| --- |
| base_model: TaylorAI/gte-tiny |
| 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: Ivysaur |
| results: |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_counterfactual |
| name: MTEB AmazonCounterfactualClassification (en) |
| config: en |
| split: test |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
| metrics: |
| - type: accuracy |
| value: 72.1044776119403 |
| - type: ap |
| value: 35.09105788324913 |
| - type: f1 |
| value: 66.26967715703572 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_polarity |
| name: MTEB AmazonPolarityClassification |
| config: default |
| split: test |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
| metrics: |
| - type: accuracy |
| value: 86.686075 |
| - type: ap |
| value: 81.92716581685914 |
| - type: f1 |
| value: 86.65902299160209 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (en) |
| config: en |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 42.698 |
| - type: f1 |
| value: 42.287785312461885 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/arguana |
| name: MTEB ArguAna |
| config: default |
| split: test |
| revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
| metrics: |
| - type: map_at_1 |
| value: 30.441000000000003 |
| - type: map_at_10 |
| value: 46.951 |
| - type: map_at_100 |
| value: 47.788000000000004 |
| - type: map_at_1000 |
| value: 47.794 |
| - type: map_at_20 |
| value: 47.621 |
| - type: map_at_3 |
| value: 42.295 |
| - type: map_at_5 |
| value: 45.126 |
| - type: mrr_at_1 |
| value: 31.65 |
| - type: mrr_at_10 |
| value: 47.394999999999996 |
| - type: mrr_at_100 |
| value: 48.238 |
| - type: mrr_at_1000 |
| value: 48.245 |
| - type: mrr_at_20 |
| value: 48.069 |
| - type: mrr_at_3 |
| value: 42.852000000000004 |
| - type: mrr_at_5 |
| value: 45.58 |
| - type: ndcg_at_1 |
| value: 30.441000000000003 |
| - type: ndcg_at_10 |
| value: 55.783 |
| - type: ndcg_at_100 |
| value: 59.227 |
| - type: ndcg_at_1000 |
| value: 59.376 |
| - type: ndcg_at_20 |
| value: 58.18 |
| - type: ndcg_at_3 |
| value: 46.291 |
| - type: ndcg_at_5 |
| value: 51.405 |
| - type: precision_at_1 |
| value: 30.441000000000003 |
| - type: precision_at_10 |
| value: 8.378 |
| - type: precision_at_100 |
| value: 0.985 |
| - type: precision_at_1000 |
| value: 0.1 |
| - type: precision_at_20 |
| value: 4.659 |
| - type: precision_at_3 |
| value: 19.298000000000002 |
| - type: precision_at_5 |
| value: 14.068 |
| - type: recall_at_1 |
| value: 30.441000000000003 |
| - type: recall_at_10 |
| value: 83.784 |
| - type: recall_at_100 |
| value: 98.506 |
| - type: recall_at_1000 |
| value: 99.644 |
| - type: recall_at_20 |
| value: 93.172 |
| - type: recall_at_3 |
| value: 57.894999999999996 |
| - type: recall_at_5 |
| value: 70.341 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-p2p |
| name: MTEB ArxivClusteringP2P |
| config: default |
| split: test |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| metrics: |
| - type: v_measure |
| value: 46.39249132731755 |
| - 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: 35.410038545643225 |
| - 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: 59.69637278242267 |
| - type: mrr |
| value: 74.02948159873367 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/biosses-sts |
| name: MTEB BIOSSES |
| config: default |
| split: test |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
| metrics: |
| - type: cos_sim_pearson |
| value: 87.14461604689758 |
| - type: cos_sim_spearman |
| value: 87.31584497244751 |
| - type: euclidean_pearson |
| value: 84.78141750973201 |
| - type: euclidean_spearman |
| value: 87.05017626840346 |
| - type: manhattan_pearson |
| value: 84.35436632710646 |
| - type: manhattan_spearman |
| value: 86.49534434907336 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/banking77 |
| name: MTEB Banking77Classification |
| config: default |
| split: test |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| metrics: |
| - type: accuracy |
| value: 81.91558441558439 |
| - type: f1 |
| value: 81.88197959191479 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-p2p |
| name: MTEB BiorxivClusteringP2P |
| config: default |
| split: test |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| metrics: |
| - type: v_measure |
| value: 38.97808934568377 |
| - 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: 31.7412250739116 |
| - 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: 30.793 |
| - type: map_at_10 |
| value: 42.254000000000005 |
| - type: map_at_100 |
| value: 43.569 |
| - type: map_at_1000 |
| value: 43.714999999999996 |
| - type: map_at_20 |
| value: 42.994 |
| - type: map_at_3 |
| value: 39.007999999999996 |
| - type: map_at_5 |
| value: 40.488 |
| - type: mrr_at_1 |
| value: 38.34 |
| - type: mrr_at_10 |
| value: 48.274 |
| - type: mrr_at_100 |
| value: 48.946 |
| - type: mrr_at_1000 |
| value: 49.001 |
| - type: mrr_at_20 |
| value: 48.701 |
| - type: mrr_at_3 |
| value: 45.756 |
| - type: mrr_at_5 |
| value: 47.036 |
| - type: ndcg_at_1 |
| value: 38.34 |
| - type: ndcg_at_10 |
| value: 48.622 |
| - type: ndcg_at_100 |
| value: 53.288999999999994 |
| - type: ndcg_at_1000 |
| value: 55.614 |
| - type: ndcg_at_20 |
| value: 50.495000000000005 |
| - type: ndcg_at_3 |
| value: 43.852999999999994 |
| - type: ndcg_at_5 |
| value: 45.442 |
| - type: precision_at_1 |
| value: 38.34 |
| - type: precision_at_10 |
| value: 9.413 |
| - type: precision_at_100 |
| value: 1.4749999999999999 |
| - type: precision_at_1000 |
| value: 0.19499999999999998 |
| - type: precision_at_20 |
| value: 5.494000000000001 |
| - type: precision_at_3 |
| value: 20.935000000000002 |
| - type: precision_at_5 |
| value: 14.735000000000001 |
| - type: recall_at_1 |
| value: 30.793 |
| - type: recall_at_10 |
| value: 60.455000000000005 |
| - type: recall_at_100 |
| value: 80.061 |
| - type: recall_at_1000 |
| value: 95.322 |
| - type: recall_at_20 |
| value: 67.27 |
| - type: recall_at_3 |
| value: 46.296 |
| - type: recall_at_5 |
| value: 51.139 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-english |
| name: MTEB CQADupstackEnglishRetrieval |
| config: default |
| split: test |
| revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
| metrics: |
| - type: map_at_1 |
| value: 27.93 |
| - type: map_at_10 |
| value: 36.085 |
| - type: map_at_100 |
| value: 37.192 |
| - type: map_at_1000 |
| value: 37.324 |
| - type: map_at_20 |
| value: 36.614999999999995 |
| - type: map_at_3 |
| value: 33.452 |
| - type: map_at_5 |
| value: 35.088 |
| - type: mrr_at_1 |
| value: 34.777 |
| - type: mrr_at_10 |
| value: 41.865 |
| - type: mrr_at_100 |
| value: 42.518 |
| - type: mrr_at_1000 |
| value: 42.571 |
| - type: mrr_at_20 |
| value: 42.219 |
| - type: mrr_at_3 |
| value: 39.628 |
| - type: mrr_at_5 |
| value: 41.038999999999994 |
| - type: ndcg_at_1 |
| value: 34.777 |
| - type: ndcg_at_10 |
| value: 41.095 |
| - type: ndcg_at_100 |
| value: 45.286 |
| - type: ndcg_at_1000 |
| value: 47.656 |
| - type: ndcg_at_20 |
| value: 42.472 |
| - type: ndcg_at_3 |
| value: 37.349 |
| - type: ndcg_at_5 |
| value: 39.318 |
| - type: precision_at_1 |
| value: 34.777 |
| - type: precision_at_10 |
| value: 7.617999999999999 |
| - type: precision_at_100 |
| value: 1.242 |
| - type: precision_at_1000 |
| value: 0.173 |
| - type: precision_at_20 |
| value: 4.481 |
| - type: precision_at_3 |
| value: 17.771 |
| - type: precision_at_5 |
| value: 12.687999999999999 |
| - type: recall_at_1 |
| value: 27.93 |
| - type: recall_at_10 |
| value: 49.464000000000006 |
| - type: recall_at_100 |
| value: 67.64099999999999 |
| - type: recall_at_1000 |
| value: 83.066 |
| - type: recall_at_20 |
| value: 54.452999999999996 |
| - type: recall_at_3 |
| value: 38.157000000000004 |
| - type: recall_at_5 |
