diff --git "a/README.md" "b/README.md" new file mode 100644--- /dev/null +++ "b/README.md" @@ -0,0 +1,5997 @@ +--- +tags: +- mteb +- Sentence Transformers +- sentence-similarity +- feature-extraction +- sentence-transformers +- llama-cpp +- gguf-my-repo +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 +base_model: intfloat/multilingual-e5-large +model-index: +- name: multilingual-e5-large + results: + - task: + type: Classification + dataset: + name: MTEB AmazonCounterfactualClassification (en) + type: mteb/amazon_counterfactual + config: en + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 79.05970149253731 + - type: ap + value: 43.486574390835635 + - type: f1 + value: 73.32700092140148 + - task: + type: Classification + dataset: + name: MTEB AmazonCounterfactualClassification (de) + type: mteb/amazon_counterfactual + config: de + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 71.22055674518201 + - type: ap + value: 81.55756710830498 + - type: f1 + value: 69.28271787752661 + - task: + type: Classification + dataset: + name: MTEB AmazonCounterfactualClassification (en-ext) + type: mteb/amazon_counterfactual + config: en-ext + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 80.41979010494754 + - type: ap + value: 29.34879922376344 + - type: f1 + value: 67.62475449011278 + - task: + type: Classification + dataset: + name: MTEB AmazonCounterfactualClassification (ja) + type: mteb/amazon_counterfactual + config: ja + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 77.8372591006424 + - type: ap + value: 26.557560591210738 + - type: f1 + value: 64.96619417368707 + - task: + type: Classification + dataset: + name: MTEB AmazonPolarityClassification + type: mteb/amazon_polarity + config: default + split: test + revision: e2d317d38cd51312af73b3d32a06d1a08b442046 + metrics: + - type: accuracy + value: 93.489875 + - type: ap + value: 90.98758636917603 + - type: f1 + value: 93.48554819717332 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (en) + type: mteb/amazon_reviews_multi + config: en + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 47.564 + - type: f1 + value: 46.75122173518047 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (de) + type: mteb/amazon_reviews_multi + config: de + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 45.400000000000006 + - type: f1 + value: 44.17195682400632 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (es) + type: mteb/amazon_reviews_multi + config: es + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 43.068 + - type: f1 + value: 42.38155696855596 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (fr) + type: mteb/amazon_reviews_multi + config: fr + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 41.89 + - type: f1 + value: 40.84407321682663 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (ja) + type: mteb/amazon_reviews_multi + config: ja + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 40.120000000000005 + - type: f1 + value: 39.522976223819114 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (zh) + type: mteb/amazon_reviews_multi + config: zh + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 38.832 + - type: f1 + value: 38.0392533394713 + - task: + type: Retrieval + dataset: + name: MTEB ArguAna + type: arguana + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 30.725 + - type: map_at_10 + value: 46.055 + - type: map_at_100 + value: 46.900999999999996 + - type: map_at_1000 + value: 46.911 + - type: map_at_3 + value: 41.548 + - type: map_at_5 + value: 44.297 + - type: mrr_at_1 + value: 31.152 + - type: mrr_at_10 + value: 46.231 + - type: mrr_at_100 + value: 47.07 + - type: mrr_at_1000 + value: 47.08 + - type: mrr_at_3 + value: 41.738 + - type: mrr_at_5 + value: 44.468999999999994 + - type: ndcg_at_1 + value: 30.725 + - type: ndcg_at_10 + value: 54.379999999999995 + - type: ndcg_at_100 + value: 58.138 + - type: ndcg_at_1000 + value: 58.389 + - type: ndcg_at_3 + value: 45.156 + - type: ndcg_at_5 + value: 50.123 + - type: precision_at_1 + value: 30.725 + - type: precision_at_10 + value: 8.087 + - type: precision_at_100 + value: 0.9769999999999999 + - type: precision_at_1000 + value: 0.1 + - type: precision_at_3 + value: 18.54 + - type: precision_at_5 + value: 13.542000000000002 + - type: recall_at_1 + value: 30.725 + - type: recall_at_10 + value: 80.868 + - type: recall_at_100 + value: 97.653 + - type: recall_at_1000 + value: 99.57300000000001 + - type: recall_at_3 + value: 55.619 + - type: recall_at_5 + value: 67.71000000000001 + - task: + type: Clustering + dataset: + name: MTEB ArxivClusteringP2P + type: mteb/arxiv-clustering-p2p + config: default + split: test + revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d + metrics: + - type: v_measure + value: 44.30960650674069 + - task: + type: Clustering + dataset: + name: MTEB ArxivClusteringS2S + type: mteb/arxiv-clustering-s2s + config: default + split: test + revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 + metrics: + - type: v_measure + value: 38.427074197498996 + - task: + type: Reranking + dataset: + name: MTEB AskUbuntuDupQuestions + type: mteb/askubuntudupquestions-reranking + config: default + split: test + revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 + metrics: + - type: map + value: 60.28270056031872 + - type: mrr + value: 74.38332673789738 + - task: + type: STS + dataset: + name: MTEB BIOSSES + type: mteb/biosses-sts + config: default + split: test + revision: d3fb88f8f02e40887cd149695127462bbcf29b4a + metrics: + - type: cos_sim_pearson + value: 84.05942144105269 + - type: cos_sim_spearman + value: 82.51212105850809 + - type: euclidean_pearson + value: 81.95639829909122 + - type: euclidean_spearman + value: 82.3717564144213 + - type: manhattan_pearson + value: 81.79273425468256 + - type: manhattan_spearman + value: 82.20066817871039 + - 