| --- |
| tags: |
| - mteb |
| model-index: |
| - name: mpnet_main |
| results: |
| - task: |
| type: Classification |
| dataset: |
| type: None |
| name: MTEB AmazonCounterfactualClassification (en) |
| config: en |
| split: test |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
| metrics: |
| - type: accuracy |
| value: 68.11940298507461 |
| - type: ap |
| value: 30.542146596139048 |
| - type: f1 |
| value: 61.92465989589396 |
| - task: |
| type: Classification |
| dataset: |
| type: None |
| name: MTEB AmazonPolarityClassification |
| config: default |
| split: test |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
| metrics: |
| - type: accuracy |
| value: 62.503875 |
| - type: ap |
| value: 58.0577571607728 |
| - type: f1 |
| value: 62.34928241469865 |
| - task: |
| type: Classification |
| dataset: |
| type: None |
| name: MTEB AmazonReviewsClassification (en) |
| config: en |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 31.66999999999999 |
| - type: f1 |
| value: 31.2458385101798 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB ArguAna |
| config: default |
| split: test |
| revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
| metrics: |
| - type: map_at_1 |
| value: 23.329 |
| - type: map_at_10 |
| value: 37.384 |
| - type: map_at_100 |
| value: 38.57 |
| - type: map_at_1000 |
| value: 38.586999999999996 |
| - type: map_at_3 |
| value: 32.492 |
| - type: map_at_5 |
| value: 35.376000000000005 |
| - type: mrr_at_1 |
| value: 23.755000000000003 |
| - type: mrr_at_10 |
| value: 37.547000000000004 |
| - type: mrr_at_100 |
| value: 38.733000000000004 |
| - type: mrr_at_1000 |
| value: 38.749 |
| - type: mrr_at_3 |
| value: 32.658 |
| - type: mrr_at_5 |
| value: 35.567 |
| - type: ndcg_at_1 |
| value: 23.329 |
| - type: ndcg_at_10 |
| value: 45.574999999999996 |
| - type: ndcg_at_100 |
| value: 50.953 |
| - type: ndcg_at_1000 |
| value: 51.354 |
| - type: ndcg_at_3 |
| value: 35.608000000000004 |
| - type: ndcg_at_5 |
| value: 40.784 |
| - type: precision_at_1 |
| value: 23.329 |
| - type: precision_at_10 |
| value: 7.183000000000001 |
| - type: precision_at_100 |
| value: 0.962 |
| - type: precision_at_1000 |
| value: 0.099 |
| - type: precision_at_3 |
| value: 14.889 |
| - type: precision_at_5 |
| value: 11.437 |
| - type: recall_at_1 |
| value: 23.329 |
| - type: recall_at_10 |
| value: 71.83500000000001 |
| - type: recall_at_100 |
| value: 96.15899999999999 |
| - type: recall_at_1000 |
| value: 99.21799999999999 |
| - type: recall_at_3 |
| value: 44.666 |
| - type: recall_at_5 |
| value: 57.18299999999999 |
| - task: |
| type: Clustering |
| dataset: |
| type: None |
| name: MTEB ArxivClusteringP2P |
| config: default |
| split: test |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| metrics: |
| - type: v_measure |
| value: 37.14558539727219 |
| - task: |
| type: Clustering |
| dataset: |
| type: None |
| name: MTEB ArxivClusteringS2S |
| config: default |
| split: test |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
| metrics: |
| - type: v_measure |
| value: 27.2291028039137 |
| - task: |
| type: Reranking |
| dataset: |
| type: None |
| name: MTEB AskUbuntuDupQuestions |
| config: default |
| split: test |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
| metrics: |
| - type: map |
| value: 55.286820678107716 |
| - type: mrr |
| value: 69.43762916062084 |
| - task: |
| type: STS |
| dataset: |
| type: None |
| name: MTEB BIOSSES |
| config: default |
| split: test |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
| metrics: |
| - type: cos_sim_pearson |
| value: 81.32170750010246 |
| - type: cos_sim_spearman |
| value: 78.48130632209363 |
| - type: euclidean_pearson |
| value: 80.42696573048755 |
| - type: euclidean_spearman |
| value: 78.48130632209363 |
| - type: manhattan_pearson |
| value: 80.68662655318546 |
| - type: manhattan_spearman |
| value: 78.4475706136436 |
| - task: |
| type: Classification |
| dataset: |
| type: None |
| name: MTEB Banking77Classification |
| config: default |
| split: test |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| metrics: |
| - type: accuracy |
| value: 73.05194805194805 |
| - type: f1 |
| value: 72.31114319146532 |
| - task: |
| type: Clustering |
| dataset: |
| type: None |
| name: MTEB BiorxivClusteringP2P |
| config: default |
| split: test |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| metrics: |
| - type: v_measure |
| value: 33.842006272885655 |
| - task: |
| type: Clustering |
| dataset: |
| type: None |
| name: MTEB BiorxivClusteringS2S |
| config: default |
| split: test |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
| metrics: |
| - type: v_measure |
| value: 25.238443830234058 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB CQADupstackAndroidRetrieval |
| config: default |
| split: test |
| revision: f46a197baaae43b4f621051089b82a364682dfeb |
| metrics: |
| - type: map_at_1 |
| value: 22.647000000000002 |
| - type: map_at_10 |
| value: 29.842999999999996 |
| - type: map_at_100 |
| value: 31.131999999999998 |
| - type: map_at_1000 |
| value: 31.289 |
| - type: map_at_3 |
| value: 27.534999999999997 |
| - type: map_at_5 |
| value: 28.782999999999998 |
| - type: mrr_at_1 |
| value: 28.183000000000003 |
| - type: mrr_at_10 |
| value: 35.225 |
| - type: mrr_at_100 |
| value: 36.128 |
| - type: mrr_at_1000 |
| value: 36.198 |
| - type: mrr_at_3 |
| value: 33.19 |
| - type: mrr_at_5 |
| value: 34.363 |
| - type: ndcg_at_1 |
| value: 28.183000000000003 |
| - type: ndcg_at_10 |
| value: 34.644000000000005 |
| - type: ndcg_at_100 |
| value: 40.194 |
| - type: ndcg_at_1000 |
| value: 43.289 |
| - type: ndcg_at_3 |
| value: 31.259999999999998 |
| - type: ndcg_at_5 |
| value: 32.707 |
| - type: precision_at_1 |
| value: 28.183000000000003 |
| - type: precision_at_10 |
| value: 6.666999999999999 |
| - type: precision_at_100 |
| value: 1.187 |
| - type: precision_at_1000 |
| value: 0.185 |
| - type: precision_at_3 |
| value: 14.974000000000002 |
| - type: precision_at_5 |
| value: 10.844 |
| - type: recall_at_1 |
| value: 22.647000000000002 |
| - type: recall_at_10 |
| value: 42.792 |
| - type: recall_at_100 |
| value: 67.399 |
| - type: recall_at_1000 |
| value: 88.646 |
| - type: recall_at_3 |
| value: 32.535 |
| - type: recall_at_5 |
| value: 36.748999999999995 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB CQADupstackEnglishRetrieval |
| config: default |
| split: test |
| revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
| metrics: |
| - type: map_at_1 |
| value: 15.895000000000001 |
| - type: map_at_10 |
| value: 21.631 |
| - type: map_at_100 |
| value: 22.56 |
| - type: map_at_1000 |
| value: 22.689 |
| - type: map_at_3 |
| value: 19.799 |
| - type: map_at_5 |
| value: 20.824 |
| - type: mrr_at_1 |
| value: 20.191 |
| - type: mrr_at_10 |
| value: 25.674999999999997 |
| - type: mrr_at_100 |
| value: 26.482 |
| - type: mrr_at_1000 |
| value: 26.558 |
| - type: mrr_at_3 |
| value: 23.854 |
| - type: mrr_at_5 |
| value: 24.85 |
| - type: ndcg_at_1 |
| value: 20.191 |
| - type: ndcg_at_10 |
| value: 25.428 |
| - type: ndcg_at_100 |
| value: 29.799999999999997 |
| - type: ndcg_at_1000 |
| value: 32.927 |
| - type: ndcg_at_3 |
| value: 22.284000000000002 |
| - type: ndcg_at_5 |
| value: 23.699 |
| - type: precision_at_1 |
| value: 20.191 |
| - type: precision_at_10 |
| value: 4.7829999999999995 |