| value: 43.829 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-gaming |
| name: MTEB CQADupstackGamingRetrieval |
| config: default |
| split: test |
| revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
| metrics: |
| - type: map_at_1 |
| value: 37.332 |
| - type: map_at_10 |
| value: 49.146 |
| - type: map_at_100 |
| value: 50.222 |
| - type: map_at_1000 |
| value: 50.281 |
| - type: map_at_20 |
| value: 49.802 |
| - type: map_at_3 |
| value: 46.264 |
| - type: map_at_5 |
| value: 47.912 |
| - type: mrr_at_1 |
| value: 43.009 |
| - type: mrr_at_10 |
| value: 52.586999999999996 |
| - type: mrr_at_100 |
| value: 53.323 |
| - type: mrr_at_1000 |
| value: 53.352999999999994 |
| - type: mrr_at_20 |
| value: 53.04299999999999 |
| - type: mrr_at_3 |
| value: 50.261 |
| - type: mrr_at_5 |
| value: 51.615 |
| - type: ndcg_at_1 |
| value: 43.009 |
| - type: ndcg_at_10 |
| value: 54.652 |
| - type: ndcg_at_100 |
| value: 58.918000000000006 |
| - type: ndcg_at_1000 |
| value: 60.172000000000004 |
| - type: ndcg_at_20 |
| value: 56.554 |
| - type: ndcg_at_3 |
| value: 49.757 |
| - type: ndcg_at_5 |
| value: 52.169 |
| - type: precision_at_1 |
| value: 43.009 |
| - type: precision_at_10 |
| value: 8.715 |
| - type: precision_at_100 |
| value: 1.1780000000000002 |
| - type: precision_at_1000 |
| value: 0.133 |
| - type: precision_at_20 |
| value: 4.931 |
| - type: precision_at_3 |
| value: 22.153 |
| - type: precision_at_5 |
| value: 15.146999999999998 |
| - type: recall_at_1 |
| value: 37.332 |
| - type: recall_at_10 |
| value: 67.55600000000001 |
| - type: recall_at_100 |
| value: 85.885 |
| - type: recall_at_1000 |
| value: 94.87400000000001 |
| - type: recall_at_20 |
| value: 74.568 |
| - type: recall_at_3 |
| value: 54.419 |
| - type: recall_at_5 |
| value: 60.288 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-gis |
| name: MTEB CQADupstackGisRetrieval |
| config: default |
| split: test |
| revision: 5003b3064772da1887988e05400cf3806fe491f2 |
| metrics: |
| - type: map_at_1 |
| value: 24.09 |
| - type: map_at_10 |
| value: 32.608 |
| - type: map_at_100 |
| value: 33.571 |
| - type: map_at_1000 |
| value: 33.668 |
| - type: map_at_20 |
| value: 33.181 |
| - type: map_at_3 |
| value: 30.091 |
| - type: map_at_5 |
| value: 31.518 |
| - type: mrr_at_1 |
| value: 25.763 |
| - type: mrr_at_10 |
| value: 34.25 |
| - type: mrr_at_100 |
| value: 35.134 |
| - type: mrr_at_1000 |
| value: 35.207 |
| - type: mrr_at_20 |
| value: 34.78 |
| - type: mrr_at_3 |
| value: 31.807999999999996 |
| - type: mrr_at_5 |
| value: 33.198 |
| - type: ndcg_at_1 |
| value: 25.763 |
| - type: ndcg_at_10 |
| value: 37.305 |
| - type: ndcg_at_100 |
| value: 42.114000000000004 |
| - type: ndcg_at_1000 |
| value: 44.467 |
| - type: ndcg_at_20 |
| value: 39.272 |
| - type: ndcg_at_3 |
| value: 32.405 |
| - type: ndcg_at_5 |
| value: 34.775 |
| - type: precision_at_1 |
| value: 25.763 |
| - type: precision_at_10 |
| value: 5.729 |
| - type: precision_at_100 |
| value: 0.853 |
| - type: precision_at_1000 |
| value: 0.109 |
| - type: precision_at_20 |
| value: 3.3329999999999997 |
| - type: precision_at_3 |
| value: 13.71 |
| - type: precision_at_5 |
| value: 9.65 |
| - type: recall_at_1 |
| value: 24.09 |
| - type: recall_at_10 |
| value: 50.161 |
| - type: recall_at_100 |
| value: 72.419 |
| - type: recall_at_1000 |
| value: 89.983 |
| - type: recall_at_20 |
| value: 57.53 |
| - type: recall_at_3 |
| value: 36.961 |
| - type: recall_at_5 |
| value: 42.568 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-mathematica |
| name: MTEB CQADupstackMathematicaRetrieval |
| config: default |
| split: test |
| revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
| metrics: |
| - type: map_at_1 |
| value: 16.333000000000002 |
| - type: map_at_10 |
| value: 23.352999999999998 |
| - type: map_at_100 |
| value: 24.618000000000002 |
| - type: map_at_1000 |
| value: 24.743000000000002 |
| - type: map_at_20 |
| value: 24.117 |
| - type: map_at_3 |
| value: 21.013 |
| - type: map_at_5 |
| value: 22.259 |
| - type: mrr_at_1 |
| value: 20.398 |
| - type: mrr_at_10 |
| value: 28.28 |
| - type: mrr_at_100 |
| value: 29.307 |
| - type: mrr_at_1000 |
| value: 29.381 |
| - type: mrr_at_20 |
| value: 28.955 |
| - type: mrr_at_3 |
| value: 25.933 |
| - type: mrr_at_5 |
| value: 27.114 |
| - type: ndcg_at_1 |
| value: 20.398 |
| - type: ndcg_at_10 |
| value: 28.359 |
| - type: ndcg_at_100 |
| value: 34.178999999999995 |
| - type: ndcg_at_1000 |
| value: 37.112 |
| - type: ndcg_at_20 |
| value: 30.982 |
| - type: ndcg_at_3 |
| value: 24.104999999999997 |
| - type: ndcg_at_5 |
| value: 25.877 |
| - type: precision_at_1 |
| value: 20.398 |
| - type: precision_at_10 |
| value: 5.2490000000000006 |
| - type: precision_at_100 |
| value: 0.927 |
| - type: precision_at_1000 |
| value: 0.131 |
| - type: precision_at_20 |
| value: 3.3520000000000003 |
| - type: precision_at_3 |
| value: 11.733 |
| - type: precision_at_5 |
| value: 8.433 |
| - type: recall_at_1 |
| value: 16.333000000000002 |
| - type: recall_at_10 |
| value: 39.082 |
| - type: recall_at_100 |
| value: 64.269 |
| - type: recall_at_1000 |
| value: 85.103 |
| - type: recall_at_20 |
| value: 48.625 |
| - type: recall_at_3 |
| value: 26.740000000000002 |
| - type: recall_at_5 |
| value: 31.519000000000002 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-physics |
| name: MTEB CQADupstackPhysicsRetrieval |
| config: default |
| split: test |
| revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
| metrics: |
| - type: map_at_1 |
| value: 26.857999999999997 |
| - type: map_at_10 |
| value: 36.258 |
| - type: map_at_100 |
| value: 37.556 |
| - type: map_at_1000 |
| value: 37.669999999999995 |
| - type: map_at_20 |
| value: 36.937 |
| - type: map_at_3 |
| value: 33.306000000000004 |
| - type: map_at_5 |
| value: 35.004999999999995 |
| - type: mrr_at_1 |
| value: 33.397 |
| - type: mrr_at_10 |
| value: 42.089 |
| - type: mrr_at_100 |
| value: 42.864999999999995 |
| - type: mrr_at_1000 |
| value: 42.915 |
| - type: mrr_at_20 |
| value: 42.510999999999996 |
| - type: mrr_at_3 |
| value: 39.413 |
| - type: mrr_at_5 |
| value: 40.905 |
| - type: ndcg_at_1 |
| value: 33.397 |
| - type: ndcg_at_10 |
| value: 42.062 |
| - type: ndcg_at_100 |
| value: 47.620000000000005 |
| - type: ndcg_at_1000 |
| value: 49.816 |
| - type: ndcg_at_20 |
| value: 44.096999999999994 |
| - type: ndcg_at_3 |
| value: 37.165 |
| - type: ndcg_at_5 |
| value: 39.493 |
| - type: precision_at_1 |
| value: 33.397 |
| - type: precision_at_10 |
| value: 7.5649999999999995 |
| - type: precision_at_100 |
| value: 1.224 |
| - type: precision_at_1000 |
| value: 0.16 |
| - type: precision_at_20 |
| value: 4.495 |
| - type: precision_at_3 |
| value: 17.613 |
| - type: precision_at_5 |
| value: 12.589 |
| - type: recall_at_1 |
| value: 26.857999999999997 |
| - type: recall_at_10 |
| value: 53.900000000000006 |
| - type: recall_at_100 |
| value: 77.595 |
| - type: recall_at_1000 |
| value: 92.116 |
| - type: recall_at_20 |
| value: 60.962 |
| - type: recall_at_3 |
| value: 39.799 |
| - type: recall_at_5 |
| value: 45.961 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-programmers |
| name: MTEB CQADupstackProgrammersRetrieval |
| config: default |
| split: test |
| revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
| metrics: |
| - type: map_at_1 |
| value: 24.131 |
| - type: map_at_10 |
| value: 33.016 |
| - type: map_at_100 |
| value: 34.263 |
| - type: map_at_1000 |
| value: 34.39 |
| - type: map_at_20 |
| value: 33.703 |
| - type: map_at_3 |
| value: 30.055 |
| - type: map_at_5 |
| value: 31.651 |
| - type: mrr_at_1 |
| value: 30.593999999999998 |
| - type: mrr_at_10 |
| value: 38.786 |
| - type: mrr_at_100 |
| value: 39.674 |
