diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -1,3 +1,5810 @@ --- license: bigscience-bloom-rail-1.0 +language: + - ak + - ar + - as + - bm + - bn + - ca + - code + - en + - es + - eu + - fon + - fr + - gu + - hi + - id + - ig + - ki + - kn + - lg + - ln + - ml + - mr + - ne + - nso + - ny + - or + - pa + - pt + - rn + - rw + - sn + - st + - sw + - ta + - te + - tn + - ts + - tum + - tw + - ur + - vi + - wo + - xh + - yo + - zh + - zhs + - zht + - zu +tags: +- mteb +model-index: +- name: udever-bloom-7b1 + results: + - task: + type: STS + dataset: + type: C-MTEB/AFQMC + name: MTEB AFQMC + config: default + split: validation + revision: None + metrics: + - type: cos_sim_pearson + value: 31.3788313486292 + - type: cos_sim_spearman + value: 31.87117445808444 + - type: euclidean_pearson + value: 30.66886666881808 + - type: euclidean_spearman + value: 31.28368681542041 + - type: manhattan_pearson + value: 30.679984531432936 + - type: manhattan_spearman + value: 31.22208726593753 + - task: + type: STS + dataset: + type: C-MTEB/ATEC + name: MTEB ATEC + config: default + split: test + revision: None + metrics: + - type: cos_sim_pearson + value: 38.403248424956764 + - type: cos_sim_spearman + value: 38.798254852046504 + - type: euclidean_pearson + value: 41.154981142995084 + - type: euclidean_spearman + value: 38.73503172297125 + - type: manhattan_pearson + value: 41.20226384035751 + - type: manhattan_spearman + value: 38.77085234568287 + - task: + type: Classification + dataset: + type: mteb/amazon_counterfactual + name: MTEB AmazonCounterfactualClassification (en) + config: en + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 73.11940298507463 + - type: ap + value: 35.692863077186466 + - type: f1 + value: 67.02733552778966 + - task: + type: Classification + dataset: + type: mteb/amazon_polarity + name: MTEB AmazonPolarityClassification + config: default + split: test + revision: e2d317d38cd51312af73b3d32a06d1a08b442046 + metrics: + - type: accuracy + value: 88.885175 + - type: ap + value: 84.75400736514149 + - type: f1 + value: 88.85806225869703 + - task: + type: Classification + dataset: + type: mteb/amazon_reviews_multi + name: MTEB AmazonReviewsClassification (en) + config: en + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 43.202 + - type: f1 + value: 42.63847450850621 + - task: + type: Retrieval + dataset: + type: arguana + name: MTEB ArguAna + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 25.676 + - type: map_at_10 + value: 42.539 + - type: map_at_100 + value: 43.383 + - type: map_at_1000 + value: 43.39 + - type: map_at_3 + value: 36.996 + - type: map_at_5 + value: 40.175 + - type: mrr_at_1 + value: 26.387 + - type: mrr_at_10 + value: 42.792 + - type: mrr_at_100 + value: 43.637 + - type: mrr_at_1000 + value: 43.644 + - type: mrr_at_3 + value: 37.21 + - type: mrr_at_5 + value: 40.407 + - type: ndcg_at_1 + value: 25.676 + - type: ndcg_at_10 + value: 52.207 + - type: ndcg_at_100 + value: 55.757999999999996 + - type: ndcg_at_1000 + value: 55.913999999999994 + - type: ndcg_at_3 + value: 40.853 + - type: ndcg_at_5 + value: 46.588 + - type: precision_at_1 + value: 25.676 + - type: precision_at_10 + value: 8.314 + - type: precision_at_100 + value: 0.985 + - type: precision_at_1000 + value: 0.1 + - type: precision_at_3 + value: 17.354 + - type: precision_at_5 + value: 13.200999999999999 + - type: recall_at_1 + value: 25.676 + - type: recall_at_10 + value: 83.14399999999999 + - type: recall_at_100 + value: 98.506 + - type: recall_at_1000 + value: 99.644 + - type: recall_at_3 + value: 52.063 + - type: recall_at_5 + value: 66.003 + - task: + type: Clustering + dataset: + type: mteb/arxiv-clustering-p2p + name: MTEB ArxivClusteringP2P + config: default + split: test + revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d + metrics: + - type: v_measure + value: 45.66024127046263 + - task: + type: Clustering + dataset: + type: mteb/arxiv-clustering-s2s + name: MTEB ArxivClusteringS2S + config: default + split: test + revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 + metrics: + - type: v_measure + value: 38.418361433667336 + - task: + type: Reranking + dataset: + type: mteb/askubuntudupquestions-reranking + name: MTEB AskUbuntuDupQuestions + config: default + split: test + revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 + metrics: + - type: map + value: 61.60189642383972 + - type: mrr + value: 75.26678538451391 + - task: + type: STS + dataset: + type: mteb/biosses-sts + name: MTEB BIOSSES + config: default + split: test + revision: d3fb88f8f02e40887cd149695127462bbcf29b4a + metrics: + - type: cos_sim_pearson + value: 87.85884182572595 + - type: cos_sim_spearman + value: 85.5242378844044 + - type: euclidean_pearson + value: 85.37705073557146 + - type: euclidean_spearman + value: 84.65132642825964 + - type: manhattan_pearson + value: 85.42179213807349 + - type: manhattan_spearman + value: 84.6959057572829 + - task: + type: STS + dataset: + type: C-MTEB/BQ + name: MTEB BQ + config: default + split: test + revision: None + metrics: + - type: cos_sim_pearson + value: 47.81802155652125 + - type: cos_sim_spearman + value: 47.66691834501235 + - type: euclidean_pearson + value: 47.781824357030935 + - type: euclidean_spearman + value: 48.03322284408188 + - type: manhattan_pearson + value: 47.871159981038346 + - type: manhattan_spearman + value: 48.18240784527666 + - task: + type: BitextMining + dataset: + type: mteb/bucc-bitext-mining + name: MTEB BUCC (de-en) + config: de-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 88.29853862212944 + - type: f1 + value: 87.70994966904566 + - type: precision + value: 87.43152897902377 + - type: recall + value: 88.29853862212944 + - task: + type: BitextMining + dataset: + type: mteb/bucc-bitext-mining + name: MTEB BUCC (fr-en) + config: fr-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 98.6022452124147 + - type: f1 + value: 98.40597255851495 + - type: precision + value: 98.30875339349916 + - type: recall + value: 98.6022452124147 + - task: + type: BitextMining + dataset: + type: mteb/bucc-bitext-mining + name: MTEB BUCC (ru-en) + config: ru-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 79.64669206789054 + - type: f1 + value: 78.74831345770036 + - type: precision + value: 78.33899087865143 + - type: recall + value: 79.64669206789054 + - task: + type: BitextMining + dataset: + type: mteb/bucc-bitext-mining + name: MTEB BUCC (zh-en) + config: zh-en + split: test + revision: d51519689f32196a32af33b075a01d0e7c51e252 + metrics: + - type: accuracy + value: 98.78883622959452 + - type: f1 + value: 98.7712831314727 + - type: precision + value: 98.76250658241179 + - type: recall + value: 98.78883622959452 + - task: + type: Classification + dataset: + type: mteb/banking77 + name: MTEB Banking77Classification + config: default + split: test + revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 + metrics: + - type: accuracy + value: 85.36363636363637 + - type: f1 + value: 85.33381612267455 + - task: + type: Clustering + dataset: + type: mteb/biorxiv-clustering-p2p + name: MTEB BiorxivClusteringP2P + config: default + split: test + revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 + metrics: + - type: v_measure + value: 35.54276849354455 + - task: + type: Clustering + dataset: + type: mteb/biorxiv-clustering-s2s + name: MTEB BiorxivClusteringS2S + config: default + split: test + revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 + metrics: + - type: v_measure + value: 32.18953191097238 + - task: + type: Clustering + dataset: + type: C-MTEB/CLSClusteringP2P + name: MTEB CLSClusteringP2P + config: default + split: test + revision: None + metrics: + - type: v_measure + value: 36.00041315364012 + - task: + type: Clustering + dataset: + type: C-MTEB/CLSClusteringS2S + name: MTEB CLSClusteringS2S + config: default + split: test + revision: None + metrics: + - type: v_measure + value: 36.35255790689628 + - task: + type: Reranking + dataset: + type: C-MTEB/CMedQAv1-reranking + name: MTEB CMedQAv1 + config: default + split: test + revision: None + metrics: + - type: map + value: 70.54141681949504 + - type: mrr + value: 74.81400793650795 + - task: + type: Reranking + dataset: + type: C-MTEB/CMedQAv2-reranking + name: MTEB CMedQAv2 + config: default + split: test + revision: None + metrics: + - type: map + value: 71.3534829537025 + - type: mrr + value: 75.85095238095238 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackAndroidRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 32.5 + - type: map_at_10 + value: 43.37 + - type: map_at_100 + value: 44.926 + - type: map_at_1000 + value: 45.047 + - type: map_at_3 + value: 40.083999999999996 + - type: map_at_5 + value: 41.71 + - type: mrr_at_1 + value: 40.343 + - type: mrr_at_10 + value: 49.706 + - type: mrr_at_100 + value: 50.470000000000006 + - type: mrr_at_1000 + value: 50.515 + - type: mrr_at_3 + value: 47.306 + - type: mrr_at_5 + value: 48.379 + - type: ndcg_at_1 + value: 40.343 + - type: ndcg_at_10 + value: 49.461 + - type: ndcg_at_100 + value: 55.084999999999994 + - type: ndcg_at_1000 + value: 56.994 + - type: ndcg_at_3 + value: 44.896 + - type: ndcg_at_5 + value: 46.437 + - type: precision_at_1 + value: 40.343 + - type: precision_at_10 + value: 9.27 + - type: precision_at_100 + value: 1.5190000000000001 + - type: precision_at_1000 + value: 0.197 + - type: precision_at_3 + value: 21.412 + - type: precision_at_5 + value: 15.021 + - type: recall_at_1 + value: 32.5 + - type: recall_at_10 + value: 60.857000000000006 + - type: recall_at_100 + value: 83.761 + - type: recall_at_1000 + value: 96.003 + - type: recall_at_3 + value: 46.675 + - type: recall_at_5 + value: 51.50900000000001 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackEnglishRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 26.931 + - type: map_at_10 + value: 35.769 + - type: map_at_100 + value: 36.8 + - type: map_at_1000 + value: 36.925999999999995 + - type: map_at_3 + value: 33.068999999999996 + - type: map_at_5 + value: 34.615 + - type: mrr_at_1 + value: 34.013 + - type: mrr_at_10 + value: 41.293 + - type: mrr_at_100 + value: 41.945 + - type: mrr_at_1000 + value: 42.002 + - type: mrr_at_3 + value: 39.204 + - type: mrr_at_5 + value: 40.436 + - type: ndcg_at_1 + value: 34.013 + - type: ndcg_at_10 + value: 40.935 + - type: ndcg_at_100 + value: 44.879999999999995 + - type: ndcg_at_1000 + value: 47.342 + - type: ndcg_at_3 + value: 