| --- |
| license: mit |
| library_name: sentence-transformers |
| pipeline_tag: sentence-similarity |
| tags: |
| - sentence-transformers |
| - feature-extraction |
| - sentence-similarity |
| - gte |
| - mteb |
| datasets: |
| - Mihaiii/qa-assistant |
| model-index: |
| - name: Bulbasaur |
| results: |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_counterfactual |
| name: MTEB AmazonCounterfactualClassification (en) |
| config: en |
| split: test |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
| metrics: |
| - type: accuracy |
| value: 71.86567164179104 |
| - type: ap |
| value: 34.08685244750869 |
| - type: f1 |
| value: 65.66014356237362 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_polarity |
| name: MTEB AmazonPolarityClassification |
| config: default |
| split: test |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
| metrics: |
| - type: accuracy |
| value: 78.78927499999999 |
| - type: ap |
| value: 73.46960735629719 |
| - type: f1 |
| value: 78.6951990840684 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (en) |
| config: en |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 39.312 |
| - type: f1 |
| value: 38.94567141563064 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/arguana |
| name: MTEB ArguAna |
| config: default |
| split: test |
| revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
| metrics: |
| - type: map_at_1 |
| value: 22.191 |
| - type: map_at_10 |
| value: 36.504 |
| - type: map_at_100 |
| value: 37.676 |
| - type: map_at_1000 |
| value: 37.693 |
| - type: map_at_20 |
| value: 37.329 |
| - type: map_at_3 |
| value: 31.840000000000003 |
| - type: map_at_5 |
| value: 34.333000000000006 |
| - type: mrr_at_1 |
| value: 23.186 |
| - type: mrr_at_10 |
| value: 36.856 |
| - type: mrr_at_100 |
| value: 38.048 |
| - type: mrr_at_1000 |
| value: 38.065 |
| - type: mrr_at_20 |
| value: 37.701 |
| - type: mrr_at_3 |
| value: 32.16 |
| - type: mrr_at_5 |
| value: 34.756 |
| - type: ndcg_at_1 |
| value: 22.191 |
| - type: ndcg_at_10 |
| value: 44.798 |
| - type: ndcg_at_100 |
| value: 50.141999999999996 |
| - type: ndcg_at_1000 |
| value: 50.599000000000004 |
| - type: ndcg_at_20 |
| value: 47.778999999999996 |
| - type: ndcg_at_3 |
| value: 35.071999999999996 |
| - type: ndcg_at_5 |
| value: 39.574 |
| - type: precision_at_1 |
| value: 22.191 |
| - type: precision_at_10 |
| value: 7.148000000000001 |
| - type: precision_at_100 |
| value: 0.9570000000000001 |
| - type: precision_at_1000 |
| value: 0.099 |
| - type: precision_at_20 |
| value: 4.1610000000000005 |
| - type: precision_at_3 |
| value: 14.817 |
| - type: precision_at_5 |
| value: 11.081000000000001 |
| - type: recall_at_1 |
| value: 22.191 |
| - type: recall_at_10 |
| value: 71.479 |
| - type: recall_at_100 |
| value: 95.661 |
| - type: recall_at_1000 |
| value: 99.289 |
| - type: recall_at_20 |
| value: 83.21499999999999 |
| - type: recall_at_3 |
| value: 44.452000000000005 |
| - type: recall_at_5 |
| value: 55.405 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-p2p |
| name: MTEB ArxivClusteringP2P |
| config: default |
| split: test |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| metrics: |
| - type: v_measure |
| value: 40.283298409035076 |
| - type: v_measures |
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| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-s2s |
| name: MTEB ArxivClusteringS2S |
| config: default |
| split: test |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
| metrics: |
| - type: v_measure |
| value: 31.058723747886102 |
| - type: v_measures |
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| - task: |
| type: Reranking |
| dataset: |
| type: mteb/askubuntudupquestions-reranking |
| name: MTEB AskUbuntuDupQuestions |
| config: default |
| split: test |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
| metrics: |
| - type: map |
| value: 57.489775602270086 |
| - type: mrr |
| value: 71.4973838104032 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/biosses-sts |
| name: MTEB BIOSSES |
| config: default |
| split: test |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.81314286759594 |
| - type: cos_sim_spearman |
| value: 85.04832342591277 |
| - type: euclidean_pearson |
| value: 84.20540608390993 |
| - type: euclidean_spearman |
| value: 84.54831203281398 |
| - type: manhattan_pearson |
| value: 84.11283044138868 |
| - type: manhattan_spearman |
| value: 84.13384475757064 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/banking77 |
| name: MTEB Banking77Classification |
| config: default |
| split: test |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| metrics: |
| - type: accuracy |
| value: 80.57792207792207 |
| - type: f1 |
| value: 80.510338047888 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-p2p |
| name: MTEB BiorxivClusteringP2P |
| config: default |
| split: test |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| metrics: |
| - type: v_measure |
| value: 35.17908628951979 |
| - type: v_measures |
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| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-s2s |
| name: MTEB BiorxivClusteringS2S |
| config: default |
| split: test |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
| metrics: |
| - type: v_measure |
| value: 28.18471478622865 |
| - type: v_measures |
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| - task: |
| type: Reranking |
| dataset: |
| type: mteb/mind_small |
| name: MTEB MindSmallReranking |
| config: default |
| split: test |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
| metrics: |
| - type: map |
| value: 31.7776266029616 |
| - type: mrr |
| value: 32.9057970138914 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack |
| name: MTEB CQADupstackRetrieval |
| config: default |
| split: test |
| revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
| metrics: |
| - type: map_at_1 |
| value: 24.78675 |
| - type: map_at_10 |
| value: 33.18391666666666 |
| - type: map_at_100 |
| value: 34.34583333333333 |
| - type: map_at_1000 |
| value: 34.46825 |
| - type: map_at_20 |
| value: 33.819 |
| - type: map_at_3 |
| value: 30.636500000000005 |
| - type: map_at_5 |
| value: 32.02091666666667 |
| - type: mrr_at_1 |
| value: 29.478749999999998 |
| - type: mrr_at_10 |
| value: 37.385 |
| - type: mrr_at_100 |
| value: 38.23491666666667 |
| - type: mrr_at_1000 |
| value: 38.298833333333334 |
| - type: mrr_at_20 |
| value: 37.87508333333333 |
| - type: mrr_at_3 |
| value: 35.089666666666666 |
| - type: mrr_at_5 |
| value: 36.36816666666667 |
| - type: ndcg_at_1 |
| value: 29.478749999999998 |
| - type: ndcg_at_10 |
| value: 38.2035 |
| - type: ndcg_at_100 |
| value: 43.301083333333324 |
| - type: ndcg_at_1000 |
| value: 45.758666666666656 |
| - type: ndcg_at_20 |
| value: 40.15116666666667 |
| - type: ndcg_at_3 |
| value: 33.86033333333334 |
| - type: ndcg_at_5 |
| value: 35.81266666666666 |
| - type: precision_at_1 |
| value: 29.478749999999998 |
| - type: precision_at_10 |
| value: 6.642833333333334 |
| - type: precision_at_100 |
| value: 1.08425 |
| - type: precision_at_1000 |
| value: 0.14850000000000002 |
| - type: precision_at_20 |
| value: 3.948083333333334 |
| - type: precision_at_3 |
| value: 15.511 |
| - type: precision_at_5 |
| value: 10.929833333333333 |
| - type: recall_at_1 |
| value: 24.78675 |
| - type: recall_at_10 |
| value: 48.9305 |
| - type: recall_at_100 |
| value: 71.49416666666666 |
| - type: recall_at_1000 |
| value: 88.54375 |
| - type: recall_at_20 |
| value: 56.06475 |
| - type: recall_at_3 |
| value: 36.66891666666666 |
| - type: recall_at_5 |
| value: 41.790499999999994 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-android |
| name: MTEB CQADupstackAndroidRetrieval |
| config: default |
| split: test |
| revision: f46a197baaae43b4f621051089b82a364682dfeb |
| metrics: |
| - type: map_at_1 |
| value: 24.271 |
| - type: map_at_10 |
| value: 33.5 |
| - type: map_at_100 |
| value: 34.818 |
| - type: map_at_1000 |
| value: 34.967 |
| - type: map_at_20 |
| value: 34.238 |
| - type: map_at_3 |
| value: 30.488 |
| - type: map_at_5 |
| value: 32.303 |
| - type: mrr_at_1 |
| value: 30.615 |
| - type: mrr_at_10 |
| value: 39.076 |
| - type: mrr_at_100 |
| value: 40.022000000000006 |
| - type: mrr_at_1000 |
| value: 40.082 |
| - type: mrr_at_20 |
| value: 39.669 |
| - type: mrr_at_3 |
| value: 36.552 |
| - type: mrr_at_5 |
| value: 38.096999999999994 |
| - type: ndcg_at_1 |
| value: 30.615 |
| - type: ndcg_at_10 |
| value: 39.106 |
| - type: ndcg_at_100 |
| value: 44.519 |
| - type: ndcg_at_1000 |
| value: 47.274 |
| - type: ndcg_at_20 |
