| --- |
| language: |
| - en |
| library_name: sentence-transformers |
| license: mit |
| pipeline_tag: sentence-similarity |
| tags: |
| - feature-extraction |
| - mteb |
| - sentence-similarity |
| - sentence-transformers |
| - transformers |
| model-index: |
| - name: NoInstruct-small-Embedding-v0 |
| results: |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_counterfactual |
| name: MTEB AmazonCounterfactualClassification (en) |
| config: en |
| split: test |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
| metrics: |
| - type: accuracy |
| value: 75.76119402985074 |
| - type: ap |
| value: 39.03628777559392 |
| - type: f1 |
| value: 69.85860402259618 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_polarity |
| name: MTEB AmazonPolarityClassification |
| config: default |
| split: test |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
| metrics: |
| - type: accuracy |
| value: 93.29920000000001 |
| - type: ap |
| value: 90.03479490717608 |
| - type: f1 |
| value: 93.28554395248467 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (en) |
| config: en |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 49.98799999999999 |
| - type: f1 |
| value: 49.46151232451642 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/arguana |
| name: MTEB ArguAna |
| config: default |
| split: test |
| revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
| metrics: |
| - type: map_at_1 |
| value: 31.935000000000002 |
| - type: map_at_10 |
| value: 48.791000000000004 |
| - type: map_at_100 |
| value: 49.619 |
| - type: map_at_1000 |
| value: 49.623 |
| - type: map_at_3 |
| value: 44.334 |
| - type: map_at_5 |
| value: 46.908 |
| - type: mrr_at_1 |
| value: 32.93 |
| - type: mrr_at_10 |
| value: 49.158 |
| - type: mrr_at_100 |
| value: 50.00599999999999 |
| - type: mrr_at_1000 |
| value: 50.01 |
| - type: mrr_at_3 |
| value: 44.618 |
| - type: mrr_at_5 |
| value: 47.325 |
| - type: ndcg_at_1 |
| value: 31.935000000000002 |
| - type: ndcg_at_10 |
| value: 57.593 |
| - type: ndcg_at_100 |
| value: 60.841 |
| - type: ndcg_at_1000 |
| value: 60.924 |
| - type: ndcg_at_3 |
| value: 48.416 |
| - type: ndcg_at_5 |
| value: 53.05 |
| - type: precision_at_1 |
| value: 31.935000000000002 |
| - type: precision_at_10 |
| value: 8.549 |
| - type: precision_at_100 |
| value: 0.9900000000000001 |
| - type: precision_at_1000 |
| value: 0.1 |
| - type: precision_at_3 |
| value: 20.081 |
| - type: precision_at_5 |
| value: 14.296000000000001 |
| - type: recall_at_1 |
| value: 31.935000000000002 |
| - type: recall_at_10 |
| value: 85.491 |
| - type: recall_at_100 |
| value: 99.004 |
| - type: recall_at_1000 |
| value: 99.644 |
| - type: recall_at_3 |
| value: 60.242 |
| - type: recall_at_5 |
| value: 71.479 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-p2p |
| name: MTEB ArxivClusteringP2P |
| config: default |
| split: test |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| metrics: |
| - type: v_measure |
| value: 47.78438534940855 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-s2s |
| name: MTEB ArxivClusteringS2S |
| config: default |
| split: test |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
| metrics: |
| - type: v_measure |
| value: 40.12916178519471 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/askubuntudupquestions-reranking |
| name: MTEB AskUbuntuDupQuestions |
| config: default |
| split: test |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
| metrics: |
| - type: map |
| value: 62.125361608299855 |
| - type: mrr |
| value: 74.92525172580574 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/biosses-sts |
| name: MTEB BIOSSES |
| config: default |
| split: test |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
| metrics: |
| - type: cos_sim_pearson |
| value: 88.64322910336641 |
| - type: cos_sim_spearman |
| value: 87.20138453306345 |
| - type: euclidean_pearson |
| value: 87.08547818178234 |
| - type: euclidean_spearman |
| value: 87.17066094143931 |
| - type: manhattan_pearson |
| value: 87.30053110771618 |
| - type: manhattan_spearman |
| value: 86.86824441211934 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/banking77 |
| name: MTEB Banking77Classification |
| config: default |
| split: test |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| metrics: |
| - type: accuracy |
| value: 86.3961038961039 |
| - type: f1 |
| value: 86.3669961645295 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-p2p |
| name: MTEB BiorxivClusteringP2P |
| config: default |
| split: test |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| metrics: |
| - type: v_measure |
| value: 39.40291404289857 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-s2s |
| name: MTEB BiorxivClusteringS2S |
| config: default |
| split: test |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
| metrics: |
| - type: v_measure |
| value: 35.102356817746816 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-android |
| name: MTEB CQADupstackAndroidRetrieval |
| config: default |
| split: test |
| revision: f46a197baaae43b4f621051089b82a364682dfeb |
| metrics: |
| - type: map_at_1 |
| value: 31.013 |
| - type: map_at_10 |
| value: 42.681999999999995 |
| - type: map_at_100 |
| value: 44.24 |
| - type: map_at_1000 |
| value: 44.372 |
| - type: map_at_3 |
| value: 39.181 |
| - type: map_at_5 |
| value: 41.071999999999996 |
| - type: mrr_at_1 |
| value: 38.196999999999996 |
| - type: mrr_at_10 |
| value: 48.604 |
| - type: mrr_at_100 |
| value: 49.315 |
| - type: mrr_at_1000 |
| value: 49.363 |
| - type: mrr_at_3 |
| value: 45.756 |
| - type: mrr_at_5 |
| value: 47.43 |
| - type: ndcg_at_1 |
| value: 38.196999999999996 |
| - type: ndcg_at_10 |
| value: 49.344 |
| - type: ndcg_at_100 |
| value: 54.662 |
| - type: ndcg_at_1000 |
| value: 56.665 |
| - type: ndcg_at_3 |
| value: 44.146 |
| - type: ndcg_at_5 |
| value: 46.514 |
| - type: precision_at_1 |
| value: 38.196999999999996 |
| - type: precision_at_10 |
| value: 9.571 |
| - type: precision_at_100 |
| value: 1.542 |
| - type: precision_at_1000 |
| value: 0.202 |
| - type: precision_at_3 |
| value: 21.364 |
| - type: precision_at_5 |
| value: 15.336 |
| - type: recall_at_1 |
| value: 31.013 |
| - type: recall_at_10 |
| value: 61.934999999999995 |
| - type: recall_at_100 |
| value: 83.923 |
| - type: recall_at_1000 |
| value: 96.601 |
| - type: recall_at_3 |
| value: 46.86 |
| - type: recall_at_5 |
| value: 53.620000000000005 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-english |
| name: MTEB CQADupstackEnglishRetrieval |
| config: default |
| split: test |
| revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
| metrics: |
| - type: map_at_1 |
| value: 29.84 |
| - type: map_at_10 |
| value: 39.335 |
| - type: map_at_100 |
| value: 40.647 |
| - type: map_at_1000 |
| value: 40.778 |
| - type: map_at_3 |
| value: 36.556 |
| - type: map_at_5 |
| value: 38.048 |
| - type: mrr_at_1 |
| value: 36.815 |
| - type: mrr_at_10 |
| value: 45.175 |
| - type: mrr_at_100 |
| value: 45.907 |
| - type: mrr_at_1000 |
| value: 45.946999999999996 |
| - type: mrr_at_3 |
| value: 42.909000000000006 |
| - type: mrr_at_5 |
| value: 44.227 |
| - type: ndcg_at_1 |
| value: 36.815 |
| - type: ndcg_at_10 |
| value: 44.783 |
| - type: ndcg_at_100 |
| value: 49.551 |
| - type: ndcg_at_1000 |
| value: 51.612 |
| - type: ndcg_at_3 |
| value: 40.697 |
| - type: ndcg_at_5 |
| value: 42.558 |
| - type: precision_at_1 |
| value: 36.815 |
| - type: precision_at_10 |
| value: 8.363 |
| - type: precision_at_100 |
| value: 1.385 |
| - type: precision_at_1000 |
| value: 0.186 |
| - type: precision_at_3 |
| value: 19.342000000000002 |
| - type: precision_at_5 |
| value: 13.706999999999999 |
| - type: recall_at_1 |
| value: 29.84 |
| - type: recall_at_10 |
| value: 54.164 |
| - type: recall_at_100 |
| value: 74.36 |
| - type: recall_at_1000 |
