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--- |
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tags: |
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- mteb |
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- transformers.js |
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- transformers |
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model-index: |
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- name: mxbai-angle-large-v1 |
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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: 75.044776119403 |
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- type: ap |
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value: 37.7362433623053 |
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- type: f1 |
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value: 68.92736573359774 |
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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: 93.84025000000001 |
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- type: ap |
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value: 90.93190875404055 |
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- type: f1 |
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value: 93.8297833897293 |
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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: 49.184 |
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- type: f1 |
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value: 48.74163227751588 |
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- task: |
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type: Retrieval |
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dataset: |
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type: arguana |
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name: MTEB ArguAna |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: map_at_1 |
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value: 41.252 |
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- type: map_at_10 |
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value: 57.778 |
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- type: map_at_100 |
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value: 58.233000000000004 |
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- type: map_at_1000 |
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value: 58.23700000000001 |
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- type: map_at_3 |
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value: 53.449999999999996 |
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- type: map_at_5 |
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value: 56.376000000000005 |
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- type: mrr_at_1 |
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value: 41.679 |
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- type: mrr_at_10 |
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value: 57.92699999999999 |
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- type: mrr_at_100 |
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value: 58.389 |
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- type: mrr_at_1000 |
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value: 58.391999999999996 |
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- type: mrr_at_3 |
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value: 53.651 |
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- type: mrr_at_5 |
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value: 56.521 |
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- type: ndcg_at_1 |
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value: 41.252 |
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- type: ndcg_at_10 |
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value: 66.018 |
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- type: ndcg_at_100 |
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value: 67.774 |
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- type: ndcg_at_1000 |
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value: 67.84400000000001 |
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- type: ndcg_at_3 |
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value: 57.372 |
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- type: ndcg_at_5 |
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value: 62.646 |
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- type: precision_at_1 |
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value: 41.252 |
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- type: precision_at_10 |
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value: 9.189 |
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- type: precision_at_100 |
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value: 0.991 |
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- type: precision_at_1000 |
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value: 0.1 |
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- type: precision_at_3 |
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value: 22.902 |
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- type: precision_at_5 |
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value: 16.302 |
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- type: recall_at_1 |
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value: 41.252 |
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- type: recall_at_10 |
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value: 91.892 |
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- type: recall_at_100 |
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value: 99.14699999999999 |
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- type: recall_at_1000 |
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value: 99.644 |
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- type: recall_at_3 |
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value: 68.706 |
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- type: recall_at_5 |
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value: 81.50800000000001 |
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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: 48.97294504317859 |
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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: 42.98071077674629 |
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- task: |
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type: Reranking |
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dataset: |
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type: mteb/askubuntudupquestions-reranking |
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name: MTEB AskUbuntuDupQuestions |
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config: default |
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split: test |
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
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metrics: |
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- type: map |
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value: 65.16477858490782 |
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- type: mrr |
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value: 78.23583080508287 |
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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: 89.6277629421789 |
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- type: cos_sim_spearman |
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value: 88.4056288400568 |
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- type: euclidean_pearson |
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value: 87.94871847578163 |
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- type: euclidean_spearman |
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value: 88.4056288400568 |
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- type: manhattan_pearson |
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value: 87.73271254229648 |
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- type: manhattan_spearman |
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value: 87.91826833762677 |
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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: 87.81818181818181 |
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- type: f1 |
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value: 87.79879337316918 |
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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: 39.91773608582761 |
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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: 36.73059477462478 |
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- task: |
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type: Retrieval |
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dataset: |
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type: BeIR/cqadupstack |
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name: MTEB CQADupstackAndroidRetrieval |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: map_at_1 |
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value: 32.745999999999995 |
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- type: map_at_10 |
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value: 43.632 |
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- type: map_at_100 |
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value: 45.206 |
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- type: map_at_1000 |
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value: 45.341 |
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- type: map_at_3 |
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value: 39.956 |
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- type: map_at_5 |
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value: 42.031 |
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- type: mrr_at_1 |
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value: 39.485 |
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- type: mrr_at_10 |