| - type: mrr_at_1000 |
| value: 39.739000000000004 |
| - type: mrr_at_20 |
| value: 39.322 |
| - type: mrr_at_3 |
| value: 36.32 |
| - type: mrr_at_5 |
| value: 37.787 |
| - type: ndcg_at_1 |
| value: 30.593999999999998 |
| - type: ndcg_at_10 |
| value: 38.606 |
| - type: ndcg_at_100 |
| value: 44.116 |
| - type: ndcg_at_1000 |
| value: 46.772999999999996 |
| - type: ndcg_at_20 |
| value: 40.775 |
| - type: ndcg_at_3 |
| value: 33.854 |
| - type: ndcg_at_5 |
| value: 35.957 |
| - type: precision_at_1 |
| value: 30.593999999999998 |
| - type: precision_at_10 |
| value: 7.112 |
| - type: precision_at_100 |
| value: 1.154 |
| - type: precision_at_1000 |
| value: 0.155 |
| - type: precision_at_20 |
| value: 4.2410000000000005 |
| - type: precision_at_3 |
| value: 16.323999999999998 |
| - type: precision_at_5 |
| value: 11.644 |
| - type: recall_at_1 |
| value: 24.131 |
| - type: recall_at_10 |
| value: 49.767 |
| - type: recall_at_100 |
| value: 73.57000000000001 |
| - type: recall_at_1000 |
| value: 91.842 |
| - type: recall_at_20 |
| value: 57.498000000000005 |
| - type: recall_at_3 |
| value: 35.888 |
| - type: recall_at_5 |
| value: 41.801 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-stats |
| name: MTEB CQADupstackStatsRetrieval |
| config: default |
| split: test |
| revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
| metrics: |
| - type: map_at_1 |
| value: 23.075000000000003 |
| - type: map_at_10 |
| value: 29.584 |
| - type: map_at_100 |
| value: 30.4 |
| - type: map_at_1000 |
| value: 30.501 |
| - type: map_at_20 |
| value: 30.051 |
| - type: map_at_3 |
| value: 27.561000000000003 |
| - type: map_at_5 |
| value: 28.603 |
| - type: mrr_at_1 |
| value: 26.227 |
| - type: mrr_at_10 |
| value: 32.647 |
| - type: mrr_at_100 |
| value: 33.391999999999996 |
| - type: mrr_at_1000 |
| value: 33.469 |
| - type: mrr_at_20 |
| value: 33.053 |
| - type: mrr_at_3 |
| value: 30.776999999999997 |
| - type: mrr_at_5 |
| value: 31.828 |
| - type: ndcg_at_1 |
| value: 26.227 |
| - type: ndcg_at_10 |
| value: 33.582 |
| - type: ndcg_at_100 |
| value: 37.814 |
| - type: ndcg_at_1000 |
| value: 40.444 |
| - type: ndcg_at_20 |
| value: 35.163 |
| - type: ndcg_at_3 |
| value: 29.874000000000002 |
| - type: ndcg_at_5 |
| value: 31.53 |
| - type: precision_at_1 |
| value: 26.227 |
| - type: precision_at_10 |
| value: 5.244999999999999 |
| - type: precision_at_100 |
| value: 0.788 |
| - type: precision_at_1000 |
| value: 0.11100000000000002 |
| - type: precision_at_20 |
| value: 3.006 |
| - type: precision_at_3 |
| value: 12.73 |
| - type: precision_at_5 |
| value: 8.741999999999999 |
| - type: recall_at_1 |
| value: 23.075000000000003 |
| - type: recall_at_10 |
| value: 42.894 |
| - type: recall_at_100 |
| value: 62.721000000000004 |
| - type: recall_at_1000 |
| value: 81.858 |
| - type: recall_at_20 |
| value: 48.842 |
| - type: recall_at_3 |
| value: 32.783 |
| - type: recall_at_5 |
| value: 36.949 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-tex |
| name: MTEB CQADupstackTexRetrieval |
| config: default |
| split: test |
| revision: 46989137a86843e03a6195de44b09deda022eec7 |
| metrics: |
| - type: map_at_1 |
| value: 17.028 |
| - type: map_at_10 |
| value: 23.377 |
| - type: map_at_100 |
| value: 24.399 |
| - type: map_at_1000 |
| value: 24.524 |
| - type: map_at_20 |
| value: 23.863 |
| - type: map_at_3 |
| value: 21.274 |
| - type: map_at_5 |
| value: 22.431 |
| - type: mrr_at_1 |
| value: 20.578 |
| - type: mrr_at_10 |
| value: 27.009 |
| - type: mrr_at_100 |
| value: 27.889999999999997 |
| - type: mrr_at_1000 |
| value: 27.969 |
| - type: mrr_at_20 |
| value: 27.46 |
| - type: mrr_at_3 |
| value: 24.959999999999997 |
| - type: mrr_at_5 |
| value: 26.113999999999997 |
| - type: ndcg_at_1 |
| value: 20.578 |
| - type: ndcg_at_10 |
| value: 27.522999999999996 |
| - type: ndcg_at_100 |
| value: 32.601 |
| - type: ndcg_at_1000 |
| value: 35.636 |
| - type: ndcg_at_20 |
| value: 29.132 |
| - type: ndcg_at_3 |
| value: 23.771 |
| - type: ndcg_at_5 |
| value: 25.539 |
| - type: precision_at_1 |
| value: 20.578 |
| - type: precision_at_10 |
| value: 4.962 |
| - type: precision_at_100 |
| value: 0.8880000000000001 |
| - type: precision_at_1000 |
| value: 0.132 |
| - type: precision_at_20 |
| value: 2.959 |
| - type: precision_at_3 |
| value: 11.068999999999999 |
| - type: precision_at_5 |
| value: 8.052 |
| - type: recall_at_1 |
| value: 17.028 |
| - type: recall_at_10 |
| value: 36.266 |
| - type: recall_at_100 |
| value: 59.556 |
| - type: recall_at_1000 |
| value: 81.416 |
| - type: recall_at_20 |
| value: 42.303000000000004 |
| - type: recall_at_3 |
| value: 25.858999999999998 |
| - type: recall_at_5 |
| value: 30.422 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-unix |
| name: MTEB CQADupstackUnixRetrieval |
| config: default |
| split: test |
| revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
| metrics: |
| - type: map_at_1 |
| value: 25.863000000000003 |
| - type: map_at_10 |
| value: 33.586 |
| - type: map_at_100 |
| value: 34.682 |
| - type: map_at_1000 |
| value: 34.791 |
| - type: map_at_20 |
| value: 34.182 |
| - type: map_at_3 |
| value: 31.044 |
| - type: map_at_5 |
| value: 32.507000000000005 |
| - type: mrr_at_1 |
| value: 30.131000000000004 |
| - type: mrr_at_10 |
| value: 37.518 |
| - type: mrr_at_100 |
| value: 38.355 |
| - type: mrr_at_1000 |
| value: 38.425 |
| - type: mrr_at_20 |
| value: 37.961 |
| - type: mrr_at_3 |
| value: 35.059000000000005 |
| - type: mrr_at_5 |
| value: 36.528 |
| - type: ndcg_at_1 |
| value: 30.131000000000004 |
| - type: ndcg_at_10 |
| value: 38.387 |
| - type: ndcg_at_100 |
| value: 43.617 |
| - type: ndcg_at_1000 |
| value: 46.038000000000004 |
| - type: ndcg_at_20 |
| value: 40.261 |
| - type: ndcg_at_3 |
| value: 33.722 |
| - type: ndcg_at_5 |
| value: 36.013 |
| - type: precision_at_1 |
| value: 30.131000000000004 |
| - type: precision_at_10 |
| value: 6.297 |
| - type: precision_at_100 |
| value: 1.008 |
| - type: precision_at_1000 |
| value: 0.132 |
| - type: precision_at_20 |
| value: 3.689 |
| - type: precision_at_3 |
| value: 15.049999999999999 |
| - type: precision_at_5 |
| value: 10.634 |
| - type: recall_at_1 |
| value: 25.863000000000003 |
| - type: recall_at_10 |
| value: 49.101 |
| - type: recall_at_100 |
| value: 72.286 |
| - type: recall_at_1000 |
| value: 89.14 |
| - type: recall_at_20 |
| value: 55.742999999999995 |
| - type: recall_at_3 |
| value: 36.513 |
| - type: recall_at_5 |
| value: 42.204 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-webmasters |
| name: MTEB CQADupstackWebmastersRetrieval |
| config: default |
| split: test |
| revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
| metrics: |
| - type: map_at_1 |
| value: 24.747 |
| - type: map_at_10 |
| value: 32.067 |
| - type: map_at_100 |
| value: 33.739999999999995 |
| - type: map_at_1000 |
| value: 33.952 |
| - type: map_at_20 |
| value: 32.927 |
| - type: map_at_3 |
| value: 29.736 |
| - type: map_at_5 |
| value: 30.996000000000002 |
| - type: mrr_at_1 |
| value: 29.644 |
| - type: mrr_at_10 |
| value: 36.683 |
| - type: mrr_at_100 |
| value: 37.808 |
| - type: mrr_at_1000 |
| value: 37.858999999999995 |
| - type: mrr_at_20 |
| value: 37.326 |
| - type: mrr_at_3 |
| value: 34.42 |
| - type: mrr_at_5 |
| value: 35.626000000000005 |
| - type: ndcg_at_1 |
| value: 29.644 |
| - type: ndcg_at_10 |
| value: 36.989 |
| - type: ndcg_at_100 |
| value: 43.589 |
| - type: ndcg_at_1000 |
| value: 46.133 |
| - type: ndcg_at_20 |
| value: 39.403 |
| - type: ndcg_at_3 |
| value: 33.273 |
| - type: ndcg_at_5 |
| value: 34.853 |
| - type: precision_at_1 |
| value: 29.644 |
| - type: precision_at_10 |
| value: 6.8180000000000005 |
| - type: precision_at_100 |
| value: 1.4529999999999998 |