| value: 41.289 |
| - type: ndcg_at_3 |
| value: 34.55 |
| - type: ndcg_at_5 |
| value: 36.815999999999995 |
| - type: precision_at_1 |
| value: 30.615 |
| - type: precision_at_10 |
| value: 7.5249999999999995 |
| - type: precision_at_100 |
| value: 1.282 |
| - type: precision_at_1000 |
| value: 0.181 |
| - type: precision_at_20 |
| value: 4.549 |
| - type: precision_at_3 |
| value: 16.643 |
| - type: precision_at_5 |
| value: 12.275 |
| - type: recall_at_1 |
| value: 24.271 |
| - type: recall_at_10 |
| value: 49.714000000000006 |
| - type: recall_at_100 |
| value: 72.792 |
| - type: recall_at_1000 |
| value: 91.21000000000001 |
| - type: recall_at_20 |
| value: 57.799 |
| - type: recall_at_3 |
| value: 36.494 |
| - type: recall_at_5 |
| value: 42.764 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-english |
| name: MTEB CQADupstackEnglishRetrieval |
| config: default |
| split: test |
| revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
| metrics: |
| - type: map_at_1 |
| value: 19.414 |
| - type: map_at_10 |
| value: 25.766 |
| - type: map_at_100 |
| value: 26.627000000000002 |
| - type: map_at_1000 |
| value: 26.749000000000002 |
| - type: map_at_20 |
| value: 26.201999999999998 |
| - type: map_at_3 |
| value: 23.738 |
| - type: map_at_5 |
| value: 24.829 |
| - type: mrr_at_1 |
| value: 24.013 |
| - type: mrr_at_10 |
| value: 30.208000000000002 |
| - type: mrr_at_100 |
| value: 30.903000000000002 |
| - type: mrr_at_1000 |
| value: 30.976 |
| - type: mrr_at_20 |
| value: 30.585 |
| - type: mrr_at_3 |
| value: 28.376 |
| - type: mrr_at_5 |
| value: 29.462 |
| - type: ndcg_at_1 |
| value: 24.013 |
| - type: ndcg_at_10 |
| value: 29.871 |
| - type: ndcg_at_100 |
| value: 33.867999999999995 |
| - type: ndcg_at_1000 |
| value: 36.565 |
| - type: ndcg_at_20 |
| value: 31.251 |
| - type: ndcg_at_3 |
| value: 26.579000000000004 |
| - type: ndcg_at_5 |
| value: 28.094 |
| - type: precision_at_1 |
| value: 24.013 |
| - type: precision_at_10 |
| value: 5.503 |
| - type: precision_at_100 |
| value: 0.936 |
| - type: precision_at_1000 |
| value: 0.14100000000000001 |
| - type: precision_at_20 |
| value: 3.2800000000000002 |
| - type: precision_at_3 |
| value: 12.590000000000002 |
| - type: precision_at_5 |
| value: 8.994 |
| - type: recall_at_1 |
| value: 19.414 |
| - type: recall_at_10 |
| value: 37.582 |
| - type: recall_at_100 |
| value: 55.181000000000004 |
| - type: recall_at_1000 |
| value: 73.342 |
| - type: recall_at_20 |
| value: 42.596000000000004 |
| - type: recall_at_3 |
| value: 28.102 |
| - type: recall_at_5 |
| value: 32.267 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-gaming |
| name: MTEB CQADupstackGamingRetrieval |
| config: default |
| split: test |
| revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
| metrics: |
| - type: map_at_1 |
| value: 31.5 |
| - type: map_at_10 |
| value: 42.179 |
| - type: map_at_100 |
| value: 43.231 |
| - type: map_at_1000 |
| value: 43.302 |
| - type: map_at_20 |
| value: 42.786 |
| - type: map_at_3 |
| value: 39.17 |
| - type: map_at_5 |
| value: 40.854 |
| - type: mrr_at_1 |
| value: 36.113 |
| - type: mrr_at_10 |
| value: 45.378 |
| - type: mrr_at_100 |
| value: 46.153 |
| - type: mrr_at_1000 |
| value: 46.194 |
| - type: mrr_at_20 |
| value: 45.831 |
| - type: mrr_at_3 |
| value: 42.947 |
| - type: mrr_at_5 |
| value: 44.339 |
| - type: ndcg_at_1 |
| value: 36.113 |
| - type: ndcg_at_10 |
| value: 47.616 |
| - type: ndcg_at_100 |
| value: 52.125 |
| - type: ndcg_at_1000 |
| value: 53.717999999999996 |
| - type: ndcg_at_20 |
| value: 49.495 |
| - type: ndcg_at_3 |
| value: 42.354 |
| - type: ndcg_at_5 |
| value: 44.885999999999996 |
| - type: precision_at_1 |
| value: 36.113 |
| - type: precision_at_10 |
| value: 7.799 |
| - type: precision_at_100 |
| value: 1.093 |
| - type: precision_at_1000 |
| value: 0.129 |
| - type: precision_at_20 |
| value: 4.4670000000000005 |
| - type: precision_at_3 |
| value: 19.017999999999997 |
| - type: precision_at_5 |
| value: 13.254 |
| - type: recall_at_1 |
| value: 31.5 |
| - type: recall_at_10 |
| value: 60.67 |
| - type: recall_at_100 |
| value: 80.484 |
| - type: recall_at_1000 |
| value: 92.04599999999999 |
| - type: recall_at_20 |
| value: 67.644 |
| - type: recall_at_3 |
| value: 46.671 |
| - type: recall_at_5 |
| value: 52.723 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-gis |
| name: MTEB CQADupstackGisRetrieval |
| config: default |
| split: test |
| revision: 5003b3064772da1887988e05400cf3806fe491f2 |
| metrics: |
| - type: map_at_1 |
| value: 17.339 |
| - type: map_at_10 |
| value: 23.014000000000003 |
| - type: map_at_100 |
| value: 23.918 |
| - type: map_at_1000 |
| value: 24.027 |
| - type: map_at_20 |
| value: 23.507 |
| - type: map_at_3 |
| value: 21.176000000000002 |
| - type: map_at_5 |
| value: 22.126 |
| - type: mrr_at_1 |
| value: 18.531 |
| - type: mrr_at_10 |
| value: 24.356 |
| - type: mrr_at_100 |
| value: 25.247000000000003 |
| - type: mrr_at_1000 |
| value: 25.338 |
| - type: mrr_at_20 |
| value: 24.858 |
| - type: mrr_at_3 |
| value: 22.542 |
| - type: mrr_at_5 |
| value: 23.508000000000003 |
| - type: ndcg_at_1 |
| value: 18.531 |
| - type: ndcg_at_10 |
| value: 26.51 |
| - type: ndcg_at_100 |
| value: 31.367 |
| - type: ndcg_at_1000 |
| value: 34.38 |
| - type: ndcg_at_20 |
| value: 28.328999999999997 |
| - type: ndcg_at_3 |
| value: 22.861 |
| - type: ndcg_at_5 |
| value: 24.456 |
| - type: precision_at_1 |
| value: 18.531 |
| - type: precision_at_10 |
| value: 4.147 |
| - type: precision_at_100 |
| value: 0.695 |
| - type: precision_at_1000 |
| value: 0.099 |
| - type: precision_at_20 |
| value: 2.492 |
| - type: precision_at_3 |
| value: 9.793000000000001 |
| - type: precision_at_5 |
| value: 6.825 |
| - type: recall_at_1 |
| value: 17.339 |
| - type: recall_at_10 |
| value: 36.010999999999996 |
| - type: recall_at_100 |
| value: 59.040000000000006 |
| - type: recall_at_1000 |
| value: 82.282 |
| - type: recall_at_20 |
| value: 43.04 |
| - type: recall_at_3 |
| value: 25.904 |
| - type: recall_at_5 |
| value: 29.837000000000003 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-mathematica |
| name: MTEB CQADupstackMathematicaRetrieval |
| config: default |
| split: test |
| revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
| metrics: |
| - type: map_at_1 |
| value: 9.251 |
| - type: map_at_10 |
| value: 14.848 |
| - type: map_at_100 |
| value: 15.940999999999999 |
| - type: map_at_1000 |
| value: 16.055 |
| - type: map_at_20 |
| value: 15.423 |
| - type: map_at_3 |
| value: 12.556999999999999 |
| - type: map_at_5 |
| value: 13.649000000000001 |
| - type: mrr_at_1 |
| value: 12.313 |
| - type: mrr_at_10 |
| value: 18.528 |
| - type: mrr_at_100 |
| value: 19.522000000000002 |
| - type: mrr_at_1000 |
| value: 19.601 |
| - type: mrr_at_20 |
| value: 19.107 |
| - type: mrr_at_3 |
| value: 16.231 |
| - type: mrr_at_5 |
| value: 17.294999999999998 |
| - type: ndcg_at_1 |
| value: 12.313 |
| - type: ndcg_at_10 |
| value: 19.303 |
| - type: ndcg_at_100 |
| value: 24.728 |
| - type: ndcg_at_1000 |
| value: 27.823999999999998 |
| - type: ndcg_at_20 |
| value: 21.318 |
| - type: ndcg_at_3 |
| value: 14.848 |
| - type: ndcg_at_5 |
| value: 16.509 |
| - type: precision_at_1 |
| value: 12.313 |
| - type: precision_at_10 |
| value: 4.03 |
| - type: precision_at_100 |
| value: 0.777 |
| - type: precision_at_1000 |
| value: 0.11800000000000001 |
| - type: precision_at_20 |
| value: 2.562 |
| - type: precision_at_3 |
| value: 7.546 |
| - type: precision_at_5 |
| value: 5.672 |
| - type: recall_at_1 |
| value: 9.251 |
| - type: recall_at_10 |
| value: 29.677999999999997 |
| - type: recall_at_100 |
| value: 53.586 |
| - type: recall_at_1000 |
| value: 76.181 |
| - type: recall_at_20 |
| value: 36.963 |
| - type: recall_at_3 |
| value: 17.072000000000003 |
| - type: recall_at_5 |
| value: 21.481 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-physics |
| name: MTEB CQADupstackPhysicsRetrieval |
| config: default |
| split: test |
| revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
| metrics: |
| - type: map_at_1 |
| value: 21.135 |
| - type: map_at_10 |
| value: 29.431 |
| - type: map_at_100 |
| value: 30.662 |
| - type: map_at_1000 |
| value: 30.792 |
| - type: map_at_20 |
| value: 30.086000000000002 |
| - type: map_at_3 |
| value: 26.593 |
| - type: map_at_5 |
| value: 28.011999999999997 |
| - type: mrr_at_1 |
| value: 26.564 |
| - type: mrr_at_10 |
| value: 34.735 |
| - type: mrr_at_100 |
| value: 35.65 |
| - type: mrr_at_1000 |
| value: 35.711999999999996 |
| - type: mrr_at_20 |
| value: 35.286 |
| - type: mrr_at_3 |
