| --- |
| pipeline_tag: sentence-similarity |
| tags: |
| - sentence-transformers |
| - feature-extraction |
| - sentence-similarity |
| - transformers |
| - mteb |
|
|
| model-index: |
| - name: bge_micro |
| results: |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_counterfactual |
| name: MTEB AmazonCounterfactualClassification (en) |
| config: en |
| split: test |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
| metrics: |
| - type: accuracy |
| value: 66.26865671641792 |
| - type: ap |
| value: 28.174006539079688 |
| - type: f1 |
| value: 59.724963358211035 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_polarity |
| name: MTEB AmazonPolarityClassification |
| config: default |
| split: test |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
| metrics: |
| - type: accuracy |
| value: 75.3691 |
| - type: ap |
| value: 69.64182876373573 |
| - type: f1 |
| value: 75.2906345000088 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (en) |
| config: en |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 35.806 |
| - type: f1 |
| value: 35.506516495961904 |
| - task: |
| type: Retrieval |
| dataset: |
| type: arguana |
| name: MTEB ArguAna |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 27.24 |
| - type: map_at_10 |
| value: 42.832 |
| - type: map_at_100 |
| value: 43.797000000000004 |
| - type: map_at_1000 |
| value: 43.804 |
| - type: map_at_3 |
| value: 38.134 |
| - type: map_at_5 |
| value: 40.744 |
| - type: mrr_at_1 |
| value: 27.951999999999998 |
| - type: mrr_at_10 |
| value: 43.111 |
| - type: mrr_at_100 |
| value: 44.083 |
| - type: mrr_at_1000 |
| value: 44.09 |
| - type: mrr_at_3 |
| value: 38.431 |
| - type: mrr_at_5 |
| value: 41.019 |
| - type: ndcg_at_1 |
| value: 27.24 |
| - type: ndcg_at_10 |
| value: 51.513 |
| - type: ndcg_at_100 |
| value: 55.762 |
| - type: ndcg_at_1000 |
| value: 55.938 |
| - type: ndcg_at_3 |
| value: 41.743 |
| - type: ndcg_at_5 |
| value: 46.454 |
| - type: precision_at_1 |
| value: 27.24 |
| - type: precision_at_10 |
| value: 7.93 |
| - type: precision_at_100 |
| value: 0.9820000000000001 |
| - type: precision_at_1000 |
| value: 0.1 |
| - type: precision_at_3 |
| value: 17.402 |
| - type: precision_at_5 |
| value: 12.731 |
| - type: recall_at_1 |
| value: 27.24 |
| - type: recall_at_10 |
| value: 79.303 |
| - type: recall_at_100 |
| value: 98.151 |
| - type: recall_at_1000 |
| value: 99.502 |
| - type: recall_at_3 |
| value: 52.205 |
| - type: recall_at_5 |
| value: 63.656 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-p2p |
| name: MTEB ArxivClusteringP2P |
| config: default |
| split: test |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| metrics: |
| - type: v_measure |
| value: 44.59766397469585 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-s2s |
| name: MTEB ArxivClusteringS2S |
| config: default |
| split: test |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
| metrics: |
| - type: v_measure |
| value: 34.480143023109626 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/askubuntudupquestions-reranking |
| name: MTEB AskUbuntuDupQuestions |
| config: default |
| split: test |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
| metrics: |
| - type: map |
| value: 58.09326229984527 |
| - type: mrr |
| value: 72.18429846546191 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/biosses-sts |
| name: MTEB BIOSSES |
| config: default |
| split: test |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.47582391622187 |
| - type: cos_sim_spearman |
| value: 83.41635852964214 |
| - type: euclidean_pearson |
| value: 84.21969728559216 |
| - type: euclidean_spearman |
| value: 83.46575724558684 |
| - type: manhattan_pearson |
| value: 83.83107014910223 |
| - type: manhattan_spearman |
| value: 83.13321954800792 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/banking77 |
| name: MTEB Banking77Classification |
| config: default |
| split: test |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| metrics: |
| - type: accuracy |
| value: 80.58116883116882 |
| - type: f1 |
| value: 80.53335622619781 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-p2p |
| name: MTEB BiorxivClusteringP2P |
| config: default |
| split: test |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| metrics: |
| - type: v_measure |
| value: 37.13458676004344 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-s2s |
| name: MTEB BiorxivClusteringS2S |
| config: default |
| split: test |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
| metrics: |
| - type: v_measure |
| value: 29.720429607514898 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackAndroidRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 26.051000000000002 |
| - type: map_at_10 |
| value: 36.291000000000004 |
| - type: map_at_100 |
| value: 37.632 |
| - type: map_at_1000 |
| value: 37.772 |
| - type: map_at_3 |
| value: 33.288000000000004 |
| - type: map_at_5 |
| value: 35.035 |
| - type: mrr_at_1 |
| value: 33.333 |
| - type: mrr_at_10 |
| value: 42.642 |
| - type: mrr_at_100 |
| value: 43.401 |
| - type: mrr_at_1000 |
| value: 43.463 |
| - type: mrr_at_3 |
| value: 40.272000000000006 |
| - type: mrr_at_5 |
| value: 41.753 |
| - type: ndcg_at_1 |
| value: 33.333 |
| - type: ndcg_at_10 |
| value: 42.291000000000004 |
| - type: ndcg_at_100 |
| value: 47.602 |
| - type: ndcg_at_1000 |
| value: 50.109 |
| - type: ndcg_at_3 |
| value: 38.033 |
| - type: ndcg_at_5 |
| value: 40.052 |
| - type: precision_at_1 |
| value: 33.333 |
| - type: precision_at_10 |
| value: 8.254999999999999 |
| - type: precision_at_100 |
| value: 1.353 |
| - type: precision_at_1000 |
| value: 0.185 |
| - type: precision_at_3 |
| value: 18.884 |
| - type: precision_at_5 |
| value: 13.447999999999999 |
| - type: recall_at_1 |
| value: 26.051000000000002 |
| - type: recall_at_10 |
| value: 53.107000000000006 |
| - type: recall_at_100 |
| value: 76.22 |
| - type: recall_at_1000 |
| value: 92.92399999999999 |
| - type: recall_at_3 |
| value: 40.073 |
| - type: recall_at_5 |
| value: 46.327 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackEnglishRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 19.698999999999998 |
| - type: map_at_10 |
| value: 26.186 |
| - type: map_at_100 |
| value: 27.133000000000003 |
| - type: map_at_1000 |
| value: 27.256999999999998 |
| - type: map_at_3 |
| value: 24.264 |
| - type: map_at_5 |
| value: 25.307000000000002 |
| - type: mrr_at_1 |
| value: 24.712999999999997 |
| - type: mrr_at_10 |
| value: 30.703999999999997 |
| - type: mrr_at_100 |
| value: 31.445 |
| - type: mrr_at_1000 |
| value: 31.517 |
| - type: mrr_at_3 |
| value: 28.992 |
| - type: mrr_at_5 |
| value: 29.963 |
| - type: ndcg_at_1 |
| value: 24.712999999999997 |
| - type: ndcg_at_10 |
| value: 30.198000000000004 |
| - type: ndcg_at_100 |
| value: 34.412 |
| - type: ndcg_at_1000 |
| value: 37.174 |
| - type: ndcg_at_3 |
| value: 27.148 |
| - type: ndcg_at_5 |
| value: 28.464 |
| - type: precision_at_1 |
| value: 24.712999999999997 |
| - type: precision_at_10 |
| value: 5.489999999999999 |
| - type: precision_at_100 |
| value: 0.955 |
| - type: precision_at_1000 |
| value: 0.14400000000000002 |
| - type: precision_at_3 |
| value: 12.803 |
| - type: precision_at_5 |
| value: 8.981 |
| - type: recall_at_1 |
| value: 19.698999999999998 |
| - type: recall_at_10 |
| value: 37.595 |
| - type: recall_at_100 |
| value: 55.962 |