| - type: precision_at_1000 |
| value: 0.23500000000000001 |
| - type: precision_at_20 |
| value: 4.457 |
| - type: precision_at_3 |
| value: 15.152 |
| - type: precision_at_5 |
| value: 10.711 |
| - type: recall_at_1 |
| value: 24.747 |
| - type: recall_at_10 |
| value: 45.714 |
| - type: recall_at_100 |
| value: 75.212 |
| - type: recall_at_1000 |
| value: 90.884 |
| - type: recall_at_20 |
| value: 54.777 |
| - type: recall_at_3 |
| value: 34.821999999999996 |
| - type: recall_at_5 |
| value: 39.278999999999996 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/cqadupstack-wordpress |
| name: MTEB CQADupstackWordpressRetrieval |
| config: default |
| split: test |
| revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
| metrics: |
| - type: map_at_1 |
| value: 19.261 |
| - type: map_at_10 |
| value: 26.873 |
| - type: map_at_100 |
| value: 27.938000000000002 |
| - type: map_at_1000 |
| value: 28.060000000000002 |
| - type: map_at_20 |
| value: 27.456000000000003 |
| - type: map_at_3 |
| value: 24.834 |
| - type: map_at_5 |
| value: 25.793 |
| - type: mrr_at_1 |
| value: 20.887 |
| - type: mrr_at_10 |
| value: 28.634999999999998 |
| - type: mrr_at_100 |
| value: 29.609 |
| - type: mrr_at_1000 |
| value: 29.698999999999998 |
| - type: mrr_at_20 |
| value: 29.173 |
| - type: mrr_at_3 |
| value: 26.741 |
| - type: mrr_at_5 |
| value: 27.628000000000004 |
| - type: ndcg_at_1 |
| value: 20.887 |
| - type: ndcg_at_10 |
| value: 31.261 |
| - type: ndcg_at_100 |
| value: 36.471 |
| - type: ndcg_at_1000 |
| value: 39.245000000000005 |
| - type: ndcg_at_20 |
| value: 33.209 |
| - type: ndcg_at_3 |
| value: 27.195999999999998 |
| - type: ndcg_at_5 |
| value: 28.786 |
| - type: precision_at_1 |
| value: 20.887 |
| - type: precision_at_10 |
| value: 4.9910000000000005 |
| - type: precision_at_100 |
| value: 0.8210000000000001 |
| - type: precision_at_1000 |
| value: 0.116 |
| - type: precision_at_20 |
| value: 2.939 |
| - type: precision_at_3 |
| value: 11.892 |
| - type: precision_at_5 |
| value: 8.133 |
| - type: recall_at_1 |
| value: 19.261 |
| - type: recall_at_10 |
| value: 42.806 |
| - type: recall_at_100 |
| value: 66.715 |
| - type: recall_at_1000 |
| value: 86.921 |
| - type: recall_at_20 |
| value: 50.205999999999996 |
| - type: recall_at_3 |
| value: 31.790000000000003 |
| - type: recall_at_5 |
| value: 35.527 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/climate-fever |
| name: MTEB ClimateFEVER |
| config: default |
| split: test |
| revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
| metrics: |
| - type: map_at_1 |
| value: 9.009 |
| - type: map_at_10 |
| value: 14.629 |
| - type: map_at_100 |
| value: 16.092000000000002 |
| - type: map_at_1000 |
| value: 16.267 |
| - type: map_at_20 |
| value: 15.384999999999998 |
| - type: map_at_3 |
| value: 12.280000000000001 |
| - type: map_at_5 |
| value: 13.442000000000002 |
| - type: mrr_at_1 |
| value: 20.0 |
| - type: mrr_at_10 |
| value: 29.298000000000002 |
| - type: mrr_at_100 |
| value: 30.375999999999998 |
| - type: mrr_at_1000 |
| value: 30.436999999999998 |
| - type: mrr_at_20 |
| value: 29.956 |
| - type: mrr_at_3 |
| value: 26.362999999999996 |
| - type: mrr_at_5 |
| value: 28.021 |
| - type: ndcg_at_1 |
| value: 20.0 |
| - type: ndcg_at_10 |
| value: 21.234 |
| - type: ndcg_at_100 |
| value: 27.687 |
| - type: ndcg_at_1000 |
| value: 31.325999999999997 |
| - type: ndcg_at_20 |
| value: 23.631 |
| - type: ndcg_at_3 |
| value: 17.101 |
| - type: ndcg_at_5 |
| value: 18.501 |
| - type: precision_at_1 |
| value: 20.0 |
| - type: precision_at_10 |
| value: 6.651 |
| - type: precision_at_100 |
| value: 1.347 |
| - type: precision_at_1000 |
| value: 0.201 |
| - type: precision_at_20 |
| value: 4.316 |
| - type: precision_at_3 |
| value: 12.53 |
| - type: precision_at_5 |
| value: 9.707 |
| - type: recall_at_1 |
| value: 9.009 |
| - type: recall_at_10 |
| value: 25.824 |
| - type: recall_at_100 |
| value: 48.535000000000004 |
| - type: recall_at_1000 |
| value: 69.44399999999999 |
| - type: recall_at_20 |
| value: 32.78 |
| - type: recall_at_3 |
| value: 15.693999999999999 |
| - type: recall_at_5 |
| value: 19.59 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/dbpedia |
| name: MTEB DBPedia |
| config: default |
| split: test |
| revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
| metrics: |
| - type: map_at_1 |
| value: 7.454 |
| - type: map_at_10 |
| value: 15.675 |
| - type: map_at_100 |
| value: 21.335 |
| - type: map_at_1000 |
| value: 22.639 |
| - type: map_at_20 |
| value: 17.822 |
| - type: map_at_3 |
| value: 11.609 |
| - type: map_at_5 |
| value: 13.342 |
| - type: mrr_at_1 |
| value: 56.25 |
| - type: mrr_at_10 |
| value: 65.30799999999999 |
| - type: mrr_at_100 |
| value: 65.90599999999999 |
| - type: mrr_at_1000 |
| value: 65.92099999999999 |
| - type: mrr_at_20 |
| value: 65.74600000000001 |
| - type: mrr_at_3 |
| value: 63.333 |
| - type: mrr_at_5 |
| value: 64.521 |
| - type: ndcg_at_1 |
| value: 44.625 |
| - type: ndcg_at_10 |
| value: 33.881 |
| - type: ndcg_at_100 |
| value: 37.775999999999996 |
| - type: ndcg_at_1000 |
| value: 44.956 |
| - type: ndcg_at_20 |
| value: 33.451 |
| - type: ndcg_at_3 |
| value: 37.72 |
| - type: ndcg_at_5 |
| value: 35.811 |
| - type: precision_at_1 |
| value: 56.25 |
| - type: precision_at_10 |
| value: 27.175 |
| - type: precision_at_100 |
| value: 8.448 |
| - type: precision_at_1000 |
| value: 1.809 |
| - type: precision_at_20 |
| value: 20.262 |
| - type: precision_at_3 |
| value: 41.333 |
| - type: precision_at_5 |
| value: 35.199999999999996 |
| - type: recall_at_1 |
| value: 7.454 |
| - type: recall_at_10 |
| value: 20.355999999999998 |
| - type: recall_at_100 |
| value: 43.168 |
| - type: recall_at_1000 |
| value: 66.559 |
| - type: recall_at_20 |
| value: 26.785999999999998 |
| - type: recall_at_3 |
| value: 13.052 |
| - type: recall_at_5 |
| value: 15.733 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/emotion |
| name: MTEB EmotionClassification |
| config: default |
| split: test |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
| metrics: |
| - type: accuracy |
| value: 45.44499999999999 |
| - type: f1 |
| value: 40.581418056070994 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/fever |
| name: MTEB FEVER |
| config: default |
| split: test |
| revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
| metrics: |
| - type: map_at_1 |
| value: 46.339000000000006 |
| - type: map_at_10 |
| value: 57.87 |
| - type: map_at_100 |
| value: 58.447 |
| - type: map_at_1000 |
| value: 58.474000000000004 |
| - type: map_at_20 |
| value: 58.241 |
| - type: map_at_3 |
| value: 55.336 |
| - type: map_at_5 |
| value: 56.879000000000005 |
| - type: mrr_at_1 |
| value: 49.91 |
| - type: mrr_at_10 |
| value: 61.55199999999999 |
| - type: mrr_at_100 |
| value: 62.07 |
| - type: mrr_at_1000 |
| value: 62.086 |
| - type: mrr_at_20 |
| value: 61.899 |
| - type: mrr_at_3 |
| value: 59.108000000000004 |
| - type: mrr_at_5 |
| value: 60.622 |
| - type: ndcg_at_1 |
| value: 49.91 |
| - type: ndcg_at_10 |
| value: 63.970000000000006 |
| - type: ndcg_at_100 |
| value: 66.625 |
| - type: ndcg_at_1000 |
| value: 67.221 |
| - type: ndcg_at_20 |
| value: 65.261 |
| - type: ndcg_at_3 |
| value: 59.059 |
| - type: ndcg_at_5 |
| value: 61.68900000000001 |
| - type: precision_at_1 |
| value: 49.91 |
| - type: precision_at_10 |
| value: 8.699 |
| - type: precision_at_100 |
| value: 1.015 |
| - type: precision_at_1000 |
| value: 0.108 |
| - type: precision_at_20 |
| value: 4.6370000000000005 |
| - type: precision_at_3 |
| value: 23.942 |
| - type: precision_at_5 |
| value: 15.815000000000001 |
| - type: recall_at_1 |
| value: 46.339000000000006 |
| - type: recall_at_10 |
| value: 79.28 |