| value: 32.002 |
| - type: mrr_at_5 |
| value: 33.527 |
| - type: ndcg_at_1 |
| value: 26.564 |
| - type: ndcg_at_10 |
| value: 35.108 |
| - type: ndcg_at_100 |
| value: 40.601 |
| - type: ndcg_at_1000 |
| value: 43.329 |
| - type: ndcg_at_20 |
| value: 37.192 |
| - type: ndcg_at_3 |
| value: 29.961 |
| - type: ndcg_at_5 |
| value: 32.131 |
| - type: precision_at_1 |
| value: 26.564 |
| - type: precision_at_10 |
| value: 6.564 |
| - type: precision_at_100 |
| value: 1.105 |
| - type: precision_at_1000 |
| value: 0.154 |
| - type: precision_at_20 |
| value: 3.941 |
| - type: precision_at_3 |
| value: 14.212 |
| - type: precision_at_5 |
| value: 10.337 |
| - type: recall_at_1 |
| value: 21.135 |
| - type: recall_at_10 |
| value: 47.242 |
| - type: recall_at_100 |
| value: 70.645 |
| - type: recall_at_1000 |
| value: 89.403 |
| - type: recall_at_20 |
| value: 54.663 |
| - type: recall_at_3 |
| value: 32.647 |
| - type: recall_at_5 |
| value: 38.122 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-programmers |
| name: MTEB CQADupstackProgrammersRetrieval |
| config: default |
| split: test |
| revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
| metrics: |
| - type: map_at_1 |
| value: 16.86 |
| - type: map_at_10 |
| value: 23.477999999999998 |
| - type: map_at_100 |
| value: 24.68 |
| - type: map_at_1000 |
| value: 24.826999999999998 |
| - type: map_at_20 |
| value: 24.122 |
| - type: map_at_3 |
| value: 21.288999999999998 |
| - type: map_at_5 |
| value: 22.453 |
| - type: mrr_at_1 |
| value: 20.776 |
| - type: mrr_at_10 |
| value: 28.029 |
| - type: mrr_at_100 |
| value: 28.951 |
| - type: mrr_at_1000 |
| value: 29.038000000000004 |
| - type: mrr_at_20 |
| value: 28.546 |
| - type: mrr_at_3 |
| value: 25.818 |
| - type: mrr_at_5 |
| value: 26.994 |
| - type: ndcg_at_1 |
| value: 20.776 |
| - type: ndcg_at_10 |
| value: 28.152 |
| - type: ndcg_at_100 |
| value: 33.82 |
| - type: ndcg_at_1000 |
| value: 37.039 |
| - type: ndcg_at_20 |
| value: 30.238 |
| - type: ndcg_at_3 |
| value: 24.197 |
| - type: ndcg_at_5 |
| value: 25.861 |
| - type: precision_at_1 |
| value: 20.776 |
| - type: precision_at_10 |
| value: 5.297000000000001 |
| - type: precision_at_100 |
| value: 0.96 |
| - type: precision_at_1000 |
| value: 0.14200000000000002 |
| - type: precision_at_20 |
| value: 3.276 |
| - type: precision_at_3 |
| value: 11.606 |
| - type: precision_at_5 |
| value: 8.356 |
| - type: recall_at_1 |
| value: 16.86 |
| - type: recall_at_10 |
| value: 37.782 |
| - type: recall_at_100 |
| value: 62.67 |
| - type: recall_at_1000 |
| value: 85.03 |
| - type: recall_at_20 |
| value: 45.2 |
| - type: recall_at_3 |
| value: 26.506999999999998 |
| - type: recall_at_5 |
| value: 31.113000000000003 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-stats |
| name: MTEB CQADupstackStatsRetrieval |
| config: default |
| split: test |
| revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
| metrics: |
| - type: map_at_1 |
| value: 15.234 |
| - type: map_at_10 |
| value: 20.939 |
| - type: map_at_100 |
| value: 21.704 |
| - type: map_at_1000 |
| value: 21.804000000000002 |
| - type: map_at_20 |
| value: 21.311 |
| - type: map_at_3 |
| value: 18.972 |
| - type: map_at_5 |
| value: 19.929 |
| - type: mrr_at_1 |
| value: 17.485 |
| - type: mrr_at_10 |
| value: 23.267 |
| - type: mrr_at_100 |
| value: 23.967 |
| - type: mrr_at_1000 |
| value: 24.054000000000002 |
| - type: mrr_at_20 |
| value: 23.604 |
| - type: mrr_at_3 |
| value: 21.345 |
| - type: mrr_at_5 |
| value: 22.303 |
| - type: ndcg_at_1 |
| value: 17.485 |
| - type: ndcg_at_10 |
| value: 24.744 |
| - type: ndcg_at_100 |
| value: 28.801 |
| - type: ndcg_at_1000 |
| value: 31.619999999999997 |
| - type: ndcg_at_20 |
| value: 26.046000000000003 |
| - type: ndcg_at_3 |
| value: 20.862 |
| - type: ndcg_at_5 |
| value: 22.459 |
| - type: precision_at_1 |
| value: 17.485 |
| - type: precision_at_10 |
| value: 4.109999999999999 |
| - type: precision_at_100 |
| value: 0.676 |
| - type: precision_at_1000 |
| value: 0.098 |
| - type: precision_at_20 |
| value: 2.3619999999999997 |
| - type: precision_at_3 |
| value: 9.254 |
| - type: precision_at_5 |
| value: 6.503 |
| - type: recall_at_1 |
| value: 15.234 |
| - type: recall_at_10 |
| value: 34.48 |
| - type: recall_at_100 |
| value: 53.225 |
| - type: recall_at_1000 |
| value: 74.64699999999999 |
| - type: recall_at_20 |
| value: 39.421 |
| - type: recall_at_3 |
| value: 23.554 |
| - type: recall_at_5 |
| value: 27.662 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-tex |
| name: MTEB CQADupstackTexRetrieval |
| config: default |
| split: test |
| revision: 46989137a86843e03a6195de44b09deda022eec7 |
| metrics: |
| - type: map_at_1 |
| value: 9.564 |
| - type: map_at_10 |
| value: 13.869000000000002 |
| - type: map_at_100 |
| value: 14.728 |
| - type: map_at_1000 |
| value: 14.853 |
| - type: map_at_20 |
| value: 14.32 |
| - type: map_at_3 |
| value: 12.307 |
| - type: map_at_5 |
| value: 13.177 |
| - type: mrr_at_1 |
| value: 11.941 |
| - type: mrr_at_10 |
| value: 16.777 |
| - type: mrr_at_100 |
| value: 17.571 |
| - type: mrr_at_1000 |
| value: 17.663999999999998 |
| - type: mrr_at_20 |
| value: 17.203 |
| - type: mrr_at_3 |
| value: 15.067 |
| - type: mrr_at_5 |
| value: 16.003999999999998 |
| - type: ndcg_at_1 |
| value: 11.941 |
| - type: ndcg_at_10 |
| value: 17.111 |
| - type: ndcg_at_100 |
| value: 21.438 |
| - type: ndcg_at_1000 |
| value: 24.756 |
| - type: ndcg_at_20 |
| value: 18.616 |
| - type: ndcg_at_3 |
| value: 14.143 |
| - type: ndcg_at_5 |
| value: 15.501000000000001 |
| - type: precision_at_1 |
| value: 11.941 |
| - type: precision_at_10 |
| value: 3.304 |
| - type: precision_at_100 |
| value: 0.658 |
| - type: precision_at_1000 |
| value: 0.11100000000000002 |
| - type: precision_at_20 |
| value: 2.077 |
| - type: precision_at_3 |
| value: 6.882000000000001 |
| - type: precision_at_5 |
| value: 5.12 |
| - type: recall_at_1 |
| value: 9.564 |
| - type: recall_at_10 |
| value: 24.068 |
| - type: recall_at_100 |
| value: 43.759 |
| - type: recall_at_1000 |
| value: 68.101 |
| - type: recall_at_20 |
| value: 29.657 |
| - type: recall_at_3 |
| value: 15.68 |
| - type: recall_at_5 |
| value: 19.238 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-unix |
| name: MTEB CQADupstackUnixRetrieval |
| config: default |
| split: test |
| revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
| metrics: |
| - type: map_at_1 |
| value: 16.171 |
| - type: map_at_10 |
| value: 22.142 |
| - type: map_at_100 |
| value: 23.261000000000003 |
| - type: map_at_1000 |
| value: 23.371 |
| - type: map_at_20 |
| value: 22.766000000000002 |
| - type: map_at_3 |
| value: 20.251 |
| - type: map_at_5 |
| value: 21.349 |
| - type: mrr_at_1 |
| value: 19.403000000000002 |
| - type: mrr_at_10 |
| value: 25.619999999999997 |
| - type: mrr_at_100 |
| value: 26.659 |
| - type: mrr_at_1000 |
| value: 26.735 |
| - type: mrr_at_20 |
| value: 26.212000000000003 |
| - type: mrr_at_3 |
| value: 23.694000000000003 |
| - type: mrr_at_5 |
| value: 24.781 |
| - type: ndcg_at_1 |
| value: 19.403000000000002 |
| - type: ndcg_at_10 |
| value: 26.104 |
| - type: ndcg_at_100 |
| value: 31.724000000000004 |
| - type: ndcg_at_1000 |
| value: 34.581 |
| - type: ndcg_at_20 |
| value: 28.231 |
| - type: ndcg_at_3 |
| value: 22.464000000000002 |
| - type: ndcg_at_5 |
| value: 24.233 |
| - type: precision_at_1 |
| value: 19.403000000000002 |
| - type: precision_at_10 |
| value: 4.422000000000001 |
| - type: precision_at_100 |
| value: 0.8170000000000001 |
| - type: precision_at_1000 |
| value: 0.11800000000000001 |
| - type: precision_at_20 |
| value: 2.78 |
| - type: precision_at_3 |
| value: 10.168000000000001 |
| - type: precision_at_5 |
| value: 7.295 |
| - type: recall_at_1 |
| value: 16.171 |
| - type: recall_at_10 |
| value: 34.899 |
| - type: recall_at_100 |
| value: 60.197 |
| - type: recall_at_1000 |
| value: 80.798 |
| - type: recall_at_20 |
| value: 42.591 |
| - type: recall_at_3 |
| value: 25.024 |
| - type: recall_at_5 |
| value: 29.42 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-webmasters |
| name: MTEB CQADupstackWebmastersRetrieval |
| config: default |
| split: test |
| revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
| metrics: |
| - type: map_at_1 |
| value: 16.412 |
| - type: map_at_10 |
| value: 23.138 |
| - type: map_at_100 |
| value: 24.46 |
| - type: map_at_1000 |
| value: 24.668 |
| - type: map_at_20 |
| value: 23.791 |
| - type: map_at_3 |
| value: 20.965 |
| - type: map_at_5 |
| value: 22.005 |
| - type: mrr_at_1 |
| value: 20.949 |
| - type: mrr_at_10 |