| - type: precision_at_100 |
| value: 0.876 |
| - type: precision_at_1000 |
| value: 0.14200000000000002 |
| - type: precision_at_3 |
| value: 10.743 |
| - type: precision_at_5 |
| value: 7.720000000000001 |
| - type: recall_at_1 |
| value: 15.895000000000001 |
| - type: recall_at_10 |
| value: 32.789 |
| - type: recall_at_100 |
| value: 52.156000000000006 |
| - type: recall_at_1000 |
| value: 73.804 |
| - type: recall_at_3 |
| value: 23.589 |
| - type: recall_at_5 |
| value: 27.486 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB CQADupstackGamingRetrieval |
| config: default |
| split: test |
| revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
| metrics: |
| - type: map_at_1 |
| value: 25.465 |
| - type: map_at_10 |
| value: 33.93 |
| - type: map_at_100 |
| value: 35.07 |
| - type: map_at_1000 |
| value: 35.165 |
| - type: map_at_3 |
| value: 31.091 |
| - type: map_at_5 |
| value: 32.722 |
| - type: mrr_at_1 |
| value: 29.654999999999998 |
| - type: mrr_at_10 |
| value: 37.156 |
| - type: mrr_at_100 |
| value: 38.074000000000005 |
| - type: mrr_at_1000 |
| value: 38.132 |
| - type: mrr_at_3 |
| value: 34.608 |
| - type: mrr_at_5 |
| value: 36.077999999999996 |
| - type: ndcg_at_1 |
| value: 29.654999999999998 |
| - type: ndcg_at_10 |
| value: 38.872 |
| - type: ndcg_at_100 |
| value: 44.293 |
| - type: ndcg_at_1000 |
| value: 46.455999999999996 |
| - type: ndcg_at_3 |
| value: 33.661 |
| - type: ndcg_at_5 |
| value: 36.237 |
| - type: precision_at_1 |
| value: 29.654999999999998 |
| - type: precision_at_10 |
| value: 6.464 |
| - type: precision_at_100 |
| value: 1.012 |
| - type: precision_at_1000 |
| value: 0.127 |
| - type: precision_at_3 |
| value: 14.943000000000001 |
| - type: precision_at_5 |
| value: 10.696 |
| - type: recall_at_1 |
| value: 25.465 |
| - type: recall_at_10 |
| value: 50.8 |
| - type: recall_at_100 |
| value: 75.373 |
| - type: recall_at_1000 |
| value: 91.053 |
| - type: recall_at_3 |
| value: 36.808 |
| - type: recall_at_5 |
| value: 43.069 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB CQADupstackGisRetrieval |
| config: default |
| split: test |
| revision: 5003b3064772da1887988e05400cf3806fe491f2 |
| metrics: |
| - type: map_at_1 |
| value: 12.853 |
| - type: map_at_10 |
| value: 18.047 |
| - type: map_at_100 |
| value: 18.9 |
| - type: map_at_1000 |
| value: 19.017999999999997 |
| - type: map_at_3 |
| value: 16.325 |
| - type: map_at_5 |
| value: 17.281 |
| - type: mrr_at_1 |
| value: 14.124 |
| - type: mrr_at_10 |
| value: 19.344 |
| - type: mrr_at_100 |
| value: 20.194000000000003 |
| - type: mrr_at_1000 |
| value: 20.298 |
| - type: mrr_at_3 |
| value: 17.589 |
| - type: mrr_at_5 |
| value: 18.601 |
| - type: ndcg_at_1 |
| value: 14.124 |
| - type: ndcg_at_10 |
| value: 21.188000000000002 |
| - type: ndcg_at_100 |
| value: 25.856 |
| - type: ndcg_at_1000 |
| value: 29.275000000000002 |
| - type: ndcg_at_3 |
| value: 17.726 |
| - type: ndcg_at_5 |
| value: 19.397000000000002 |
| - type: precision_at_1 |
| value: 14.124 |
| - type: precision_at_10 |
| value: 3.379 |
| - type: precision_at_100 |
| value: 0.61 |
| - type: precision_at_1000 |
| value: 0.095 |
| - type: precision_at_3 |
| value: 7.608 |
| - type: precision_at_5 |
| value: 5.537 |
| - type: recall_at_1 |
| value: 12.853 |
| - type: recall_at_10 |
| value: 29.731999999999996 |
| - type: recall_at_100 |
| value: 51.99399999999999 |
| - type: recall_at_1000 |
| value: 78.581 |
| - type: recall_at_3 |
| value: 20.339 |
| - type: recall_at_5 |
| value: 24.304000000000002 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB CQADupstackMathematicaRetrieval |
| config: default |
| split: test |
| revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
| metrics: |
| - type: map_at_1 |
| value: 6.736000000000001 |
| - type: map_at_10 |
| value: 10.587 |
| - type: map_at_100 |
| value: 11.515 |
| - type: map_at_1000 |
| value: 11.633000000000001 |
| - type: map_at_3 |
| value: 9.24 |
| - type: map_at_5 |
| value: 9.856 |
| - type: mrr_at_1 |
| value: 8.955 |
| - type: mrr_at_10 |
| value: 13.383999999999999 |
| - type: mrr_at_100 |
| value: 14.297 |
| - type: mrr_at_1000 |
| value: 14.391000000000002 |
| - type: mrr_at_3 |
| value: 11.92 |
| - type: mrr_at_5 |
| value: 12.584999999999999 |
| - type: ndcg_at_1 |
| value: 8.955 |
| - type: ndcg_at_10 |
| value: 13.498 |
| - type: ndcg_at_100 |
| value: 18.684 |
| - type: ndcg_at_1000 |
| value: 22.105 |
| - type: ndcg_at_3 |
| value: 10.881 |
| - type: ndcg_at_5 |
| value: 11.824 |
| - type: precision_at_1 |
| value: 8.955 |
| - type: precision_at_10 |
| value: 2.662 |
| - type: precision_at_100 |
| value: 0.633 |
| - type: precision_at_1000 |
| value: 0.106 |
| - type: precision_at_3 |
| value: 5.473 |
| - type: precision_at_5 |
| value: 3.9800000000000004 |
| - type: recall_at_1 |
| value: 6.736000000000001 |
| - type: recall_at_10 |
| value: 19.945 |
| - type: recall_at_100 |
| value: 43.807 |
| - type: recall_at_1000 |
| value: 69.215 |
| - type: recall_at_3 |
| value: 12.458 |
| - type: recall_at_5 |
| value: 14.878 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB CQADupstackPhysicsRetrieval |
| config: default |
| split: test |
| revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
| metrics: |
| - type: map_at_1 |
| value: 19.169 |
| - type: map_at_10 |
| value: 25.34 |
| - type: map_at_100 |
| value: 26.509 |
| - type: map_at_1000 |
| value: 26.663999999999998 |
| - type: map_at_3 |
| value: 22.964000000000002 |
| - type: map_at_5 |
| value: 24.229 |
| - type: mrr_at_1 |
| value: 23.483999999999998 |
| - type: mrr_at_10 |
| value: 29.872 |
| - type: mrr_at_100 |
| value: 30.775999999999996 |
| - type: mrr_at_1000 |
| value: 30.858 |
| - type: mrr_at_3 |
| value: 27.43 |
| - type: mrr_at_5 |
| value: 28.782000000000004 |
| - type: ndcg_at_1 |
| value: 23.483999999999998 |
| - type: ndcg_at_10 |
| value: 29.859 |
| - type: ndcg_at_100 |
| value: 35.498000000000005 |
| - type: ndcg_at_1000 |
| value: 38.875 |
| - type: ndcg_at_3 |
| value: 25.635 |
| - type: ndcg_at_5 |
| value: 27.522000000000002 |
| - type: precision_at_1 |
| value: 23.483999999999998 |
| - type: precision_at_10 |
| value: 5.573 |
| - type: precision_at_100 |
| value: 1.002 |
| - type: precision_at_1000 |
| value: 0.15 |
| - type: precision_at_3 |
| value: 11.902 |
| - type: precision_at_5 |
| value: 8.72 |
| - type: recall_at_1 |
| value: 19.169 |
| - type: recall_at_10 |
| value: 38.991 |
| - type: recall_at_100 |
| value: 64.13600000000001 |
| - type: recall_at_1000 |
| value: 87.45 |
| - type: recall_at_3 |
| value: 27.053 |
| - type: recall_at_5 |
| value: 31.996999999999996 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB CQADupstackProgrammersRetrieval |
| config: default |
| split: test |
| revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
| metrics: |
| - type: map_at_1 |
| value: 13.791999999999998 |
| - type: map_at_10 |
| value: 19.362 |
| - type: map_at_100 |
| value: 20.51 |
| - type: map_at_1000 |
| value: 20.663999999999998 |
| - type: map_at_3 |
| value: 17.408 |
| - type: map_at_5 |
| value: 18.373 |
| - type: mrr_at_1 |
| value: 17.122999999999998 |
| - type: mrr_at_10 |
| value: 22.939 |
| - type: mrr_at_100 |
| value: 23.913999999999998 |
| - type: mrr_at_1000 |
| value: 24.016000000000002 |
| - type: mrr_at_3 |
| value: 20.871000000000002 |