37.071 + - type: ndcg_at_5 + value: 38.903 + - type: precision_at_1 + value: 34.013 + - type: precision_at_10 + value: 7.617999999999999 + - type: precision_at_100 + value: 1.185 + - type: precision_at_1000 + value: 0.169 + - type: precision_at_3 + value: 17.855999999999998 + - type: precision_at_5 + value: 12.65 + - type: recall_at_1 + value: 26.931 + - type: recall_at_10 + value: 50.256 + - type: recall_at_100 + value: 67.026 + - type: recall_at_1000 + value: 83.138 + - type: recall_at_3 + value: 38.477 + - type: recall_at_5 + value: 43.784 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackGamingRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 38.474000000000004 + - type: map_at_10 + value: 50.486 + - type: map_at_100 + value: 51.620999999999995 + - type: map_at_1000 + value: 51.675000000000004 + - type: map_at_3 + value: 47.64 + - type: map_at_5 + value: 49.187999999999995 + - type: mrr_at_1 + value: 43.824000000000005 + - type: mrr_at_10 + value: 53.910000000000004 + - type: mrr_at_100 + value: 54.601 + - type: mrr_at_1000 + value: 54.632000000000005 + - type: mrr_at_3 + value: 51.578 + - type: mrr_at_5 + value: 52.922999999999995 + - type: ndcg_at_1 + value: 43.824000000000005 + - type: ndcg_at_10 + value: 56.208000000000006 + - type: ndcg_at_100 + value: 60.624 + - type: ndcg_at_1000 + value: 61.78 + - type: ndcg_at_3 + value: 51.27 + - type: ndcg_at_5 + value: 53.578 + - type: precision_at_1 + value: 43.824000000000005 + - type: precision_at_10 + value: 8.978 + - type: precision_at_100 + value: 1.216 + - type: precision_at_1000 + value: 0.136 + - type: precision_at_3 + value: 22.884 + - type: precision_at_5 + value: 15.498000000000001 + - type: recall_at_1 + value: 38.474000000000004 + - type: recall_at_10 + value: 69.636 + - type: recall_at_100 + value: 88.563 + - type: recall_at_1000 + value: 96.86200000000001 + - type: recall_at_3 + value: 56.347 + - type: recall_at_5 + value: 61.980000000000004 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackGisRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 23.13 + - type: map_at_10 + value: 31.892 + - type: map_at_100 + value: 32.938 + - type: map_at_1000 + value: 33.025999999999996 + - type: map_at_3 + value: 29.072 + - type: map_at_5 + value: 30.775000000000002 + - type: mrr_at_1 + value: 25.197999999999997 + - type: mrr_at_10 + value: 34.224 + - type: mrr_at_100 + value: 35.149 + - type: mrr_at_1000 + value: 35.215999999999994 + - type: mrr_at_3 + value: 31.563000000000002 + - type: mrr_at_5 + value: 33.196 + - type: ndcg_at_1 + value: 25.197999999999997 + - type: ndcg_at_10 + value: 37.117 + - type: ndcg_at_100 + value: 42.244 + - type: ndcg_at_1000 + value: 44.432 + - type: ndcg_at_3 + value: 31.604 + - type: ndcg_at_5 + value: 34.543 + - type: precision_at_1 + value: 25.197999999999997 + - type: precision_at_10 + value: 5.876 + - type: precision_at_100 + value: 0.886 + - type: precision_at_1000 + value: 0.11100000000000002 + - type: precision_at_3 + value: 13.672 + - type: precision_at_5 + value: 9.831 + - type: recall_at_1 + value: 23.13 + - type: recall_at_10 + value: 50.980000000000004 + - type: recall_at_100 + value: 74.565 + - type: recall_at_1000 + value: 90.938 + - type: recall_at_3 + value: 36.038 + - type: recall_at_5 + value: 43.326 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackMathematicaRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 17.317 + - type: map_at_10 + value: 24.517 + - type: map_at_100 + value: 25.771 + - type: map_at_1000 + value: 25.915 + - type: map_at_3 + value: 22.332 + - type: map_at_5 + value: 23.526 + - type: mrr_at_1 + value: 21.766 + - type: mrr_at_10 + value: 29.096 + - type: mrr_at_100 + value: 30.165 + - type: mrr_at_1000 + value: 30.253000000000004 + - type: mrr_at_3 + value: 27.114 + - type: mrr_at_5 + value: 28.284 + - type: ndcg_at_1 + value: 21.766 + - type: ndcg_at_10 + value: 29.060999999999996 + - type: ndcg_at_100 + value: 35.107 + - type: ndcg_at_1000 + value: 38.339 + - type: ndcg_at_3 + value: 25.121 + - type: ndcg_at_5 + value: 26.953 + - type: precision_at_1 + value: 21.766 + - type: precision_at_10 + value: 5.274 + - type: precision_at_100 + value: 0.958 + - type: precision_at_1000 + value: 0.13699999999999998 + - type: precision_at_3 + value: 11.816 + - type: precision_at_5 + value: 8.433 + - type: recall_at_1 + value: 17.317 + - type: recall_at_10 + value: 38.379999999999995 + - type: recall_at_100 + value: 64.792 + - type: recall_at_1000 + value: 87.564 + - type: recall_at_3 + value: 27.737000000000002 + - type: recall_at_5 + value: 32.340999999999994 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackPhysicsRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 28.876 + - type: map_at_10 + value: 40.02 + - type: map_at_100 + value: 41.367 + - type: map_at_1000 + value: 41.482 + - type: map_at_3 + value: 36.651 + - type: map_at_5 + value: 38.411 + - type: mrr_at_1 + value: 35.804 + - type: mrr_at_10 + value: 45.946999999999996 + - type: mrr_at_100 + value: 46.696 + - type: mrr_at_1000 + value: 46.741 + - type: mrr_at_3 + value: 43.118 + - type: mrr_at_5 + value: 44.74 + - type: ndcg_at_1 + value: 35.804 + - type: ndcg_at_10 + value: 46.491 + - type: ndcg_at_100 + value: 51.803 + - type: ndcg_at_1000 + value: 53.845 + - type: ndcg_at_3 + value: 40.97 + - type: ndcg_at_5 + value: 43.431 + - type: precision_at_1 + value: 35.804 + - type: precision_at_10 + value: 8.595 + - type: precision_at_100 + value: 1.312 + - type: precision_at_1000 + value: 0.167 + - type: precision_at_3 + value: 19.634 + - type: precision_at_5 + value: 13.879 + - type: recall_at_1 + value: 28.876 + - type: recall_at_10 + value: 59.952000000000005 + - type: recall_at_100 + value: 81.978 + - type: recall_at_1000 + value: 95.03399999999999 + - type: recall_at_3 + value: 44.284 + - type: recall_at_5 + value: 50.885999999999996 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackProgrammersRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 24.238 + - type: map_at_10 + value: 34.276 + - type: map_at_100 + value: 35.65 + - type: map_at_1000 + value: 35.769 + - type: map_at_3 + value: 31.227 + - type: map_at_5 + value: 33.046 + - type: mrr_at_1 + value: 30.137000000000004 + - type: mrr_at_10 + value: 39.473 + - type: mrr_at_100 + value: 40.400999999999996 + - type: mrr_at_1000 + value: 40.455000000000005 + - type: mrr_at_3 + value: 36.891 + - type: mrr_at_5 + value: 38.391999999999996 + - type: ndcg_at_1 + value: 30.137000000000004 + - type: ndcg_at_10 + value: 40.08 + - type: ndcg_at_100 + value: 46.01 + - type: ndcg_at_1000 + value: 48.36 + - type: ndcg_at_3 + value: 35.163 + - type: ndcg_at_5 + value: 37.583 + - type: precision_at_1 + value: 30.137000000000004 + - type: precision_at_10 + value: 7.466 + - type: precision_at_100 + value: 1.228 + - type: precision_at_1000 + value: 0.16199999999999998 + - type: precision_at_3 + value: 17.122999999999998 + - type: precision_at_5 + value: 12.283 + - type: recall_at_1 + value: 24.238 + - type: recall_at_10 + value: 52.078 + - type: recall_at_100 + value: 77.643 + - type: recall_at_1000 + value: 93.49199999999999 + - type: recall_at_3 + value: 38.161 + - type: recall_at_5 + value: 44.781 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 24.915250000000004 + - type: map_at_10 + value: 33.98191666666666 + - type: map_at_100 + value: 35.19166666666667 + - type: map_at_1000 + value: 35.30983333333333 + - type: map_at_3 + value: 31.27391666666666 + - type: map_at_5 + value: 32.74366666666666 + - type: mrr_at_1 + value: 29.800749999999994 + - type: mrr_at_10 + value: 38.235749999999996 + - type: mrr_at_100 + value: 39.10616666666667 + - type: mrr_at_1000 + value: 39.166583333333335 + - type: mrr_at_3 + value: 35.91033333333334 + - type: mrr_at_5 + value: 37.17766666666667 + - type: ndcg_at_1 + value: 29.800749999999994 + - type: ndcg_at_10 + value: 39.287833333333325 + - type: ndcg_at_100 + value: 44.533833333333334 + - type: ndcg_at_1000 + value: 46.89608333333333 + - type: ndcg_at_3 + value: 34.676 + - type: ndcg_at_5 + value: 36.75208333333333 + - type: precision_at_1 + value: 29.800749999999994 + - type: precision_at_10 + value: 6.9134166666666665 + - type: precision_at_100 + value: 1.1206666666666665 + - type: precision_at_1000 + value: 0.15116666666666667 + - type: precision_at_3 + value: 16.069083333333335 + - type: precision_at_5 + value: 11.337916666666668 + - type: recall_at_1 + value: 24.915250000000004 + - type: recall_at_10 + value: 50.86333333333334 + - type: recall_at_100 + value: 73.85574999999999 + - type: recall_at_1000 + value: 90.24041666666666 + - type: recall_at_3 + value: 37.80116666666666 + - type: recall_at_5 + value: 43.263 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackStatsRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 22.853 + - type: map_at_10 + value: 30.349999999999998 + - type: map_at_100 + value: 31.341 + - type: map_at_1000 + value: 31.44 + - type: map_at_3 + value: 28.294999999999998 + - type: map_at_5 + value: 29.412 + - type: mrr_at_1 + value: 25.919999999999998 + - type: mrr_at_10 + value: 33.194 + - type: mrr_at_100 + value: 34.071 + - type: mrr_at_1000 + value: 34.136 + - type: mrr_at_3 + value: 31.391000000000002 + - type: mrr_at_5 + value: 32.311 + - type: ndcg_at_1 + value: 25.919999999999998 + - type: ndcg_at_10 + value: 34.691 + - type: ndcg_at_100 + value: 39.83 + - type: ndcg_at_1000 + value: 42.193000000000005 + - type: ndcg_at_3 + value: 30.91 + - type: ndcg_at_5 + value: 32.634 + - type: precision_at_1 + value: 25.919999999999998 + - type: precision_at_10 + value: 5.521 + - type: precision_at_100 + value: 0.882 + - type: precision_at_1000 + value: 0.117 + - type: precision_at_3 + value: 13.547999999999998 + - type: precision_at_5 + value: 9.293999999999999 + - type: recall_at_1 + value: 22.853 + - type: recall_at_10 + value: 45.145 + - type: recall_at_100 + value: 69.158 + - type: recall_at_1000 + value: 86.354 + - type: recall_at_3 + value: 34.466 + - type: recall_at_5 + value: 39.044000000000004 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackTexRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 17.151 + - type: map_at_10 + value: 23.674 + - type: map_at_100 + value: 24.738 + - type: map_at_1000 + value: 24.864 + - type: map_at_3 + value: 21.514 + - type: map_at_5 + value: 22.695 + - type: mrr_at_1 + value: 20.991 + - type: mrr_at_10 + value: 27.612 + - type: mrr_at_100 + value: 