| value: 87.484 |
| - type: recall_at_3 |
| value: 42.306 |
| - type: recall_at_5 |
| value: 47.371 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-gaming |
| name: MTEB CQADupstackGamingRetrieval |
| config: default |
| split: test |
| revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
| metrics: |
| - type: map_at_1 |
| value: 39.231 |
| - type: map_at_10 |
| value: 51.44800000000001 |
| - type: map_at_100 |
| value: 52.574 |
| - type: map_at_1000 |
| value: 52.629999999999995 |
| - type: map_at_3 |
| value: 48.077 |
| - type: map_at_5 |
| value: 50.019000000000005 |
| - type: mrr_at_1 |
| value: 44.89 |
| - type: mrr_at_10 |
| value: 54.803000000000004 |
| - type: mrr_at_100 |
| value: 55.556000000000004 |
| - type: mrr_at_1000 |
| value: 55.584 |
| - type: mrr_at_3 |
| value: 52.32 |
| - type: mrr_at_5 |
| value: 53.846000000000004 |
| - type: ndcg_at_1 |
| value: 44.89 |
| - type: ndcg_at_10 |
| value: 57.228 |
| - type: ndcg_at_100 |
| value: 61.57 |
| - type: ndcg_at_1000 |
| value: 62.613 |
| - type: ndcg_at_3 |
| value: 51.727000000000004 |
| - type: ndcg_at_5 |
| value: 54.496 |
| - type: precision_at_1 |
| value: 44.89 |
| - type: precision_at_10 |
| value: 9.266 |
| - type: precision_at_100 |
| value: 1.2309999999999999 |
| - type: precision_at_1000 |
| value: 0.136 |
| - type: precision_at_3 |
| value: 23.051 |
| - type: precision_at_5 |
| value: 15.987000000000002 |
| - type: recall_at_1 |
| value: 39.231 |
| - type: recall_at_10 |
| value: 70.82000000000001 |
| - type: recall_at_100 |
| value: 89.446 |
| - type: recall_at_1000 |
| value: 96.665 |
| - type: recall_at_3 |
| value: 56.40500000000001 |
| - type: recall_at_5 |
| value: 62.993 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-gis |
| name: MTEB CQADupstackGisRetrieval |
| config: default |
| split: test |
| revision: 5003b3064772da1887988e05400cf3806fe491f2 |
| metrics: |
| - type: map_at_1 |
| value: 25.296000000000003 |
| - type: map_at_10 |
| value: 34.021 |
| - type: map_at_100 |
| value: 35.158 |
| - type: map_at_1000 |
| value: 35.233 |
| - type: map_at_3 |
| value: 31.424999999999997 |
| - type: map_at_5 |
| value: 33.046 |
| - type: mrr_at_1 |
| value: 27.232 |
| - type: mrr_at_10 |
| value: 36.103 |
| - type: mrr_at_100 |
| value: 37.076 |
| - type: mrr_at_1000 |
| value: 37.135 |
| - type: mrr_at_3 |
| value: 33.635 |
| - type: mrr_at_5 |
| value: 35.211 |
| - type: ndcg_at_1 |
| value: 27.232 |
| - type: ndcg_at_10 |
| value: 38.878 |
| - type: ndcg_at_100 |
| value: 44.284 |
| - type: ndcg_at_1000 |
| value: 46.268 |
| - type: ndcg_at_3 |
| value: 33.94 |
| - type: ndcg_at_5 |
| value: 36.687 |
| - type: precision_at_1 |
| value: 27.232 |
| - type: precision_at_10 |
| value: 5.921 |
| - type: precision_at_100 |
| value: 0.907 |
| - type: precision_at_1000 |
| value: 0.11199999999999999 |
| - type: precision_at_3 |
| value: 14.426 |
| - type: precision_at_5 |
| value: 10.215 |
| - type: recall_at_1 |
| value: 25.296000000000003 |
| - type: recall_at_10 |
| value: 51.708 |
| - type: recall_at_100 |
| value: 76.36699999999999 |
| - type: recall_at_1000 |
| value: 91.306 |
| - type: recall_at_3 |
| value: 38.651 |
| - type: recall_at_5 |
| value: 45.201 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-mathematica |
| name: MTEB CQADupstackMathematicaRetrieval |
| config: default |
| split: test |
| revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
| metrics: |
| - type: map_at_1 |
| value: 16.24 |
| - type: map_at_10 |
| value: 24.696 |
| - type: map_at_100 |
| value: 25.945 |
| - type: map_at_1000 |
| value: 26.069 |
| - type: map_at_3 |
| value: 22.542 |
| - type: map_at_5 |
| value: 23.526 |
| - type: mrr_at_1 |
| value: 20.149 |
| - type: mrr_at_10 |
| value: 29.584 |
| - type: mrr_at_100 |
| value: 30.548 |
| - type: mrr_at_1000 |
| value: 30.618000000000002 |
| - type: mrr_at_3 |
| value: 27.301 |
| - type: mrr_at_5 |
| value: 28.563 |
| - type: ndcg_at_1 |
| value: 20.149 |
| - type: ndcg_at_10 |
| value: 30.029 |
| - type: ndcg_at_100 |
| value: 35.812 |
| - type: ndcg_at_1000 |
| value: 38.755 |
| - type: ndcg_at_3 |
| value: 26.008 |
| - type: ndcg_at_5 |
| value: 27.517000000000003 |
| - type: precision_at_1 |
| value: 20.149 |
| - type: precision_at_10 |
| value: 5.647 |
| - type: precision_at_100 |
| value: 0.968 |
| - type: precision_at_1000 |
| value: 0.136 |
| - type: precision_at_3 |
| value: 12.934999999999999 |
| - type: precision_at_5 |
| value: 8.955 |
| - type: recall_at_1 |
| value: 16.24 |
| - type: recall_at_10 |
| value: 41.464 |
| - type: recall_at_100 |
| value: 66.781 |
| - type: recall_at_1000 |
| value: 87.85300000000001 |
| - type: recall_at_3 |
| value: 29.822 |
| - type: recall_at_5 |
| value: 34.096 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-physics |
| name: MTEB CQADupstackPhysicsRetrieval |
| config: default |
| split: test |
| revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
| metrics: |
| - type: map_at_1 |
| value: 29.044999999999998 |
| - type: map_at_10 |
| value: 39.568999999999996 |
| - type: map_at_100 |
| value: 40.831 |
| - type: map_at_1000 |
| value: 40.948 |
| - type: map_at_3 |
| value: 36.495 |
| - type: map_at_5 |
| value: 38.21 |
| - type: mrr_at_1 |
| value: 35.611 |
| - type: mrr_at_10 |
| value: 45.175 |
| - type: mrr_at_100 |
| value: 45.974 |
| - type: mrr_at_1000 |
| value: 46.025 |
| - type: mrr_at_3 |
| value: 42.765 |
| - type: mrr_at_5 |
| value: 44.151 |
| - type: ndcg_at_1 |
| value: 35.611 |
| - type: ndcg_at_10 |
| value: 45.556999999999995 |
| - type: ndcg_at_100 |
| value: 50.86000000000001 |
| - type: ndcg_at_1000 |
| value: 52.983000000000004 |
| - type: ndcg_at_3 |
| value: 40.881 |
| - type: ndcg_at_5 |
| value: 43.035000000000004 |
| - type: precision_at_1 |
| value: 35.611 |
| - type: precision_at_10 |
| value: 8.306 |
| - type: precision_at_100 |
| value: 1.276 |
| - type: precision_at_1000 |
| value: 0.165 |
| - type: precision_at_3 |
| value: 19.57 |
| - type: precision_at_5 |
| value: 13.725000000000001 |
| - type: recall_at_1 |
| value: 29.044999999999998 |
| - type: recall_at_10 |
| value: 57.513999999999996 |
| - type: recall_at_100 |
| value: 80.152 |
| - type: recall_at_1000 |
| value: 93.982 |
| - type: recall_at_3 |
| value: 44.121 |
| - type: recall_at_5 |
| value: 50.007000000000005 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-programmers |
| name: MTEB CQADupstackProgrammersRetrieval |
| config: default |
| split: test |
| revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
| metrics: |
| - type: map_at_1 |
| value: 22.349 |
| - type: map_at_10 |
| value: 33.434000000000005 |
| - type: map_at_100 |
| value: 34.8 |
| - type: map_at_1000 |
| value: 34.919 |
| - type: map_at_3 |
| value: 30.348000000000003 |
| - type: map_at_5 |
| value: 31.917 |
| - type: mrr_at_1 |
| value: 28.195999999999998 |
| - type: mrr_at_10 |
| value: 38.557 |
| - type: mrr_at_100 |
| value: 39.550999999999995 |
| - type: mrr_at_1000 |
| value: 39.607 |
| - type: mrr_at_3 |
| value: 36.035000000000004 |
| - type: mrr_at_5 |
| value: 37.364999999999995 |
| - type: ndcg_at_1 |
| value: 28.195999999999998 |
| - type: ndcg_at_10 |
| value: 39.656000000000006 |
| - type: ndcg_at_100 |
| value: 45.507999999999996 |
| - type: ndcg_at_1000 |
| value: 47.848 |
| - type: ndcg_at_3 |
| value: 34.609 |
| - type: ndcg_at_5 |
| value: 36.65 |
| - type: precision_at_1 |
| value: 28.195999999999998 |
| - type: precision_at_10 |
| value: 7.534000000000001 |
| - type: precision_at_100 |
| value: 1.217 |
| - type: precision_at_1000 |
| value: 0.158 |
| - type: precision_at_3 |
| value: 17.085 |
| - type: precision_at_5 |
| value: 12.169 |
| - type: recall_at_1 |
| value: 22.349 |
| - type: recall_at_10 |
| value: 53.127 |
| - type: recall_at_100 |
| value: 77.884 |
| - type: recall_at_1000 |
| value: 93.705 |
| - type: recall_at_3 |
