diff --git "a/README.md" "b/README.md" new file mode 100644--- /dev/null +++ "b/README.md" @@ -0,0 +1,5428 @@ +--- +base_model: intfloat/multilingual-e5-large-instruct +language: +- multilingual +- af +- am +- ar +- as +- az +- be +- bg +- bn +- br +- bs +- ca +- cs +- cy +- da +- de +- el +- en +- eo +- es +- et +- eu +- fa +- fi +- fr +- fy +- ga +- gd +- gl +- gu +- ha +- he +- hi +- hr +- hu +- hy +- id +- is +- it +- ja +- jv +- ka +- kk +- km +- kn +- ko +- ku +- ky +- la +- lo +- lt +- lv +- mg +- mk +- ml +- mn +- mr +- ms +- my +- ne +- nl +- 'no' +- om +- or +- pa +- pl +- ps +- pt +- ro +- ru +- sa +- sd +- si +- sk +- sl +- so +- sq +- sr +- su +- sv +- sw +- ta +- te +- th +- tl +- tr +- ug +- uk +- ur +- uz +- vi +- xh +- yi +- zh +license: mit +tags: +- mteb +- sentence-transformers +- transformers +- llama-cpp +- gguf-my-repo +model-index: +- name: multilingual-e5-large-instruct + results: + - task: + type: Classification + dataset: + name: MTEB AmazonCounterfactualClassification (en) + type: mteb/amazon_counterfactual + config: en + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 76.23880597014924 + - type: ap + value: 39.07351965022687 + - type: f1 + value: 70.04836733862683 + - task: + type: Classification + dataset: + name: MTEB AmazonCounterfactualClassification (de) + type: mteb/amazon_counterfactual + config: de + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 66.71306209850107 + - type: ap + value: 79.01499914759529 + - type: f1 + value: 64.81951817560703 + - task: + type: Classification + dataset: + name: MTEB AmazonCounterfactualClassification (en-ext) + type: mteb/amazon_counterfactual + config: en-ext + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 73.85307346326837 + - type: ap + value: 22.447519885878737 + - type: f1 + value: 61.0162730745633 + - task: + type: Classification + dataset: + name: MTEB AmazonCounterfactualClassification (ja) + type: mteb/amazon_counterfactual + config: ja + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 76.04925053533191 + - type: ap + value: 23.44983217128922 + - type: f1 + value: 62.5723230907759 + - task: + type: Classification + dataset: + name: MTEB AmazonPolarityClassification + type: mteb/amazon_polarity + config: default + split: test + revision: e2d317d38cd51312af73b3d32a06d1a08b442046 + metrics: + - type: accuracy + value: 96.28742500000001 + - type: ap + value: 94.8449918887462 + - type: f1 + value: 96.28680923610432 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (en) + type: mteb/amazon_reviews_multi + config: en + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 56.716 + - type: f1 + value: 55.76510398266401 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (de) + type: mteb/amazon_reviews_multi + config: de + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 52.99999999999999 + - type: f1 + value: 52.00829994765178 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (es) + type: mteb/amazon_reviews_multi + config: es + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 48.806000000000004 + - type: f1 + value: 48.082345914983634 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (fr) + type: mteb/amazon_reviews_multi + config: fr + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 48.507999999999996 + - type: f1 + value: 47.68752844642045 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (ja) + type: mteb/amazon_reviews_multi + config: ja + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 47.709999999999994 + - type: f1 + value: 47.05870376637181 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (zh) + type: mteb/amazon_reviews_multi + config: zh + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 44.662000000000006 + - type: f1 + value: 43.42371965372771 + - task: + type: Retrieval + dataset: + name: MTEB ArguAna + type: arguana + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 31.721 + - type: map_at_10 + value: 49.221 + - type: map_at_100 + value: 49.884 + - type: map_at_1000 + value: 49.888 + - type: map_at_3 + value: 44.31 + - type: map_at_5 + value: 47.276 + - type: mrr_at_1 + value: 32.432 + - type: mrr_at_10 + value: 49.5 + - type: mrr_at_100 + value: 50.163000000000004 + - type: mrr_at_1000 + value: 50.166 + - type: mrr_at_3 + value: 44.618 + - type: mrr_at_5 + value: 47.541 + - type: ndcg_at_1 + value: 31.721 + - type: ndcg_at_10 + value: 58.384 + - type: ndcg_at_100 + value: 61.111000000000004 + - type: ndcg_at_1000 + value: 61.187999999999995 + - type: ndcg_at_3 + value: 48.386 + - type: ndcg_at_5 + value: 53.708999999999996 + - type: precision_at_1 + value: 31.721 + - type: precision_at_10 + value: 8.741 + - type: precision_at_100 + value: 0.991 + - type: precision_at_1000 + value: 0.1 + - type: precision_at_3 + value: 20.057 + - type: precision_at_5 + value: 14.609 + - type: recall_at_1 + value: 31.721 + - type: recall_at_10 + value: 87.411 + - type: recall_at_100 + value: 99.075 + - type: recall_at_1000 + value: 99.644 + - type: recall_at_3 + value: 60.171 + - type: recall_at_5 + value: 73.044 + - task: + type: Clustering + dataset: + name: MTEB ArxivClusteringP2P + type: mteb/arxiv-clustering-p2p + config: default + split: test + revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d + metrics: + - type: v_measure + value: 46.40419580759799 + - task: + type: Clustering + dataset: + name: MTEB ArxivClusteringS2S + type: mteb/arxiv-clustering-s2s + config: default + split: test + revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 + metrics: + - type: v_measure + value: 40.48593255007969 + - task: + type: Reranking + dataset: + name: MTEB AskUbuntuDupQuestions + type: mteb/askubuntudupquestions-reranking + config: default + split: test + revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 + metrics: + - type: map + value: 63.889179122289995 + - type: mrr + value: 77.61146286769556 + - task: + type: STS + dataset: + name: MTEB BIOSSES + type: mteb/biosses-sts + config: default + split: test + revision: d3fb88f8f02e40887cd149695127462bbcf29b4a + metrics: + - type: cos_sim_pearson + value: 88.15075203727929 + - type: cos_sim_spearman + value: 86.9622224570873 + - type: euclidean_pearson + value: 86.70473853624121 + - type: euclidean_spearman + value: 86.9622224570873 + - type: manhattan_pearson + value: 86.21089380980065 + - type: manhattan_spearman + value: 86.75318154937008 + - task: + type: BitextMining + dataset: + name: MTEB BUCC (de-en) + type: mteb/bucc-bitext-mining + config: de-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 99.65553235908142 + - type: f1 + value: 99.60681976339595 + - type: precision + value: 99.58246346555325 + - type: recall + value: 99.65553235908142 + - task: + type: BitextMining + dataset: + name: MTEB BUCC (fr-en) + type: mteb/bucc-bitext-mining + config: fr-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 99.26260180497468 + - type: f1 + value: 99.14520507740848 + - type: precision + value: 99.08650671362535 + - type: recall + value: 99.26260180497468 + - task: + type: BitextMining + dataset: + name: MTEB BUCC (ru-en) + type: mteb/bucc-bitext-mining + config: ru-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 98.07412538967787 + - type: f1 + value: 97.86629719431936 + - type: precision + value: 97.76238309664012 + - type: recall + value: 98.07412538967787 + - task: + type: BitextMining + dataset: + name: MTEB BUCC (zh-en) + type: mteb/bucc-bitext-mining + config: zh-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 99.42074776197998 + - type: f1 + value: 99.38564156573635 + - type: precision + value: 99.36808846761454 + - type: recall + value: 99.42074776197998 + - task: + type: Classification + dataset: + name: MTEB Banking77Classification + type: mteb/banking77 + config: default + split: test + revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 + metrics: + - type: accuracy + value: 85.73376623376623 + - type: f1 + value: 85.68480707214599 + - task: + type: Clustering + dataset: + name: MTEB BiorxivClusteringP2P + type: mteb/biorxiv-clustering-p2p + config: default + split: test + revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 + metrics: + - type: v_measure + value: 40.935218072113855 + - task: + type: Clustering + dataset: + name: MTEB BiorxivClusteringS2S + type: mteb/biorxiv-clustering-s2s + config: default + split: test + revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 + metrics: + - type: v_measure + value: 36.276389017675264 + - task: + type: Retrieval + dataset: + name: MTEB CQADupstackRetrieval + type: BeIR/cqadupstack + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 27.764166666666668 + - type: map_at_10 + value: 37.298166666666674 + - type: map_at_100 + value: 38.530166666666666 + - type: map_at_1000 + value: 38.64416666666667 + - type: map_at_3 + value: 34.484833333333334 + - type: map_at_5 + value: 36.0385 + - type: mrr_at_1 + value: 32.93558333333333 + - type: mrr_at_10 + value: 41.589749999999995 + - type: mrr_at_100 + value: 42.425333333333334 + - type: mrr_at_1000 + value: 42.476333333333336 + - type: mrr_at_3 + value: 39.26825 + - type: mrr_at_5 + value: 40.567083333333336 + - type: ndcg_at_1 + value: 32.93558333333333 + - type: ndcg_at_10 + value: 42.706583333333334 + - type: ndcg_at_100 + value: 47.82483333333333 + - type: ndcg_at_1000 + value: 49.95733333333334 + - type: ndcg_at_3 + value: 38.064750000000004 + - type: ndcg_at_5 + value: 40.18158333333333 + - type: precision_at_1 + value: 32.93558333333333 + - type: precision_at_10 + value: 7.459833333333334 + - type: precision_at_100 + value: 1.1830833333333335 + - type: precision_at_1000 + value: 0.15608333333333332 + - type: precision_at_3 + value: 17.5235 + - type: precision_at_5 + value: 12.349833333333333 + - type: recall_at_1 + value: 27.764166666666668 + - type: recall_at_10 + value: 54.31775 + - type: recall_at_100 + value: 76.74350000000001 + - type: recall_at_1000 + value: 91.45208333333332 + - type: recall_at_3 + value: 41.23425 + - type: recall_at_5 + value: 46.73983333333334 + - task: + type: Retrieval + dataset: + name: MTEB ClimateFEVER + type: climate-fever + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 12.969 + - type: map_at_10 + value: 21.584999999999997 + - type: map_at_100 + value: 23.3 + - type: map_at_1000 + value: 23.5 + - type: map_at_3 + value: 18.218999999999998 + - type: map_at_5 + value: 19.983 + - type: mrr_at_1 + value: 29.316 + - type: mrr_at_10 + value: 40.033 + - type: mrr_at_100 + value: 40.96 + - type: mrr_at_1000 + value: 41.001 + - type: mrr_at_3 + value: 37.123 + - type: mrr_at_5 + value: 38.757999999999996 + - type: ndcg_at_1 + value: 29.316 + - type: ndcg_at_10 + value: 29.858 + - type: ndcg_at_100 + value: 36.756 + - type: ndcg_at_1000 + value: 40.245999999999995 + - type: ndcg_at_3 + value: 24.822 + - type: ndcg_at_5 + value: 26.565 + - type: precision_at_1 + value: 29.316 + - type: precision_at_10 + value: 9.186 + - type: precision_at_100 + value: 1.6549999999999998 + - type: precision_at_1000 + value: 0.22999999999999998 + - type: precision_at_3 + value: 18.436 + - type: precision_at_5 + value: 13.876 + - type: recall_at_1 + value: 12.969 + - type: recall_at_10 + value: 35.142 + - type: recall_at_100 + value: 59.143 + - type: recall_at_1000 + value: 