |
|
|
value: 74.59582598471486 |
|
|
- type: euclidean_recall |
|
|
value: 78.15676008623345 |
|
|
- type: manhattan_accuracy |
|
|
value: 88.19032095315714 |
|
|
- type: manhattan_ap |
|
|
value: 84.0865561436236 |
|
|
- type: manhattan_f1 |
|
|
value: 76.16665422235496 |
|
|
- type: manhattan_precision |
|
|
value: 73.93100449340484 |
|
|
- type: manhattan_recall |
|
|
value: 78.54173082845703 |
|
|
- type: max_accuracy |
|
|
value: 88.19032095315714 |
|
|
- type: max_ap |
|
|
value: 84.09120337117118 |
|
|
- type: max_f1 |
|
|
value: 76.33478718604302 |
|
|
--- |
|
|
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() |
|
|
``` |