| value: 38.611000000000004 |
| - type: recall_at_5 |
| value: 44.182 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack |
| name: MTEB CQADupstackRetrieval |
| config: default |
| split: test |
| revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
| metrics: |
| - type: map_at_1 |
| value: 25.215749999999996 |
| - type: map_at_10 |
| value: 34.332750000000004 |
| - type: map_at_100 |
| value: 35.58683333333333 |
| - type: map_at_1000 |
| value: 35.70458333333333 |
| - type: map_at_3 |
| value: 31.55441666666667 |
| - type: map_at_5 |
| value: 33.100833333333334 |
| - type: mrr_at_1 |
| value: 29.697250000000004 |
| - type: mrr_at_10 |
| value: 38.372249999999994 |
| - type: mrr_at_100 |
| value: 39.26708333333334 |
| - type: mrr_at_1000 |
| value: 39.3265 |
| - type: mrr_at_3 |
| value: 35.946083333333334 |
| - type: mrr_at_5 |
| value: 37.336999999999996 |
| - type: ndcg_at_1 |
| value: 29.697250000000004 |
| - type: ndcg_at_10 |
| value: 39.64575 |
| - type: ndcg_at_100 |
| value: 44.996833333333335 |
| - type: ndcg_at_1000 |
| value: 47.314499999999995 |
| - type: ndcg_at_3 |
| value: 34.93383333333334 |
| - type: ndcg_at_5 |
| value: 37.15291666666667 |
| - type: precision_at_1 |
| value: 29.697250000000004 |
| - type: precision_at_10 |
| value: 6.98825 |
| - type: precision_at_100 |
| value: 1.138 |
| - type: precision_at_1000 |
| value: 0.15283333333333332 |
| - type: precision_at_3 |
| value: 16.115583333333333 |
| - type: precision_at_5 |
| value: 11.460916666666666 |
| - type: recall_at_1 |
| value: 25.215749999999996 |
| - type: recall_at_10 |
| value: 51.261250000000004 |
| - type: recall_at_100 |
| value: 74.67258333333334 |
| - type: recall_at_1000 |
| value: 90.72033333333334 |
| - type: recall_at_3 |
| value: 38.1795 |
| - type: recall_at_5 |
| value: 43.90658333333334 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-stats |
| name: MTEB CQADupstackStatsRetrieval |
| config: default |
| split: test |
| revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
| metrics: |
| - type: map_at_1 |
| value: 24.352 |
| - type: map_at_10 |
| value: 30.576999999999998 |
| - type: map_at_100 |
| value: 31.545 |
| - type: map_at_1000 |
| value: 31.642 |
| - type: map_at_3 |
| value: 28.605000000000004 |
| - type: map_at_5 |
| value: 29.828 |
| - type: mrr_at_1 |
| value: 26.994 |
| - type: mrr_at_10 |
| value: 33.151 |
| - type: mrr_at_100 |
| value: 33.973 |
| - type: mrr_at_1000 |
| value: 34.044999999999995 |
| - type: mrr_at_3 |
| value: 31.135 |
| - type: mrr_at_5 |
| value: 32.262 |
| - type: ndcg_at_1 |
| value: 26.994 |
| - type: ndcg_at_10 |
| value: 34.307 |
| - type: ndcg_at_100 |
| value: 39.079 |
| - type: ndcg_at_1000 |
| value: 41.548 |
| - type: ndcg_at_3 |
| value: 30.581000000000003 |
| - type: ndcg_at_5 |
| value: 32.541 |
| - type: precision_at_1 |
| value: 26.994 |
| - type: precision_at_10 |
| value: 5.244999999999999 |
| - type: precision_at_100 |
| value: 0.831 |
| - type: precision_at_1000 |
| value: 0.11100000000000002 |
| - type: precision_at_3 |
| value: 12.781 |
| - type: precision_at_5 |
| value: 9.017999999999999 |
| - type: recall_at_1 |
| value: 24.352 |
| - type: recall_at_10 |
| value: 43.126999999999995 |
| - type: recall_at_100 |
| value: 64.845 |
| - type: recall_at_1000 |
| value: 83.244 |
| - type: recall_at_3 |
| value: 33.308 |
| - type: recall_at_5 |
| value: 37.984 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-tex |
| name: MTEB CQADupstackTexRetrieval |
| config: default |
| split: test |
| revision: 46989137a86843e03a6195de44b09deda022eec7 |
| metrics: |
| - type: map_at_1 |
| value: 16.592000000000002 |
| - type: map_at_10 |
| value: 23.29 |
| - type: map_at_100 |
| value: 24.423000000000002 |
| - type: map_at_1000 |
| value: 24.554000000000002 |
| - type: map_at_3 |
| value: 20.958 |
| - type: map_at_5 |
| value: 22.267 |
| - type: mrr_at_1 |
| value: 20.061999999999998 |
| - type: mrr_at_10 |
| value: 26.973999999999997 |
| - type: mrr_at_100 |
| value: 27.944999999999997 |
| - type: mrr_at_1000 |
| value: 28.023999999999997 |
| - type: mrr_at_3 |
| value: 24.839 |
| - type: mrr_at_5 |
| value: 26.033 |
| - type: ndcg_at_1 |
| value: 20.061999999999998 |
| - type: ndcg_at_10 |
| value: 27.682000000000002 |
| - type: ndcg_at_100 |
| value: 33.196 |
| - type: ndcg_at_1000 |
| value: 36.246 |
| - type: ndcg_at_3 |
| value: 23.559 |
| - type: ndcg_at_5 |
| value: 25.507 |
| - type: precision_at_1 |
| value: 20.061999999999998 |
| - type: precision_at_10 |
| value: 5.086 |
| - type: precision_at_100 |
| value: 0.9249999999999999 |
| - type: precision_at_1000 |
| value: 0.136 |
| - type: precision_at_3 |
| value: 11.046 |
| - type: precision_at_5 |
| value: 8.149000000000001 |
| - type: recall_at_1 |
| value: 16.592000000000002 |
| - type: recall_at_10 |
| value: 37.181999999999995 |
| - type: recall_at_100 |
| value: 62.224999999999994 |
| - type: recall_at_1000 |
| value: 84.072 |
| - type: recall_at_3 |
| value: 25.776 |
| - type: recall_at_5 |
| value: 30.680000000000003 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-unix |
| name: MTEB CQADupstackUnixRetrieval |
| config: default |
| split: test |
| revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
| metrics: |
| - type: map_at_1 |
| value: 26.035999999999998 |
| - type: map_at_10 |
| value: 34.447 |
| - type: map_at_100 |
| value: 35.697 |
| - type: map_at_1000 |
| value: 35.802 |
| - type: map_at_3 |
| value: 31.64 |
| - type: map_at_5 |
| value: 33.056999999999995 |
| - type: mrr_at_1 |
| value: 29.851 |
| - type: mrr_at_10 |
| value: 38.143 |
| - type: mrr_at_100 |
| value: 39.113 |
| - type: mrr_at_1000 |
| value: 39.175 |
| - type: mrr_at_3 |
| value: 35.665 |
| - type: mrr_at_5 |
| value: 36.901 |
| - type: ndcg_at_1 |
| value: 29.851 |
| - type: ndcg_at_10 |
| value: 39.554 |
| - type: ndcg_at_100 |
| value: 45.091 |
| - type: ndcg_at_1000 |
| value: 47.504000000000005 |
| - type: ndcg_at_3 |
| value: 34.414 |
| - type: ndcg_at_5 |
| value: 36.508 |
| - type: precision_at_1 |
| value: 29.851 |
| - type: precision_at_10 |
| value: 6.614000000000001 |
| - type: precision_at_100 |
| value: 1.051 |
| - type: precision_at_1000 |
| value: 0.13699999999999998 |
| - type: precision_at_3 |
| value: 15.329999999999998 |
| - type: precision_at_5 |
| value: 10.671999999999999 |
| - type: recall_at_1 |
| value: 26.035999999999998 |
| - type: recall_at_10 |
| value: 51.396 |
| - type: recall_at_100 |
| value: 75.09 |
| - type: recall_at_1000 |
| value: 91.904 |
| - type: recall_at_3 |
| value: 37.378 |
| - type: recall_at_5 |
| value: 42.69 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-webmasters |
| name: MTEB CQADupstackWebmastersRetrieval |
| config: default |
| split: test |
| revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
| metrics: |
| - type: map_at_1 |
| value: 23.211000000000002 |
| - type: map_at_10 |
| value: 32.231 |
| - type: map_at_100 |
| value: 33.772999999999996 |
| - type: map_at_1000 |
| value: 33.982 |
| - type: map_at_3 |
| value: 29.128 |
| - type: map_at_5 |
| value: 31.002999999999997 |
| - type: mrr_at_1 |
| value: 27.668 |
| - type: mrr_at_10 |
| value: 36.388 |
| - type: mrr_at_100 |
| value: 37.384 |
| - type: mrr_at_1000 |
| value: 37.44 |
| - type: mrr_at_3 |
| value: 33.762 |
| - type: mrr_at_5 |
| value: 35.234 |
| - type: ndcg_at_1 |
| value: 27.668 |
| - type: ndcg_at_10 |
| value: 38.043 |
| - type: ndcg_at_100 |
| value: 44.21 |
| - type: ndcg_at_1000 |
| value: 46.748 |
| - type: ndcg_at_3 |
| value: 32.981 |
| - type: ndcg_at_5 |
| value: 35.58 |
| - type: precision_at_1 |
| value: 27.668 |
| - type: precision_at_10 |
| value: 7.352 |
| - type: precision_at_100 |
| value: 1.5 |
| - type: precision_at_1000 |
| value: 0.23700000000000002 |
| - type: precision_at_3 |
| value: 15.613 |
| - type: precision_at_5 |