28.526 + - type: mrr_at_1000 + value: 28.603 + - type: mrr_at_3 + value: 25.618999999999996 + - type: mrr_at_5 + value: 26.674 + - type: ndcg_at_1 + value: 20.991 + - type: ndcg_at_10 + value: 27.983000000000004 + - type: ndcg_at_100 + value: 33.190999999999995 + - type: ndcg_at_1000 + value: 36.172 + - type: ndcg_at_3 + value: 24.195 + - type: ndcg_at_5 + value: 25.863999999999997 + - type: precision_at_1 + value: 20.991 + - type: precision_at_10 + value: 5.093 + - type: precision_at_100 + value: 0.8959999999999999 + - type: precision_at_1000 + value: 0.132 + - type: precision_at_3 + value: 11.402 + - type: precision_at_5 + value: 8.197000000000001 + - type: recall_at_1 + value: 17.151 + - type: recall_at_10 + value: 37.025000000000006 + - type: recall_at_100 + value: 60.787 + - type: recall_at_1000 + value: 82.202 + - type: recall_at_3 + value: 26.19 + - type: recall_at_5 + value: 30.657 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackUnixRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 25.463 + - type: map_at_10 + value: 34.372 + - type: map_at_100 + value: 35.475 + - type: map_at_1000 + value: 35.582 + - type: map_at_3 + value: 31.791000000000004 + - type: map_at_5 + value: 33.292 + - type: mrr_at_1 + value: 30.784 + - type: mrr_at_10 + value: 38.948 + - type: mrr_at_100 + value: 39.792 + - type: mrr_at_1000 + value: 39.857 + - type: mrr_at_3 + value: 36.614000000000004 + - type: mrr_at_5 + value: 37.976 + - type: ndcg_at_1 + value: 30.784 + - type: ndcg_at_10 + value: 39.631 + - type: ndcg_at_100 + value: 44.747 + - type: ndcg_at_1000 + value: 47.172 + - type: ndcg_at_3 + value: 34.976 + - type: ndcg_at_5 + value: 37.241 + - type: precision_at_1 + value: 30.784 + - type: precision_at_10 + value: 6.622999999999999 + - type: precision_at_100 + value: 1.04 + - type: precision_at_1000 + value: 0.135 + - type: precision_at_3 + value: 16.014 + - type: precision_at_5 + value: 11.286999999999999 + - type: recall_at_1 + value: 25.463 + - type: recall_at_10 + value: 51.23799999999999 + - type: recall_at_100 + value: 73.4 + - type: recall_at_1000 + value: 90.634 + - type: recall_at_3 + value: 38.421 + - type: recall_at_5 + value: 44.202999999999996 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackWebmastersRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 23.714 + - type: map_at_10 + value: 32.712 + - type: map_at_100 + value: 34.337 + - type: map_at_1000 + value: 34.556 + - type: map_at_3 + value: 29.747 + - type: map_at_5 + value: 31.208000000000002 + - type: mrr_at_1 + value: 29.051 + - type: mrr_at_10 + value: 37.589 + - type: mrr_at_100 + value: 38.638 + - type: mrr_at_1000 + value: 38.692 + - type: mrr_at_3 + value: 35.079 + - type: mrr_at_5 + value: 36.265 + - type: ndcg_at_1 + value: 29.051 + - type: ndcg_at_10 + value: 38.681 + - type: ndcg_at_100 + value: 44.775999999999996 + - type: ndcg_at_1000 + value: 47.354 + - type: ndcg_at_3 + value: 33.888 + - type: ndcg_at_5 + value: 35.854 + - type: precision_at_1 + value: 29.051 + - type: precision_at_10 + value: 7.489999999999999 + - type: precision_at_100 + value: 1.518 + - type: precision_at_1000 + value: 0.241 + - type: precision_at_3 + value: 16.008 + - type: precision_at_5 + value: 11.66 + - type: recall_at_1 + value: 23.714 + - type: recall_at_10 + value: 50.324000000000005 + - type: recall_at_100 + value: 77.16 + - type: recall_at_1000 + value: 93.186 + - type: recall_at_3 + value: 36.356 + - type: recall_at_5 + value: 41.457 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackWordpressRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 18.336 + - type: map_at_10 + value: 26.345000000000002 + - type: map_at_100 + value: 27.336 + - type: map_at_1000 + value: 27.436 + - type: map_at_3 + value: 23.865 + - type: map_at_5 + value: 25.046000000000003 + - type: mrr_at_1 + value: 19.778000000000002 + - type: mrr_at_10 + value: 27.837 + - type: mrr_at_100 + value: 28.82 + - type: mrr_at_1000 + value: 28.897000000000002 + - type: mrr_at_3 + value: 25.446999999999996 + - type: mrr_at_5 + value: 26.556 + - type: ndcg_at_1 + value: 19.778000000000002 + - type: ndcg_at_10 + value: 31.115 + - type: ndcg_at_100 + value: 36.109 + - type: ndcg_at_1000 + value: 38.769999999999996 + - type: ndcg_at_3 + value: 26.048 + - type: ndcg_at_5 + value: 28.004 + - type: precision_at_1 + value: 19.778000000000002 + - type: precision_at_10 + value: 5.157 + - type: precision_at_100 + value: 0.808 + - type: precision_at_1000 + value: 0.11 + - type: precision_at_3 + value: 11.459999999999999 + - type: precision_at_5 + value: 8.022 + - type: recall_at_1 + value: 18.336 + - type: recall_at_10 + value: 44.489000000000004 + - type: recall_at_100 + value: 67.43599999999999 + - type: recall_at_1000 + value: 87.478 + - type: recall_at_3 + value: 30.462 + - type: recall_at_5 + value: 35.188 + - task: + type: Retrieval + dataset: + type: climate-fever + name: MTEB ClimateFEVER + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 10.747 + - type: map_at_10 + value: 18.625 + - type: map_at_100 + value: 20.465 + - type: map_at_1000 + value: 20.639 + - type: map_at_3 + value: 15.57 + - type: map_at_5 + value: 17.089 + - type: mrr_at_1 + value: 24.169 + - type: mrr_at_10 + value: 35.96 + - type: mrr_at_100 + value: 36.888 + - type: mrr_at_1000 + value: 36.931999999999995 + - type: mrr_at_3 + value: 32.443 + - type: mrr_at_5 + value: 34.433 + - type: ndcg_at_1 + value: 24.169 + - type: ndcg_at_10 + value: 26.791999999999998 + - type: ndcg_at_100 + value: 34.054 + - type: ndcg_at_1000 + value: 37.285000000000004 + - type: ndcg_at_3 + value: 21.636 + - type: ndcg_at_5 + value: 23.394000000000002 + - type: precision_at_1 + value: 24.169 + - type: precision_at_10 + value: 8.476 + - type: precision_at_100 + value: 1.6209999999999998 + - type: precision_at_1000 + value: 0.22200000000000003 + - type: precision_at_3 + value: 16.156000000000002 + - type: precision_at_5 + value: 12.520999999999999 + - type: recall_at_1 + value: 10.747 + - type: recall_at_10 + value: 32.969 + - type: recall_at_100 + value: 57.99999999999999 + - type: recall_at_1000 + value: 76.12299999999999 + - type: recall_at_3 + value: 20.315 + - type: recall_at_5 + value: 25.239 + - task: + type: Retrieval + dataset: + type: C-MTEB/CmedqaRetrieval + name: MTEB CmedqaRetrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 14.751 + - type: map_at_10 + value: 22.03 + - type: map_at_100 + value: 23.471 + - type: map_at_1000 + value: 23.644000000000002 + - type: map_at_3 + value: 19.559 + - type: map_at_5 + value: 20.863 + - type: mrr_at_1 + value: 23.581 + - type: mrr_at_10 + value: 29.863 + - type: mrr_at_100 + value: 30.839 + - type: mrr_at_1000 + value: 30.925000000000004 + - type: mrr_at_3 + value: 27.894000000000002 + - type: mrr_at_5 + value: 28.965999999999998 + - type: ndcg_at_1 + value: 23.581 + - type: ndcg_at_10 + value: 26.996 + - type: ndcg_at_100 + value: 33.537 + - type: ndcg_at_1000 + value: 37.307 + - type: ndcg_at_3 + value: 23.559 + - type: ndcg_at_5 + value: 24.839 + - type: precision_at_1 + value: 23.581 + - type: precision_at_10 + value: 6.209 + - type: precision_at_100 + value: 1.165 + - type: precision_at_1000 + value: 0.165 + - type: precision_at_3 + value: 13.62 + - type: precision_at_5 + value: 9.882 + - type: recall_at_1 + value: 14.751 + - type: recall_at_10 + value: 34.075 + - type: recall_at_100 + value: 61.877 + - type: recall_at_1000 + value: 88.212 + - type: recall_at_3 + value: 23.519000000000002 + - type: recall_at_5 + value: 27.685 + - task: + type: PairClassification + dataset: + type: C-MTEB/CMNLI + name: MTEB Cmnli + config: default + split: validation + revision: None + metrics: + - type: cos_sim_accuracy + value: 76.36800962116656 + - type: cos_sim_ap + value: 85.14376065556142 + - type: cos_sim_f1 + value: 77.81474723623485 + - type: cos_sim_precision + value: 71.92460317460318 + - type: cos_sim_recall + value: 84.75566986205284 + - type: dot_accuracy + value: 71.94227300060132 + - type: dot_ap + value: 79.03676891584456 + - type: dot_f1 + value: 74.95833333333334 + - type: dot_precision + value: 67.59346233327072 + - type: dot_recall + value: 84.12438625204582 + - type: euclidean_accuracy + value: 76.043295249549 + - type: euclidean_ap + value: 85.28765360616536 + - type: euclidean_f1 + value: 78.01733248784612 + - type: euclidean_precision + value: 71.1861137897782 + - type: euclidean_recall + value: 86.29880757540333 + - type: manhattan_accuracy + value: 76.17558628983764 + - type: manhattan_ap + value: 85.52739323094916 + - type: manhattan_f1 + value: 78.30788804071246 + - type: manhattan_precision + value: 71.63918525703201 + - type: manhattan_recall + value: 86.34556932429273 + - type: max_accuracy + value: 76.36800962116656 + - type: max_ap + value: 85.52739323094916 + - type: max_f1 + value: 78.30788804071246 + - task: + type: Retrieval + dataset: + type: C-MTEB/CovidRetrieval + name: MTEB CovidRetrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 56.164 + - type: map_at_10 + value: 64.575 + - type: map_at_100 + value: 65.098 + - type: map_at_1000 + value: 65.118 + - type: map_at_3 + value: 62.329 + - type: map_at_5 + value: 63.535 + - type: mrr_at_1 + value: 56.269999999999996 + - type: mrr_at_10 + value: 64.63600000000001 + - type: mrr_at_100 + value: 65.14 + - type: mrr_at_1000 + value: 65.16 + - type: mrr_at_3 + value: 62.522 + - type: mrr_at_5 + value: 63.57000000000001 + - type: ndcg_at_1 + value: 56.269999999999996 + - type: ndcg_at_10 + value: 68.855 + - type: ndcg_at_100 + value: 71.47099999999999 + - type: ndcg_at_1000 + value: 72.02499999999999 + - type: ndcg_at_3 + value: 64.324 + - type: ndcg_at_5 + value: 66.417 + - type: precision_at_1 + value: 56.269999999999996 + - type: precision_at_10 + value: 8.303 + - type: precision_at_100 + value: 0.9570000000000001 + - type: precision_at_1000 + value: 0.1 + - type: precision_at_3 + value: 23.427999999999997 + - type: precision_at_5 + value: 15.09 + - type: recall_at_1 + value: 56.164 + - type: recall_at_10 + value: 82.271 + - type: recall_at_100 + value: 94.626 + - type: recall_at_1000 + value: 99.05199999999999 + - type: recall_at_3 + value: 69.94200000000001 + - type: recall_at_5 + value: 74.947 + - task: + type: Retrieval + dataset: + type: dbpedia-entity + name: MTEB DBPedia + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 8.686 + - type: map_at_10 + value: 17.766000000000002 + - type: map_at_100 + value: 