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value: 49.537 |
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- type: mrr_at_100 |
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value: 50.249 |
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- type: mrr_at_1000 |
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value: 50.294000000000004 |
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- type: mrr_at_3 |
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|
value: 46.757 |
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- type: mrr_at_5 |
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value: 48.481 |
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- type: ndcg_at_1 |
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value: 39.485 |
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- type: ndcg_at_10 |
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value: 50.058 |
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- type: ndcg_at_100 |
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value: 55.586 |
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- type: ndcg_at_1000 |
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value: 57.511 |
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- type: ndcg_at_3 |
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value: 44.786 |
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- type: ndcg_at_5 |
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value: 47.339999999999996 |
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- type: precision_at_1 |
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value: 39.485 |
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- type: precision_at_10 |
|
|
value: 9.557 |
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- type: precision_at_100 |
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value: 1.552 |
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- type: precision_at_1000 |
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value: 0.202 |
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- type: precision_at_3 |
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value: 21.412 |
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- type: precision_at_5 |
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value: 15.479000000000001 |
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- type: recall_at_1 |
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value: 32.745999999999995 |
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- type: recall_at_10 |
|
|
value: 62.056 |
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- type: recall_at_100 |
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value: 85.088 |
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- type: recall_at_1000 |
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value: 96.952 |
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- type: recall_at_3 |
|
|
value: 46.959 |
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- type: recall_at_5 |
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value: 54.06999999999999 |
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- task: |
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type: Retrieval |
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dataset: |
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type: BeIR/cqadupstack |
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name: MTEB CQADupstackEnglishRetrieval |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: map_at_1 |
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|
value: 31.898 |
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- type: map_at_10 |
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|
value: 42.142 |
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|
- type: map_at_100 |
|
|
value: 43.349 |
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|
- type: map_at_1000 |
|
|
value: 43.483 |
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|
- type: map_at_3 |
|
|
value: 39.18 |
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|
- type: map_at_5 |
|
|
value: 40.733000000000004 |
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|
- type: mrr_at_1 |
|
|
value: 39.617999999999995 |
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|
- type: mrr_at_10 |
|
|
value: 47.922 |
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|
- type: mrr_at_100 |
|
|
value: 48.547000000000004 |
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|
- type: mrr_at_1000 |
|
|
value: 48.597 |
|
|
- type: mrr_at_3 |
|
|
value: 45.86 |
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|
- type: mrr_at_5 |
|
|
value: 46.949000000000005 |
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|
- type: ndcg_at_1 |
|
|
value: 39.617999999999995 |
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|
- type: ndcg_at_10 |
|
|
value: 47.739 |
|
|
- type: ndcg_at_100 |
|
|
value: 51.934999999999995 |
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|
- type: ndcg_at_1000 |
|
|
value: 54.007000000000005 |
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|
- type: ndcg_at_3 |
|
|
value: 43.748 |
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|
- type: ndcg_at_5 |
|
|
value: 45.345 |
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|
- type: precision_at_1 |
|
|
value: 39.617999999999995 |
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|
- type: precision_at_10 |
|
|
value: 8.962 |
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|
- type: precision_at_100 |
|
|
value: 1.436 |
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|
- type: precision_at_1000 |
|
|
value: 0.192 |
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- type: precision_at_3 |
|
|
value: 21.083 |
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- type: precision_at_5 |
|
|
value: 14.752 |
|
|
- type: recall_at_1 |
|
|
value: 31.898 |
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|
- type: recall_at_10 |
|
|
value: 57.587999999999994 |
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|
- type: recall_at_100 |
|
|
value: 75.323 |
|
|
- type: recall_at_1000 |
|
|
value: 88.304 |
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|
- type: recall_at_3 |
|
|
value: 45.275 |
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- type: recall_at_5 |
|
|
value: 49.99 |
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- task: |
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type: Retrieval |
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dataset: |
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type: BeIR/cqadupstack |
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name: MTEB CQADupstackGamingRetrieval |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: map_at_1 |
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|
value: 40.458 |
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- type: map_at_10 |
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|
value: 52.942 |
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|
- type: map_at_100 |
|
|
value: 53.974 |
|
|
- type: map_at_1000 |
|
|
value: 54.031 |
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|
- type: map_at_3 |
|
|
value: 49.559999999999995 |
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|
- type: map_at_5 |
|
|
value: 51.408 |
|
|
- type: mrr_at_1 |
|
|
value: 46.27 |
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|
- type: mrr_at_10 |
|
|
value: 56.31699999999999 |
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|
- type: mrr_at_100 |
|
|
value: 56.95099999999999 |
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|
- type: mrr_at_1000 |
|
|
value: 56.98 |
|
|
- type: mrr_at_3 |
|
|
value: 53.835 |
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|
- type: mrr_at_5 |
|
|
value: 55.252 |
|
|
- type: ndcg_at_1 |
|
|
value: 46.27 |
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|
- type: ndcg_at_10 |
|
|
value: 58.964000000000006 |
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|
- type: ndcg_at_100 |
|
|
value: 62.875 |
|
|
- type: ndcg_at_1000 |
|
|
value: 63.969 |
|
|
- type: ndcg_at_3 |
|
|
value: 53.297000000000004 |
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|
- type: ndcg_at_5 |
|
|
value: 55.938 |
|
|
- type: precision_at_1 |
|
|
value: 46.27 |
|
|
- type: precision_at_10 |
|
|
value: 9.549000000000001 |
|
|
- type: precision_at_100 |
|
|
value: 1.2409999999999999 |
|
|
- type: precision_at_1000 |
|
|
value: 0.13799999999999998 |
|
|
- type: precision_at_3 |
|
|
value: 23.762 |
|
|
- type: precision_at_5 |
|
|
value: 16.262999999999998 |
|
|
- type: recall_at_1 |
|
|
value: 40.458 |
|
|
- type: recall_at_10 |
|
|
value: 73.446 |
|
|
- type: recall_at_100 |
|
|
value: 90.12400000000001 |
|
|
- type: recall_at_1000 |
|
|
value: 97.795 |
|
|
- type: recall_at_3 |
|
|
value: 58.123000000000005 |
|
|
- type: recall_at_5 |
|
|
value: 64.68 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: BeIR/cqadupstack |
|
|
name: MTEB CQADupstackGisRetrieval |
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|
config: default |
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|
split: test |
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revision: None |
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|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 27.443 |
|
|
- type: map_at_10 |
|
|
value: 36.081 |
|
|
- type: map_at_100 |
|
|
value: 37.163000000000004 |
|
|
- type: map_at_1000 |
|
|
value: 37.232 |
|
|
- type: map_at_3 |
|
|
value: 33.308 |
|
|
- type: map_at_5 |
|
|
value: 34.724 |
|
|
- type: mrr_at_1 |
|
|
value: 29.492 |
|
|
- type: mrr_at_10 |
|
|
value: 38.138 |
|
|
- type: mrr_at_100 |
|
|
value: 39.065 |
|
|
- type: mrr_at_1000 |
|
|
value: 39.119 |
|
|
- type: mrr_at_3 |
|
|
value: 35.593 |
|
|
- type: mrr_at_5 |
|
|
value: 36.785000000000004 |
|
|
- type: ndcg_at_1 |
|
|
value: 29.492 |
|
|
- type: ndcg_at_10 |
|
|
value: 41.134 |
|
|
- type: ndcg_at_100 |
|
|
value: 46.300999999999995 |
|
|
- type: ndcg_at_1000 |
|
|
value: 48.106 |
|
|
- type: ndcg_at_3 |
|
|
value: 35.77 |
|
|
- type: ndcg_at_5 |
|
|
value: 38.032 |
|
|
- type: precision_at_1 |
|
|
value: 29.492 |
|
|
- type: precision_at_10 |
|
|
value: 6.249 |
|
|
- type: precision_at_100 |
|
|
value: 0.9299999999999999 |
|
|
- type: precision_at_1000 |
|
|
value: 0.11199999999999999 |
|
|
- type: precision_at_3 |