| value: 11.501999999999999 |
| - type: recall_at_1 |
| value: 23.211000000000002 |
| - type: recall_at_10 |
| value: 49.851 |
| - type: recall_at_100 |
| value: 77.596 |
| - type: recall_at_1000 |
| value: 93.683 |
| - type: recall_at_3 |
| value: 35.403 |
| - type: recall_at_5 |
| value: 42.485 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-wordpress |
| name: MTEB CQADupstackWordpressRetrieval |
| config: default |
| split: test |
| revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
| metrics: |
| - type: map_at_1 |
| value: 19.384 |
| - type: map_at_10 |
| value: 26.262999999999998 |
| - type: map_at_100 |
| value: 27.409 |
| - type: map_at_1000 |
| value: 27.526 |
| - type: map_at_3 |
| value: 23.698 |
| - type: map_at_5 |
| value: 25.217 |
| - type: mrr_at_1 |
| value: 20.702 |
| - type: mrr_at_10 |
| value: 27.810000000000002 |
| - type: mrr_at_100 |
| value: 28.863 |
| - type: mrr_at_1000 |
| value: 28.955 |
| - type: mrr_at_3 |
| value: 25.230999999999998 |
| - type: mrr_at_5 |
| value: 26.821 |
| - type: ndcg_at_1 |
| value: 20.702 |
| - type: ndcg_at_10 |
| value: 30.688 |
| - type: ndcg_at_100 |
| value: 36.138999999999996 |
| - type: ndcg_at_1000 |
| value: 38.984 |
| - type: ndcg_at_3 |
| value: 25.663000000000004 |
| - type: ndcg_at_5 |
| value: 28.242 |
| - type: precision_at_1 |
| value: 20.702 |
| - type: precision_at_10 |
| value: 4.954 |
| - type: precision_at_100 |
| value: 0.823 |
| - type: precision_at_1000 |
| value: 0.11800000000000001 |
| - type: precision_at_3 |
| value: 10.844 |
| - type: precision_at_5 |
| value: 8.096 |
| - type: recall_at_1 |
| value: 19.384 |
| - type: recall_at_10 |
| value: 42.847 |
| - type: recall_at_100 |
| value: 67.402 |
| - type: recall_at_1000 |
| value: 88.145 |
| - type: recall_at_3 |
| value: 29.513 |
| - type: recall_at_5 |
| value: 35.57 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/climate-fever |
| name: MTEB ClimateFEVER |
| config: default |
| split: test |
| revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
| metrics: |
| - type: map_at_1 |
| value: 14.915000000000001 |
| - type: map_at_10 |
| value: 25.846999999999998 |
| - type: map_at_100 |
| value: 27.741 |
| - type: map_at_1000 |
| value: 27.921000000000003 |
| - type: map_at_3 |
| value: 21.718 |
| - type: map_at_5 |
| value: 23.948 |
| - type: mrr_at_1 |
| value: 33.941 |
| - type: mrr_at_10 |
| value: 46.897 |
| - type: mrr_at_100 |
| value: 47.63 |
| - type: mrr_at_1000 |
| value: 47.658 |
| - type: mrr_at_3 |
| value: 43.919999999999995 |
| - type: mrr_at_5 |
| value: 45.783 |
| - type: ndcg_at_1 |
| value: 33.941 |
| - type: ndcg_at_10 |
| value: 35.202 |
| - type: ndcg_at_100 |
| value: 42.132 |
| - type: ndcg_at_1000 |
| value: 45.190999999999995 |
| - type: ndcg_at_3 |
| value: 29.68 |
| - type: ndcg_at_5 |
| value: 31.631999999999998 |
| - type: precision_at_1 |
| value: 33.941 |
| - type: precision_at_10 |
| value: 10.906 |
| - type: precision_at_100 |
| value: 1.8339999999999999 |
| - type: precision_at_1000 |
| value: 0.241 |
| - type: precision_at_3 |
| value: 22.606 |
| - type: precision_at_5 |
| value: 17.081 |
| - type: recall_at_1 |
| value: 14.915000000000001 |
| - type: recall_at_10 |
| value: 40.737 |
| - type: recall_at_100 |
| value: 64.42 |
| - type: recall_at_1000 |
| value: 81.435 |
| - type: recall_at_3 |
| value: 26.767000000000003 |
| - type: recall_at_5 |
| value: 32.895 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/dbpedia |
| name: MTEB DBPedia |
| config: default |
| split: test |
| revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
| metrics: |
| - type: map_at_1 |
| value: 8.665000000000001 |
| - type: map_at_10 |
| value: 19.087 |
| - type: map_at_100 |
| value: 26.555 |
| - type: map_at_1000 |
| value: 28.105999999999998 |
| - type: map_at_3 |
| value: 13.858999999999998 |
| - type: map_at_5 |
| value: 16.083 |
| - type: mrr_at_1 |
| value: 68.5 |
| - type: mrr_at_10 |
| value: 76.725 |
| - type: mrr_at_100 |
| value: 76.974 |
| - type: mrr_at_1000 |
| value: 76.981 |
| - type: mrr_at_3 |
| value: 75.583 |
| - type: mrr_at_5 |
| value: 76.208 |
| - type: ndcg_at_1 |
| value: 55.875 |
| - type: ndcg_at_10 |
| value: 41.018 |
| - type: ndcg_at_100 |
| value: 44.982 |
| - type: ndcg_at_1000 |
| value: 52.43 |
| - type: ndcg_at_3 |
| value: 46.534 |
| - type: ndcg_at_5 |
| value: 43.083 |
| - type: precision_at_1 |
| value: 68.5 |
| - type: precision_at_10 |
| value: 32.35 |
| - type: precision_at_100 |
| value: 10.078 |
| - type: precision_at_1000 |
| value: 1.957 |
| - type: precision_at_3 |
| value: 50.083 |
| - type: precision_at_5 |
| value: 41.3 |
| - type: recall_at_1 |
| value: 8.665000000000001 |
| - type: recall_at_10 |
| value: 24.596999999999998 |
| - type: recall_at_100 |
| value: 50.612 |
| - type: recall_at_1000 |
| value: 74.24 |
| - type: recall_at_3 |
| value: 15.337 |
| - type: recall_at_5 |
| value: 18.796 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/emotion |
| name: MTEB EmotionClassification |
| config: default |
| split: test |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
| metrics: |
| - type: accuracy |
| value: 55.06500000000001 |
| - type: f1 |
| value: 49.827367590822035 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/fever |
| name: MTEB FEVER |
| config: default |
| split: test |
| revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
| metrics: |
| - type: map_at_1 |
| value: 76.059 |
| - type: map_at_10 |
| value: 83.625 |
| - type: map_at_100 |
| value: 83.845 |
| - type: map_at_1000 |
| value: 83.858 |
| - type: map_at_3 |
| value: 82.67099999999999 |
| - type: map_at_5 |
| value: 83.223 |
| - type: mrr_at_1 |
| value: 82.013 |
| - type: mrr_at_10 |
| value: 88.44800000000001 |
| - type: mrr_at_100 |
| value: 88.535 |
| - type: mrr_at_1000 |
| value: 88.537 |
| - type: mrr_at_3 |
| value: 87.854 |
| - type: mrr_at_5 |
| value: 88.221 |
| - type: ndcg_at_1 |
| value: 82.013 |
| - type: ndcg_at_10 |
| value: 87.128 |
| - type: ndcg_at_100 |
| value: 87.922 |
| - type: ndcg_at_1000 |
| value: 88.166 |
| - type: ndcg_at_3 |
| value: 85.648 |
| - type: ndcg_at_5 |
| value: 86.366 |
| - type: precision_at_1 |
| value: 82.013 |
| - type: precision_at_10 |
| value: 10.32 |
| - type: precision_at_100 |
| value: 1.093 |
| - type: precision_at_1000 |
| value: 0.11299999999999999 |
| - type: precision_at_3 |
| value: 32.408 |
| - type: precision_at_5 |
| value: 19.973 |
| - type: recall_at_1 |
| value: 76.059 |
| - type: recall_at_10 |
| value: 93.229 |
| - type: recall_at_100 |
| value: 96.387 |
| - type: recall_at_1000 |
| value: 97.916 |
| - type: recall_at_3 |
| value: 89.025 |
| - type: recall_at_5 |
| value: 90.96300000000001 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/fiqa |
| name: MTEB FiQA2018 |
| config: default |
| split: test |
| revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
| metrics: |
| - type: map_at_1 |
| value: 20.479 |
| - type: map_at_10 |
| value: 33.109 |
| - type: map_at_100 |
| value: 34.803 |
| - type: map_at_1000 |
| value: 35.003 |
| - type: map_at_3 |
| value: 28.967 |
| - type: map_at_5 |
| value: 31.385 |
| - type: mrr_at_1 |
| value: 40.278000000000006 |
| - type: mrr_at_10 |
| value: 48.929 |
| - type: mrr_at_100 |
| value: 49.655 |
| - type: mrr_at_1000 |
| value: 49.691 |
| - type: mrr_at_3 |
| value: 46.605000000000004 |
| - type: mrr_at_5 |
| value: 48.056 |
| - type: ndcg_at_1 |
| value: 40.278000000000006 |
| - type: ndcg_at_10 |
| value: 40.649 |
| - type: ndcg_at_100 |
| value: 47.027 |
| - type: ndcg_at_1000 |
| value: 50.249 |
| - type: ndcg_at_3 |
| value: 37.364000000000004 |
| - type: ndcg_at_5 |
| value: 38.494 |
| - type: precision_at_1 |
| value: 40.278000000000006 |
| - type: precision_at_10 |
| value: 11.327 |
| - type: precision_at_100 |
| value: 1.802 |
| - type: precision_at_1000 |
| value: 0.23700000000000002 |