23.507 + - type: map_at_1000 + value: 24.757 + - type: map_at_3 + value: 13.238 + - type: map_at_5 + value: 15.161 + - type: mrr_at_1 + value: 65.25 + - type: mrr_at_10 + value: 72.88 + - type: mrr_at_100 + value: 73.246 + - type: mrr_at_1000 + value: 73.261 + - type: mrr_at_3 + value: 71.542 + - type: mrr_at_5 + value: 72.392 + - type: ndcg_at_1 + value: 53.75 + - type: ndcg_at_10 + value: 37.623 + - type: ndcg_at_100 + value: 40.302 + - type: ndcg_at_1000 + value: 47.471999999999994 + - type: ndcg_at_3 + value: 43.324 + - type: ndcg_at_5 + value: 39.887 + - type: precision_at_1 + value: 65.25 + - type: precision_at_10 + value: 28.749999999999996 + - type: precision_at_100 + value: 8.34 + - type: precision_at_1000 + value: 1.703 + - type: precision_at_3 + value: 46.583000000000006 + - type: precision_at_5 + value: 38.0 + - type: recall_at_1 + value: 8.686 + - type: recall_at_10 + value: 22.966 + - type: recall_at_100 + value: 44.3 + - type: recall_at_1000 + value: 67.77499999999999 + - type: recall_at_3 + value: 14.527999999999999 + - type: recall_at_5 + value: 17.617 + - task: + type: Retrieval + dataset: + type: C-MTEB/DuRetrieval + name: MTEB DuRetrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 22.439 + - type: map_at_10 + value: 68.484 + - type: map_at_100 + value: 71.67999999999999 + - type: map_at_1000 + value: 71.761 + - type: map_at_3 + value: 46.373999999999995 + - type: map_at_5 + value: 58.697 + - type: mrr_at_1 + value: 80.65 + - type: mrr_at_10 + value: 86.53 + - type: mrr_at_100 + value: 86.624 + - type: mrr_at_1000 + value: 86.631 + - type: mrr_at_3 + value: 85.95 + - type: mrr_at_5 + value: 86.297 + - type: ndcg_at_1 + value: 80.65 + - type: ndcg_at_10 + value: 78.075 + - type: ndcg_at_100 + value: 82.014 + - type: ndcg_at_1000 + value: 82.903 + - type: ndcg_at_3 + value: 75.785 + - type: ndcg_at_5 + value: 74.789 + - type: precision_at_1 + value: 80.65 + - type: precision_at_10 + value: 38.425 + - type: precision_at_100 + value: 4.62 + - type: precision_at_1000 + value: 0.483 + - type: precision_at_3 + value: 68.25 + - type: precision_at_5 + value: 57.92 + - type: recall_at_1 + value: 22.439 + - type: recall_at_10 + value: 80.396 + - type: recall_at_100 + value: 92.793 + - type: recall_at_1000 + value: 97.541 + - type: recall_at_3 + value: 49.611 + - type: recall_at_5 + value: 65.065 + - task: + type: Retrieval + dataset: + type: C-MTEB/EcomRetrieval + name: MTEB EcomRetrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 43.9 + - type: map_at_10 + value: 53.394 + - type: map_at_100 + value: 54.078 + - type: map_at_1000 + value: 54.105000000000004 + - type: map_at_3 + value: 50.583 + - type: map_at_5 + value: 52.443 + - type: mrr_at_1 + value: 43.9 + - type: mrr_at_10 + value: 53.394 + - type: mrr_at_100 + value: 54.078 + - type: mrr_at_1000 + value: 54.105000000000004 + - type: mrr_at_3 + value: 50.583 + - type: mrr_at_5 + value: 52.443 + - type: ndcg_at_1 + value: 43.9 + - type: ndcg_at_10 + value: 58.341 + - type: ndcg_at_100 + value: 61.753 + - type: ndcg_at_1000 + value: 62.525 + - type: ndcg_at_3 + value: 52.699 + - type: ndcg_at_5 + value: 56.042 + - type: precision_at_1 + value: 43.9 + - type: precision_at_10 + value: 7.3999999999999995 + - type: precision_at_100 + value: 0.901 + - type: precision_at_1000 + value: 0.096 + - type: precision_at_3 + value: 19.6 + - type: precision_at_5 + value: 13.38 + - type: recall_at_1 + value: 43.9 + - type: recall_at_10 + value: 74.0 + - type: recall_at_100 + value: 90.10000000000001 + - type: recall_at_1000 + value: 96.3 + - type: recall_at_3 + value: 58.8 + - type: recall_at_5 + value: 66.9 + - task: + type: Classification + dataset: + type: mteb/emotion + name: MTEB EmotionClassification + config: default + split: test + revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 + metrics: + - type: accuracy + value: 48.765 + - type: f1 + value: 44.2791193129597 + - task: + type: Retrieval + dataset: + type: fever + name: MTEB FEVER + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 56.89999999999999 + - type: map_at_10 + value: 68.352 + - type: map_at_100 + value: 68.768 + - type: map_at_1000 + value: 68.782 + - type: map_at_3 + value: 66.27300000000001 + - type: map_at_5 + value: 67.67699999999999 + - type: mrr_at_1 + value: 61.476 + - type: mrr_at_10 + value: 72.662 + - type: mrr_at_100 + value: 72.993 + - type: mrr_at_1000 + value: 72.99799999999999 + - type: mrr_at_3 + value: 70.75200000000001 + - type: mrr_at_5 + value: 72.056 + - type: ndcg_at_1 + value: 61.476 + - type: ndcg_at_10 + value: 73.98400000000001 + - type: ndcg_at_100 + value: 75.744 + - type: ndcg_at_1000 + value: 76.036 + - type: ndcg_at_3 + value: 70.162 + - type: ndcg_at_5 + value: 72.482 + - type: precision_at_1 + value: 61.476 + - type: precision_at_10 + value: 9.565 + - type: precision_at_100 + value: 1.054 + - type: precision_at_1000 + value: 0.109 + - type: precision_at_3 + value: 27.943 + - type: precision_at_5 + value: 18.056 + - type: recall_at_1 + value: 56.89999999999999 + - type: recall_at_10 + value: 87.122 + - type: recall_at_100 + value: 94.742 + - type: recall_at_1000 + value: 96.70100000000001 + - type: recall_at_3 + value: 76.911 + - type: recall_at_5 + value: 82.607 + - task: + type: Retrieval + dataset: + type: fiqa + name: MTEB FiQA2018 + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 17.610999999999997 + - type: map_at_10 + value: 29.12 + - type: map_at_100 + value: 30.958000000000002 + - type: map_at_1000 + value: 31.151 + - type: map_at_3 + value: 25.369000000000003 + - type: map_at_5 + value: 27.445000000000004 + - type: mrr_at_1 + value: 35.185 + - type: mrr_at_10 + value: 44.533 + - type: mrr_at_100 + value: 45.385 + - type: mrr_at_1000 + value: 45.432 + - type: mrr_at_3 + value: 42.258 + - type: mrr_at_5 + value: 43.608999999999995 + - type: ndcg_at_1 + value: 35.185 + - type: ndcg_at_10 + value: 36.696 + - type: ndcg_at_100 + value: 43.491 + - type: ndcg_at_1000 + value: 46.800000000000004 + - type: ndcg_at_3 + value: 33.273 + - type: ndcg_at_5 + value: 34.336 + - type: precision_at_1 + value: 35.185 + - type: precision_at_10 + value: 10.309 + - type: precision_at_100 + value: 1.719 + - type: precision_at_1000 + value: 0.231 + - type: precision_at_3 + value: 22.479 + - type: precision_at_5 + value: 16.481 + - type: recall_at_1 + value: 17.610999999999997 + - type: recall_at_10 + value: 43.29 + - type: recall_at_100 + value: 68.638 + - type: recall_at_1000 + value: 88.444 + - type: recall_at_3 + value: 30.303 + - type: recall_at_5 + value: 35.856 + - task: + type: Retrieval + dataset: + type: hotpotqa + name: MTEB HotpotQA + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 34.18 + - type: map_at_10 + value: 47.753 + - type: map_at_100 + value: 48.522 + - type: map_at_1000 + value: 48.596000000000004 + - type: map_at_3 + value: 45.222 + - type: map_at_5 + value: 46.793 + - type: mrr_at_1 + value: 68.35900000000001 + - type: mrr_at_10 + value: 74.503 + - type: mrr_at_100 + value: 74.811 + - type: mrr_at_1000 + value: 74.82799999999999 + - type: mrr_at_3 + value: 73.347 + - type: mrr_at_5 + value: 74.06700000000001 + - type: ndcg_at_1 + value: 68.35900000000001 + - type: ndcg_at_10 + value: 56.665 + - type: ndcg_at_100 + value: 59.629 + - type: ndcg_at_1000 + value: 61.222 + - type: ndcg_at_3 + value: 52.81400000000001 + - type: ndcg_at_5 + value: 54.94 + - type: precision_at_1 + value: 68.35900000000001 + - type: precision_at_10 + value: 11.535 + - type: precision_at_100 + value: 1.388 + - type: precision_at_1000 + value: 0.16 + - type: precision_at_3 + value: 32.784 + - type: precision_at_5 + value: 21.348 + - type: recall_at_1 + value: 34.18 + - type: recall_at_10 + value: 57.677 + - type: recall_at_100 + value: 69.379 + - type: recall_at_1000 + value: 80.061 + - type: recall_at_3 + value: 49.175999999999995 + - type: recall_at_5 + value: 53.369 + - task: + type: Classification + dataset: + type: C-MTEB/IFlyTek-classification + name: MTEB IFlyTek + config: default + split: validation + revision: None + metrics: + - type: accuracy + value: 46.23316660253944 + - type: f1 + value: 39.09397722262806 + - task: + type: Classification + dataset: + type: mteb/imdb + name: MTEB ImdbClassification + config: default + split: test + revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 + metrics: + - type: accuracy + value: 78.46119999999999 + - type: ap + value: 72.53477126781094 + - type: f1 + value: 78.28701752379332 + - task: + type: Classification + dataset: + type: C-MTEB/JDReview-classification + name: MTEB JDReview + config: default + split: test + revision: None + metrics: + - type: accuracy + value: 84.16510318949344 + - type: ap + value: 50.10324581565756 + - type: f1 + value: 78.34748161287605 + - task: + type: STS + dataset: + type: C-MTEB/LCQMC + name: MTEB LCQMC + config: default + split: test + revision: None + metrics: + - type: cos_sim_pearson + value: 68.71925879533819 + - type: cos_sim_spearman + value: 75.33926640820977 + - type: euclidean_pearson + value: 74.59557932790653 + - type: euclidean_spearman + value: 75.76006440878783 + - type: manhattan_pearson + value: 74.7461963483351 + - type: manhattan_spearman + value: 75.87111519308131 + - task: + type: Retrieval + dataset: + type: C-MTEB/MMarcoRetrieval + name: MTEB MMarcoRetrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 66.249 + - type: map_at_10 + value: 75.236 + - type: map_at_100 + value: 75.581 + - type: map_at_1000 + value: 75.593 + - type: map_at_3 + value: 73.463 + - type: map_at_5 + value: 74.602 + - type: mrr_at_1 + value: 68.42399999999999 + - type: mrr_at_10 + value: 75.81099999999999 + - type: mrr_at_100 + value: 76.115 + - type: mrr_at_1000 + value: 76.126 + - type: mrr_at_3 + value: 74.26899999999999 + - type: mrr_at_5 + value: 75.24300000000001 + - type: ndcg_at_1 + value: 68.42399999999999 + - type: ndcg_at_10 + value: 78.81700000000001 + - type: ndcg_at_100 + value: 80.379 + - type: ndcg_at_1000 + value: 80.667 + - type: ndcg_at_3 + value: 75.476 + - type: ndcg_at_5 + value: 77.38199999999999 + - type: precision_at_1 + value: 68.42399999999999 + - type: precision_at_10 + value: 9.491 + - type: precision_at_100 + value: 1.027 + - type: precision_at_1000 + value: 0.105 + - type: precision_at_3 + value: 28.352 + - type: precision_at_5 + value: 18.043 + - type: recall_at_1 + value: 66.249 + - type: recall_at_10 + value: 89.238 + - type: recall_at_100 + value: 