| - type: recall_at_1000 |
| value: 74.836 |
| - type: recall_at_3 |
| value: 28.538999999999998 |
| - type: recall_at_5 |
| value: 32.279 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackGamingRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 34.224 |
| - type: map_at_10 |
| value: 44.867000000000004 |
| - type: map_at_100 |
| value: 45.944 |
| - type: map_at_1000 |
| value: 46.013999999999996 |
| - type: map_at_3 |
| value: 42.009 |
| - type: map_at_5 |
| value: 43.684 |
| - type: mrr_at_1 |
| value: 39.436 |
| - type: mrr_at_10 |
| value: 48.301 |
| - type: mrr_at_100 |
| value: 49.055 |
| - type: mrr_at_1000 |
| value: 49.099 |
| - type: mrr_at_3 |
| value: 45.956 |
| - type: mrr_at_5 |
| value: 47.445 |
| - type: ndcg_at_1 |
| value: 39.436 |
| - type: ndcg_at_10 |
| value: 50.214000000000006 |
| - type: ndcg_at_100 |
| value: 54.63 |
| - type: ndcg_at_1000 |
| value: 56.165 |
| - type: ndcg_at_3 |
| value: 45.272 |
| - type: ndcg_at_5 |
| value: 47.826 |
| - type: precision_at_1 |
| value: 39.436 |
| - type: precision_at_10 |
| value: 8.037999999999998 |
| - type: precision_at_100 |
| value: 1.118 |
| - type: precision_at_1000 |
| value: 0.13 |
| - type: precision_at_3 |
| value: 20.125 |
| - type: precision_at_5 |
| value: 13.918 |
| - type: recall_at_1 |
| value: 34.224 |
| - type: recall_at_10 |
| value: 62.690999999999995 |
| - type: recall_at_100 |
| value: 81.951 |
| - type: recall_at_1000 |
| value: 92.93299999999999 |
| - type: recall_at_3 |
| value: 49.299 |
| - type: recall_at_5 |
| value: 55.533 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackGisRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 21.375 |
| - type: map_at_10 |
| value: 28.366000000000003 |
| - type: map_at_100 |
| value: 29.363 |
| - type: map_at_1000 |
| value: 29.458000000000002 |
| - type: map_at_3 |
| value: 26.247 |
| - type: map_at_5 |
| value: 27.439000000000004 |
| - type: mrr_at_1 |
| value: 22.938 |
| - type: mrr_at_10 |
| value: 30.072 |
| - type: mrr_at_100 |
| value: 30.993 |
| - type: mrr_at_1000 |
| value: 31.070999999999998 |
| - type: mrr_at_3 |
| value: 28.004 |
| - type: mrr_at_5 |
| value: 29.179 |
| - type: ndcg_at_1 |
| value: 22.938 |
| - type: ndcg_at_10 |
| value: 32.516 |
| - type: ndcg_at_100 |
| value: 37.641999999999996 |
| - type: ndcg_at_1000 |
| value: 40.150999999999996 |
| - type: ndcg_at_3 |
| value: 28.341 |
| - type: ndcg_at_5 |
| value: 30.394 |
| - type: precision_at_1 |
| value: 22.938 |
| - type: precision_at_10 |
| value: 5.028 |
| - type: precision_at_100 |
| value: 0.8 |
| - type: precision_at_1000 |
| value: 0.105 |
| - type: precision_at_3 |
| value: 12.052999999999999 |
| - type: precision_at_5 |
| value: 8.497 |
| - type: recall_at_1 |
| value: 21.375 |
| - type: recall_at_10 |
| value: 43.682 |
| - type: recall_at_100 |
| value: 67.619 |
| - type: recall_at_1000 |
| value: 86.64699999999999 |
| - type: recall_at_3 |
| value: 32.478 |
| - type: recall_at_5 |
| value: 37.347 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackMathematicaRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 14.95 |
| - type: map_at_10 |
| value: 21.417 |
| - type: map_at_100 |
| value: 22.525000000000002 |
| - type: map_at_1000 |
| value: 22.665 |
| - type: map_at_3 |
| value: 18.684 |
| - type: map_at_5 |
| value: 20.275000000000002 |
| - type: mrr_at_1 |
| value: 18.159 |
| - type: mrr_at_10 |
| value: 25.373 |
| - type: mrr_at_100 |
| value: 26.348 |
| - type: mrr_at_1000 |
| value: 26.432 |
| - type: mrr_at_3 |
| value: 22.698999999999998 |
| - type: mrr_at_5 |
| value: 24.254 |
| - type: ndcg_at_1 |
| value: 18.159 |
| - type: ndcg_at_10 |
| value: 26.043 |
| - type: ndcg_at_100 |
| value: 31.491999999999997 |
| - type: ndcg_at_1000 |
| value: 34.818 |
| - type: ndcg_at_3 |
| value: 21.05 |
| - type: ndcg_at_5 |
| value: 23.580000000000002 |
| - type: precision_at_1 |
| value: 18.159 |
| - type: precision_at_10 |
| value: 4.938 |
| - type: precision_at_100 |
| value: 0.872 |
| - type: precision_at_1000 |
| value: 0.129 |
| - type: precision_at_3 |
| value: 9.908999999999999 |
| - type: precision_at_5 |
| value: 7.611999999999999 |
| - type: recall_at_1 |
| value: 14.95 |
| - type: recall_at_10 |
| value: 36.285000000000004 |
| - type: recall_at_100 |
| value: 60.431999999999995 |
| - type: recall_at_1000 |
| value: 84.208 |
| - type: recall_at_3 |
| value: 23.006 |
| - type: recall_at_5 |
| value: 29.304999999999996 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackPhysicsRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 23.580000000000002 |
| - type: map_at_10 |
| value: 32.906 |
| - type: map_at_100 |
| value: 34.222 |
| - type: map_at_1000 |
| value: 34.346 |
| - type: map_at_3 |
| value: 29.891000000000002 |
| - type: map_at_5 |
| value: 31.679000000000002 |
| - type: mrr_at_1 |
| value: 28.778 |
| - type: mrr_at_10 |
| value: 37.783 |
| - type: mrr_at_100 |
| value: 38.746 |
| - type: mrr_at_1000 |
| value: 38.804 |
| - type: mrr_at_3 |
| value: 35.098 |
| - type: mrr_at_5 |
| value: 36.739 |
| - type: ndcg_at_1 |
| value: 28.778 |
| - type: ndcg_at_10 |
| value: 38.484 |
| - type: ndcg_at_100 |
| value: 44.322 |
| - type: ndcg_at_1000 |
| value: 46.772000000000006 |
| - type: ndcg_at_3 |
| value: 33.586 |
| - type: ndcg_at_5 |
| value: 36.098 |
| - type: precision_at_1 |
| value: 28.778 |
| - type: precision_at_10 |
| value: 7.151000000000001 |
| - type: precision_at_100 |
| value: 1.185 |
| - type: precision_at_1000 |
| value: 0.158 |
| - type: precision_at_3 |
| value: 16.105 |
| - type: precision_at_5 |
| value: 11.704 |
| - type: recall_at_1 |
| value: 23.580000000000002 |
| - type: recall_at_10 |
| value: 50.151999999999994 |
| - type: recall_at_100 |
| value: 75.114 |
| - type: recall_at_1000 |
| value: 91.467 |
| - type: recall_at_3 |
| value: 36.552 |
| - type: recall_at_5 |
| value: 43.014 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackProgrammersRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 20.669999999999998 |
| - type: map_at_10 |
| value: 28.687 |
| - type: map_at_100 |
| value: 30.061 |
| - type: map_at_1000 |
| value: 30.197000000000003 |
| - type: map_at_3 |
| value: 26.134 |
| - type: map_at_5 |
| value: 27.508 |
| - type: mrr_at_1 |
| value: 26.256 |
| - type: mrr_at_10 |
| value: 34.105999999999995 |
| - type: mrr_at_100 |
| value: 35.137 |
| - type: mrr_at_1000 |
| value: 35.214 |
| - type: mrr_at_3 |
| value: 31.791999999999998 |
| - type: mrr_at_5 |
| value: 33.145 |
| - type: ndcg_at_1 |
| value: 26.256 |
| - type: ndcg_at_10 |
| value: 33.68 |
| - type: ndcg_at_100 |
| value: 39.7 |
| - type: ndcg_at_1000 |
| value: 42.625 |
| - type: ndcg_at_3 |
| value: 29.457 |
| - type: ndcg_at_5 |
| value: 31.355 |
| - type: precision_at_1 |
| value: 26.256 |
| - type: precision_at_10 |
| value: 6.2330000000000005 |
| - type: precision_at_100 |
| value: 1.08 |
| - type: precision_at_1000 |
| value: 0.149 |
| - type: precision_at_3 |
| value: 14.193 |
| - type: precision_at_5 |
| value: 10.113999999999999 |
| - type: recall_at_1 |
| value: 20.669999999999998 |
| - type: recall_at_10 |
| value: 43.254999999999995 |
| - type: recall_at_100 |
| value: 69.118 |
| - type: recall_at_1000 |
| value: 89.408 |
| - type: recall_at_3 |
| value: 31.135 |
| - type: recall_at_5 |
| value: 36.574 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 21.488833333333336 |
| - type: map_at_10 |