| - type: precision_at_3 |
| value: 25.102999999999998 |
| - type: precision_at_5 |
| value: 18.457 |
| - type: recall_at_1 |
| value: 20.479 |
| - type: recall_at_10 |
| value: 46.594 |
| - type: recall_at_100 |
| value: 71.101 |
| - type: recall_at_1000 |
| value: 90.31099999999999 |
| - type: recall_at_3 |
| value: 33.378 |
| - type: recall_at_5 |
| value: 39.587 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/hotpotqa |
| name: MTEB HotpotQA |
| config: default |
| split: test |
| revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
| metrics: |
| - type: map_at_1 |
| value: 36.59 |
| - type: map_at_10 |
| value: 58.178 |
| - type: map_at_100 |
| value: 59.095 |
| - type: map_at_1000 |
| value: 59.16400000000001 |
| - type: map_at_3 |
| value: 54.907 |
| - type: map_at_5 |
| value: 56.89999999999999 |
| - type: mrr_at_1 |
| value: 73.18 |
| - type: mrr_at_10 |
| value: 79.935 |
| - type: mrr_at_100 |
| value: 80.16799999999999 |
| - type: mrr_at_1000 |
| value: 80.17800000000001 |
| - type: mrr_at_3 |
| value: 78.776 |
| - type: mrr_at_5 |
| value: 79.522 |
| - type: ndcg_at_1 |
| value: 73.18 |
| - type: ndcg_at_10 |
| value: 66.538 |
| - type: ndcg_at_100 |
| value: 69.78 |
| - type: ndcg_at_1000 |
| value: 71.102 |
| - type: ndcg_at_3 |
| value: 61.739 |
| - type: ndcg_at_5 |
| value: 64.35600000000001 |
| - type: precision_at_1 |
| value: 73.18 |
| - type: precision_at_10 |
| value: 14.035 |
| - type: precision_at_100 |
| value: 1.657 |
| - type: precision_at_1000 |
| value: 0.183 |
| - type: precision_at_3 |
| value: 39.684999999999995 |
| - type: precision_at_5 |
| value: 25.885 |
| - type: recall_at_1 |
| value: 36.59 |
| - type: recall_at_10 |
| value: 70.176 |
| - type: recall_at_100 |
| value: 82.836 |
| - type: recall_at_1000 |
| value: 91.526 |
| - type: recall_at_3 |
| value: 59.526999999999994 |
| - type: recall_at_5 |
| value: 64.713 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/imdb |
| name: MTEB ImdbClassification |
| config: default |
| split: test |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
| metrics: |
| - type: accuracy |
| value: 90.1472 |
| - type: ap |
| value: 85.73994227076815 |
| - type: f1 |
| value: 90.1271700788608 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/msmarco |
| name: MTEB MSMARCO |
| config: default |
| split: dev |
| revision: c5a29a104738b98a9e76336939199e264163d4a0 |
| metrics: |
| - type: map_at_1 |
| value: 21.689 |
| - type: map_at_10 |
| value: 33.518 |
| - type: map_at_100 |
| value: 34.715 |
| - type: map_at_1000 |
| value: 34.766000000000005 |
| - type: map_at_3 |
| value: 29.781000000000002 |
| - type: map_at_5 |
| value: 31.838 |
| - type: mrr_at_1 |
| value: 22.249 |
| - type: mrr_at_10 |
| value: 34.085 |
| - type: mrr_at_100 |
| value: 35.223 |
| - type: mrr_at_1000 |
| value: 35.266999999999996 |
| - type: mrr_at_3 |
| value: 30.398999999999997 |
| - type: mrr_at_5 |
| value: 32.437 |
| - type: ndcg_at_1 |
| value: 22.249 |
| - type: ndcg_at_10 |
| value: 40.227000000000004 |
| - type: ndcg_at_100 |
| value: 45.961999999999996 |
| - type: ndcg_at_1000 |
| value: 47.248000000000005 |
| - type: ndcg_at_3 |
| value: 32.566 |
| - type: ndcg_at_5 |
| value: 36.229 |
| - type: precision_at_1 |
| value: 22.249 |
| - type: precision_at_10 |
| value: 6.358 |
| - type: precision_at_100 |
| value: 0.923 |
| - type: precision_at_1000 |
| value: 0.10300000000000001 |
| - type: precision_at_3 |
| value: 13.83 |
| - type: precision_at_5 |
| value: 10.145999999999999 |
| - type: recall_at_1 |
| value: 21.689 |
| - type: recall_at_10 |
| value: 60.92999999999999 |
| - type: recall_at_100 |
| value: 87.40599999999999 |
| - type: recall_at_1000 |
| value: 97.283 |
| - type: recall_at_3 |
| value: 40.01 |
| - type: recall_at_5 |
| value: 48.776 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_domain |
| name: MTEB MTOPDomainClassification (en) |
| config: en |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 95.28727770177838 |
| - type: f1 |
| value: 95.02577308660041 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_intent |
| name: MTEB MTOPIntentClassification (en) |
| config: en |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
| - type: accuracy |
| value: 79.5736434108527 |
| - type: f1 |
| value: 61.2451202054398 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (en) |
| config: en |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
| - type: accuracy |
| value: 76.01210490921318 |
| - type: f1 |
| value: 73.70188053982473 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (en) |
| config: en |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 79.33422999327504 |
| - type: f1 |
| value: 79.48369022509658 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-p2p |
| name: MTEB MedrxivClusteringP2P |
| config: default |
| split: test |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
| metrics: |
| - type: v_measure |
| value: 34.70891567267726 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-s2s |
| name: MTEB MedrxivClusteringS2S |
| config: default |
| split: test |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
| metrics: |
| - type: v_measure |
| value: 32.15203494451706 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/mind_small |
| name: MTEB MindSmallReranking |
| config: default |
| split: test |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
| metrics: |
| - type: map |
| value: 31.919517862194173 |
| - type: mrr |
| value: 33.15466289140483 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/nfcorpus |
| name: MTEB NFCorpus |
| config: default |
| split: test |
| revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
| metrics: |
| - type: map_at_1 |
| value: 5.992 |
| - type: map_at_10 |
| value: 13.197000000000001 |
| - type: map_at_100 |
| value: 16.907 |
| - type: map_at_1000 |
| value: 18.44 |
| - type: map_at_3 |
| value: 9.631 |
| - type: map_at_5 |
| value: 11.243 |
| - type: mrr_at_1 |
| value: 44.272 |
| - type: mrr_at_10 |
| value: 53.321 |
| - type: mrr_at_100 |
| value: 53.903 |
| - type: mrr_at_1000 |
| value: 53.952999999999996 |
| - type: mrr_at_3 |
| value: 51.393 |
| - type: mrr_at_5 |
| value: 52.708999999999996 |
| - type: ndcg_at_1 |
| value: 42.415000000000006 |
| - type: ndcg_at_10 |
| value: 34.921 |
| - type: ndcg_at_100 |
| value: 32.384 |
| - type: ndcg_at_1000 |
| value: 41.260000000000005 |
| - type: ndcg_at_3 |
| value: 40.186 |
| - type: ndcg_at_5 |
| value: 37.89 |
| - type: precision_at_1 |
| value: 44.272 |
| - type: precision_at_10 |
| value: 26.006 |
| - type: precision_at_100 |
| value: 8.44 |
| - type: precision_at_1000 |
| value: 2.136 |
| - type: precision_at_3 |
| value: 37.977 |
| - type: precision_at_5 |
| value: 32.755 |
| - type: recall_at_1 |
| value: 5.992 |
| - type: recall_at_10 |
| value: 17.01 |
| - type: recall_at_100 |
| value: 33.080999999999996 |
| - type: recall_at_1000 |
| value: 65.054 |
| - type: recall_at_3 |
| value: 10.528 |
| - type: recall_at_5 |
| value: 13.233 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/nq |
| name: MTEB NQ |
| config: default |
| split: test |
| revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
| metrics: |
| - type: map_at_1 |
| value: 28.871999999999996 |
| - type: map_at_10 |
| value: 43.286 |
| - type: map_at_100 |
| value: 44.432 |
| - type: map_at_1000 |
| value: 44.464999999999996 |
| - type: map_at_3 |
| value: 38.856 |
| - type: map_at_5 |
| value: 41.514 |
| - type: mrr_at_1 |
| value: 32.619 |
| - type: mrr_at_10 |
| value: 45.75 |
| - type: mrr_at_100 |
| value: 46.622 |
| - type: mrr_at_1000 |
| value: 46.646 |
| - type: mrr_at_3 |
| value: 41.985 |
| - type: mrr_at_5 |
| value: 44.277 |
| - type: ndcg_at_1 |
| value: 32.59 |
| - type: ndcg_at_10 |
| value: 50.895999999999994 |
| - type: ndcg_at_100 |
| value: 55.711999999999996 |