| value: 27.46 |
| - type: mrr_at_100 |
| value: 28.546 |
| - type: mrr_at_1000 |
| value: 28.619 |
| - type: mrr_at_20 |
| value: 28.038999999999998 |
| - type: mrr_at_3 |
| value: 25.461 |
| - type: mrr_at_5 |
| value: 26.528000000000002 |
| - type: ndcg_at_1 |
| value: 20.949 |
| - type: ndcg_at_10 |
| value: 27.919 |
| - type: ndcg_at_100 |
| value: 33.886 |
| - type: ndcg_at_1000 |
| value: 37.284 |
| - type: ndcg_at_20 |
| value: 29.876 |
| - type: ndcg_at_3 |
| value: 24.246000000000002 |
| - type: ndcg_at_5 |
| value: 25.607999999999997 |
| - type: precision_at_1 |
| value: 20.949 |
| - type: precision_at_10 |
| value: 5.534 |
| - type: precision_at_100 |
| value: 1.2409999999999999 |
| - type: precision_at_1000 |
| value: 0.22 |
| - type: precision_at_20 |
| value: 3.5180000000000002 |
| - type: precision_at_3 |
| value: 11.726 |
| - type: precision_at_5 |
| value: 8.498 |
| - type: recall_at_1 |
| value: 16.412 |
| - type: recall_at_10 |
| value: 37.012 |
| - type: recall_at_100 |
| value: 64.702 |
| - type: recall_at_1000 |
| value: 87.442 |
| - type: recall_at_20 |
| value: 44.797 |
| - type: recall_at_3 |
| value: 25.872 |
| - type: recall_at_5 |
| value: 29.732999999999997 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-wordpress |
| name: MTEB CQADupstackWordpressRetrieval |
| config: default |
| split: test |
| revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
| metrics: |
| - type: map_at_1 |
| value: 11.158 |
| - type: map_at_10 |
| value: 15.809999999999999 |
| - type: map_at_100 |
| value: 16.821 |
| - type: map_at_1000 |
| value: 16.925 |
| - type: map_at_20 |
| value: 16.403000000000002 |
| - type: map_at_3 |
| value: 13.791999999999998 |
| - type: map_at_5 |
| value: 14.817 |
| - type: mrr_at_1 |
| value: 12.384 |
| - type: mrr_at_10 |
| value: 17.291999999999998 |
| - type: mrr_at_100 |
| value: 18.271 |
| - type: mrr_at_1000 |
| value: 18.360000000000003 |
| - type: mrr_at_20 |
| value: 17.854999999999997 |
| - type: mrr_at_3 |
| value: 15.096000000000002 |
| - type: mrr_at_5 |
| value: 16.214000000000002 |
| - type: ndcg_at_1 |
| value: 12.384 |
| - type: ndcg_at_10 |
| value: 19.250999999999998 |
| - type: ndcg_at_100 |
| value: 24.524 |
| - type: ndcg_at_1000 |
| value: 27.624 |
| - type: ndcg_at_20 |
| value: 21.387999999999998 |
| - type: ndcg_at_3 |
| value: 14.995 |
| - type: ndcg_at_5 |
| value: 16.861 |
| - type: precision_at_1 |
| value: 12.384 |
| - type: precision_at_10 |
| value: 3.29 |
| - type: precision_at_100 |
| value: 0.632 |
| - type: precision_at_1000 |
| value: 0.095 |
| - type: precision_at_20 |
| value: 2.1260000000000003 |
| - type: precision_at_3 |
| value: 6.47 |
| - type: precision_at_5 |
| value: 4.917 |
| - type: recall_at_1 |
| value: 11.158 |
| - type: recall_at_10 |
| value: 28.737000000000002 |
| - type: recall_at_100 |
| value: 53.400000000000006 |
| - type: recall_at_1000 |
| value: 77.509 |
| - type: recall_at_20 |
| value: 36.969 |
| - type: recall_at_3 |
| value: 17.197000000000003 |
| - type: recall_at_5 |
| value: 21.701 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/climate-fever |
| name: MTEB ClimateFEVER |
| config: default |
| split: test |
| revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
| metrics: |
| - type: map_at_1 |
| value: 7.172000000000001 |
| - type: map_at_10 |
| value: 11.935 |
| - type: map_at_100 |
| value: 13.305 |
| - type: map_at_1000 |
| value: 13.517000000000001 |
| - type: map_at_20 |
| value: 12.589 |
| - type: map_at_3 |
| value: 9.9 |
| - type: map_at_5 |
| value: 10.839 |
| - type: mrr_at_1 |
| value: 15.895999999999999 |
| - type: mrr_at_10 |
| value: 24.215999999999998 |
| - type: mrr_at_100 |
| value: 25.418000000000003 |
| - type: mrr_at_1000 |
| value: 25.480000000000004 |
| - type: mrr_at_20 |
| value: 24.934 |
| - type: mrr_at_3 |
| value: 21.064 |
| - type: mrr_at_5 |
| value: 22.676 |
| - type: ndcg_at_1 |
| value: 15.895999999999999 |
| - type: ndcg_at_10 |
| value: 17.69 |
| - type: ndcg_at_100 |
| value: 24.232 |
| - type: ndcg_at_1000 |
| value: 28.405 |
| - type: ndcg_at_20 |
| value: 19.933999999999997 |
| - type: ndcg_at_3 |
| value: 13.761000000000001 |
| - type: ndcg_at_5 |
| value: 14.963000000000001 |
| - type: precision_at_1 |
| value: 15.895999999999999 |
| - type: precision_at_10 |
| value: 5.733 |
| - type: precision_at_100 |
| value: 1.266 |
| - type: precision_at_1000 |
| value: 0.203 |
| - type: precision_at_20 |
| value: 3.798 |
| - type: precision_at_3 |
| value: 10.076 |
| - type: precision_at_5 |
| value: 7.9479999999999995 |
| - type: recall_at_1 |
| value: 7.172000000000001 |
| - type: recall_at_10 |
| value: 22.149 |
| - type: recall_at_100 |
| value: 45.491 |
| - type: recall_at_1000 |
| value: 69.34 |
| - type: recall_at_20 |
| value: 28.634999999999998 |
| - type: recall_at_3 |
| value: 12.701 |
| - type: recall_at_5 |
| value: 15.952 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/dbpedia |
| name: MTEB DBPedia |
| config: default |
| split: test |
| revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
| metrics: |
| - type: map_at_1 |
| value: 7.101 |
| - type: map_at_10 |
| value: 15.125 |
| - type: map_at_100 |
| value: 20.026 |
| - type: map_at_1000 |
| value: 21.194 |
| - type: map_at_20 |
| value: 17.008000000000003 |
| - type: map_at_3 |
| value: 10.915999999999999 |
| - type: map_at_5 |
| value: 12.705 |
| - type: mrr_at_1 |
| value: 53.5 |
| - type: mrr_at_10 |
| value: 63.475 |
| - type: mrr_at_100 |
| value: 63.998 |
| - type: mrr_at_1000 |
| value: 64.019 |
| - type: mrr_at_20 |
| value: 63.800999999999995 |
| - type: mrr_at_3 |
| value: 62.041999999999994 |
| - type: mrr_at_5 |
| value: 62.678999999999995 |
| - type: ndcg_at_1 |
| value: 41.875 |
| - type: ndcg_at_10 |
| value: 32.967 |
| - type: ndcg_at_100 |
| value: 35.557 |
| - type: ndcg_at_1000 |
| value: 42.537000000000006 |
| - type: ndcg_at_20 |
| value: 31.930999999999997 |
| - type: ndcg_at_3 |
| value: 36.67 |
| - type: ndcg_at_5 |
| value: 34.474 |
| - type: precision_at_1 |
| value: 53.5 |
| - type: precision_at_10 |
| value: 27.0 |
| - type: precision_at_100 |
| value: 7.872999999999999 |
| - type: precision_at_1000 |
| value: 1.637 |
| - type: precision_at_20 |
| value: 19.487 |
| - type: precision_at_3 |
| value: 41.583 |
| - type: precision_at_5 |
| value: 34.699999999999996 |
| - type: recall_at_1 |
| value: 7.101 |
| - type: recall_at_10 |
| value: 20.408 |
| - type: recall_at_100 |
| value: 40.286 |
| - type: recall_at_1000 |
| value: 63.49399999999999 |
| - type: recall_at_20 |
| value: 25.478 |
| - type: recall_at_3 |
| value: 12.278 |
| - type: recall_at_5 |
| value: 15.392 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/emotion |
| name: MTEB EmotionClassification |
| config: default |
| split: test |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
| metrics: |
| - type: accuracy |
| value: 44.79 |
| - type: f1 |
| value: 39.606429663804356 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/fever |
| name: MTEB FEVER |
| config: default |
| split: test |
| revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
| metrics: |
| - type: map_at_1 |
| value: 27.898 |
| - type: map_at_10 |
| value: 39.315 |
| - type: map_at_100 |
| value: 40.219 |
| - type: map_at_1000 |
| value: 40.268 |
| - type: map_at_20 |
| value: 39.893 |
| - type: map_at_3 |
| value: 35.993 |
| - type: map_at_5 |
| value: 38.016 |
| - type: mrr_at_1 |
| value: 30.003 |
| - type: mrr_at_10 |
| value: 41.85 |
| - type: mrr_at_100 |
| value: 42.722 |
| - type: mrr_at_1000 |
| value: 42.760999999999996 |
| - type: mrr_at_20 |
| value: 42.419000000000004 |
| - type: mrr_at_3 |
| value: 38.451 |
| - type: mrr_at_5 |
| value: 40.547 |
| - type: ndcg_at_1 |
| value: 30.003 |
| - type: ndcg_at_10 |
| value: 45.907 |
| - type: ndcg_at_100 |
| value: 50.198 |
| - type: ndcg_at_1000 |
| value: 51.405 |
| - type: ndcg_at_20 |
| value: 47.97 |
| - type: ndcg_at_3 |
| value: 39.234 |
| - type: ndcg_at_5 |
| value: 42.844 |
| - type: precision_at_1 |
| value: 30.003 |
| - type: precision_at_10 |
| value: 7.0040000000000004 |
| - type: precision_at_100 |
| value: 0.9259999999999999 |
| - type: precision_at_1000 |
| value: 0.104 |
| - type: precision_at_20 |
| value: 3.9510000000000005 |
| - type: precision_at_3 |
| value: 16.647000000000002 |
| - type: precision_at_5 |
| value: 11.914 |
| - type: recall_at_1 |
| value: 27.898 |
| - type: recall_at_10 |
| value: 64.003 |
| - type: recall_at_100 |
| value: 83.42500000000001 |
| - type: recall_at_1000 |
| value: 92.448 |
| - type: recall_at_20 |
| value: 71.93 |
| - type: recall_at_3 |
| value: 46.12 |