| - type: recall_at_100 |
| value: 91.148 |
| - type: recall_at_1000 |
| value: 95.438 |
| - type: recall_at_20 |
| value: 84.187 |
| - type: recall_at_3 |
| value: 66.019 |
| - type: recall_at_5 |
| value: 72.394 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/fiqa |
| name: MTEB FiQA2018 |
| config: default |
| split: test |
| revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
| metrics: |
| - type: map_at_1 |
| value: 14.504 |
| - type: map_at_10 |
| value: 24.099999999999998 |
| - type: map_at_100 |
| value: 25.820999999999998 |
| - type: map_at_1000 |
| value: 25.997999999999998 |
| - type: map_at_20 |
| value: 25.003999999999998 |
| - type: map_at_3 |
| value: 21.218999999999998 |
| - type: map_at_5 |
| value: 22.744 |
| - type: mrr_at_1 |
| value: 29.475 |
| - type: mrr_at_10 |
| value: 38.072 |
| - type: mrr_at_100 |
| value: 39.196999999999996 |
| - type: mrr_at_1000 |
| value: 39.249 |
| - type: mrr_at_20 |
| value: 38.757999999999996 |
| - type: mrr_at_3 |
| value: 36.214 |
| - type: mrr_at_5 |
| value: 37.094 |
| - type: ndcg_at_1 |
| value: 29.475 |
| - type: ndcg_at_10 |
| value: 30.708999999999996 |
| - type: ndcg_at_100 |
| value: 37.744 |
| - type: ndcg_at_1000 |
| value: 41.215 |
| - type: ndcg_at_20 |
| value: 33.336 |
| - type: ndcg_at_3 |
| value: 28.243000000000002 |
| - type: ndcg_at_5 |
| value: 28.62 |
| - type: precision_at_1 |
| value: 29.475 |
| - type: precision_at_10 |
| value: 8.596 |
| - type: precision_at_100 |
| value: 1.562 |
| - type: precision_at_1000 |
| value: 0.219 |
| - type: precision_at_20 |
| value: 5.394 |
| - type: precision_at_3 |
| value: 19.084 |
| - type: precision_at_5 |
| value: 13.672999999999998 |
| - type: recall_at_1 |
| value: 14.504 |
| - type: recall_at_10 |
| value: 36.232 |
| - type: recall_at_100 |
| value: 62.712 |
| - type: recall_at_1000 |
| value: 83.864 |
| - type: recall_at_20 |
| value: 44.357 |
| - type: recall_at_3 |
| value: 26.029000000000003 |
| - type: recall_at_5 |
| value: 29.909000000000002 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/hotpotqa |
| name: MTEB HotpotQA |
| config: default |
| split: test |
| revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
| metrics: |
| - type: map_at_1 |
| value: 31.634 |
| - type: map_at_10 |
| value: 45.007000000000005 |
| - type: map_at_100 |
| value: 45.963 |
| - type: map_at_1000 |
| value: 46.052 |
| - type: map_at_20 |
| value: 45.550000000000004 |
| - type: map_at_3 |
| value: 42.092 |
| - type: map_at_5 |
| value: 43.832 |
| - type: mrr_at_1 |
| value: 63.268 |
| - type: mrr_at_10 |
| value: 70.691 |
| - type: mrr_at_100 |
| value: 71.063 |
| - type: mrr_at_1000 |
| value: 71.082 |
| - type: mrr_at_20 |
| value: 70.917 |
| - type: mrr_at_3 |
| value: 69.176 |
| - type: mrr_at_5 |
| value: 70.132 |
| - type: ndcg_at_1 |
| value: 63.268 |
| - type: ndcg_at_10 |
| value: 54.205000000000005 |
| - type: ndcg_at_100 |
| value: 57.847 |
| - type: ndcg_at_1000 |
| value: 59.64 |
| - type: ndcg_at_20 |
| value: 55.663 |
| - type: ndcg_at_3 |
| value: 49.613 |
| - type: ndcg_at_5 |
| value: 52.054 |
| - type: precision_at_1 |
| value: 63.268 |
| - type: precision_at_10 |
| value: 11.357000000000001 |
| - type: precision_at_100 |
| value: 1.423 |
| - type: precision_at_1000 |
| value: 0.166 |
| - type: precision_at_20 |
| value: 6.148 |
| - type: precision_at_3 |
| value: 31.041999999999998 |
| - type: precision_at_5 |
| value: 20.551 |
| - type: recall_at_1 |
| value: 31.634 |
| - type: recall_at_10 |
| value: 56.786 |
| - type: recall_at_100 |
| value: 71.128 |
| - type: recall_at_1000 |
| value: 82.97099999999999 |
| - type: recall_at_20 |
| value: 61.47899999999999 |
| - type: recall_at_3 |
| value: 46.563 |
| - type: recall_at_5 |
| value: 51.376999999999995 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/imdb |
| name: MTEB ImdbClassification |
| config: default |
| split: test |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
| metrics: |
| - type: accuracy |
| value: 80.7996 |
| - type: ap |
| value: 74.98592172204835 |
| - type: f1 |
| value: 80.77161545117626 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/msmarco |
| name: MTEB MSMARCO |
| config: default |
| split: dev |
| revision: c5a29a104738b98a9e76336939199e264163d4a0 |
| metrics: |
| - type: map_at_1 |
| value: 16.637 |
| - type: map_at_10 |
| value: 27.331 |
| - type: map_at_100 |
| value: 28.518 |
| - type: map_at_1000 |
| value: 28.583 |
| - type: map_at_20 |
| value: 28.031 |
| - type: map_at_3 |
| value: 23.715 |
| - type: map_at_5 |
| value: 25.758 |
| - type: mrr_at_1 |
| value: 17.077 |
| - type: mrr_at_10 |
| value: 27.807 |
| - type: mrr_at_100 |
| value: 28.965999999999998 |
| - type: mrr_at_1000 |
| value: 29.025000000000002 |
| - type: mrr_at_20 |
| value: 28.499999999999996 |
| - type: mrr_at_3 |
| value: 24.234 |
| - type: mrr_at_5 |
| value: 26.257 |
| - type: ndcg_at_1 |
| value: 17.077 |
| - type: ndcg_at_10 |
| value: 33.607 |
| - type: ndcg_at_100 |
| value: 39.593 |
| - type: ndcg_at_1000 |
| value: 41.317 |
| - type: ndcg_at_20 |
| value: 36.118 |
| - type: ndcg_at_3 |
| value: 26.204 |
| - type: ndcg_at_5 |
| value: 29.862 |
| - type: precision_at_1 |
| value: 17.077 |
| - type: precision_at_10 |
| value: 5.54 |
| - type: precision_at_100 |
| value: 0.857 |
| - type: precision_at_1000 |
| value: 0.101 |
| - type: precision_at_20 |
| value: 3.2870000000000004 |
| - type: precision_at_3 |
| value: 11.361 |
| - type: precision_at_5 |
| value: 8.673 |
| - type: recall_at_1 |
| value: 16.637 |
| - type: recall_at_10 |
| value: 53.077 |
| - type: recall_at_100 |
| value: 81.306 |
| - type: recall_at_1000 |
| value: 94.72699999999999 |
| - type: recall_at_20 |
| value: 62.855000000000004 |
| - type: recall_at_3 |
| value: 32.897999999999996 |
| - type: recall_at_5 |
| value: 41.697 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_domain |
| name: MTEB MTOPDomainClassification (en) |
| config: en |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 92.12494300045599 |
| - type: f1 |
| value: 91.6522604757574 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_intent |
| name: MTEB MTOPIntentClassification (en) |
| config: en |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
| - type: accuracy |
| value: 71.86046511627907 |
| - type: f1 |
| value: 53.8926541769729 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (en) |
| config: en |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
| - type: accuracy |
| value: 70.34633490248824 |
| - type: f1 |
| value: 67.94196699295675 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (en) |
| config: en |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 74.88903833221251 |
| - type: f1 |
| value: 74.54991713265153 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-p2p |
| name: MTEB MedrxivClusteringP2P |
| config: default |
| split: test |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
| metrics: |
| - type: v_measure |
| value: 33.129785771060526 |
| - 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: 30.29367725266166 |
| - 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: 5.542 |
| - type: map_at_10 |
| value: 11.734 |
| - type: map_at_100 |
| value: 14.812 |
| - type: map_at_1000 |
| value: 16.184 |
| - type: map_at_20 |
| value: 13.045000000000002 |
| - type: map_at_3 |
| value: 8.859 |
| - type: map_at_5 |
| value: 10.162 |
| - type: mrr_at_1 |
| value: 43.963 |
| - type: mrr_at_10 |
| value: 51.914 |
| - type: mrr_at_100 |
| value: 52.422000000000004 |
| - type: mrr_at_1000 |
| value: 52.479 |
| - type: mrr_at_20 |
| value: 52.215 |
| - type: mrr_at_3 |
| value: 49.897000000000006 |
| - type: mrr_at_5 |
| value: 50.965 |
| - type: ndcg_at_1 |
| value: 42.105 |
| - type: ndcg_at_10 |
| value: 32.035000000000004 |