| value: 29.025416666666665 |
| - type: map_at_100 |
| value: 30.141249999999992 |
| - type: map_at_1000 |
| value: 30.264083333333335 |
| - type: map_at_3 |
| value: 26.599333333333337 |
| - type: map_at_5 |
| value: 28.004666666666665 |
| - type: mrr_at_1 |
| value: 25.515 |
| - type: mrr_at_10 |
| value: 32.8235 |
| - type: mrr_at_100 |
| value: 33.69958333333333 |
| - type: mrr_at_1000 |
| value: 33.77191666666668 |
| - type: mrr_at_3 |
| value: 30.581000000000003 |
| - type: mrr_at_5 |
| value: 31.919666666666668 |
| - type: ndcg_at_1 |
| value: 25.515 |
| - type: ndcg_at_10 |
| value: 33.64241666666666 |
| - type: ndcg_at_100 |
| value: 38.75816666666667 |
| - type: ndcg_at_1000 |
| value: 41.472166666666666 |
| - type: ndcg_at_3 |
| value: 29.435083333333335 |
| - type: ndcg_at_5 |
| value: 31.519083333333338 |
| - type: precision_at_1 |
| value: 25.515 |
| - type: precision_at_10 |
| value: 5.89725 |
| - type: precision_at_100 |
| value: 0.9918333333333335 |
| - type: precision_at_1000 |
| value: 0.14075 |
| - type: precision_at_3 |
| value: 13.504000000000001 |
| - type: precision_at_5 |
| value: 9.6885 |
| - type: recall_at_1 |
| value: 21.488833333333336 |
| - type: recall_at_10 |
| value: 43.60808333333333 |
| - type: recall_at_100 |
| value: 66.5045 |
| - type: recall_at_1000 |
| value: 85.70024999999998 |
| - type: recall_at_3 |
| value: 31.922166666666662 |
| - type: recall_at_5 |
| value: 37.29758333333334 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackStatsRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 20.781 |
| - type: map_at_10 |
| value: 27.173000000000002 |
| - type: map_at_100 |
| value: 27.967 |
| - type: map_at_1000 |
| value: 28.061999999999998 |
| - type: map_at_3 |
| value: 24.973 |
| - type: map_at_5 |
| value: 26.279999999999998 |
| - type: mrr_at_1 |
| value: 23.773 |
| - type: mrr_at_10 |
| value: 29.849999999999998 |
| - type: mrr_at_100 |
| value: 30.595 |
| - type: mrr_at_1000 |
| value: 30.669 |
| - type: mrr_at_3 |
| value: 27.761000000000003 |
| - type: mrr_at_5 |
| value: 29.003 |
| - type: ndcg_at_1 |
| value: 23.773 |
| - type: ndcg_at_10 |
| value: 31.033 |
| - type: ndcg_at_100 |
| value: 35.174 |
| - type: ndcg_at_1000 |
| value: 37.72 |
| - type: ndcg_at_3 |
| value: 26.927 |
| - type: ndcg_at_5 |
| value: 29.047 |
| - type: precision_at_1 |
| value: 23.773 |
| - type: precision_at_10 |
| value: 4.8469999999999995 |
| - type: precision_at_100 |
| value: 0.75 |
| - type: precision_at_1000 |
| value: 0.104 |
| - type: precision_at_3 |
| value: 11.452 |
| - type: precision_at_5 |
| value: 8.129 |
| - type: recall_at_1 |
| value: 20.781 |
| - type: recall_at_10 |
| value: 40.463 |
| - type: recall_at_100 |
| value: 59.483 |
| - type: recall_at_1000 |
| value: 78.396 |
| - type: recall_at_3 |
| value: 29.241 |
| - type: recall_at_5 |
| value: 34.544000000000004 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackTexRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 15.074000000000002 |
| - type: map_at_10 |
| value: 20.757 |
| - type: map_at_100 |
| value: 21.72 |
| - type: map_at_1000 |
| value: 21.844 |
| - type: map_at_3 |
| value: 18.929000000000002 |
| - type: map_at_5 |
| value: 19.894000000000002 |
| - type: mrr_at_1 |
| value: 18.307000000000002 |
| - type: mrr_at_10 |
| value: 24.215 |
| - type: mrr_at_100 |
| value: 25.083 |
| - type: mrr_at_1000 |
| value: 25.168000000000003 |
| - type: mrr_at_3 |
| value: 22.316 |
| - type: mrr_at_5 |
| value: 23.36 |
| - type: ndcg_at_1 |
| value: 18.307000000000002 |
| - type: ndcg_at_10 |
| value: 24.651999999999997 |
| - type: ndcg_at_100 |
| value: 29.296 |
| - type: ndcg_at_1000 |
| value: 32.538 |
| - type: ndcg_at_3 |
| value: 21.243000000000002 |
| - type: ndcg_at_5 |
| value: 22.727 |
| - type: precision_at_1 |
| value: 18.307000000000002 |
| - type: precision_at_10 |
| value: 4.446 |
| - type: precision_at_100 |
| value: 0.792 |
| - type: precision_at_1000 |
| value: 0.124 |
| - type: precision_at_3 |
| value: 9.945 |
| - type: precision_at_5 |
| value: 7.123 |
| - type: recall_at_1 |
| value: 15.074000000000002 |
| - type: recall_at_10 |
| value: 33.031 |
| - type: recall_at_100 |
| value: 53.954 |
| - type: recall_at_1000 |
| value: 77.631 |
| - type: recall_at_3 |
| value: 23.253 |
| - type: recall_at_5 |
| value: 27.218999999999998 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackUnixRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 21.04 |
| - type: map_at_10 |
| value: 28.226000000000003 |
| - type: map_at_100 |
| value: 29.337999999999997 |
| - type: map_at_1000 |
| value: 29.448999999999998 |
| - type: map_at_3 |
| value: 25.759 |
| - type: map_at_5 |
| value: 27.226 |
| - type: mrr_at_1 |
| value: 24.067 |
| - type: mrr_at_10 |
| value: 31.646 |
| - type: mrr_at_100 |
| value: 32.592999999999996 |
| - type: mrr_at_1000 |
| value: 32.668 |
| - type: mrr_at_3 |
| value: 29.26 |
| - type: mrr_at_5 |
| value: 30.725 |
| - type: ndcg_at_1 |
| value: 24.067 |
| - type: ndcg_at_10 |
| value: 32.789 |
| - type: ndcg_at_100 |
| value: 38.253 |
| - type: ndcg_at_1000 |
| value: 40.961 |
| - type: ndcg_at_3 |
| value: 28.189999999999998 |
| - type: ndcg_at_5 |
| value: 30.557000000000002 |
| - type: precision_at_1 |
| value: 24.067 |
| - type: precision_at_10 |
| value: 5.532 |
| - type: precision_at_100 |
| value: 0.928 |
| - type: precision_at_1000 |
| value: 0.128 |
| - type: precision_at_3 |
| value: 12.5 |
| - type: precision_at_5 |
| value: 9.16 |
| - type: recall_at_1 |
| value: 21.04 |
| - type: recall_at_10 |
| value: 43.167 |
| - type: recall_at_100 |
| value: 67.569 |
| - type: recall_at_1000 |
| value: 86.817 |
| - type: recall_at_3 |
| value: 31.178 |
| - type: recall_at_5 |
| value: 36.730000000000004 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackWebmastersRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 21.439 |
| - type: map_at_10 |
| value: 28.531000000000002 |
| - type: map_at_100 |
| value: 29.953999999999997 |
| - type: map_at_1000 |
| value: 30.171 |
| - type: map_at_3 |
| value: 26.546999999999997 |
| - type: map_at_5 |
| value: 27.71 |
| - type: mrr_at_1 |
| value: 26.087 |
| - type: mrr_at_10 |
| value: 32.635 |
| - type: mrr_at_100 |
| value: 33.629999999999995 |
| - type: mrr_at_1000 |
| value: 33.71 |
| - type: mrr_at_3 |
| value: 30.731 |
| - type: mrr_at_5 |
| value: 31.807999999999996 |
| - type: ndcg_at_1 |
| value: 26.087 |
| - type: ndcg_at_10 |
| value: 32.975 |
| - type: ndcg_at_100 |
| value: 38.853 |
| - type: ndcg_at_1000 |
| value: 42.158 |
| - type: ndcg_at_3 |
| value: 29.894 |
| - type: ndcg_at_5 |
| value: 31.397000000000002 |
| - type: precision_at_1 |
| value: 26.087 |
| - type: precision_at_10 |
| value: 6.2059999999999995 |
| - type: precision_at_100 |
| value: 1.298 |
| - type: precision_at_1000 |
| value: 0.22200000000000003 |
| - type: precision_at_3 |
| value: 14.097000000000001 |
| - type: precision_at_5 |
| value: 9.959999999999999 |
| - type: recall_at_1 |
| value: 21.439 |
| - type: recall_at_10 |
| value: 40.519 |
| - type: recall_at_100 |
| value: 68.073 |
| - type: recall_at_1000 |
| value: 89.513 |
| - type: recall_at_3 |
| value: 31.513 |
| - type: recall_at_5 |
| value: 35.702 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackWordpressRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 18.983 |
| - type: map_at_10 |
| value: 24.898 |
| - type: map_at_100 |