| - type: mrr_at_5 |
| value: 22.019 |
| - type: ndcg_at_1 |
| value: 17.122999999999998 |
| - type: ndcg_at_10 |
| value: 23.219 |
| - type: ndcg_at_100 |
| value: 28.610999999999997 |
| - type: ndcg_at_1000 |
| value: 32.361000000000004 |
| - type: ndcg_at_3 |
| value: 19.657 |
| - type: ndcg_at_5 |
| value: 21.153 |
| - type: precision_at_1 |
| value: 17.122999999999998 |
| - type: precision_at_10 |
| value: 4.3950000000000005 |
| - type: precision_at_100 |
| value: 0.852 |
| - type: precision_at_1000 |
| value: 0.136 |
| - type: precision_at_3 |
| value: 9.399000000000001 |
| - type: precision_at_5 |
| value: 6.963 |
| - type: recall_at_1 |
| value: 13.791999999999998 |
| - type: recall_at_10 |
| value: 31.407 |
| - type: recall_at_100 |
| value: 54.69199999999999 |
| - type: recall_at_1000 |
| value: 81.281 |
| - type: recall_at_3 |
| value: 21.253 |
| - type: recall_at_5 |
| value: 25.22 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack |
| name: MTEB CQADupstackRetrieval |
| config: default |
| split: test |
| revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
| metrics: |
| - type: map_at_1 |
| value: 14.433916666666665 |
| - type: map_at_10 |
| value: 19.892166666666668 |
| - type: map_at_100 |
| value: 20.87308333333333 |
| - type: map_at_1000 |
| value: 21.008416666666665 |
| - type: map_at_3 |
| value: 18.058666666666667 |
| - type: map_at_5 |
| value: 19.015583333333336 |
| - type: mrr_at_1 |
| value: 17.51 |
| - type: mrr_at_10 |
| value: 23.03275 |
| - type: mrr_at_100 |
| value: 23.89025 |
| - type: mrr_at_1000 |
| value: 23.980333333333334 |
| - type: mrr_at_3 |
| value: 21.20616666666667 |
| - type: mrr_at_5 |
| value: 22.195833333333333 |
| - type: ndcg_at_1 |
| value: 17.51 |
| - type: ndcg_at_10 |
| value: 23.55825 |
| - type: ndcg_at_100 |
| value: 28.414249999999996 |
| - type: ndcg_at_1000 |
| value: 31.749083333333328 |
| - type: ndcg_at_3 |
| value: 20.22475 |
| - type: ndcg_at_5 |
| value: 21.668916666666664 |
| - type: precision_at_1 |
| value: 17.51 |
| - type: precision_at_10 |
| value: 4.271333333333334 |
| - type: precision_at_100 |
| value: 0.8016666666666666 |
| - type: precision_at_1000 |
| value: 0.12825 |
| - type: precision_at_3 |
| value: 9.423833333333336 |
| - type: precision_at_5 |
| value: 6.818833333333334 |
| - type: recall_at_1 |
| value: 14.433916666666665 |
| - type: recall_at_10 |
| value: 31.521166666666662 |
| - type: recall_at_100 |
| value: 53.71125 |
| - type: recall_at_1000 |
| value: 77.92325000000001 |
| - type: recall_at_3 |
| value: 22.02575 |
| - type: recall_at_5 |
| value: 25.789916666666663 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB CQADupstackStatsRetrieval |
| config: default |
| split: test |
| revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
| metrics: |
| - type: map_at_1 |
| value: 11.074 |
| - type: map_at_10 |
| value: 15.728 |
| - type: map_at_100 |
| value: 16.442999999999998 |
| - type: map_at_1000 |
| value: 16.536 |
| - type: map_at_3 |
| value: 14.082 |
| - type: map_at_5 |
| value: 14.808 |
| - type: mrr_at_1 |
| value: 12.883 |
| - type: mrr_at_10 |
| value: 17.687 |
| - type: mrr_at_100 |
| value: 18.436 |
| - type: mrr_at_1000 |
| value: 18.515 |
| - type: mrr_at_3 |
| value: 16.181 |
| - type: mrr_at_5 |
| value: 16.84 |
| - type: ndcg_at_1 |
| value: 12.883 |
| - type: ndcg_at_10 |
| value: 18.778 |
| - type: ndcg_at_100 |
| value: 22.817999999999998 |
| - type: ndcg_at_1000 |
| value: 25.657999999999998 |
| - type: ndcg_at_3 |
| value: 15.606 |
| - type: ndcg_at_5 |
| value: 16.727 |
| - type: precision_at_1 |
| value: 12.883 |
| - type: precision_at_10 |
| value: 3.2520000000000002 |
| - type: precision_at_100 |
| value: 0.5780000000000001 |
| - type: precision_at_1000 |
| value: 0.089 |
| - type: precision_at_3 |
| value: 7.156999999999999 |
| - type: precision_at_5 |
| value: 5.061 |
| - type: recall_at_1 |
| value: 11.074 |
| - type: recall_at_10 |
| value: 26.479999999999997 |
| - type: recall_at_100 |
| value: 45.61 |
| - type: recall_at_1000 |
| value: 67.586 |
| - type: recall_at_3 |
| value: 17.377000000000002 |
| - type: recall_at_5 |
| value: 20.238 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB CQADupstackTexRetrieval |
| config: default |
| split: test |
| revision: 46989137a86843e03a6195de44b09deda022eec7 |
| metrics: |
| - type: map_at_1 |
| value: 7.303999999999999 |
| - type: map_at_10 |
| value: 10.779 |
| - type: map_at_100 |
| value: 11.484 |
| - type: map_at_1000 |
| value: 11.616 |
| - type: map_at_3 |
| value: 9.62 |
| - type: map_at_5 |
| value: 10.263 |
| - type: mrr_at_1 |
| value: 9.394 |
| - type: mrr_at_10 |
| value: 13.22 |
| - type: mrr_at_100 |
| value: 13.924 |
| - type: mrr_at_1000 |
| value: 14.032 |
| - type: mrr_at_3 |
| value: 11.912 |
| - type: mrr_at_5 |
| value: 12.671 |
| - type: ndcg_at_1 |
| value: 9.394 |
| - type: ndcg_at_10 |
| value: 13.276 |
| - type: ndcg_at_100 |
| value: 17.118 |
| - type: ndcg_at_1000 |
| value: 20.878 |
| - type: ndcg_at_3 |
| value: 11.084 |
| - type: ndcg_at_5 |
| value: 12.113999999999999 |
| - type: precision_at_1 |
| value: 9.394 |
| - type: precision_at_10 |
| value: 2.533 |
| - type: precision_at_100 |
| value: 0.538 |
| - type: precision_at_1000 |
| value: 0.10300000000000001 |
| - type: precision_at_3 |
| value: 5.391 |
| - type: precision_at_5 |
| value: 4.0329999999999995 |
| - type: recall_at_1 |
| value: 7.303999999999999 |
| - type: recall_at_10 |
| value: 18.523999999999997 |
| - type: recall_at_100 |
| value: 36.452 |
| - type: recall_at_1000 |
| value: 64.38199999999999 |
| - type: recall_at_3 |
| value: 12.366000000000001 |
| - type: recall_at_5 |
| value: 14.994 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB CQADupstackUnixRetrieval |
| config: default |
| split: test |
| revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
| metrics: |
| - type: map_at_1 |
| value: 12.963 |
| - type: map_at_10 |
| value: 17.46 |
| - type: map_at_100 |
| value: 18.297 |
| - type: map_at_1000 |
| value: 18.428 |
| - type: map_at_3 |
| value: 15.709999999999999 |
| - type: map_at_5 |
| value: 16.551 |
| - type: mrr_at_1 |
| value: 15.485 |
| - type: mrr_at_10 |
| value: 20.501 |
| - type: mrr_at_100 |
| value: 21.278 |
| - type: mrr_at_1000 |
| value: 21.379 |
| - type: mrr_at_3 |
| value: 18.548000000000002 |
| - type: mrr_at_5 |
| value: 19.537 |
| - type: ndcg_at_1 |
| value: 15.485 |
| - type: ndcg_at_10 |
| value: 20.994 |
| - type: ndcg_at_100 |
| value: 25.506 |
| - type: ndcg_at_1000 |
| value: 29.022 |
| - type: ndcg_at_3 |
| value: 17.410999999999998 |
| - type: ndcg_at_5 |
| value: 18.808 |
| - type: precision_at_1 |
| value: 15.485 |
| - type: precision_at_10 |
| value: 3.666 |
| - type: precision_at_100 |
| value: 0.662 |
| - type: precision_at_1000 |
| value: 0.109 |
| - type: precision_at_3 |
| value: 7.898 |
| - type: precision_at_5 |
| value: 5.672 |
| - type: recall_at_1 |
| value: 12.963 |
| - type: recall_at_10 |
| value: 29.201 |
| - type: recall_at_100 |
| value: 50.109 |
| - type: recall_at_1000 |
| value: 75.797 |
| - type: recall_at_3 |
| value: 18.989 |
| - type: recall_at_5 |
| value: 22.601 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB CQADupstackWebmastersRetrieval |
| config: default |
| split: test |
| revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
| metrics: |
| - type: map_at_1 |