| - type: ndcg_at_100 |
| value: 29.487999999999996 |
| - type: ndcg_at_1000 |
| value: 38.316 |
| - type: ndcg_at_20 |
| value: 30.255 |
| - type: ndcg_at_3 |
| value: 37.098 |
| - type: ndcg_at_5 |
| value: 34.98 |
| - type: precision_at_1 |
| value: 43.344 |
| - type: precision_at_10 |
| value: 23.313 |
| - type: precision_at_100 |
| value: 7.591 |
| - type: precision_at_1000 |
| value: 2.023 |
| - type: precision_at_20 |
| value: 17.755000000000003 |
| - type: precision_at_3 |
| value: 33.745999999999995 |
| - type: precision_at_5 |
| value: 29.474 |
| - type: recall_at_1 |
| value: 5.542 |
| - type: recall_at_10 |
| value: 15.61 |
| - type: recall_at_100 |
| value: 29.413 |
| - type: recall_at_1000 |
| value: 61.926 |
| - type: recall_at_20 |
| value: 19.517 |
| - type: recall_at_3 |
| value: 9.669 |
| - type: recall_at_5 |
| value: 11.772 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/nq |
| name: MTEB NQ |
| config: default |
| split: test |
| revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
| metrics: |
| - type: map_at_1 |
| value: 21.590999999999998 |
| - type: map_at_10 |
| value: 35.088 |
| - type: map_at_100 |
| value: 36.386 |
| - type: map_at_1000 |
| value: 36.439 |
| - type: map_at_20 |
| value: 35.93 |
| - type: map_at_3 |
| value: 30.985000000000003 |
| - type: map_at_5 |
| value: 33.322 |
| - type: mrr_at_1 |
| value: 24.189 |
| - type: mrr_at_10 |
| value: 37.395 |
| - type: mrr_at_100 |
| value: 38.449 |
| - type: mrr_at_1000 |
| value: 38.486 |
| - type: mrr_at_20 |
| value: 38.092999999999996 |
| - type: mrr_at_3 |
| value: 33.686 |
| - type: mrr_at_5 |
| value: 35.861 |
| - type: ndcg_at_1 |
| value: 24.189 |
| - type: ndcg_at_10 |
| value: 42.471 |
| - type: ndcg_at_100 |
| value: 48.150999999999996 |
| - type: ndcg_at_1000 |
| value: 49.342000000000006 |
| - type: ndcg_at_20 |
| value: 45.245000000000005 |
| - type: ndcg_at_3 |
| value: 34.483000000000004 |
| - type: ndcg_at_5 |
| value: 38.505 |
| - type: precision_at_1 |
| value: 24.189 |
| - type: precision_at_10 |
| value: 7.3870000000000005 |
| - type: precision_at_100 |
| value: 1.056 |
| - type: precision_at_1000 |
| value: 0.117 |
| - type: precision_at_20 |
| value: 4.35 |
| - type: precision_at_3 |
| value: 16.009999999999998 |
| - type: precision_at_5 |
| value: 11.883000000000001 |
| - type: recall_at_1 |
| value: 21.590999999999998 |
| - type: recall_at_10 |
| value: 62.79 |
| - type: recall_at_100 |
| value: 87.71 |
| - type: recall_at_1000 |
| value: 96.418 |
| - type: recall_at_20 |
| value: 73.042 |
| - type: recall_at_3 |
| value: 41.876999999999995 |
| - type: recall_at_5 |
| value: 51.205 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/quora |
| name: MTEB QuoraRetrieval |
| config: default |
| split: test |
| revision: e4e08e0b7dbe3c8700f0daef558ff32256715259 |
| metrics: |
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| value: 68.31099999999999 |
| - type: map_at_10 |
| value: 81.845 |
| - type: map_at_100 |
| value: 82.518 |
| - type: map_at_1000 |
| value: 82.541 |
| - type: map_at_20 |
| value: 82.292 |
| - type: map_at_3 |
| value: 78.827 |
| - type: map_at_5 |
| value: 80.715 |
| - type: mrr_at_1 |
| value: 78.62 |
| - type: mrr_at_10 |
| value: 85.42 |
| - type: mrr_at_100 |
| value: 85.54899999999999 |
| - type: mrr_at_1000 |
| value: 85.55 |
| - type: mrr_at_20 |
| value: 85.516 |
| - type: mrr_at_3 |
| value: 84.265 |
| - type: mrr_at_5 |
| value: 85.021 |
| - type: ndcg_at_1 |
| value: 78.63 |
| - type: ndcg_at_10 |
| value: 86.032 |
| - type: ndcg_at_100 |
| value: 87.50099999999999 |
| - type: ndcg_at_1000 |
| value: 87.67200000000001 |
| - type: ndcg_at_20 |
| value: 86.822 |
| - type: ndcg_at_3 |
| value: 82.813 |
| - type: ndcg_at_5 |
| value: 84.555 |
| - type: precision_at_1 |
| value: 78.63 |
| - type: precision_at_10 |
| value: 13.025999999999998 |
| - type: precision_at_100 |
| value: 1.504 |
| - type: precision_at_1000 |
| value: 0.156 |
| - type: precision_at_20 |
| value: 6.944999999999999 |
| - type: precision_at_3 |
| value: 36.013 |
| - type: precision_at_5 |
| value: 23.788 |
| - type: recall_at_1 |
| value: 68.31099999999999 |
| - type: recall_at_10 |
| value: 94.003 |
| - type: recall_at_100 |
| value: 99.11999999999999 |
| - type: recall_at_1000 |
| value: 99.923 |
| - type: recall_at_20 |
| value: 96.55799999999999 |
| - type: recall_at_3 |
| value: 84.836 |
| - type: recall_at_5 |
| value: 89.655 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering |
| name: MTEB RedditClustering |
| config: default |
| split: test |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| metrics: |
| - type: v_measure |
| value: 47.52530454226057 |
| - type: v_measures |
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| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering-p2p |
| name: MTEB RedditClusteringP2P |
| config: default |
| split: test |
| revision: 385e3cb46b4cfa89021f56c4380204149d0efe33 |
| metrics: |
| - type: v_measure |
| value: 56.028612066452 |
| - 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: 4.108 |
| - type: map_at_10 |
| value: 10.953 |
| - type: map_at_100 |
| value: 13.004 |
| - type: map_at_1000 |
| value: 13.303 |
| - type: map_at_20 |
| value: 12.004 |
| - type: map_at_3 |
| value: 7.754999999999999 |
| - type: map_at_5 |
| value: 9.19 |
| - type: mrr_at_1 |
| value: 20.200000000000003 |
| - type: mrr_at_10 |
| value: 31.069999999999997 |
| - type: mrr_at_100 |
| value: 32.222 |
| - type: mrr_at_1000 |
| value: 32.277 |
| - type: mrr_at_20 |
| value: 31.761 |
| - type: mrr_at_3 |
| value: 27.717000000000002 |
| - type: mrr_at_5 |
| value: 29.416999999999998 |
| - type: ndcg_at_1 |
| value: 20.200000000000003 |
| - type: ndcg_at_10 |
| value: 18.636 |
| - type: ndcg_at_100 |
| value: 26.442 |
| - type: ndcg_at_1000 |
| value: 31.828 |
| - type: ndcg_at_20 |
| value: 21.441 |
| - type: ndcg_at_3 |
| value: 17.323 |
| - type: ndcg_at_5 |
| value: 15.010000000000002 |
| - type: precision_at_1 |
| value: 20.200000000000003 |
| - type: precision_at_10 |
| value: 9.9 |
| - type: precision_at_100 |
| value: 2.106 |
| - type: precision_at_1000 |
| value: 0.33999999999999997 |
| - type: precision_at_20 |
| value: 6.575 |
| - type: precision_at_3 |
| value: 16.367 |
| - type: precision_at_5 |
| value: 13.200000000000001 |
| - type: recall_at_1 |
| value: 4.108 |
| - type: recall_at_10 |
| value: 20.052 |
| - type: recall_at_100 |
| value: 42.723 |
| - type: recall_at_1000 |
| value: 69.118 |
| - type: recall_at_20 |
| value: 26.662999999999997 |
| - type: recall_at_3 |
| value: 9.963 |
| - type: recall_at_5 |
| value: 13.377 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sickr-sts |
| name: MTEB SICK-R |
| config: default |
| split: test |
| revision: 20a6d6f312dd54037fe07a32d58e5e168867909d |
| metrics: |
| - type: cos_sim_pearson |
| value: 81.73133871784073 |
| - type: cos_sim_spearman |
| value: 75.63155962642634 |
| - type: euclidean_pearson |
| value: 78.84721858652286 |
| - type: euclidean_spearman |
| value: 75.52150847464515 |
| - type: manhattan_pearson |
| value: 78.65433033180727 |
| - type: manhattan_spearman |
| value: 75.30995832884881 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts12-sts |
| name: MTEB STS12 |
| config: default |
| split: test |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| metrics: |
| - type: cos_sim_pearson |
| value: 75.66063073145264 |
| - type: cos_sim_spearman |
| value: 68.58158236004101 |
| - type: euclidean_pearson |
| value: 72.54019756825143 |
| - type: euclidean_spearman |
| value: 69.05526621955067 |
| - type: manhattan_pearson |
| value: 72.69442494173272 |
| - type: manhattan_spearman |
| value: 69.24310689645435 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts13-sts |