| value: 25.836 |
| - type: map_at_1000 |
| value: 25.934 |
| - type: map_at_3 |
| value: 22.467000000000002 |
| - type: map_at_5 |
| value: 24.019 |
| - type: mrr_at_1 |
| value: 20.333000000000002 |
| - type: mrr_at_10 |
| value: 26.555 |
| - type: mrr_at_100 |
| value: 27.369 |
| - type: mrr_at_1000 |
| value: 27.448 |
| - type: mrr_at_3 |
| value: 24.091 |
| - type: mrr_at_5 |
| value: 25.662000000000003 |
| - type: ndcg_at_1 |
| value: 20.333000000000002 |
| - type: ndcg_at_10 |
| value: 28.834 |
| - type: ndcg_at_100 |
| value: 33.722 |
| - type: ndcg_at_1000 |
| value: 36.475 |
| - type: ndcg_at_3 |
| value: 24.08 |
| - type: ndcg_at_5 |
| value: 26.732 |
| - type: precision_at_1 |
| value: 20.333000000000002 |
| - type: precision_at_10 |
| value: 4.603 |
| - type: precision_at_100 |
| value: 0.771 |
| - type: precision_at_1000 |
| value: 0.11100000000000002 |
| - type: precision_at_3 |
| value: 9.982000000000001 |
| - type: precision_at_5 |
| value: 7.6160000000000005 |
| - type: recall_at_1 |
| value: 18.983 |
| - type: recall_at_10 |
| value: 39.35 |
| - type: recall_at_100 |
| value: 62.559 |
| - type: recall_at_1000 |
| value: 83.623 |
| - type: recall_at_3 |
| value: 26.799 |
| - type: recall_at_5 |
| value: 32.997 |
| - task: |
| type: Retrieval |
| dataset: |
| type: climate-fever |
| name: MTEB ClimateFEVER |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 10.621 |
| - type: map_at_10 |
| value: 17.298 |
| - type: map_at_100 |
| value: 18.983 |
| - type: map_at_1000 |
| value: 19.182 |
| - type: map_at_3 |
| value: 14.552999999999999 |
| - type: map_at_5 |
| value: 15.912 |
| - type: mrr_at_1 |
| value: 23.453 |
| - type: mrr_at_10 |
| value: 33.932 |
| - type: mrr_at_100 |
| value: 34.891 |
| - type: mrr_at_1000 |
| value: 34.943000000000005 |
| - type: mrr_at_3 |
| value: 30.770999999999997 |
| - type: mrr_at_5 |
| value: 32.556000000000004 |
| - type: ndcg_at_1 |
| value: 23.453 |
| - type: ndcg_at_10 |
| value: 24.771 |
| - type: ndcg_at_100 |
| value: 31.738 |
| - type: ndcg_at_1000 |
| value: 35.419 |
| - type: ndcg_at_3 |
| value: 20.22 |
| - type: ndcg_at_5 |
| value: 21.698999999999998 |
| - type: precision_at_1 |
| value: 23.453 |
| - type: precision_at_10 |
| value: 7.785 |
| - type: precision_at_100 |
| value: 1.5270000000000001 |
| - type: precision_at_1000 |
| value: 0.22 |
| - type: precision_at_3 |
| value: 14.962 |
| - type: precision_at_5 |
| value: 11.401 |
| - type: recall_at_1 |
| value: 10.621 |
| - type: recall_at_10 |
| value: 29.726000000000003 |
| - type: recall_at_100 |
| value: 53.996 |
| - type: recall_at_1000 |
| value: 74.878 |
| - type: recall_at_3 |
| value: 18.572 |
| - type: recall_at_5 |
| value: 22.994999999999997 |
| - task: |
| type: Retrieval |
| dataset: |
| type: dbpedia-entity |
| name: MTEB DBPedia |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 6.819 |
| - type: map_at_10 |
| value: 14.188 |
| - type: map_at_100 |
| value: 19.627 |
| - type: map_at_1000 |
| value: 20.757 |
| - type: map_at_3 |
| value: 10.352 |
| - type: map_at_5 |
| value: 12.096 |
| - type: mrr_at_1 |
| value: 54.25 |
| - type: mrr_at_10 |
| value: 63.798 |
| - type: mrr_at_100 |
| value: 64.25 |
| - type: mrr_at_1000 |
| value: 64.268 |
| - type: mrr_at_3 |
| value: 61.667 |
| - type: mrr_at_5 |
| value: 63.153999999999996 |
| - type: ndcg_at_1 |
| value: 39.5 |
| - type: ndcg_at_10 |
| value: 31.064999999999998 |
| - type: ndcg_at_100 |
| value: 34.701 |
| - type: ndcg_at_1000 |
| value: 41.687000000000005 |
| - type: ndcg_at_3 |
| value: 34.455999999999996 |
| - type: ndcg_at_5 |
| value: 32.919 |
| - type: precision_at_1 |
| value: 54.25 |
| - type: precision_at_10 |
| value: 25.4 |
| - type: precision_at_100 |
| value: 7.79 |
| - type: precision_at_1000 |
| value: 1.577 |
| - type: precision_at_3 |
| value: 39.333 |
| - type: precision_at_5 |
| value: 33.6 |
| - type: recall_at_1 |
| value: 6.819 |
| - type: recall_at_10 |
| value: 19.134 |
| - type: recall_at_100 |
| value: 41.191 |
| - type: recall_at_1000 |
| value: 64.699 |
| - type: recall_at_3 |
| value: 11.637 |
| - type: recall_at_5 |
| value: 14.807 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/emotion |
| name: MTEB EmotionClassification |
| config: default |
| split: test |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
| metrics: |
| - type: accuracy |
| value: 42.474999999999994 |
| - type: f1 |
| value: 37.79154895614037 |
| - task: |
| type: Retrieval |
| dataset: |
| type: fever |
| name: MTEB FEVER |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 53.187 |
| - type: map_at_10 |
| value: 64.031 |
| - type: map_at_100 |
| value: 64.507 |
| - type: map_at_1000 |
| value: 64.526 |
| - type: map_at_3 |
| value: 61.926 |
| - type: map_at_5 |
| value: 63.278999999999996 |
| - type: mrr_at_1 |
| value: 57.396 |
| - type: mrr_at_10 |
| value: 68.296 |
| - type: mrr_at_100 |
| value: 68.679 |
| - type: mrr_at_1000 |
| value: 68.688 |
| - type: mrr_at_3 |
| value: 66.289 |
| - type: mrr_at_5 |
| value: 67.593 |
| - type: ndcg_at_1 |
| value: 57.396 |
| - type: ndcg_at_10 |
| value: 69.64 |
| - type: ndcg_at_100 |
| value: 71.75399999999999 |
| - type: ndcg_at_1000 |
| value: 72.179 |
| - type: ndcg_at_3 |
| value: 65.66199999999999 |
| - type: ndcg_at_5 |
| value: 67.932 |
| - type: precision_at_1 |
| value: 57.396 |
| - type: precision_at_10 |
| value: 9.073 |
| - type: precision_at_100 |
| value: 1.024 |
| - type: precision_at_1000 |
| value: 0.107 |
| - type: precision_at_3 |
| value: 26.133 |
| - type: precision_at_5 |
| value: 16.943 |
| - type: recall_at_1 |
| value: 53.187 |
| - type: recall_at_10 |
| value: 82.839 |
| - type: recall_at_100 |
| value: 92.231 |
| - type: recall_at_1000 |
| value: 95.249 |
| - type: recall_at_3 |
| value: 72.077 |
| - type: recall_at_5 |
| value: 77.667 |
| - task: |
| type: Retrieval |
| dataset: |
| type: fiqa |
| name: MTEB FiQA2018 |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 10.957 |
| - type: map_at_10 |
| value: 18.427 |
| - type: map_at_100 |
| value: 19.885 |
| - type: map_at_1000 |
| value: 20.088 |
| - type: map_at_3 |
| value: 15.709000000000001 |
| - type: map_at_5 |
| value: 17.153 |
| - type: mrr_at_1 |
| value: 22.377 |
| - type: mrr_at_10 |
| value: 30.076999999999998 |
| - type: mrr_at_100 |
| value: 31.233 |
| - type: mrr_at_1000 |
| value: 31.311 |
| - type: mrr_at_3 |
| value: 27.521 |
| - type: mrr_at_5 |
| value: 29.025000000000002 |
| - type: ndcg_at_1 |
| value: 22.377 |
| - type: ndcg_at_10 |
| value: 24.367 |
| - type: ndcg_at_100 |
| value: 31.04 |
| - type: ndcg_at_1000 |
| value: 35.106 |
| - type: ndcg_at_3 |
| value: 21.051000000000002 |
| - type: ndcg_at_5 |
| value: 22.231 |
| - type: precision_at_1 |
| value: 22.377 |
| - type: precision_at_10 |
| value: 7.005999999999999 |
| - type: precision_at_100 |
| value: 1.3599999999999999 |
| - type: precision_at_1000 |
| value: 0.208 |
| - type: precision_at_3 |
| value: 13.991999999999999 |
| - type: precision_at_5 |
| value: 10.833 |
| - type: recall_at_1 |
| value: 10.957 |
| - type: recall_at_10 |
| value: 30.274 |
| - type: recall_at_100 |
| value: 55.982 |
| - type: recall_at_1000 |
| value: 80.757 |
| - type: recall_at_3 |
| value: 19.55 |
| - type: recall_at_5 |
| value: 24.105999999999998 |
| - task: |
| type: Retrieval |
| dataset: |
| type: hotpotqa |
| name: MTEB HotpotQA |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 29.526999999999997 |