| - type: recall_at_5 |
| value: 54.812000000000005 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/fiqa |
| name: MTEB FiQA2018 |
| config: default |
| split: test |
| revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
| metrics: |
| - type: map_at_1 |
| value: 10.282 |
| - type: map_at_10 |
| value: 16.141 |
| - type: map_at_100 |
| value: 17.634 |
| - type: map_at_1000 |
| value: 17.836 |
| - type: map_at_20 |
| value: 16.99 |
| - type: map_at_3 |
| value: 13.947000000000001 |
| - type: map_at_5 |
| value: 15.149000000000001 |
| - type: mrr_at_1 |
| value: 20.679 |
| - type: mrr_at_10 |
| value: 26.966 |
| - type: mrr_at_100 |
| value: 28.108 |
| - type: mrr_at_1000 |
| value: 28.183999999999997 |
| - type: mrr_at_20 |
| value: 27.672 |
| - type: mrr_at_3 |
| value: 24.743000000000002 |
| - type: mrr_at_5 |
| value: 25.916 |
| - type: ndcg_at_1 |
| value: 20.679 |
| - type: ndcg_at_10 |
| value: 21.291 |
| - type: ndcg_at_100 |
| value: 27.884999999999998 |
| - type: ndcg_at_1000 |
| value: 32.122 |
| - type: ndcg_at_20 |
| value: 23.898 |
| - type: ndcg_at_3 |
| value: 18.553 |
| - type: ndcg_at_5 |
| value: 19.468 |
| - type: precision_at_1 |
| value: 20.679 |
| - type: precision_at_10 |
| value: 6.019 |
| - type: precision_at_100 |
| value: 1.252 |
| - type: precision_at_1000 |
| value: 0.201 |
| - type: precision_at_20 |
| value: 4.0120000000000005 |
| - type: precision_at_3 |
| value: 12.243 |
| - type: precision_at_5 |
| value: 9.321 |
| - type: recall_at_1 |
| value: 10.282 |
| - type: recall_at_10 |
| value: 25.901999999999997 |
| - type: recall_at_100 |
| value: 50.956999999999994 |
| - type: recall_at_1000 |
| value: 76.935 |
| - type: recall_at_20 |
| value: 34.104 |
| - type: recall_at_3 |
| value: 16.973 |
| - type: recall_at_5 |
| value: 20.549999999999997 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/hotpotqa |
| name: MTEB HotpotQA |
| config: default |
| split: test |
| revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
| metrics: |
| - type: map_at_1 |
| value: 30.567 |
| - type: map_at_10 |
| value: 42.314 |
| - type: map_at_100 |
| value: 43.205 |
| - type: map_at_1000 |
| value: 43.288 |
| - type: map_at_20 |
| value: 42.812 |
| - type: map_at_3 |
| value: 39.695 |
| - type: map_at_5 |
| value: 41.214 |
| - type: mrr_at_1 |
| value: 61.134 |
| - type: mrr_at_10 |
| value: 68.57600000000001 |
| - type: mrr_at_100 |
| value: 68.95599999999999 |
| - type: mrr_at_1000 |
| value: 68.97999999999999 |
| - type: mrr_at_20 |
| value: 68.818 |
| - type: mrr_at_3 |
| value: 66.99300000000001 |
| - type: mrr_at_5 |
| value: 67.919 |
| - type: ndcg_at_1 |
| value: 61.134 |
| - type: ndcg_at_10 |
| value: 51.518 |
| - type: ndcg_at_100 |
| value: 55.022000000000006 |
| - type: ndcg_at_1000 |
| value: 56.81699999999999 |
| - type: ndcg_at_20 |
| value: 52.893 |
| - type: ndcg_at_3 |
| value: 47.216 |
| - type: ndcg_at_5 |
| value: 49.413000000000004 |
| - type: precision_at_1 |
| value: 61.134 |
| - type: precision_at_10 |
| value: 10.729 |
| - type: precision_at_100 |
| value: 1.351 |
| - type: precision_at_1000 |
| value: 0.159 |
| - type: precision_at_20 |
| value: 5.8069999999999995 |
| - type: precision_at_3 |
| value: 29.336000000000002 |
| - type: precision_at_5 |
| value: 19.346 |
| - type: recall_at_1 |
| value: 30.567 |
| - type: recall_at_10 |
| value: 53.64600000000001 |
| - type: recall_at_100 |
| value: 67.562 |
| - type: recall_at_1000 |
| value: 79.521 |
| - type: recall_at_20 |
| value: 58.069 |
| - type: recall_at_3 |
| value: 44.004 |
| - type: recall_at_5 |
| value: 48.366 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/imdb |
| name: MTEB ImdbClassification |
| config: default |
| split: test |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
| metrics: |
| - type: accuracy |
| value: 71.5272 |
| - type: ap |
| value: 65.49215755861609 |
| - type: f1 |
| value: 71.4156268611186 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/msmarco |
| name: MTEB MSMARCO |
| config: default |
| split: dev |
| revision: c5a29a104738b98a9e76336939199e264163d4a0 |
| metrics: |
| - type: map_at_1 |
| value: 14.574000000000002 |
| - type: map_at_10 |
| value: 23.966 |
| - type: map_at_100 |
| value: 25.19 |
| - type: map_at_1000 |
| value: 25.266 |
| - type: map_at_20 |
| value: 24.668 |
| - type: map_at_3 |
| value: 20.815 |
| - type: map_at_5 |
| value: 22.576 |
| - type: mrr_at_1 |
| value: 14.957 |
| - type: mrr_at_10 |
| value: 24.413999999999998 |
| - type: mrr_at_100 |
| value: 25.616 |
| - type: mrr_at_1000 |
| value: 25.685999999999996 |
| - type: mrr_at_20 |
| value: 25.11 |
| - type: mrr_at_3 |
| value: 21.304000000000002 |
| - type: mrr_at_5 |
| value: 23.047 |
| - type: ndcg_at_1 |
| value: 14.957 |
| - type: ndcg_at_10 |
| value: 29.49 |
| - type: ndcg_at_100 |
| value: 35.734 |
| - type: ndcg_at_1000 |
| value: 37.785000000000004 |
| - type: ndcg_at_20 |
| value: 32.004 |
| - type: ndcg_at_3 |
| value: 23.006999999999998 |
| - type: ndcg_at_5 |
| value: 26.154 |
| - type: precision_at_1 |
| value: 14.957 |
| - type: precision_at_10 |
| value: 4.8500000000000005 |
| - type: precision_at_100 |
| value: 0.8009999999999999 |
| - type: precision_at_1000 |
| value: 0.098 |
| - type: precision_at_20 |
| value: 2.943 |
| - type: precision_at_3 |
| value: 9.962 |
| - type: precision_at_5 |
| value: 7.556 |
| - type: recall_at_1 |
| value: 14.574000000000002 |
| - type: recall_at_10 |
| value: 46.655 |
| - type: recall_at_100 |
| value: 76.26899999999999 |
| - type: recall_at_1000 |
| value: 92.303 |
| - type: recall_at_20 |
| value: 56.424 |
| - type: recall_at_3 |
| value: 28.874 |
| - type: recall_at_5 |
| value: 36.441 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_domain |
| name: MTEB MTOPDomainClassification (en) |
| config: en |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 90.78887368901049 |
| - type: f1 |
| value: 90.30465646125157 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_intent |
| name: MTEB MTOPIntentClassification (en) |
| config: en |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
| - type: accuracy |
| value: 68.71865025079799 |
| - type: f1 |
| value: 50.7484789245504 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (en) |
| config: en |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
| - type: accuracy |
| value: 68.8399462004035 |
| - type: f1 |
| value: 66.66574227334513 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (en) |
| config: en |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 73.74915938130464 |
| - type: f1 |
| value: 73.61179700374726 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-p2p |
| name: MTEB MedrxivClusteringP2P |
| config: default |
| split: test |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
| metrics: |
| - type: v_measure |
| value: 30.3983428793953 |
| - type: v_measures |
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| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-s2s |
| name: MTEB MedrxivClusteringS2S |
| config: default |
| split: test |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
| metrics: |
| - type: v_measure |
| value: 28.78917156239751 |
| - type: v_measures |
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| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/nfcorpus |
| name: MTEB NFCorpus |
| config: default |
| split: test |
| revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
| metrics: |
| - type: map_at_1 |
| value: 3.726 |
| - type: map_at_10 |
| value: 8.604000000000001 |
| - type: map_at_100 |
| value: 10.95 |
| - type: map_at_1000 |
| value: 12.256 |
| - type: map_at_20 |
| value: 9.573 |
| - type: map_at_3 |
| value: 6.264 |
| - type: map_at_5 |
| value: 7.343 |
| - type: mrr_at_1 |
| value: 37.771 |
| - type: mrr_at_10 |
| value: 46.476 |
| - type: mrr_at_100 |
| value: 47.164 |
| - type: mrr_at_1000 |
| value: 47.213 |
| - type: mrr_at_20 |
| value: 46.792 |
| - type: mrr_at_3 |
| value: 44.272 |
| - type: mrr_at_5 |
| value: 45.728 |
| - type: ndcg_at_1 |
| value: 35.604 |
| - type: ndcg_at_10 |
| value: 26.778000000000002 |
| - type: ndcg_at_100 |
| value: 24.313000000000002 |
| - type: ndcg_at_1000 |
| value: 33.601 |
| - type: ndcg_at_20 |
| value: 24.788 |
| - type: ndcg_at_3 |
| value: 30.991999999999997 |
| - type: ndcg_at_5 |
| value: 28.9 |
| - type: precision_at_1 |
| value: 37.152 |
| - type: precision_at_10 |
| value: 19.875999999999998 |
| - type: precision_at_100 |
| value: 6.449000000000001 |
| - type: precision_at_1000 |
| value: 1.934 |
| - type: precision_at_20 |
| value: 14.721 |
| - type: precision_at_3 |