| value: 15.260000000000002 |
| - type: map_at_10 |
| value: 21.165 |
| - type: map_at_100 |
| value: 22.400000000000002 |
| - type: map_at_1000 |
| value: 22.612 |
| - type: map_at_3 |
| value: 19.427 |
| - type: map_at_5 |
| value: 20.312 |
| - type: mrr_at_1 |
| value: 19.368 |
| - type: mrr_at_10 |
| value: 25.148 |
| - type: mrr_at_100 |
| value: 26.143 |
| - type: mrr_at_1000 |
| value: 26.235000000000003 |
| - type: mrr_at_3 |
| value: 23.584 |
| - type: mrr_at_5 |
| value: 24.433 |
| - type: ndcg_at_1 |
| value: 19.368 |
| - type: ndcg_at_10 |
| value: 25.239 |
| - type: ndcg_at_100 |
| value: 30.509999999999998 |
| - type: ndcg_at_1000 |
| value: 34.326 |
| - type: ndcg_at_3 |
| value: 22.57 |
| - type: ndcg_at_5 |
| value: 23.668 |
| - type: precision_at_1 |
| value: 19.368 |
| - type: precision_at_10 |
| value: 4.9799999999999995 |
| - type: precision_at_100 |
| value: 1.117 |
| - type: precision_at_1000 |
| value: 0.201 |
| - type: precision_at_3 |
| value: 11.067 |
| - type: precision_at_5 |
| value: 7.904999999999999 |
| - type: recall_at_1 |
| value: 15.260000000000002 |
| - type: recall_at_10 |
| value: 32.368 |
| - type: recall_at_100 |
| value: 56.908 |
| - type: recall_at_1000 |
| value: 82.708 |
| - type: recall_at_3 |
| value: 23.816000000000003 |
| - type: recall_at_5 |
| value: 27.191 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB CQADupstackWordpressRetrieval |
| config: default |
| split: test |
| revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
| metrics: |
| - type: map_at_1 |
| value: 10.049 |
| - type: map_at_10 |
| value: 14.834 |
| - type: map_at_100 |
| value: 15.656999999999998 |
| - type: map_at_1000 |
| value: 15.787 |
| - type: map_at_3 |
| value: 13.503000000000002 |
| - type: map_at_5 |
| value: 14.185 |
| - type: mrr_at_1 |
| value: 11.275 |
| - type: mrr_at_10 |
| value: 16.242 |
| - type: mrr_at_100 |
| value: 17.037 |
| - type: mrr_at_1000 |
| value: 17.152 |
| - type: mrr_at_3 |
| value: 14.787 |
| - type: mrr_at_5 |
| value: 15.591 |
| - type: ndcg_at_1 |
| value: 11.275 |
| - type: ndcg_at_10 |
| value: 17.704 |
| - type: ndcg_at_100 |
| value: 22.083 |
| - type: ndcg_at_1000 |
| value: 25.817 |
| - type: ndcg_at_3 |
| value: 14.921999999999999 |
| - type: ndcg_at_5 |
| value: 16.171 |
| - type: precision_at_1 |
| value: 11.275 |
| - type: precision_at_10 |
| value: 2.902 |
| - type: precision_at_100 |
| value: 0.553 |
| - type: precision_at_1000 |
| value: 0.096 |
| - type: precision_at_3 |
| value: 6.531000000000001 |
| - type: precision_at_5 |
| value: 4.695 |
| - type: recall_at_1 |
| value: 10.049 |
| - type: recall_at_10 |
| value: 25.224999999999998 |
| - type: recall_at_100 |
| value: 45.899 |
| - type: recall_at_1000 |
| value: 74.576 |
| - type: recall_at_3 |
| value: 17.726 |
| - type: recall_at_5 |
| value: 20.752000000000002 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB ClimateFEVER |
| config: default |
| split: test |
| revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
| metrics: |
| - type: map_at_1 |
| value: 6.762 |
| - type: map_at_10 |
| value: 12.867 |
| - type: map_at_100 |
| value: 14.478 |
| - type: map_at_1000 |
| value: 14.696000000000002 |
| - type: map_at_3 |
| value: 10.437000000000001 |
| - type: map_at_5 |
| value: 11.689 |
| - type: mrr_at_1 |
| value: 15.309000000000001 |
| - type: mrr_at_10 |
| value: 25.839000000000002 |
| - type: mrr_at_100 |
| value: 26.994 |
| - type: mrr_at_1000 |
| value: 27.056 |
| - type: mrr_at_3 |
| value: 22.400000000000002 |
| - type: mrr_at_5 |
| value: 24.451999999999998 |
| - type: ndcg_at_1 |
| value: 15.309000000000001 |
| - type: ndcg_at_10 |
| value: 19.384999999999998 |
| - type: ndcg_at_100 |
| value: 26.517000000000003 |
| - type: ndcg_at_1000 |
| value: 30.676 |
| - type: ndcg_at_3 |
| value: 14.876000000000001 |
| - type: ndcg_at_5 |
| value: 16.611 |
| - type: precision_at_1 |
| value: 15.309000000000001 |
| - type: precision_at_10 |
| value: 6.489000000000001 |
| - type: precision_at_100 |
| value: 1.409 |
| - type: precision_at_1000 |
| value: 0.217 |
| - type: precision_at_3 |
| value: 11.530999999999999 |
| - type: precision_at_5 |
| value: 9.381 |
| - type: recall_at_1 |
| value: 6.762 |
| - type: recall_at_10 |
| value: 24.996 |
| - type: recall_at_100 |
| value: 50.202999999999996 |
| - type: recall_at_1000 |
| value: 73.87899999999999 |
| - type: recall_at_3 |
| value: 14.149000000000001 |
| - type: recall_at_5 |
| value: 18.648 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB DBPedia |
| config: default |
| split: test |
| revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
| metrics: |
| - type: map_at_1 |
| value: 3.846 |
| - type: map_at_10 |
| value: 9.048 |
| - type: map_at_100 |
| value: 12.656 |
| - type: map_at_1000 |
| value: 13.605999999999998 |
| - type: map_at_3 |
| value: 6.293 |
| - type: map_at_5 |
| value: 7.5920000000000005 |
| - type: mrr_at_1 |
| value: 41.5 |
| - type: mrr_at_10 |
| value: 51.08200000000001 |
| - type: mrr_at_100 |
| value: 51.82299999999999 |
| - type: mrr_at_1000 |
| value: 51.856 |
| - type: mrr_at_3 |
| value: 48.5 |
| - type: mrr_at_5 |
| value: 49.836999999999996 |
| - type: ndcg_at_1 |
| value: 30.375000000000004 |
| - type: ndcg_at_10 |
| value: 23.343 |
| - type: ndcg_at_100 |
| value: 26.261000000000003 |
| - type: ndcg_at_1000 |
| value: 33.053 |
| - type: ndcg_at_3 |
| value: 25.814999999999998 |
| - type: ndcg_at_5 |
| value: 24.583 |
| - type: precision_at_1 |
| value: 41.5 |
| - type: precision_at_10 |
| value: 20.849999999999998 |
| - type: precision_at_100 |
| value: 6.635000000000001 |
| - type: precision_at_1000 |
| value: 1.438 |
| - type: precision_at_3 |
| value: 30.833 |
| - type: precision_at_5 |
| value: 26.85 |
| - type: recall_at_1 |
| value: 3.846 |
| - type: recall_at_10 |
| value: 13.83 |
| - type: recall_at_100 |
| value: 32.757999999999996 |
| - type: recall_at_1000 |
| value: 56.25 |
| - type: recall_at_3 |
| value: 7.574 |
| - type: recall_at_5 |
| value: 10.071 |
| - task: |
| type: Classification |
| dataset: |
| type: None |
| name: MTEB EmotionClassification |
| config: default |
| split: test |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
| metrics: |
| - type: accuracy |
| value: 46.62 |
| - type: f1 |
| value: 42.79767018915584 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB FEVER |
| config: default |
| split: test |
| revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
| metrics: |
| - type: map_at_1 |
| value: 15.677 |
| - type: map_at_10 |
| value: 23.551 |
| - type: map_at_100 |
| value: 24.442 |
| - type: map_at_1000 |
| value: 24.514 |
| - type: map_at_3 |
| value: 21.192 |
| - type: map_at_5 |
| value: 22.499 |
| - type: mrr_at_1 |
| value: 16.742 |
| - type: mrr_at_10 |
| value: 25.019000000000002 |
| - type: mrr_at_100 |
| value: 25.894000000000002 |
| - type: mrr_at_1000 |
| value: 25.958 |
| - type: mrr_at_3 |
| value: 22.555 |
| - type: mrr_at_5 |
| value: 23.909 |
| - type: ndcg_at_1 |
| value: 16.742 |
| - type: ndcg_at_10 |
| value: 28.247 |
| - type: ndcg_at_100 |
| value: 32.797 |
| - type: ndcg_at_1000 |
| value: 34.809 |
| - type: ndcg_at_3 |
| value: 23.358999999999998 |
| - type: ndcg_at_5 |
| value: 25.705 |
| - type: precision_at_1 |
| value: 16.742 |
| - type: precision_at_10 |
| value: 4.532 |
| - type: precision_at_100 |
| value: 0.701 |