| name: MTEB STS13 |
| config: default |
| split: test |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| metrics: |
| - type: cos_sim_pearson |
| value: 79.93061145846976 |
| - type: cos_sim_spearman |
| value: 80.54473705232682 |
| - type: euclidean_pearson |
| value: 80.25598213392439 |
| - type: euclidean_spearman |
| value: 80.57639468906437 |
| - type: manhattan_pearson |
| value: 80.04739474388745 |
| - type: manhattan_spearman |
| value: 80.35672978503159 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts14-sts |
| name: MTEB STS14 |
| config: default |
| split: test |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| metrics: |
| - type: cos_sim_pearson |
| value: 80.63106651366024 |
| - type: cos_sim_spearman |
| value: 77.628680514703 |
| - type: euclidean_pearson |
| value: 79.88625241187461 |
| - type: euclidean_spearman |
| value: 77.80535399731345 |
| - type: manhattan_pearson |
| value: 79.78810133011544 |
| - type: manhattan_spearman |
| value: 77.73028091841451 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts15-sts |
| name: MTEB STS15 |
| config: default |
| split: test |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.30832602658512 |
| - type: cos_sim_spearman |
| value: 86.15687211744392 |
| - type: euclidean_pearson |
| value: 85.94586990553746 |
| - type: euclidean_spearman |
| value: 86.48157226860724 |
| - type: manhattan_pearson |
| value: 85.88233798668581 |
| - type: manhattan_spearman |
| value: 86.42359889540302 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts16-sts |
| name: MTEB STS16 |
| config: default |
| split: test |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| metrics: |
| - type: cos_sim_pearson |
| value: 81.48207305822743 |
| - type: cos_sim_spearman |
| value: 82.8229306585227 |
| - type: euclidean_pearson |
| value: 82.3912454156615 |
| - type: euclidean_spearman |
| value: 83.09865476559257 |
| - type: manhattan_pearson |
| value: 82.30053520575876 |
| - type: manhattan_spearman |
| value: 83.00392320200139 |
| - 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: 87.83517082969622 |
| - type: cos_sim_spearman |
| value: 88.5704237984555 |
| - type: euclidean_pearson |
| value: 88.15443024833176 |
| - type: euclidean_spearman |
| value: 88.60313594495189 |
| - type: manhattan_pearson |
| value: 87.99012996276818 |
| - type: manhattan_spearman |
| value: 88.39306322978999 |
| - 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: 67.62856734038614 |
| - type: cos_sim_spearman |
| value: 67.38775280429276 |
| - type: euclidean_pearson |
| value: 68.09416503472238 |
| - type: euclidean_spearman |
| value: 67.45221088834498 |
| - type: manhattan_pearson |
| value: 68.31811474137709 |
| - type: manhattan_spearman |
| value: 67.75846817406287 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/stsbenchmark-sts |
| name: MTEB STSBenchmark |
| config: default |
| split: test |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
| metrics: |
| - type: cos_sim_pearson |
| value: 84.13302836216701 |
| - type: cos_sim_spearman |
| value: 84.24952159575491 |
| - type: euclidean_pearson |
| value: 84.65017899273384 |
| - type: euclidean_spearman |
| value: 84.43303793097236 |
| - type: manhattan_pearson |
| value: 84.55589549879238 |
| - type: manhattan_spearman |
| value: 84.42827667887977 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/scidocs-reranking |
| name: MTEB SciDocsRR |
| config: default |
| split: test |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| metrics: |
| - type: map |
| value: 80.03616790601166 |
| - type: mrr |
| value: 94.31135132115524 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/scifact |
| name: MTEB SciFact |
| config: default |
| split: test |
| revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
| metrics: |
| - type: map_at_1 |
| value: 51.678000000000004 |
| - type: map_at_10 |
| value: 62.011 |
| - type: map_at_100 |
| value: 62.443000000000005 |
| - type: map_at_1000 |
| value: 62.468999999999994 |
| - type: map_at_20 |
| value: 62.226000000000006 |
| - type: map_at_3 |
| value: 58.443999999999996 |
| - type: map_at_5 |
| value: 60.550000000000004 |
| - type: mrr_at_1 |
| value: 54.0 |
| - type: mrr_at_10 |
| value: 63.27199999999999 |
| - type: mrr_at_100 |
| value: 63.596 |
| - type: mrr_at_1000 |
| value: 63.619 |
| - type: mrr_at_20 |
| value: 63.416 |
| - type: mrr_at_3 |
| value: 60.5 |
| - type: mrr_at_5 |
| value: 62.283 |
| - type: ndcg_at_1 |
| value: 54.0 |
| - type: ndcg_at_10 |
| value: 67.315 |
| - type: ndcg_at_100 |
| value: 69.372 |
| - type: ndcg_at_1000 |
| value: 70.15400000000001 |
| - type: ndcg_at_20 |
| value: 67.943 |
| - type: ndcg_at_3 |
| value: 61.121 |
| - type: ndcg_at_5 |
| value: 64.399 |
| - type: precision_at_1 |
| value: 54.0 |
| - type: precision_at_10 |
| value: 9.232999999999999 |
| - type: precision_at_100 |
| value: 1.047 |
| - type: precision_at_1000 |
| value: 0.11100000000000002 |
| - type: precision_at_20 |
| value: 4.7829999999999995 |
| - type: precision_at_3 |
| value: 23.666999999999998 |
| - type: precision_at_5 |
| value: 16.2 |
| - type: recall_at_1 |
| value: 51.678000000000004 |
| - type: recall_at_10 |
| value: 82.389 |
| - type: recall_at_100 |
| value: 92.0 |
| - type: recall_at_1000 |
| value: 98.333 |
| - type: recall_at_20 |
| value: 84.63300000000001 |
| - type: recall_at_3 |
| value: 66.05 |
| - type: recall_at_5 |
| value: 74.006 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/sprintduplicatequestions-pairclassification |
| name: MTEB SprintDuplicateQuestions |
| config: default |
| split: test |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 99.82673267326733 |
| - type: cos_sim_ap |
| value: 95.11999931294784 |
| - type: cos_sim_f1 |
| value: 91.0941475826972 |
| - type: cos_sim_precision |
| value: 92.74611398963731 |
| - type: cos_sim_recall |
| value: 89.5 |
| - type: dot_accuracy |
| value: 99.73861386138614 |
| - type: dot_ap |
| value: 92.76208671816435 |
| - type: dot_f1 |
| value: 86.5055387713998 |
| - type: dot_precision |
| value: 87.11967545638946 |
| - type: dot_recall |
| value: 85.9 |
| - type: euclidean_accuracy |
| value: 99.82376237623762 |
| - type: euclidean_ap |
| value: 95.02471241011084 |
| - type: euclidean_f1 |
| value: 90.97363083164299 |
| - type: euclidean_precision |
| value: 92.28395061728395 |
| - type: euclidean_recall |
| value: 89.7 |
| - type: manhattan_accuracy |
| value: 99.82574257425742 |
| - type: manhattan_ap |
| value: 95.08424842231868 |
| - type: manhattan_f1 |
| value: 91.10212335692619 |
| - type: manhattan_precision |
| value: 92.12678936605317 |
| - type: manhattan_recall |
| value: 90.10000000000001 |
| - type: max_accuracy |
| value: 99.82673267326733 |
| - type: max_ap |
| value: 95.11999931294784 |
| - type: max_f1 |
| value: 91.10212335692619 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering |
| name: MTEB StackExchangeClustering |
| config: default |
| split: test |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
| metrics: |
| - type: v_measure |
| value: 53.870949746768424 |
| - type: v_measures |
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| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering-p2p |
| name: MTEB StackExchangeClusteringP2P |
| config: default |
| split: test |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
| metrics: |
| - type: v_measure |
| value: 33.56703823226784 |
| - 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: 49.82873266157383 |
| - type: mrr |
| value: 50.652096065699006 |
| - task: |
| type: Summarization |
| dataset: |
| type: mteb/summeval |
| name: MTEB SummEval |
| config: default |
| split: test |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
| metrics: |