|
|
value: 15.065999999999999 |
|
|
- type: precision_at_5 |
|
|
value: 10.373000000000001 |
|
|
- type: recall_at_1 |
|
|
value: 27.443 |
|
|
- type: recall_at_10 |
|
|
value: 54.80199999999999 |
|
|
- type: recall_at_100 |
|
|
value: 78.21900000000001 |
|
|
- type: recall_at_1000 |
|
|
value: 91.751 |
|
|
- type: recall_at_3 |
|
|
value: 40.211000000000006 |
|
|
- type: recall_at_5 |
|
|
value: 45.599000000000004 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: BeIR/cqadupstack |
|
|
name: MTEB CQADupstackMathematicaRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 18.731 |
|
|
- type: map_at_10 |
|
|
value: 26.717999999999996 |
|
|
- type: map_at_100 |
|
|
value: 27.897 |
|
|
- type: map_at_1000 |
|
|
value: 28.029 |
|
|
- type: map_at_3 |
|
|
value: 23.91 |
|
|
- type: map_at_5 |
|
|
value: 25.455 |
|
|
- type: mrr_at_1 |
|
|
value: 23.134 |
|
|
- type: mrr_at_10 |
|
|
value: 31.769 |
|
|
- type: mrr_at_100 |
|
|
value: 32.634 |
|
|
- type: mrr_at_1000 |
|
|
value: 32.707 |
|
|
- type: mrr_at_3 |
|
|
value: 28.938999999999997 |
|
|
- type: mrr_at_5 |
|
|
value: 30.531000000000002 |
|
|
- type: ndcg_at_1 |
|
|
value: 23.134 |
|
|
- type: ndcg_at_10 |
|
|
value: 32.249 |
|
|
- type: ndcg_at_100 |
|
|
value: 37.678 |
|
|
- type: ndcg_at_1000 |
|
|
value: 40.589999999999996 |
|
|
- type: ndcg_at_3 |
|
|
value: 26.985999999999997 |
|
|
- type: ndcg_at_5 |
|
|
value: 29.457 |
|
|
- type: precision_at_1 |
|
|
value: 23.134 |
|
|
- type: precision_at_10 |
|
|
value: 5.8709999999999996 |
|
|
- type: precision_at_100 |
|
|
value: 0.988 |
|
|
- type: precision_at_1000 |
|
|
value: 0.13799999999999998 |
|
|
- type: precision_at_3 |
|
|
value: 12.852 |
|
|
- type: precision_at_5 |
|
|
value: 9.428 |
|
|
- type: recall_at_1 |
|
|
value: 18.731 |
|
|
- type: recall_at_10 |
|
|
value: 44.419 |
|
|
- type: recall_at_100 |
|
|
value: 67.851 |
|
|
- type: recall_at_1000 |
|
|
value: 88.103 |
|
|
- type: recall_at_3 |
|
|
value: 29.919 |
|
|
- type: recall_at_5 |
|
|
value: 36.230000000000004 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: BeIR/cqadupstack |
|
|
name: MTEB CQADupstackPhysicsRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 30.324 |
|
|
- type: map_at_10 |
|
|
value: 41.265 |
|
|
- type: map_at_100 |
|
|
value: 42.559000000000005 |
|
|
- type: map_at_1000 |
|
|
value: 42.669000000000004 |
|
|
- type: map_at_3 |
|
|
value: 38.138 |
|
|
- type: map_at_5 |
|
|
value: 39.881 |
|
|
- type: mrr_at_1 |
|
|
value: 36.67 |
|
|
- type: mrr_at_10 |
|
|
value: 46.774 |
|
|
- type: mrr_at_100 |
|
|
value: 47.554 |
|
|
- type: mrr_at_1000 |
|
|
value: 47.593 |
|
|
- type: mrr_at_3 |
|
|
value: 44.338 |
|
|
- type: mrr_at_5 |
|
|
value: 45.723 |
|
|
- type: ndcg_at_1 |
|
|
value: 36.67 |
|
|
- type: ndcg_at_10 |
|
|
value: 47.367 |
|
|
- type: ndcg_at_100 |
|
|
value: 52.623 |
|
|
- type: ndcg_at_1000 |
|
|
value: 54.59 |
|
|
- type: ndcg_at_3 |
|
|
value: 42.323 |
|
|
- type: ndcg_at_5 |
|
|
value: 44.727 |
|
|
- type: precision_at_1 |
|
|
value: 36.67 |
|
|
- type: precision_at_10 |
|
|
value: 8.518 |
|
|
- type: precision_at_100 |
|
|
value: 1.2890000000000001 |
|
|
- type: precision_at_1000 |
|
|
value: 0.163 |
|
|
- type: precision_at_3 |
|
|
value: 19.955000000000002 |
|
|
- type: precision_at_5 |
|
|
value: 14.11 |
|
|
- type: recall_at_1 |
|
|
value: 30.324 |
|
|
- type: recall_at_10 |
|
|
value: 59.845000000000006 |
|
|
- type: recall_at_100 |
|
|
value: 81.77499999999999 |
|
|
- type: recall_at_1000 |
|
|
value: 94.463 |
|
|
- type: recall_at_3 |
|
|
value: 46.019 |
|
|
- type: recall_at_5 |
|
|
value: 52.163000000000004 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: BeIR/cqadupstack |
|
|
name: MTEB CQADupstackProgrammersRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 24.229 |
|
|
- type: map_at_10 |
|
|
value: 35.004000000000005 |
|
|
- type: map_at_100 |
|
|
value: 36.409000000000006 |
|
|
- type: map_at_1000 |
|
|
value: 36.521 |
|
|
- type: map_at_3 |
|
|
value: 31.793 |
|
|
- type: map_at_5 |
|
|
value: 33.432 |
|
|
- type: mrr_at_1 |
|
|
value: 30.365 |
|
|
- type: mrr_at_10 |
|
|
value: 40.502 |
|
|
- type: mrr_at_100 |
|
|
value: 41.372 |
|
|
- type: mrr_at_1000 |
|
|
value: 41.435 |
|
|
- type: mrr_at_3 |
|
|
value: 37.804 |
|
|
- type: mrr_at_5 |
|
|
value: 39.226 |
|
|
- type: ndcg_at_1 |
|
|
value: 30.365 |
|
|
- type: ndcg_at_10 |
|
|
value: 41.305 |
|
|
- type: ndcg_at_100 |
|
|
value: 47.028999999999996 |
|
|
- type: ndcg_at_1000 |
|
|
value: 49.375 |
|
|
- type: ndcg_at_3 |
|
|
value: 35.85 |
|
|
- type: ndcg_at_5 |
|
|
value: 38.12 |
|
|
- type: precision_at_1 |
|
|
value: 30.365 |
|
|
- type: precision_at_10 |
|
|
value: 7.808 |
|
|
- type: precision_at_100 |
|
|
value: 1.228 |
|
|
- type: precision_at_1000 |
|
|
value: 0.161 |
|
|
- type: precision_at_3 |
|
|
value: 17.352 |
|
|
- type: precision_at_5 |
|
|
value: 12.42 |
|
|
- type: recall_at_1 |
|
|
value: 24.229 |
|
|
- type: recall_at_10 |
|
|
value: 54.673 |
|
|
- type: recall_at_100 |
|
|
value: 78.766 |
|
|
- type: recall_at_1000 |
|
|
value: 94.625 |
|
|
- type: recall_at_3 |
|
|
value: 39.602 |
|
|
- type: recall_at_5 |
|
|
value: 45.558 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: BeIR/cqadupstack |
|
|
name: MTEB CQADupstackRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 26.695 |
|
|
- type: map_at_10 |
|
|
value: 36.0895 |
|
|
- type: map_at_100 |
|
|
value: 37.309416666666664 |
|
|
- type: map_at_1000 |
|
|
value: 37.42558333333334 |
|
|
- type: map_at_3 |
|
|
value: 33.19616666666666 |
|
|
- type: map_at_5 |
|
|
value: 34.78641666666667 |
|
|
- type: mrr_at_1 |
|
|
value: 31.486083333333337 |
|
|
- type: mrr_at_10 |
|
|
value: 40.34774999999999 |
|
|
- type: mrr_at_100 |
|
|
value: 41.17533333333333 |
|
|
- type: mrr_at_1000 |
|
|
value: 41.231583333333326 |
|
|
- type: mrr_at_3 |
|
|
value: 37.90075 |
|
|
- type: mrr_at_5 |
|
|
value: 39.266999999999996 |
|
|
- type: ndcg_at_1 |
|
|
value: 31.486083333333337 |
|
|
- type: ndcg_at_10 |
|
|
value: 41.60433333333334 |
|
|
- type: ndcg_at_100 |
|
|
value: 46.74525 |
|
|
- type: ndcg_at_1000 |
|
|
value: 48.96166666666667 |
|
|
- type: ndcg_at_3 |
|
|
value: 36.68825 |
|
|
- type: ndcg_at_5 |
|
|
value: 38.966499999999996 |
|
|
- type: precision_at_1 |
|
|
value: 31.486083333333337 |
|
|
- type: precision_at_10 |
|
|
value: 7.29675 |
|
|
- type: precision_at_100 |
|
|
value: 1.1621666666666666 |
|
|
- type: precision_at_1000 |
|
|
value: 0.1545 |
|
|
- type: precision_at_3 |
|
|
value: 16.8815 |
|
|
- type: precision_at_5 |
|
|
value: 11.974583333333333 |
|
|
- type: recall_at_1 |
|
|
value: 26.695 |
|
|
- type: recall_at_10 |
|
|
value: 53.651916666666665 |
|
|
- type: recall_at_100 |
|
|
value: 76.12083333333332 |
|
|
- type: recall_at_1000 |
|
|
value: 91.31191666666668 |
|
|
- type: recall_at_3 |
|
|
value: 40.03575 |
|
|
- type: recall_at_5 |
|
|
value: 45.876666666666665 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: BeIR/cqadupstack |
|
|
name: MTEB CQADupstackStatsRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 25.668000000000003 |
|
|
- type: map_at_10 |
|
|
value: 32.486 |
|
|
- type: map_at_100 |
|
|
value: 33.371 |
|
|
- type: map_at_1000 |
|
|
value: 33.458 |
|
|
- type: map_at_3 |
|
|
value: 30.261 |
|
|
- type: map_at_5 |
|
|
value: 31.418000000000003 |
|
|
- type: mrr_at_1 |
|
|
value: 28.988000000000003 |
|
|
- type: mrr_at_10 |
|
|
value: 35.414 |
|
|
- type: mrr_at_100 |
|
|
value: 36.149 |
|
|
- type: mrr_at_1000 |
|
|
value: 36.215 |
|
|
- type: mrr_at_3 |
|
|
value: 33.333 |
|
|
- type: mrr_at_5 |
|
|
value: 34.43 |
|
|
- type: ndcg_at_1 |
|
|
value: 28.988000000000003 |
|
|
- type: ndcg_at_10 |
|
|
value: 36.732 |
|
|
- type: ndcg_at_100 |
|
|
value: 41.331 |
|
|
- type: ndcg_at_1000 |
|
|
value: 43.575 |
|
|
- type: ndcg_at_3 |
|
|
value: 32.413 |
|
|
- type: ndcg_at_5 |
|
|
value: 34.316 |
|
|
- type: precision_at_1 |
|
|
value: 28.988000000000003 |
|
|
- type: precision_at_10 |
|
|
value: 5.7059999999999995 |
|
|
- type: precision_at_100 |
|
|
value: 0.882 |
|
|
- type: precision_at_1000 |
|
|
value: 0.11299999999999999 |
|
|
- type: precision_at_3 |
|
|
value: 13.65 |
|
|
- type: precision_at_5 |
|
|
value: 9.417 |
|
|
- type: recall_at_1 |
|
|
value: 25.668000000000003 |
|
|
- type: recall_at_10 |
|
|
value: 47.147 |
|
|
- type: recall_at_100 |
|
|
value: 68.504 |
|
|
- type: recall_at_1000 |
|
|
value: 85.272 |
|
|
- type: recall_at_3 |
|
|
value: 35.19 |
|
|
- type: recall_at_5 |
|
|
value: 39.925 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: BeIR/cqadupstack |
|
|
name: MTEB CQADupstackTexRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 17.256 |
|
|
- type: map_at_10 |
|
|
value: 24.58 |
|
|
- type: map_at_100 |
|
|
value: 25.773000000000003 |
|
|
- type: map_at_1000 |
|
|
value: 25.899 |
|
|
- type: map_at_3 |
|
|
value: 22.236 |
|
|
- type: map_at_5 |
|
|
value: 23.507 |
|
|
- type: mrr_at_1 |
|
|
value: 20.957 |
|
|
- type: mrr_at_10 |
|
|
value: 28.416000000000004 |
|
|
- type: mrr_at_100 |
|
|
value: 29.447000000000003 |
|
|
- type: mrr_at_1000 |
|
|
value: 29.524 |
|
|
- type: mrr_at_3 |
|
|
value: 26.245 |
|
|
- type: mrr_at_5 |
|
|
value: 27.451999999999998 |
|
|
- type: ndcg_at_1 |
|
|
value: 20.957 |
|
|
- type: ndcg_at_10 |
|
|
value: 29.285 |
|
|
- type: ndcg_at_100 |
|
|
value: 35.003 |
|
|
- type: ndcg_at_1000 |
|
|
value: 37.881 |
|
|
- type: ndcg_at_3 |
|
|
value: 25.063000000000002 |
|
|
- type: ndcg_at_5 |
|
|
value: 26.983 |
|
|
- type: precision_at_1 |
|
|
value: 20.957 |
|
|
- type: precision_at_10 |
|
|
value: 5.344 |
|
|
- type: precision_at_100 |
|
|
value: 0.958 |
|
|
- type: precision_at_1000 |
|
|
value: 0.13799999999999998 |
|
|
- type: precision_at_3 |
|
|
value: 11.918 |
|
|
- type: precision_at_5 |
|
|
value: 8.596 |
|
|
- type: recall_at_1 |
|
|
value: 17.256 |
|
|
- type: recall_at_10 |
|
|
value: 39.644 |
|
|
- type: recall_at_100 |
|
|
value: 65.279 |
|
|
- type: recall_at_1000 |
|
|
value: 85.693 |
|
|
- type: recall_at_3 |
|
|
value: 27.825 |
|
|
- type: recall_at_5 |
|
|
value: 32.792 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: BeIR/cqadupstack |
|
|
name: MTEB CQADupstackUnixRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 26.700000000000003 |
|
|
- type: map_at_10 |
|
|
value: 36.205999999999996 |
|
|
- type: map_at_100 |
|
|
value: 37.316 |
|
|
- type: map_at_1000 |
|
|
value: 37.425000000000004 |
|
|
- type: map_at_3 |
|
|
value: 33.166000000000004 |
|
|