| value: 28.999000000000002 |
| - type: precision_at_5 |
| value: 24.582 |
| - type: recall_at_1 |
| value: 3.726 |
| - type: recall_at_10 |
| value: 12.529000000000002 |
| - type: recall_at_100 |
| value: 25.726 |
| - type: recall_at_1000 |
| value: 58.336 |
| - type: recall_at_20 |
| value: 16.028000000000002 |
| - type: recall_at_3 |
| value: 7.176 |
| - type: recall_at_5 |
| value: 9.511 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/nq |
| name: MTEB NQ |
| config: default |
| split: test |
| revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
| metrics: |
| - type: map_at_1 |
| value: 15.110000000000001 |
| - type: map_at_10 |
| value: 25.983 |
| - type: map_at_100 |
| value: 27.332 |
| - type: map_at_1000 |
| value: 27.406999999999996 |
| - type: map_at_20 |
| value: 26.804 |
| - type: map_at_3 |
| value: 22.182 |
| - type: map_at_5 |
| value: 24.247 |
| - type: mrr_at_1 |
| value: 17.236 |
| - type: mrr_at_10 |
| value: 28.177999999999997 |
| - type: mrr_at_100 |
| value: 29.346 |
| - type: mrr_at_1000 |
| value: 29.401 |
| - type: mrr_at_20 |
| value: 28.906 |
| - type: mrr_at_3 |
| value: 24.593999999999998 |
| - type: mrr_at_5 |
| value: 26.540999999999997 |
| - type: ndcg_at_1 |
| value: 17.207 |
| - type: ndcg_at_10 |
| value: 32.603 |
| - type: ndcg_at_100 |
| value: 38.883 |
| - type: ndcg_at_1000 |
| value: 40.708 |
| - type: ndcg_at_20 |
| value: 35.397 |
| - type: ndcg_at_3 |
| value: 25.002999999999997 |
| - type: ndcg_at_5 |
| value: 28.572999999999997 |
| - type: precision_at_1 |
| value: 17.207 |
| - type: precision_at_10 |
| value: 5.985 |
| - type: precision_at_100 |
| value: 0.951 |
| - type: precision_at_1000 |
| value: 0.11299999999999999 |
| - type: precision_at_20 |
| value: 3.656 |
| - type: precision_at_3 |
| value: 11.848 |
| - type: precision_at_5 |
| value: 9.125 |
| - type: recall_at_1 |
| value: 15.110000000000001 |
| - type: recall_at_10 |
| value: 51.00900000000001 |
| - type: recall_at_100 |
| value: 79.193 |
| - type: recall_at_1000 |
| value: 92.828 |
| - type: recall_at_20 |
| value: 61.402 |
| - type: recall_at_3 |
| value: 30.791 |
| - type: recall_at_5 |
| value: 39.091 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/quora |
| name: MTEB QuoraRetrieval |
| config: default |
| split: test |
| revision: e4e08e0b7dbe3c8700f0daef558ff32256715259 |
| metrics: |
| - type: map_at_1 |
| value: 67.465 |
| - type: map_at_10 |
| value: 81.035 |
| - type: map_at_100 |
| value: 81.718 |
| - type: map_at_1000 |
| value: 81.742 |
| - type: map_at_20 |
| value: 81.486 |
| - type: map_at_3 |
| value: 77.972 |
| - type: map_at_5 |
| value: 79.903 |
| - type: mrr_at_1 |
| value: 77.64 |
| - type: mrr_at_10 |
| value: 84.584 |
| - type: mrr_at_100 |
| value: 84.722 |
| - type: mrr_at_1000 |
| value: 84.724 |
| - type: mrr_at_20 |
| value: 84.684 |
| - type: mrr_at_3 |
| value: 83.325 |
| - type: mrr_at_5 |
| value: 84.15899999999999 |
| - type: ndcg_at_1 |
| value: 77.66999999999999 |
| - type: ndcg_at_10 |
| value: 85.30499999999999 |
| - type: ndcg_at_100 |
| value: 86.834 |
| - type: ndcg_at_1000 |
| value: 87.033 |
| - type: ndcg_at_20 |
| value: 86.12100000000001 |
| - type: ndcg_at_3 |
| value: 81.974 |
| - type: ndcg_at_5 |
| value: 83.813 |
| - type: precision_at_1 |
| value: 77.66999999999999 |
| - type: precision_at_10 |
| value: 12.931000000000001 |
| - type: precision_at_100 |
| value: 1.5 |
| - type: precision_at_1000 |
| value: 0.156 |
| - type: precision_at_20 |
| value: 6.903 |
| - type: precision_at_3 |
| value: 35.730000000000004 |
| - type: precision_at_5 |
| value: 23.642 |
| - type: recall_at_1 |
| value: 67.465 |
| - type: recall_at_10 |
| value: 93.581 |
| - type: recall_at_100 |
| value: 98.91499999999999 |
| - type: recall_at_1000 |
| value: 99.90599999999999 |
| - type: recall_at_20 |
| value: 96.221 |
| - type: recall_at_3 |
| value: 84.071 |
| - type: recall_at_5 |
| value: 89.14999999999999 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering |
| name: MTEB RedditClustering |
| config: default |
| split: test |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| metrics: |
| - type: v_measure |
| value: 45.929215298244664 |
| - type: v_measures |
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0.43113656944924467] |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering-p2p |
| name: MTEB RedditClusteringP2P |
| config: default |
| split: test |
| revision: 385e3cb46b4cfa89021f56c4380204149d0efe33 |
| metrics: |
| - type: v_measure |
| value: 51.444598402601414 |
| - type: v_measures |
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| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/scidocs |
| name: MTEB SCIDOCS |
| config: default |
| split: test |
| revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88 |
| metrics: |
| - type: map_at_1 |
| value: 3.5929999999999995 |
| - type: map_at_10 |
| value: 8.753 |
| - type: map_at_100 |
| value: 10.349 |
| - type: map_at_1000 |
| value: 10.624 |
| - type: map_at_20 |
| value: 9.553 |
| - type: map_at_3 |
| value: 6.2700000000000005 |
| - type: map_at_5 |
| value: 7.5329999999999995 |
| - type: mrr_at_1 |
| value: 17.7 |
| - type: mrr_at_10 |
| value: 27.167 |
| - type: mrr_at_100 |
| value: 28.351 |
| - type: mrr_at_1000 |
| value: 28.418 |
| - type: mrr_at_20 |
| value: 27.819 |
| - type: mrr_at_3 |
| value: 24.282999999999998 |
| - type: mrr_at_5 |
| value: 26.073 |
| - type: ndcg_at_1 |
| value: 17.7 |
| - type: ndcg_at_10 |
| value: 15.312000000000001 |
| - type: ndcg_at_100 |
| value: 22.178 |
| - type: ndcg_at_1000 |
| value: 27.575 |
| - type: ndcg_at_20 |
| value: 17.648 |
| - type: ndcg_at_3 |
| value: 14.41 |
| - type: ndcg_at_5 |
| value: 12.774 |
| - type: precision_at_1 |
| value: 17.7 |
| - type: precision_at_10 |
| value: 7.93 |
| - type: precision_at_100 |
| value: 1.7930000000000001 |
| - type: precision_at_1000 |
| value: 0.31 |
| - type: precision_at_20 |
| value: 5.315 |
| - type: precision_at_3 |
| value: 13.367 |
| - type: precision_at_5 |
| value: 11.26 |
| - type: recall_at_1 |
| value: 3.5929999999999995 |
| - type: recall_at_10 |
| value: 16.088 |
| - type: recall_at_100 |
| value: 36.39 |
| - type: recall_at_1000 |
| value: 62.932 |
| - type: recall_at_20 |
| value: 21.562 |
| - type: recall_at_3 |
| value: 8.123 |
| - type: recall_at_5 |
| value: 11.393 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sickr-sts |
| name: MTEB SICK-R |
| config: default |
| split: test |
| revision: 20a6d6f312dd54037fe07a32d58e5e168867909d |
| metrics: |
| - type: cos_sim_pearson |
| value: 82.6885494958054 |
| - type: cos_sim_spearman |
| value: 76.0433546110243 |
| - type: euclidean_pearson |
| value: 79.85820435751087 |
| - type: euclidean_spearman |
| value: 75.9326257444857 |
| - type: manhattan_pearson |
| value: 79.6973024858654 |
| - type: manhattan_spearman |
| value: 75.71084698490509 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts12-sts |
| name: MTEB STS12 |
| config: default |
| split: test |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| metrics: |
| - type: cos_sim_pearson |
| value: 77.34659218404506 |
| - type: cos_sim_spearman |
| value: 69.49541146727839 |
| - type: euclidean_pearson |
| value: 74.80982564474151 |
| - type: euclidean_spearman |
| value: 70.04102091813081 |
| - type: manhattan_pearson |
| value: 75.00200126757426 |
| - type: manhattan_spearman |
| value: 70.22802660355588 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts13-sts |
| name: MTEB STS13 |
| config: default |
| split: test |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| metrics: |
| - type: cos_sim_pearson |
| value: 79.91444494464905 |
| - type: cos_sim_spearman |
| value: 80.96085686108583 |
| - type: euclidean_pearson |
| value: 80.5915387592164 |
| - type: euclidean_spearman |
| value: 80.8861855866439 |
| - type: manhattan_pearson |
| value: 80.46881359994653 |
| - type: manhattan_spearman |
| value: 80.80230339264102 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts14-sts |
| name: MTEB STS14 |
| config: default |
| split: test |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| metrics: |
| - type: cos_sim_pearson |
| value: 80.81974904249208 |
| - type: cos_sim_spearman |
| value: 77.08348207580887 |
| - type: euclidean_pearson |
| value: 80.13431221409199 |
| - type: euclidean_spearman |
| value: 77.31778188790902 |
| - type: manhattan_pearson |
| value: 80.05343415464556 |
| - type: manhattan_spearman |
| value: 77.26095229151665 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts15-sts |
| name: MTEB STS15 |
| config: default |
| split: test |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| metrics: |