78.594 + - type: recall_at_3 + value: 22.604 + - type: recall_at_5 + value: 27.883000000000003 + - task: + type: Retrieval + dataset: + name: MTEB DBPedia + type: dbpedia-entity + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 8.527999999999999 + - type: map_at_10 + value: 17.974999999999998 + - type: map_at_100 + value: 25.665 + - type: map_at_1000 + value: 27.406000000000002 + - type: map_at_3 + value: 13.017999999999999 + - type: map_at_5 + value: 15.137 + - type: mrr_at_1 + value: 62.5 + - type: mrr_at_10 + value: 71.891 + - type: mrr_at_100 + value: 72.294 + - type: mrr_at_1000 + value: 72.296 + - type: mrr_at_3 + value: 69.958 + - type: mrr_at_5 + value: 71.121 + - type: ndcg_at_1 + value: 50.875 + - type: ndcg_at_10 + value: 38.36 + - type: ndcg_at_100 + value: 44.235 + - type: ndcg_at_1000 + value: 52.154 + - type: ndcg_at_3 + value: 43.008 + - type: ndcg_at_5 + value: 40.083999999999996 + - type: precision_at_1 + value: 62.5 + - type: precision_at_10 + value: 30.0 + - type: precision_at_100 + value: 10.038 + - type: precision_at_1000 + value: 2.0869999999999997 + - type: precision_at_3 + value: 46.833000000000006 + - type: precision_at_5 + value: 38.800000000000004 + - type: recall_at_1 + value: 8.527999999999999 + - type: recall_at_10 + value: 23.828 + - type: recall_at_100 + value: 52.322 + - type: recall_at_1000 + value: 77.143 + - type: recall_at_3 + value: 14.136000000000001 + - type: recall_at_5 + value: 17.761 + - task: + type: Classification + dataset: + name: MTEB EmotionClassification + type: mteb/emotion + config: default + split: test + revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 + metrics: + - type: accuracy + value: 51.51 + - type: f1 + value: 47.632159862049896 + - task: + type: Retrieval + dataset: + name: MTEB FEVER + type: fever + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 60.734 + - type: map_at_10 + value: 72.442 + - type: map_at_100 + value: 72.735 + - type: map_at_1000 + value: 72.75 + - type: map_at_3 + value: 70.41199999999999 + - type: map_at_5 + value: 71.80499999999999 + - type: mrr_at_1 + value: 65.212 + - type: mrr_at_10 + value: 76.613 + - type: mrr_at_100 + value: 76.79899999999999 + - type: mrr_at_1000 + value: 76.801 + - type: mrr_at_3 + value: 74.8 + - type: mrr_at_5 + value: 76.12400000000001 + - type: ndcg_at_1 + value: 65.212 + - type: ndcg_at_10 + value: 77.988 + - type: ndcg_at_100 + value: 79.167 + - type: ndcg_at_1000 + value: 79.452 + - type: ndcg_at_3 + value: 74.362 + - type: ndcg_at_5 + value: 76.666 + - type: precision_at_1 + value: 65.212 + - type: precision_at_10 + value: 10.003 + - type: precision_at_100 + value: 1.077 + - type: precision_at_1000 + value: 0.11199999999999999 + - type: precision_at_3 + value: 29.518 + - type: precision_at_5 + value: 19.016 + - type: recall_at_1 + value: 60.734 + - type: recall_at_10 + value: 90.824 + - type: recall_at_100 + value: 95.71600000000001 + - type: recall_at_1000 + value: 97.577 + - type: recall_at_3 + value: 81.243 + - type: recall_at_5 + value: 86.90299999999999 + - task: + type: Retrieval + dataset: + name: MTEB FiQA2018 + type: fiqa + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 23.845 + - type: map_at_10 + value: 39.281 + - type: map_at_100 + value: 41.422 + - type: map_at_1000 + value: 41.593 + - type: map_at_3 + value: 34.467 + - type: map_at_5 + value: 37.017 + - type: mrr_at_1 + value: 47.531 + - type: mrr_at_10 + value: 56.204 + - type: mrr_at_100 + value: 56.928999999999995 + - type: mrr_at_1000 + value: 56.962999999999994 + - type: mrr_at_3 + value: 54.115 + - type: mrr_at_5 + value: 55.373000000000005 + - type: ndcg_at_1 + value: 47.531 + - type: ndcg_at_10 + value: 47.711999999999996 + - type: ndcg_at_100 + value: 54.510999999999996 + - type: ndcg_at_1000 + value: 57.103 + - type: ndcg_at_3 + value: 44.145 + - type: ndcg_at_5 + value: 45.032 + - type: precision_at_1 + value: 47.531 + - type: precision_at_10 + value: 13.194 + - type: precision_at_100 + value: 2.045 + - type: precision_at_1000 + value: 0.249 + - type: precision_at_3 + value: 29.424 + - type: precision_at_5 + value: 21.451 + - type: recall_at_1 + value: 23.845 + - type: recall_at_10 + value: 54.967 + - type: recall_at_100 + value: 79.11399999999999 + - type: recall_at_1000 + value: 94.56700000000001 + - type: recall_at_3 + value: 40.256 + - type: recall_at_5 + value: 46.215 + - task: + type: Retrieval + dataset: + name: MTEB HotpotQA + type: hotpotqa + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 37.819 + - type: map_at_10 + value: 60.889 + - type: map_at_100 + value: 61.717999999999996 + - type: map_at_1000 + value: 61.778 + - type: map_at_3 + value: 57.254000000000005 + - type: map_at_5 + value: 59.541 + - type: mrr_at_1 + value: 75.638 + - type: mrr_at_10 + value: 82.173 + - type: mrr_at_100 + value: 82.362 + - type: mrr_at_1000 + value: 82.37 + - type: mrr_at_3 + value: 81.089 + - type: mrr_at_5 + value: 81.827 + - type: ndcg_at_1 + value: 75.638 + - type: ndcg_at_10 + value: 69.317 + - type: ndcg_at_100 + value: 72.221 + - type: ndcg_at_1000 + value: 73.382 + - type: ndcg_at_3 + value: 64.14 + - type: ndcg_at_5 + value: 67.07600000000001 + - type: precision_at_1 + value: 75.638 + - type: precision_at_10 + value: 14.704999999999998 + - type: precision_at_100 + value: 1.698 + - type: precision_at_1000 + value: 0.185 + - type: precision_at_3 + value: 41.394999999999996 + - type: precision_at_5 + value: 27.162999999999997 + - type: recall_at_1 + value: 37.819 + - type: recall_at_10 + value: 73.52499999999999 + - type: recall_at_100 + value: 84.875 + - type: recall_at_1000 + value: 92.559 + - type: recall_at_3 + value: 62.092999999999996 + - type: recall_at_5 + value: 67.907 + - task: + type: Classification + dataset: + name: MTEB ImdbClassification + type: mteb/imdb + config: default + split: test + revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 + metrics: + - type: accuracy + value: 94.60079999999999 + - type: ap + value: 92.67396345347356 + - type: f1 + value: 94.5988098167121 + - task: + type: Retrieval + dataset: + name: MTEB MSMARCO + type: msmarco + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 21.285 + - type: map_at_10 + value: 33.436 + - type: map_at_100 + value: 34.63 + - type: map_at_1000 + value: 34.681 + - type: map_at_3 + value: 29.412 + - type: map_at_5 + value: 31.715 + - type: mrr_at_1 + value: 21.848 + - type: mrr_at_10 + value: 33.979 + - type: mrr_at_100 + value: 35.118 + - type: mrr_at_1000 + value: 35.162 + - type: mrr_at_3 + value: 30.036 + - type: mrr_at_5 + value: 32.298 + - type: ndcg_at_1 + value: 21.862000000000002 + - type: ndcg_at_10 + value: 40.43 + - type: ndcg_at_100 + value: 46.17 + - type: ndcg_at_1000 + value: 47.412 + - type: ndcg_at_3 + value: 32.221 + - type: ndcg_at_5 + value: 36.332 + - type: precision_at_1 + value: 21.862000000000002 + - type: precision_at_10 + value: 6.491 + - type: precision_at_100 + value: 0.935 + - type: precision_at_1000 + value: 0.104 + - type: precision_at_3 + value: 13.744 + - type: precision_at_5 + value: 10.331999999999999 + - type: recall_at_1 + value: 21.285 + - type: recall_at_10 + value: 62.083 + - type: recall_at_100 + value: 88.576 + - type: recall_at_1000 + value: 98.006 + - type: recall_at_3 + value: 39.729 + - type: recall_at_5 + value: 49.608000000000004 + - task: + type: Classification + dataset: + name: MTEB MTOPDomainClassification (en) + type: mteb/mtop_domain + config: en + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 93.92612859097127 + - type: f1 + value: 93.82370333372853 + - task: + type: Classification + dataset: + name: MTEB MTOPDomainClassification (de) + type: mteb/mtop_domain + config: de + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - 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task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (th) + type: mteb/amazon_massive_scenario + config: th + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 75.1815736381977 + - type: f1 + value: 75.08016717887205 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (tl) + type: mteb/amazon_massive_scenario + config: tl + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 72.86482851378614 + - type: f1 + value: 72.39521180006291 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (tr) + type: mteb/amazon_massive_scenario + config: tr + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 76.46940147948891 + - type: f1 + value: 76.70044085362349 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ur) + type: mteb/amazon_massive_scenario + config: ur + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 71.89307330195024 + - type: f1 + value: 71.5721825332298 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (vi) + type: mteb/amazon_massive_scenario + config: vi + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 74.7511768661735 + - type: f1 + value: 75.17918654541515 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (zh-CN) + type: mteb/amazon_massive_scenario + config: zh-CN + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 78.69535978480162 + - type: f1 + value: 78.90019070153316 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (zh-TW) + type: mteb/amazon_massive_scenario + config: zh-TW + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 75.45729657027572 + - type: f1 + value: 76.19578371794672 + - 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type: recall_at_1000 + value: 65.551 + - type: recall_at_3 + value: 10.483 + - type: recall_at_5 + value: 13.078999999999999 + - task: + type: Retrieval + dataset: + name: MTEB NQ + type: nq + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 35.231 + - type: map_at_10 + value: 50.202000000000005 + - type: map_at_100 + value: 51.154999999999994 + - type: map_at_1000 + value: 51.181 + - type: map_at_3 + value: 45.774 + - type: map_at_5 + value: 48.522 + - type: mrr_at_1 + value: 39.687 + - type: mrr_at_10 + value: 52.88 + - type: mrr_at_100 + value: 53.569 + - type: mrr_at_1000 + value: 53.58500000000001 + - type: mrr_at_3 + value: 49.228 + - type: mrr_at_5 + value: 51.525 + - type: ndcg_at_1 + value: 39.687 + - type: ndcg_at_10 + value: 57.754000000000005 + - type: ndcg_at_100 + value: 61.597 + - type: ndcg_at_1000 + value: 62.18900000000001 + - type: ndcg_at_3 + value: 49.55 + - type: ndcg_at_5 + value: 54.11899999999999 + - type: precision_at_1 + value: 39.687 + - type: precision_at_10 + value: 9.313 + - type: precision_at_100 + value: 1.146 + - type: precision_at_1000 + value: 0.12 + - type: precision_at_3 + value: 22.229 + - type: precision_at_5 + value: 15.939 + - type: recall_at_1 + value: 35.231 + - type: recall_at_10 + value: 78.083 + - type: recall_at_100 + value: 94.42099999999999 + - type: recall_at_1000 + value: 98.81 + - type: recall_at_3 + value: 57.047000000000004 + - type: recall_at_5 + value: 67.637 + - task: + type: Retrieval + dataset: + name: MTEB QuoraRetrieval + type: quora + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 71.241 + - type: map_at_10 + value: 85.462 + - type: map_at_100 + value: 86.083 + - type: map_at_1000 + value: 86.09700000000001 + - type: map_at_3 + value: 82.49499999999999 + - type: map_at_5 + value: 84.392 + - type: mrr_at_1 + value: 82.09 + - type: mrr_at_10 + value: 88.301 + - type: mrr_at_100 + value: 88.383 + - type: mrr_at_1000 + value: 88.384 + - type: mrr_at_3 + value: 87.37 + - type: mrr_at_5 + value: 88.035 + - type: ndcg_at_1 + value: 82.12 + - type: ndcg_at_10 + value: 89.149 + - type: ndcg_at_100 + value: 90.235 + - type: ndcg_at_1000 + value: 90.307 + - type: ndcg_at_3 + value: 86.37599999999999 + - type: ndcg_at_5 + value: 87.964 + - type: precision_at_1 + value: 82.12 + - type: precision_at_10 + value: 13.56 + - type: precision_at_100 + value: 1.539 + - type: precision_at_1000 + value: 0.157 + - type: precision_at_3 + value: 37.88 + - type: precision_at_5 + value: 24.92 + - type: recall_at_1 + value: 71.241 + - type: recall_at_10 + value: 96.128 + - type: recall_at_100 + value: 99.696 + - type: recall_at_1000 + value: 99.994 + - type: recall_at_3 + value: 88.181 + - type: recall_at_5 + value: 92.694 + - task: + type: Clustering + dataset: + name: MTEB RedditClustering + type: mteb/reddit-clustering + config: default + split: test + revision: 24640382cdbf8abc73003fb0fa6d111a705499eb + metrics: + - type: v_measure + value: 56.59757799655151 + - task: + type: Clustering + dataset: + name: MTEB RedditClusteringP2P + type: mteb/reddit-clustering-p2p + config: default + split: test + revision: 282350215ef01743dc01b456c7f5241fa8937f16 + metrics: + - type: v_measure + value: 64.27391998854624 + - task: + type: Retrieval + dataset: + name: MTEB SCIDOCS + type: scidocs + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 4.243 + - type: map_at_10 + value: 10.965 + - type: map_at_100 + value: 12.934999999999999 + - type: map_at_1000 + value: 13.256 + - type: map_at_3 + value: 7.907 + - type: map_at_5 + value: 9.435 + - type: mrr_at_1 + value: 20.9 + - type: mrr_at_10 + value: 31.849 + - type: mrr_at_100 + value: 32.964 + - type: mrr_at_1000 + value: 33.024 + - type: mrr_at_3 + value: 28.517 + - type: mrr_at_5 + value: 30.381999999999998 + - type: ndcg_at_1 + value: 20.9 + - type: ndcg_at_10 + value: 18.723 + - type: ndcg_at_100 + value: 26.384999999999998 + - type: ndcg_at_1000 + value: 32.114 + - type: ndcg_at_3 + value: 17.753 + - type: ndcg_at_5 + value: 15.558 + - type: precision_at_1 + value: 20.9 + - type: precision_at_10 + value: 9.8 + - type: precision_at_100 + value: 2.078 + - type: precision_at_1000 + value: 0.345 + - type: precision_at_3 + value: 16.900000000000002 + - type: precision_at_5 + value: 13.88 + - type: recall_at_1 + value: 4.243 + - type: recall_at_10 + value: 19.885 + - type: recall_at_100 + value: 42.17 + - type: recall_at_1000 + value: 70.12 + - type: recall_at_3 + value: 10.288 + - type: recall_at_5 + value: 14.072000000000001 + - task: + type: STS + dataset: + name: MTEB SICK-R + type: mteb/sickr-sts + config: default + split: test + revision: a6ea5a8cab320b040a23452cc28066d9beae2cee + metrics: + - type: cos_sim_pearson + value: 85.84209174935282 + - type: cos_sim_spearman + value: 81.73248048438833 + - type: euclidean_pearson + value: 83.02810070308149 + - type: euclidean_spearman + value: 81.73248295679514 + - type: manhattan_pearson + value: 82.95368060376002 + - type: manhattan_spearman + value: 81.60277910998718 + - task: + type: STS + dataset: + name: MTEB STS12 + type: mteb/sts12-sts + config: default + split: test + revision: a0d554a64d88156834ff5ae9920b964011b16384 + metrics: + - type: cos_sim_pearson + value: 88.52628804556943 + - type: cos_sim_spearman + value: 82.5713913555672 + - type: euclidean_pearson + value: 85.8796774746988 + - type: euclidean_spearman + value: 82.57137506803424 + - type: manhattan_pearson + value: 85.79671002960058 + - type: manhattan_spearman + value: 82.49445981618027 + - task: + type: STS + dataset: + name: MTEB STS13 + type: mteb/sts13-sts + config: default + split: test + revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca + metrics: + - type: cos_sim_pearson + value: 86.23682503505542 + - type: cos_sim_spearman + value: 87.15008956711806 + - type: euclidean_pearson + value: 86.79805401524959 + - type: euclidean_spearman + value: 87.15008956711806 + - type: manhattan_pearson + value: 86.65298502699244 + - type: manhattan_spearman + value: 86.97677821948562 + - task: + type: STS + dataset: + name: MTEB STS14 + type: mteb/sts14-sts + config: default + split: test + revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 + metrics: + - type: cos_sim_pearson + value: 85.63370304677802 + - type: cos_sim_spearman + value: 84.97105553540318 + - type: euclidean_pearson + value: 85.28896108687721 + - type: euclidean_spearman + value: 84.97105553540318 + - type: manhattan_pearson + value: 85.09663190337331 + - type: manhattan_spearman + value: 84.79126831644619 + - task: + type: STS + dataset: + name: MTEB STS15 + type: mteb/sts15-sts + config: default + split: test + revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 + metrics: + - type: cos_sim_pearson + value: 90.2614838800733 + - type: cos_sim_spearman + value: 91.0509162991835 + - type: euclidean_pearson + value: 90.33098317533373 + - type: euclidean_spearman + value: 91.05091625871644 + - type: manhattan_pearson + value: 90.26250435151107 + - type: manhattan_spearman + value: 90.97999594417519 + - task: + type: STS + dataset: + name: MTEB STS16 + type: mteb/sts16-sts + config: default + split: test + revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 + metrics: + - type: cos_sim_pearson + value: 85.80480973335091 + - type: cos_sim_spearman + value: 87.313695492969 + - type: euclidean_pearson + value: 86.49267251576939 + - type: euclidean_spearman + value: 87.313695492969 + - type: manhattan_pearson + value: 86.44019901831935 + - type: manhattan_spearman + value: 87.24205395460392 + - task: + type: STS + dataset: + name: MTEB STS17 (en-en) + type: mteb/sts17-crosslingual-sts + config: en-en + split: test + revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d + metrics: + - type: cos_sim_pearson + value: 90.05662789380672 + - type: cos_sim_spearman + value: 90.02759424426651 + - type: euclidean_pearson + value: 90.4042483422981 + - type: euclidean_spearman + value: 90.02759424426651 + - type: manhattan_pearson + value: 90.51446975000226 + - type: manhattan_spearman + value: 90.08832889933616 + - task: + type: STS + dataset: + name: MTEB STS22 (en) + type: mteb/sts22-crosslingual-sts + config: en + split: test + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + metrics: + - type: cos_sim_pearson + value: 67.5975528273532 + - type: cos_sim_spearman + value: 67.62969861411354 + - type: euclidean_pearson + value: 69.224275734323 + - type: euclidean_spearman + value: 67.62969861411354 + - type: manhattan_pearson + value: 69.3761447059927 + - type: manhattan_spearman + value: 67.90921005611467 + - task: + type: STS + dataset: + name: MTEB STSBenchmark + type: mteb/stsbenchmark-sts + config: default + split: test + revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 + metrics: + - type: cos_sim_pearson + value: 87.11244327231684 + - type: cos_sim_spearman + value: 88.37902438979035 + - type: euclidean_pearson + value: 87.86054279847336 + - type: euclidean_spearman + value: 88.37902438979035 + - type: manhattan_pearson + value: 87.77257757320378 + - type: manhattan_spearman + value: 88.25208966098123 + - task: + type: Reranking + dataset: + name: MTEB SciDocsRR + type: mteb/scidocs-reranking + config: default + split: test + revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab + metrics: + - type: map + value: 85.87174608143563 + - type: mrr + value: 96.12836872640794 + - task: + type: Retrieval + dataset: + name: MTEB SciFact + type: scifact + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 57.760999999999996 + - type: map_at_10 + value: 67.258 + - type: map_at_100 + value: 67.757 + - type: map_at_1000 + value: 67.78800000000001 + - type: map_at_3 + value: 64.602 + - type: map_at_5 + value: 65.64 + - type: mrr_at_1 + value: 60.667 + - type: mrr_at_10 + value: 68.441 + - type: mrr_at_100 + value: 68.825 + - type: mrr_at_1000 + value: 68.853 + - type: mrr_at_3 + value: 66.444 + - type: mrr_at_5 + value: 67.26100000000001 + - type: ndcg_at_1 + value: 60.667 + - type: ndcg_at_10 + value: 71.852 + - type: ndcg_at_100 + value: 73.9 + - type: ndcg_at_1000 + value: 74.628 + - type: ndcg_at_3 + value: 67.093 + - type: ndcg_at_5 + value: 68.58 + - type: precision_at_1 + value: 60.667 + - type: precision_at_10 + value: 9.6 + - type: precision_at_100 + value: 1.0670000000000002 + - type: precision_at_1000 + value: 0.11199999999999999 + - type: precision_at_3 + value: 26.111 + - type: precision_at_5 + value: 16.733 + - type: recall_at_1 + value: 57.760999999999996 + - type: recall_at_10 + value: 84.967 + - type: recall_at_100 + value: 93.833 + - type: recall_at_1000 + value: 99.333 + - type: recall_at_3 + value: 71.589 + - type: recall_at_5 + value: 75.483 + - task: + type: PairClassification + dataset: + name: MTEB SprintDuplicateQuestions + type: mteb/sprintduplicatequestions-pairclassification + config: default + split: test + revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 + metrics: + - type: cos_sim_accuracy + value: 99.66633663366336 + - type: cos_sim_ap + value: 91.17685358899108 + - type: cos_sim_f1 + value: 82.16818642350559 + - type: cos_sim_precision + value: 83.26488706365504 + - type: cos_sim_recall + value: 81.10000000000001 + - type: dot_accuracy + value: 99.66633663366336 + - type: dot_ap + value: 91.17663411119032 + - type: dot_f1 + value: 82.16818642350559 + - type: dot_precision + value: 83.26488706365504 + - type: dot_recall + value: 81.10000000000001 + - type: euclidean_accuracy + value: 99.66633663366336 + - type: euclidean_ap + value: 91.17685189882275 + - type: euclidean_f1 + value: 82.16818642350559 + - type: euclidean_precision + value: 83.26488706365504 + - type: euclidean_recall + value: 81.10000000000001 + - type: manhattan_accuracy + value: 99.66633663366336 + - type: manhattan_ap + value: 91.2241619496737 + - type: manhattan_f1 + value: 82.20472440944883 + - type: manhattan_precision + value: 86.51933701657458 + - type: manhattan_recall + value: 78.3 + - type: max_accuracy + value: 99.66633663366336 + - type: max_ap + value: 91.2241619496737 + - type: max_f1 + value: 82.20472440944883 + - task: + type: Clustering + dataset: + name: MTEB StackExchangeClustering + type: mteb/stackexchange-clustering + config: default + split: test + revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 + metrics: + - type: v_measure + value: 66.85101268897951 + - task: + type: Clustering + dataset: + name: MTEB StackExchangeClusteringP2P + type: mteb/stackexchange-clustering-p2p + config: default + split: test + revision: 815ca46b2622cec33ccafc3735d572c266efdb44 + metrics: + - type: v_measure + value: 42.461184054706905 + - task: + type: Reranking + dataset: + name: MTEB StackOverflowDupQuestions + type: mteb/stackoverflowdupquestions-reranking + config: default + split: test + revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 + metrics: + - type: map + value: 51.44542568873886 + - type: mrr + value: 52.33656151854681 + - task: + type: Summarization + dataset: + name: MTEB SummEval + type: mteb/summeval + config: default + split: test + revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c + metrics: + - type: cos_sim_pearson + value: 30.75982974997539 + - type: cos_sim_spearman + value: 30.385405026539914 + - type: dot_pearson + value: 30.75982433546523 + - type: dot_spearman + value: 30.385405026539914 + - task: + type: Retrieval + dataset: + name: MTEB TRECCOVID + type: trec-covid + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 0.22799999999999998 + - type: map_at_10 + value: 2.064 + - type: map_at_100 + value: 13.056000000000001 + - type: map_at_1000 + value: 31.747999999999998 + - type: map_at_3 + value: 0.67 + - type: map_at_5 + value: 1.097 + - type: mrr_at_1 + value: 90.0 + - type: mrr_at_10 + value: 94.667 + - type: mrr_at_100 + value: 94.667 + - type: mrr_at_1000 + value: 94.667 + - type: mrr_at_3 + value: 94.667 + - type: mrr_at_5 + value: 94.667 + - type: ndcg_at_1 + value: 86.0 + - type: ndcg_at_10 + value: 82.0 + - type: ndcg_at_100 + value: 64.307 + - type: ndcg_at_1000 + value: 57.023999999999994 + - type: ndcg_at_3 + value: 85.816 + - type: ndcg_at_5 + value: 84.904 + - type: precision_at_1 + value: 90.0 + - type: precision_at_10 + value: 85.8 + - type: precision_at_100 + value: 66.46 + - type: precision_at_1000 + value: 25.202 + - type: precision_at_3 + value: 90.0 + - type: precision_at_5 + value: 89.2 + - type: recall_at_1 + value: 0.22799999999999998 + - type: recall_at_10 + value: 2.235 + - type: recall_at_100 + value: 16.185 + - type: recall_at_1000 + value: 53.620999999999995 + - type: recall_at_3 + value: 0.7040000000000001 + - type: recall_at_5 + value: 1.172 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (sqi-eng) + type: mteb/tatoeba-bitext-mining + config: sqi-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 97.39999999999999 + - type: f1 + value: 96.75 + - type: precision + value: 96.45 + - type: recall + value: 97.39999999999999 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (fry-eng) + type: mteb/tatoeba-bitext-mining + config: fry-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 85.54913294797689 + - type: f1 + value: 82.46628131021194 + - type: precision + value: 81.1175337186898 + - type: recall + value: 85.54913294797689 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (kur-eng) + type: mteb/tatoeba-bitext-mining + config: kur-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 81.21951219512195 + - type: f1 + value: 77.33333333333334 + - type: precision + value: 75.54878048780488 + - type: recall + value: 81.21951219512195 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (tur-eng) + type: mteb/tatoeba-bitext-mining + config: tur-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 98.6 + - type: f1 + value: 98.26666666666665 + - type: precision + value: 98.1 + - type: recall + value: 98.6 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (deu-eng) + type: mteb/tatoeba-bitext-mining + config: deu-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 99.5 + - type: f1 + value: 99.33333333333333 + - type: precision + value: 99.25 + - type: recall + value: 99.5 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (nld-eng) + type: mteb/tatoeba-bitext-mining + config: nld-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 97.8 + - type: f1 + value: 97.2 + - type: precision + value: 96.89999999999999 + - type: recall + value: 97.8 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (ron-eng) + type: mteb/tatoeba-bitext-mining + config: ron-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 97.8 + - type: f1 + value: 97.18333333333334 + - type: precision + value: 96.88333333333333 + - type: recall + value: 97.8 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (ang-eng) + type: mteb/tatoeba-bitext-mining + config: ang-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 77.61194029850746 + - type: f1 + value: 72.81094527363183 + - type: precision + value: 70.83333333333333 + - type: recall + value: 77.61194029850746 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (ido-eng) + type: mteb/tatoeba-bitext-mining + config: ido-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 93.7 + - type: f1 + value: 91.91666666666667 + - type: precision + value: 91.08333333333334 + - type: recall + value: 93.7 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (jav-eng) + type: mteb/tatoeba-bitext-mining + config: jav-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 88.29268292682927 + - type: f1 + value: 85.27642276422765 + - type: precision + value: 84.01277584204414 + - type: recall + value: 88.29268292682927 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (isl-eng) + type: mteb/tatoeba-bitext-mining + config: isl-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 96.1 + - type: f1 + value: 95.0 + - type: precision + value: 94.46666666666668 + - type: recall + value: 96.1 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (slv-eng) + type: mteb/tatoeba-bitext-mining + config: slv-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - 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type: mrr_at_100 + value: 56.82000000000001 + - type: mrr_at_1000 + value: 56.82000000000001 + - type: mrr_at_3 + value: 52.381 + - type: mrr_at_5 + value: 53.81 + - type: ndcg_at_1 + value: 42.857 + - type: ndcg_at_10 + value: 27.249000000000002 + - type: ndcg_at_100 + value: 36.529 + - type: ndcg_at_1000 + value: 48.136 + - type: ndcg_at_3 + value: 33.938 + - type: ndcg_at_5 + value: 29.951 + - type: precision_at_1 + value: 44.897999999999996 + - type: precision_at_10 + value: 22.653000000000002 + - type: precision_at_100 + value: 7.000000000000001 + - type: precision_at_1000 + value: 1.48 + - type: precision_at_3 + value: 