- type: map_at_5 |
|
|
value: 35.032999999999994 |
|
|
- type: mrr_at_1 |
|
|
value: 31.436999999999998 |
|
|
- type: mrr_at_10 |
|
|
value: 40.61 |
|
|
- type: mrr_at_100 |
|
|
value: 41.415 |
|
|
- type: mrr_at_1000 |
|
|
value: 41.48 |
|
|
- type: mrr_at_3 |
|
|
value: 37.966 |
|
|
- type: mrr_at_5 |
|
|
value: 39.599000000000004 |
|
|
- type: ndcg_at_1 |
|
|
value: 31.436999999999998 |
|
|
- type: ndcg_at_10 |
|
|
value: 41.771 |
|
|
- type: ndcg_at_100 |
|
|
value: 46.784 |
|
|
- type: ndcg_at_1000 |
|
|
value: 49.183 |
|
|
- type: ndcg_at_3 |
|
|
value: 36.437000000000005 |
|
|
- type: ndcg_at_5 |
|
|
value: 39.291 |
|
|
- type: precision_at_1 |
|
|
value: 31.436999999999998 |
|
|
- type: precision_at_10 |
|
|
value: 6.987 |
|
|
- type: precision_at_100 |
|
|
value: 1.072 |
|
|
- type: precision_at_1000 |
|
|
value: 0.13899999999999998 |
|
|
- type: precision_at_3 |
|
|
value: 16.448999999999998 |
|
|
- type: precision_at_5 |
|
|
value: 11.866 |
|
|
- type: recall_at_1 |
|
|
value: 26.700000000000003 |
|
|
- type: recall_at_10 |
|
|
value: 54.301 |
|
|
- type: recall_at_100 |
|
|
value: 75.871 |
|
|
- type: recall_at_1000 |
|
|
value: 92.529 |
|
|
- type: recall_at_3 |
|
|
value: 40.201 |
|
|
- type: recall_at_5 |
|
|
value: 47.208 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: BeIR/cqadupstack |
|
|
name: MTEB CQADupstackWebmastersRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 24.296 |
|
|
- type: map_at_10 |
|
|
value: 33.116 |
|
|
- type: map_at_100 |
|
|
value: 34.81 |
|
|
- type: map_at_1000 |
|
|
value: 35.032000000000004 |
|
|
- type: map_at_3 |
|
|
value: 30.105999999999998 |
|
|
- type: map_at_5 |
|
|
value: 31.839000000000002 |
|
|
- type: mrr_at_1 |
|
|
value: 29.051 |
|
|
- type: mrr_at_10 |
|
|
value: 37.803 |
|
|
- type: mrr_at_100 |
|
|
value: 38.856 |
|
|
- type: mrr_at_1000 |
|
|
value: 38.903999999999996 |
|
|
- type: mrr_at_3 |
|
|
value: 35.211 |
|
|
- type: mrr_at_5 |
|
|
value: 36.545 |
|
|
- type: ndcg_at_1 |
|
|
value: 29.051 |
|
|
- type: ndcg_at_10 |
|
|
value: 39.007 |
|
|
- type: ndcg_at_100 |
|
|
value: 45.321 |
|
|
- type: ndcg_at_1000 |
|
|
value: 47.665 |
|
|
- type: ndcg_at_3 |
|
|
value: 34.1 |
|
|
- type: ndcg_at_5 |
|
|
value: 36.437000000000005 |
|
|
- type: precision_at_1 |
|
|
value: 29.051 |
|
|
- type: precision_at_10 |
|
|
value: 7.668 |
|
|
- type: precision_at_100 |
|
|
value: 1.542 |
|
|
- type: precision_at_1000 |
|
|
value: 0.24 |
|
|
- type: precision_at_3 |
|
|
value: 16.14 |
|
|
- type: precision_at_5 |
|
|
value: 11.897 |
|
|
- type: recall_at_1 |
|
|
value: 24.296 |
|
|
- type: recall_at_10 |
|
|
value: 49.85 |
|
|
- type: recall_at_100 |
|
|
value: 78.457 |
|
|
- type: recall_at_1000 |
|
|
value: 92.618 |
|
|
- type: recall_at_3 |
|
|
value: 36.138999999999996 |
|
|
- type: recall_at_5 |
|
|
value: 42.223 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: BeIR/cqadupstack |
|
|
name: MTEB CQADupstackWordpressRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 20.591 |
|
|
- type: map_at_10 |
|
|
value: 28.902 |
|
|
- type: map_at_100 |
|
|
value: 29.886000000000003 |
|
|
- type: map_at_1000 |
|
|
value: 29.987000000000002 |
|
|
- type: map_at_3 |
|
|
value: 26.740000000000002 |
|
|
- type: map_at_5 |
|
|
value: 27.976 |
|
|
- type: mrr_at_1 |
|
|
value: 22.366 |
|
|
- type: mrr_at_10 |
|
|
value: 30.971 |
|
|
- type: mrr_at_100 |
|
|
value: 31.865 |
|
|
- type: mrr_at_1000 |
|
|
value: 31.930999999999997 |
|
|
- type: mrr_at_3 |
|
|
value: 28.927999999999997 |
|
|
- type: mrr_at_5 |
|
|
value: 30.231 |
|
|
- type: ndcg_at_1 |
|
|
value: 22.366 |
|
|
- type: ndcg_at_10 |
|
|
value: 33.641 |
|
|
- type: ndcg_at_100 |
|
|
value: 38.477 |
|
|
- type: ndcg_at_1000 |
|
|
value: 41.088 |
|
|
- type: ndcg_at_3 |
|
|
value: 29.486 |
|
|
- type: ndcg_at_5 |
|
|
value: 31.612000000000002 |
|
|
- type: precision_at_1 |
|
|
value: 22.366 |
|
|
- type: precision_at_10 |
|
|
value: 5.3420000000000005 |
|
|
- type: precision_at_100 |
|
|
value: 0.828 |
|
|
- type: precision_at_1000 |
|
|
value: 0.11800000000000001 |
|
|
- type: precision_at_3 |
|
|
value: 12.939 |
|
|
- type: precision_at_5 |
|
|
value: 9.094 |
|
|
- type: recall_at_1 |
|
|
value: 20.591 |
|
|
- type: recall_at_10 |
|
|
value: 46.052 |
|
|
- type: recall_at_100 |
|
|
value: 68.193 |
|
|
- type: recall_at_1000 |
|
|
value: 87.638 |
|
|
- type: recall_at_3 |
|
|
value: 34.966 |
|
|
- type: recall_at_5 |
|
|
value: 40.082 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: climate-fever |
|
|
name: MTEB ClimateFEVER |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 15.091 |
|
|
- type: map_at_10 |
|
|
value: 26.38 |
|
|
- type: map_at_100 |
|
|
value: 28.421999999999997 |
|
|
- type: map_at_1000 |
|
|
value: 28.621999999999996 |
|
|
- type: map_at_3 |
|
|
value: 21.597 |
|
|
- type: map_at_5 |
|
|
value: 24.12 |
|
|
- type: mrr_at_1 |
|
|
value: 34.266999999999996 |
|
|
- type: mrr_at_10 |
|
|
value: 46.864 |
|
|
- type: mrr_at_100 |
|
|
value: 47.617 |
|
|
- type: mrr_at_1000 |
|
|
value: 47.644 |
|
|
- type: mrr_at_3 |
|
|
value: 43.312 |
|
|
- type: mrr_at_5 |
|
|
value: 45.501000000000005 |
|
|
- type: ndcg_at_1 |
|
|
value: 34.266999999999996 |
|
|
- type: ndcg_at_10 |
|
|
value: 36.095 |
|
|
- type: ndcg_at_100 |
|
|
value: 43.447 |
|
|
- type: ndcg_at_1000 |
|
|
value: 46.661 |
|
|
- type: ndcg_at_3 |
|
|
value: 29.337999999999997 |
|
|
- type: ndcg_at_5 |
|
|
value: 31.824 |
|
|
- type: precision_at_1 |
|
|
value: 34.266999999999996 |
|
|
- type: precision_at_10 |
|
|
value: 11.472 |
|
|
- type: precision_at_100 |
|
|
value: 1.944 |
|
|
- type: precision_at_1000 |
|
|
value: 0.255 |
|
|
- type: precision_at_3 |
|
|
value: 21.933 |
|
|
- type: precision_at_5 |
|
|
value: 17.224999999999998 |
|
|
- type: recall_at_1 |
|
|
value: 15.091 |
|
|
- type: recall_at_10 |
|
|
value: 43.022 |
|
|
- type: recall_at_100 |
|
|
value: 68.075 |
|
|
- type: recall_at_1000 |
|
|
value: 85.76 |
|
|
- type: recall_at_3 |
|
|
value: 26.564 |
|
|
- type: recall_at_5 |
|
|
value: 33.594 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: dbpedia-entity |
|
|
name: MTEB DBPedia |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 9.252 |
|
|
- type: map_at_10 |
|
|
value: 20.923 |
|
|
- type: map_at_100 |
|
|
value: 30.741000000000003 |
|
|
- type: map_at_1000 |
|
|
value: 32.542 |
|
|
- type: map_at_3 |
|
|
value: 14.442 |
|
|
- type: map_at_5 |
|
|
value: 17.399 |
|
|
- type: mrr_at_1 |
|
|
value: 70.25 |
|
|
- type: mrr_at_10 |
|
|
value: 78.17 |
|
|
- type: mrr_at_100 |
|
|
value: 78.444 |
|
|
- type: mrr_at_1000 |
|
|
value: 78.45100000000001 |
|
|
- type: mrr_at_3 |
|
|
value: 76.958 |
|
|
- type: mrr_at_5 |
|
|
value: 77.571 |
|
|
- type: ndcg_at_1 |
|
|
value: 58.375 |
|
|
- type: ndcg_at_10 |
|
|
value: 44.509 |
|
|
- type: ndcg_at_100 |
|
|
value: 49.897999999999996 |
|
|
- type: ndcg_at_1000 |
|
|
value: 57.269999999999996 |
|
|
- type: ndcg_at_3 |
|
|
value: 48.64 |
|
|
- type: ndcg_at_5 |
|
|
value: 46.697 |
|
|
- type: precision_at_1 |
|
|
value: 70.25 |
|
|
- type: precision_at_10 |
|
|
value: 36.05 |
|
|
- type: precision_at_100 |
|
|
value: 11.848 |
|
|
- type: precision_at_1000 |
|
|
value: 2.213 |
|
|
- type: precision_at_3 |
|
|
value: 52.917 |
|
|
- type: precision_at_5 |
|
|
value: 45.7 |
|
|
- type: recall_at_1 |
|
|
value: 9.252 |
|
|
- type: recall_at_10 |
|
|
value: 27.006999999999998 |
|
|
- type: recall_at_100 |
|
|
value: 57.008 |
|
|
- type: recall_at_1000 |
|
|
value: 80.697 |
|
|
- type: recall_at_3 |
|
|
value: 15.798000000000002 |
|
|
- type: recall_at_5 |
|
|
value: 20.4 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/emotion |
|
|
name: MTEB EmotionClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 50.88 |
|
|
- type: f1 |
|
|
value: 45.545495028653384 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: fever |
|
|
name: MTEB FEVER |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 75.424 |
|
|
- type: map_at_10 |
|
|
value: 83.435 |
|
|
- type: map_at_100 |
|
|
value: 83.66900000000001 |
|
|
- type: map_at_1000 |
|
|
value: 83.685 |
|
|
- type: map_at_3 |
|
|
value: 82.39800000000001 |
|
|
- type: map_at_5 |
|
|
value: 83.07 |
|
|
- type: mrr_at_1 |
|
|
value: 81.113 |
|
|
- type: mrr_at_10 |
|
|
value: 87.77199999999999 |
|
|
- type: mrr_at_100 |
|
|
value: 87.862 |
|
|
- type: mrr_at_1000 |
|
|
value: 87.86500000000001 |
|
|
- type: mrr_at_3 |
|
|
value: 87.17099999999999 |
|
|
- type: mrr_at_5 |
|
|
value: 87.616 |
|
|
- type: ndcg_at_1 |
|
|
value: 81.113 |
|
|
- type: ndcg_at_10 |
|
|
value: 86.909 |
|
|
- type: ndcg_at_100 |
|
|
value: 87.746 |
|
|
- type: ndcg_at_1000 |
|
|
value: 88.017 |
|
|
- type: ndcg_at_3 |
|
|
value: 85.368 |
|
|
- type: ndcg_at_5 |
|
|
value: 86.28099999999999 |
|
|
- type: precision_at_1 |
|
|
value: 81.113 |
|
|
- type: precision_at_10 |
|
|
value: 10.363 |
|
|
- type: precision_at_100 |
|
|
value: 1.102 |
|
|
- type: precision_at_1000 |
|
|
value: 0.11399999999999999 |
|
|
- type: precision_at_3 |
|
|
value: 32.507999999999996 |
|
|
- type: precision_at_5 |
|
|
value: 20.138 |
|
|
- type: recall_at_1 |
|
|
value: 75.424 |
|
|
- type: recall_at_10 |
|
|
value: 93.258 |
|
|
- type: recall_at_100 |
|
|
value: 96.545 |
|
|
- type: recall_at_1000 |
|
|
value: 98.284 |
|
|
- type: recall_at_3 |
|
|
value: 89.083 |
|
|
- type: recall_at_5 |
|
|
value: 91.445 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: fiqa |
|
|
name: MTEB FiQA2018 |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 22.532 |
|
|
- type: map_at_10 |
|
|
value: 37.141999999999996 |
|
|
- type: map_at_100 |
|
|
value: 39.162 |
|
|
- type: map_at_1000 |
|
|
value: 39.322 |
|
|
- type: map_at_3 |
|
|
value: 32.885 |
|
|
- type: map_at_5 |
|
|
value: 35.093999999999994 |
|
|
- type: mrr_at_1 |
|
|
value: 44.29 |
|
|
- type: mrr_at_10 |
|
|
value: 53.516 |
|
|
- type: mrr_at_100 |
|
|
value: 54.24 |
|
|
- type: mrr_at_1000 |
|
|
value: 54.273 |
|
|
- type: mrr_at_3 |
|
|
value: 51.286 |
|
|
- type: mrr_at_5 |
|
|
value: 52.413 |
|
|
- type: ndcg_at_1 |
|
|
value: 44.29 |
|
|
- type: ndcg_at_10 |
|
|
value: 45.268 |
|
|
- type: ndcg_at_100 |
|
|
value: 52.125 |
|
|
- type: ndcg_at_1000 |
|
|
value: 54.778000000000006 |
|
|
- type: ndcg_at_3 |
|
|
value: 41.829 |
|
|
- type: ndcg_at_5 |
|
|
value: 42.525 |
|
|
- type: precision_at_1 |
|
|
value: 44.29 |
|
|
- type: precision_at_10 |
|
|
value: 12.5 |
|
|
- type: precision_at_100 |
|
|
value: 1.9720000000000002 |
|
|