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: 99.46764091858039 + - type: f1 + value: 99.37717466945023 + - type: precision + value: 99.33194154488518 + - type: recall + value: 99.46764091858039 + - 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: 98.29407880255337 + - type: f1 + value: 98.11248073959938 + - type: precision + value: 98.02443319392472 + - type: recall + value: 98.29407880255337 + - 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: 97.79009352268791 + - type: f1 + value: 97.5176076665512 + - type: precision + value: 97.38136473848286 + - type: recall + value: 97.79009352268791 + - 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: 99.26276987888363 + - type: f1 + value: 99.20133403545726 + - type: precision + value: 99.17500438827453 + - type: recall + value: 99.26276987888363 + - task: + type: Classification + dataset: + name: MTEB Banking77Classification + type: mteb/banking77 + config: default + split: test + revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 + metrics: + - type: accuracy + value: 84.72727272727273 + - type: f1 + value: 84.67672206031433 + - task: + type: Clustering + dataset: + name: MTEB BiorxivClusteringP2P + type: mteb/biorxiv-clustering-p2p + config: default + split: test + revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 + metrics: + - type: v_measure + value: 35.34220182511161 + - task: + type: Clustering + dataset: + name: MTEB BiorxivClusteringS2S + type: mteb/biorxiv-clustering-s2s + config: default + split: test + revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 + metrics: + - type: v_measure + value: 33.4987096128766 + - task: + type: Retrieval + dataset: + name: MTEB CQADupstackRetrieval + type: BeIR/cqadupstack + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 25.558249999999997 + - type: map_at_10 + value: 34.44425000000001 + - type: map_at_100 + value: 35.59833333333333 + - type: map_at_1000 + value: 35.706916666666665 + - type: map_at_3 + value: 31.691749999999995 + - type: map_at_5 + value: 33.252916666666664 + - type: mrr_at_1 + value: 30.252666666666666 + - type: mrr_at_10 + value: 38.60675 + - type: mrr_at_100 + value: 39.42666666666666 + - type: mrr_at_1000 + value: 39.48408333333334 + - type: mrr_at_3 + value: 36.17441666666665 + - type: mrr_at_5 + value: 37.56275 + - type: ndcg_at_1 + value: 30.252666666666666 + - type: ndcg_at_10 + value: 39.683 + - type: ndcg_at_100 + value: 44.68541666666667 + - type: ndcg_at_1000 + value: 46.94316666666668 + - type: ndcg_at_3 + value: 34.961749999999995 + - type: ndcg_at_5 + value: 37.215666666666664 + - type: precision_at_1 + value: 30.252666666666666 + - type: precision_at_10 + value: 6.904166666666667 + - type: precision_at_100 + value: 1.0989999999999995 + - type: precision_at_1000 + value: 0.14733333333333334 + - type: precision_at_3 + value: 16.037666666666667 + - type: precision_at_5 + value: 11.413583333333333 + - type: recall_at_1 + value: 25.558249999999997 + - type: recall_at_10 + value: 51.13341666666666 + - type: recall_at_100 + value: 73.08366666666667 + - type: recall_at_1000 + value: 88.79483333333334 + - type: recall_at_3 + value: 37.989083333333326 + - type: recall_at_5 + value: 43.787833333333325 + - task: + type: Retrieval + dataset: + name: MTEB ClimateFEVER + type: climate-fever + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 10.338 + - type: map_at_10 + value: 18.360000000000003 + - type: map_at_100 + value: 19.942 + - type: map_at_1000 + value: 20.134 + - type: map_at_3 + value: 15.174000000000001 + - type: map_at_5 + value: 16.830000000000002 + - type: mrr_at_1 + value: 23.257 + - type: mrr_at_10 + value: 33.768 + - type: mrr_at_100 + value: 34.707 + - type: mrr_at_1000 + value: 34.766000000000005 + - type: mrr_at_3 + value: 30.977 + - type: mrr_at_5 + value: 32.528 + - type: ndcg_at_1 + value: 23.257 + - type: ndcg_at_10 + value: 25.733 + - type: ndcg_at_100 + value: 32.288 + - type: ndcg_at_1000 + value: 35.992000000000004 + - type: ndcg_at_3 + value: 20.866 + - type: ndcg_at_5 + value: 22.612 + - type: precision_at_1 + value: 23.257 + - type: precision_at_10 + value: 8.124 + - type: precision_at_100 + value: 1.518 + - type: precision_at_1000 + value: 0.219 + - type: precision_at_3 + value: 15.679000000000002 + - type: precision_at_5 + value: 12.117 + - type: recall_at_1 + value: 10.338 + - type: recall_at_10 + value: 31.154 + - type: recall_at_100 + value: 54.161 + - type: recall_at_1000 + value: 75.21900000000001 + - type: recall_at_3 + value: 19.427 + - type: recall_at_5 + value: 24.214 + - task: + type: Retrieval + dataset: + name: MTEB DBPedia + type: dbpedia-entity + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 8.498 + - type: map_at_10 + value: 19.103 + - type: map_at_100 + value: 27.375 + - type: map_at_1000 + value: 28.981 + - type: map_at_3 + value: 13.764999999999999 + - type: map_at_5 + value: 15.950000000000001 + - type: mrr_at_1 + value: 65.5 + - type: mrr_at_10 + value: 74.53800000000001 + - type: mrr_at_100 + value: 74.71799999999999 + - type: mrr_at_1000 + value: 74.725 + - type: mrr_at_3 + value: 72.792 + - type: mrr_at_5 + value: 73.554 + - type: ndcg_at_1 + value: 53.37499999999999 + - type: ndcg_at_10 + value: 41.286 + - type: ndcg_at_100 + value: 45.972 + - type: ndcg_at_1000 + value: 53.123 + - type: ndcg_at_3 + value: 46.172999999999995 + - type: ndcg_at_5 + value: 43.033 + - type: precision_at_1 + value: 65.5 + - type: precision_at_10 + value: 32.725 + - type: precision_at_100 + value: 10.683 + - type: precision_at_1000 + value: 1.978 + - type: precision_at_3 + value: 50 + - type: precision_at_5 + value: 41.349999999999994 + - type: recall_at_1 + value: 8.498 + - type: recall_at_10 + value: 25.070999999999998 + - type: recall_at_100 + value: 52.383 + - type: recall_at_1000 + value: 74.91499999999999 + - type: recall_at_3 + value: 15.207999999999998 + - type: recall_at_5 + value: 18.563 + - task: + type: Classification + dataset: + name: MTEB EmotionClassification + type: mteb/emotion + config: default + split: test + revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 + metrics: + - type: accuracy + value: 46.5 + - type: f1 + value: 41.93833713984145 + - task: + type: Retrieval + dataset: + name: MTEB FEVER + type: fever + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 67.914 + - type: map_at_10 + value: 78.10000000000001 + - type: map_at_100 + value: 78.333 + - type: map_at_1000 + value: 78.346 + - type: map_at_3 + value: 76.626 + - type: map_at_5 + value: 77.627 + - type: mrr_at_1 + value: 72.74199999999999 + - type: mrr_at_10 + value: 82.414 + - type: mrr_at_100 + value: 82.511 + - type: mrr_at_1000 + value: 82.513 + - type: mrr_at_3 + value: 81.231 + - type: mrr_at_5 + value: 82.065 + - type: ndcg_at_1 + value: 72.74199999999999 + - type: ndcg_at_10 + value: 82.806 + - type: ndcg_at_100 + value: 83.677 + - type: ndcg_at_1000 + value: 83.917 + - type: ndcg_at_3 + value: 80.305 + - type: ndcg_at_5 + value: 81.843 + - type: precision_at_1 + value: 72.74199999999999 + - type: precision_at_10 + value: 10.24 + - type: precision_at_100 + value: 1.089 + - type: precision_at_1000 + value: 0.11299999999999999 + - type: precision_at_3 + value: 31.268 + - type: precision_at_5 + value: 19.706000000000003 + - type: recall_at_1 + value: 67.914 + - type: recall_at_10 + value: 92.889 + - type: recall_at_100 + value: 96.42699999999999 + - type: recall_at_1000 + value: 97.92 + - type: recall_at_3 + value: 86.21 + - type: recall_at_5 + value: 90.036 + - task: + type: Retrieval + dataset: + name: MTEB FiQA2018 + type: fiqa + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 22.166 + - type: map_at_10 + value: 35.57 + - type: map_at_100 + value: 37.405 + - type: map_at_1000 + value: 37.564 + - type: map_at_3 + value: 30.379 + - type: map_at_5 + value: 33.324 + - type: mrr_at_1 + value: 43.519000000000005 + - type: mrr_at_10 + value: 51.556000000000004 + - type: mrr_at_100 + value: 52.344 + - type: mrr_at_1000 + value: 52.373999999999995 + - type: mrr_at_3 + value: 48.868 + - type: mrr_at_5 + value: 50.319 + - type: ndcg_at_1 + value: 43.519000000000005 + - type: ndcg_at_10 + value: 43.803 + - type: ndcg_at_100 + value: 50.468999999999994 + - type: ndcg_at_1000 + value: 53.111 + - type: ndcg_at_3 + value: 38.893 + - type: ndcg_at_5 + value: 40.653 + - type: precision_at_1 + value: 43.519000000000005 + - type: precision_at_10 + value: 12.253 + - type: precision_at_100 + value: 1.931 + - type: precision_at_1000 + value: 0.242 + - type: precision_at_3 + value: 25.617 + - type: precision_at_5 + value: 19.383 + - type: recall_at_1 + value: 22.166 + - type: recall_at_10 + value: 51.6 + - type: recall_at_100 + value: 76.574 + - type: recall_at_1000 + value: 92.192 + - type: recall_at_3 + value: 34.477999999999994 + - type: recall_at_5 + value: 41.835 + - task: + type: Retrieval + dataset: + name: MTEB HotpotQA + type: hotpotqa + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 39.041 + - type: map_at_10 + value: 62.961999999999996 + - type: map_at_100 + value: 63.79899999999999 + - type: map_at_1000 + value: 63.854 + - type: map_at_3 + value: 59.399 + - type: map_at_5 + value: 61.669 + - type: mrr_at_1 + value: 78.082 + - type: mrr_at_10 + value: 84.321 + - type: mrr_at_100 + value: 84.49600000000001 + - type: mrr_at_1000 + value: 84.502 + - type: mrr_at_3 + value: 83.421 + - type: mrr_at_5 + value: 83.977 + - type: ndcg_at_1 + value: 78.082 + - type: ndcg_at_10 + value: 71.229 + - type: ndcg_at_100 + value: 74.10900000000001 + - type: ndcg_at_1000 + value: 75.169 + - type: ndcg_at_3 + value: 66.28699999999999 + - type: ndcg_at_5 + value: 69.084 + - type: precision_at_1 + value: 78.082 + - type: precision_at_10 + value: 14.993 + - type: precision_at_100 + value: 1.7239999999999998 + - type: precision_at_1000 + value: 0.186 + - type: precision_at_3 + value: 42.737 + - type: precision_at_5 + value: 27.843 + - type: recall_at_1 + value: 39.041 + - type: recall_at_10 + value: 74.96300000000001 + - type: recall_at_100 + value: 86.199 + - type: recall_at_1000 + value: 93.228 + - type: recall_at_3 + value: 64.105 + - type: recall_at_5 + value: 69.608 + - task: + type: Classification + dataset: + name: MTEB ImdbClassification + type: mteb/imdb + config: default + split: test + revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 + metrics: + - type: accuracy + value: 90.23160000000001 + - type: ap + value: 85.5674856808308 + - type: f1 + value: 90.18033354786317 + - task: + type: Retrieval + dataset: + name: MTEB MSMARCO + type: msmarco + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 24.091 + - type: map_at_10 + value: 36.753 + - type: map_at_100 + value: 37.913000000000004 + - type: map_at_1000 + value: 37.958999999999996 + - type: map_at_3 + value: 32.818999999999996 + - type: map_at_5 + value: 35.171 + - type: mrr_at_1 + value: 24.742 + - type: mrr_at_10 + value: 37.285000000000004 + - type: mrr_at_100 + value: 38.391999999999996 + - type: mrr_at_1000 + value: 38.431 + - type: mrr_at_3 + value: 33.440999999999995 + - type: mrr_at_5 + value: 35.75 + - type: ndcg_at_1 + value: 24.742 + - type: ndcg_at_10 + value: 43.698 + - type: ndcg_at_100 + value: 49.145 + - type: ndcg_at_1000 + value: 50.23800000000001 + - type: ndcg_at_3 + value: 35.769 + - type: ndcg_at_5 + value: 39.961999999999996 + - type: precision_at_1 + value: 24.742 + - type: precision_at_10 + value: 6.7989999999999995 + - type: precision_at_100 + value: 0.95 + - type: precision_at_1000 + value: 0.104 + - type: precision_at_3 + value: 15.096000000000002 + - type: precision_at_5 + value: 11.183 + - type: recall_at_1 + value: 24.091 + - type: recall_at_10 + value: 65.068 + - type: recall_at_100 + value: 89.899 + - type: recall_at_1000 + value: 