| - type: ndcg_at_1000 |
| value: 56.48800000000001 |
| - type: ndcg_at_3 |
| value: 42.504999999999995 |
| - type: ndcg_at_5 |
| value: 46.969 |
| - type: precision_at_1 |
| value: 32.59 |
| - type: precision_at_10 |
| value: 8.543000000000001 |
| - type: precision_at_100 |
| value: 1.123 |
| - type: precision_at_1000 |
| value: 0.12 |
| - type: precision_at_3 |
| value: 19.448 |
| - type: precision_at_5 |
| value: 14.218 |
| - type: recall_at_1 |
| value: 28.871999999999996 |
| - type: recall_at_10 |
| value: 71.748 |
| - type: recall_at_100 |
| value: 92.55499999999999 |
| - type: recall_at_1000 |
| value: 98.327 |
| - type: recall_at_3 |
| value: 49.944 |
| - type: recall_at_5 |
| value: 60.291 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/quora |
| name: MTEB QuoraRetrieval |
| config: default |
| split: test |
| revision: e4e08e0b7dbe3c8700f0daef558ff32256715259 |
| metrics: |
| - type: map_at_1 |
| value: 70.664 |
| - type: map_at_10 |
| value: 84.681 |
| - type: map_at_100 |
| value: 85.289 |
| - type: map_at_1000 |
| value: 85.306 |
| - type: map_at_3 |
| value: 81.719 |
| - type: map_at_5 |
| value: 83.601 |
| - type: mrr_at_1 |
| value: 81.35 |
| - type: mrr_at_10 |
| value: 87.591 |
| - type: mrr_at_100 |
| value: 87.691 |
| - type: mrr_at_1000 |
| value: 87.693 |
| - type: mrr_at_3 |
| value: 86.675 |
| - type: mrr_at_5 |
| value: 87.29299999999999 |
| - type: ndcg_at_1 |
| value: 81.33 |
| - type: ndcg_at_10 |
| value: 88.411 |
| - type: ndcg_at_100 |
| value: 89.579 |
| - type: ndcg_at_1000 |
| value: 89.687 |
| - type: ndcg_at_3 |
| value: 85.613 |
| - type: ndcg_at_5 |
| value: 87.17 |
| - type: precision_at_1 |
| value: 81.33 |
| - type: precision_at_10 |
| value: 13.422 |
| - type: precision_at_100 |
| value: 1.5270000000000001 |
| - type: precision_at_1000 |
| value: 0.157 |
| - type: precision_at_3 |
| value: 37.463 |
| - type: precision_at_5 |
| value: 24.646 |
| - type: recall_at_1 |
| value: 70.664 |
| - type: recall_at_10 |
| value: 95.54 |
| - type: recall_at_100 |
| value: 99.496 |
| - type: recall_at_1000 |
| value: 99.978 |
| - type: recall_at_3 |
| value: 87.481 |
| - type: recall_at_5 |
| value: 91.88499999999999 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering |
| name: MTEB RedditClustering |
| config: default |
| split: test |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| metrics: |
| - type: v_measure |
| value: 55.40341814991112 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering-p2p |
| name: MTEB RedditClusteringP2P |
| config: default |
| split: test |
| revision: 385e3cb46b4cfa89021f56c4380204149d0efe33 |
| metrics: |
| - type: v_measure |
| value: 61.231318481346655 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/scidocs |
| name: MTEB SCIDOCS |
| config: default |
| split: test |
| revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88 |
| metrics: |
| - type: map_at_1 |
| value: 4.833 |
| - type: map_at_10 |
| value: 13.149 |
| - type: map_at_100 |
| value: 15.578 |
| - type: map_at_1000 |
| value: 15.963 |
| - type: map_at_3 |
| value: 9.269 |
| - type: map_at_5 |
| value: 11.182 |
| - type: mrr_at_1 |
| value: 23.9 |
| - type: mrr_at_10 |
| value: 35.978 |
| - type: mrr_at_100 |
| value: 37.076 |
| - type: mrr_at_1000 |
| value: 37.126 |
| - type: mrr_at_3 |
| value: 32.333 |
| - type: mrr_at_5 |
| value: 34.413 |
| - type: ndcg_at_1 |
| value: 23.9 |
| - type: ndcg_at_10 |
| value: 21.823 |
| - type: ndcg_at_100 |
| value: 30.833 |
| - type: ndcg_at_1000 |
| value: 36.991 |
| - type: ndcg_at_3 |
| value: 20.465 |
| - type: ndcg_at_5 |
| value: 17.965999999999998 |
| - type: precision_at_1 |
| value: 23.9 |
| - type: precision_at_10 |
| value: 11.49 |
| - type: precision_at_100 |
| value: 2.444 |
| - type: precision_at_1000 |
| value: 0.392 |
| - type: precision_at_3 |
| value: 19.3 |
| - type: precision_at_5 |
| value: 15.959999999999999 |
| - type: recall_at_1 |
| value: 4.833 |
| - type: recall_at_10 |
| value: 23.294999999999998 |
| - type: recall_at_100 |
| value: 49.63 |
| - type: recall_at_1000 |
| value: 79.49199999999999 |
| - type: recall_at_3 |
| value: 11.732 |
| - type: recall_at_5 |
| value: 16.167 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sickr-sts |
| name: MTEB SICK-R |
| config: default |
| split: test |
| revision: 20a6d6f312dd54037fe07a32d58e5e168867909d |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.62938108735759 |
| - type: cos_sim_spearman |
| value: 80.30777094408789 |
| - type: euclidean_pearson |
| value: 82.94516686659536 |
| - type: euclidean_spearman |
| value: 80.34489663248169 |
| - type: manhattan_pearson |
| value: 82.85830094736245 |
| - type: manhattan_spearman |
| value: 80.24902623215449 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts12-sts |
| name: MTEB STS12 |
| config: default |
| split: test |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.23777464247604 |
| - type: cos_sim_spearman |
| value: 75.75714864112797 |
| - type: euclidean_pearson |
| value: 82.33806918604493 |
| - type: euclidean_spearman |
| value: 75.45282124387357 |
| - type: manhattan_pearson |
| value: 82.32555620660538 |
| - type: manhattan_spearman |
| value: 75.49228731684082 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts13-sts |
| name: MTEB STS13 |
| config: default |
| split: test |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| metrics: |
| - type: cos_sim_pearson |
| value: 84.88151620954451 |
| - type: cos_sim_spearman |
| value: 86.08377598473446 |
| - type: euclidean_pearson |
| value: 85.36958329369413 |
| - type: euclidean_spearman |
| value: 86.10274219670679 |
| - type: manhattan_pearson |
| value: 85.25873897594711 |
| - type: manhattan_spearman |
| value: 85.98096461661584 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts14-sts |
| name: MTEB STS14 |
| config: default |
| split: test |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| metrics: |
| - type: cos_sim_pearson |
| value: 84.29360558735978 |
| - type: cos_sim_spearman |
| value: 82.28284203795577 |
| - type: euclidean_pearson |
| value: 83.81636655536633 |
| - type: euclidean_spearman |
| value: 82.24340438530236 |
| - type: manhattan_pearson |
| value: 83.83914453428608 |
| - type: manhattan_spearman |
| value: 82.28391354080694 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts15-sts |
| name: MTEB STS15 |
| config: default |
| split: test |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| metrics: |
| - type: cos_sim_pearson |
| value: 87.47344180426744 |
| - type: cos_sim_spearman |
| value: 88.90045649789438 |
| - type: euclidean_pearson |
| value: 88.43020815961273 |
| - type: euclidean_spearman |
| value: 89.0087449011776 |
| - type: manhattan_pearson |
| value: 88.37601826505525 |
| - type: manhattan_spearman |
| value: 88.96756360690617 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts16-sts |
| name: MTEB STS16 |
| config: default |
| split: test |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| metrics: |
| - type: cos_sim_pearson |
| value: 83.35997025304613 |
| - type: cos_sim_spearman |
| value: 85.18237675717147 |
| - type: euclidean_pearson |
| value: 84.46478196990202 |
| - type: euclidean_spearman |
| value: 85.27748677712205 |
| - type: manhattan_pearson |
| value: 84.29342543953123 |
| - type: manhattan_spearman |
| value: 85.10579612516567 |
| - 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: 88.56668329596836 |
| - type: cos_sim_spearman |
| value: 88.72837234129177 |
| - type: euclidean_pearson |
| value: 89.39395650897828 |
| - type: euclidean_spearman |
| value: 88.82001247906778 |
| - type: manhattan_pearson |
| value: 89.41735354368878 |
| - type: manhattan_spearman |
| value: 88.95159141850039 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (en) |
| config: en |
| split: test |
| revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| metrics: |