| - type: map_at_10 |
| value: 40.714 |
| - type: map_at_100 |
| value: 41.655 |
| - type: map_at_1000 |
| value: 41.744 |
| - type: map_at_3 |
| value: 38.171 |
| - type: map_at_5 |
| value: 39.646 |
| - type: mrr_at_1 |
| value: 59.055 |
| - type: mrr_at_10 |
| value: 66.411 |
| - type: mrr_at_100 |
| value: 66.85900000000001 |
| - type: mrr_at_1000 |
| value: 66.88300000000001 |
| - type: mrr_at_3 |
| value: 64.846 |
| - type: mrr_at_5 |
| value: 65.824 |
| - type: ndcg_at_1 |
| value: 59.055 |
| - type: ndcg_at_10 |
| value: 49.732 |
| - type: ndcg_at_100 |
| value: 53.441 |
| - type: ndcg_at_1000 |
| value: 55.354000000000006 |
| - type: ndcg_at_3 |
| value: 45.551 |
| - type: ndcg_at_5 |
| value: 47.719 |
| - type: precision_at_1 |
| value: 59.055 |
| - type: precision_at_10 |
| value: 10.366 |
| - type: precision_at_100 |
| value: 1.328 |
| - type: precision_at_1000 |
| value: 0.158 |
| - type: precision_at_3 |
| value: 28.322999999999997 |
| - type: precision_at_5 |
| value: 18.709 |
| - type: recall_at_1 |
| value: 29.526999999999997 |
| - type: recall_at_10 |
| value: 51.83 |
| - type: recall_at_100 |
| value: 66.42099999999999 |
| - type: recall_at_1000 |
| value: 79.176 |
| - type: recall_at_3 |
| value: 42.485 |
| - type: recall_at_5 |
| value: 46.772000000000006 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/imdb |
| name: MTEB ImdbClassification |
| config: default |
| split: test |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
| metrics: |
| - type: accuracy |
| value: 70.69959999999999 |
| - type: ap |
| value: 64.95539314492567 |
| - type: f1 |
| value: 70.5554935943308 |
| - task: |
| type: Retrieval |
| dataset: |
| type: msmarco |
| name: MTEB MSMARCO |
| config: default |
| split: dev |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 13.153 |
| - type: map_at_10 |
| value: 22.277 |
| - type: map_at_100 |
| value: 23.462 |
| - type: map_at_1000 |
| value: 23.546 |
| - type: map_at_3 |
| value: 19.026 |
| - type: map_at_5 |
| value: 20.825 |
| - type: mrr_at_1 |
| value: 13.539000000000001 |
| - type: mrr_at_10 |
| value: 22.753 |
| - type: mrr_at_100 |
| value: 23.906 |
| - type: mrr_at_1000 |
| value: 23.982999999999997 |
| - type: mrr_at_3 |
| value: 19.484 |
| - type: mrr_at_5 |
| value: 21.306 |
| - type: ndcg_at_1 |
| value: 13.553 |
| - type: ndcg_at_10 |
| value: 27.848 |
| - type: ndcg_at_100 |
| value: 33.900999999999996 |
| - type: ndcg_at_1000 |
| value: 36.155 |
| - type: ndcg_at_3 |
| value: 21.116 |
| - type: ndcg_at_5 |
| value: 24.349999999999998 |
| - type: precision_at_1 |
| value: 13.553 |
| - type: precision_at_10 |
| value: 4.695 |
| - type: precision_at_100 |
| value: 0.7779999999999999 |
| - type: precision_at_1000 |
| value: 0.097 |
| - type: precision_at_3 |
| value: 9.207 |
| - type: precision_at_5 |
| value: 7.155 |
| - type: recall_at_1 |
| value: 13.153 |
| - type: recall_at_10 |
| value: 45.205 |
| - type: recall_at_100 |
| value: 73.978 |
| - type: recall_at_1000 |
| value: 91.541 |
| - type: recall_at_3 |
| value: 26.735 |
| - type: recall_at_5 |
| value: 34.493 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_domain |
| name: MTEB MTOPDomainClassification (en) |
| config: en |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 90.2530779753762 |
| - type: f1 |
| value: 89.59402328284126 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_intent |
| name: MTEB MTOPIntentClassification (en) |
| config: en |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
| - type: accuracy |
| value: 67.95029639762883 |
| - type: f1 |
| value: 48.99988836758662 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (en) |
| config: en |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
| - type: accuracy |
| value: 67.77740416946874 |
| - type: f1 |
| value: 66.21341120969817 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (en) |
| config: en |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 73.03631472763955 |
| - type: f1 |
| value: 72.5779336237941 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-p2p |
| name: MTEB MedrxivClusteringP2P |
| config: default |
| split: test |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
| metrics: |
| - type: v_measure |
| value: 31.98182669158824 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-s2s |
| name: MTEB MedrxivClusteringS2S |
| config: default |
| split: test |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
| metrics: |
| - type: v_measure |
| value: 29.259462874407582 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/mind_small |
| name: MTEB MindSmallReranking |
| config: default |
| split: test |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
| metrics: |
| - type: map |
| value: 31.29342377286548 |
| - type: mrr |
| value: 32.32805799117226 |
| - task: |
| type: Retrieval |
| dataset: |
| type: nfcorpus |
| name: MTEB NFCorpus |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 4.692 |
| - type: map_at_10 |
| value: 10.559000000000001 |
| - type: map_at_100 |
| value: 13.665 |
| - type: map_at_1000 |
| value: 15.082 |
| - type: map_at_3 |
| value: 7.68 |
| - type: map_at_5 |
| value: 8.844000000000001 |
| - type: mrr_at_1 |
| value: 38.7 |
| - type: mrr_at_10 |
| value: 47.864000000000004 |
| - type: mrr_at_100 |
| value: 48.583999999999996 |
| - type: mrr_at_1000 |
| value: 48.636 |
| - type: mrr_at_3 |
| value: 45.975 |
| - type: mrr_at_5 |
| value: 47.074 |
| - type: ndcg_at_1 |
| value: 36.378 |
| - type: ndcg_at_10 |
| value: 30.038999999999998 |
| - type: ndcg_at_100 |
| value: 28.226000000000003 |
| - type: ndcg_at_1000 |
| value: 36.958 |
| - type: ndcg_at_3 |
| value: 33.469 |
| - type: ndcg_at_5 |
| value: 32.096999999999994 |
| - type: precision_at_1 |
| value: 38.080000000000005 |
| - type: precision_at_10 |
| value: 22.941 |
| - type: precision_at_100 |
| value: 7.632 |
| - type: precision_at_1000 |
| value: 2.0420000000000003 |
| - type: precision_at_3 |
| value: 31.579 |
| - type: precision_at_5 |
| value: 28.235 |
| - type: recall_at_1 |
| value: 4.692 |
| - type: recall_at_10 |
| value: 14.496 |
| - type: recall_at_100 |
| value: 29.69 |
| - type: recall_at_1000 |
| value: 61.229 |
| - type: recall_at_3 |
| value: 8.871 |
| - type: recall_at_5 |
| value: 10.825999999999999 |
| - task: |
| type: Retrieval |
| dataset: |
| type: nq |
| name: MTEB NQ |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 13.120000000000001 |
| - type: map_at_10 |
| value: 24.092 |
| - type: map_at_100 |
| value: 25.485999999999997 |
| - type: map_at_1000 |
| value: 25.557999999999996 |
| - type: map_at_3 |
| value: 20.076 |
| - type: map_at_5 |
| value: 22.368 |
| - type: mrr_at_1 |
| value: 15.093 |
| - type: mrr_at_10 |
| value: 26.142 |
| - type: mrr_at_100 |
| value: 27.301 |
| - type: mrr_at_1000 |
| value: 27.357 |
| - type: mrr_at_3 |
| value: 22.364 |
| - type: mrr_at_5 |
| value: 24.564 |
| - type: ndcg_at_1 |
| value: 15.093 |
| - type: ndcg_at_10 |
| value: 30.734 |
| - type: ndcg_at_100 |
| value: 37.147999999999996 |
| - type: ndcg_at_1000 |
| value: 38.997 |
| - type: ndcg_at_3 |
| value: 22.82 |
| - type: ndcg_at_5 |
| value: 26.806 |
| - type: precision_at_1 |
| value: 15.093 |
| - type: precision_at_10 |
| value: 5.863 |
| - type: precision_at_100 |
| value: 0.942 |
| - type: precision_at_1000 |
| value: 0.11199999999999999 |
| - type: precision_at_3 |