| - type: precision_at_1000 |
| value: 0.089 |
| - type: precision_at_3 |
| value: 10.145999999999999 |
| - type: precision_at_5 |
| value: 7.342 |
| - type: recall_at_1 |
| value: 15.677 |
| - type: recall_at_10 |
| value: 41.571000000000005 |
| - type: recall_at_100 |
| value: 62.834999999999994 |
| - type: recall_at_1000 |
| value: 78.387 |
| - type: recall_at_3 |
| value: 28.214 |
| - type: recall_at_5 |
| value: 33.891 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB FiQA2018 |
| config: default |
| split: test |
| revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
| metrics: |
| - type: map_at_1 |
| value: 7.5520000000000005 |
| - type: map_at_10 |
| value: 12.378 |
| - type: map_at_100 |
| value: 13.572999999999999 |
| - type: map_at_1000 |
| value: 13.79 |
| - type: map_at_3 |
| value: 10.737 |
| - type: map_at_5 |
| value: 11.629000000000001 |
| - type: mrr_at_1 |
| value: 15.123000000000001 |
| - type: mrr_at_10 |
| value: 21.001 |
| - type: mrr_at_100 |
| value: 22.112000000000002 |
| - type: mrr_at_1000 |
| value: 22.21 |
| - type: mrr_at_3 |
| value: 19.264 |
| - type: mrr_at_5 |
| value: 20.166999999999998 |
| - type: ndcg_at_1 |
| value: 15.123000000000001 |
| - type: ndcg_at_10 |
| value: 16.699 |
| - type: ndcg_at_100 |
| value: 22.688 |
| - type: ndcg_at_1000 |
| value: 27.394000000000002 |
| - type: ndcg_at_3 |
| value: 14.516000000000002 |
| - type: ndcg_at_5 |
| value: 15.336 |
| - type: precision_at_1 |
| value: 15.123000000000001 |
| - type: precision_at_10 |
| value: 4.7219999999999995 |
| - type: precision_at_100 |
| value: 1.065 |
| - type: precision_at_1000 |
| value: 0.188 |
| - type: precision_at_3 |
| value: 9.825000000000001 |
| - type: precision_at_5 |
| value: 7.284 |
| - type: recall_at_1 |
| value: 7.5520000000000005 |
| - type: recall_at_10 |
| value: 20.887 |
| - type: recall_at_100 |
| value: 44.613 |
| - type: recall_at_1000 |
| value: 73.55699999999999 |
| - type: recall_at_3 |
| value: 13.715 |
| - type: recall_at_5 |
| value: 16.75 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB HotpotQA |
| config: default |
| split: test |
| revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
| metrics: |
| - type: map_at_1 |
| value: 15.314 |
| - type: map_at_10 |
| value: 21.73 |
| - type: map_at_100 |
| value: 22.595000000000002 |
| - type: map_at_1000 |
| value: 22.7 |
| - type: map_at_3 |
| value: 19.914 |
| - type: map_at_5 |
| value: 20.891000000000002 |
| - type: mrr_at_1 |
| value: 30.628 |
| - type: mrr_at_10 |
| value: 37.302 |
| - type: mrr_at_100 |
| value: 38.04 |
| - type: mrr_at_1000 |
| value: 38.102999999999994 |
| - type: mrr_at_3 |
| value: 35.445 |
| - type: mrr_at_5 |
| value: 36.464999999999996 |
| - type: ndcg_at_1 |
| value: 30.628 |
| - type: ndcg_at_10 |
| value: 27.986 |
| - type: ndcg_at_100 |
| value: 32.103 |
| - type: ndcg_at_1000 |
| value: 34.739 |
| - type: ndcg_at_3 |
| value: 24.48 |
| - type: ndcg_at_5 |
| value: 26.125 |
| - type: precision_at_1 |
| value: 30.628 |
| - type: precision_at_10 |
| value: 6.243 |
| - type: precision_at_100 |
| value: 0.955 |
| - type: precision_at_1000 |
| value: 0.131 |
| - type: precision_at_3 |
| value: 15.517 |
| - type: precision_at_5 |
| value: 10.613999999999999 |
| - type: recall_at_1 |
| value: 15.314 |
| - type: recall_at_10 |
| value: 31.215 |
| - type: recall_at_100 |
| value: 47.752 |
| - type: recall_at_1000 |
| value: 65.422 |
| - type: recall_at_3 |
| value: 23.275000000000002 |
| - type: recall_at_5 |
| value: 26.535999999999998 |
| - task: |
| type: Classification |
| dataset: |
| type: None |
| name: MTEB ImdbClassification |
| config: default |
| split: test |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
| metrics: |
| - type: accuracy |
| value: 61.661200000000015 |
| - type: ap |
| value: 57.26137842361126 |
| - type: f1 |
| value: 61.44069729315865 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB MSMARCO |
| config: default |
| split: dev |
| revision: c5a29a104738b98a9e76336939199e264163d4a0 |
| metrics: |
| - type: map_at_1 |
| value: 6.308999999999999 |
| - type: map_at_10 |
| value: 11.003 |
| - type: map_at_100 |
| value: 11.865 |
| - type: map_at_1000 |
| value: 11.974 |
| - type: map_at_3 |
| value: 9.309000000000001 |
| - type: map_at_5 |
| value: 10.145999999999999 |
| - type: mrr_at_1 |
| value: 6.5329999999999995 |
| - type: mrr_at_10 |
| value: 11.296000000000001 |
| - type: mrr_at_100 |
| value: 12.168 |
| - type: mrr_at_1000 |
| value: 12.273 |
| - type: mrr_at_3 |
| value: 9.582 |
| - type: mrr_at_5 |
| value: 10.42 |
| - type: ndcg_at_1 |
| value: 6.519 |
| - type: ndcg_at_10 |
| value: 13.998 |
| - type: ndcg_at_100 |
| value: 18.701 |
| - type: ndcg_at_1000 |
| value: 21.944 |
| - type: ndcg_at_3 |
| value: 10.383000000000001 |
| - type: ndcg_at_5 |
| value: 11.898 |
| - type: precision_at_1 |
| value: 6.519 |
| - type: precision_at_10 |
| value: 2.4330000000000003 |
| - type: precision_at_100 |
| value: 0.486 |
| - type: precision_at_1000 |
| value: 0.077 |
| - type: precision_at_3 |
| value: 4.585 |
| - type: precision_at_5 |
| value: 3.5130000000000003 |
| - type: recall_at_1 |
| value: 6.308999999999999 |
| - type: recall_at_10 |
| value: 23.381 |
| - type: recall_at_100 |
| value: 46.25 |
| - type: recall_at_1000 |
| value: 72.261 |
| - type: recall_at_3 |
| value: 13.239 |
| - type: recall_at_5 |
| value: 16.902 |
| - task: |
| type: Classification |
| dataset: |
| type: None |
| name: MTEB MTOPDomainClassification (en) |
| config: en |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 87.84313725490198 |
| - type: f1 |
| value: 87.24204022782286 |
| - task: |
| type: Classification |
| dataset: |
| type: None |
| name: MTEB MTOPIntentClassification (en) |
| config: en |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
| - type: accuracy |
| value: 56.409028727770185 |
| - type: f1 |
| value: 38.57449573016968 |
| - task: |
| type: Classification |
| dataset: |
| type: None |
| name: MTEB MassiveIntentClassification (en) |
| config: en |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
| - type: accuracy |
| value: 62.010759919300604 |
| - type: f1 |
| value: 60.290520300650584 |
| - task: |
| type: Classification |
| dataset: |
| type: None |
| name: MTEB MassiveScenarioClassification (en) |
| config: en |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 70.65232010759918 |
| - type: f1 |
| value: 69.36104886302014 |
| - task: |
| type: Clustering |
| dataset: |
| type: None |
| name: MTEB MedrxivClusteringP2P |
| config: default |
| split: test |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
| metrics: |
| - type: v_measure |
| value: 30.364401278066065 |
| - task: |
| type: Clustering |
| dataset: |
| type: None |
| name: MTEB MedrxivClusteringS2S |
| config: default |
| split: test |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
| metrics: |
| - type: v_measure |
| value: 28.00495863318603 |
| - task: |
| type: Reranking |
| dataset: |
| type: None |
| name: MTEB MindSmallReranking |
| config: default |
| split: test |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
| metrics: |
| - type: map |
| value: 30.917670435424853 |
| - type: mrr |
| value: 31.929615376181395 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB NFCorpus |
| config: default |
| split: test |
| revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