- type: precision_at_1000 |
|
|
value: 0.245 |
|
|
- type: precision_at_3 |
|
|
value: 28.035 |
|
|
- type: precision_at_5 |
|
|
value: 20.093 |
|
|
- type: recall_at_1 |
|
|
value: 22.532 |
|
|
- type: recall_at_10 |
|
|
value: 52.419000000000004 |
|
|
- type: recall_at_100 |
|
|
value: 77.43299999999999 |
|
|
- type: recall_at_1000 |
|
|
value: 93.379 |
|
|
- type: recall_at_3 |
|
|
value: 38.629000000000005 |
|
|
- type: recall_at_5 |
|
|
value: 43.858000000000004 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: hotpotqa |
|
|
name: MTEB HotpotQA |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 39.359 |
|
|
- type: map_at_10 |
|
|
value: 63.966 |
|
|
- type: map_at_100 |
|
|
value: 64.87 |
|
|
- type: map_at_1000 |
|
|
value: 64.92599999999999 |
|
|
- type: map_at_3 |
|
|
value: 60.409 |
|
|
- type: map_at_5 |
|
|
value: 62.627 |
|
|
- type: mrr_at_1 |
|
|
value: 78.717 |
|
|
- type: mrr_at_10 |
|
|
value: 84.468 |
|
|
- type: mrr_at_100 |
|
|
value: 84.655 |
|
|
- type: mrr_at_1000 |
|
|
value: 84.661 |
|
|
- type: mrr_at_3 |
|
|
value: 83.554 |
|
|
- type: mrr_at_5 |
|
|
value: 84.133 |
|
|
- type: ndcg_at_1 |
|
|
value: 78.717 |
|
|
- type: ndcg_at_10 |
|
|
value: 72.03399999999999 |
|
|
- type: ndcg_at_100 |
|
|
value: 75.158 |
|
|
- type: ndcg_at_1000 |
|
|
value: 76.197 |
|
|
- type: ndcg_at_3 |
|
|
value: 67.049 |
|
|
- type: ndcg_at_5 |
|
|
value: 69.808 |
|
|
- type: precision_at_1 |
|
|
value: 78.717 |
|
|
- type: precision_at_10 |
|
|
value: 15.201 |
|
|
- type: precision_at_100 |
|
|
value: 1.764 |
|
|
- type: precision_at_1000 |
|
|
value: 0.19 |
|
|
- type: precision_at_3 |
|
|
value: 43.313 |
|
|
- type: precision_at_5 |
|
|
value: 28.165000000000003 |
|
|
- type: recall_at_1 |
|
|
value: 39.359 |
|
|
- type: recall_at_10 |
|
|
value: 76.003 |
|
|
- type: recall_at_100 |
|
|
value: 88.197 |
|
|
- type: recall_at_1000 |
|
|
value: 95.003 |
|
|
- type: recall_at_3 |
|
|
value: 64.97 |
|
|
- type: recall_at_5 |
|
|
value: 70.41199999999999 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/imdb |
|
|
name: MTEB ImdbClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 92.83200000000001 |
|
|
- type: ap |
|
|
value: 89.33560571859861 |
|
|
- type: f1 |
|
|
value: 92.82322915005167 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: msmarco |
|
|
name: MTEB MSMARCO |
|
|
config: default |
|
|
split: dev |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 21.983 |
|
|
- type: map_at_10 |
|
|
value: 34.259 |
|
|
- type: map_at_100 |
|
|
value: 35.432 |
|
|
- type: map_at_1000 |
|
|
value: 35.482 |
|
|
- type: map_at_3 |
|
|
value: 30.275999999999996 |
|
|
- type: map_at_5 |
|
|
value: 32.566 |
|
|
- type: mrr_at_1 |
|
|
value: 22.579 |
|
|
- type: mrr_at_10 |
|
|
value: 34.882999999999996 |
|
|
- type: mrr_at_100 |
|
|
value: 35.984 |
|
|
- type: mrr_at_1000 |
|
|
value: 36.028 |
|
|
- type: mrr_at_3 |
|
|
value: 30.964999999999996 |
|
|
- type: mrr_at_5 |
|
|
value: 33.245000000000005 |
|
|
- type: ndcg_at_1 |
|
|
value: 22.564 |
|
|
- type: ndcg_at_10 |
|
|
value: 41.258 |
|
|
- type: ndcg_at_100 |
|
|
value: 46.824 |
|
|
- type: ndcg_at_1000 |
|
|
value: 48.037 |
|
|
- type: ndcg_at_3 |
|
|
value: 33.17 |
|
|
- type: ndcg_at_5 |
|
|
value: 37.263000000000005 |
|
|
- type: precision_at_1 |
|
|
value: 22.564 |
|
|
- type: precision_at_10 |
|
|
value: 6.572 |
|
|
- type: precision_at_100 |
|
|
value: 0.935 |
|
|
- type: precision_at_1000 |
|
|
value: 0.104 |
|
|
- type: precision_at_3 |
|
|
value: 14.130999999999998 |
|
|
- type: precision_at_5 |
|
|
value: 10.544 |
|
|
- type: recall_at_1 |
|
|
value: 21.983 |
|
|
- type: recall_at_10 |
|
|
value: 62.775000000000006 |
|
|
- type: recall_at_100 |
|
|
value: 88.389 |
|
|
- type: recall_at_1000 |
|
|
value: 97.603 |
|
|
- type: recall_at_3 |
|
|
value: 40.878 |
|
|
- type: recall_at_5 |
|
|
value: 50.690000000000005 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/mtop_domain |
|
|
name: MTEB MTOPDomainClassification (en) |
|
|
config: en |
|
|
split: test |
|
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 93.95120839033288 |
|
|
- type: f1 |
|
|
value: 93.73824125055208 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/mtop_intent |
|
|
name: MTEB MTOPIntentClassification (en) |
|
|
config: en |
|
|
split: test |
|
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 76.78978568171455 |
|
|
- type: f1 |
|
|
value: 57.50180552858304 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_intent |
|
|
name: MTEB MassiveIntentClassification (en) |
|
|
config: en |
|
|
split: test |
|
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 76.24411566913248 |
|
|
- type: f1 |
|
|
value: 74.37851403532832 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (en) |
|
|
config: en |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 79.94620040349699 |
|
|
- type: f1 |
|
|
value: 80.21293397970435 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/medrxiv-clustering-p2p |
|
|
name: MTEB MedrxivClusteringP2P |
|
|
config: default |
|
|
split: test |
|
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 33.44403096245675 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/medrxiv-clustering-s2s |
|
|
name: MTEB MedrxivClusteringS2S |
|
|
config: default |
|
|
split: test |
|
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 31.659594631336812 |
|
|
- task: |
|
|
type: Reranking |
|
|
dataset: |
|
|
type: mteb/mind_small |
|
|
name: MTEB MindSmallReranking |
|
|
config: default |
|
|
split: test |
|
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
|
metrics: |
|
|
- type: map |
|
|
value: 32.53833075108798 |
|
|
- type: mrr |
|
|
value: 33.78840823218308 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: nfcorpus |
|
|
name: MTEB NFCorpus |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 7.185999999999999 |
|
|
- type: map_at_10 |
|
|
value: 15.193999999999999 |
|
|
- type: map_at_100 |
|
|
value: 19.538 |
|
|
- type: map_at_1000 |
|
|
value: 21.178 |
|
|
- type: map_at_3 |
|
|
value: 11.208 |
|
|
- type: map_at_5 |
|
|
value: 12.745999999999999 |
|
|
- type: mrr_at_1 |
|
|
value: 48.916 |
|
|
- type: mrr_at_10 |
|
|
value: 58.141 |
|
|
- type: mrr_at_100 |
|
|
value: 58.656 |
|
|
- type: mrr_at_1000 |
|
|
value: 58.684999999999995 |
|
|
- type: mrr_at_3 |
|
|
value: 55.521 |
|
|
- type: mrr_at_5 |
|
|
value: 57.239 |
|
|
- type: ndcg_at_1 |
|
|
value: 47.059 |
|
|
- type: ndcg_at_10 |
|
|
value: 38.644 |
|
|
- type: ndcg_at_100 |
|
|
value: 36.272999999999996 |
|
|
- type: ndcg_at_1000 |
|
|
value: 44.996 |
|
|
- type: ndcg_at_3 |
|
|
value: 43.293 |
|
|
- type: ndcg_at_5 |
|
|
value: 40.819 |
|
|
- type: precision_at_1 |
|
|
value: 48.916 |
|
|
- type: precision_at_10 |
|
|
value: 28.607 |
|
|
- type: precision_at_100 |
|
|
value: 9.195 |
|
|
- type: precision_at_1000 |
|
|
value: 2.225 |
|
|
- type: precision_at_3 |
|
|
value: 40.454 |
|
|
- type: precision_at_5 |
|
|
value: 34.985 |
|
|
- type: recall_at_1 |
|
|
value: 7.185999999999999 |
|
|
- type: recall_at_10 |
|
|
value: 19.654 |
|
|
- type: recall_at_100 |
|
|
value: 37.224000000000004 |
|
|
- type: recall_at_1000 |
|
|
value: 68.663 |
|
|
- type: recall_at_3 |
|
|
value: 12.158 |
|
|
- type: recall_at_5 |
|
|
value: 14.674999999999999 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: nq |
|
|
name: MTEB NQ |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 31.552000000000003 |
|
|
- type: map_at_10 |
|
|
value: 47.75 |
|
|
- type: map_at_100 |
|
|
value: 48.728 |
|
|
- type: map_at_1000 |
|
|
value: 48.754 |
|
|
- type: map_at_3 |
|
|
value: 43.156 |
|
|
- type: map_at_5 |
|
|
value: 45.883 |
|
|
- type: mrr_at_1 |
|
|
value: 35.66 |
|
|
- type: mrr_at_10 |
|
|
value: 50.269 |
|
|
- type: mrr_at_100 |
|
|
value: 50.974 |
|
|
- type: mrr_at_1000 |
|
|
value: 50.991 |
|
|
- type: mrr_at_3 |
|
|
value: 46.519 |
|
|
- type: mrr_at_5 |
|
|
value: 48.764 |
|
|
- type: ndcg_at_1 |
|
|
value: 35.632000000000005 |
|
|
- type: ndcg_at_10 |
|
|
value: 55.786 |
|
|
- type: ndcg_at_100 |
|
|
value: 59.748999999999995 |
|
|
- type: ndcg_at_1000 |
|
|
value: 60.339 |
|
|
- type: ndcg_at_3 |
|
|
value: 47.292 |
|
|
- type: ndcg_at_5 |
|
|
value: 51.766999999999996 |
|
|
- type: precision_at_1 |
|
|
value: 35.632000000000005 |
|
|
- type: precision_at_10 |
|
|
value: 9.267 |
|
|
- type: precision_at_100 |
|
|
value: 1.149 |
|
|
- type: precision_at_1000 |
|
|
value: 0.12 |
|
|
- type: precision_at_3 |
|
|
value: 21.601 |
|
|
- type: precision_at_5 |
|
|
value: 15.539 |
|
|
- type: recall_at_1 |
|
|
value: 31.552000000000003 |
|
|
- type: recall_at_10 |
|
|
value: 77.62400000000001 |
|
|
- type: recall_at_100 |
|
|
value: 94.527 |
|
|
- type: recall_at_1000 |
|
|
value: 98.919 |
|
|
- type: recall_at_3 |
|
|
value: 55.898 |
|
|
- type: recall_at_5 |
|
|
value: 66.121 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: quora |
|
|
name: MTEB QuoraRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 71.414 |
|
|
- type: map_at_10 |
|
|
value: 85.37400000000001 |
|
|
- type: map_at_100 |
|
|
value: 86.01100000000001 |
|
|
- type: map_at_1000 |
|
|
value: 86.027 |
|
|
- type: map_at_3 |
|
|
value: 82.562 |
|
|
- type: map_at_5 |
|
|
value: 84.284 |
|
|
- type: mrr_at_1 |
|
|
value: 82.24000000000001 |
|
|
- type: mrr_at_10 |
|
|
value: 88.225 |
|
|
- type: mrr_at_100 |
|
|
value: 88.324 |
|
|
- type: mrr_at_1000 |
|
|
value: 88.325 |
|
|
- type: mrr_at_3 |
|
|
value: 87.348 |
|
|
- type: mrr_at_5 |
|
|
value: 87.938 |
|
|
- type: ndcg_at_1 |
|
|
value: 82.24000000000001 |
|
|
- type: ndcg_at_10 |
|
|
value: 88.97699999999999 |
|
|
- type: ndcg_at_100 |
|
|
value: 90.16 |
|
|
- type: ndcg_at_1000 |
|
|
value: 90.236 |
|
|
- type: ndcg_at_3 |
|
|
value: 86.371 |
|
|
- type: ndcg_at_5 |
|
|
value: 87.746 |
|
|
- type: precision_at_1 |
|
|
value: 82.24000000000001 |
|
|
- type: precision_at_10 |
|
|
value: 13.481000000000002 |
|
|
- type: precision_at_100 |
|
|
value: 1.534 |
|
|
- type: precision_at_1000 |
|
|
value: 0.157 |
|
|
- type: precision_at_3 |
|
|
value: 37.86 |
|
|
- type: precision_at_5 |
|
|
value: 24.738 |
|
|
- type: recall_at_1 |
|
|
value: 71.414 |
|
|
- type: recall_at_10 |
|
|
value: 95.735 |
|
|
- type: recall_at_100 |
|
|
value: 99.696 |
|
|
- type: recall_at_1000 |
|
|
value: 99.979 |
|
|
- type: recall_at_3 |
|
|
value: 88.105 |
|
|
- type: recall_at_5 |
|
|
value: 92.17999999999999 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/reddit-clustering |
|
|
name: MTEB RedditClustering |