| value: 11.047 |
| - type: precision_at_5 |
| value: 8.863999999999999 |
| - type: recall_at_1 |
| value: 13.120000000000001 |
| - type: recall_at_10 |
| value: 49.189 |
| - type: recall_at_100 |
| value: 78.032 |
| - type: recall_at_1000 |
| value: 92.034 |
| - type: recall_at_3 |
| value: 28.483000000000004 |
| - type: recall_at_5 |
| value: 37.756 |
| - task: |
| type: Retrieval |
| dataset: |
| type: quora |
| name: MTEB QuoraRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 67.765 |
| - type: map_at_10 |
| value: 81.069 |
| - type: map_at_100 |
| value: 81.757 |
| - type: map_at_1000 |
| value: 81.782 |
| - type: map_at_3 |
| value: 78.148 |
| - type: map_at_5 |
| value: 79.95400000000001 |
| - type: mrr_at_1 |
| value: 77.8 |
| - type: mrr_at_10 |
| value: 84.639 |
| - type: mrr_at_100 |
| value: 84.789 |
| - type: mrr_at_1000 |
| value: 84.79100000000001 |
| - type: mrr_at_3 |
| value: 83.467 |
| - type: mrr_at_5 |
| value: 84.251 |
| - type: ndcg_at_1 |
| value: 77.82 |
| - type: ndcg_at_10 |
| value: 85.286 |
| - type: ndcg_at_100 |
| value: 86.86500000000001 |
| - type: ndcg_at_1000 |
| value: 87.062 |
| - type: ndcg_at_3 |
| value: 82.116 |
| - type: ndcg_at_5 |
| value: 83.811 |
| - type: precision_at_1 |
| value: 77.82 |
| - type: precision_at_10 |
| value: 12.867999999999999 |
| - type: precision_at_100 |
| value: 1.498 |
| - type: precision_at_1000 |
| value: 0.156 |
| - type: precision_at_3 |
| value: 35.723 |
| - type: precision_at_5 |
| value: 23.52 |
| - type: recall_at_1 |
| value: 67.765 |
| - type: recall_at_10 |
| value: 93.381 |
| - type: recall_at_100 |
| value: 98.901 |
| - type: recall_at_1000 |
| value: 99.864 |
| - type: recall_at_3 |
| value: 84.301 |
| - type: recall_at_5 |
| value: 89.049 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering |
| name: MTEB RedditClustering |
| config: default |
| split: test |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| metrics: |
| - type: v_measure |
| value: 45.27190981742137 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering-p2p |
| name: MTEB RedditClusteringP2P |
| config: default |
| split: test |
| revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
| metrics: |
| - type: v_measure |
| value: 54.47444004585028 |
| - task: |
| type: Retrieval |
| dataset: |
| type: scidocs |
| name: MTEB SCIDOCS |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 4.213 |
| - type: map_at_10 |
| value: 10.166 |
| - type: map_at_100 |
| value: 11.987 |
| - type: map_at_1000 |
| value: 12.285 |
| - type: map_at_3 |
| value: 7.538 |
| - type: map_at_5 |
| value: 8.606 |
| - type: mrr_at_1 |
| value: 20.8 |
| - type: mrr_at_10 |
| value: 30.066 |
| - type: mrr_at_100 |
| value: 31.290000000000003 |
| - type: mrr_at_1000 |
| value: 31.357000000000003 |
| - type: mrr_at_3 |
| value: 27.083000000000002 |
| - type: mrr_at_5 |
| value: 28.748 |
| - type: ndcg_at_1 |
| value: 20.8 |
| - type: ndcg_at_10 |
| value: 17.258000000000003 |
| - type: ndcg_at_100 |
| value: 24.801000000000002 |
| - type: ndcg_at_1000 |
| value: 30.348999999999997 |
| - type: ndcg_at_3 |
| value: 16.719 |
| - type: ndcg_at_5 |
| value: 14.145 |
| - type: precision_at_1 |
| value: 20.8 |
| - type: precision_at_10 |
| value: 8.88 |
| - type: precision_at_100 |
| value: 1.9789999999999999 |
| - type: precision_at_1000 |
| value: 0.332 |
| - type: precision_at_3 |
| value: 15.5 |
| - type: precision_at_5 |
| value: 12.1 |
| - type: recall_at_1 |
| value: 4.213 |
| - type: recall_at_10 |
| value: 17.983 |
| - type: recall_at_100 |
| value: 40.167 |
| - type: recall_at_1000 |
| value: 67.43 |
| - type: recall_at_3 |
| value: 9.433 |
| - type: recall_at_5 |
| value: 12.267999999999999 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sickr-sts |
| name: MTEB SICK-R |
| config: default |
| split: test |
| revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
| metrics: |
| - type: cos_sim_pearson |
| value: 80.36742239848913 |
| - type: cos_sim_spearman |
| value: 72.39470010828755 |
| - type: euclidean_pearson |
| value: 77.26919895870947 |
| - type: euclidean_spearman |
| value: 72.26534999077315 |
| - type: manhattan_pearson |
| value: 77.04066349814258 |
| - type: manhattan_spearman |
| value: 72.0072248699278 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts12-sts |
| name: MTEB STS12 |
| config: default |
| split: test |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| metrics: |
| - type: cos_sim_pearson |
| value: 80.26991474037257 |
| - type: cos_sim_spearman |
| value: 71.90287122017716 |
| - type: euclidean_pearson |
| value: 76.68006075912453 |
| - type: euclidean_spearman |
| value: 71.69301858764365 |
| - type: manhattan_pearson |
| value: 76.72277285842371 |
| - type: manhattan_spearman |
| value: 71.73265239703795 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts13-sts |
| name: MTEB STS13 |
| config: default |
| split: test |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| metrics: |
| - type: cos_sim_pearson |
| value: 79.74371413317881 |
| - type: cos_sim_spearman |
| value: 80.9279612820358 |
| - type: euclidean_pearson |
| value: 80.6417435294782 |
| - type: euclidean_spearman |
| value: 81.17460969254459 |
| - type: manhattan_pearson |
| value: 80.51820155178402 |
| - type: manhattan_spearman |
| value: 81.08028700017084 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts14-sts |
| name: MTEB STS14 |
| config: default |
| split: test |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| metrics: |
| - type: cos_sim_pearson |
| value: 80.37085777051112 |
| - type: cos_sim_spearman |
| value: 76.60308382518285 |
| - type: euclidean_pearson |
| value: 79.59684787227351 |
| - type: euclidean_spearman |
| value: 76.8769048249242 |
| - type: manhattan_pearson |
| value: 79.55617632538295 |
| - type: manhattan_spearman |
| value: 76.90186497973124 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts15-sts |
| name: MTEB STS15 |
| config: default |
| split: test |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| metrics: |
| - type: cos_sim_pearson |
| value: 83.99513105301321 |
| - type: cos_sim_spearman |
| value: 84.92034548133665 |
| - type: euclidean_pearson |
| value: 84.70872540095195 |
| - type: euclidean_spearman |
| value: 85.14591726040749 |
| - type: manhattan_pearson |
| value: 84.65707417430595 |
| - type: manhattan_spearman |
| value: 85.10407163865375 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts16-sts |
| name: MTEB STS16 |
| config: default |
| split: test |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| metrics: |
| - type: cos_sim_pearson |
| value: 79.40758449150897 |
| - type: cos_sim_spearman |
| value: 80.71692246880549 |
| - type: euclidean_pearson |
| value: 80.51658552062683 |
| - type: euclidean_spearman |
| value: 80.87118389043233 |
| - type: manhattan_pearson |
| value: 80.41534690825016 |
| - type: manhattan_spearman |
| value: 80.73925282537256 |
| - 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: 84.93617076910748 |
| - type: cos_sim_spearman |
| value: 85.61118538966805 |
| - type: euclidean_pearson |
| value: 85.56187558635287 |
| - type: euclidean_spearman |
| value: 85.21910090757267 |
| - type: manhattan_pearson |
| value: 85.29916699037645 |
| - type: manhattan_spearman |
| value: 84.96820527868671 |
| - 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: 64.22294088543077 |
| - type: cos_sim_spearman |