| metrics: |
| - type: map_at_1 |
| value: 4.279 |
| - type: map_at_10 |
| value: 8.491999999999999 |
| - type: map_at_100 |
| value: 10.969 |
| - type: map_at_1000 |
| value: 12.396 |
| - type: map_at_3 |
| value: 6.254999999999999 |
| - type: map_at_5 |
| value: 7.417 |
| - type: mrr_at_1 |
| value: 34.056 |
| - type: mrr_at_10 |
| value: 43.877 |
| - type: mrr_at_100 |
| value: 44.590999999999994 |
| - type: mrr_at_1000 |
| value: 44.651 |
| - type: mrr_at_3 |
| value: 41.382999999999996 |
| - type: mrr_at_5 |
| value: 42.838 |
| - type: ndcg_at_1 |
| value: 32.198 |
| - type: ndcg_at_10 |
| value: 25.971 |
| - type: ndcg_at_100 |
| value: 25.112000000000002 |
| - type: ndcg_at_1000 |
| value: 34.83 |
| - type: ndcg_at_3 |
| value: 29.018 |
| - type: ndcg_at_5 |
| value: 28.447 |
| - type: precision_at_1 |
| value: 34.056 |
| - type: precision_at_10 |
| value: 19.412 |
| - type: precision_at_100 |
| value: 7.053 |
| - type: precision_at_1000 |
| value: 2.061 |
| - type: precision_at_3 |
| value: 27.761000000000003 |
| - type: precision_at_5 |
| value: 25.076999999999998 |
| - type: recall_at_1 |
| value: 4.279 |
| - type: recall_at_10 |
| value: 12.917000000000002 |
| - type: recall_at_100 |
| value: 27.386 |
| - type: recall_at_1000 |
| value: 62.90599999999999 |
| - type: recall_at_3 |
| value: 7.234999999999999 |
| - type: recall_at_5 |
| value: 9.866 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB NQ |
| config: default |
| split: test |
| revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
| metrics: |
| - type: map_at_1 |
| value: 8.427 |
| - type: map_at_10 |
| value: 14.471 |
| - type: map_at_100 |
| value: 15.704 |
| - type: map_at_1000 |
| value: 15.809000000000001 |
| - type: map_at_3 |
| value: 12.059000000000001 |
| - type: map_at_5 |
| value: 13.288 |
| - type: mrr_at_1 |
| value: 9.647 |
| - type: mrr_at_10 |
| value: 16.064999999999998 |
| - type: mrr_at_100 |
| value: 17.212 |
| - type: mrr_at_1000 |
| value: 17.297 |
| - type: mrr_at_3 |
| value: 13.562 |
| - type: mrr_at_5 |
| value: 14.843 |
| - type: ndcg_at_1 |
| value: 9.647 |
| - type: ndcg_at_10 |
| value: 18.613 |
| - type: ndcg_at_100 |
| value: 24.834999999999997 |
| - type: ndcg_at_1000 |
| value: 27.716 |
| - type: ndcg_at_3 |
| value: 13.605 |
| - type: ndcg_at_5 |
| value: 15.797 |
| - type: precision_at_1 |
| value: 9.647 |
| - type: precision_at_10 |
| value: 3.531 |
| - type: precision_at_100 |
| value: 0.7060000000000001 |
| - type: precision_at_1000 |
| value: 0.098 |
| - type: precision_at_3 |
| value: 6.431000000000001 |
| - type: precision_at_5 |
| value: 5.093 |
| - type: recall_at_1 |
| value: 8.427 |
| - type: recall_at_10 |
| value: 29.995 |
| - type: recall_at_100 |
| value: 58.760999999999996 |
| - type: recall_at_1000 |
| value: 81.033 |
| - type: recall_at_3 |
| value: 16.621 |
| - type: recall_at_5 |
| value: 21.69 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB QuoraRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 63.709 |
| - type: map_at_10 |
| value: 76.66 |
| - type: map_at_100 |
| value: 77.444 |
| - type: map_at_1000 |
| value: 77.474 |
| - type: map_at_3 |
| value: 73.639 |
| - type: map_at_5 |
| value: 75.495 |
| - type: mrr_at_1 |
| value: 73.42 |
| - type: mrr_at_10 |
| value: 80.643 |
| - type: mrr_at_100 |
| value: 80.886 |
| - type: mrr_at_1000 |
| value: 80.891 |
| - type: mrr_at_3 |
| value: 79.163 |
| - type: mrr_at_5 |
| value: 80.132 |
| - type: ndcg_at_1 |
| value: 73.44000000000001 |
| - type: ndcg_at_10 |
| value: 81.26100000000001 |
| - type: ndcg_at_100 |
| value: 83.34 |
| - type: ndcg_at_1000 |
| value: 83.65599999999999 |
| - type: ndcg_at_3 |
| value: 77.593 |
| - type: ndcg_at_5 |
| value: 79.552 |
| - type: precision_at_1 |
| value: 73.44000000000001 |
| - type: precision_at_10 |
| value: 12.356 |
| - type: precision_at_100 |
| value: 1.472 |
| - type: precision_at_1000 |
| value: 0.155 |
| - type: precision_at_3 |
| value: 33.733000000000004 |
| - type: precision_at_5 |
| value: 22.398 |
| - type: recall_at_1 |
| value: 63.709 |
| - type: recall_at_10 |
| value: 90.24 |
| - type: recall_at_100 |
| value: 97.992 |
| - type: recall_at_1000 |
| value: 99.725 |
| - type: recall_at_3 |
| value: 79.843 |
| - type: recall_at_5 |
| value: 85.199 |
| - task: |
| type: Clustering |
| dataset: |
| type: None |
| name: MTEB RedditClustering |
| config: default |
| split: test |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| metrics: |
| - type: v_measure |
| value: 42.214155529412366 |
| - task: |
| type: Clustering |
| dataset: |
| type: None |
| name: MTEB RedditClusteringP2P |
| config: default |
| split: test |
| revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
| metrics: |
| - type: v_measure |
| value: 48.10171269080449 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB SCIDOCS |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 3.098 |
| - type: map_at_10 |
| value: 7.359999999999999 |
| - type: map_at_100 |
| value: 8.888 |
| - type: map_at_1000 |
| value: 9.158 |
| - type: map_at_3 |
| value: 5.406 |
| - type: map_at_5 |
| value: 6.308999999999999 |
| - type: mrr_at_1 |
| value: 15.2 |
| - type: mrr_at_10 |
| value: 23.508000000000003 |
| - type: mrr_at_100 |
| value: 24.709 |
| - type: mrr_at_1000 |
| value: 24.787 |
| - type: mrr_at_3 |
| value: 20.383000000000003 |
| - type: mrr_at_5 |
| value: 22.103 |
| - type: ndcg_at_1 |
| value: 15.2 |
| - type: ndcg_at_10 |
| value: 13.174 |
| - type: ndcg_at_100 |
| value: 19.885 |
| - type: ndcg_at_1000 |
| value: 25.247999999999998 |
| - type: ndcg_at_3 |
| value: 12.242 |
| - type: ndcg_at_5 |
| value: 10.702 |
| - type: precision_at_1 |
| value: 15.2 |
| - type: precision_at_10 |
| value: 6.93 |
| - type: precision_at_100 |
| value: 1.6709999999999998 |
| - type: precision_at_1000 |
| value: 0.296 |
| - type: precision_at_3 |
| value: 11.4 |
| - type: precision_at_5 |
| value: 9.379999999999999 |
| - type: recall_at_1 |
| value: 3.098 |
| - type: recall_at_10 |
| value: 14.048 |
| - type: recall_at_100 |
| value: 33.902 |
| - type: recall_at_1000 |
| value: 60.17 |
| - type: recall_at_3 |
| value: 6.9430000000000005 |
| - type: recall_at_5 |
| value: 9.498 |
| - task: |
| type: STS |
| dataset: |
| type: None |
| name: MTEB SICK-R |
| config: default |
| split: test |
| revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
| metrics: |
| - type: cos_sim_pearson |
| value: 76.69196724733715 |
| - type: cos_sim_spearman |
| value: 65.00669029968084 |
| - type: euclidean_pearson |
| value: 71.35623218354901 |
| - type: euclidean_spearman |
| value: 65.00662504036774 |
| - type: manhattan_pearson |
| value: 69.46286814034032 |
| - type: manhattan_spearman |
| value: 64.05091703970768 |
| - task: |
| type: STS |
| dataset: |
| type: None |
| name: MTEB STS12 |
| config: default |
| split: test |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| metrics: |
| - type: cos_sim_pearson |
| value: 75.45675254280496 |
| - type: cos_sim_spearman |
| value: 67.48465522195806 |
| - type: euclidean_pearson |
| value: 71.932572180082 |
| - type: euclidean_spearman |
| value: 67.48597260989263 |
| - type: manhattan_pearson |
| value: 70.01381315407934 |
| - type: manhattan_spearman |
| value: 66.83129276722313 |
| - task: |
| type: STS |
| dataset: |
| type: None |
| name: MTEB STS13 |
| config: default |