| - type: cos_sim_pearson |
| value: 67.466167902991 |
| - type: cos_sim_spearman |
| value: 68.54466147197274 |
| - type: euclidean_pearson |
| value: 69.35551179564695 |
| - type: euclidean_spearman |
| value: 68.75455717749132 |
| - type: manhattan_pearson |
| value: 69.42432368208264 |
| - type: manhattan_spearman |
| value: 68.83203709670562 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/stsbenchmark-sts |
| name: MTEB STSBenchmark |
| config: default |
| split: test |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.33241300373689 |
| - type: cos_sim_spearman |
| value: 86.97909372129874 |
| - type: euclidean_pearson |
| value: 86.99526113559924 |
| - type: euclidean_spearman |
| value: 87.02644372623219 |
| - type: manhattan_pearson |
| value: 86.78744182759846 |
| - type: manhattan_spearman |
| value: 86.8886180198196 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/scidocs-reranking |
| name: MTEB SciDocsRR |
| config: default |
| split: test |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| metrics: |
| - type: map |
| value: 86.18374413668717 |
| - type: mrr |
| value: 95.93213068703264 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/scifact |
| name: MTEB SciFact |
| config: default |
| split: test |
| revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
| metrics: |
| - type: map_at_1 |
| value: 58.31699999999999 |
| - type: map_at_10 |
| value: 67.691 |
| - type: map_at_100 |
| value: 68.201 |
| - type: map_at_1000 |
| value: 68.232 |
| - type: map_at_3 |
| value: 64.47800000000001 |
| - type: map_at_5 |
| value: 66.51 |
| - type: mrr_at_1 |
| value: 61.0 |
| - type: mrr_at_10 |
| value: 68.621 |
| - type: mrr_at_100 |
| value: 68.973 |
| - type: mrr_at_1000 |
| value: 69.002 |
| - type: mrr_at_3 |
| value: 66.111 |
| - type: mrr_at_5 |
| value: 67.578 |
| - type: ndcg_at_1 |
| value: 61.0 |
| - type: ndcg_at_10 |
| value: 72.219 |
| - type: ndcg_at_100 |
| value: 74.397 |
| - type: ndcg_at_1000 |
| value: 75.021 |
| - type: ndcg_at_3 |
| value: 66.747 |
| - type: ndcg_at_5 |
| value: 69.609 |
| - type: precision_at_1 |
| value: 61.0 |
| - type: precision_at_10 |
| value: 9.6 |
| - type: precision_at_100 |
| value: 1.08 |
| - type: precision_at_1000 |
| value: 0.11299999999999999 |
| - type: precision_at_3 |
| value: 25.667 |
| - type: precision_at_5 |
| value: 17.267 |
| - type: recall_at_1 |
| value: 58.31699999999999 |
| - type: recall_at_10 |
| value: 85.233 |
| - type: recall_at_100 |
| value: 95.167 |
| - type: recall_at_1000 |
| value: 99.667 |
| - type: recall_at_3 |
| value: 70.589 |
| - type: recall_at_5 |
| value: 77.628 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/sprintduplicatequestions-pairclassification |
| name: MTEB SprintDuplicateQuestions |
| config: default |
| split: test |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 99.83267326732673 |
| - type: cos_sim_ap |
| value: 96.13707107038228 |
| - type: cos_sim_f1 |
| value: 91.48830263812842 |
| - type: cos_sim_precision |
| value: 91.0802775024777 |
| - type: cos_sim_recall |
| value: 91.9 |
| - type: dot_accuracy |
| value: 99.83069306930693 |
| - type: dot_ap |
| value: 96.21199069147254 |
| - type: dot_f1 |
| value: 91.36295556665004 |
| - type: dot_precision |
| value: 91.22632103688933 |
| - type: dot_recall |
| value: 91.5 |
| - type: euclidean_accuracy |
| value: 99.83267326732673 |
| - type: euclidean_ap |
| value: 96.08957801367436 |
| - type: euclidean_f1 |
| value: 91.33004926108374 |
| - type: euclidean_precision |
| value: 90.0 |
| - type: euclidean_recall |
| value: 92.7 |
| - type: manhattan_accuracy |
| value: 99.83564356435643 |
| - type: manhattan_ap |
| value: 96.10534946461945 |
| - type: manhattan_f1 |
| value: 91.74950298210736 |
| - type: manhattan_precision |
| value: 91.20553359683794 |
| - type: manhattan_recall |
| value: 92.30000000000001 |
| - type: max_accuracy |
| value: 99.83564356435643 |
| - type: max_ap |
| value: 96.21199069147254 |
| - type: max_f1 |
| value: 91.74950298210736 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering |
| name: MTEB StackExchangeClustering |
| config: default |
| split: test |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
| metrics: |
| - type: v_measure |
| value: 62.045718843534736 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering-p2p |
| name: MTEB StackExchangeClusteringP2P |
| config: default |
| split: test |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
| metrics: |
| - type: v_measure |
| value: 36.6501777041092 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/stackoverflowdupquestions-reranking |
| name: MTEB StackOverflowDupQuestions |
| config: default |
| split: test |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
| metrics: |
| - type: map |
| value: 52.963913408053955 |
| - type: mrr |
| value: 53.87972423818012 |
| - task: |
| type: Summarization |
| dataset: |
| type: mteb/summeval |
| name: MTEB SummEval |
| config: default |
| split: test |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
| metrics: |
| - type: cos_sim_pearson |
| value: 30.44195730764998 |
| - type: cos_sim_spearman |
| value: 30.59626288679397 |
| - type: dot_pearson |
| value: 30.22974492404086 |
| - type: dot_spearman |
| value: 29.345245972906497 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/trec-covid |
| name: MTEB TRECCOVID |
| config: default |
| split: test |
| revision: bb9466bac8153a0349341eb1b22e06409e78ef4e |
| metrics: |
| - type: map_at_1 |
| value: 0.24 |
| - type: map_at_10 |
| value: 2.01 |
| - type: map_at_100 |
| value: 11.928999999999998 |
| - type: map_at_1000 |
| value: 29.034 |
| - type: map_at_3 |
| value: 0.679 |
| - type: map_at_5 |
| value: 1.064 |
| - type: mrr_at_1 |
| value: 92.0 |
| - type: mrr_at_10 |
| value: 96.0 |
| - type: mrr_at_100 |
| value: 96.0 |
| - type: mrr_at_1000 |
| value: 96.0 |
| - type: mrr_at_3 |
| value: 96.0 |
| - type: mrr_at_5 |
| value: 96.0 |
| - type: ndcg_at_1 |
| value: 87.0 |
| - type: ndcg_at_10 |
| value: 80.118 |
| - type: ndcg_at_100 |
| value: 60.753 |
| - type: ndcg_at_1000 |
| value: 54.632999999999996 |
| - type: ndcg_at_3 |
| value: 83.073 |
| - type: ndcg_at_5 |
| value: 80.733 |
| - type: precision_at_1 |
| value: 92.0 |
| - type: precision_at_10 |
| value: 84.8 |
| - type: precision_at_100 |
| value: 62.019999999999996 |
| - type: precision_at_1000 |
| value: 24.028 |
| - type: precision_at_3 |
| value: 87.333 |
| - type: precision_at_5 |
| value: 85.2 |
| - type: recall_at_1 |
| value: 0.24 |
| - type: recall_at_10 |
| value: 2.205 |
| - type: recall_at_100 |
| value: 15.068000000000001 |
| - type: recall_at_1000 |
| value: 51.796 |
| - type: recall_at_3 |
| value: 0.698 |
| - type: recall_at_5 |
| value: 1.1199999999999999 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/touche2020 |
| name: MTEB Touche2020 |
| config: default |
| split: test |
| revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
| metrics: |
| - type: map_at_1 |
| value: 3.066 |
| - type: map_at_10 |
| value: 9.219 |
| - type: map_at_100 |
| value: 15.387 |
| - type: map_at_1000 |
| value: 16.957 |
| - type: map_at_3 |
| value: 5.146 |
| - type: map_at_5 |
| value: 6.6739999999999995 |
| - type: mrr_at_1 |
| value: 40.816 |
| - type: mrr_at_10 |
| value: 50.844 |
| - type: mrr_at_100 |
| value: 51.664 |
| - type: mrr_at_1000 |
| value: 51.664 |
| - type: mrr_at_3 |
| value: 46.259 |
| - type: mrr_at_5 |
| value: 49.116 |
| - type: ndcg_at_1 |
| value: 37.755 |
| - type: ndcg_at_10 |
| value: 23.477 |
| - type: ndcg_at_100 |
| value: 36.268 |
| - type: ndcg_at_1000 |
| value: 47.946 |
| - type: ndcg_at_3 |
| value: 25.832 |
| - type: ndcg_at_5 |
| value: 24.235 |
| - type: precision_at_1 |
| value: 40.816 |
| - type: precision_at_10 |
| value: 20.204 |
| - type: precision_at_100 |
| value: 7.611999999999999 |