| value: 65.89748502901078 |
| - type: euclidean_pearson |
| value: 66.15637850660805 |
| - type: euclidean_spearman |
| value: 65.86095841381278 |
| - type: manhattan_pearson |
| value: 66.80966197857856 |
| - type: manhattan_spearman |
| value: 66.48325202219692 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/stsbenchmark-sts |
| name: MTEB STSBenchmark |
| config: default |
| split: test |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
| metrics: |
| - type: cos_sim_pearson |
| value: 81.75298158703048 |
| - type: cos_sim_spearman |
| value: 81.32168373072322 |
| - type: euclidean_pearson |
| value: 82.3251793712207 |
| - type: euclidean_spearman |
| value: 81.31655163330606 |
| - type: manhattan_pearson |
| value: 82.14136865023298 |
| - type: manhattan_spearman |
| value: 81.13410964028606 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/scidocs-reranking |
| name: MTEB SciDocsRR |
| config: default |
| split: test |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| metrics: |
| - type: map |
| value: 78.77937068780793 |
| - type: mrr |
| value: 93.334709952357 |
| - task: |
| type: Retrieval |
| dataset: |
| type: scifact |
| name: MTEB SciFact |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 50.705999999999996 |
| - type: map_at_10 |
| value: 60.699999999999996 |
| - type: map_at_100 |
| value: 61.256 |
| - type: map_at_1000 |
| value: 61.285000000000004 |
| - type: map_at_3 |
| value: 57.633 |
| - type: map_at_5 |
| value: 59.648 |
| - type: mrr_at_1 |
| value: 53.0 |
| - type: mrr_at_10 |
| value: 61.717999999999996 |
| - type: mrr_at_100 |
| value: 62.165000000000006 |
| - type: mrr_at_1000 |
| value: 62.190999999999995 |
| - type: mrr_at_3 |
| value: 59.389 |
| - type: mrr_at_5 |
| value: 60.922 |
| - type: ndcg_at_1 |
| value: 53.0 |
| - type: ndcg_at_10 |
| value: 65.413 |
| - type: ndcg_at_100 |
| value: 68.089 |
| - type: ndcg_at_1000 |
| value: 69.01899999999999 |
| - type: ndcg_at_3 |
| value: 60.327 |
| - type: ndcg_at_5 |
| value: 63.263999999999996 |
| - type: precision_at_1 |
| value: 53.0 |
| - type: precision_at_10 |
| value: 8.933 |
| - type: precision_at_100 |
| value: 1.04 |
| - type: precision_at_1000 |
| value: 0.11199999999999999 |
| - type: precision_at_3 |
| value: 23.778 |
| - type: precision_at_5 |
| value: 16.2 |
| - type: recall_at_1 |
| value: 50.705999999999996 |
| - type: recall_at_10 |
| value: 78.633 |
| - type: recall_at_100 |
| value: 91.333 |
| - type: recall_at_1000 |
| value: 99.0 |
| - type: recall_at_3 |
| value: 65.328 |
| - type: recall_at_5 |
| value: 72.583 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/sprintduplicatequestions-pairclassification |
| name: MTEB SprintDuplicateQuestions |
| config: default |
| split: test |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 99.82178217821782 |
| - type: cos_sim_ap |
| value: 95.30078788098801 |
| - type: cos_sim_f1 |
| value: 91.11549851924975 |
| - type: cos_sim_precision |
| value: 89.96101364522417 |
| - type: cos_sim_recall |
| value: 92.30000000000001 |
| - type: dot_accuracy |
| value: 99.74851485148515 |
| - type: dot_ap |
| value: 93.12383012680787 |
| - type: dot_f1 |
| value: 87.17171717171716 |
| - type: dot_precision |
| value: 88.06122448979592 |
| - type: dot_recall |
| value: 86.3 |
| - type: euclidean_accuracy |
| value: 99.82673267326733 |
| - type: euclidean_ap |
| value: 95.29507269622621 |
| - type: euclidean_f1 |
| value: 91.3151364764268 |
| - type: euclidean_precision |
| value: 90.64039408866995 |
| - type: euclidean_recall |
| value: 92.0 |
| - type: manhattan_accuracy |
| value: 99.82178217821782 |
| - type: manhattan_ap |
| value: 95.34300712110257 |
| - type: manhattan_f1 |
| value: 91.05367793240556 |
| - type: manhattan_precision |
| value: 90.51383399209486 |
| - type: manhattan_recall |
| value: 91.60000000000001 |
| - type: max_accuracy |
| value: 99.82673267326733 |
| - type: max_ap |
| value: 95.34300712110257 |
| - type: max_f1 |
| value: 91.3151364764268 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering |
| name: MTEB StackExchangeClustering |
| config: default |
| split: test |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
| metrics: |
| - type: v_measure |
| value: 53.10993894014712 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering-p2p |
| name: MTEB StackExchangeClusteringP2P |
| config: default |
| split: test |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
| metrics: |
| - type: v_measure |
| value: 34.67216071080345 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/stackoverflowdupquestions-reranking |
| name: MTEB StackOverflowDupQuestions |
| config: default |
| split: test |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
| metrics: |
| - type: map |
| value: 48.96344255085851 |
| - type: mrr |
| value: 49.816123419064596 |
| - task: |
| type: Summarization |
| dataset: |
| type: mteb/summeval |
| name: MTEB SummEval |
| config: default |
| split: test |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
| metrics: |
| - type: cos_sim_pearson |
| value: 30.580410074992177 |
| - type: cos_sim_spearman |
| value: 31.155995112739966 |
| - type: dot_pearson |
| value: 31.112094423048998 |
| - type: dot_spearman |
| value: 31.29974829801922 |
| - task: |
| type: Retrieval |
| dataset: |
| type: trec-covid |
| name: MTEB TRECCOVID |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 0.17700000000000002 |
| - type: map_at_10 |
| value: 1.22 |
| - type: map_at_100 |
| value: 6.2170000000000005 |
| - type: map_at_1000 |
| value: 15.406 |
| - type: map_at_3 |
| value: 0.483 |
| - type: map_at_5 |
| value: 0.729 |
| - type: mrr_at_1 |
| value: 64.0 |
| - type: mrr_at_10 |
| value: 76.333 |
| - type: mrr_at_100 |
| value: 76.47 |
| - type: mrr_at_1000 |
| value: 76.47 |
| - type: mrr_at_3 |
| value: 75.0 |
| - type: mrr_at_5 |
| value: 76.0 |
| - type: ndcg_at_1 |
| value: 59.0 |
| - type: ndcg_at_10 |
| value: 52.62 |
| - type: ndcg_at_100 |
| value: 39.932 |
| - type: ndcg_at_1000 |
| value: 37.317 |
| - type: ndcg_at_3 |
| value: 57.123000000000005 |
| - type: ndcg_at_5 |
| value: 56.376000000000005 |
| - type: precision_at_1 |
| value: 64.0 |
| - type: precision_at_10 |
| value: 55.800000000000004 |
| - type: precision_at_100 |
| value: 41.04 |
| - type: precision_at_1000 |
| value: 17.124 |
| - type: precision_at_3 |
| value: 63.333 |
| - type: precision_at_5 |
| value: 62.0 |
| - type: recall_at_1 |
| value: 0.17700000000000002 |
| - type: recall_at_10 |
| value: 1.46 |
| - type: recall_at_100 |
| value: 9.472999999999999 |
| - type: recall_at_1000 |
| value: 35.661 |
| - type: recall_at_3 |
| value: 0.527 |
| - type: recall_at_5 |
| value: 0.8250000000000001 |
| - task: |
| type: Retrieval |
| dataset: |
| type: webis-touche2020 |
| name: MTEB Touche2020 |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 1.539 |
| - type: map_at_10 |
| value: 7.178 |
| - type: map_at_100 |
| value: 12.543000000000001 |
| - type: map_at_1000 |
| value: 14.126 |
| - type: map_at_3 |
| value: 3.09 |
| - type: map_at_5 |
| value: 5.008 |
| - type: mrr_at_1 |
| value: 18.367 |
| - type: mrr_at_10 |
| value: 32.933 |
| - type: mrr_at_100 |
| value: 34.176 |
| - type: mrr_at_1000 |
| value: 34.176 |
| - type: mrr_at_3 |
| value: 27.551 |
| - type: mrr_at_5 |
| value: 30.714000000000002 |
| - type: ndcg_at_1 |
| value: 15.306000000000001 |
| - type: ndcg_at_10 |