| split: test |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| metrics: |
| - type: cos_sim_pearson |
| value: 75.56784955823615 |
| - type: cos_sim_spearman |
| value: 77.1656947836492 |
| - type: euclidean_pearson |
| value: 76.86159714478943 |
| - type: euclidean_spearman |
| value: 77.16570697849755 |
| - type: manhattan_pearson |
| value: 77.05983226779968 |
| - type: manhattan_spearman |
| value: 77.43229771628044 |
| - task: |
| type: STS |
| dataset: |
| type: None |
| name: MTEB STS14 |
| config: default |
| split: test |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| metrics: |
| - type: cos_sim_pearson |
| value: 77.28801641888653 |
| - type: cos_sim_spearman |
| value: 72.72947194978411 |
| - type: euclidean_pearson |
| value: 76.2115552769551 |
| - type: euclidean_spearman |
| value: 72.72946226092458 |
| - type: manhattan_pearson |
| value: 75.19019262864614 |
| - type: manhattan_spearman |
| value: 72.18378967267259 |
| - task: |
| type: STS |
| dataset: |
| type: None |
| name: MTEB STS15 |
| config: default |
| split: test |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| metrics: |
| - type: cos_sim_pearson |
| value: 79.73471725204746 |
| - type: cos_sim_spearman |
| value: 80.79015625826382 |
| - type: euclidean_pearson |
| value: 80.81110611872813 |
| - type: euclidean_spearman |
| value: 80.79016252191039 |
| - type: manhattan_pearson |
| value: 79.93979968573043 |
| - type: manhattan_spearman |
| value: 80.07556394648903 |
| - task: |
| type: STS |
| dataset: |
| type: None |
| name: MTEB STS16 |
| config: default |
| split: test |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| metrics: |
| - type: cos_sim_pearson |
| value: 74.47923638473124 |
| - type: cos_sim_spearman |
| value: 75.71286196807024 |
| - type: euclidean_pearson |
| value: 75.83804880943377 |
| - type: euclidean_spearman |
| value: 75.71341236422742 |
| - type: manhattan_pearson |
| value: 75.93646913049322 |
| - type: manhattan_spearman |
| value: 75.85181752457555 |
| - task: |
| type: STS |
| dataset: |
| type: None |
| name: MTEB STS17 (en-en) |
| config: en-en |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 82.62219071209913 |
| - type: cos_sim_spearman |
| value: 83.44167690000958 |
| - type: euclidean_pearson |
| value: 83.28214784087085 |
| - type: euclidean_spearman |
| value: 83.44255138870209 |
| - type: manhattan_pearson |
| value: 82.77261607066816 |
| - type: manhattan_spearman |
| value: 83.06899474864443 |
| - task: |
| type: STS |
| dataset: |
| type: None |
| name: MTEB STS22 (en) |
| config: en |
| split: test |
| revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| metrics: |
| - type: cos_sim_pearson |
| value: 64.70345108985259 |
| - type: cos_sim_spearman |
| value: 62.482753044620786 |
| - type: euclidean_pearson |
| value: 64.79437494489187 |
| - type: euclidean_spearman |
| value: 62.482753044620786 |
| - type: manhattan_pearson |
| value: 63.71939825347573 |
| - type: manhattan_spearman |
| value: 61.174953862000336 |
| - task: |
| type: STS |
| dataset: |
| type: None |
| name: MTEB STSBenchmark |
| config: default |
| split: test |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
| metrics: |
| - type: cos_sim_pearson |
| value: 76.07865440954043 |
| - type: cos_sim_spearman |
| value: 74.54667758834077 |
| - type: euclidean_pearson |
| value: 76.48558570428264 |
| - type: euclidean_spearman |
| value: 74.54672598094477 |
| - type: manhattan_pearson |
| value: 76.06256712227383 |
| - type: manhattan_spearman |
| value: 74.42758128821515 |
| - task: |
| type: Reranking |
| dataset: |
| type: None |
| name: MTEB SciDocsRR |
| config: default |
| split: test |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| metrics: |
| - type: map |
| value: 75.15143418949978 |
| - type: mrr |
| value: 91.98409705762647 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB SciFact |
| config: default |
| split: test |
| revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
| metrics: |
| - type: map_at_1 |
| value: 33.417 |
| - type: map_at_10 |
| value: 42.594 |
| - type: map_at_100 |
| value: 43.535000000000004 |
| - type: map_at_1000 |
| value: 43.6 |
| - type: map_at_3 |
| value: 39.759 |
| - type: map_at_5 |
| value: 41.506 |
| - type: mrr_at_1 |
| value: 35.667 |
| - type: mrr_at_10 |
| value: 44.446000000000005 |
| - type: mrr_at_100 |
| value: 45.244 |
| - type: mrr_at_1000 |
| value: 45.300000000000004 |
| - type: mrr_at_3 |
| value: 42.167 |
| - type: mrr_at_5 |
| value: 43.5 |
| - type: ndcg_at_1 |
| value: 35.667 |
| - type: ndcg_at_10 |
| value: 47.591 |
| - type: ndcg_at_100 |
| value: 52.611 |
| - type: ndcg_at_1000 |
| value: 54.31 |
| - type: ndcg_at_3 |
| value: 42.356 |
| - type: ndcg_at_5 |
| value: 45.194 |
| - type: precision_at_1 |
| value: 35.667 |
| - type: precision_at_10 |
| value: 6.7669999999999995 |
| - type: precision_at_100 |
| value: 0.967 |
| - type: precision_at_1000 |
| value: 0.11100000000000002 |
| - type: precision_at_3 |
| value: 16.889000000000003 |
| - type: precision_at_5 |
| value: 11.799999999999999 |
| - type: recall_at_1 |
| value: 33.417 |
| - type: recall_at_10 |
| value: 61.260999999999996 |
| - type: recall_at_100 |
| value: 85.556 |
| - type: recall_at_1000 |
| value: 98.867 |
| - type: recall_at_3 |
| value: 47.528 |
| - type: recall_at_5 |
| value: 54.388999999999996 |
| - task: |
| type: PairClassification |
| dataset: |
| type: None |
| name: MTEB SprintDuplicateQuestions |
| config: default |
| split: test |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 99.73267326732673 |
| - type: cos_sim_ap |
| value: 92.36951341438333 |
| - type: cos_sim_f1 |
| value: 86.04073522106309 |
| - type: cos_sim_precision |
| value: 85.48864758144127 |
| - type: cos_sim_recall |
| value: 86.6 |
| - type: dot_accuracy |
| value: 99.73267326732673 |
| - type: dot_ap |
| value: 92.36951341438333 |
| - type: dot_f1 |
| value: 86.04073522106309 |
| - type: dot_precision |
| value: 85.48864758144127 |
| - type: dot_recall |
| value: 86.6 |
| - type: euclidean_accuracy |
| value: 99.73267326732673 |
| - type: euclidean_ap |
| value: 92.36951341438333 |
| - type: euclidean_f1 |
| value: 86.04073522106309 |
| - type: euclidean_precision |
| value: 85.48864758144127 |
| - type: euclidean_recall |
| value: 86.6 |
| - type: manhattan_accuracy |
| value: 99.74455445544554 |
| - type: manhattan_ap |
| value: 92.96894184904977 |
| - type: manhattan_f1 |
| value: 86.8917576961271 |
| - type: manhattan_precision |
| value: 86.29191321499013 |
| - type: manhattan_recall |
| value: 87.5 |
| - type: max_accuracy |
| value: 99.74455445544554 |
| - type: max_ap |
| value: 92.96894184904977 |
| - type: max_f1 |
| value: 86.8917576961271 |
| - task: |
| type: Clustering |
| dataset: |
| type: None |
| name: MTEB StackExchangeClustering |
| config: default |
| split: test |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
| metrics: |
| - type: v_measure |
| value: 45.349940718460374 |
| - task: |
| type: Clustering |
| dataset: |
| type: None |
| name: MTEB StackExchangeClusteringP2P |
| config: default |
| split: test |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
| metrics: |
| - type: v_measure |
| value: 31.266631844140036 |
| - task: |
| type: Reranking |
| dataset: |
| type: None |
| name: MTEB StackOverflowDupQuestions |
| config: default |