|
|
config: default |
|
|
split: test |
|
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 60.22146692057259 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/reddit-clustering-p2p |
|
|
name: MTEB RedditClusteringP2P |
|
|
config: default |
|
|
split: test |
|
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 65.29273320614578 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: scidocs |
|
|
name: MTEB SCIDOCS |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 5.023 |
|
|
- type: map_at_10 |
|
|
value: 14.161000000000001 |
|
|
- type: map_at_100 |
|
|
value: 16.68 |
|
|
- type: map_at_1000 |
|
|
value: 17.072000000000003 |
|
|
- type: map_at_3 |
|
|
value: 9.763 |
|
|
- type: map_at_5 |
|
|
value: 11.977 |
|
|
- type: mrr_at_1 |
|
|
value: 24.8 |
|
|
- type: mrr_at_10 |
|
|
value: 37.602999999999994 |
|
|
- type: mrr_at_100 |
|
|
value: 38.618 |
|
|
- type: mrr_at_1000 |
|
|
value: 38.659 |
|
|
- type: mrr_at_3 |
|
|
value: 34.117 |
|
|
- type: mrr_at_5 |
|
|
value: 36.082 |
|
|
- type: ndcg_at_1 |
|
|
value: 24.8 |
|
|
- type: ndcg_at_10 |
|
|
value: 23.316 |
|
|
- type: ndcg_at_100 |
|
|
value: 32.613 |
|
|
- type: ndcg_at_1000 |
|
|
value: 38.609 |
|
|
- type: ndcg_at_3 |
|
|
value: 21.697 |
|
|
- type: ndcg_at_5 |
|
|
value: 19.241 |
|
|
- type: precision_at_1 |
|
|
value: 24.8 |
|
|
- type: precision_at_10 |
|
|
value: 12.36 |
|
|
- type: precision_at_100 |
|
|
value: 2.593 |
|
|
- type: precision_at_1000 |
|
|
value: 0.402 |
|
|
- type: precision_at_3 |
|
|
value: 20.767 |
|
|
- type: precision_at_5 |
|
|
value: 17.34 |
|
|
- type: recall_at_1 |
|
|
value: 5.023 |
|
|
- type: recall_at_10 |
|
|
value: 25.069999999999997 |
|
|
- type: recall_at_100 |
|
|
value: 52.563 |
|
|
- type: recall_at_1000 |
|
|
value: 81.525 |
|
|
- type: recall_at_3 |
|
|
value: 12.613 |
|
|
- type: recall_at_5 |
|
|
value: 17.583 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sickr-sts |
|
|
name: MTEB SICK-R |
|
|
config: default |
|
|
split: test |
|
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 87.71506247604255 |
|
|
- type: cos_sim_spearman |
|
|
value: 82.91813463738802 |
|
|
- type: euclidean_pearson |
|
|
value: 85.5154616194479 |
|
|
- type: euclidean_spearman |
|
|
value: 82.91815254466314 |
|
|
- type: manhattan_pearson |
|
|
value: 85.5280917850374 |
|
|
- type: manhattan_spearman |
|
|
value: 82.92276537286398 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts12-sts |
|
|
name: MTEB STS12 |
|
|
config: default |
|
|
split: test |
|
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 87.43772054228462 |
|
|
- type: cos_sim_spearman |
|
|
value: 78.75750601716682 |
|
|
- type: euclidean_pearson |
|
|
value: 85.76074482955764 |
|
|
- type: euclidean_spearman |
|
|
value: 78.75651057223058 |
|
|
- type: manhattan_pearson |
|
|
value: 85.73390291701668 |
|
|
- type: manhattan_spearman |
|
|
value: 78.72699385957797 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts13-sts |
|
|
name: MTEB STS13 |
|
|
config: default |
|
|
split: test |
|
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 89.58144067172472 |
|
|
- type: cos_sim_spearman |
|
|
value: 90.3524512966946 |
|
|
- type: euclidean_pearson |
|
|
value: 89.71365391594237 |
|
|
- type: euclidean_spearman |
|
|
value: 90.35239632843408 |
|
|
- type: manhattan_pearson |
|
|
value: 89.66905421746478 |
|
|
- type: manhattan_spearman |
|
|
value: 90.31508211683513 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts14-sts |
|
|
name: MTEB STS14 |
|
|
config: default |
|
|
split: test |
|
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 87.77692637102102 |
|
|
- type: cos_sim_spearman |
|
|
value: 85.45710562643485 |
|
|
- type: euclidean_pearson |
|
|
value: 87.42456979928723 |
|
|
- type: euclidean_spearman |
|
|
value: 85.45709386240908 |
|
|
- type: manhattan_pearson |
|
|
value: 87.40754529526272 |
|
|
- type: manhattan_spearman |
|
|
value: 85.44834854173303 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts15-sts |
|
|
name: MTEB STS15 |
|
|
config: default |
|
|
split: test |
|
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 88.28491331695997 |
|
|
- type: cos_sim_spearman |
|
|
value: 89.62037029566964 |
|
|
- type: euclidean_pearson |
|
|
value: 89.02479391362826 |
|
|
- type: euclidean_spearman |
|
|
value: 89.62036733618466 |
|
|
- type: manhattan_pearson |
|
|
value: 89.00394756040342 |
|
|
- type: manhattan_spearman |
|
|
value: 89.60867744215236 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts16-sts |
|
|
name: MTEB STS16 |
|
|
config: default |
|
|
split: test |
|
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 85.08911381280191 |
|
|
- type: cos_sim_spearman |
|
|
value: 86.5791780765767 |
|
|
- type: euclidean_pearson |
|
|
value: 86.16063473577861 |
|
|
- type: euclidean_spearman |
|
|
value: 86.57917745378766 |
|
|
- type: manhattan_pearson |
|
|
value: 86.13677924604175 |
|
|
- type: manhattan_spearman |
|
|
value: 86.56115615768685 |
|
|
- 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: 89.58029496205235 |
|
|
- type: cos_sim_spearman |
|
|
value: 89.49551253826998 |
|
|
- type: euclidean_pearson |
|
|
value: 90.13714840963748 |
|
|
- type: euclidean_spearman |
|
|
value: 89.49551253826998 |
|
|
- type: manhattan_pearson |
|
|
value: 90.13039633601363 |
|
|
- type: manhattan_spearman |
|
|
value: 89.4513453745516 |
|
|
- 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: 69.01546399666435 |
|
|
- type: cos_sim_spearman |
|
|
value: 69.33824484595624 |
|
|
- type: euclidean_pearson |
|
|
value: 70.76511642998874 |
|
|
- type: euclidean_spearman |
|
|
value: 69.33824484595624 |
|
|
- type: manhattan_pearson |
|
|
value: 70.84320785047453 |
|
|
- type: manhattan_spearman |
|
|
value: 69.54233632223537 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/stsbenchmark-sts |
|
|
name: MTEB STSBenchmark |
|
|
config: default |
|
|
split: test |
|
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 87.26389196390119 |
|
|
- type: cos_sim_spearman |
|
|
value: 89.09721478341385 |
|
|
- type: euclidean_pearson |
|
|
value: 88.97208685922517 |
|
|
- type: euclidean_spearman |
|
|
value: 89.09720927308881 |
|
|
- type: manhattan_pearson |
|
|
value: 88.97513670502573 |
|
|
- type: manhattan_spearman |
|
|
value: 89.07647853984004 |
|
|
- task: |
|
|
type: Reranking |
|
|
dataset: |
|
|
type: mteb/scidocs-reranking |
|
|
name: MTEB SciDocsRR |
|
|
config: default |
|
|
split: test |
|
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
|
metrics: |
|
|
- type: map |
|
|
value: 87.53075025771936 |
|
|
- type: mrr |
|
|
value: 96.24327651288436 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: scifact |
|
|
name: MTEB SciFact |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 60.428000000000004 |
|
|
- type: map_at_10 |
|
|
value: 70.088 |
|
|
- type: map_at_100 |
|
|
value: 70.589 |
|
|
- type: map_at_1000 |
|
|
value: 70.614 |
|
|
- type: map_at_3 |
|
|
value: 67.191 |
|
|
- type: map_at_5 |
|
|
value: 68.515 |
|
|
- type: mrr_at_1 |
|
|
value: 63.333 |
|
|
- type: mrr_at_10 |
|
|
value: 71.13000000000001 |
|
|
- type: mrr_at_100 |
|
|
value: 71.545 |
|
|
- type: mrr_at_1000 |
|
|
value: 71.569 |
|
|
- type: mrr_at_3 |
|
|
value: 68.944 |
|
|
- type: mrr_at_5 |
|
|
value: 70.078 |
|
|
- type: ndcg_at_1 |
|
|
value: 63.333 |
|
|
- type: ndcg_at_10 |
|
|
value: 74.72800000000001 |
|
|
- type: ndcg_at_100 |
|
|
value: 76.64999999999999 |
|
|
- type: ndcg_at_1000 |
|
|
value: 77.176 |
|
|
- type: ndcg_at_3 |
|
|
value: 69.659 |
|
|
- type: ndcg_at_5 |
|
|
value: 71.626 |
|
|
- type: precision_at_1 |
|
|
value: 63.333 |
|
|
- type: precision_at_10 |
|
|
value: 10 |
|
|
- type: precision_at_100 |
|
|
value: 1.09 |
|
|
- type: precision_at_1000 |
|
|
value: 0.11299999999999999 |
|
|
- type: precision_at_3 |
|
|
value: 27.111 |
|
|
- type: precision_at_5 |
|
|
value: 17.666999999999998 |
|
|
- type: recall_at_1 |
|
|
value: 60.428000000000004 |
|
|
- type: recall_at_10 |
|
|
value: 87.98899999999999 |
|
|
- type: recall_at_100 |
|
|
value: 96.167 |
|
|
- type: recall_at_1000 |
|
|
value: 100 |
|
|
- type: recall_at_3 |
|
|
value: 74.006 |
|
|
- type: recall_at_5 |
|
|
value: 79.05 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: mteb/sprintduplicatequestions-pairclassification |
|
|
name: MTEB SprintDuplicateQuestions |
|
|
config: default |
|
|
split: test |
|
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 99.87326732673267 |
|
|
- type: cos_sim_ap |
|
|
value: 96.81770773701805 |
|
|
- type: cos_sim_f1 |
|
|
value: 93.6318407960199 |
|
|
- type: cos_sim_precision |
|
|
value: 93.16831683168317 |
|
|
- type: cos_sim_recall |
|
|
value: 94.1 |
|
|
- type: dot_accuracy |
|
|
value: 99.87326732673267 |
|
|
- type: dot_ap |
|
|
value: 96.8174218946665 |
|
|
- type: dot_f1 |
|
|
value: 93.6318407960199 |
|
|
- type: dot_precision |
|
|
value: 93.16831683168317 |
|
|
- type: dot_recall |
|
|
value: 94.1 |
|
|
- type: euclidean_accuracy |
|
|
value: 99.87326732673267 |
|
|
- type: euclidean_ap |
|
|
value: 96.81770773701807 |
|
|
- type: euclidean_f1 |
|
|
value: 93.6318407960199 |
|
|
- type: euclidean_precision |
|
|
value: 93.16831683168317 |
|
|
- type: euclidean_recall |
|
|
value: 94.1 |
|
|
- type: manhattan_accuracy |
|
|
value: 99.87227722772278 |
|
|
- type: manhattan_ap |
|
|
value: 96.83164126821747 |
|
|
- type: manhattan_f1 |
|
|
value: 93.54677338669335 |
|
|
- type: manhattan_precision |
|
|
value: 93.5935935935936 |
|
|
- type: manhattan_recall |
|
|
value: 93.5 |
|
|
- type: max_accuracy |
|
|
value: 99.87326732673267 |
|
|
- type: max_ap |
|
|
value: 96.83164126821747 |
|
|
- type: max_f1 |
|
|
value: 93.6318407960199 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/stackexchange-clustering |
|
|
name: MTEB StackExchangeClustering |
|
|
config: default |
|
|
split: test |
|
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 65.6212042420246 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/stackexchange-clustering-p2p |
|
|
name: MTEB StackExchangeClusteringP2P |
|
|
config: default |
|
|
split: test |
|
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 35.779230635982564 |
|
|
- task: |
|
|
type: Reranking |
|
|
dataset: |
|
|
type: mteb/stackoverflowdupquestions-reranking |
|
|
name: MTEB StackOverflowDupQuestions |
|
|
config: default |
|
|
split: test |
|
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
|
metrics: |
|
|
- type: map |
|
|