| - type: cos_sim_pearson |
| value: 31.35739606124227 |
| - type: cos_sim_spearman |
| value: 31.26775311472305 |
| - type: dot_pearson |
| value: 29.421400993418278 |
| - type: dot_spearman |
| value: 30.180472594773534 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/trec-covid |
| name: MTEB TRECCOVID |
| config: default |
| split: test |
| revision: bb9466bac8153a0349341eb1b22e06409e78ef4e |
| metrics: |
| - type: map_at_1 |
| value: 0.184 |
| - type: map_at_10 |
| value: 1.398 |
| - type: map_at_100 |
| value: 7.2090000000000005 |
| - type: map_at_1000 |
| value: 18.414 |
| - type: map_at_20 |
| value: 2.414 |
| - type: map_at_3 |
| value: 0.509 |
| - type: map_at_5 |
| value: 0.767 |
| - type: mrr_at_1 |
| value: 72.0 |
| - type: mrr_at_10 |
| value: 80.467 |
| - type: mrr_at_100 |
| value: 80.735 |
| - type: mrr_at_1000 |
| value: 80.735 |
| - type: mrr_at_20 |
| value: 80.735 |
| - type: mrr_at_3 |
| value: 79.0 |
| - type: mrr_at_5 |
| value: 79.80000000000001 |
| - type: ndcg_at_1 |
| value: 68.0 |
| - type: ndcg_at_10 |
| value: 60.324 |
| - type: ndcg_at_100 |
| value: 43.866 |
| - type: ndcg_at_1000 |
| value: 41.932 |
| - type: ndcg_at_20 |
| value: 56.013999999999996 |
| - type: ndcg_at_3 |
| value: 66.458 |
| - type: ndcg_at_5 |
| value: 63.048 |
| - type: precision_at_1 |
| value: 72.0 |
| - type: precision_at_10 |
| value: 64.2 |
| - type: precision_at_100 |
| value: 44.56 |
| - type: precision_at_1000 |
| value: 18.736 |
| - type: precision_at_20 |
| value: 59.0 |
| - type: precision_at_3 |
| value: 72.0 |
| - type: precision_at_5 |
| value: 67.2 |
| - type: recall_at_1 |
| value: 0.184 |
| - type: recall_at_10 |
| value: 1.649 |
| - type: recall_at_100 |
| value: 10.659 |
| - type: recall_at_1000 |
| value: 40.424 |
| - type: recall_at_20 |
| value: 3.0349999999999997 |
| - type: recall_at_3 |
| value: 0.5519999999999999 |
| - type: recall_at_5 |
| value: 0.852 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/touche2020 |
| name: MTEB Touche2020 |
| config: default |
| split: test |
| revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
| metrics: |
| - type: map_at_1 |
| value: 1.252 |
| - type: map_at_10 |
| value: 8.029 |
| - type: map_at_100 |
| value: 13.504 |
| - type: map_at_1000 |
| value: 15.013000000000002 |
| - type: map_at_20 |
| value: 10.306 |
| - type: map_at_3 |
| value: 3.372 |
| - type: map_at_5 |
| value: 4.923 |
| - type: mrr_at_1 |
| value: 18.367 |
| - type: mrr_at_10 |
| value: 36.612 |
| - type: mrr_at_100 |
| value: 37.345 |
| - type: mrr_at_1000 |
| value: 37.345 |
| - type: mrr_at_20 |
| value: 36.955 |
| - type: mrr_at_3 |
| value: 32.993 |
| - type: mrr_at_5 |
| value: 33.912 |
| - type: ndcg_at_1 |
| value: 16.326999999999998 |
| - type: ndcg_at_10 |
| value: 21.124000000000002 |
| - type: ndcg_at_100 |
| value: 32.635 |
| - type: ndcg_at_1000 |
| value: 43.993 |
| - type: ndcg_at_20 |
| value: 22.429 |
| - type: ndcg_at_3 |
| value: 20.836 |
| - type: ndcg_at_5 |
| value: 20.437 |
| - type: precision_at_1 |
| value: 18.367 |
| - type: precision_at_10 |
| value: 21.02 |
| - type: precision_at_100 |
| value: 7.245 |
| - type: precision_at_1000 |
| value: 1.473 |
| - type: precision_at_20 |
| value: 15.714 |
| - type: precision_at_3 |
| value: 23.128999999999998 |
| - type: precision_at_5 |
| value: 22.448999999999998 |
| - type: recall_at_1 |
| value: 1.252 |
| - type: recall_at_10 |
| value: 15.312999999999999 |
| - type: recall_at_100 |
| value: 44.908 |
| - type: recall_at_1000 |
| value: 79.396 |
| - type: recall_at_20 |
| value: 22.647000000000002 |
| - type: recall_at_3 |
| value: 4.883 |
| - type: recall_at_5 |
| value: 7.917000000000001 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/toxic_conversations_50k |
| name: MTEB ToxicConversationsClassification |
| config: default |
| split: test |
| revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de |
| metrics: |
| - type: accuracy |
| value: 65.458984375 |
| - type: ap |
| value: 12.013147326225168 |
| - type: f1 |
| value: 50.30981581053394 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/tweet_sentiment_extraction |
| name: MTEB TweetSentimentExtractionClassification |
| config: default |
| split: test |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| metrics: |
| - type: accuracy |
| value: 58.658743633276735 |
| - type: f1 |
| value: 59.01001910848807 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/twentynewsgroups-clustering |
| name: MTEB TwentyNewsgroupsClustering |
| config: default |
| split: test |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| metrics: |
| - type: v_measure |
| value: 40.7719980016582 |
| - 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: 84.71717231924659 |
| - type: cos_sim_ap |
| value: 69.78325722226528 |
| - type: cos_sim_f1 |
| value: 66.23786691615015 |
| - type: cos_sim_precision |
| value: 59.483301827347205 |
| - type: cos_sim_recall |
| value: 74.72295514511873 |
| - type: dot_accuracy |
| value: 81.95148119449246 |
| - type: dot_ap |
| value: 60.71125646179137 |
| - type: dot_f1 |
| value: 58.44781026182928 |
| - type: dot_precision |
| value: 52.65496086312672 |
| - type: dot_recall |
| value: 65.67282321899735 |
| - type: euclidean_accuracy |
| value: 84.84830422602371 |
| - type: euclidean_ap |
| value: 69.97192936786296 |
| - type: euclidean_f1 |
| value: 66.53649011471808 |
| - type: euclidean_precision |
| value: 61.898274296094456 |
| - type: euclidean_recall |
| value: 71.92612137203166 |
| - type: manhattan_accuracy |
| value: 84.75889610776659 |
| - type: manhattan_ap |
| value: 69.75691180376053 |
| - type: manhattan_f1 |
| value: 66.32788868723533 |
| - type: manhattan_precision |
| value: 61.2513966480447 |
| - type: manhattan_recall |
| value: 72.32189973614776 |
| - type: max_accuracy |
| value: 84.84830422602371 |
| - type: max_ap |
| value: 69.97192936786296 |
| - type: max_f1 |
| value: 66.53649011471808 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twitterurlcorpus-pairclassification |
| name: MTEB TwitterURLCorpus |
| config: default |
| split: test |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
| metrics: |
| - type: cos_sim_accuracy |
| value: 88.43287926417511 |
| - type: cos_sim_ap |
| value: 85.07378179191598 |
| - type: cos_sim_f1 |
| value: 77.50230244980658 |
| - type: cos_sim_precision |
| value: 74.30246521155613 |
| - type: cos_sim_recall |
| value: 80.99014474899907 |
| - type: dot_accuracy |
| value: 86.946481934257 |
| - type: dot_ap |
| value: 80.90485630835825 |
| - type: dot_f1 |
| value: 74.43342263413221 |
| - type: dot_precision |
| value: 70.24736914035807 |
| - type: dot_recall |
| value: 79.1499846011703 |
| - type: euclidean_accuracy |
| value: 88.49303372530757 |
| - type: euclidean_ap |
| value: 85.08920672765427 |
| - type: euclidean_f1 |
| value: 77.53514807059526 |
| - type: euclidean_precision |
| value: 75.3707473102646 |
| - type: euclidean_recall |
| value: 79.82753310748383 |
| - type: manhattan_accuracy |
| value: 88.47168859393798 |
| - type: manhattan_ap |
| value: 85.01816084029292 |
| - type: manhattan_f1 |
| value: 77.36513181524315 |
| - type: manhattan_precision |
| value: 72.5057223643463 |
| - type: manhattan_recall |
| value: 82.9226978749615 |
| - type: max_accuracy |
| value: 88.49303372530757 |
| - type: max_ap |
| value: 85.08920672765427 |
| - type: max_f1 |
| value: 77.53514807059526 |
| --- |
| # Ivysaur |
|
|
| This is a fine-tune of [gte-tiny](https://huggingface.co/TaylorAI/gte-tiny) 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/Ivysaur') |
| 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/Ivysaur') |
| model = AutoModel.from_pretrained('Mihaiii/Ivysaur') |
| |
| # 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. |