| split: test |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
| metrics: |
| - type: map |
| value: 42.02550203348626 |
| - type: mrr |
| value: 42.442651302945414 |
| - task: |
| type: Summarization |
| dataset: |
| type: None |
| name: MTEB SummEval |
| config: default |
| split: test |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
| metrics: |
| - type: cos_sim_pearson |
| value: 30.22842420698354 |
| - type: cos_sim_spearman |
| value: 30.568909812744543 |
| - type: dot_pearson |
| value: 30.228424144316747 |
| - type: dot_spearman |
| value: 30.619692862283827 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB TRECCOVID |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 0.125 |
| - type: map_at_10 |
| value: 0.86 |
| - type: map_at_100 |
| value: 4.665 |
| - type: map_at_1000 |
| value: 11.877 |
| - type: map_at_3 |
| value: 0.299 |
| - type: map_at_5 |
| value: 0.47200000000000003 |
| - type: mrr_at_1 |
| value: 50.0 |
| - type: mrr_at_10 |
| value: 64.711 |
| - type: mrr_at_100 |
| value: 65.065 |
| - type: mrr_at_1000 |
| value: 65.065 |
| - type: mrr_at_3 |
| value: 62.0 |
| - type: mrr_at_5 |
| value: 62.9 |
| - type: ndcg_at_1 |
| value: 43.0 |
| - type: ndcg_at_10 |
| value: 43.147999999999996 |
| - type: ndcg_at_100 |
| value: 33.417 |
| - type: ndcg_at_1000 |
| value: 31.341 |
| - type: ndcg_at_3 |
| value: 43.653999999999996 |
| - type: ndcg_at_5 |
| value: 43.21 |
| - type: precision_at_1 |
| value: 50.0 |
| - type: precision_at_10 |
| value: 48.199999999999996 |
| - type: precision_at_100 |
| value: 35.46 |
| - type: precision_at_1000 |
| value: 15.342 |
| - type: precision_at_3 |
| value: 48.0 |
| - type: precision_at_5 |
| value: 47.599999999999994 |
| - type: recall_at_1 |
| value: 0.125 |
| - type: recall_at_10 |
| value: 1.145 |
| - type: recall_at_100 |
| value: 7.727 |
| - type: recall_at_1000 |
| value: 30.742000000000004 |
| - type: recall_at_3 |
| value: 0.356 |
| - type: recall_at_5 |
| value: 0.5780000000000001 |
| - task: |
| type: Retrieval |
| dataset: |
| type: None |
| name: MTEB Touche2020 |
| config: default |
| split: test |
| revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
| metrics: |
| - type: map_at_1 |
| value: 1.585 |
| - type: map_at_10 |
| value: 7.398000000000001 |
| - type: map_at_100 |
| value: 13.603000000000002 |
| - type: map_at_1000 |
| value: 15.267 |
| - type: map_at_3 |
| value: 3.857 |
| - type: map_at_5 |
| value: 5.509 |
| - type: mrr_at_1 |
| value: 24.490000000000002 |
| - type: mrr_at_10 |
| value: 39.883 |
| - type: mrr_at_100 |
| value: 41.082 |
| - type: mrr_at_1000 |
| value: 41.082 |
| - type: mrr_at_3 |
| value: 35.034 |
| - type: mrr_at_5 |
| value: 37.483 |
| - type: ndcg_at_1 |
| value: 23.469 |
| - type: ndcg_at_10 |
| value: 21.221999999999998 |
| - type: ndcg_at_100 |
| value: 34.851 |
| - type: ndcg_at_1000 |
| value: 46.26 |
| - type: ndcg_at_3 |
| value: 21.906 |
| - type: ndcg_at_5 |
| value: 21.229 |
| - type: precision_at_1 |
| value: 24.490000000000002 |
| - type: precision_at_10 |
| value: 19.796 |
| - type: precision_at_100 |
| value: 8.122 |
| - type: precision_at_1000 |
| value: 1.541 |
| - type: precision_at_3 |
| value: 23.810000000000002 |
| - type: precision_at_5 |
| value: 22.041 |
| - type: recall_at_1 |
| value: 1.585 |
| - type: recall_at_10 |
| value: 13.664000000000001 |
| - type: recall_at_100 |
| value: 49.559 |
| - type: recall_at_1000 |
| value: 83.978 |
| - type: recall_at_3 |
| value: 5.088 |
| - type: recall_at_5 |
| value: 8.203000000000001 |
| - task: |
| type: Classification |
| dataset: |
| type: None |
| name: MTEB ToxicConversationsClassification |
| config: default |
| split: test |
| revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
| metrics: |
| - type: accuracy |
| value: 71.68520000000001 |
| - type: ap |
| value: 14.622321024533974 |
| - type: f1 |
| value: 55.1924859473184 |
| - task: |
| type: Classification |
| dataset: |
| type: None |
| name: MTEB TweetSentimentExtractionClassification |
| config: default |
| split: test |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| metrics: |
| - type: accuracy |
| value: 53.34748160724392 |
| - type: f1 |
| value: 53.518629300332755 |
| - task: |
| type: Clustering |
| dataset: |
| type: None |
| name: MTEB TwentyNewsgroupsClustering |
| config: default |
| split: test |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| metrics: |
| - type: v_measure |
| value: 40.22582442073446 |
| - task: |
| type: PairClassification |
| dataset: |
| type: None |
| name: MTEB TwitterSemEval2015 |
| config: default |
| split: test |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 82.46408773916671 |
| - type: cos_sim_ap |
| value: 60.57612839124909 |
| - type: cos_sim_f1 |
| value: 58.366606170598914 |
| - type: cos_sim_precision |
| value: 53.899441340782126 |
| - type: cos_sim_recall |
| value: 63.641160949868066 |
| - type: dot_accuracy |
| value: 82.46408773916671 |
| - type: dot_ap |
| value: 60.57612839124909 |
| - type: dot_f1 |
| value: 58.366606170598914 |
| - type: dot_precision |
| value: 53.899441340782126 |
| - type: dot_recall |
| value: 63.641160949868066 |
| - type: euclidean_accuracy |
| value: 82.46408773916671 |
| - type: euclidean_ap |
| value: 60.57612839124909 |
| - type: euclidean_f1 |
| value: 58.366606170598914 |
| - type: euclidean_precision |
| value: 53.899441340782126 |
| - type: euclidean_recall |
| value: 63.641160949868066 |
| - type: manhattan_accuracy |
| value: 81.68921738093819 |
| - type: manhattan_ap |
| value: 58.62502289564927 |
| - type: manhattan_f1 |
| value: 57.40318906605921 |
| - type: manhattan_precision |
| value: 50.50100200400801 |
| - type: manhattan_recall |
| value: 66.49076517150397 |
| - type: max_accuracy |
| value: 82.46408773916671 |
| - type: max_ap |
| value: 60.57612839124909 |
| - type: max_f1 |
| value: 58.366606170598914 |
| - task: |
| type: PairClassification |
| dataset: |
| type: None |
| name: MTEB TwitterURLCorpus |
| config: default |
| split: test |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
| metrics: |
| - type: cos_sim_accuracy |
| value: 86.89602980556526 |
| - type: cos_sim_ap |
| value: 81.92992391915341 |
| - type: cos_sim_f1 |
| value: 74.31139877741819 |
| - type: cos_sim_precision |
| value: 69.71393873971124 |
| - type: cos_sim_recall |
| value: 79.55805358792732 |
| - type: dot_accuracy |
| value: 86.89602980556526 |
| - type: dot_ap |
| value: 81.92992407440505 |
| - type: dot_f1 |
| value: 74.31139877741819 |
| - type: dot_precision |
| value: 69.71393873971124 |
| - type: dot_recall |
| value: 79.55805358792732 |
| - type: euclidean_accuracy |
| value: 86.89602980556526 |
| - type: euclidean_ap |
| value: 81.92992329073074 |
| - type: euclidean_f1 |
| value: 74.31139877741819 |
| - type: euclidean_precision |
| value: 69.71393873971124 |
| - type: euclidean_recall |
| value: 79.55805358792732 |
| - type: manhattan_accuracy |
| value: 86.94454146776886 |
| - type: manhattan_ap |
| value: 81.96535237136042 |
| - type: manhattan_f1 |
| value: 74.41181834761991 |
| - type: manhattan_precision |
| value: 70.70076939072572 |
| - type: manhattan_recall |
| value: 78.53403141361257 |
| - type: max_accuracy |
| value: 86.94454146776886 |
| - type: max_ap |
| value: 81.96535237136042 |
| - type: max_f1 |
| value: 74.41181834761991 |
| --- |
