diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -1,3 +1,7910 @@ --- license: bigscience-bloom-rail-1.0 +language: + - ak + - ar + - as + - bm + - bn + - ca + - code + - en + - es + - eu + - fon + - fr + - gu + - hi + - id + - ig + - ki + - kn + - lg + - ln + - ml + - mr + - ne + - nso + - ny + - or + - pa + - pt + - rn + - rw + - sn + - st + - sw + - ta + - te + - tn + - ts + - tum + - tw + - ur + - vi + - wo + - xh + - yo + - zh + - zhs + - zht + - zu +tags: +- mteb +model-index: +- name: udever-bloom-1b1 + results: + - task: + type: STS + dataset: + type: C-MTEB/AFQMC + name: MTEB AFQMC + config: default + split: validation + revision: None + metrics: + - type: cos_sim_pearson + value: 27.90020553155914 + - type: cos_sim_spearman + value: 27.980812877007445 + - type: euclidean_pearson + value: 27.412021502878105 + - type: euclidean_spearman + value: 27.608320539898134 + - type: manhattan_pearson + value: 27.493591460276278 + - type: manhattan_spearman + value: 27.715134644174423 + - task: + type: STS + dataset: + type: C-MTEB/ATEC + name: MTEB ATEC + config: default + split: test + revision: None + metrics: + - type: cos_sim_pearson + value: 35.15277604796132 + - type: cos_sim_spearman + value: 35.863846005221575 + - type: euclidean_pearson + value: 37.65681598655078 + - type: euclidean_spearman + value: 35.50116107334066 + - type: manhattan_pearson + value: 37.736463166370854 + - type: manhattan_spearman + value: 35.53412987209704 + - task: + type: Classification + dataset: + type: mteb/amazon_counterfactual + name: MTEB AmazonCounterfactualClassification (en) + config: en + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 69.9402985074627 + - type: ap + value: 33.4661141650045 + - type: f1 + value: 64.31759903129324 + - task: + type: Classification + dataset: + type: mteb/amazon_counterfactual + name: MTEB AmazonCounterfactualClassification (de) + config: de + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 66.02783725910065 + - type: ap + value: 78.25152113775748 + - type: f1 + value: 64.00236113368896 + - task: + type: Classification + dataset: + type: mteb/amazon_counterfactual + name: MTEB AmazonCounterfactualClassification (en-ext) + config: en-ext + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 72.01649175412295 + - type: ap + value: 21.28416661100625 + - type: f1 + value: 59.481902269256096 + - task: + type: Classification + dataset: + type: mteb/amazon_counterfactual + name: MTEB AmazonCounterfactualClassification (ja) + config: ja + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 58.76873661670234 + - type: ap + value: 12.828869547428084 + - type: f1 + value: 47.5200475889544 + - task: + type: Classification + dataset: + type: mteb/amazon_polarity + name: MTEB AmazonPolarityClassification + config: default + split: test + revision: e2d317d38cd51312af73b3d32a06d1a08b442046 + metrics: + - type: accuracy + value: 87.191175 + - type: ap + value: 82.4408783026622 + - type: f1 + value: 87.16605834054603 + - task: + type: Classification + dataset: + type: mteb/amazon_reviews_multi + name: MTEB AmazonReviewsClassification (en) + config: en + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 41.082 + - type: f1 + value: 40.54924237159631 + - task: + type: Classification + dataset: + type: mteb/amazon_reviews_multi + name: MTEB AmazonReviewsClassification (de) + config: de + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 30.447999999999997 + - type: f1 + value: 30.0643283775686 + - task: + type: Classification + dataset: + type: mteb/amazon_reviews_multi + name: MTEB AmazonReviewsClassification (es) + config: es + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 40.800000000000004 + - type: f1 + value: 39.64954112879312 + - task: + type: Classification + dataset: + type: mteb/amazon_reviews_multi + name: MTEB AmazonReviewsClassification (fr) + config: fr + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 40.686 + - type: f1 + value: 39.917643425172 + - task: + type: Classification + dataset: + type: mteb/amazon_reviews_multi + name: MTEB AmazonReviewsClassification (ja) + config: ja + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 32.074 + - type: f1 + value: 31.878305643409334 + - task: + type: Classification + dataset: + type: mteb/amazon_reviews_multi + name: MTEB AmazonReviewsClassification (zh) + config: zh + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 38.122 + - type: f1 + value: 37.296210966123446 + - task: + type: Retrieval + dataset: + type: arguana + name: MTEB ArguAna + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 22.262 + - type: map_at_10 + value: 37.667 + - type: map_at_100 + value: 38.812999999999995 + - type: map_at_1000 + value: 38.829 + - type: map_at_3 + value: 32.421 + - type: map_at_5 + value: 35.202 + - type: mrr_at_1 + value: 22.759999999999998 + - type: mrr_at_10 + value: 37.817 + - type: mrr_at_100 + value: 38.983000000000004 + - type: mrr_at_1000 + value: 38.999 + - type: mrr_at_3 + value: 32.61 + - type: mrr_at_5 + value: 35.333999999999996 + - type: ndcg_at_1 + value: 22.262 + - type: ndcg_at_10 + value: 46.671 + - type: ndcg_at_100 + value: 51.519999999999996 + - type: ndcg_at_1000 + value: 51.876999999999995 + - type: ndcg_at_3 + value: 35.696 + - type: ndcg_at_5 + value: 40.722 + - type: precision_at_1 + value: 22.262 + - type: precision_at_10 + value: 7.575 + - type: precision_at_100 + value: 0.9690000000000001 + - type: precision_at_1000 + value: 0.1 + - type: precision_at_3 + value: 15.055 + - type: precision_at_5 + value: 11.479000000000001 + - type: recall_at_1 + value: 22.262 + - type: recall_at_10 + value: 75.747 + - type: recall_at_100 + value: 96.871 + - type: recall_at_1000 + value: 99.57300000000001 + - type: recall_at_3 + value: 45.164 + - type: recall_at_5 + value: 57.397 + - task: + type: Clustering + dataset: + type: mteb/arxiv-clustering-p2p + name: MTEB ArxivClusteringP2P + config: default + split: test + revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d + metrics: + - type: v_measure + value: 44.51799756336072 + - task: + type: Clustering + dataset: + type: mteb/arxiv-clustering-s2s + name: MTEB ArxivClusteringS2S + config: default + split: test + revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 + metrics: + - type: v_measure + value: 34.44923356952161 + - task: + type: Reranking + dataset: + type: mteb/askubuntudupquestions-reranking + name: MTEB AskUbuntuDupQuestions + config: default + split: test + revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 + metrics: + - type: map + value: 59.49540399419566 + - type: mrr + value: 73.43028624192061 + - task: + type: STS + dataset: + type: mteb/biosses-sts + name: MTEB BIOSSES + config: default + split: test + revision: d3fb88f8f02e40887cd149695127462bbcf29b4a + metrics: + - type: cos_sim_pearson + value: 87.67018580352695 + - type: cos_sim_spearman + value: 84.64530219460785 + - type: euclidean_pearson + value: 87.10187265189109 + - type: euclidean_spearman + value: 86.19051812629264 + - type: manhattan_pearson + value: 86.78890467534343 + - type: manhattan_spearman + value: 85.60134807514734 + - task: + type: STS + dataset: + type: C-MTEB/BQ + name: MTEB BQ + config: default + split: test + revision: None + metrics: + - type: cos_sim_pearson + value: 46.308790362891266 + - type: cos_sim_spearman + value: 46.22674926863126 + - type: euclidean_pearson + value: 47.36625172551589 + - type: euclidean_spearman + value: 47.55854392572494 + - type: manhattan_pearson + value: 47.3342490976193 + - type: manhattan_spearman + value: 47.52249648456463 + - task: + type: BitextMining + dataset: + type: mteb/bucc-bitext-mining + name: MTEB BUCC (de-en) + config: de-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 42.67223382045929 + - type: f1 + value: 42.02704262244064 + - type: precision + value: 41.76166726545405 + - type: recall + value: 42.67223382045929 + - task: + type: BitextMining + dataset: + type: mteb/bucc-bitext-mining + name: MTEB BUCC (fr-en) + config: fr-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 97.95289456306405 + - type: f1 + value: 97.70709516472228 + - type: precision + value: 97.58602978941964 + - type: recall + value: 97.95289456306405 + - task: + type: BitextMining + dataset: + type: mteb/bucc-bitext-mining + name: MTEB BUCC (ru-en) + config: ru-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 25.375822653273296 + - type: f1 + value: 24.105776263207947 + - type: precision + value: 23.644628498465117 + - type: recall + value: 25.375822653273296 + - task: + type: BitextMining + dataset: + type: mteb/bucc-bitext-mining + name: MTEB BUCC (zh-en) + config: zh-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 98.31490258030541 + - type: f1 + value: 98.24469018781815 + - type: precision + value: 98.2095839915745 + - type: recall + value: 98.31490258030541 + - task: + type: Classification + dataset: + type: mteb/banking77 + name: MTEB Banking77Classification + config: default + split: test + revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 + metrics: + - type: accuracy + value: 82.89285714285714 + - type: f1 + value: 82.84943089389121 + - task: + type: Clustering + dataset: + type: mteb/biorxiv-clustering-p2p + name: MTEB BiorxivClusteringP2P + config: default + split: test + revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 + metrics: + - type: v_measure + value: 35.25261508107809 + - task: + type: Clustering + dataset: + type: mteb/biorxiv-clustering-s2s + name: MTEB BiorxivClusteringS2S + config: default + split: test + revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 + metrics: + - type: v_measure + value: 30.708512338509653 + - task: + type: Clustering + dataset: + type: C-MTEB/CLSClusteringP2P + name: MTEB CLSClusteringP2P + config: default + split: test + revision: None + metrics: + - type: v_measure + value: 35.361295166692464 + - task: + type: Clustering + dataset: + type: C-MTEB/CLSClusteringS2S + name: MTEB CLSClusteringS2S + config: default + split: test + revision: None + metrics: + - type: v_measure + value: 37.06879287045825 + - task: + type: Reranking + dataset: + type: C-MTEB/CMedQAv1-reranking + name: MTEB CMedQAv1 + config: default + split: test + revision: None + metrics: + - type: map + value: 66.06033605600476 + - type: mrr + value: 70.82825396825396 + - task: + type: Reranking + dataset: + type: C-MTEB/CMedQAv2-reranking + name: MTEB CMedQAv2 + config: default + split: test + revision: None + metrics: + - type: map + value: 66.9600733219955 + - type: mrr + value: 72.19742063492063 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackAndroidRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 29.526999999999997 + - type: map_at_10 + value: 38.747 + - type: map_at_100 + value: 40.172999999999995 + - type: map_at_1000 + value: 40.311 + - type: map_at_3 + value: 35.969 + - type: map_at_5 + value: 37.344 + - type: mrr_at_1 + value: 36.767 + - type: mrr_at_10 + value: 45.082 + - type: mrr_at_100 + value: 45.898 + - type: mrr_at_1000 + value: 45.958 + - type: mrr_at_3 + value: 43.085 + - type: mrr_at_5 + value: 44.044 + - type: ndcg_at_1 + value: 36.767 + - type: ndcg_at_10 + value: 44.372 + - type: ndcg_at_100 + value: 49.908 + - type: ndcg_at_1000 + value: 52.358000000000004 + - type: ndcg_at_3 + value: 40.711000000000006 + - type: ndcg_at_5 + value: 41.914 + - type: precision_at_1 + value: 36.767 + - type: precision_at_10 + value: 8.283 + - type: precision_at_100 + value: 1.3679999999999999 + - type: precision_at_1000 + value: 0.189 + - type: precision_at_3 + value: 19.599 + - type: precision_at_5 + value: 13.505 + - type: recall_at_1 + value: 29.526999999999997 + - type: recall_at_10 + value: 54.198 + - type: recall_at_100 + value: 77.818 + - type: recall_at_1000 + value: 93.703 + - type: recall_at_3 + value: 42.122 + - type: recall_at_5 + value: 46.503 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackEnglishRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 22.646 + - type: map_at_10 + value: 30.447999999999997 + - type: map_at_100 + value: 31.417 + - type: map_at_1000 + value: 31.528 + - type: map_at_3 + value: 28.168 + - type: map_at_5 + value: 29.346 + - type: mrr_at_1 + value: 28.854000000000003 + - type: mrr_at_10 + value: 35.611 + - type: mrr_at_100 + value: 36.321 + - type: mrr_at_1000 + value: 36.378 + - type: mrr_at_3 + value: 33.726 + - type: mrr_at_5 + value: 34.745 + - type: ndcg_at_1 + value: 28.854000000000003 + - type: ndcg_at_10 + value: 35.052 + - type: ndcg_at_100 + value: 39.190999999999995 + - type: ndcg_at_1000 + value: 41.655 + - type: ndcg_at_3 + value: 31.684 + - type: ndcg_at_5 + value: 32.998 + - type: precision_at_1 + value: 28.854000000000003 + - type: precision_at_10 + value: 6.49 + - type: precision_at_100 + value: 1.057 + - type: precision_at_1000 + value: 0.153 + - type: precision_at_3 + value: 15.244 + - type: precision_at_5 + value: 10.599 + - type: recall_at_1 + value: 22.646 + - type: recall_at_10 + value: 43.482 + - type: recall_at_100 + value: 61.324 + - type: recall_at_1000 + value: 77.866 + - type: recall_at_3 + value: 33.106 + - type: recall_at_5 + value: 37.124 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackGamingRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 35.061 + - type: map_at_10 + value: 46.216 + - type: map_at_100 + value: 47.318 + - type: map_at_1000 + value: 47.384 + - type: map_at_3 + value: 43.008 + - type: map_at_5 + value: 44.79 + - type: mrr_at_1 + value: 40.251 + - type: mrr_at_10 + value: 49.677 + - type: mrr_at_100 + value: 50.39 + - type: mrr_at_1000 + value: 50.429 + - type: mrr_at_3 + value: 46.792 + - type: mrr_at_5 + value: 48.449999999999996 + - type: ndcg_at_1 + value: 40.251 + - type: ndcg_at_10 + value: 51.99399999999999 + - type: ndcg_at_100 + value: 56.418 + - type: ndcg_at_1000 + value: 57.798 + - type: ndcg_at_3 + value: 46.192 + - type: ndcg_at_5 + value: 48.998000000000005 + - type: precision_at_1 + value: 40.251 + - type: precision_at_10 + value: 8.469999999999999 + - type: precision_at_100 + value: 1.159 + - type: precision_at_1000 + value: 0.133 + - type: precision_at_3 + value: 20.46 + - type: precision_at_5 + value: 14.332 + - type: recall_at_1 + value: 35.061 + - type: recall_at_10 + value: 65.818 + - type: recall_at_100 + value: 84.935 + - type: recall_at_1000 + value: 94.69300000000001 + - type: recall_at_3 + value: 50.300999999999995 + - type: recall_at_5 + value: 57.052 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackGisRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 20.776 + - type: map_at_10 + value: 27.945999999999998 + - type: map_at_100 + value: 28.976000000000003 + - type: map_at_1000 + value: 29.073999999999998 + - type: map_at_3 + value: 25.673000000000002 + - type: map_at_5 + value: 26.96 + - type: mrr_at_1 + value: 22.486 + - type: mrr_at_10 + value: 29.756 + - type: mrr_at_100 + value: 30.735 + - type: mrr_at_1000 + value: 30.81 + - type: mrr_at_3 + value: 27.571 + - type: mrr_at_5 + value: 28.808 + - type: ndcg_at_1 + value: 22.486 + - type: ndcg_at_10 + value: 32.190000000000005 + - type: ndcg_at_100 + value: 37.61 + - type: ndcg_at_1000 + value: 40.116 + - type: ndcg_at_3 + value: 27.688000000000002 + - type: ndcg_at_5 + value: 29.87 + - type: precision_at_1 + value: 22.486 + - type: precision_at_10 + value: 5.028 + - type: precision_at_100 + value: 0.818 + - type: precision_at_1000 + value: 0.107 + - type: precision_at_3 + value: 11.827 + - type: precision_at_5 + value: 8.362 + - type: recall_at_1 + value: 20.776 + - type: recall_at_10 + value: 43.588 + - type: recall_at_100 + value: 69.139 + - type: recall_at_1000 + value: 88.144 + - type: recall_at_3 + value: 31.411 + - type: recall_at_5 + value: 36.655 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackMathematicaRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 12.994 + - type: map_at_10 + value: 19.747999999999998 + - type: map_at_100 + value: 20.877000000000002 + - type: map_at_1000 + value: 21.021 + - type: map_at_3 + value: 17.473 + - type: map_at_5 + value: 18.683 + - type: mrr_at_1 + value: 16.542 + - type: mrr_at_10 + value: 23.830000000000002 + - type: mrr_at_100 + value: 24.789 + - type: mrr_at_1000 + value: 24.877 + - type: mrr_at_3 + value: 21.476 + - type: mrr_at_5 + value: 22.838 + - type: ndcg_at_1 + value: 16.542 + - type: ndcg_at_10 + value: 24.422 + - type: ndcg_at_100 + value: 30.011 + - type: ndcg_at_1000 + value: 33.436 + - type: ndcg_at_3 + value: 20.061999999999998 + - type: ndcg_at_5 + value: 22.009999999999998 + - type: precision_at_1 + value: 16.542 + - type: precision_at_10 + value: 4.664 + - type: precision_at_100 + value: 0.876 + - type: precision_at_1000 + value: 0.132 + - type: precision_at_3 + value: 9.826 + - type: precision_at_5 + value: 7.2139999999999995 + - type: recall_at_1 + value: 12.994 + - type: recall_at_10 + value: 34.917 + - type: recall_at_100 + value: 59.455000000000005 + - type: recall_at_1000 + value: 83.87299999999999 + - type: recall_at_3 + value: 22.807 + - type: recall_at_5 + value: 27.773999999999997 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackPhysicsRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 24.85 + - type: map_at_10 + value: 35.285 + - type: map_at_100 + value: 36.592999999999996 + - type: map_at_1000 + value: 36.720000000000006 + - type: map_at_3 + value: 32.183 + - type: map_at_5 + value: 33.852 + - type: mrr_at_1 + value: 30.703000000000003 + - type: mrr_at_10 + value: 40.699000000000005 + - type: mrr_at_100 + value: 41.598 + - type: mrr_at_1000 + value: 41.654 + - type: mrr_at_3 + value: 38.080999999999996 + - type: mrr_at_5 + value: 39.655 + - type: ndcg_at_1 + value: 30.703000000000003 + - type: ndcg_at_10 + value: 41.422 + - type: ndcg_at_100 + value: 46.998 + - type: ndcg_at_1000 + value: 49.395 + - type: ndcg_at_3 + value: 36.353 + - type: ndcg_at_5 + value: 38.7 + - type: precision_at_1 + value: 30.703000000000003 + - type: precision_at_10 + value: 7.757 + - type: precision_at_100 + value: 1.2349999999999999 + - type: precision_at_1000 + value: 0.164 + - type: precision_at_3 + value: 17.613 + - type: precision_at_5 + value: 12.589 + - type: recall_at_1 + value: 24.85 + - type: recall_at_10 + value: 54.19500000000001 + - type: recall_at_100 + value: 77.697 + - type: recall_at_1000 + value: 93.35900000000001 + - type: recall_at_3 + value: 39.739999999999995 + - type: recall_at_5 + value: 46.03 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackProgrammersRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 19.844 + - type: map_at_10 + value: 28.663 + - type: map_at_100 + value: 30.013 + - type: map_at_1000 + value: 30.139 + - type: map_at_3 + value: 25.953 + - type: map_at_5 + value: 27.425 + - type: mrr_at_1 + value: 25.457 + - type: mrr_at_10 + value: 34.266000000000005 + - type: mrr_at_100 + value: 35.204 + - type: mrr_at_1000 + value: 35.27 + - type: mrr_at_3 + value: 31.791999999999998 + - type: mrr_at_5 + value: 33.213 + - type: ndcg_at_1 + value: 25.457 + - type: ndcg_at_10 + value: 34.266000000000005 + - type: ndcg_at_100 + value: 40.239999999999995 + - type: ndcg_at_1000 + value: 42.917 + - type: ndcg_at_3 + value: 29.593999999999998 + - type: ndcg_at_5 + value: 31.71 + - type: precision_at_1 + value: 25.457 + - type: precision_at_10 + value: 6.438000000000001 + - type: precision_at_100 + value: 1.1159999999999999 + - type: precision_at_1000 + value: 0.153 + - type: precision_at_3 + value: 14.46 + - type: precision_at_5 + value: 10.388 + - type: recall_at_1 + value: 19.844 + - type: recall_at_10 + value: 45.787 + - type: recall_at_100 + value: 71.523 + - type: recall_at_1000 + value: 89.689 + - type: recall_at_3 + value: 32.665 + - type: recall_at_5 + value: 38.292 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 21.601166666666668 + - type: map_at_10 + value: 29.434166666666666 + - type: map_at_100 + value: 30.5905 + - type: map_at_1000 + value: 30.716583333333343 + - type: map_at_3 + value: 26.962333333333333 + - type: map_at_5 + value: 28.287250000000004 + - type: mrr_at_1 + value: 25.84825 + - type: mrr_at_10 + value: 33.49966666666667 + - type: mrr_at_100 + value: 34.39425000000001 + - type: mrr_at_1000 + value: 34.46366666666667 + - type: mrr_at_3 + value: 31.256 + - type: mrr_at_5 + value: 32.52016666666667 + - type: ndcg_at_1 + value: 25.84825 + - type: ndcg_at_10 + value: 34.2975 + - type: ndcg_at_100 + value: 39.50983333333333 + - type: ndcg_at_1000 + value: 42.17958333333333 + - type: ndcg_at_3 + value: 30.00558333333333 + - type: ndcg_at_5 + value: 31.931416666666664 + - type: precision_at_1 + value: 25.84825 + - type: precision_at_10 + value: 6.075083333333334 + - type: precision_at_100 + value: 1.0205833333333334 + - type: precision_at_1000 + value: 0.14425 + - type: precision_at_3 + value: 13.903249999999998 + - type: precision_at_5 + value: 9.874999999999998 + - type: recall_at_1 + value: 21.601166666666668 + - type: recall_at_10 + value: 44.787333333333336 + - type: recall_at_100 + value: 67.89450000000001 + - type: recall_at_1000 + value: 86.62424999999999 + - type: recall_at_3 + value: 32.66375 + - type: recall_at_5 + value: 37.71825 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackStatsRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 19.804 + - type: map_at_10 + value: 25.983 + - type: map_at_100 + value: 26.956999999999997 + - type: map_at_1000 + value: 27.067999999999998 + - type: map_at_3 + value: 23.804 + - type: map_at_5 + value: 24.978 + - type: mrr_at_1 + value: 22.853 + - type: mrr_at_10 + value: 28.974 + - type: mrr_at_100 + value: 29.855999999999998 + - type: mrr_at_1000 + value: 29.936 + - type: mrr_at_3 + value: 26.866 + - type: mrr_at_5 + value: 28.032 + - type: ndcg_at_1 + value: 22.853 + - type: ndcg_at_10 + value: 29.993 + - type: ndcg_at_100 + value: 34.735 + - type: ndcg_at_1000 + value: 37.637 + - type: ndcg_at_3 + value: 25.863000000000003 + - type: ndcg_at_5 + value: 27.769 + - type: precision_at_1 + value: 22.853 + - type: precision_at_10 + value: 4.8469999999999995 + - type: precision_at_100 + value: 0.779 + - type: precision_at_1000 + value: 0.11 + - type: precision_at_3 + value: 11.35 + - type: precision_at_5 + value: 7.9750000000000005 + - type: recall_at_1 + value: 19.804 + - type: recall_at_10 + value: 39.616 + - type: recall_at_100 + value: 61.06399999999999 + - type: recall_at_1000 + value: 82.69800000000001 + - type: recall_at_3 + value: 28.012999999999998 + - type: recall_at_5 + value: 32.96 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackTexRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 13.156 + - type: map_at_10 + value: 18.734 + - type: map_at_100 + value: 19.721 + - type: map_at_1000 + value: 19.851 + - type: map_at_3 + value: 17.057 + - type: map_at_5 + value: 17.941 + - type: mrr_at_1 + value: 16.07 + - type: mrr_at_10 + value: 22.113 + - type: mrr_at_100 + value: 23.021 + - type: mrr_at_1000 + value: 23.108 + - type: mrr_at_3 + value: 20.429 + - type: mrr_at_5 + value: 21.332 + - type: ndcg_at_1 + value: 16.07 + - type: ndcg_at_10 + value: 22.427 + - type: ndcg_at_100 + value: 27.277 + - type: ndcg_at_1000 + value: 30.525000000000002 + - type: ndcg_at_3 + value: 19.374 + - type: ndcg_at_5 + value: 20.695 + - type: precision_at_1 + value: 16.07 + - type: precision_at_10 + value: 4.1259999999999994 + - type: precision_at_100 + value: 0.769 + - type: precision_at_1000 + value: 0.122 + - type: precision_at_3 + value: 9.325999999999999 + - type: precision_at_5 + value: 6.683 + - type: recall_at_1 + value: 13.156 + - type: recall_at_10 + value: 30.223 + - type: recall_at_100 + value: 52.012 + - type: recall_at_1000 + value: 75.581 + - type: recall_at_3 + value: 21.508 + - type: recall_at_5 + value: 24.975 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackUnixRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 22.14 + - type: map_at_10 + value: 28.961 + - type: map_at_100 + value: 29.996000000000002 + - type: map_at_1000 + value: 30.112 + - type: map_at_3 + value: 26.540000000000003 + - type: map_at_5 + value: 27.916999999999998 + - type: mrr_at_1 + value: 25.746000000000002 + - type: mrr_at_10 + value: 32.936 + - type: mrr_at_100 + value: 33.811 + - type: mrr_at_1000 + value: 33.887 + - type: mrr_at_3 + value: 30.55 + - type: mrr_at_5 + value: 32.08 + - type: ndcg_at_1 + value: 25.746000000000002 + - type: ndcg_at_10 + value: 33.536 + - type: ndcg_at_100 + value: 38.830999999999996 + - type: ndcg_at_1000 + value: 41.644999999999996 + - type: ndcg_at_3 + value: 29.004 + - type: ndcg_at_5 + value: 31.284 + - type: precision_at_1 + value: 25.746000000000002 + - type: precision_at_10 + value: 5.569 + - type: precision_at_100 + value: 0.9259999999999999 + - type: precision_at_1000 + value: 0.128 + - type: precision_at_3 + value: 12.748999999999999 + - type: precision_at_5 + value: 9.216000000000001 + - type: recall_at_1 + value: 22.14 + - type: recall_at_10 + value: 43.628 + - type: recall_at_100 + value: 67.581 + - type: recall_at_1000 + value: 87.737 + - type: recall_at_3 + value: 31.579 + - type: recall_at_5 + value: 37.12 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackWebmastersRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 22.384 + - type: map_at_10 + value: 30.156 + - type: map_at_100 + value: 31.728 + - type: map_at_1000 + value: 31.971 + - type: map_at_3 + value: 27.655 + - type: map_at_5 + value: 28.965000000000003 + - type: mrr_at_1 + value: 27.075 + - type: mrr_at_10 + value: 34.894 + - type: mrr_at_100 + value: 36.0 + - type: mrr_at_1000 + value: 36.059000000000005 + - type: mrr_at_3 + value: 32.708 + - type: mrr_at_5 + value: 33.893 + - type: ndcg_at_1 + value: 27.075 + - type: ndcg_at_10 + value: 35.58 + - type: ndcg_at_100 + value: 41.597 + - type: ndcg_at_1000 + value: 44.529999999999994 + - type: ndcg_at_3 + value: 31.628 + - type: ndcg_at_5 + value: 33.333 + - type: precision_at_1 + value: 27.075 + - type: precision_at_10 + value: 6.9959999999999996 + - type: precision_at_100 + value: 1.431 + - type: precision_at_1000 + value: 0.23800000000000002 + - type: precision_at_3 + value: 15.02 + - type: precision_at_5 + value: 10.909 + - type: recall_at_1 + value: 22.384 + - type: recall_at_10 + value: 45.052 + - type: recall_at_100 + value: 72.441 + - type: recall_at_1000 + value: 91.047 + - type: recall_at_3 + value: 33.617000000000004 + - type: recall_at_5 + value: 38.171 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackWordpressRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 16.032 + - type: map_at_10 + value: 22.323 + - type: map_at_100 + value: 23.317 + - type: map_at_1000 + value: 23.419999999999998 + - type: map_at_3 + value: 20.064999999999998 + - type: map_at_5 + value: 21.246000000000002 + - type: mrr_at_1 + value: 17.375 + - type: mrr_at_10 + value: 24.157999999999998 + - type: mrr_at_100 + value: 25.108000000000004 + - type: mrr_at_1000 + value: 25.197999999999997 + - type: mrr_at_3 + value: 21.996 + - type: mrr_at_5 + value: 23.152 + - type: ndcg_at_1 + value: 17.375 + - type: ndcg_at_10 + value: 26.316 + - type: ndcg_at_100 + value: 31.302000000000003 + - type: ndcg_at_1000 + value: 34.143 + - type: ndcg_at_3 + value: 21.914 + - type: ndcg_at_5 + value: 23.896 + - type: precision_at_1 + value: 17.375 + - type: precision_at_10 + value: 4.233 + - type: precision_at_100 + value: 0.713 + - type: precision_at_1000 + value: 0.10200000000000001 + - type: precision_at_3 + value: 9.365 + - type: precision_at_5 + value: 6.728000000000001 + - type: recall_at_1 + value: 16.032 + - type: recall_at_10 + value: 36.944 + - type: recall_at_100 + value: 59.745000000000005 + - type: recall_at_1000 + value: 81.101 + - type: recall_at_3 + value: 25.096 + - type: recall_at_5 + value: 29.963 + - task: + type: Retrieval + dataset: + type: climate-fever + name: MTEB ClimateFEVER + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 9.656 + - type: map_at_10 + value: 17.578 + - type: map_at_100 + value: 19.38 + - type: map_at_1000 + value: 19.552 + - type: map_at_3 + value: 14.544 + - type: map_at_5 + value: 15.914 + - type: mrr_at_1 + value: 21.041999999999998 + - type: mrr_at_10 + value: 33.579 + - type: mrr_at_100 + value: 34.483000000000004 + - type: mrr_at_1000 + value: 34.526 + - type: mrr_at_3 + value: 30.0 + - type: mrr_at_5 + value: 31.813999999999997 + - type: ndcg_at_1 + value: 21.041999999999998 + - type: ndcg_at_10 + value: 25.563999999999997 + - type: ndcg_at_100 + value: 32.714 + - type: ndcg_at_1000 + value: 35.943000000000005 + - type: ndcg_at_3 + value: 20.357 + - type: ndcg_at_5 + value: 21.839 + - type: precision_at_1 + value: 21.041999999999998 + - type: precision_at_10 + value: 8.319 + - type: precision_at_100 + value: 1.593 + - type: precision_at_1000 + value: 0.219 + - type: precision_at_3 + value: 15.440000000000001 + - type: precision_at_5 + value: 11.792 + - type: recall_at_1 + value: 9.656 + - type: recall_at_10 + value: 32.023 + - type: recall_at_100 + value: 56.812 + - type: recall_at_1000 + value: 75.098 + - type: recall_at_3 + value: 19.455 + - type: recall_at_5 + value: 23.68 + - task: + type: Retrieval + dataset: + type: C-MTEB/CmedqaRetrieval + name: MTEB CmedqaRetrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 13.084999999999999 + - type: map_at_10 + value: 19.389 + - type: map_at_100 + value: 20.761 + - type: map_at_1000 + value: 20.944 + - type: map_at_3 + value: 17.273 + - type: map_at_5 + value: 18.37 + - type: mrr_at_1 + value: 20.955 + - type: mrr_at_10 + value: 26.741999999999997 + - type: mrr_at_100 + value: 27.724 + - type: mrr_at_1000 + value: 27.819 + - type: mrr_at_3 + value: 24.881 + - type: mrr_at_5 + value: 25.833000000000002 + - type: ndcg_at_1 + value: 20.955 + - type: ndcg_at_10 + value: 23.905 + - type: ndcg_at_100 + value: 30.166999999999998 + - type: ndcg_at_1000 + value: 34.202 + - type: ndcg_at_3 + value: 20.854 + - type: ndcg_at_5 + value: 21.918000000000003 + - type: precision_at_1 + value: 20.955 + - type: precision_at_10 + value: 5.479 + - type: precision_at_100 + value: 1.065 + - type: precision_at_1000 + value: 0.159 + - type: precision_at_3 + value: 11.960999999999999 + - type: precision_at_5 + value: 8.647 + - type: recall_at_1 + value: 13.084999999999999 + - type: recall_at_10 + value: 30.202 + - type: recall_at_100 + value: 56.579 + - type: recall_at_1000 + value: 84.641 + - type: recall_at_3 + value: 20.751 + - type: recall_at_5 + value: 24.317 + - task: + type: PairClassification + dataset: + type: C-MTEB/CMNLI + name: MTEB Cmnli + config: default + split: validation + revision: None + metrics: + - type: cos_sim_accuracy + value: 72.8322309079976 + - type: cos_sim_ap + value: 81.34356949111096 + - type: cos_sim_f1 + value: 74.88546438983758 + - type: cos_sim_precision + value: 67.50516238032664 + - type: cos_sim_recall + value: 84.07762450315643 + - type: dot_accuracy + value: 69.28442573662056 + - type: dot_ap + value: 74.87961278837321 + - type: dot_f1 + value: 72.20502901353966 + - type: dot_precision + value: 61.5701797789873 + - type: dot_recall + value: 87.2808043020809 + - type: euclidean_accuracy + value: 71.99037883343355 + - type: euclidean_ap + value: 80.70039825164011 + - type: euclidean_f1 + value: 74.23149154887813 + - type: euclidean_precision + value: 64.29794520547945 + - type: euclidean_recall + value: 87.79518353986438 + - type: manhattan_accuracy + value: 72.0625375826819 + - type: manhattan_ap + value: 80.78886354854423 + - type: manhattan_f1 + value: 74.20842299415924 + - type: manhattan_precision + value: 66.0525355709595 + - type: manhattan_recall + value: 84.66214636427402 + - type: max_accuracy + value: 72.8322309079976 + - type: max_ap + value: 81.34356949111096 + - type: max_f1 + value: 74.88546438983758 + - task: + type: Retrieval + dataset: + type: C-MTEB/CovidRetrieval + name: MTEB CovidRetrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 54.847 + - type: map_at_10 + value: 63.736000000000004 + - type: map_at_100 + value: 64.302 + - type: map_at_1000 + value: 64.319 + - type: map_at_3 + value: 61.565000000000005 + - type: map_at_5 + value: 62.671 + - type: mrr_at_1 + value: 54.900000000000006 + - type: mrr_at_10 + value: 63.744 + - type: mrr_at_100 + value: 64.287 + - type: mrr_at_1000 + value: 64.30399999999999 + - type: mrr_at_3 + value: 61.590999999999994 + - type: mrr_at_5 + value: 62.724000000000004 + - type: ndcg_at_1 + value: 55.005 + - type: ndcg_at_10 + value: 68.142 + - type: ndcg_at_100 + value: 70.95 + - type: ndcg_at_1000 + value: 71.40100000000001 + - type: ndcg_at_3 + value: 63.641999999999996 + - type: ndcg_at_5 + value: 65.62599999999999 + - type: precision_at_1 + value: 55.005 + - type: precision_at_10 + value: 8.272 + - type: precision_at_100 + value: 0.963 + - type: precision_at_1000 + value: 0.1 + - type: precision_at_3 + value: 23.288 + - type: precision_at_5 + value: 14.963000000000001 + - type: recall_at_1 + value: 54.847 + - type: recall_at_10 + value: 81.955 + - type: recall_at_100 + value: 95.258 + - type: recall_at_1000 + value: 98.84100000000001 + - type: recall_at_3 + value: 69.547 + - type: recall_at_5 + value: 74.315 + - task: + type: Retrieval + dataset: + type: dbpedia-entity + name: MTEB DBPedia + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 7.2620000000000005 + - type: map_at_10 + value: 15.196000000000002 + - type: map_at_100 + value: 19.454 + - type: map_at_1000 + value: 20.445 + - type: map_at_3 + value: 11.532 + - type: map_at_5 + value: 13.053999999999998 + - type: mrr_at_1 + value: 57.49999999999999 + - type: mrr_at_10 + value: 66.661 + - type: mrr_at_100 + value: 67.086 + - type: mrr_at_1000 + value: 67.105 + - type: mrr_at_3 + value: 64.625 + - type: mrr_at_5 + value: 65.962 + - type: ndcg_at_1 + value: 46.125 + - type: ndcg_at_10 + value: 32.609 + - type: ndcg_at_100 + value: 34.611999999999995 + - type: ndcg_at_1000 + value: 40.836 + - type: ndcg_at_3 + value: 37.513000000000005 + - type: ndcg_at_5 + value: 34.699999999999996 + - type: precision_at_1 + value: 57.49999999999999 + - type: precision_at_10 + value: 24.975 + - type: precision_at_100 + value: 6.9830000000000005 + - type: precision_at_1000 + value: 1.505 + - type: precision_at_3 + value: 40.75 + - type: precision_at_5 + value: 33.2 + - type: recall_at_1 + value: 7.2620000000000005 + - type: recall_at_10 + value: 20.341 + - type: recall_at_100 + value: 38.690999999999995 + - type: recall_at_1000 + value: 58.879000000000005 + - type: recall_at_3 + value: 12.997 + - type: recall_at_5 + value: 15.628 + - task: + type: Retrieval + dataset: + type: C-MTEB/DuRetrieval + name: MTEB DuRetrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 20.86 + - type: map_at_10 + value: 62.28 + - type: map_at_100 + value: 65.794 + - type: map_at_1000 + value: 65.903 + - type: map_at_3 + value: 42.616 + - type: map_at_5 + value: 53.225 + - type: mrr_at_1 + value: 76.75 + - type: mrr_at_10 + value: 83.387 + - type: mrr_at_100 + value: 83.524 + - type: mrr_at_1000 + value: 83.531 + - type: mrr_at_3 + value: 82.592 + - type: mrr_at_5 + value: 83.07900000000001 + - type: ndcg_at_1 + value: 76.75 + - type: ndcg_at_10 + value: 72.83500000000001 + - type: ndcg_at_100 + value: 77.839 + - type: ndcg_at_1000 + value: 78.976 + - type: ndcg_at_3 + value: 70.977 + - type: ndcg_at_5 + value: 69.419 + - type: precision_at_1 + value: 76.75 + - type: precision_at_10 + value: 35.825 + - type: precision_at_100 + value: 4.507 + - type: precision_at_1000 + value: 0.47800000000000004 + - type: precision_at_3 + value: 63.733 + - type: precision_at_5 + value: 53.44 + - type: recall_at_1 + value: 20.86 + - type: recall_at_10 + value: 75.115 + - type: recall_at_100 + value: 90.47699999999999 + - type: recall_at_1000 + value: 96.304 + - type: recall_at_3 + value: 45.976 + - type: recall_at_5 + value: 59.971 + - task: + type: Retrieval + dataset: + type: C-MTEB/EcomRetrieval + name: MTEB EcomRetrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 37.8 + - type: map_at_10 + value: 47.154 + - type: map_at_100 + value: 48.012 + - type: map_at_1000 + value: 48.044 + - type: map_at_3 + value: 44.667 + - type: map_at_5 + value: 45.992 + - type: mrr_at_1 + value: 37.8 + - type: mrr_at_10 + value: 47.154 + - type: mrr_at_100 + value: 48.012 + - type: mrr_at_1000 + value: 48.044 + - type: mrr_at_3 + value: 44.667 + - type: mrr_at_5 + value: 45.992 + - type: ndcg_at_1 + value: 37.8 + - type: ndcg_at_10 + value: 52.025 + - type: ndcg_at_100 + value: 56.275 + - type: ndcg_at_1000 + value: 57.174 + - type: ndcg_at_3 + value: 46.861999999999995 + - type: ndcg_at_5 + value: 49.229 + - type: precision_at_1 + value: 37.8 + - type: precision_at_10 + value: 6.75 + - type: precision_at_100 + value: 0.8750000000000001 + - type: precision_at_1000 + value: 0.095 + - type: precision_at_3 + value: 17.732999999999997 + - type: precision_at_5 + value: 11.78 + - type: recall_at_1 + value: 37.8 + - type: recall_at_10 + value: 67.5 + - type: recall_at_100 + value: 87.5 + - type: recall_at_1000 + value: 94.69999999999999 + - type: recall_at_3 + value: 53.2 + - type: recall_at_5 + value: 58.9 + - task: + type: Classification + dataset: + type: mteb/emotion + name: MTEB EmotionClassification + config: default + split: test + revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 + metrics: + - type: accuracy + value: 46.845 + - type: f1 + value: 42.70952656074019 + - task: + type: Retrieval + dataset: + type: fever + name: MTEB FEVER + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 50.058 + - type: map_at_10 + value: 61.295 + - type: map_at_100 + value: 61.82 + - type: map_at_1000 + value: 61.843 + - type: map_at_3 + value: 58.957 + - type: map_at_5 + value: 60.467999999999996 + - type: mrr_at_1 + value: 54.05 + - type: mrr_at_10 + value: 65.52900000000001 + - type: mrr_at_100 + value: 65.984 + - type: mrr_at_1000 + value: 65.999 + - type: mrr_at_3 + value: 63.286 + - type: mrr_at_5 + value: 64.777 + - type: ndcg_at_1 + value: 54.05 + - type: ndcg_at_10 + value: 67.216 + - type: ndcg_at_100 + value: 69.594 + - type: ndcg_at_1000 + value: 70.13000000000001 + - type: ndcg_at_3 + value: 62.778999999999996 + - type: ndcg_at_5 + value: 65.36 + - type: precision_at_1 + value: 54.05 + - type: precision_at_10 + value: 8.924 + - type: precision_at_100 + value: 1.019 + - type: precision_at_1000 + value: 0.108 + - type: precision_at_3 + value: 25.218 + - type: precision_at_5 + value: 16.547 + - type: recall_at_1 + value: 50.058 + - type: recall_at_10 + value: 81.39699999999999 + - type: recall_at_100 + value: 92.022 + - type: recall_at_1000 + value: 95.877 + - type: recall_at_3 + value: 69.485 + - type: recall_at_5 + value: 75.833 + - task: + type: Retrieval + dataset: + type: fiqa + name: MTEB FiQA2018 + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 15.078 + - type: map_at_10 + value: 24.162 + - type: map_at_100 + value: 25.818 + - type: map_at_1000 + value: 26.009 + - type: map_at_3 + value: 20.706 + - type: map_at_5 + value: 22.542 + - type: mrr_at_1 + value: 30.709999999999997 + - type: mrr_at_10 + value: 38.828 + - type: mrr_at_100 + value: 39.794000000000004 + - type: mrr_at_1000 + value: 39.843 + - type: mrr_at_3 + value: 36.163000000000004 + - type: mrr_at_5 + value: 37.783 + - type: ndcg_at_1 + value: 30.709999999999997 + - type: ndcg_at_10 + value: 31.290000000000003 + - type: ndcg_at_100 + value: 38.051 + - type: ndcg_at_1000 + value: 41.487 + - type: ndcg_at_3 + value: 27.578999999999997 + - type: ndcg_at_5 + value: 28.799000000000003 + - type: precision_at_1 + value: 30.709999999999997 + - type: precision_at_10 + value: 8.92 + - type: precision_at_100 + value: 1.5599999999999998 + - type: precision_at_1000 + value: 0.219 + - type: precision_at_3 + value: 18.416 + - type: precision_at_5 + value: 13.827 + - type: recall_at_1 + value: 15.078 + - type: recall_at_10 + value: 37.631 + - type: recall_at_100 + value: 63.603 + - type: recall_at_1000 + value: 84.121 + - type: recall_at_3 + value: 24.438 + - type: recall_at_5 + value: 29.929 + - task: + type: Retrieval + dataset: + type: hotpotqa + name: MTEB HotpotQA + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 31.202 + - type: map_at_10 + value: 42.653 + - type: map_at_100 + value: 43.411 + - type: map_at_1000 + value: 43.479 + - type: map_at_3 + value: 40.244 + - type: map_at_5 + value: 41.736000000000004 + - type: mrr_at_1 + value: 62.404 + - type: mrr_at_10 + value: 69.43599999999999 + - type: mrr_at_100 + value: 69.788 + - type: mrr_at_1000 + value: 69.809 + - type: mrr_at_3 + value: 68.12700000000001 + - type: mrr_at_5 + value: 68.961 + - type: ndcg_at_1 + value: 62.404 + - type: ndcg_at_10 + value: 51.665000000000006 + - type: ndcg_at_100 + value: 54.623 + - type: ndcg_at_1000 + value: 56.154 + - type: ndcg_at_3 + value: 47.861 + - type: ndcg_at_5 + value: 49.968 + - type: precision_at_1 + value: 62.404 + - type: precision_at_10 + value: 10.57 + - type: precision_at_100 + value: 1.2890000000000001 + - type: precision_at_1000 + value: 0.149 + - type: precision_at_3 + value: 29.624 + - type: precision_at_5 + value: 19.441 + - type: recall_at_1 + value: 31.202 + - type: recall_at_10 + value: 52.849000000000004 + - type: recall_at_100 + value: 64.47 + - type: recall_at_1000 + value: 74.74 + - type: recall_at_3 + value: 44.436 + - type: recall_at_5 + value: 48.602000000000004 + - task: + type: Classification + dataset: + type: C-MTEB/IFlyTek-classification + name: MTEB IFlyTek + config: default + split: validation + revision: None + metrics: + - type: accuracy + value: 43.51673720661793 + - type: f1 + value: 35.81126468608715 + - task: + type: Classification + dataset: + type: mteb/imdb + name: MTEB ImdbClassification + config: default + split: test + revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 + metrics: + - type: accuracy + value: 74.446 + - type: ap + value: 68.71359666500074 + - type: f1 + value: 74.32080431056023 + - task: + type: Classification + dataset: + type: C-MTEB/JDReview-classification + name: MTEB JDReview + config: default + split: test + revision: None + metrics: + - type: accuracy + value: 81.08818011257036 + - type: ap + value: 43.68599141287235 + - type: f1 + value: 74.37787266346157 + - task: + type: STS + dataset: + type: C-MTEB/LCQMC + name: MTEB LCQMC + config: default + split: test + revision: None + metrics: + - type: cos_sim_pearson + value: 65.9116523539515 + - type: cos_sim_spearman + value: 72.79966865646485 + - type: euclidean_pearson + value: 71.4995885009818 + - type: euclidean_spearman + value: 72.91799793240196 + - type: manhattan_pearson + value: 71.83065174544116 + - type: manhattan_spearman + value: 73.22568775268935 + - task: + type: Retrieval + dataset: + type: C-MTEB/MMarcoRetrieval + name: MTEB MMarcoRetrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 61.79900000000001 + - type: map_at_10 + value: 70.814 + - type: map_at_100 + value: 71.22500000000001 + - type: map_at_1000 + value: 71.243 + - type: map_at_3 + value: 68.795 + - type: map_at_5 + value: 70.12 + - type: mrr_at_1 + value: 63.910999999999994 + - type: mrr_at_10 + value: 71.437 + - type: mrr_at_100 + value: 71.807 + - type: mrr_at_1000 + value: 71.82300000000001 + - type: mrr_at_3 + value: 69.65599999999999 + - type: mrr_at_5 + value: 70.821 + - type: ndcg_at_1 + value: 63.910999999999994 + - type: ndcg_at_10 + value: 74.664 + - type: ndcg_at_100 + value: 76.545 + - type: ndcg_at_1000 + value: 77.00099999999999 + - type: ndcg_at_3 + value: 70.838 + - type: ndcg_at_5 + value: 73.076 + - type: precision_at_1 + value: 63.910999999999994 + - type: precision_at_10 + value: 9.139999999999999 + - type: precision_at_100 + value: 1.008 + - type: precision_at_1000 + value: 0.105 + - type: precision_at_3 + value: 26.729000000000003 + - type: precision_at_5 + value: 17.232 + - type: recall_at_1 + value: 61.79900000000001 + - type: recall_at_10 + value: 85.941 + - type: recall_at_100 + value: 94.514 + - type: recall_at_1000 + value: 98.04899999999999 + - type: recall_at_3 + value: 75.85499999999999 + - type: recall_at_5 + value: 81.15599999999999 + - task: + type: Retrieval + dataset: + type: msmarco + name: MTEB MSMARCO + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 20.079 + - type: map_at_10 + value: 31.735000000000003 + - type: map_at_100 + value: 32.932 + - type: map_at_1000 + value: 32.987 + - type: map_at_3 + value: 28.216 + - type: map_at_5 + value: 30.127 + - type: mrr_at_1 + value: 20.688000000000002 + - type: mrr_at_10 + value: 32.357 + - type: mrr_at_100 + value: 33.487 + - type: mrr_at_1000 + value: 33.536 + - type: mrr_at_3 + value: 28.887 + - type: mrr_at_5 + value: 30.764000000000003 + - type: ndcg_at_1 + value: 20.688000000000002 + - type: ndcg_at_10 + value: 38.266 + - type: ndcg_at_100 + value: 44.105 + - type: ndcg_at_1000 + value: 45.554 + - type: ndcg_at_3 + value: 31.046000000000003 + - type: ndcg_at_5 + value: 34.44 + - type: precision_at_1 + value: 20.688000000000002 + - type: precision_at_10 + value: 6.0920000000000005 + - type: precision_at_100 + value: 0.903 + - type: precision_at_1000 + value: 0.10300000000000001 + - type: precision_at_3 + value: 13.338 + - type: precision_at_5 + value: 9.725 + - type: recall_at_1 + value: 20.079 + - type: recall_at_10 + value: 58.315 + - type: recall_at_100 + value: 85.50999999999999 + - type: recall_at_1000 + value: 96.72800000000001 + - type: recall_at_3 + value: 38.582 + - type: recall_at_5 + value: 46.705999999999996 + - task: + type: Classification + dataset: + type: mteb/mtop_domain + name: MTEB MTOPDomainClassification (en) + config: en + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 92.18422252621978 + - type: f1 + value: 91.82800582693794 + - task: + type: Classification + dataset: + type: mteb/mtop_domain + name: MTEB MTOPDomainClassification (de) + config: de + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 74.63792617638771 + - type: f1 + value: 73.13966942566492 + - task: + type: Classification + dataset: + type: mteb/mtop_domain + name: MTEB MTOPDomainClassification (es) + config: es + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 92.07138092061375 + - type: f1 + value: 91.58983799467875 + - task: + type: Classification + dataset: + type: mteb/mtop_domain + name: MTEB MTOPDomainClassification (fr) + config: fr + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 89.19824616348262 + - type: f1 + value: 89.06796384273765 + - task: + type: Classification + dataset: + type: mteb/mtop_domain + name: MTEB MTOPDomainClassification (hi) + config: hi + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 88.54069558981713 + - type: f1 + value: 87.83448658971352 + - task: + type: Classification + dataset: + type: mteb/mtop_domain + name: MTEB MTOPDomainClassification (th) + config: th + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 55.63471971066908 + - type: f1 + value: 53.84017845089774 + - task: + type: Classification + dataset: + type: mteb/mtop_intent + name: MTEB MTOPIntentClassification (en) + config: en + split: test + revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba + metrics: + - type: accuracy + value: 70.29867761057912 + - type: f1 + value: 52.76509068762125 + - task: + type: Classification + dataset: + type: mteb/mtop_intent + name: MTEB MTOPIntentClassification (de) + config: de + split: test + revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba + metrics: + - type: accuracy + value: 53.39814032121725 + - type: f1 + value: 34.27161745913036 + - task: + type: Classification + dataset: + type: mteb/mtop_intent + name: MTEB MTOPIntentClassification (es) + config: es + split: test + revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba + metrics: + - type: accuracy + value: 71.33422281521014 + - type: f1 + value: 52.171603212251384 + - task: + type: Classification + dataset: + type: mteb/mtop_intent + name: MTEB MTOPIntentClassification (fr) + config: fr + split: test + revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba + metrics: + - type: accuracy + value: 66.6019417475728 + - type: f1 + value: 49.212091278323975 + - task: + type: Classification + dataset: + type: mteb/mtop_intent + name: MTEB MTOPIntentClassification (hi) + config: hi + split: test + revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba + metrics: + - type: accuracy + value: 66.73001075654356 + - type: f1 + value: 45.97084834271623 + - task: + type: Classification + dataset: + type: mteb/mtop_intent + name: MTEB MTOPIntentClassification (th) + config: th + split: test + revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba + metrics: + - type: accuracy + value: 42.13381555153707 + - type: f1 + value: 27.222558885215964 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (af) + config: af + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 44.97982515131137 + - type: f1 + value: 43.08686679862984 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (am) + config: am + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 25.353059852051107 + - type: f1 + value: 24.56465252790922 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (ar) + config: ar + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 57.078009414929376 + - type: f1 + value: 54.933541125458795 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (az) + config: az + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 39.10558170813719 + - type: f1 + value: 39.15270496151374 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (bn) + config: bn + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 61.368527236045736 + - type: f1 + value: 58.65381984021665 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (cy) + config: cy + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 42.96906523201076 + - type: f1 + value: 41.88085083446726 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (da) + config: da + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 49.54270342972428 + - type: f1 + value: 48.44206747172913 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (de) + config: de + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 50.93140551445864 + - type: f1 + value: 47.40396853548677 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (el) + config: el + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 40.09414929388029 + - type: f1 + value: 38.27158057191927 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (en) + config: en + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 67.93207800941494 + - type: f1 + value: 66.50282035579518 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (es) + config: es + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 63.81304640215198 + - type: f1 + value: 62.51979490279083 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (fa) + config: fa + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 49.05850706119704 + - type: f1 + value: 47.49872899848797 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (fi) + config: fi + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 42.57901815736382 + - type: f1 + value: 40.386069905109956 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (fr) + config: fr + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 65.33960995292534 + - type: f1 + value: 63.96475759829612 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (he) + config: he + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - 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type: accuracy + value: 45.595158036314736 + - type: f1 + value: 44.241686886064755 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (pt) + config: pt + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 70.24209818426363 + - type: f1 + value: 70.48109122752663 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (ro) + config: ro + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 52.73369199731002 + - type: f1 + value: 51.14034087602817 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (ru) + config: ru + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 54.263618022864826 + - type: f1 + value: 53.3188846615122 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (sl) + config: sl + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 46.88634835238735 + - type: f1 + value: 45.257261686960796 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (sq) + config: sq + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 47.15534633490249 + - type: f1 + value: 45.218807618409215 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (sv) + config: sv + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 47.9119031607263 + - type: f1 + value: 45.96730030717468 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (sw) + config: sw + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 51.20040349697377 + - type: f1 + value: 49.113423730259214 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (ta) + config: ta + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 61.8392737054472 + - type: f1 + value: 61.65834459536364 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (te) + config: te + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 59.791526563550775 + - type: f1 + value: 58.2891677685128 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (th) + config: th + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 41.62071284465366 + - type: f1 + value: 39.591525429243575 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (tl) + config: tl + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 50.46738399462004 + - type: f1 + value: 49.50612154409957 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (tr) + config: tr + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 43.41291190316072 + - type: f1 + value: 43.85070302174815 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (ur) + config: ur + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 60.15131136516476 + - type: f1 + value: 59.260012738676316 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (vi) + config: vi + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 68.98789509078682 + - type: f1 + value: 69.86968024553558 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (zh-CN) + config: zh-CN + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 74.72091459314055 + - type: f1 + value: 74.69866015852224 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (zh-TW) + config: zh-TW + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 71.7014122394082 + - type: f1 + value: 72.66856729607628 + - task: + type: Retrieval + dataset: + type: C-MTEB/MedicalRetrieval + name: MTEB MedicalRetrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 35.8 + - type: map_at_10 + value: 40.949999999999996 + - type: map_at_100 + value: 41.455999999999996 + - type: map_at_1000 + value: 41.52 + - type: map_at_3 + value: 40.033 + - type: map_at_5 + value: 40.493 + - type: mrr_at_1 + value: 35.9 + - type: mrr_at_10 + value: 41.0 + - type: mrr_at_100 + value: 41.506 + - type: mrr_at_1000 + value: 41.57 + - type: mrr_at_3 + value: 40.083 + - type: mrr_at_5 + value: 40.543 + - type: ndcg_at_1 + value: 35.8 + - type: ndcg_at_10 + value: 43.269000000000005 + - type: ndcg_at_100 + value: 45.974 + - type: ndcg_at_1000 + value: 47.969 + - type: ndcg_at_3 + value: 41.339999999999996 + - type: ndcg_at_5 + value: 42.167 + - type: precision_at_1 + value: 35.8 + - type: precision_at_10 + value: 5.050000000000001 + - type: precision_at_100 + value: 0.637 + - type: precision_at_1000 + value: 0.08 + - type: precision_at_3 + value: 15.033 + - type: precision_at_5 + value: 9.42 + - type: recall_at_1 + value: 35.8 + - type: recall_at_10 + value: 50.5 + - type: recall_at_100 + value: 63.7 + - type: recall_at_1000 + value: 80.0 + - type: recall_at_3 + value: 45.1 + - type: recall_at_5 + value: 47.099999999999994 + - task: + type: Clustering + dataset: + type: mteb/medrxiv-clustering-p2p + name: MTEB MedrxivClusteringP2P + config: default + split: test + revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 + metrics: + - type: v_measure + value: 29.43291218491871 + - task: + type: Clustering + dataset: + type: mteb/medrxiv-clustering-s2s + name: MTEB MedrxivClusteringS2S + config: default + split: test + revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 + metrics: + - type: v_measure + value: 28.87018200800912 + - task: + type: Reranking + dataset: + type: mteb/mind_small + name: MTEB MindSmallReranking + config: default + split: test + revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 + metrics: + - type: map + value: 30.51003589330728 + - type: mrr + value: 31.57412386045135 + - task: + type: Reranking + dataset: + type: C-MTEB/Mmarco-reranking + name: MTEB MMarcoReranking + config: default + split: dev + revision: None + metrics: + - type: map + value: 26.136250989818222 + - type: mrr + value: 25.00753968253968 + - task: + type: Classification + dataset: + type: C-MTEB/MultilingualSentiment-classification + name: MTEB MultilingualSentiment + config: default + split: validation + revision: None + metrics: + - type: accuracy + value: 66.32999999999998 + - type: f1 + value: 66.2828795526323 + - task: + type: Retrieval + dataset: + type: nfcorpus + name: MTEB NFCorpus + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 4.369 + - type: map_at_10 + value: 11.04 + - type: map_at_100 + value: 13.850000000000001 + - type: map_at_1000 + value: 15.290000000000001 + - type: map_at_3 + value: 8.014000000000001 + - type: map_at_5 + value: 9.4 + - type: mrr_at_1 + value: 39.938 + - type: mrr_at_10 + value: 49.043 + - type: mrr_at_100 + value: 49.775000000000006 + - type: mrr_at_1000 + value: 49.803999999999995 + - type: mrr_at_3 + value: 47.007 + - type: mrr_at_5 + value: 48.137 + - type: ndcg_at_1 + value: 37.461 + - type: ndcg_at_10 + value: 30.703000000000003 + - type: ndcg_at_100 + value: 28.686 + - type: ndcg_at_1000 + value: 37.809 + - type: ndcg_at_3 + value: 35.697 + - type: ndcg_at_5 + value: 33.428000000000004 + - type: precision_at_1 + value: 39.628 + - type: precision_at_10 + value: 23.250999999999998 + - type: precision_at_100 + value: 7.553999999999999 + - type: precision_at_1000 + value: 2.077 + - type: precision_at_3 + value: 34.159 + - type: precision_at_5 + value: 29.164 + - type: recall_at_1 + value: 4.369 + - type: recall_at_10 + value: 15.024000000000001 + - type: recall_at_100 + value: 30.642999999999997 + - type: recall_at_1000 + value: 62.537 + - type: recall_at_3 + value: 9.504999999999999 + - type: recall_at_5 + value: 11.89 + - task: + type: Retrieval + dataset: + type: nq + name: MTEB NQ + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 26.161 + - type: map_at_10 + value: 39.126 + - type: map_at_100 + value: 40.201 + - type: map_at_1000 + value: 40.247 + - type: map_at_3 + value: 35.169 + - type: map_at_5 + value: 37.403 + - type: mrr_at_1 + value: 29.403000000000002 + - type: mrr_at_10 + value: 41.644999999999996 + - type: mrr_at_100 + value: 42.503 + - type: mrr_at_1000 + value: 42.535000000000004 + - type: mrr_at_3 + value: 38.321 + - type: mrr_at_5 + value: 40.265 + - type: ndcg_at_1 + value: 29.403000000000002 + - type: ndcg_at_10 + value: 46.155 + - type: ndcg_at_100 + value: 50.869 + - type: ndcg_at_1000 + value: 52.004 + - type: ndcg_at_3 + value: 38.65 + - type: ndcg_at_5 + value: 42.400999999999996 + - type: precision_at_1 + value: 29.403000000000002 + - type: precision_at_10 + value: 7.743 + - type: precision_at_100 + value: 1.0410000000000001 + - type: precision_at_1000 + value: 0.11499999999999999 + - type: precision_at_3 + value: 17.623 + - type: precision_at_5 + value: 12.764000000000001 + - type: recall_at_1 + value: 26.161 + - type: recall_at_10 + value: 65.155 + - type: recall_at_100 + value: 85.885 + - type: recall_at_1000 + value: 94.443 + - type: recall_at_3 + value: 45.592 + - type: recall_at_5 + value: 54.234 + - task: + type: PairClassification + dataset: + type: C-MTEB/OCNLI + name: MTEB Ocnli + config: default + split: validation + revision: None + metrics: + - type: cos_sim_accuracy + value: 65.34921494315105 + - type: cos_sim_ap + value: 68.58191894316523 + - type: cos_sim_f1 + value: 70.47294418406477 + - type: cos_sim_precision + value: 59.07142857142858 + - type: cos_sim_recall + value: 87.32840549102428 + - type: dot_accuracy + value: 61.93827828911749 + - type: dot_ap + value: 64.19230712895958 + - type: dot_f1 + value: 68.30769230769232 + - type: dot_precision + value: 53.72050816696915 + - type: dot_recall + value: 93.76979936642027 + - type: euclidean_accuracy + value: 67.0817541959935 + - type: euclidean_ap + value: 69.17499163875786 + - type: euclidean_f1 + value: 71.67630057803468 + - type: euclidean_precision + value: 61.904761904761905 + - type: euclidean_recall + value: 85.11087645195353 + - type: manhattan_accuracy + value: 67.19003789929616 + - type: manhattan_ap + value: 69.72684682556992 + - type: manhattan_f1 + value: 71.25396106835673 + - type: manhattan_precision + value: 62.361331220285265 + - type: manhattan_recall + value: 83.10454065469905 + - type: max_accuracy + value: 67.19003789929616 + - type: max_ap + value: 69.72684682556992 + - type: max_f1 + value: 71.67630057803468 + - task: + type: Classification + dataset: + type: C-MTEB/OnlineShopping-classification + name: MTEB OnlineShopping + config: default + split: test + revision: None + metrics: + - type: accuracy + value: 88.35000000000001 + - type: ap + value: 85.45377991151882 + - type: f1 + value: 88.33274122313945 + - task: + type: STS + dataset: + type: C-MTEB/PAWSX + name: MTEB PAWSX + config: default + split: test + revision: None + metrics: + - type: cos_sim_pearson + value: 13.700131726042631 + - type: cos_sim_spearman + value: 15.663851577320184 + - type: euclidean_pearson + value: 17.869909454798112 + - type: euclidean_spearman + value: 16.09518673735175 + - type: manhattan_pearson + value: 18.030818366917593 + - type: manhattan_spearman + value: 16.34096397687474 + - task: + type: STS + dataset: + type: C-MTEB/QBQTC + name: MTEB QBQTC + config: default + split: test + revision: None + metrics: + - type: cos_sim_pearson + value: 30.200343733562946 + - type: cos_sim_spearman + value: 32.645434631834966 + - type: euclidean_pearson + value: 32.612030669583234 + - type: euclidean_spearman + value: 34.67603837485763 + - type: manhattan_pearson + value: 32.6673080122766 + - type: manhattan_spearman + value: 34.8163622783733 + - task: + type: Retrieval + dataset: + type: quora + name: MTEB QuoraRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 69.321 + - type: map_at_10 + value: 83.07 + - type: map_at_100 + value: 83.737 + - type: map_at_1000 + value: 83.758 + - type: map_at_3 + value: 80.12700000000001 + - type: map_at_5 + value: 81.97 + - type: mrr_at_1 + value: 79.74 + - type: mrr_at_10 + value: 86.22 + - type: mrr_at_100 + value: 86.345 + - type: mrr_at_1000 + value: 86.347 + - type: mrr_at_3 + value: 85.172 + - type: mrr_at_5 + value: 85.89099999999999 + - type: ndcg_at_1 + value: 79.77 + - type: ndcg_at_10 + value: 87.01299999999999 + - type: ndcg_at_100 + value: 88.382 + - type: ndcg_at_1000 + value: 88.53 + - type: ndcg_at_3 + value: 84.04 + - type: ndcg_at_5 + value: 85.68 + - type: precision_at_1 + value: 79.77 + - type: precision_at_10 + value: 13.211999999999998 + - type: precision_at_100 + value: 1.52 + - type: precision_at_1000 + value: 0.157 + - type: precision_at_3 + value: 36.730000000000004 + - type: precision_at_5 + value: 24.21 + - type: recall_at_1 + value: 69.321 + - type: recall_at_10 + value: 94.521 + - type: recall_at_100 + value: 99.258 + - type: recall_at_1000 + value: 99.97200000000001 + - type: recall_at_3 + value: 85.97200000000001 + - type: recall_at_5 + value: 90.589 + - task: + type: Clustering + dataset: + type: mteb/reddit-clustering + name: MTEB RedditClustering + config: default + split: test + revision: 24640382cdbf8abc73003fb0fa6d111a705499eb + metrics: + - type: v_measure + value: 44.51751457277441 + - task: + type: Clustering + dataset: + type: mteb/reddit-clustering-p2p + name: MTEB RedditClusteringP2P + config: default + split: test + revision: 282350215ef01743dc01b456c7f5241fa8937f16 + metrics: + - type: v_measure + value: 53.60727449352775 + - task: + type: Retrieval + dataset: + type: scidocs + name: MTEB SCIDOCS + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 4.058 + - type: map_at_10 + value: 9.995999999999999 + - type: map_at_100 + value: 11.738 + - type: map_at_1000 + value: 11.999 + - type: map_at_3 + value: 7.353999999999999 + - type: map_at_5 + value: 8.68 + - type: mrr_at_1 + value: 20.0 + - type: mrr_at_10 + value: 30.244 + - type: mrr_at_100 + value: 31.378 + - type: mrr_at_1000 + value: 31.445 + - type: mrr_at_3 + value: 26.933 + - type: mrr_at_5 + value: 28.748 + - type: ndcg_at_1 + value: 20.0 + - type: ndcg_at_10 + value: 17.235 + - type: ndcg_at_100 + value: 24.241 + - type: ndcg_at_1000 + value: 29.253 + - type: ndcg_at_3 + value: 16.542 + - type: ndcg_at_5 + value: 14.386 + - type: precision_at_1 + value: 20.0 + - type: precision_at_10 + value: 8.9 + - type: precision_at_100 + value: 1.8929999999999998 + - type: precision_at_1000 + value: 0.31 + - type: precision_at_3 + value: 15.567 + - type: precision_at_5 + value: 12.620000000000001 + - type: recall_at_1 + value: 4.058 + - type: recall_at_10 + value: 18.062 + - type: recall_at_100 + value: 38.440000000000005 + - type: recall_at_1000 + value: 63.044999999999995 + - type: recall_at_3 + value: 9.493 + - type: recall_at_5 + value: 12.842 + - task: + type: STS + dataset: + type: mteb/sickr-sts + name: MTEB SICK-R + config: default + split: test + revision: a6ea5a8cab320b040a23452cc28066d9beae2cee + metrics: + - type: cos_sim_pearson + value: 85.36702895231333 + - type: cos_sim_spearman + value: 79.91790376084445 + - type: euclidean_pearson + value: 81.58989754571684 + - type: euclidean_spearman + value: 79.43876559435684 + - type: manhattan_pearson + value: 81.5041355053572 + - type: manhattan_spearman + value: 79.35411927652234 + - task: + type: STS + dataset: + type: mteb/sts12-sts + name: MTEB STS12 + config: default + split: test + revision: a0d554a64d88156834ff5ae9920b964011b16384 + metrics: + - type: cos_sim_pearson + value: 83.77166067512005 + - type: cos_sim_spearman + value: 75.7961015562481 + - type: euclidean_pearson + value: 82.03845114943047 + - type: euclidean_spearman + value: 78.75422268992615 + - type: manhattan_pearson + value: 82.11841609875198 + - type: manhattan_spearman + value: 78.79349601386468 + - task: + type: STS + dataset: + type: mteb/sts13-sts + name: MTEB STS13 + config: default + split: test + revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca + metrics: + - type: cos_sim_pearson + value: 83.28403658061106 + - type: cos_sim_spearman + value: 83.61682237930194 + - type: euclidean_pearson + value: 84.50220149144553 + - type: euclidean_spearman + value: 85.01944483089126 + - type: manhattan_pearson + value: 84.5526583345216 + - type: manhattan_spearman + value: 85.06290695547032 + - task: + type: STS + dataset: + type: mteb/sts14-sts + name: MTEB STS14 + config: default + split: test + revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 + metrics: + - type: cos_sim_pearson + value: 82.66893263127082 + - type: cos_sim_spearman + value: 78.73277873007592 + - type: euclidean_pearson + value: 80.78325001462842 + - type: euclidean_spearman + value: 79.1692321029638 + - type: manhattan_pearson + value: 80.82812137898084 + - type: manhattan_spearman + value: 79.23433932409523 + - task: + type: STS + dataset: + type: mteb/sts15-sts + name: MTEB STS15 + config: default + split: test + revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 + metrics: + - type: cos_sim_pearson + value: 85.6046231732945 + - type: cos_sim_spearman + value: 86.41326579037185 + - type: euclidean_pearson + value: 85.85739124012164 + - type: euclidean_spearman + value: 86.54285701350923 + - type: manhattan_pearson + value: 85.78835254765399 + - type: manhattan_spearman + value: 86.45431641050791 + - task: + type: STS + dataset: + type: mteb/sts16-sts + name: MTEB STS16 + config: default + split: test + revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 + metrics: + - 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type: cos_sim_spearman + value: 79.53464687577328 + - type: euclidean_pearson + value: 79.25913610578554 + - type: euclidean_spearman + value: 79.55288323830753 + - type: manhattan_pearson + value: 79.44759977916512 + - type: manhattan_spearman + value: 79.71927216173198 + - task: + type: STS + dataset: + type: mteb/stsbenchmark-sts + name: MTEB STSBenchmark + config: default + split: test + revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 + metrics: + - type: cos_sim_pearson + value: 85.07398235741444 + - type: cos_sim_spearman + value: 85.78865814488006 + - type: euclidean_pearson + value: 83.2824378418878 + - type: euclidean_spearman + value: 83.36258201307002 + - type: manhattan_pearson + value: 83.22221949643878 + - type: manhattan_spearman + value: 83.27892691688584 + - task: + type: Reranking + dataset: + type: mteb/scidocs-reranking + name: MTEB SciDocsRR + config: default + split: test + revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab + metrics: + - type: map + value: 78.1122816381465 + - type: mrr + value: 93.44523849425809 + - task: + type: Retrieval + dataset: + type: scifact + name: MTEB SciFact + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 51.132999999999996 + - type: map_at_10 + value: 60.672000000000004 + - type: map_at_100 + value: 61.504000000000005 + - type: map_at_1000 + value: 61.526 + - type: map_at_3 + value: 57.536 + - type: map_at_5 + value: 59.362 + - type: mrr_at_1 + value: 53.667 + - type: mrr_at_10 + value: 61.980000000000004 + - type: mrr_at_100 + value: 62.633 + - type: mrr_at_1000 + value: 62.653000000000006 + - type: mrr_at_3 + value: 59.721999999999994 + - type: mrr_at_5 + value: 60.789 + - type: ndcg_at_1 + value: 53.667 + - type: ndcg_at_10 + value: 65.42099999999999 + - type: ndcg_at_100 + value: 68.884 + - type: ndcg_at_1000 + value: 69.494 + - type: ndcg_at_3 + value: 60.007 + - type: ndcg_at_5 + value: 62.487 + - type: precision_at_1 + value: 53.667 + - type: precision_at_10 + value: 8.833 + - type: precision_at_100 + value: 1.0699999999999998 + - type: precision_at_1000 + value: 0.11199999999999999 + - type: precision_at_3 + value: 23.222 + - type: precision_at_5 + value: 15.667 + - type: recall_at_1 + value: 51.132999999999996 + - type: recall_at_10 + value: 78.989 + - type: recall_at_100 + value: 94.167 + - type: recall_at_1000 + value: 99.0 + - type: recall_at_3 + value: 64.328 + - type: recall_at_5 + value: 70.35 + - task: + type: PairClassification + dataset: + type: mteb/sprintduplicatequestions-pairclassification + name: MTEB SprintDuplicateQuestions + config: default + split: test + revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 + metrics: + - type: cos_sim_accuracy + value: 99.78910891089109 + - type: cos_sim_ap + value: 94.58344155979994 + - type: cos_sim_f1 + value: 89.2354124748491 + - type: cos_sim_precision + value: 89.77732793522267 + - type: cos_sim_recall + value: 88.7 + - type: dot_accuracy + value: 99.74158415841585 + - type: dot_ap + value: 92.08599680108772 + - type: dot_f1 + value: 87.00846192135391 + - type: dot_precision + value: 86.62041625371654 + - type: dot_recall + value: 87.4 + - type: euclidean_accuracy + value: 99.78316831683168 + - type: euclidean_ap + value: 94.57715670055748 + - type: euclidean_f1 + value: 88.98765432098766 + - type: euclidean_precision + value: 87.90243902439025 + - type: euclidean_recall + value: 90.10000000000001 + - type: manhattan_accuracy + value: 99.78811881188119 + - type: manhattan_ap + value: 94.73016642953513 + - type: manhattan_f1 + value: 89.3326838772528 + - type: manhattan_precision + value: 87.08452041785375 + - type: manhattan_recall + value: 91.7 + - type: max_accuracy + value: 99.78910891089109 + - type: max_ap + value: 94.73016642953513 + - type: max_f1 + value: 89.3326838772528 + - task: + type: Clustering + dataset: + type: mteb/stackexchange-clustering + name: MTEB StackExchangeClustering + config: default + split: test + revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 + metrics: + - type: v_measure + value: 57.11358892084413 + - task: + type: Clustering + dataset: + type: mteb/stackexchange-clustering-p2p + name: MTEB StackExchangeClusteringP2P + config: default + split: test + revision: 815ca46b2622cec33ccafc3735d572c266efdb44 + metrics: + - type: v_measure + value: 31.914375833951354 + - task: + type: Reranking + dataset: + type: mteb/stackoverflowdupquestions-reranking + name: MTEB StackOverflowDupQuestions + config: default + split: test + revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 + metrics: + - type: map + value: 48.9994487557691 + - type: mrr + value: 49.78547290128173 + - task: + type: Summarization + dataset: + type: mteb/summeval + name: MTEB SummEval + config: default + split: test + revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c + metrics: + - type: cos_sim_pearson + value: 30.19567881069216 + - type: cos_sim_spearman + value: 31.098791519646298 + - type: dot_pearson + value: 30.61141391110544 + - type: dot_spearman + value: 30.995416064312153 + - task: + type: Reranking + dataset: + type: C-MTEB/T2Reranking + name: MTEB T2Reranking + config: default + split: dev + revision: None + metrics: + - type: map + value: 65.9449793956858 + - type: mrr + value: 75.83074738584217 + - task: + type: Retrieval + dataset: + type: C-MTEB/T2Retrieval + name: MTEB T2Retrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 23.186999999999998 + - type: map_at_10 + value: 63.007000000000005 + - type: map_at_100 + value: 66.956 + - type: map_at_1000 + value: 67.087 + - type: map_at_3 + value: 44.769999999999996 + - type: map_at_5 + value: 54.629000000000005 + - type: mrr_at_1 + value: 81.22500000000001 + - type: mrr_at_10 + value: 85.383 + - type: mrr_at_100 + value: 85.555 + - type: mrr_at_1000 + value: 85.564 + - type: mrr_at_3 + value: 84.587 + - type: mrr_at_5 + value: 85.105 + - type: ndcg_at_1 + value: 81.22500000000001 + - type: ndcg_at_10 + value: 72.81 + - type: ndcg_at_100 + value: 78.108 + - type: ndcg_at_1000 + value: 79.477 + - type: ndcg_at_3 + value: 75.36 + - type: ndcg_at_5 + value: 73.19099999999999 + - type: precision_at_1 + value: 81.22500000000001 + - 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type: recall_at_5 + value: 1.18 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (sqi-eng) + config: sqi-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 16.0 + - type: f1 + value: 12.072197229668266 + - type: precision + value: 11.07125213426268 + - type: recall + value: 16.0 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (fry-eng) + config: fry-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 31.79190751445087 + - type: f1 + value: 25.33993944398569 + - type: precision + value: 23.462449892587426 + - type: recall + value: 31.79190751445087 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (kur-eng) + config: kur-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 14.390243902439023 + - 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type: accuracy + value: 9.0 + - type: f1 + value: 6.189958106409719 + - type: precision + value: 5.445330404889228 + - type: recall + value: 9.0 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (khm-eng) + config: khm-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 0.2770083102493075 + - type: f1 + value: 0.011664800298618888 + - type: precision + value: 0.005957856811560036 + - type: recall + value: 0.2770083102493075 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (ces-eng) + config: ces-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 8.799999999999999 + - type: f1 + value: 5.636139438882621 + - type: precision + value: 4.993972914553003 + - type: recall + value: 8.799999999999999 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (tzl-eng) + config: tzl-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 37.5 + - type: f1 + value: 31.31118881118881 + - type: precision + value: 29.439102564102566 + - type: recall + value: 37.5 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (urd-eng) + config: urd-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 74.5 + - type: f1 + value: 68.96380952380953 + - type: precision + value: 66.67968253968255 + - type: recall + value: 74.5 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (ara-eng) + config: ara-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 89.0 + - type: f1 + value: 86.42523809523809 + - type: precision + value: 85.28333333333332 + - type: recall + value: 89.0 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (kor-eng) + config: kor-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 17.2 + - type: f1 + value: 12.555081585081584 + - type: precision + value: 11.292745310245309 + - type: recall + value: 17.2 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (yid-eng) + config: yid-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 0.3537735849056604 + - type: f1 + value: 0.12010530448397783 + - type: precision + value: 0.11902214818132154 + - type: recall + value: 0.3537735849056604 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (fin-eng) + config: fin-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 5.8999999999999995 + - type: f1 + value: 4.26942162679512 + - type: precision + value: 3.967144120536608 + - type: recall + value: 5.8999999999999995 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (tha-eng) + config: tha-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 2.737226277372263 + - type: f1 + value: 1.64474042578532 + - type: precision + value: 1.567547886228932 + - type: recall + value: 2.737226277372263 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (wuu-eng) + config: wuu-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 84.89999999999999 + - type: f1 + value: 81.17555555555555 + - type: precision + value: 79.56416666666667 + - type: recall + value: 84.89999999999999 + - task: + type: Clustering + dataset: + type: C-MTEB/ThuNewsClusteringP2P + name: MTEB ThuNewsClusteringP2P + config: default + split: test + revision: None + metrics: + - type: v_measure + value: 48.90675612551149 + - task: + type: Clustering + dataset: + type: C-MTEB/ThuNewsClusteringS2S + name: MTEB ThuNewsClusteringS2S + config: default + split: test + revision: None + metrics: + - type: v_measure + value: 48.33955538054993 + - task: + type: Retrieval + dataset: + type: webis-touche2020 + name: MTEB Touche2020 + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 2.604 + - type: map_at_10 + value: 10.005 + - type: map_at_100 + value: 15.626999999999999 + - type: map_at_1000 + value: 16.974 + - type: map_at_3 + value: 5.333 + - type: map_at_5 + value: 7.031999999999999 + - type: mrr_at_1 + value: 30.612000000000002 + - type: mrr_at_10 + value: 45.324999999999996 + - type: mrr_at_100 + value: 46.261 + - type: mrr_at_1000 + value: 46.275 + - type: mrr_at_3 + value: 41.156 + - type: mrr_at_5 + value: 43.401 + - type: ndcg_at_1 + value: 28.571 + - type: ndcg_at_10 + value: 24.917 + - type: ndcg_at_100 + value: 35.304 + - type: ndcg_at_1000 + value: 45.973000000000006 + - type: ndcg_at_3 + value: 25.813000000000002 + - type: ndcg_at_5 + value: 24.627 + - type: precision_at_1 + value: 30.612000000000002 + - type: precision_at_10 + value: 23.061 + - type: precision_at_100 + value: 7.327 + - type: precision_at_1000 + value: 1.443 + - type: precision_at_3 + value: 27.211000000000002 + - type: precision_at_5 + value: 24.898 + - type: recall_at_1 + value: 2.604 + - type: recall_at_10 + value: 16.459 + - type: recall_at_100 + value: 45.344 + - type: recall_at_1000 + value: 77.437 + - type: recall_at_3 + value: 6.349 + - type: recall_at_5 + value: 9.487 + - task: + type: Classification + dataset: + type: mteb/toxic_conversations_50k + name: MTEB ToxicConversationsClassification + config: default + split: test + revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c + metrics: + - type: accuracy + value: 72.01180000000001 + - type: ap + value: 14.626345366340157 + - type: f1 + value: 55.341805198526096 + - task: + type: Classification + dataset: + type: mteb/tweet_sentiment_extraction + name: MTEB TweetSentimentExtractionClassification + config: default + split: test + revision: d604517c81ca91fe16a244d1248fc021f9ecee7a + metrics: + - type: accuracy + value: 61.51103565365025 + - type: f1 + value: 61.90767326783032 + - task: + type: Clustering + dataset: + type: mteb/twentynewsgroups-clustering + name: MTEB TwentyNewsgroupsClustering + config: default + split: test + revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 + metrics: + - type: v_measure + value: 39.80161553107969 + - task: + type: PairClassification + dataset: + type: mteb/twittersemeval2015-pairclassification + name: MTEB TwitterSemEval2015 + config: default + split: test + revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 + metrics: + - type: cos_sim_accuracy + value: 84.32377659891517 + - type: cos_sim_ap + value: 69.1354481874608 + - type: cos_sim_f1 + value: 64.52149133222514 + - type: cos_sim_precision + value: 58.65716753022453 + - type: cos_sim_recall + value: 71.68865435356201 + - type: dot_accuracy + value: 82.82172021219527 + - type: dot_ap + value: 64.00853575391538 + - type: dot_f1 + value: 60.32341223341926 + - type: dot_precision + value: 54.25801011804384 + - type: dot_recall + value: 67.9155672823219 + - type: euclidean_accuracy + value: 84.1151576563152 + - type: euclidean_ap + value: 67.83576623331122 + - type: euclidean_f1 + value: 63.15157338457842 + - type: euclidean_precision + value: 57.95855379188713 + - type: euclidean_recall + value: 69.36675461741424 + - type: manhattan_accuracy + value: 84.09727603266377 + - type: manhattan_ap + value: 67.82849173216036 + - type: manhattan_f1 + value: 63.34376956793989 + - type: manhattan_precision + value: 60.28605482717521 + - type: manhattan_recall + value: 66.72823218997361 + - type: max_accuracy + value: 84.32377659891517 + - type: max_ap + value: 69.1354481874608 + - type: max_f1 + value: 64.52149133222514 + - task: + type: PairClassification + dataset: + type: mteb/twitterurlcorpus-pairclassification + name: MTEB TwitterURLCorpus + config: default + split: test + revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf + metrics: + - type: cos_sim_accuracy + value: 88.90053168781775 + - type: cos_sim_ap + value: 85.61513175543742 + - type: cos_sim_f1 + value: 78.12614999632001 + - type: cos_sim_precision + value: 74.82729451571973 + - type: cos_sim_recall + value: 81.72928857406838 + - type: dot_accuracy + value: 88.3086894089339 + - type: dot_ap + value: 83.12888443163673 + - type: dot_f1 + value: 77.2718948023882 + - type: dot_precision + value: 73.69524208761266 + - type: dot_recall + value: 81.21342777948875 + - type: euclidean_accuracy + value: 88.51825978965343 + - type: euclidean_ap + value: 84.99220411819988 + - type: euclidean_f1 + value: 77.30590577305905 + - type: euclidean_precision + value: 74.16183335691045 + - type: euclidean_recall + value: 80.72836464428703 + - type: manhattan_accuracy + value: 88.54542632048744 + - type: manhattan_ap + value: 84.98068073894048 + - type: manhattan_f1 + value: 77.28853696440466 + - type: manhattan_precision + value: 74.39806240205158 + - type: manhattan_recall + value: 80.41268863566368 + - type: max_accuracy + value: 88.90053168781775 + - type: max_ap + value: 85.61513175543742 + - type: max_f1 + value: 78.12614999632001 + - task: + type: Retrieval + dataset: + type: C-MTEB/VideoRetrieval + name: MTEB VideoRetrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 41.8 + - type: map_at_10 + value: 51.413 + - type: map_at_100 + value: 52.127 + - type: map_at_1000 + value: 52.168000000000006 + - type: map_at_3 + value: 49.25 + - type: map_at_5 + value: 50.425 + - type: mrr_at_1 + value: 41.699999999999996 + - type: mrr_at_10 + value: 51.363 + - type: mrr_at_100 + value: 52.077 + - type: mrr_at_1000 + value: 52.117999999999995 + - type: mrr_at_3 + value: 49.2 + - type: mrr_at_5 + value: 50.375 + - type: ndcg_at_1 + value: 41.8 + - type: ndcg_at_10 + value: 56.071000000000005 + - type: ndcg_at_100 + value: 59.58599999999999 + - type: ndcg_at_1000 + value: 60.718 + - type: ndcg_at_3 + value: 51.605999999999995 + - type: ndcg_at_5 + value: 53.714 + - type: precision_at_1 + value: 41.8 + - type: precision_at_10 + value: 7.07 + - type: precision_at_100 + value: 0.873 + - type: precision_at_1000 + value: 0.096 + - type: precision_at_3 + value: 19.467000000000002 + - type: precision_at_5 + value: 12.7 + - type: recall_at_1 + value: 41.8 + - type: recall_at_10 + value: 70.7 + - type: recall_at_100 + value: 87.3 + - type: recall_at_1000 + value: 96.39999999999999 + - type: recall_at_3 + value: 58.4 + - type: recall_at_5 + value: 63.5 + - task: + type: Classification + dataset: + type: C-MTEB/waimai-classification + name: MTEB Waimai + config: default + split: test + revision: None + metrics: + - type: accuracy + value: 82.67 + - type: ap + value: 63.20621490084175 + - type: f1 + value: 80.81778523320692 --- + +# Model Card for udever-bloom + + + +`udever-bloom-1b1` is finetuned from [bigscience/bloom-1b1](https://huggingface.co/bigscience/bloom-1b1) via [BitFit](https://aclanthology.org/2022.acl-short.1/) on MS MARCO Passage Ranking, SNLI and MultiNLI data. +It is a universal embedding model across tasks, natural and programming languages. +(From the technical view, `udever` is merely with some minor improvements to `sgpt-bloom`) + +
+ + +## Model Details + +### Model Description + +- **Developed by:** Alibaba Group +- **Model type:** Transformer-based Language Model (decoder-only) +- **Language(s) (NLP):** Multiple; see [bloom training data](https://huggingface.co/bigscience/bloom-1b1#training-data) +- **Finetuned from model :** [bigscience/bloom-1b1](https://huggingface.co/bigscience/bloom-1b1) + +### Model Sources + + + +- **Repository:** [github.com/izhx/uni-rep](https://github.com/izhx/uni-rep) +- **Paper :** [Language Models are Universal Embedders](https://arxiv.org/pdf/2310.08232.pdf) +- **Training Date :** 2023-06 + + + +## How to Get Started with the Model + +Use the code below to get started with the model. + +```python +import torch +from transformers import AutoTokenizer, BloomModel + +tokenizer = AutoTokenizer.from_pretrained('izhx/udever-bloom-1b1') +model = BloomModel.from_pretrained('izhx/udever-bloom-1b1') + +boq, eoq, bod, eod = '[BOQ]', '[EOQ]', '[BOD]', '[EOD]' +eoq_id, eod_id = tokenizer.convert_tokens_to_ids([eoq, eod]) + +if tokenizer.padding_side != 'left': + print('!!!', tokenizer.padding_side) + tokenizer.padding_side = 'left' + + +def encode(texts: list, is_query: bool = True, max_length=300): + bos = boq if is_query else bod + eos_id = eoq_id if is_query else eod_id + texts = [bos + t for t in texts] + encoding = tokenizer( + texts, truncation=True, max_length=max_length - 1, padding=True + ) + for ids, mask in zip(encoding['input_ids'], encoding['attention_mask']): + ids.append(eos_id) + mask.append(1) + inputs = tokenizer.pad(encoding, return_tensors='pt') + with torch.inference_mode(): + outputs = model(**inputs) + embeds = outputs.last_hidden_state[:, -1] + return embeds + +encode(['I am Bert', 'You are Elmo']) + +``` + +## Training Details + +### Training Data + + + +- MS MARCO Passage Ranking, retrieved by (https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/ms_marco/train_bi-encoder_mnrl.py#L86) +- SNLI and MultiNLI (https://sbert.net/datasets/AllNLI.tsv.gz) + + +### Training Procedure + + + +#### Preprocessing + +MS MARCO hard negatives provided by (https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/ms_marco/train_bi-encoder_mnrl.py#L86). +Negatives for SNLI and MultiNLI are randomly sampled. + + +#### Training Hyperparameters + +- **Training regime:** tf32, BitFit +- **Batch size:** 1024 +- **Epochs:** 3 +- **Optimizer:** AdamW +- **Learning rate:** 1e-4 +- **Scheduler:** constant with warmup. +- **Warmup:** 0.25 epoch + + +## Evaluation + +### Table 1: Massive Text Embedding Benchmark [MTEB](https://huggingface.co/spaces/mteb/leaderboard) + +| MTEB | Avg. | Class. | Clust. | PairClass. | Rerank. | Retr. | STS | Summ. | +|-----------------------------|--------------|--------------|--------------|--------------|--------------|--------------|--------------|--------| +| #Datasets ➡️ | 56 | 12 | 11 | 3 | 4 | 15 | 10 | 1 | +|| +| bge-large-en-v1.5 | **64.23** | **75.97** | 46.08| **87.12** | **60.03** | **54.29** | 83.11| 31.61 | +| bge-base-en-v1.5 | 63.55| 75.53| 45.77| 86.55| 58.86| 53.25| 82.4| 31.07 | +| gte-large | 63.13| 73.33| **46.84** | 85| 59.13| 52.22| **83.35** | 31.66 | +| gte-base | 62.39| 73.01| 46.2| 84.57| 58.61| 51.14| 82.3| 31.17 | +| e5-large-v2 | 62.25| 75.24| 44.49| 86.03| 56.61| 50.56| 82.05| 30.19 | +| instructor-xl | 61.79| 73.12| 44.74| 86.62| 57.29| 49.26| 83.06| 32.32 | +| instructor-large | 61.59| 73.86| 45.29| 85.89| 57.54| 47.57| 83.15| 31.84 | +| e5-base-v2 | 61.5 | 73.84| 43.8| 85.73| 55.91| 50.29| 81.05| 30.28 | +| e5-large | 61.42| 73.14| 43.33| 85.94| 56.53| 49.99| 82.06| 30.97 | +| text-embedding-ada-002 (OpenAI API) | 60.99| 70.93| 45.9 | 84.89| 56.32| 49.25| 80.97| 30.8 | +| e5-base | 60.44| 72.63| 42.11| 85.09| 55.7 | 48.75| 80.96| 31.01 | +| SGPT-5.8B-msmarco | 58.93| 68.13| 40.34| 82 | 56.56| 50.25| 78.1 | 31.46 | +| sgpt-bloom-7b1-msmarco | 57.59| 66.19| 38.93| 81.9 | 55.65| 48.22| 77.74| **33.6** | +|| +| Udever-bloom-560m | 55.80| 68.04| 36.89| 81.05| 52.60| 41.19| 79.93| 32.06 | +| Udever-bloom-1b1 | 58.28| 70.18| 39.11| 83.11| 54.28| 45.27| 81.52| 31.10 | +| Udever-bloom-3b | 59.86| 71.91| 40.74| 84.06| 54.90| 47.67| 82.37| 30.62 | +| Udever-bloom-7b1 | 60.63 | 72.13| 40.81| 85.40| 55.91| 49.34| 83.01| 30.97 | + + +### Table 2: [CodeSearchNet](https://github.com/github/CodeSearchNet) + +| CodeSearchNet | Go | Ruby | Python | Java | JS | PHP | Avg. | +|-|-|-|-|-|-|-|-| +| CodeBERT | 69.3 | 70.6 | 84.0 | 86.8 | 74.8 | 70.6 | 76.0 | +| GraphCodeBERT | 84.1 | 73.2 | 87.9 | 75.7 | 71.1 | 72.5 | 77.4 | +| cpt-code S | **97.7** | **86.3** | 99.8 | 94.0 | 86.0 | 96.7 | 93.4 | +| cpt-code M | 97.5 | 85.5 | **99.9** | **94.4** | **86.5** | **97.2** | **93.5** | +| sgpt-bloom-7b1-msmarco | 76.79 | 69.25 | 95.68 | 77.93 | 70.35 | 73.45 | 77.24 | +|| +| Udever-bloom-560m | 75.38 | 66.67 | 96.23 | 78.99 | 69.39 | 73.69 | 76.73 | +| Udever-bloom-1b1 | 78.76 | 72.85 | 97.67 | 82.77 | 74.38 | 78.97 | 80.90 | +| Udever-bloom-3b | 80.63 | 75.40 | 98.02 | 83.88 | 76.18 | 79.67 | 82.29 | +| Udever-bloom-7b1 | 79.37 | 76.59 | 98.38 | 84.68 | 77.49 | 80.03 | 82.76 | + + +### Table 3: Chinese multi-domain retrieval [Multi-cpr](https://dl.acm.org/doi/10.1145/3477495.3531736) + +| | | |E-commerce | | Entertainment video | | Medical | | +|--|--|--|--|--|--|--|--|--| +| Model | Train | Backbone | MRR@10 | Recall@1k | MRR@10 | Recall@1k | MRR@10 | Recall@1k | +|| +| BM25 | - | - | 0.225 | 0.815 | 0.225 | 0.780 | 0.187 | 0.482 | +| Doc2Query | - | - | 0.239 | 0.826 | 0.238 | 0.794 | 0.210 | 0.505 | +| DPR-1 | In-Domain | BERT | 0.270 | 0.921 | 0.254 | 0.934 | 0.327 | 0.747 | +| DPR-2 | In-Domain | BERT-CT | 0.289 | **0.926** | 0.263 | **0.935** | 0.339 | **0.769** | +| text-embedding-ada-002 | General | GPT | 0.183 | 0.825 | 0.159 | 0.786 | 0.245 | 0.593 | +| sgpt-bloom-7b1-msmarco | General | BLOOM | 0.242 | 0.840 | 0.227 | 0.829 | 0.311 | 0.675 | +|| + | Udever-bloom-560m | General | BLOOM | 0.156 | 0.802 | 0.149 | 0.749 | 0.245 | 0.571 | + | Udever-bloom-1b1 | General | BLOOM | 0.244 | 0.863 | 0.208 | 0.815 | 0.241 | 0.557 | + | Udever-bloom-3b | General | BLOOM | 0.267 | 0.871 | 0.228 | 0.836 | 0.288 | 0.619 | + | Udever-bloom-7b1 | General | BLOOM | **0.296** | 0.889 | **0.267** | 0.907 | **0.343** | 0.705 | + +#### More results refer to [paper](https://arxiv.org/pdf/2310.08232.pdf) section 3. + + + +## Technical Specifications + +### Model Architecture and Objective + +- Model: [bigscience/bloom-1b1](https://huggingface.co/bigscience/bloom-1b1). +- Objective: Constrastive loss with hard negatives (refer to [paper](https://arxiv.org/pdf/2310.08232.pdf) section 2.2). + + +### Compute Infrastructure + +- Nvidia A100 SXM4 80GB. +- torch 2.0.0, transformers 4.29.2. + + +## Citation + +**BibTeX:** + +```BibTeX +@article{zhang2023language, + title={Language Models are Universal Embedders}, + author={Zhang, Xin and Li, Zehan and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan and Zhang, Min}, + journal={arXiv preprint arXiv:2310.08232}, + year={2023} +} +```