| - type: precision_at_1000 |
| value: 1.543 |
| - type: precision_at_3 |
| value: 25.169999999999998 |
| - type: precision_at_5 |
| value: 23.265 |
| - type: recall_at_1 |
| value: 3.066 |
| - type: recall_at_10 |
| value: 14.985999999999999 |
| - type: recall_at_100 |
| value: 47.902 |
| - type: recall_at_1000 |
| value: 83.56400000000001 |
| - type: recall_at_3 |
| value: 5.755 |
| - type: recall_at_5 |
| value: 8.741999999999999 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/toxic_conversations_50k |
| name: MTEB ToxicConversationsClassification |
| config: default |
| split: test |
| revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de |
| metrics: |
| - type: accuracy |
| value: 69.437 |
| - type: ap |
| value: 12.844066827082706 |
| - type: f1 |
| value: 52.74974809872495 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/tweet_sentiment_extraction |
| name: MTEB TweetSentimentExtractionClassification |
| config: default |
| split: test |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| metrics: |
| - type: accuracy |
| value: 61.26768534238823 |
| - type: f1 |
| value: 61.65100187399282 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/twentynewsgroups-clustering |
| name: MTEB TwentyNewsgroupsClustering |
| config: default |
| split: test |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| metrics: |
| - type: v_measure |
| value: 49.860968711078804 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twittersemeval2015-pairclassification |
| name: MTEB TwitterSemEval2015 |
| config: default |
| split: test |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 85.7423854085951 |
| - type: cos_sim_ap |
| value: 73.47560303339571 |
| - type: cos_sim_f1 |
| value: 67.372778183589 |
| - type: cos_sim_precision |
| value: 62.54520795660036 |
| - type: cos_sim_recall |
| value: 73.00791556728232 |
| - type: dot_accuracy |
| value: 85.36091077069798 |
| - type: dot_ap |
| value: 72.42521572307255 |
| - type: dot_f1 |
| value: 66.90576304724215 |
| - type: dot_precision |
| value: 62.96554934823091 |
| - type: dot_recall |
| value: 71.37203166226914 |
| - type: euclidean_accuracy |
| value: 85.76026703224653 |
| - type: euclidean_ap |
| value: 73.44852563860128 |
| - type: euclidean_f1 |
| value: 67.3 |
| - type: euclidean_precision |
| value: 63.94299287410926 |
| - type: euclidean_recall |
| value: 71.02902374670185 |
| - type: manhattan_accuracy |
| value: 85.7423854085951 |
| - type: manhattan_ap |
| value: 73.2635034755551 |
| - type: manhattan_f1 |
| value: 67.3180263800684 |
| - type: manhattan_precision |
| value: 62.66484765802638 |
| - type: manhattan_recall |
| value: 72.71767810026385 |
| - type: max_accuracy |
| value: 85.76026703224653 |
| - type: max_ap |
| value: 73.47560303339571 |
| - type: max_f1 |
| value: 67.372778183589 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twitterurlcorpus-pairclassification |
| name: MTEB TwitterURLCorpus |
| config: default |
| split: test |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
| metrics: |
| - type: cos_sim_accuracy |
| value: 88.67543757519307 |
| - type: cos_sim_ap |
| value: 85.35516518531304 |
| - type: cos_sim_f1 |
| value: 77.58197635511934 |
| - type: cos_sim_precision |
| value: 75.01078360891445 |
| - type: cos_sim_recall |
| value: 80.33569448721897 |
| - type: dot_accuracy |
| value: 87.61400240617844 |
| - type: dot_ap |
| value: 83.0774968268665 |
| - type: dot_f1 |
| value: 75.68229012162561 |
| - type: dot_precision |
| value: 72.99713876967095 |
| - type: dot_recall |
| value: 78.57252848783493 |
| - type: euclidean_accuracy |
| value: 88.73753250281368 |
| - type: euclidean_ap |
| value: 85.48043564821317 |
| - type: euclidean_f1 |
| value: 77.75975862719216 |
| - type: euclidean_precision |
| value: 76.21054187920456 |
| - type: euclidean_recall |
| value: 79.37326763166 |
| - type: manhattan_accuracy |
| value: 88.75111576823068 |
| - type: manhattan_ap |
| value: 85.44993439423668 |
| - type: manhattan_f1 |
| value: 77.6861329994845 |
| - type: manhattan_precision |
| value: 74.44601270289344 |
| - type: manhattan_recall |
| value: 81.22112719433323 |
| - type: max_accuracy |
| value: 88.75111576823068 |
| - type: max_ap |
| value: 85.48043564821317 |
| - type: max_f1 |
| value: 77.75975862719216 |
| --- |
| <h1 align="center">NoInstruct small Embedding v0</h1> |
|
|
| *NoInstruct Embedding: Asymmetric Pooling is All You Need* |
|
|
| This model has improved retrieval performance compared to the [avsolatorio/GIST-small-Embedding-v0](https://huggingface.co/avsolatorio/GIST-small-Embedding-v0) model. |
|
|
| One of the things that the `GIST` family of models fell short on is the performance on retrieval tasks. We propose a method that produces improved retrieval performance while maintaining independence on crafting arbitrary instructions, a trending paradigm in embedding models for retrieval tasks, when encoding a query. |
|
|
| Technical details of the model will be published shortly. |
|
|
| # Usage |
|
|
| ```Python |
| from typing import Union |
| import torch |
| import torch.nn.functional as F |
| from transformers import AutoModel, AutoTokenizer |
| |
| model = AutoModel.from_pretrained("avsolatorio/NoInstruct-small-Embedding-v0") |
| tokenizer = AutoTokenizer.from_pretrained("avsolatorio/NoInstruct-small-Embedding-v0") |
| |
| |
| def get_embedding(text: Union[str, list[str]], mode: str = "sentence"): |
| model.eval() |
| |
| assert mode in ("query", "sentence"), f"mode={mode} was passed but only `query` and `sentence` are the supported modes." |
| |
| if isinstance(text, str): |
| text = [text] |
| |
| inp = tokenizer(text, return_tensors="pt", padding=True, truncation=True) |
| |
| with torch.no_grad(): |
| output = model(**inp) |
| |
| # The model is optimized to use the mean pooling for queries, |
| # while the sentence / document embedding uses the [CLS] representation. |
| |
| if mode == "query": |
| vectors = output.last_hidden_state * inp["attention_mask"].unsqueeze(2) |
| vectors = vectors.sum(dim=1) / inp["attention_mask"].sum(dim=-1).view(-1, 1) |
| else: |
| vectors = output.last_hidden_state[:, 0, :] |
| |
| return vectors |
| |
| |
| texts = [ |
| "Illustration of the REaLTabFormer model. The left block shows the non-relational tabular data model using GPT-2 with a causal LM head. In contrast, the right block shows how a relational dataset's child table is modeled using a sequence-to-sequence (Seq2Seq) model. The Seq2Seq model uses the observations in the parent table to condition the generation of the observations in the child table. The trained GPT-2 model on the parent table, with weights frozen, is also used as the encoder in the Seq2Seq model.", |
| "Predicting human mobility holds significant practical value, with applications ranging from enhancing disaster risk planning to simulating epidemic spread. In this paper, we present the GeoFormer, a decoder-only transformer model adapted from the GPT architecture to forecast human mobility.", |
| "As the economies of Southeast Asia continue adopting digital technologies, policy makers increasingly ask how to prepare the workforce for emerging labor demands. However, little is known about the skills that workers need to adapt to these changes" |
| ] |
| |
| # Compute embeddings |
| embeddings = get_embedding(texts, mode="sentence") |
| |
| # Compute cosine-similarity for each pair of sentences |
| scores = F.cosine_similarity(embeddings.unsqueeze(1), embeddings.unsqueeze(0), dim=-1) |
| print(scores.cpu().numpy()) |
| |
| # Test the retrieval performance. |
| query = get_embedding("Which sentence talks about concept on jobs?", mode="query") |
| |
| scores = F.cosine_similarity(query, embeddings, dim=-1) |
| print(scores.cpu().numpy()) |
| ``` |
|
|
| Support for the Sentence Transformers library will follow soon. |
|
|