| value: 18.343 |
| - type: ndcg_at_100 |
| value: 30.076000000000004 |
| - type: ndcg_at_1000 |
| value: 42.266999999999996 |
| - type: ndcg_at_3 |
| value: 17.233999999999998 |
| - type: ndcg_at_5 |
| value: 18.677 |
| - type: precision_at_1 |
| value: 18.367 |
| - type: precision_at_10 |
| value: 18.367 |
| - type: precision_at_100 |
| value: 6.837 |
| - type: precision_at_1000 |
| value: 1.467 |
| - type: precision_at_3 |
| value: 19.048000000000002 |
| - type: precision_at_5 |
| value: 21.224 |
| - type: recall_at_1 |
| value: 1.539 |
| - type: recall_at_10 |
| value: 13.289000000000001 |
| - type: recall_at_100 |
| value: 42.480000000000004 |
| - type: recall_at_1000 |
| value: 79.463 |
| - type: recall_at_3 |
| value: 4.202999999999999 |
| - type: recall_at_5 |
| value: 7.9030000000000005 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/toxic_conversations_50k |
| name: MTEB ToxicConversationsClassification |
| config: default |
| split: test |
| revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
| metrics: |
| - type: accuracy |
| value: 69.2056 |
| - type: ap |
| value: 13.564165903349778 |
| - type: f1 |
| value: 53.303385089202656 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/tweet_sentiment_extraction |
| name: MTEB TweetSentimentExtractionClassification |
| config: default |
| split: test |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| metrics: |
| - type: accuracy |
| value: 56.71477079796264 |
| - type: f1 |
| value: 57.01563439439609 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/twentynewsgroups-clustering |
| name: MTEB TwentyNewsgroupsClustering |
| config: default |
| split: test |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| metrics: |
| - type: v_measure |
| value: 39.373040570976514 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twittersemeval2015-pairclassification |
| name: MTEB TwitterSemEval2015 |
| config: default |
| split: test |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 83.44757703999524 |
| - type: cos_sim_ap |
| value: 65.78689843625949 |
| - type: cos_sim_f1 |
| value: 62.25549384206713 |
| - type: cos_sim_precision |
| value: 57.39091718610864 |
| - type: cos_sim_recall |
| value: 68.02110817941951 |
| - type: dot_accuracy |
| value: 81.3971508612982 |
| - type: dot_ap |
| value: 58.42933051967154 |
| - type: dot_f1 |
| value: 57.85580214198962 |
| - type: dot_precision |
| value: 49.74368710841086 |
| - type: dot_recall |
| value: 69.12928759894459 |
| - type: euclidean_accuracy |
| value: 83.54294569946951 |
| - type: euclidean_ap |
| value: 66.10612585693795 |
| - type: euclidean_f1 |
| value: 62.66666666666667 |
| - type: euclidean_precision |
| value: 58.88631090487239 |
| - type: euclidean_recall |
| value: 66.96569920844327 |
| - type: manhattan_accuracy |
| value: 83.43565595756095 |
| - type: manhattan_ap |
| value: 65.88532290329134 |
| - type: manhattan_f1 |
| value: 62.58408721874276 |
| - type: manhattan_precision |
| value: 55.836092715231786 |
| - type: manhattan_recall |
| value: 71.18733509234828 |
| - type: max_accuracy |
| value: 83.54294569946951 |
| - type: max_ap |
| value: 66.10612585693795 |
| - type: max_f1 |
| value: 62.66666666666667 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twitterurlcorpus-pairclassification |
| name: MTEB TwitterURLCorpus |
| config: default |
| split: test |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
| metrics: |
| - type: cos_sim_accuracy |
| value: 88.02344083517679 |
| - type: cos_sim_ap |
| value: 84.21589190889944 |
| - type: cos_sim_f1 |
| value: 76.36723039754007 |
| - type: cos_sim_precision |
| value: 72.79134682484299 |
| - type: cos_sim_recall |
| value: 80.31259624268556 |
| - type: dot_accuracy |
| value: 87.43353902278108 |
| - type: dot_ap |
| value: 82.08962394120071 |
| - type: dot_f1 |
| value: 74.97709923664122 |
| - type: dot_precision |
| value: 74.34150772025431 |
| - type: dot_recall |
| value: 75.62365260240222 |
| - type: euclidean_accuracy |
| value: 87.97686963946133 |
| - type: euclidean_ap |
| value: 84.20578083922416 |
| - type: euclidean_f1 |
| value: 76.4299182903834 |
| - type: euclidean_precision |
| value: 73.51874244256348 |
| - type: euclidean_recall |
| value: 79.58115183246073 |
| - type: manhattan_accuracy |
| value: 88.00209570380719 |
| - type: manhattan_ap |
| value: 84.14700304263556 |
| - type: manhattan_f1 |
| value: 76.36429345861944 |
| - type: manhattan_precision |
| value: 71.95886119057349 |
| - type: manhattan_recall |
| value: 81.34431783184478 |
| - type: max_accuracy |
| value: 88.02344083517679 |
| - type: max_ap |
| value: 84.21589190889944 |
| - type: max_f1 |
| value: 76.4299182903834 |
| --- |
| |
| # bge-micro |
|
|
| This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search. |
| It is distilled from [bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5/blob/main/config.json), with 1/4 the non-embedding parameters. |
| It has 1/2 the parameters of the smallest commonly-used embedding model, all-MiniLM-L6-v2, with similar performance. |
|
|
| <!--- Describe your model here --> |
|
|
| ## Usage (Sentence-Transformers) |
|
|
| Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed: |
|
|
| ``` |
| pip install -U sentence-transformers |
| ``` |
|
|
| Then you can use the model like this: |
|
|
| ```python |
| from sentence_transformers import SentenceTransformer |
| sentences = ["This is an example sentence", "Each sentence is converted"] |
| |
| model = SentenceTransformer('{MODEL_NAME}') |
| embeddings = model.encode(sentences) |
| print(embeddings) |
| ``` |
|
|
|
|
|
|
| ## Usage (HuggingFace Transformers) |
| Without [sentence-transformers](https://www.SBERT.net), you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings. |
|
|
| ```python |
| from transformers import AutoTokenizer, AutoModel |
| import torch |
| |
| |
| #Mean Pooling - Take attention mask into account for correct averaging |
| def mean_pooling(model_output, attention_mask): |
| token_embeddings = model_output[0] #First element of model_output contains all token embeddings |
| input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float() |
| return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9) |
| |
| |
| # Sentences we want sentence embeddings for |
| sentences = ['This is an example sentence', 'Each sentence is converted'] |
| |
| # Load model from HuggingFace Hub |
| tokenizer = AutoTokenizer.from_pretrained('{MODEL_NAME}') |
| model = AutoModel.from_pretrained('{MODEL_NAME}') |
| |
| # Tokenize sentences |
| encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt') |
| |
| # Compute token embeddings |
| with torch.no_grad(): |
| model_output = model(**encoded_input) |
| |
| # Perform pooling. In this case, mean pooling. |
| sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask']) |
| |
| print("Sentence embeddings:") |
| print(sentence_embeddings) |
| ``` |
|
|
|
|
|
|
| ## Evaluation Results |
|
|
| <!--- Describe how your model was evaluated --> |
|
|
| For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name={MODEL_NAME}) |
|
|
|
|
|
|
| ## Full Model Architecture |
| ``` |
| SentenceTransformer( |
| (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel |
| (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False}) |
| ) |
| ``` |
|
|
| ## Citing & Authors |
|
|
| <!--- Describe where people can find more information --> |