98.16 + - type: recall_at_3 + value: 43.68 + - type: recall_at_5 + value: 53.754999999999995 + - task: + type: Classification + dataset: + name: MTEB MTOPDomainClassification (en) + type: mteb/mtop_domain + config: en + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 93.66621067031465 + - type: f1 + value: 93.49622853272142 + - task: + type: Classification + dataset: + name: MTEB MTOPDomainClassification (de) + type: mteb/mtop_domain + config: de + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 91.94702733164272 + - type: f1 + value: 91.17043441745282 + - task: + type: Classification + dataset: + name: MTEB MTOPDomainClassification (es) + type: mteb/mtop_domain + config: es + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 92.20146764509674 + - type: f1 + value: 91.98359080555608 + - task: + type: Classification + dataset: + name: MTEB MTOPDomainClassification (fr) + type: mteb/mtop_domain + config: fr + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 88.99780770435328 + - type: f1 + value: 89.19746342724068 + - task: + type: Classification + dataset: + name: MTEB MTOPDomainClassification (hi) + type: mteb/mtop_domain + config: hi + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - 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type: accuracy + value: 73.90383322125084 + - type: f1 + value: 73.59201554448323 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (en) + type: mteb/amazon_massive_scenario + config: en + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 77.51176866173503 + - type: f1 + value: 77.46104434577758 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (es) + type: mteb/amazon_massive_scenario + config: es + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 74.31069266980496 + - type: f1 + value: 74.61048660675635 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (fa) + type: mteb/amazon_massive_scenario + config: fa + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 72.95225285810356 + - type: f1 + value: 72.33160006574627 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (fi) + type: mteb/amazon_massive_scenario + config: fi + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 73.12373907195696 + - type: f1 + value: 73.20921012557481 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (fr) + type: mteb/amazon_massive_scenario + config: fr + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 73.86684599865501 + - type: f1 + value: 73.82348774610831 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (he) + type: mteb/amazon_massive_scenario + config: he + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 71.40215198386012 + - type: f1 + value: 71.11945183971858 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (hi) + type: mteb/amazon_massive_scenario + config: hi + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - 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task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (is) + type: mteb/amazon_massive_scenario + config: is + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 67.15198386012105 + - type: f1 + value: 66.02172193802167 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (it) + type: mteb/amazon_massive_scenario + config: it + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 74.32414256893072 + - type: f1 + value: 74.30943421170574 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ja) + type: mteb/amazon_massive_scenario + config: ja + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 77.46805648957633 + - type: f1 + value: 77.62808409298209 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (jv) + type: mteb/amazon_massive_scenario + config: jv + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - 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task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ko) + type: mteb/amazon_massive_scenario + config: ko + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 75.04707464694015 + - type: f1 + value: 75.05099199098998 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (lv) + type: mteb/amazon_massive_scenario + config: lv + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 70.50437121721586 + - type: f1 + value: 69.83397721096314 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ml) + type: mteb/amazon_massive_scenario + config: ml + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 69.94283792871553 + - type: f1 + value: 68.8704663703913 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (mn) + type: mteb/amazon_massive_scenario + config: mn + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 64.79488903833222 + - type: f1 + value: 63.615424063345436 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ms) + type: mteb/amazon_massive_scenario + config: ms + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 69.88231338264963 + - type: f1 + value: 68.57892302593237 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (my) + type: mteb/amazon_massive_scenario + config: my + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 63.248150638870214 + - type: f1 + value: 61.06680605338809 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (nb) + type: mteb/amazon_massive_scenario + config: nb + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 74.84196368527236 + - type: f1 + value: 74.52566464968763 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (nl) + type: mteb/amazon_massive_scenario + config: nl + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 74.8285137861466 + - type: f1 + value: 74.8853197608802 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (pl) + type: mteb/amazon_massive_scenario + config: pl + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 74.13248150638869 + - type: f1 + value: 74.3982040999179 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (pt) + type: mteb/amazon_massive_scenario + config: pt + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 73.49024882313383 + - type: f1 + value: 73.82153848368573 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ro) + type: mteb/amazon_massive_scenario + config: ro + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 71.72158708809684 + - type: f1 + value: 71.85049433180541 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ru) + type: mteb/amazon_massive_scenario + config: ru + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 75.137861466039 + - type: f1 + value: 75.37628348188467 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (sl) + type: mteb/amazon_massive_scenario + config: sl + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 71.86953597848016 + - type: f1 + value: 71.87537624521661 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (sq) + type: mteb/amazon_massive_scenario + config: sq + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 70.27572293207801 + - type: f1 + value: 68.80017302344231 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (sv) + type: mteb/amazon_massive_scenario + config: sv + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 76.09952925353059 + - type: f1 + value: 76.07992707688408 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (sw) + type: mteb/amazon_massive_scenario + config: sw + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 63.140551445864155 + - type: f1 + value: 61.73855010331415 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ta) + type: mteb/amazon_massive_scenario + config: ta + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 66.27774041694687 + - type: f1 + value: 64.83664868894539 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (te) + type: mteb/amazon_massive_scenario + config: te + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 66.69468728984533 + - type: f1 + value: 64.76239666920868 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (th) + type: mteb/amazon_massive_scenario + config: th + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 73.44653665097512 + - type: f1 + value: 73.14646052013873 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (tl) + type: mteb/amazon_massive_scenario + config: tl + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 67.71351714862139 + - type: f1 + value: 66.67212180163382 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (tr) + type: mteb/amazon_massive_scenario + config: tr + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 73.9946200403497 + - type: f1 + value: 73.87348793725525 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (ur) + type: mteb/amazon_massive_scenario + config: ur + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 68.15400134498992 + - type: f1 + value: 67.09433241421094 + - task: + type: Classification + dataset: + name: MTEB MassiveScenarioClassification (vi) + type: mteb/amazon_massive_scenario + config: vi + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 73.11365164761264 + - type: f1 + value: 73.59502539433753 + - 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: 76.82582380632145 + - type: f1 + value: 76.89992945316313 + - 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: 71.81237390719569 + - type: f1 + value: 72.36499770986265 + - task: + type: Clustering + dataset: + name: MTEB MedrxivClusteringP2P + type: mteb/medrxiv-clustering-p2p + config: default + split: test + revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 + metrics: + - type: v_measure + value: 31.480506569594695 + - task: + type: Clustering + dataset: + name: MTEB MedrxivClusteringS2S + type: mteb/medrxiv-clustering-s2s + config: default + split: test + revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 + metrics: + - type: v_measure + value: 29.71252128004552 + - task: + type: Reranking + dataset: + name: MTEB MindSmallReranking + type: mteb/mind_small + config: default + split: test + revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 + metrics: + - type: map + value: 31.421396787056548 + - type: mrr + value: 32.48155274872267 + - task: + type: Retrieval + dataset: + name: MTEB NFCorpus + type: nfcorpus + config: default + split: test + revision: None + metrics: + - 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type: recall_at_1 + value: 5.595 + - type: recall_at_10 + value: 16.466 + - type: recall_at_100 + value: 31.226 + - type: recall_at_1000 + value: 62.778999999999996 + - type: recall_at_3 + value: 9.931 + - type: recall_at_5 + value: 12.884 + - task: + type: Retrieval + dataset: + name: MTEB NQ + type: nq + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 40.414 + - type: map_at_10 + value: 56.754000000000005 + - type: map_at_100 + value: 57.457 + - type: map_at_1000 + value: 57.477999999999994 + - type: map_at_3 + value: 52.873999999999995 + - type: map_at_5 + value: 55.175 + - type: mrr_at_1 + value: 45.278 + - type: mrr_at_10 + value: 59.192 + - type: mrr_at_100 + value: 59.650000000000006 + - type: mrr_at_1000 + value: 59.665 + - type: mrr_at_3 + value: 56.141 + - type: mrr_at_5 + value: 57.998000000000005 + - type: ndcg_at_1 + value: 45.278 + - type: ndcg_at_10 + value: 64.056 + - type: ndcg_at_100 + value: 66.89 + - type: ndcg_at_1000 + value: 67.364 + - type: ndcg_at_3 + value: 56.97 + - type: ndcg_at_5 + value: 60.719 + - type: precision_at_1 + value: 45.278 + - type: precision_at_10 + value: 9.994 + - type: precision_at_100 + value: 1.165 + - type: precision_at_1000 + value: 0.121 + - type: precision_at_3 + value: 25.512 + - type: precision_at_5 + value: 17.509 + - type: recall_at_1 + value: 40.414 + - type: recall_at_10 + value: 83.596 + - type: recall_at_100 + value: 95.72 + - type: recall_at_1000 + value: 99.24 + - type: recall_at_3 + value: 65.472 + - type: recall_at_5 + value: 74.039 + - task: + type: Retrieval + dataset: + name: MTEB QuoraRetrieval + type: quora + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 70.352 + - type: map_at_10 + value: 84.369 + - type: map_at_100 + value: 85.02499999999999 + - type: map_at_1000 + value: 85.04 + - type: map_at_3 + value: 81.42399999999999 + - type: map_at_5 + value: 83.279 + - type: mrr_at_1 + value: 81.05 + - type: mrr_at_10 + value: 87.401 + - 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type: v_measure + value: 46.54068723291946 + - task: + type: Clustering + dataset: + name: MTEB RedditClusteringP2P + type: mteb/reddit-clustering-p2p + config: default + split: test + revision: 282350215ef01743dc01b456c7f5241fa8937f16 + metrics: + - type: v_measure + value: 63.216287629895994 + - task: + type: Retrieval + dataset: + name: MTEB SCIDOCS + type: scidocs + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 4.023000000000001 + - type: map_at_10 + value: 10.071 + - type: map_at_100 + value: 11.892 + - type: map_at_1000 + value: 12.196 + - type: map_at_3 + value: 7.234 + - type: map_at_5 + value: 8.613999999999999 + - type: mrr_at_1 + value: 19.900000000000002 + - type: mrr_at_10 + value: 30.516 + - type: mrr_at_100 + value: 31.656000000000002 + - type: mrr_at_1000 + value: 31.723000000000003 + - type: mrr_at_3 + value: 27.400000000000002 + - type: mrr_at_5 + value: 29.270000000000003 + - type: ndcg_at_1 + value: 19.900000000000002 + - type: ndcg_at_10 + value: 17.474 + - 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type: euclidean_spearman + value: 80.18961335654585 + - type: manhattan_pearson + value: 81.13925443187625 + - type: manhattan_spearman + value: 80.07948723044424 + - task: + type: STS + dataset: + name: MTEB STS12 + type: mteb/sts12-sts + config: default + split: test + revision: a0d554a64d88156834ff5ae9920b964011b16384 + metrics: + - type: cos_sim_pearson + value: 86.94262461316023 + - type: cos_sim_spearman + value: 80.01596278563865 + - type: euclidean_pearson + value: 83.80799622922581 + - type: euclidean_spearman + value: 79.94984954947103 + - type: manhattan_pearson + value: 83.68473841756281 + - type: manhattan_spearman + value: 79.84990707951822 + - task: + type: STS + dataset: + name: MTEB STS13 + type: mteb/sts13-sts + config: default + split: test + revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca + metrics: + - type: cos_sim_pearson + value: 80.57346443146068 + - type: cos_sim_spearman + value: 81.54689837570866 + - type: euclidean_pearson + value: 81.10909881516007 + - type: euclidean_spearman + value: 81.56746243261762 + - type: manhattan_pearson + value: 80.87076036186582 + - type: manhattan_spearman + value: 81.33074987964402 + - task: + type: STS + dataset: + name: MTEB STS14 + type: mteb/sts14-sts + config: default + split: test + revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 + metrics: + - type: cos_sim_pearson + value: 79.54733787179849 + - type: cos_sim_spearman + value: 77.72202105610411 + - type: euclidean_pearson + value: 78.9043595478849 + - type: euclidean_spearman + value: 77.93422804309435 + - type: manhattan_pearson + value: 78.58115121621368 + - type: manhattan_spearman + value: 77.62508135122033 + - task: + type: STS + dataset: + name: MTEB STS15 + type: mteb/sts15-sts + config: default + split: test + revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 + metrics: + - type: cos_sim_pearson + value: 88.59880017237558 + - type: cos_sim_spearman + value: 89.31088630824758 + - type: euclidean_pearson + value: 88.47069261564656 + - type: euclidean_spearman + value: 89.33581971465233 + - 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type: manhattan_pearson + value: 63.055779168508764 + - type: manhattan_spearman + value: 65.49585020501449 + - task: + type: STS + dataset: + name: MTEB STS22 (es-it) + type: mteb/sts22-crosslingual-sts + config: es-it + split: test + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + metrics: + - type: cos_sim_pearson + value: 59.587830825340404 + - type: cos_sim_spearman + value: 68.93467614588089 + - type: euclidean_pearson + value: 62.3073527367404 + - type: euclidean_spearman + value: 69.69758171553175 + - type: manhattan_pearson + value: 61.9074580815789 + - type: manhattan_spearman + value: 69.57696375597865 + - task: + type: STS + dataset: + name: MTEB STS22 (de-fr) + type: mteb/sts22-crosslingual-sts + config: de-fr + split: test + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + metrics: + - type: cos_sim_pearson + value: 57.143220125577066 + - type: cos_sim_spearman + value: 67.78857859159226 + - type: euclidean_pearson + value: 55.58225107923733 + - type: euclidean_spearman + value: 67.80662907184563 + - 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type: manhattan_pearson + value: 59.03256832438492 + - type: manhattan_spearman + value: 61.97797868009122 + - task: + type: STS + dataset: + name: MTEB STSBenchmark + type: mteb/stsbenchmark-sts + config: default + split: test + revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 + metrics: + - type: cos_sim_pearson + value: 85.00757054859712 + - type: cos_sim_spearman + value: 87.29283629622222 + - type: euclidean_pearson + value: 86.54824171775536 + - type: euclidean_spearman + value: 87.24364730491402 + - type: manhattan_pearson + value: 86.5062156915074 + - type: manhattan_spearman + value: 87.15052170378574 + - task: + type: Reranking + dataset: + name: MTEB SciDocsRR + type: mteb/scidocs-reranking + config: default + split: test + revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab + metrics: + - type: map + value: 82.03549357197389 + - type: mrr + value: 95.05437645143527 + - task: + type: Retrieval + dataset: + name: MTEB SciFact + type: scifact + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 57.260999999999996 + - type: map_at_10 + value: 66.259 + - type: map_at_100 + value: 66.884 + - type: map_at_1000 + value: 66.912 + - type: map_at_3 + value: 63.685 + - type: map_at_5 + value: 65.35499999999999 + - type: mrr_at_1 + value: 60.333000000000006 + - type: mrr_at_10 + value: 67.5 + - type: mrr_at_100 + value: 68.013 + - type: mrr_at_1000 + value: 68.038 + - type: mrr_at_3 + value: 65.61099999999999 + - type: mrr_at_5 + value: 66.861 + - type: ndcg_at_1 + value: 60.333000000000006 + - type: ndcg_at_10 + value: 70.41 + - type: ndcg_at_100 + value: 73.10600000000001 + - type: ndcg_at_1000 + value: 73.846 + - type: ndcg_at_3 + value: 66.133 + - type: ndcg_at_5 + value: 68.499 + - type: precision_at_1 + value: 60.333000000000006 + - type: precision_at_10 + value: 9.232999999999999 + - type: precision_at_100 + value: 1.0630000000000002 + - type: precision_at_1000 + value: 0.11299999999999999 + - type: precision_at_3 + value: 25.667 + - type: precision_at_5 + value: 17.067 + - 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type: v_measure + value: 32.68850574423839 + - task: + type: Reranking + dataset: + name: MTEB StackOverflowDupQuestions + type: mteb/stackoverflowdupquestions-reranking + config: default + split: test + revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 + metrics: + - type: map + value: 49.71580650644033 + - type: mrr + value: 50.50971903913081 + - task: + type: Summarization + dataset: + name: MTEB SummEval + type: mteb/summeval + config: default + split: test + revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c + metrics: + - type: cos_sim_pearson + value: 29.152190498799484 + - type: cos_sim_spearman + value: 29.686180371952727 + - type: dot_pearson + value: 27.248664793816342 + - type: dot_spearman + value: 28.37748983721745 + - task: + type: Retrieval + dataset: + name: MTEB TRECCOVID + type: trec-covid + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 0.20400000000000001 + - type: map_at_10 + value: 1.6209999999999998 + - type: map_at_100 + value: 9.690999999999999 + - 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type: recall_at_3 + value: 0.613 + - type: recall_at_5 + value: 0.991 + - 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: 95.89999999999999 + - type: f1 + value: 94.69999999999999 + - type: precision + value: 94.11666666666667 + - type: recall + value: 95.89999999999999 + - 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: 68.20809248554913 + - type: f1 + value: 63.431048720066066 + - type: precision + value: 61.69143958161298 + - type: recall + value: 68.20809248554913 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (kur-eng) + type: mteb/tatoeba-bitext-mining + config: kur-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - 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type: accuracy + value: 88.3 + - type: f1 + value: 85.5 + - type: precision + value: 84.25833333333334 + - type: recall + value: 88.3 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (khm-eng) + type: mteb/tatoeba-bitext-mining + config: khm-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 65.51246537396122 + - type: f1 + value: 60.02297410192148 + - type: precision + value: 58.133467727289236 + - type: recall + value: 65.51246537396122 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (ces-eng) + type: mteb/tatoeba-bitext-mining + config: ces-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 96 + - type: f1 + value: 94.89 + - type: precision + value: 94.39166666666667 + - type: recall + value: 96 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (tzl-eng) + type: mteb/tatoeba-bitext-mining + config: tzl-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 57.692307692307686 + - type: f1 + value: 53.162393162393165 + - type: precision + value: 51.70673076923077 + - type: recall + value: 57.692307692307686 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (urd-eng) + type: mteb/tatoeba-bitext-mining + config: urd-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 91.60000000000001 + - type: f1 + value: 89.21190476190475 + - type: precision + value: 88.08666666666667 + - type: recall + value: 91.60000000000001 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (ara-eng) + type: mteb/tatoeba-bitext-mining + config: ara-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 88 + - type: f1 + value: 85.47 + - type: precision + value: 84.43266233766234 + - type: recall + value: 88 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (kor-eng) + type: mteb/tatoeba-bitext-mining + config: kor-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 92.7 + - type: f1 + value: 90.64999999999999 + - type: precision + value: 89.68333333333332 + - type: recall + value: 92.7 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (yid-eng) + type: mteb/tatoeba-bitext-mining + config: yid-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 80.30660377358491 + - type: f1 + value: 76.33044137466307 + - type: precision + value: 74.78970125786164 + - type: recall + value: 80.30660377358491 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (fin-eng) + type: mteb/tatoeba-bitext-mining + config: fin-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 96.39999999999999 + - type: f1 + value: 95.44 + - type: precision + value: 94.99166666666666 + - type: recall + value: 96.39999999999999 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (tha-eng) + type: mteb/tatoeba-bitext-mining + config: tha-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 96.53284671532847 + - type: f1 + value: 95.37712895377129 + - type: precision + value: 94.7992700729927 + - type: recall + value: 96.53284671532847 + - task: + type: BitextMining + dataset: + name: MTEB Tatoeba (wuu-eng) + type: mteb/tatoeba-bitext-mining + config: wuu-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 89 + - type: f1 + value: 86.23190476190476 + - type: precision + value: 85.035 + - type: recall + value: 89 + - task: + type: Retrieval + dataset: + name: MTEB Touche2020 + type: webis-touche2020 + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 2.585 + - type: map_at_10 + value: 9.012 + - type: map_at_100 + value: 14.027000000000001 + - type: map_at_1000 + value: 15.565000000000001 + - type: map_at_3 + value: 5.032 + - type: map_at_5 + value: 6.657 + - type: mrr_at_1 + value: 28.571 + - type: mrr_at_10 + value: 45.377 + - type: mrr_at_100 + value: 46.119 + - type: mrr_at_1000 + value: 46.127 + - type: mrr_at_3 + value: 41.156 + - type: mrr_at_5 + value: 42.585 + - type: ndcg_at_1 + value: 27.551 + - type: ndcg_at_10 + value: 23.395 + - type: ndcg_at_100 + value: 33.342 + - type: ndcg_at_1000 + value: 45.523 + - type: ndcg_at_3 + value: 25.158 + - type: ndcg_at_5 + value: 23.427 + - type: precision_at_1 + value: 28.571 + - type: precision_at_10 + value: 21.429000000000002 + - type: precision_at_100 + value: 6.714 + - type: precision_at_1000 + value: 1.473 + - type: precision_at_3 + value: 27.211000000000002 + - type: precision_at_5 + value: 24.490000000000002 + - type: recall_at_1 + value: 2.585 + - type: recall_at_10 + value: 15.418999999999999 + - type: recall_at_100 + value: 42.485 + - type: recall_at_1000 + value: 79.536 + - type: recall_at_3 + value: 6.239999999999999 + - type: recall_at_5 + value: 8.996 + - task: + type: Classification + dataset: + name: MTEB ToxicConversationsClassification + type: mteb/toxic_conversations_50k + config: default + split: test + revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c + metrics: + - type: accuracy + value: 71.3234 + - type: ap + value: 14.361688653847423 + - type: f1 + value: 54.819068624319044 + - task: + type: Classification + dataset: + name: MTEB TweetSentimentExtractionClassification + type: mteb/tweet_sentiment_extraction + config: default + split: test + revision: d604517c81ca91fe16a244d1248fc021f9ecee7a + metrics: + - type: accuracy + value: 61.97792869269949 + - type: f1 + value: 62.28965628513728 + - task: + type: Clustering + dataset: + name: MTEB TwentyNewsgroupsClustering + type: mteb/twentynewsgroups-clustering + config: default + split: test + revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 + metrics: + - type: v_measure + value: 38.90540145385218 + - task: + type: PairClassification + dataset: + name: MTEB TwitterSemEval2015 + type: mteb/twittersemeval2015-pairclassification + config: default + split: test + revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 + metrics: + - type: cos_sim_accuracy + value: 86.53513739047506 + - type: cos_sim_ap + value: 75.27741586677557 + - type: cos_sim_f1 + value: 69.18792902473774 + - type: cos_sim_precision + value: 67.94708725515136 + - type: cos_sim_recall + value: 70.47493403693932 + - type: dot_accuracy + value: 84.7052512368123 + - type: dot_ap + value: 69.36075482849378 + - type: dot_f1 + value: 64.44688376631296 + - type: dot_precision + value: 59.92288500793831 + - type: dot_recall + value: 69.70976253298153 + - type: euclidean_accuracy + value: 86.60666388508076 + - type: euclidean_ap + value: 75.47512772621097 + - type: euclidean_f1 + value: 69.413872536473 + - type: euclidean_precision + value: 67.39562624254472 + - type: euclidean_recall + value: 71.55672823218997 + - type: manhattan_accuracy + value: 86.52917684925792 + - type: manhattan_ap + value: 75.34000110496703 + - type: manhattan_f1 + value: 69.28489190226429 + - type: manhattan_precision + value: 67.24608889992551 + - type: manhattan_recall + value: 71.45118733509234 + - type: max_accuracy + value: 86.60666388508076 + - type: max_ap + value: 75.47512772621097 + - type: max_f1 + value: 69.413872536473 + - task: + type: PairClassification + dataset: + name: MTEB TwitterURLCorpus + type: mteb/twitterurlcorpus-pairclassification + config: default + split: test + revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf + metrics: + - type: cos_sim_accuracy + value: 89.01695967710637 + - type: cos_sim_ap + value: 85.8298270742901 + - type: cos_sim_f1 + value: 78.46988128389272 + - type: cos_sim_precision + value: 74.86017897091722 + - type: cos_sim_recall + value: 82.44533415460425 + - type: dot_accuracy + value: 88.19420188613343 + - type: dot_ap + value: 83.82679165901324 + - type: dot_f1 + value: 76.55833777304208 + - type: dot_precision + value: 75.6884875846501 + - type: dot_recall + value: 77.44841392054204 + - type: euclidean_accuracy + value: 89.03054294252338 + - type: euclidean_ap + value: 85.89089555185325 + - type: euclidean_f1 + value: 78.62997658079624 + - type: euclidean_precision + value: 74.92329149232914 + - type: euclidean_recall + value: 82.72251308900523 + - type: manhattan_accuracy + value: 89.0266620095471 + - type: manhattan_ap + value: 85.86458997929147 + - type: manhattan_f1 + value: 78.50685331000291 + - type: manhattan_precision + value: 74.5499861534201 + - type: manhattan_recall + value: 82.90729904527257 + - type: max_accuracy + value: 89.03054294252338 + - type: max_ap + value: 85.89089555185325 + - type: max_f1 + value: 78.62997658079624 +--- + +# nnch/multilingual-e5-large-Q4_K_M-GGUF +This model was converted to GGUF format from [`intfloat/multilingual-e5-large`](https://huggingface.co/intfloat/multilingual-e5-large) 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) 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 nnch/multilingual-e5-large-Q4_K_M-GGUF --hf-file multilingual-e5-large-q4_k_m.gguf -p "The meaning to life and the universe is" +``` + +### Server: +```bash +llama-server --hf-repo nnch/multilingual-e5-large-Q4_K_M-GGUF --hf-file multilingual-e5-large-q4_k_m.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 nnch/multilingual-e5-large-Q4_K_M-GGUF --hf-file multilingual-e5-large-q4_k_m.gguf -p "The meaning to life and the universe is" +``` +or +``` +./llama-server --hf-repo nnch/multilingual-e5-large-Q4_K_M-GGUF --hf-file multilingual-e5-large-q4_k_m.gguf -c 2048 +```