| - type: cos_sim_pearson |
| value: 84.37398871508579 |
| - type: cos_sim_spearman |
| value: 85.41548418250477 |
| - type: euclidean_pearson |
| value: 85.18569982361353 |
| - type: euclidean_spearman |
| value: 85.73446512176643 |
| - type: manhattan_pearson |
| value: 85.1016252976206 |
| - type: manhattan_spearman |
| value: 85.66092136939069 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts16-sts |
| name: MTEB STS16 |
| config: default |
| split: test |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| metrics: |
| - type: cos_sim_pearson |
| value: 80.59702638640928 |
| - type: cos_sim_spearman |
| value: 82.29583005583622 |
| - type: euclidean_pearson |
| value: 81.83307796549182 |
| - type: euclidean_spearman |
| value: 82.39554204652183 |
| - type: manhattan_pearson |
| value: 81.78282737393326 |
| - type: manhattan_spearman |
| value: 82.34235304571907 |
| - 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: 86.89190122908971 |
| - type: cos_sim_spearman |
| value: 88.03461344591356 |
| - type: euclidean_pearson |
| value: 87.81999485969313 |
| - type: euclidean_spearman |
| value: 88.07040076481854 |
| - type: manhattan_pearson |
| value: 87.53382294293554 |
| - type: manhattan_spearman |
| value: 87.76615089464353 |
| - 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: 57.97869820676485 |
| - type: cos_sim_spearman |
| value: 64.12171377270657 |
| - type: euclidean_pearson |
| value: 60.9601725696545 |
| - type: euclidean_spearman |
| value: 63.48982922146721 |
| - type: manhattan_pearson |
| value: 61.37553142926566 |
| - type: manhattan_spearman |
| value: 63.759462595791796 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/stsbenchmark-sts |
| name: MTEB STSBenchmark |
| config: default |
| split: test |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
| metrics: |
| - type: cos_sim_pearson |
| value: 83.14812517797631 |
| - type: cos_sim_spearman |
| value: 83.33681512924129 |
| - type: euclidean_pearson |
| value: 84.0552689078266 |
| - type: euclidean_spearman |
| value: 83.45075258664495 |
| - type: manhattan_pearson |
| value: 83.94309504683835 |
| - type: manhattan_spearman |
| value: 83.37311472277489 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/scidocs-reranking |
| name: MTEB SciDocsRR |
| config: default |
| split: test |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| metrics: |
| - type: map |
| value: 77.89395841192561 |
| - type: mrr |
| value: 93.39039319431475 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/scifact |
| name: MTEB SciFact |
| config: default |
| split: test |
| revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
| metrics: |
| - type: map_at_1 |
| value: 47.65 |
| - type: map_at_10 |
| value: 58.287 |
| - type: map_at_100 |
| value: 58.965999999999994 |
| - type: map_at_1000 |
| value: 58.998 |
| - type: map_at_20 |
| value: 58.709 |
| - type: map_at_3 |
| value: 55.272 |
| - type: map_at_5 |
| value: 57.135999999999996 |
| - type: mrr_at_1 |
| value: 50.333000000000006 |
| - type: mrr_at_10 |
| value: 59.589999999999996 |
| - type: mrr_at_100 |
| value: 60.129999999999995 |
| - type: mrr_at_1000 |
| value: 60.162000000000006 |
| - type: mrr_at_20 |
| value: 59.95700000000001 |
| - type: mrr_at_3 |
| value: 57.389 |
| - type: mrr_at_5 |
| value: 58.656 |
| - type: ndcg_at_1 |
| value: 50.333000000000006 |
| - type: ndcg_at_10 |
| value: 63.232 |
| - type: ndcg_at_100 |
| value: 66.213 |
| - type: ndcg_at_1000 |
| value: 67.203 |
| - type: ndcg_at_20 |
| value: 64.63499999999999 |
| - type: ndcg_at_3 |
| value: 58.163 |
| - type: ndcg_at_5 |
| value: 60.785999999999994 |
| - type: precision_at_1 |
| value: 50.333000000000006 |
| - type: precision_at_10 |
| value: 8.633000000000001 |
| - type: precision_at_100 |
| value: 1.03 |
| - type: precision_at_1000 |
| value: 0.11100000000000002 |
| - type: precision_at_20 |
| value: 4.633 |
| - type: precision_at_3 |
| value: 22.889 |
| - type: precision_at_5 |
| value: 15.4 |
| - type: recall_at_1 |
| value: 47.65 |
| - type: recall_at_10 |
| value: 76.95 |
| - type: recall_at_100 |
| value: 90.333 |
| - type: recall_at_1000 |
| value: 98.333 |
| - type: recall_at_20 |
| value: 82.267 |
| - type: recall_at_3 |
| value: 63.632999999999996 |
| - type: recall_at_5 |
| value: 69.978 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/sprintduplicatequestions-pairclassification |
| name: MTEB SprintDuplicateQuestions |
| config: default |
| split: test |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 99.82277227722773 |
| - type: cos_sim_ap |
| value: 95.3535743677476 |
| - type: cos_sim_f1 |
| value: 91.00050276520865 |
| - type: cos_sim_precision |
| value: 91.50657229524772 |
| - type: cos_sim_recall |
| value: 90.5 |
| - type: dot_accuracy |
| value: 99.73267326732673 |
| - type: dot_ap |
| value: 92.1266370356305 |
| - type: dot_f1 |
| value: 86.13810741687979 |
| - type: dot_precision |
| value: 88.1675392670157 |
| - type: dot_recall |
| value: 84.2 |
| - type: euclidean_accuracy |
| value: 99.82277227722773 |
| - type: euclidean_ap |
| value: 95.24537694377634 |
| - type: euclidean_f1 |
| value: 90.91831557584982 |
| - type: euclidean_precision |
| value: 92.27600411946447 |
| - type: euclidean_recall |
| value: 89.60000000000001 |
| - type: manhattan_accuracy |
| value: 99.81881188118813 |
| - type: manhattan_ap |
| value: 95.30188096008806 |
| - type: manhattan_f1 |
| value: 90.83625438157236 |
| - type: manhattan_precision |
| value: 90.97291875626881 |
| - type: manhattan_recall |
| value: 90.7 |
| - type: max_accuracy |
| value: 99.82277227722773 |
| - type: max_ap |
| value: 95.3535743677476 |
| - type: max_f1 |
| value: 91.00050276520865 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering |
| name: MTEB StackExchangeClustering |
| config: default |
| split: test |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
| metrics: |
| - type: v_measure |
| value: 52.18146042107239 |
| - type: v_measures |
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0.5139233234458377] |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering-p2p |
| name: MTEB StackExchangeClusteringP2P |
| config: default |
| split: test |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
| metrics: |
| - type: v_measure |
| value: 30.666751785479224 |
| - type: v_measures |
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| - task: |
| type: Reranking |
| dataset: |
| type: mteb/stackoverflowdupquestions-reranking |
| name: MTEB StackOverflowDupQuestions |
| config: default |
| split: test |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
| metrics: |
| - type: map |
| value: 46.78149995864765 |
| - type: mrr |
| value: 47.45282393260334 |
| - task: |
| type: Summarization |
| dataset: |
| type: mteb/summeval |
| name: MTEB SummEval |
| config: default |
| split: test |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
| metrics: |
| - type: cos_sim_pearson |
| value: 31.202698233290022 |
| - type: cos_sim_spearman |
| value: 30.971936219818662 |
| - type: dot_pearson |
| value: 25.486069760264634 |
| - type: dot_spearman |
| value: 25.811060638581246 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/trec-covid |
| name: MTEB TRECCOVID |
| config: default |
| split: test |
| revision: bb9466bac8153a0349341eb1b22e06409e78ef4e |
| metrics: |
| - type: map_at_1 |
| value: 0.16999999999999998 |
| - type: map_at_10 |
| value: 0.943 |
| - type: map_at_100 |
| value: 5.0200000000000005 |
| - type: map_at_1000 |
| value: 13.855 |
| - type: map_at_20 |
| value: 1.609 |
| - type: map_at_3 |
| value: 0.384 |
| - type: map_at_5 |
| value: 0.5660000000000001 |
| - type: mrr_at_1 |
| value: 68.0 |
| - type: mrr_at_10 |
| value: 77.983 |
| - type: mrr_at_100 |
| value: 78.16499999999999 |
| - type: mrr_at_1000 |
| value: 78.16499999999999 |
| - type: mrr_at_20 |
| value: 78.16499999999999 |
| - type: mrr_at_3 |
| value: 75.667 |
| - type: mrr_at_5 |
| value: 77.067 |
| - type: ndcg_at_1 |
| value: 62.0 |
| - type: ndcg_at_10 |
| value: 47.772999999999996 |
| - type: ndcg_at_100 |
| value: 36.15 |
| - type: ndcg_at_1000 |
| value: 36.071 |
| - type: ndcg_at_20 |
| value: 44.641 |
| - type: ndcg_at_3 |
| value: 52.608999999999995 |
| - type: ndcg_at_5 |
| value: 50.397999999999996 |
| - type: precision_at_1 |
| value: 68.0 |
| - type: precision_at_10 |
| value: 50.8 |
| - type: precision_at_100 |
| value: 37.62 |
| - type: precision_at_1000 |
| value: 16.97 |
| - type: precision_at_20 |
| value: 47.099999999999994 |
| - type: precision_at_3 |
| value: 56.667 |
| - type: precision_at_5 |