value: 55.217701909036286 |
|
|
- type: mrr |
|
|
value: 56.17658995416349 |
|
|
- task: |
|
|
type: Summarization |
|
|
dataset: |
|
|
type: mteb/summeval |
|
|
name: MTEB SummEval |
|
|
config: default |
|
|
split: test |
|
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 30.954206018888453 |
|
|
- type: cos_sim_spearman |
|
|
value: 32.71062599450096 |
|
|
- type: dot_pearson |
|
|
value: 30.95420929056943 |
|
|
- type: dot_spearman |
|
|
value: 32.71062599450096 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: trec-covid |
|
|
name: MTEB TRECCOVID |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 0.22699999999999998 |
|
|
- type: map_at_10 |
|
|
value: 1.924 |
|
|
- type: map_at_100 |
|
|
value: 10.525 |
|
|
- type: map_at_1000 |
|
|
value: 24.973 |
|
|
- type: map_at_3 |
|
|
value: 0.638 |
|
|
- type: map_at_5 |
|
|
value: 1.0659999999999998 |
|
|
- type: mrr_at_1 |
|
|
value: 84 |
|
|
- type: mrr_at_10 |
|
|
value: 91.067 |
|
|
- type: mrr_at_100 |
|
|
value: 91.067 |
|
|
- type: mrr_at_1000 |
|
|
value: 91.067 |
|
|
- type: mrr_at_3 |
|
|
value: 90.667 |
|
|
- type: mrr_at_5 |
|
|
value: 91.067 |
|
|
- type: ndcg_at_1 |
|
|
value: 81 |
|
|
- type: ndcg_at_10 |
|
|
value: 75.566 |
|
|
- type: ndcg_at_100 |
|
|
value: 56.387 |
|
|
- type: ndcg_at_1000 |
|
|
value: 49.834 |
|
|
- type: ndcg_at_3 |
|
|
value: 80.899 |
|
|
- type: ndcg_at_5 |
|
|
value: 80.75099999999999 |
|
|
- type: precision_at_1 |
|
|
value: 84 |
|
|
- type: precision_at_10 |
|
|
value: 79 |
|
|
- type: precision_at_100 |
|
|
value: 57.56 |
|
|
- type: precision_at_1000 |
|
|
value: 21.8 |
|
|
- type: precision_at_3 |
|
|
value: 84.667 |
|
|
- type: precision_at_5 |
|
|
value: 85.2 |
|
|
- type: recall_at_1 |
|
|
value: 0.22699999999999998 |
|
|
- type: recall_at_10 |
|
|
value: 2.136 |
|
|
- type: recall_at_100 |
|
|
value: 13.861 |
|
|
- type: recall_at_1000 |
|
|
value: 46.299 |
|
|
- type: recall_at_3 |
|
|
value: 0.6649999999999999 |
|
|
- type: recall_at_5 |
|
|
value: 1.145 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: webis-touche2020 |
|
|
name: MTEB Touche2020 |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 2.752 |
|
|
- type: map_at_10 |
|
|
value: 9.951 |
|
|
- type: map_at_100 |
|
|
value: 16.794999999999998 |
|
|
- type: map_at_1000 |
|
|
value: 18.251 |
|
|
- type: map_at_3 |
|
|
value: 5.288 |
|
|
- type: map_at_5 |
|
|
value: 6.954000000000001 |
|
|
- type: mrr_at_1 |
|
|
value: 38.775999999999996 |
|
|
- type: mrr_at_10 |
|
|
value: 50.458000000000006 |
|
|
- type: mrr_at_100 |
|
|
value: 51.324999999999996 |
|
|
- type: mrr_at_1000 |
|
|
value: 51.339999999999996 |
|
|
- type: mrr_at_3 |
|
|
value: 46.939 |
|
|
- type: mrr_at_5 |
|
|
value: 47.857 |
|
|
- type: ndcg_at_1 |
|
|
value: 36.735 |
|
|
- type: ndcg_at_10 |
|
|
value: 25.198999999999998 |
|
|
- type: ndcg_at_100 |
|
|
value: 37.938 |
|
|
- type: ndcg_at_1000 |
|
|
value: 49.145 |
|
|
- type: ndcg_at_3 |
|
|
value: 29.348000000000003 |
|
|
- type: ndcg_at_5 |
|
|
value: 25.804 |
|
|
- type: precision_at_1 |
|
|
value: 38.775999999999996 |
|
|
- type: precision_at_10 |
|
|
value: 22.041 |
|
|
- type: precision_at_100 |
|
|
value: 7.939 |
|
|
- type: precision_at_1000 |
|
|
value: 1.555 |
|
|
- type: precision_at_3 |
|
|
value: 29.932 |
|
|
- type: precision_at_5 |
|
|
value: 24.490000000000002 |
|
|
- type: recall_at_1 |
|
|
value: 2.752 |
|
|
- type: recall_at_10 |
|
|
value: 16.197 |
|
|
- type: recall_at_100 |
|
|
value: 49.166 |
|
|
- type: recall_at_1000 |
|
|
value: 84.18900000000001 |
|
|
- type: recall_at_3 |
|
|
value: 6.438000000000001 |
|
|
- type: recall_at_5 |
|
|
value: 9.093 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/toxic_conversations_50k |
|
|
name: MTEB ToxicConversationsClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 71.47980000000001 |
|
|
- type: ap |
|
|
value: 14.605194452178754 |
|
|
- type: f1 |
|
|
value: 55.07362924988948 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/tweet_sentiment_extraction |
|
|
name: MTEB TweetSentimentExtractionClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 59.708545557441994 |
|
|
- type: f1 |
|
|
value: 60.04751270975683 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: mteb/twentynewsgroups-clustering |
|
|
name: MTEB TwentyNewsgroupsClustering |
|
|
config: default |
|
|
split: test |
|
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 53.21105960597211 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: mteb/twittersemeval2015-pairclassification |
|
|
name: MTEB TwitterSemEval2015 |
|
|
config: default |
|
|
split: test |
|
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 87.58419264469214 |
|
|
- type: cos_sim_ap |
|
|
value: 78.55300004517404 |
|
|
- type: cos_sim_f1 |
|
|
value: 71.49673530889001 |
|
|
- type: cos_sim_precision |
|
|
value: 68.20795400095831 |
|
|
- type: cos_sim_recall |
|
|
value: 75.11873350923483 |
|
|
- type: dot_accuracy |
|
|
value: 87.58419264469214 |
|
|
- type: dot_ap |
|
|
value: 78.55297659559511 |
|
|
- type: dot_f1 |
|
|
value: 71.49673530889001 |
|
|
- type: dot_precision |
|
|
value: 68.20795400095831 |
|
|
- type: dot_recall |
|
|
value: 75.11873350923483 |
|
|
- type: euclidean_accuracy |
|
|
value: 87.58419264469214 |
|
|
- type: euclidean_ap |
|
|
value: 78.55300477331477 |
|
|
- type: euclidean_f1 |
|
|
value: 71.49673530889001 |
|
|
- type: euclidean_precision |
|
|
value: 68.20795400095831 |
|
|
- type: euclidean_recall |
|
|
value: 75.11873350923483 |
|
|
- type: manhattan_accuracy |
|
|
value: 87.5663110210407 |
|
|
- type: manhattan_ap |
|
|
value: 78.49982050876562 |
|
|
- type: manhattan_f1 |
|
|
value: 71.35488740722104 |
|
|
- type: manhattan_precision |
|
|
value: 68.18946862226497 |
|
|
- type: manhattan_recall |
|
|
value: 74.82849604221636 |
|
|
- type: max_accuracy |
|
|
value: 87.58419264469214 |
|
|
- type: max_ap |
|
|
value: 78.55300477331477 |
|
|
- type: max_f1 |
|
|
value: 71.49673530889001 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: mteb/twitterurlcorpus-pairclassification |
|
|
name: MTEB TwitterURLCorpus |
|
|
config: default |
|
|
split: test |
|
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 89.09069740365584 |
|
|
- type: cos_sim_ap |
|
|
value: 86.22749303724757 |
|
|
- type: cos_sim_f1 |
|
|
value: 78.36863452005407 |
|
|
- type: cos_sim_precision |
|
|
value: 76.49560117302053 |
|
|
- type: cos_sim_recall |
|
|
value: 80.33569448721897 |
|
|
- type: dot_accuracy |
|
|
value: 89.09069740365584 |
|
|
- type: dot_ap |
|
|
value: 86.22750233655673 |
|
|
- type: dot_f1 |
|
|
value: 78.36863452005407 |
|
|
- type: dot_precision |
|
|
value: 76.49560117302053 |
|
|
- type: dot_recall |
|
|
value: 80.33569448721897 |
|
|
- type: euclidean_accuracy |
|
|
value: 89.09069740365584 |
|
|
- type: euclidean_ap |
|
|
value: 86.22749355597347 |
|
|
- type: euclidean_f1 |
|
|
value: 78.36863452005407 |
|
|
- type: euclidean_precision |
|
|
value: 76.49560117302053 |
|
|
- type: euclidean_recall |
|
|
value: 80.33569448721897 |
|
|
- type: manhattan_accuracy |
|
|
value: 89.08293553770326 |
|
|
- type: manhattan_ap |
|
|
value: 86.21913616084771 |
|
|
- type: manhattan_f1 |
|
|
value: 78.3907031479847 |
|
|
- type: manhattan_precision |
|
|
value: 75.0352013517319 |
|
|
- type: manhattan_recall |
|
|
value: 82.06036341238065 |
|
|
- type: max_accuracy |
|
|
value: 89.09069740365584 |
|
|
- type: max_ap |
|
|
value: 86.22750233655673 |
|
|
- type: max_f1 |
|
|
value: 78.3907031479847 |
|
|
license: apache-2.0 |
|
|
language: |
|
|
- en |
|
|
library_name: sentence-transformers |
|
|
pipeline_tag: feature-extraction |
|
|
--- |
|
|
|
|
|
<br><br> |
|
|
|
|
|
<p align="center"> |
|
|
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</p> |
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<p align="center"> |
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<b>The crispy sentence embedding family from <a href="https://mixedbread.ai"><b>mixedbread ai</b></a>.</b> |
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</p> |
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# mxbai-embed-large-v1 |
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This is our base sentence embedding model. It was trained using [AnglE](https://arxiv.org/abs/2309.12871) loss on our high-quality large scale data. It achieves SOTA performance on BERT-large scale. Find out more in our [blog post](https://mixedbread.ai/blog/mxbai-embed-large-v1). |
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## Quickstart |
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Here, we provide several ways to produce sentence embeddings. Please note that you have to provide the prompt `Represent this sentence for searching relevant passages:` for query if you want to use it for retrieval. Besides that you don't need any prompt. |
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### sentence-transformers |
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``` |
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python -m pip install -U sentence-transformers |
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``` |
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```python |
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from sentence_transformers import SentenceTransformer |
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from sentence_transformers.util import cos_sim |
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# 1. load model |
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model = SentenceTransformer("mixedbread-ai/mxbai-embed-large-v1") |
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# For retrieval you need to pass this prompt. |
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query = 'Represent this sentence for searching relevant passages: A man is eating a piece of bread' |
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docs = [ |
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query, |
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"A man is eating food.", |
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"A man is eating pasta.", |
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"The girl is carrying a baby.", |
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"A man is riding a horse.", |
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] |
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# 2. Encode |