32.653 + - type: precision_at_5 + value: 27.755000000000003 + - type: recall_at_1 + value: 3.2910000000000004 + - type: recall_at_10 + value: 16.16 + - type: recall_at_100 + value: 43.908 + - type: recall_at_1000 + value: 79.823 + - type: recall_at_3 + value: 7.156 + - type: recall_at_5 + value: 10.204 + - task: + type: Classification + dataset: + name: MTEB ToxicConversationsClassification + type: mteb/toxic_conversations_50k + config: default + split: test + revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c + metrics: + - type: accuracy + value: 71.05879999999999 + - type: ap + value: 14.609748142799111 + - type: f1 + value: 54.878956295843096 + - task: + type: Classification + dataset: + name: MTEB TweetSentimentExtractionClassification + type: mteb/tweet_sentiment_extraction + config: default + split: test + revision: d604517c81ca91fe16a244d1248fc021f9ecee7a + metrics: + - type: accuracy + value: 64.61799660441426 + - type: f1 + value: 64.8698191961434 + - task: + type: Clustering + dataset: + name: MTEB TwentyNewsgroupsClustering + type: mteb/twentynewsgroups-clustering + config: default + split: test + revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 + metrics: + - type: v_measure + value: 51.32860036611885 + - task: + type: PairClassification + dataset: + name: MTEB TwitterSemEval2015 + type: mteb/twittersemeval2015-pairclassification + config: default + split: test + revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 + metrics: + - type: cos_sim_accuracy + value: 88.34714192048638 + - type: cos_sim_ap + value: 80.26732975975634 + - type: cos_sim_f1 + value: 73.53415148134374 + - type: cos_sim_precision + value: 69.34767360299276 + - type: cos_sim_recall + value: 78.25857519788919 + - type: dot_accuracy + value: 88.34714192048638 + - type: dot_ap + value: 80.26733698491206 + - type: dot_f1 + value: 73.53415148134374 + - type: dot_precision + value: 69.34767360299276 + - type: dot_recall + value: 78.25857519788919 + - type: euclidean_accuracy + value: 88.34714192048638 + - type: euclidean_ap + value: 80.26734337771738 + - type: euclidean_f1 + value: 73.53415148134374 + - type: euclidean_precision + value: 69.34767360299276 + - type: euclidean_recall + value: 78.25857519788919 + - type: manhattan_accuracy + value: 88.30541813196639 + - type: manhattan_ap + value: 80.19415808104145 + - type: manhattan_f1 + value: 73.55143870713441 + - type: manhattan_precision + value: 73.25307511122743 + - type: manhattan_recall + value: 73.85224274406332 + - type: max_accuracy + value: 88.34714192048638 + - type: max_ap + value: 80.26734337771738 + - type: max_f1 + value: 73.55143870713441 + - task: + type: PairClassification + dataset: + name: MTEB TwitterURLCorpus + type: mteb/twitterurlcorpus-pairclassification + config: default + split: test + revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf + metrics: + - type: cos_sim_accuracy + value: 89.81061047075717 + - type: cos_sim_ap + value: 87.11747055081017 + - type: cos_sim_f1 + value: 80.04355498817256 + - type: cos_sim_precision + value: 78.1165262000733 + - type: cos_sim_recall + value: 82.06806282722513 + - type: dot_accuracy + value: 89.81061047075717 + - type: dot_ap + value: 87.11746902745236 + - type: dot_f1 + value: 80.04355498817256 + - type: dot_precision + value: 78.1165262000733 + - type: dot_recall + value: 82.06806282722513 + - type: euclidean_accuracy + value: 89.81061047075717 + - type: euclidean_ap + value: 87.11746919324248 + - type: euclidean_f1 + value: 80.04355498817256 + - type: euclidean_precision + value: 78.1165262000733 + - type: euclidean_recall + value: 82.06806282722513 + - type: manhattan_accuracy + value: 89.79508673885202 + - type: manhattan_ap + value: 87.11074390832218 + - type: manhattan_f1 + value: 80.13002540726349 + - type: manhattan_precision + value: 77.83826945412311 + - type: manhattan_recall + value: 82.56082537727133 + - type: max_accuracy + value: 89.81061047075717 + - type: max_ap + value: 87.11747055081017 + - type: max_f1 + value: 80.13002540726349 +--- + +# KeyurRamoliya/multilingual-e5-large-instruct-Q8_0-GGUF +This model was converted to GGUF format from [`intfloat/multilingual-e5-large-instruct`](https://huggingface.co/intfloat/multilingual-e5-large-instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. +Refer to the [original model card](https://huggingface.co/intfloat/multilingual-e5-large-instruct) for more details on the model. + +## Use with llama.cpp +Install llama.cpp through brew (works on Mac and Linux) + +```bash +brew install llama.cpp + +``` +Invoke the llama.cpp server or the CLI. + +### CLI: +```bash +llama-cli --hf-repo KeyurRamoliya/multilingual-e5-large-instruct-Q8_0-GGUF --hf-file multilingual-e5-large-instruct-q8_0.gguf -p "The meaning to life and the universe is" +``` + +### Server: +```bash +llama-server --hf-repo KeyurRamoliya/multilingual-e5-large-instruct-Q8_0-GGUF --hf-file multilingual-e5-large-instruct-q8_0.gguf -c 2048 +``` + +Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. + +Step 1: Clone llama.cpp from GitHub. +``` +git clone https://github.com/ggerganov/llama.cpp +``` + +Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). +``` +cd llama.cpp && LLAMA_CURL=1 make +``` + +Step 3: Run inference through the main binary. +``` +./llama-cli --hf-repo KeyurRamoliya/multilingual-e5-large-instruct-Q8_0-GGUF --hf-file multilingual-e5-large-instruct-q8_0.gguf -p "The meaning to life and the universe is" +``` +or +``` +./llama-server --hf-repo KeyurRamoliya/multilingual-e5-large-instruct-Q8_0-GGUF --hf-file multilingual-e5-large-instruct-q8_0.gguf -c 2048 +```