| value: 54.0 |
| - type: recall_at_1 |
| value: 0.16999999999999998 |
| - type: recall_at_10 |
| value: 1.2349999999999999 |
| - type: recall_at_100 |
| value: 8.666 |
| - type: recall_at_1000 |
| value: 35.326 |
| - type: recall_at_20 |
| value: 2.276 |
| - type: recall_at_3 |
| value: 0.428 |
| - type: recall_at_5 |
| value: 0.672 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/touche2020 |
| name: MTEB Touche2020 |
| config: default |
| split: test |
| revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
| metrics: |
| - type: map_at_1 |
| value: 1.897 |
| - type: map_at_10 |
| value: 6.034 |
| - type: map_at_100 |
| value: 10.475 |
| - type: map_at_1000 |
| value: 11.95 |
| - type: map_at_20 |
| value: 8.149000000000001 |
| - type: map_at_3 |
| value: 2.8449999999999998 |
| - type: map_at_5 |
| value: 3.972 |
| - type: mrr_at_1 |
| value: 24.490000000000002 |
| - type: mrr_at_10 |
| value: 33.751 |
| - type: mrr_at_100 |
| value: 35.544 |
| - type: mrr_at_1000 |
| value: 35.544 |
| - type: mrr_at_20 |
| value: 34.926 |
| - type: mrr_at_3 |
| value: 29.252 |
| - type: mrr_at_5 |
| value: 31.905 |
| - type: ndcg_at_1 |
| value: 22.448999999999998 |
| - type: ndcg_at_10 |
| value: 16.303 |
| - type: ndcg_at_100 |
| value: 27.165 |
| - type: ndcg_at_1000 |
| value: 39.736 |
| - type: ndcg_at_20 |
| value: 18.340999999999998 |
| - type: ndcg_at_3 |
| value: 15.137999999999998 |
| - type: ndcg_at_5 |
| value: 16.332 |
| - type: precision_at_1 |
| value: 24.490000000000002 |
| - type: precision_at_10 |
| value: 15.714 |
| - type: precision_at_100 |
| value: 6.184 |
| - type: precision_at_1000 |
| value: 1.439 |
| - type: precision_at_20 |
| value: 13.163 |
| - type: precision_at_3 |
| value: 15.645999999999999 |
| - type: precision_at_5 |
| value: 17.551 |
| - type: recall_at_1 |
| value: 1.897 |
| - type: recall_at_10 |
| value: 11.938 |
| - type: recall_at_100 |
| value: 39.249 |
| - type: recall_at_1000 |
| value: 78.121 |
| - type: recall_at_20 |
| value: 19.244 |
| - type: recall_at_3 |
| value: 3.5409999999999995 |
| - type: recall_at_5 |
| value: 6.297999999999999 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/toxic_conversations_50k |
| name: MTEB ToxicConversationsClassification |
| config: default |
| split: test |
| revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de |
| metrics: |
| - type: accuracy |
| value: 66.2939453125 |
| - type: ap |
| value: 11.764275936169392 |
| - type: f1 |
| value: 50.50689429240701 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/tweet_sentiment_extraction |
| name: MTEB TweetSentimentExtractionClassification |
| config: default |
| split: test |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| metrics: |
| - type: accuracy |
| value: 59.49066213921902 |
| - type: f1 |
| value: 59.85044985699777 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/twentynewsgroups-clustering |
| name: MTEB TwentyNewsgroupsClustering |
| config: default |
| split: test |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| metrics: |
| - type: v_measure |
| value: 39.44109250212289 |
| - type: v_measures |
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| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twittersemeval2015-pairclassification |
| name: MTEB TwitterSemEval2015 |
| config: default |
| split: test |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 84.25821064552662 |
| - type: cos_sim_ap |
| value: 67.96785265119063 |
| - type: cos_sim_f1 |
| value: 65.0070788107598 |
| - type: cos_sim_precision |
| value: 58.792146820315835 |
| - type: cos_sim_recall |
| value: 72.69129287598945 |
| - type: dot_accuracy |
| value: 81.47463789712106 |
| - type: dot_ap |
| value: 58.234902049577684 |
| - type: dot_f1 |
| value: 56.73442037078401 |
| - type: dot_precision |
| value: 49.18667699457785 |
| - type: dot_recall |
| value: 67.01846965699208 |
| - type: euclidean_accuracy |
| value: 84.30589497526375 |
| - type: euclidean_ap |
| value: 68.07824251821404 |
| - type: euclidean_f1 |
| value: 65.09073543457498 |
| - type: euclidean_precision |
| value: 59.44177932839075 |
| - type: euclidean_recall |
| value: 71.92612137203166 |
| - type: manhattan_accuracy |
| value: 84.24032902187518 |
| - type: manhattan_ap |
| value: 67.76838044141897 |
| - type: manhattan_f1 |
| value: 64.75698520779525 |
| - type: manhattan_precision |
| value: 58.333333333333336 |
| - type: manhattan_recall |
| value: 72.77044854881267 |
| - type: max_accuracy |
| value: 84.30589497526375 |
| - type: max_ap |
| value: 68.07824251821404 |
| - type: max_f1 |
| value: 65.09073543457498 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twitterurlcorpus-pairclassification |
| name: MTEB TwitterURLCorpus |
| config: default |
| split: test |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
| metrics: |
| - type: cos_sim_accuracy |
| value: 88.2951061435169 |
| - type: cos_sim_ap |
| value: 84.74905878045149 |
| - type: cos_sim_f1 |
| value: 77.01659871869538 |
| - type: cos_sim_precision |
| value: 73.0392156862745 |
| - type: cos_sim_recall |
| value: 81.45210963966738 |
| - type: dot_accuracy |
| value: 86.37598478674273 |
| - type: dot_ap |
| value: 79.17253140971533 |
| - type: dot_f1 |
| value: 73.19411657889958 |
| - type: dot_precision |
| value: 69.27201484842236 |
| - type: dot_recall |
| value: 77.58700338774254 |
| - type: euclidean_accuracy |
| value: 88.29122521054062 |
| - type: euclidean_ap |
| value: 84.64901724668165 |
| - type: euclidean_f1 |
| value: 76.99685189252507 |
| - type: euclidean_precision |
| value: 73.39148639218422 |
| - type: euclidean_recall |
| value: 80.97474591931014 |
| - type: manhattan_accuracy |
| value: 88.29316567702877 |
| - type: manhattan_ap |
| value: 84.5869003947086 |
| - type: manhattan_f1 |
| value: 76.9094138543517 |
| - type: manhattan_precision |
| value: 74.03818751781134 |
| - type: manhattan_recall |
| value: 80.01231906375116 |
| - type: max_accuracy |
| value: 88.2951061435169 |
| - type: max_ap |
| value: 84.74905878045149 |
| - type: max_f1 |
| value: 77.01659871869538 |
| --- |
| # Bulbasaur |
|
|
| This is a distill of [gte-tiny](https://huggingface.co/TaylorAI/gte-tiny) trained using [qa-assistant](https://huggingface.co/datasets/Mihaiii/qa-assistant). |
|
|
| ## Intended purpose |
|
|
| <span style="color:blue">This model is designed for use in semantic-autocomplete ([click here for demo](https://mihaiii.github.io/semantic-autocomplete/)).</span> |
|
|
| ## Usage (Sentence-Transformers) (same as [gte-tiny](https://huggingface.co/TaylorAI/gte-tiny)) |
|
|
| Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed: |
|
|
| ``` |
| pip install -U sentence-transformers |
| ``` |
|
|
| Then you can use the model like this: |
|
|
| ```python |
| from sentence_transformers import SentenceTransformer |
| sentences = ["This is an example sentence", "Each sentence is converted"] |
| |
| model = SentenceTransformer('Mihaiii/Bulbasaur') |
| embeddings = model.encode(sentences) |
| print(embeddings) |
| ``` |
|
|
|
|
|
|
| ## Usage (HuggingFace Transformers) (same as [gte-tiny](https://huggingface.co/TaylorAI/gte-tiny)) |
| Without [sentence-transformers](https://www.SBERT.net), you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings. |
|
|
| ```python |
| from transformers import AutoTokenizer, AutoModel |
| import torch |
| |
| |
| #Mean Pooling - Take attention mask into account for correct averaging |
| def mean_pooling(model_output, attention_mask): |
| token_embeddings = model_output[0] #First element of model_output contains all token embeddings |
| input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float() |
| return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9) |
| |
| |
| # Sentences we want sentence embeddings for |
| sentences = ['This is an example sentence', 'Each sentence is converted'] |
| |
| # Load model from HuggingFace Hub |
| tokenizer = AutoTokenizer.from_pretrained('Mihaiii/Bulbasaur') |
| model = AutoModel.from_pretrained('Mihaiii/Bulbasaur') |
| |
| # Tokenize sentences |
| encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt') |
| |
| # Compute token embeddings |
| with torch.no_grad(): |
| model_output = model(**encoded_input) |
| |
| # Perform pooling. In this case, mean pooling. |
| sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask']) |
| |
| print("Sentence embeddings:") |
| print(sentence_embeddings) |
| ``` |
|
|
| ### Limitation (same as [gte-small](https://huggingface.co/thenlper/gte-small)) |
| This model exclusively caters to English texts, and any lengthy texts will be truncated to a maximum of 512 tokens. |