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embeddings = model.encode(docs) |
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similarities = cos_sim(embeddings[0], embeddings[1:]) |
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print('similarities:', similarities) |
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``` |
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### Transformers |
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```python |
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from typing import Dict |
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import torch |
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import numpy as np |
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from transformers import AutoModel, AutoTokenizer |
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from sentence_transformers.util import cos_sim |
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# For retrieval you need to pass this prompt. Please find our more in our blog post. |
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def transform_query(query: str) -> str: |
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""" For retrieval, add the prompt for query (not for documents). |
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""" |
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return f'Represent this sentence for searching relevant passages: {query}' |
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# The model works really well with cls pooling (default) but also with mean poolin. |
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def pooling(outputs: torch.Tensor, inputs: Dict, strategy: str = 'cls') -> np.ndarray: |
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if strategy == 'cls': |
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outputs = outputs[:, 0] |
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elif strategy == 'mean': |
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outputs = torch.sum( |
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outputs * inputs["attention_mask"][:, :, None], dim=1) / torch.sum(inputs["attention_mask"]) |
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else: |
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raise NotImplementedError |
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return outputs.detach().cpu().numpy() |
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# 1. load model |
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model_id = 'mixedbread-ai/mxbai-embed-large-v1' |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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model = AutoModel.from_pretrained(model_id).cuda() |
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docs = [ |
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transform_query('A man is eating a piece of bread'), |
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"A man is eating food.", |
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"A man is eating pasta.", |
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"The girl is carrying a baby.", |
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"A man is riding a horse.", |
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] |
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# 2. encode |
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inputs = tokenizer(docs, padding=True, return_tensors='pt') |
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for k, v in inputs.items(): |
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inputs[k] = v.cuda() |
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outputs = model(**inputs).last_hidden_state |
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embeddings = pooling(outputs, inputs, 'cls') |
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similarities = cos_sim(embeddings[0], embeddings[1:]) |
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print('similarities:', similarities) |
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``` |
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### Transformers.js |
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If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@xenova/transformers) using: |
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```bash |
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npm i @xenova/transformers |
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``` |
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You can then use the model to compute embeddings like this: |
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```js |
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import { pipeline, cos_sim } from '@xenova/transformers'; |
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// Create a feature extraction pipeline |
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const extractor = await pipeline('feature-extraction', 'mixedbread-ai/mxbai-embed-large-v1', { |
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quantized: false, // Comment out this line to use the quantized version |
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}); |
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// Generate sentence embeddings |
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const docs = [ |
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'Represent this sentence for searching relevant passages: A man is eating a piece of bread', |
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'A man is eating food.', |
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'A man is eating pasta.', |
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'The girl is carrying a baby.', |
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'A man is riding a horse.', |
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] |
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const output = await extractor(docs, { pooling: 'cls' }); |
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// Compute similarity scores |
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const [source_embeddings, ...document_embeddings ] = output.tolist(); |
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const similarities = document_embeddings.map(x => cos_sim(source_embeddings, x)); |
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console.log(similarities); // [0.7919578577247139, 0.6369278664248345, 0.16512018371357193, 0.3620778366720027] |
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``` |
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### Using API |
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You’ll be able to use the models through our API as well. The API is coming soon and will have some exciting features. Stay tuned! |
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## Evaluation |
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As of March 2024, our model archives SOTA performance for Bert-large sized models on the [MTEB](https://huggingface.co/spaces/mteb/leaderboard). It ourperforms commercial models like OpenAIs text-embedding-3-large and matches the performance of model 20x it's size like the [echo-mistral-7b](https://huggingface.co/jspringer/echo-mistral-7b-instruct-lasttoken). Our model was trained with no overlap of the MTEB data, which indicates that our model generalizes well across several domains, tasks and text length. We know there are some limitations with this model, which will be fixed in v2. |
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| Model | Avg (56 datasets) | Classification (12 datasets) | Clustering (11 datasets) | PairClassification (3 datasets) | Reranking (4 datasets) | Retrieval (15 datasets) | STS (10 datasets) | Summarization (1 dataset) | |
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| --------------------------------------------------------------------------------------------- | ----------------- | ---------------------------- | ------------------------ | ------------------------------- | ---------------------- | ----------------------- | ----------------- | ------------------------- | |
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| **mxbai-embed-large-v1** | **64.68** | 75.64 | 46.71 | 87.2 | 60.11 | 54.39 | 85.00 | 32.71 | |
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| [bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5) | 64.23 | 75.97 | 46.08 | 87.12 | 60.03 | 54.29 | 83.11 | 31.61 | |
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| [mxbai-embed-2d-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-2d-large-v1) | 63.25 | 74.14 | 46.07 | 85.89 | 58.94 | 51.42 | 84.9 | 31.55 | |
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| [nomic-embed-text-v1](https://huggingface.co/nomic-ai/nomic-embed-text-v1) | 62.39 | 74.12 | 43.91 | 85.15 | 55.69 | 52.81 | 82.06 | 30.08 | |
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| [jina-embeddings-v2-base-en](https://huggingface.co/jinaai/jina-embeddings-v2-base-en) | 60.38 | 73.45 | 41.73 | 85.38 | 56.98 | 47.87 | 80.7 | 31.6 | |
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| *Proprietary Models* | | | | | | | | | |
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| [OpenAI text-embedding-3-large](https://openai.com/blog/new-embedding-models-and-api-updates) | 64.58 | 75.45 | 49.01 | 85.72 | 59.16 | 55.44 | 81.73 | 29.92 | |
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| [Cohere embed-english-v3.0](https://txt.cohere.com/introducing-embed-v3/) | 64.47 | 76.49 | 47.43 | 85.84 | 58.01 | 55.00 | 82.62 | 30.18 | |
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| [OpenAI text-embedding-ada-002](https://openai.com/blog/new-and-improved-embedding-model) | 60.99 | 70.93 | 45.90 | 84.89 | 56.32 | 49.25 | 80.97 | 30.80 | |
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Please find more information in our [blog post](https://mixedbread.ai/blog/mxbai-embed-large-v1). |
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## Community |
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Please join our [Discord Community](https://discord.gg/jDfMHzAVfU) and share your feedback and thoughts! We are here to help and also always happy to chat. |
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## License |
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Apache 2.0 |