96.319 + - type: recall_at_1000 + value: 98.524 + - type: recall_at_3 + value: 80.438 + - type: recall_at_5 + value: 84.95 + - task: + type: Retrieval + dataset: + type: msmarco + name: MTEB MSMARCO + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 23.083000000000002 + - type: map_at_10 + value: 35.251 + - type: map_at_100 + value: 36.461 + - type: map_at_1000 + value: 36.507 + - type: map_at_3 + value: 31.474999999999998 + - type: map_at_5 + value: 33.658 + - type: mrr_at_1 + value: 23.724999999999998 + - type: mrr_at_10 + value: 35.88 + - type: mrr_at_100 + value: 37.021 + - type: mrr_at_1000 + value: 37.062 + - type: mrr_at_3 + value: 32.159 + - type: mrr_at_5 + value: 34.325 + - type: ndcg_at_1 + value: 23.724999999999998 + - type: ndcg_at_10 + value: 42.018 + - type: ndcg_at_100 + value: 47.764 + - type: ndcg_at_1000 + value: 48.916 + - type: ndcg_at_3 + value: 34.369 + - type: ndcg_at_5 + value: 38.266 + - type: precision_at_1 + value: 23.724999999999998 + - type: precision_at_10 + value: 6.553000000000001 + - type: precision_at_100 + value: 0.942 + - type: precision_at_1000 + value: 0.104 + - type: precision_at_3 + value: 14.532 + - type: precision_at_5 + value: 10.696 + - type: recall_at_1 + value: 23.083000000000002 + - type: recall_at_10 + value: 62.739 + - type: recall_at_100 + value: 89.212 + - type: recall_at_1000 + value: 97.991 + - type: recall_at_3 + value: 42.064 + - type: recall_at_5 + value: 51.417 + - task: + type: Classification + dataset: + type: mteb/mtop_domain + name: MTEB MTOPDomainClassification (en) + config: en + split: test + revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf + metrics: + - type: accuracy + value: 93.43365253077975 + - type: f1 + value: 93.07455671032345 + - task: + type: Classification + dataset: + type: mteb/mtop_intent + name: MTEB MTOPIntentClassification (en) + config: en + split: test + revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba + metrics: + - type: accuracy + value: 71.72822617419061 + - type: f1 + value: 55.6093871673643 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_intent + name: MTEB MassiveIntentClassification (en) + config: en + split: test + revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 + metrics: + - type: accuracy + value: 72.03765971755212 + - type: f1 + value: 70.88235592002572 + - task: + type: Classification + dataset: + type: mteb/amazon_massive_scenario + name: MTEB MassiveScenarioClassification (en) + config: en + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 76.86281102891728 + - type: f1 + value: 77.15496923811003 + - task: + type: Retrieval + dataset: + type: C-MTEB/MedicalRetrieval + name: MTEB MedicalRetrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 41.8 + - type: map_at_10 + value: 46.993 + - type: map_at_100 + value: 47.534 + - type: map_at_1000 + value: 47.587 + - type: map_at_3 + value: 45.717 + - type: map_at_5 + value: 46.357 + - type: mrr_at_1 + value: 42.0 + - type: mrr_at_10 + value: 47.093 + - type: mrr_at_100 + value: 47.634 + - type: mrr_at_1000 + value: 47.687000000000005 + - type: mrr_at_3 + value: 45.817 + - type: mrr_at_5 + value: 46.457 + - type: ndcg_at_1 + value: 41.8 + - type: ndcg_at_10 + value: 49.631 + - type: ndcg_at_100 + value: 52.53 + - type: ndcg_at_1000 + value: 54.238 + - type: ndcg_at_3 + value: 46.949000000000005 + - type: ndcg_at_5 + value: 48.102000000000004 + - type: precision_at_1 + value: 41.8 + - type: precision_at_10 + value: 5.800000000000001 + - type: precision_at_100 + value: 0.722 + - type: precision_at_1000 + value: 0.086 + - type: precision_at_3 + value: 16.833000000000002 + - type: precision_at_5 + value: 10.66 + - type: recall_at_1 + value: 41.8 + - type: recall_at_10 + value: 57.99999999999999 + - type: recall_at_100 + value: 72.2 + - type: recall_at_1000 + value: 86.3 + - type: recall_at_3 + value: 50.5 + - type: recall_at_5 + value: 53.300000000000004 + - task: + type: Clustering + dataset: + type: mteb/medrxiv-clustering-p2p + name: MTEB MedrxivClusteringP2P + config: default + split: test + revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 + metrics: + - type: v_measure + value: 30.949060810392886 + - task: + type: Clustering + dataset: + type: mteb/medrxiv-clustering-s2s + name: MTEB MedrxivClusteringS2S + config: default + split: test + revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 + metrics: + - type: v_measure + value: 28.87339864059011 + - task: + type: Reranking + dataset: + type: mteb/mind_small + name: MTEB MindSmallReranking + config: default + split: test + revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 + metrics: + - type: map + value: 31.217934626189926 + - type: mrr + value: 32.27509143911496 + - task: + type: Reranking + dataset: + type: C-MTEB/Mmarco-reranking + name: MTEB MMarcoReranking + config: default + split: dev + revision: None + metrics: + - type: map + value: 26.691638884089574 + - type: mrr + value: 25.15674603174603 + - task: + type: Classification + dataset: + type: C-MTEB/MultilingualSentiment-classification + name: MTEB MultilingualSentiment + config: default + split: validation + revision: None + metrics: + - type: accuracy + value: 68.35666666666667 + - type: f1 + value: 68.30294399725629 + - task: + type: Retrieval + dataset: + type: nfcorpus + name: MTEB NFCorpus + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 5.759 + - type: map_at_10 + value: 13.425999999999998 + - type: map_at_100 + value: 16.988 + - type: map_at_1000 + value: 18.512 + - type: map_at_3 + value: 9.737 + - type: map_at_5 + value: 11.558 + - type: mrr_at_1 + value: 48.297000000000004 + - type: mrr_at_10 + value: 56.788000000000004 + - type: mrr_at_100 + value: 57.306000000000004 + - type: mrr_at_1000 + value: 57.349000000000004 + - type: mrr_at_3 + value: 54.386 + - type: mrr_at_5 + value: 56.135000000000005 + - type: ndcg_at_1 + value: 46.285 + - type: ndcg_at_10 + value: 36.016 + - type: ndcg_at_100 + value: 32.984 + - type: ndcg_at_1000 + value: 42.093 + - type: ndcg_at_3 + value: 41.743 + - type: ndcg_at_5 + value: 39.734 + - type: precision_at_1 + value: 48.297000000000004 + - type: precision_at_10 + value: 26.779999999999998 + - type: precision_at_100 + value: 8.505 + - type: precision_at_1000 + value: 2.1420000000000003 + - type: precision_at_3 + value: 39.422000000000004 + - type: precision_at_5 + value: 34.675 + - type: recall_at_1 + value: 5.759 + - type: recall_at_10 + value: 17.251 + - type: recall_at_100 + value: 33.323 + - type: recall_at_1000 + value: 66.759 + - type: recall_at_3 + value: 10.703 + - type: recall_at_5 + value: 13.808000000000002 + - task: + type: Retrieval + dataset: + type: nq + name: MTEB NQ + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 31.696999999999996 + - type: map_at_10 + value: 46.099000000000004 + - type: map_at_100 + value: 47.143 + - type: map_at_1000 + value: 47.178 + - type: map_at_3 + value: 41.948 + - type: map_at_5 + value: 44.504 + - type: mrr_at_1 + value: 35.717999999999996 + - type: mrr_at_10 + value: 48.653 + - type: mrr_at_100 + value: 49.456 + - type: mrr_at_1000 + value: 49.479 + - type: mrr_at_3 + value: 45.283 + - type: mrr_at_5 + value: 47.422 + - type: ndcg_at_1 + value: 35.689 + - type: ndcg_at_10 + value: 53.312000000000005 + - type: ndcg_at_100 + value: 57.69 + - type: ndcg_at_1000 + value: 58.489000000000004 + - type: ndcg_at_3 + value: 45.678999999999995 + - type: ndcg_at_5 + value: 49.897000000000006 + - type: precision_at_1 + value: 35.689 + - type: precision_at_10 + value: 8.685 + - type: precision_at_100 + value: 1.111 + - type: precision_at_1000 + value: 0.11900000000000001 + - type: precision_at_3 + value: 20.558 + - type: precision_at_5 + value: 14.802999999999999 + - type: recall_at_1 + value: 31.696999999999996 + - type: recall_at_10 + value: 72.615 + - type: recall_at_100 + value: 91.563 + - type: recall_at_1000 + value: 97.52300000000001 + - type: recall_at_3 + value: 53.203 + - type: recall_at_5 + value: 62.836000000000006 + - task: + type: PairClassification + dataset: + type: C-MTEB/OCNLI + name: MTEB Ocnli + config: default + split: validation + revision: None + metrics: + - type: cos_sim_accuracy + value: 67.94802382241473 + - type: cos_sim_ap + value: 72.1545049768353 + - type: cos_sim_f1 + value: 71.24658780709737 + - type: cos_sim_precision + value: 62.589928057553955 + - type: cos_sim_recall + value: 82.68215417106653 + - type: dot_accuracy + value: 63.56253383865729 + - type: dot_ap + value: 66.5298825401086 + - type: dot_f1 + value: 69.31953840031835 + - type: dot_precision + value: 55.61941251596424 + - type: dot_recall + value: 91.97465681098205 + - type: euclidean_accuracy + value: 69.46399566865186 + - type: euclidean_ap + value: 73.63177936887436 + - type: euclidean_f1 + value: 72.91028446389497 + - type: euclidean_precision + value: 62.25710014947683 + - type: euclidean_recall + value: 87.96198521647307 + - type: manhattan_accuracy + value: 69.89713048186248 + - type: manhattan_ap + value: 74.11555425121965 + - type: manhattan_f1 + value: 72.8923476005188 + - type: manhattan_precision + value: 61.71303074670571 + - type: manhattan_recall + value: 89.01795142555439 + - type: max_accuracy + value: 69.89713048186248 + - type: max_ap + value: 74.11555425121965 + - type: max_f1 + value: 72.91028446389497 + - task: + type: Classification + dataset: + type: C-MTEB/OnlineShopping-classification + name: MTEB OnlineShopping + config: default + split: test + revision: None + metrics: + - type: accuracy + value: 90.93 + - type: ap + value: 88.66185083484555 + - type: f1 + value: 90.91685771516175 + - task: + type: STS + dataset: + type: C-MTEB/PAWSX + name: MTEB PAWSX + config: default + split: test + revision: None + metrics: + - type: cos_sim_pearson + value: 14.385178129184318 + - type: cos_sim_spearman + value: 17.246549728263478 + - type: euclidean_pearson + value: 18.921969136664913 + - type: euclidean_spearman + value: 17.245713577354014 + - type: manhattan_pearson + value: 18.98503959815216 + - type: manhattan_spearman + value: 17.37740013639568 + - task: + type: STS + dataset: + type: C-MTEB/QBQTC + name: MTEB QBQTC + config: default + split: test + revision: None + metrics: + - type: cos_sim_pearson + value: 32.04198138050403 + - type: cos_sim_spearman + value: 34.4844617563846 + - type: euclidean_pearson + value: 34.2634608256121 + - type: euclidean_spearman + value: 36.322207068208066 + - type: manhattan_pearson + value: 34.414939622012284 + - type: manhattan_spearman + value: 36.49437789416394 + - task: + type: Retrieval + dataset: + type: quora + name: MTEB QuoraRetrieval + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 70.858 + - type: map_at_10 + value: 84.516 + - type: map_at_100 + value: 85.138 + - type: map_at_1000 + value: 85.153 + - type: map_at_3 + value: 81.487 + - type: map_at_5 + value: 83.41199999999999 + - type: mrr_at_1 + value: 81.55 + - type: mrr_at_10 + value: 87.51400000000001 + - type: mrr_at_100 + value: 87.607 + - type: mrr_at_1000 + value: 87.60900000000001 + - type: mrr_at_3 + value: 86.49 + - type: mrr_at_5 + value: 87.21 + - type: ndcg_at_1 + value: 81.57 + - type: ndcg_at_10 + value: 88.276 + - type: ndcg_at_100 + value: 89.462 + - type: ndcg_at_1000 + value: 89.571 + - type: ndcg_at_3 + value: 85.294 + - type: ndcg_at_5 + value: 86.979 + - type: precision_at_1 + value: 81.57 + - type: precision_at_10 + value: 13.389999999999999 + - type: precision_at_100 + value: 1.532 + - type: precision_at_1000 + value: 0.157 + - type: precision_at_3 + value: 37.2 + - type: precision_at_5 + value: 24.544 + - type: recall_at_1 + value: 70.858 + - type: recall_at_10 + value: 95.428 + - type: recall_at_100 + value: 99.46000000000001 + - type: recall_at_1000 + value: 99.98 + - type: recall_at_3 + value: 86.896 + - type: recall_at_5 + value: 91.617 + - task: + type: Clustering + dataset: + type: mteb/reddit-clustering + name: MTEB RedditClustering + config: default + split: test + revision: 24640382cdbf8abc73003fb0fa6d111a705499eb + metrics: + - type: v_measure + value: 47.90089115942085 + - task: + type: Clustering + dataset: + type: mteb/reddit-clustering-p2p + name: MTEB RedditClusteringP2P + config: default + split: test + revision: 282350215ef01743dc01b456c7f5241fa8937f16 + metrics: + - type: v_measure + value: 55.948584594903515 + - task: + type: Retrieval + dataset: + type: scidocs + name: MTEB SCIDOCS + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 4.513 + - type: map_at_10 + value: 11.189 + - type: map_at_100 + value: 13.034 + - type: map_at_1000 + value: 13.312 + - type: map_at_3 + value: 8.124 + - type: map_at_5 + value: 9.719999999999999 + - type: mrr_at_1 + value: 22.1 + - type: mrr_at_10 + value: 32.879999999999995 + - type: mrr_at_100 + value: 33.916000000000004 + - type: mrr_at_1000 + value: 33.982 + - type: mrr_at_3 + value: 29.633 + - type: mrr_at_5 + value: 31.663000000000004 + - type: ndcg_at_1 + value: 22.1 + - type: ndcg_at_10 + value: 18.944 + - type: ndcg_at_100 + value: 26.240000000000002 + - type: ndcg_at_1000 + value: 31.282 + - type: ndcg_at_3 + value: 18.17 + - type: ndcg_at_5 + value: 15.976 + - type: precision_at_1 + value: 22.1 + - type: precision_at_10 + value: 9.700000000000001 + - type: precision_at_100 + value: 2.025 + - type: precision_at_1000 + value: 0.32299999999999995 + - type: precision_at_3 + value: 16.933 + - type: precision_at_5 + value: 14.02 + - type: recall_at_1 + value: 4.513 + - type: recall_at_10 + value: 19.723 + - type: recall_at_100 + value: 41.117 + - type: recall_at_1000 + value: 65.718 + - type: recall_at_3 + value: 10.333 + - type: recall_at_5 + value: 14.252 + - task: + type: STS + dataset: + type: mteb/sickr-sts + name: MTEB SICK-R + config: default + split: test + revision: a6ea5a8cab320b040a23452cc28066d9beae2cee + metrics: + - type: cos_sim_pearson + value: 85.93526522406187 + - type: cos_sim_spearman + value: 81.4067321748142 + - type: euclidean_pearson + value: 82.23783344725466 + - type: euclidean_spearman + value: 80.88990344685583 + - type: manhattan_pearson + value: 82.3367264631989 + - type: manhattan_spearman + value: 80.9278067738814 + - task: + type: STS + dataset: + type: mteb/sts12-sts + name: MTEB STS12 + config: default + split: test + revision: a0d554a64d88156834ff5ae9920b964011b16384 + metrics: + - type: cos_sim_pearson + value: 85.23458296088118 + - type: cos_sim_spearman + value: 77.47310329678291 + - type: euclidean_pearson + value: 83.73584591194671 + - type: euclidean_spearman + value: 80.15616176452284 + - type: manhattan_pearson + value: 84.03063128849925 + - type: manhattan_spearman + value: 80.36472448270416 + - task: + type: STS + dataset: + type: mteb/sts13-sts + name: MTEB STS13 + config: default + split: test + revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca + metrics: + - type: cos_sim_pearson + value: 86.11807249122802 + - type: cos_sim_spearman + value: 86.37854318479079 + - type: euclidean_pearson + value: 86.65850909046301 + - type: euclidean_spearman + value: 87.85344963531178 + - type: manhattan_pearson + value: 86.77920459868837 + - type: manhattan_spearman + value: 87.97331161741792 + - task: + type: STS + dataset: + type: mteb/sts14-sts + name: MTEB STS14 + config: default + split: test + revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 + metrics: + - type: cos_sim_pearson + value: 84.4649953305265 + - type: cos_sim_spearman + value: 81.17166984686445 + - type: euclidean_pearson + value: 82.36880883967271 + - type: euclidean_spearman + value: 81.28206358558401 + - type: manhattan_pearson + value: 82.56994704487155 + - type: manhattan_spearman + value: 81.52094918949243 + - task: + type: STS + dataset: + type: mteb/sts15-sts + name: MTEB STS15 + config: default + split: test + revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 + metrics: + - type: cos_sim_pearson + value: 87.5328930220188 + - type: cos_sim_spearman + value: 88.23398394823562 + - type: euclidean_pearson + value: 88.0817998861656 + - type: euclidean_spearman + value: 88.68995789914679 + - type: manhattan_pearson + value: 88.11885742601258 + - type: manhattan_spearman + value: 88.7318106493293 + - task: + type: STS + dataset: + type: mteb/sts16-sts + name: MTEB STS16 + config: default + split: test + revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 + metrics: + - type: cos_sim_pearson + value: 84.81883368511858 + - type: cos_sim_spearman + value: 86.28679308000675 + - type: euclidean_pearson + value: 84.33705182713047 + - type: euclidean_spearman + value: 84.83018555455023 + - type: manhattan_pearson + value: 84.3271850394614 + - type: manhattan_spearman + value: 84.77974015415639 + - task: + type: STS + dataset: + type: mteb/sts17-crosslingual-sts + name: MTEB STS17 (en-en) + config: en-en + split: test + revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d + metrics: + - type: cos_sim_pearson + value: 90.71845282522295 + - type: cos_sim_spearman + value: 90.6215253553308 + - type: euclidean_pearson + value: 89.486847313806 + - type: euclidean_spearman + value: 89.11692037511729 + - type: manhattan_pearson + value: 89.53911733450684 + - type: manhattan_spearman + value: 89.2507288145461 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (en) + config: en + split: test + revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 + metrics: + - type: cos_sim_pearson + value: 65.81961557635002 + - type: cos_sim_spearman + value: 65.01437718770094 + - type: euclidean_pearson + value: 66.53720271639384 + - type: euclidean_spearman + value: 65.66538718470727 + - type: manhattan_pearson + value: 66.85160833477023 + - type: manhattan_spearman + value: 65.86253623736344 + - task: + type: STS + dataset: + type: C-MTEB/STSB + name: MTEB STSB + config: default + split: test + revision: None + metrics: + - type: cos_sim_pearson + value: 81.74904608584143 + - type: cos_sim_spearman + value: 82.02672847550606 + - type: euclidean_pearson + value: 81.47843718306068 + - type: euclidean_spearman + value: 81.7259314292303 + - type: manhattan_pearson + value: 81.70320276859634 + - type: manhattan_spearman + value: 81.94903024173293 + - task: + type: STS + dataset: + type: mteb/stsbenchmark-sts + name: MTEB STSBenchmark + config: default + split: test + revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 + metrics: + - type: cos_sim_pearson + value: 87.37129233774877 + - type: cos_sim_spearman + value: 88.02311088852667 + - type: euclidean_pearson + value: 85.864664021262 + - type: euclidean_spearman + value: 86.24775921494894 + - type: manhattan_pearson + value: 85.85401868812795 + - type: manhattan_spearman + value: 86.22999105137849 + - task: + type: Reranking + dataset: + type: mteb/scidocs-reranking + name: MTEB SciDocsRR + config: default + split: test + revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab + metrics: + - type: map + value: 80.2684105571225 + - type: mrr + value: 94.3528194753685 + - task: + type: Retrieval + dataset: + type: scifact + name: MTEB SciFact + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 55.161 + - type: map_at_10 + value: 64.794 + - type: map_at_100 + value: 65.66499999999999 + - type: map_at_1000 + value: 65.684 + - type: map_at_3 + value: 62.326 + - type: map_at_5 + value: 63.863 + - type: mrr_at_1 + value: 58.333 + - type: mrr_at_10 + value: 66.396 + - type: mrr_at_100 + value: 67.07300000000001 + - type: mrr_at_1000 + value: 67.092 + - type: mrr_at_3 + value: 64.61099999999999 + - type: mrr_at_5 + value: 65.744 + - type: ndcg_at_1 + value: 58.333 + - type: ndcg_at_10 + value: 69.294 + - type: ndcg_at_100 + value: 72.612 + - type: ndcg_at_1000 + value: 73.083 + - type: ndcg_at_3 + value: 65.226 + - type: ndcg_at_5 + value: 67.44 + - type: precision_at_1 + value: 58.333 + - type: precision_at_10 + value: 9.2 + - type: precision_at_100 + value: 1.083 + - type: precision_at_1000 + value: 0.11199999999999999 + - type: precision_at_3 + value: 25.667 + - type: precision_at_5 + value: 16.866999999999997 + - type: recall_at_1 + value: 55.161 + - type: recall_at_10 + value: 81.289 + - type: recall_at_100 + value: 95.333 + - type: recall_at_1000 + value: 99.0 + - type: recall_at_3 + value: 70.45 + - type: recall_at_5 + value: 76.128 + - task: + type: PairClassification + dataset: + type: mteb/sprintduplicatequestions-pairclassification + name: MTEB SprintDuplicateQuestions + config: default + split: test + revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 + metrics: + - type: cos_sim_accuracy + value: 99.81980198019802 + - type: cos_sim_ap + value: 95.61939598272275 + - type: cos_sim_f1 + value: 91.00684261974584 + - type: cos_sim_precision + value: 89.0057361376673 + - type: cos_sim_recall + value: 93.10000000000001 + - type: dot_accuracy + value: 99.78910891089109 + - type: dot_ap + value: 94.52852299178002 + - type: dot_f1 + value: 89.2586989409985 + - type: dot_precision + value: 90.03051881993896 + - type: dot_recall + value: 88.5 + - type: euclidean_accuracy + value: 99.81782178217821 + - type: euclidean_ap + value: 95.41313424258671 + - type: euclidean_f1 + value: 90.91806515301086 + - type: euclidean_precision + value: 89.76608187134502 + - type: euclidean_recall + value: 92.10000000000001 + - type: manhattan_accuracy + value: 99.81584158415842 + - type: manhattan_ap + value: 95.52722650384223 + - type: manhattan_f1 + value: 90.86444007858546 + - type: manhattan_precision + value: 89.28571428571429 + - type: manhattan_recall + value: 92.5 + - type: max_accuracy + value: 99.81980198019802 + - type: max_ap + value: 95.61939598272275 + - type: max_f1 + value: 91.00684261974584 + - task: + type: Clustering + dataset: + type: mteb/stackexchange-clustering + name: MTEB StackExchangeClustering + config: default + split: test + revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 + metrics: + - type: v_measure + value: 60.2736951820551 + - task: + type: Clustering + dataset: + type: mteb/stackexchange-clustering-p2p + name: MTEB StackExchangeClusteringP2P + config: default + split: test + revision: 815ca46b2622cec33ccafc3735d572c266efdb44 + metrics: + - type: v_measure + value: 32.34316824844043 + - task: + type: Reranking + dataset: + type: mteb/stackoverflowdupquestions-reranking + name: MTEB StackOverflowDupQuestions + config: default + split: test + revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 + metrics: + - type: map + value: 50.55034024386463 + - type: mrr + value: 51.468598803157626 + - task: + type: Summarization + dataset: + type: mteb/summeval + name: MTEB SummEval + config: default + split: test + revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c + metrics: + - type: cos_sim_pearson + value: 31.20772719310616 + - type: cos_sim_spearman + value: 30.966269993937523 + - type: dot_pearson + value: 30.866563682880965 + - type: dot_spearman + value: 29.906699130890875 + - task: + type: Reranking + dataset: + type: C-MTEB/T2Reranking + name: MTEB T2Reranking + config: default + split: dev + revision: None + metrics: + - type: map + value: 67.87990805824984 + - type: mrr + value: 78.16078682657897 + - task: + type: Retrieval + dataset: + type: C-MTEB/T2Retrieval + name: MTEB T2Retrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 26.009 + - type: map_at_10 + value: 71.319 + - type: map_at_100 + value: 74.895 + - type: map_at_1000 + value: 74.995 + - type: map_at_3 + value: 50.778 + - type: map_at_5 + value: 62.00599999999999 + - type: mrr_at_1 + value: 87.41 + - type: mrr_at_10 + value: 90.18599999999999 + - type: mrr_at_100 + value: 90.29700000000001 + - type: mrr_at_1000 + value: 90.302 + - type: mrr_at_3 + value: 89.701 + - type: mrr_at_5 + value: 89.992 + - type: ndcg_at_1 + value: 87.41 + - type: ndcg_at_10 + value: 79.822 + - type: ndcg_at_100 + value: 83.877 + - type: ndcg_at_1000 + value: 84.882 + - type: ndcg_at_3 + value: 82.391 + - type: ndcg_at_5 + value: 80.339 + - type: precision_at_1 + value: 87.41 + - type: precision_at_10 + value: 39.546 + - type: precision_at_100 + value: 4.824 + - type: precision_at_1000 + value: 0.507 + - type: precision_at_3 + value: 72.129 + - type: precision_at_5 + value: 59.915 + - type: recall_at_1 + value: 26.009 + - type: recall_at_10 + value: 78.144 + - type: recall_at_100 + value: 91.375 + - type: recall_at_1000 + value: 96.42399999999999 + - type: recall_at_3 + value: 52.529 + - type: recall_at_5 + value: 65.46 + - task: + type: Classification + dataset: + type: C-MTEB/TNews-classification + name: MTEB TNews + config: default + split: validation + revision: None + metrics: + - type: accuracy + value: 47.803000000000004 + - type: f1 + value: 46.298520969605775 + - task: + type: Retrieval + dataset: + type: trec-covid + name: MTEB TRECCOVID + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 0.252 + - type: map_at_10 + value: 2.181 + - type: map_at_100 + value: 12.82 + - type: map_at_1000 + value: 30.307000000000002 + - type: map_at_3 + value: 0.716 + - type: map_at_5 + value: 1.133 + - type: mrr_at_1 + value: 96.0 + - type: mrr_at_10 + value: 98.0 + - type: mrr_at_100 + value: 98.0 + - type: mrr_at_1000 + value: 98.0 + - type: mrr_at_3 + value: 98.0 + - type: mrr_at_5 + value: 98.0 + - type: ndcg_at_1 + value: 92.0 + - type: ndcg_at_10 + value: 83.818 + - type: ndcg_at_100 + value: 63.327999999999996 + - type: ndcg_at_1000 + value: 55.883 + - type: ndcg_at_3 + value: 87.16199999999999 + - type: ndcg_at_5 + value: 85.03 + - type: precision_at_1 + value: 96.0 + - type: precision_at_10 + value: 88.0 + - type: precision_at_100 + value: 64.94 + - type: precision_at_1000 + value: 24.688 + - type: precision_at_3 + value: 91.333 + - type: precision_at_5 + value: 88.8 + - type: recall_at_1 + value: 0.252 + - type: recall_at_10 + value: 2.326 + - type: recall_at_100 + value: 15.665000000000001 + - type: recall_at_1000 + value: 52.559999999999995 + - type: recall_at_3 + value: 0.735 + - type: recall_at_5 + value: 1.175 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (sqi-eng) + config: sqi-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 19.0 + - type: f1 + value: 15.331629955575188 + - type: precision + value: 14.38509724403208 + - type: recall + value: 19.0 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (fry-eng) + config: fry-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 39.884393063583815 + - type: f1 + value: 32.369942196531795 + - type: precision + value: 30.036929993577395 + - type: recall + value: 39.884393063583815 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (kur-eng) + config: kur-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 15.365853658536585 + - type: f1 + value: 12.49755078527547 + - type: precision + value: 11.840415442997939 + - type: recall + value: 15.365853658536585 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (tur-eng) + config: tur-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 11.1 + - type: f1 + value: 8.955359175928436 + - type: precision + value: 8.324461412770235 + - type: recall + value: 11.1 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (deu-eng) + config: deu-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 87.7 + - type: f1 + value: 85.06214285714286 + - type: precision + value: 83.98761904761905 + - type: recall + value: 87.7 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (nld-eng) + config: nld-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 56.00000000000001 + - type: f1 + value: 49.8456850459482 + - type: precision + value: 47.80084415584415 + - type: recall + value: 56.00000000000001 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (ron-eng) + config: ron-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 38.1 + - type: f1 + value: 33.85465329991646 + - type: precision + value: 32.37519841269841 + - type: recall + value: 38.1 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (ang-eng) + config: ang-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 42.53731343283582 + - type: f1 + value: 34.67903986560703 + - type: precision + value: 32.17128642501776 + - type: recall + value: 42.53731343283582 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (ido-eng) + config: ido-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 53.900000000000006 + - type: f1 + value: 47.83909812409812 + - type: precision + value: 45.67887667887668 + - type: recall + value: 53.900000000000006 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (jav-eng) + config: jav-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - type: accuracy + value: 26.34146341463415 + - type: f1 + value: 22.264125162260022 + - type: precision + value: 21.384015912351636 + - type: recall + value: 26.34146341463415 + - task: + type: BitextMining + dataset: + type: mteb/tatoeba-bitext-mining + name: MTEB Tatoeba (isl-eng) + config: isl-eng + split: test + revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 + metrics: + - 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type: v_measure + value: 49.19154423543331 + - task: + type: Clustering + dataset: + type: C-MTEB/ThuNewsClusteringS2S + name: MTEB ThuNewsClusteringS2S + config: default + split: test + revision: None + metrics: + - type: v_measure + value: 47.76345036893387 + - task: + type: Retrieval + dataset: + type: webis-touche2020 + name: MTEB Touche2020 + config: default + split: test + revision: None + metrics: + - type: map_at_1 + value: 2.396 + - type: map_at_10 + value: 9.994 + - type: map_at_100 + value: 16.067999999999998 + - type: map_at_1000 + value: 17.59 + - type: map_at_3 + value: 4.733 + - type: map_at_5 + value: 6.7589999999999995 + - type: mrr_at_1 + value: 28.571 + - type: mrr_at_10 + value: 47.678 + - type: mrr_at_100 + value: 48.311 + - type: mrr_at_1000 + value: 48.317 + - type: mrr_at_3 + value: 43.878 + - type: mrr_at_5 + value: 46.224 + - type: ndcg_at_1 + value: 25.509999999999998 + - type: ndcg_at_10 + value: 25.189 + - type: ndcg_at_100 + value: 36.179 + - type: ndcg_at_1000 + value: 47.562 + - type: ndcg_at_3 + value: 26.858999999999998 + - type: ndcg_at_5 + value: 26.825 + - type: precision_at_1 + value: 28.571 + - type: precision_at_10 + value: 23.469 + - type: precision_at_100 + value: 7.550999999999999 + - type: precision_at_1000 + value: 1.51 + - type: precision_at_3 + value: 29.252 + - type: precision_at_5 + value: 28.571 + - type: recall_at_1 + value: 2.396 + - type: recall_at_10 + value: 16.551 + - type: recall_at_100 + value: 46.438 + - type: recall_at_1000 + value: 81.04 + - type: recall_at_3 + value: 6.145 + - type: recall_at_5 + value: 9.728 + - task: + type: Classification + dataset: + type: mteb/toxic_conversations_50k + name: MTEB ToxicConversationsClassification + config: default + split: test + revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c + metrics: + - type: accuracy + value: 71.5842 + - type: ap + value: 14.770823761227014 + - type: f1 + value: 55.22772349179383 + - task: + type: Classification + dataset: + type: mteb/tweet_sentiment_extraction + name: MTEB TweetSentimentExtractionClassification + config: default + split: test + revision: d604517c81ca91fe16a244d1248fc021f9ecee7a + metrics: + - type: accuracy + value: 62.13921901528015 + - type: f1 + value: 62.450042974251694 + - task: + type: Clustering + dataset: + type: mteb/twentynewsgroups-clustering + name: MTEB TwentyNewsgroupsClustering + config: default + split: test + revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 + metrics: + - type: v_measure + value: 40.81463922932671 + - task: + type: PairClassification + dataset: + type: mteb/twittersemeval2015-pairclassification + name: MTEB TwitterSemEval2015 + config: default + split: test + revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 + metrics: + - type: cos_sim_accuracy + value: 85.86755677415509 + - type: cos_sim_ap + value: 73.8131664470889 + - type: cos_sim_f1 + value: 68.03196803196803 + - type: cos_sim_precision + value: 64.58036984352773 + - type: cos_sim_recall + value: 71.87335092348285 + - type: dot_accuracy + value: 84.58604041246946 + - type: dot_ap + value: 69.43165607336826 + - type: dot_f1 + value: 65.84285381207741 + - type: dot_precision + value: 58.980785296574766 + - type: dot_recall + value: 74.51187335092348 + - type: euclidean_accuracy + value: 85.60529296060082 + - type: euclidean_ap + value: 72.48939155702391 + - type: euclidean_f1 + value: 66.84775898259045 + - type: euclidean_precision + value: 62.822000464144814 + - type: euclidean_recall + value: 71.42480211081794 + - type: manhattan_accuracy + value: 85.5456875484294 + - type: manhattan_ap + value: 72.37178636434892 + - type: manhattan_f1 + value: 66.6751398068124 + - type: manhattan_precision + value: 64.32074546346249 + - type: manhattan_recall + value: 69.2084432717678 + - type: max_accuracy + value: 85.86755677415509 + - type: max_ap + value: 73.8131664470889 + - type: max_f1 + value: 68.03196803196803 + - task: + type: PairClassification + dataset: + type: mteb/twitterurlcorpus-pairclassification + name: MTEB TwitterURLCorpus + config: default + split: test + revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf + metrics: + - type: cos_sim_accuracy + value: 89.39341017580627 + - type: cos_sim_ap + value: 86.7769866448429 + - type: cos_sim_f1 + value: 79.26586570354536 + - type: cos_sim_precision + value: 76.02149017390076 + - type: cos_sim_recall + value: 82.79950723744996 + - type: dot_accuracy + value: 89.15861373074087 + - type: dot_ap + value: 85.15235322715995 + - type: dot_f1 + value: 78.97118887294403 + - type: dot_precision + value: 75.6290083867785 + - type: dot_recall + value: 82.62242069602709 + - type: euclidean_accuracy + value: 89.0266620095471 + - type: euclidean_ap + value: 86.18904940615533 + - type: euclidean_f1 + value: 78.37750135208222 + - type: euclidean_precision + value: 73.70312605953754 + - type: euclidean_recall + value: 83.68493994456422 + - type: manhattan_accuracy + value: 88.98397174680794 + - type: manhattan_ap + value: 86.18302538523727 + - type: manhattan_f1 + value: 78.42197035745423 + - type: manhattan_precision + value: 74.23658872077029 + - type: manhattan_recall + value: 83.10748383122882 + - type: max_accuracy + value: 89.39341017580627 + - type: max_ap + value: 86.7769866448429 + - type: max_f1 + value: 79.26586570354536 + - task: + type: Retrieval + dataset: + type: C-MTEB/VideoRetrieval + name: MTEB VideoRetrieval + config: default + split: dev + revision: None + metrics: + - type: map_at_1 + value: 46.9 + - type: map_at_10 + value: 57.399 + - type: map_at_100 + value: 57.976000000000006 + - type: map_at_1000 + value: 58.00300000000001 + - type: map_at_3 + value: 54.967 + - type: map_at_5 + value: 56.562 + - type: mrr_at_1 + value: 46.800000000000004 + - type: mrr_at_10 + value: 57.349000000000004 + - type: mrr_at_100 + value: 57.926 + - type: mrr_at_1000 + value: 57.952999999999996 + - type: mrr_at_3 + value: 54.917 + - type: mrr_at_5 + value: 56.51199999999999 + - type: ndcg_at_1 + value: 46.9 + - type: ndcg_at_10 + value: 62.437 + - type: ndcg_at_100 + value: 65.273 + - type: ndcg_at_1000 + value: 65.999 + - type: ndcg_at_3 + value: 57.524 + - type: ndcg_at_5 + value: 60.402 + - type: precision_at_1 + value: 46.9 + - type: precision_at_10 + value: 7.82 + - type: precision_at_100 + value: 0.915 + - type: precision_at_1000 + value: 0.097 + - type: precision_at_3 + value: 21.633 + - type: precision_at_5 + value: 14.38 + - type: recall_at_1 + value: 46.9 + - type: recall_at_10 + value: 78.2 + - type: recall_at_100 + value: 91.5 + - type: recall_at_1000 + value: 97.2 + - type: recall_at_3 + value: 64.9 + - type: recall_at_5 + value: 71.89999999999999 + - task: + type: Classification + dataset: + type: C-MTEB/waimai-classification + name: MTEB Waimai + config: default + split: test + revision: None + metrics: + - type: accuracy + value: 84.68 + - type: ap + value: 66.4749730574293 + - type: f1 + value: 82.93606561551698 --- +# Model Card for udever-bloom + + + +`udever-bloom-7b1` is finetuned from [bigscience/bloom-7b1](https://huggingface.co/bigscience/bloom-7b1) via [BitFit](https://aclanthology.org/2022.acl-short.1/) on MS MARCO Passage Ranking, SNLI and MultiNLI data. +It is a universal embedding model across tasks, natural and programming languages. +(From the technical view, `udever` is merely with some minor improvements to `sgpt-bloom`) + + + + +## Model Details + +### Model Description + +- **Developed by:** Alibaba Group +- **Model type:** Transformer-based Language Model (decoder-only) +- **Language(s) (NLP):** Multiple; see [bloom training data](https://huggingface.co/bigscience/bloom-7b1#training-data) +- **Finetuned from model :** [bigscience/bloom-7b1](https://huggingface.co/bigscience/bloom-7b1) + +### Model Sources + + + +- **Repository:** [github.com/izhx/uni-rep](https://github.com/izhx/uni-rep) +- **Paper :** [Language Models are Universal Embedders](https://arxiv.org/pdf/2310.08232.pdf) +- **Training Date :** 2023-06 + + +### Checkpoints + - [udever-bloom-560m](https://huggingface.co/izhx/udever-bloom-560m) + - [udever-bloom-1b1](https://huggingface.co/izhx/udever-bloom-1b1) + - [udever-bloom-3b](https://huggingface.co/izhx/udever-bloom-3b) + - [udever-bloom-7b1](https://huggingface.co/izhx/udever-bloom-7b1) + +On ModelScope / 魔搭社区: [udever-bloom-560m](https://modelscope.cn/models/damo/udever-bloom-560m), [udever-bloom-1b1](https://modelscope.cn/models/damo/udever-bloom-1b1), [udever-bloom-3b](https://modelscope.cn/models/damo/udever-bloom-3b), [udever-bloom-7b1](https://modelscope.cn/models/damo/udever-bloom-7b1) + + +## How to Get Started with the Model + +Use the code below to get started with the model. + +```python +import torch +from transformers import AutoTokenizer, BloomModel + +tokenizer = AutoTokenizer.from_pretrained('izhx/udever-bloom-7b1') +model = BloomModel.from_pretrained('izhx/udever-bloom-7b1') + +boq, eoq, bod, eod = '[BOQ]', '[EOQ]', '[BOD]', '[EOD]' +eoq_id, eod_id = tokenizer.convert_tokens_to_ids([eoq, eod]) + +if tokenizer.padding_side != 'left': + print('!!!', tokenizer.padding_side) + tokenizer.padding_side = 'left' + + +def encode(texts: list, is_query: bool = True, max_length=300): + bos = boq if is_query else bod + eos_id = eoq_id if is_query else eod_id + texts = [bos + t for t in texts] + encoding = tokenizer( + texts, truncation=True, max_length=max_length - 1, padding=True + ) + for ids, mask in zip(encoding['input_ids'], encoding['attention_mask']): + ids.append(eos_id) + mask.append(1) + inputs = tokenizer.pad(encoding, return_tensors='pt') + with torch.inference_mode(): + outputs = model(**inputs) + embeds = outputs.last_hidden_state[:, -1] + return embeds + +encode(['I am Bert', 'You are Elmo']) + +``` + +## Training Details + +### Training Data + + + +- MS MARCO Passage Ranking, retrieved by (https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/ms_marco/train_bi-encoder_mnrl.py#L86) +- SNLI and MultiNLI (https://sbert.net/datasets/AllNLI.tsv.gz) + + +### Training Procedure + + + +#### Preprocessing + +MS MARCO hard negatives provided by (https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/ms_marco/train_bi-encoder_mnrl.py#L86). +Negatives for SNLI and MultiNLI are randomly sampled. + + +#### Training Hyperparameters + +- **Training regime:** tf32, BitFit +- **Batch size:** 1024 +- **Epochs:** 3 +- **Optimizer:** AdamW +- **Learning rate:** 1e-4 +- **Scheduler:** constant with warmup. +- **Warmup:** 0.25 epoch + + +## Evaluation + +### Table 1: Massive Text Embedding Benchmark [MTEB](https://huggingface.co/spaces/mteb/leaderboard) + +| MTEB | Avg. | Class. | Clust. | PairClass. | Rerank. | Retr. | STS | Summ. | +|-----------------------------|--------------|--------------|--------------|--------------|--------------|--------------|--------------|--------| +| #Datasets ➡️ | 56 | 12 | 11 | 3 | 4 | 15 | 10 | 1 | +|| +| bge-large-en-v1.5 | **64.23** | **75.97** | 46.08| **87.12** | **60.03** | **54.29** | 83.11| 31.61 | +| bge-base-en-v1.5 | 63.55| 75.53| 45.77| 86.55| 58.86| 53.25| 82.4| 31.07 | +| gte-large | 63.13| 73.33| **46.84** | 85| 59.13| 52.22| **83.35** | 31.66 | +| gte-base | 62.39| 73.01| 46.2| 84.57| 58.61| 51.14| 82.3| 31.17 | +| e5-large-v2 | 62.25| 75.24| 44.49| 86.03| 56.61| 50.56| 82.05| 30.19 | +| instructor-xl | 61.79| 73.12| 44.74| 86.62| 57.29| 49.26| 83.06| 32.32 | +| instructor-large | 61.59| 73.86| 45.29| 85.89| 57.54| 47.57| 83.15| 31.84 | +| e5-base-v2 | 61.5 | 73.84| 43.8| 85.73| 55.91| 50.29| 81.05| 30.28 | +| e5-large | 61.42| 73.14| 43.33| 85.94| 56.53| 49.99| 82.06| 30.97 | +| text-embedding-ada-002 (OpenAI API) | 60.99| 70.93| 45.9 | 84.89| 56.32| 49.25| 80.97| 30.8 | +| e5-base | 60.44| 72.63| 42.11| 85.09| 55.7 | 48.75| 80.96| 31.01 | +| SGPT-5.8B-msmarco | 58.93| 68.13| 40.34| 82 | 56.56| 50.25| 78.1 | 31.46 | +| sgpt-bloom-7b1-msmarco | 57.59| 66.19| 38.93| 81.9 | 55.65| 48.22| 77.74| **33.6** | +|| +| Udever-bloom-560m | 55.80| 68.04| 36.89| 81.05| 52.60| 41.19| 79.93| 32.06 | +| Udever-bloom-1b1 | 58.28| 70.18| 39.11| 83.11| 54.28| 45.27| 81.52| 31.10 | +| Udever-bloom-3b | 59.86| 71.91| 40.74| 84.06| 54.90| 47.67| 82.37| 30.62 | +| Udever-bloom-7b1 | 60.63 | 72.13| 40.81| 85.40| 55.91| 49.34| 83.01| 30.97 | + + +### Table 2: [CodeSearchNet](https://github.com/github/CodeSearchNet) + +| CodeSearchNet | Go | Ruby | Python | Java | JS | PHP | Avg. | +|-|-|-|-|-|-|-|-| +| CodeBERT | 69.3 | 70.6 | 84.0 | 86.8 | 74.8 | 70.6 | 76.0 | +| GraphCodeBERT | 84.1 | 73.2 | 87.9 | 75.7 | 71.1 | 72.5 | 77.4 | +| cpt-code S | **97.7** | **86.3** | 99.8 | 94.0 | 86.0 | 96.7 | 93.4 | +| cpt-code M | 97.5 | 85.5 | **99.9** | **94.4** | **86.5** | **97.2** | **93.5** | +| sgpt-bloom-7b1-msmarco | 76.79 | 69.25 | 95.68 | 77.93 | 70.35 | 73.45 | 77.24 | +|| +| Udever-bloom-560m | 75.38 | 66.67 | 96.23 | 78.99 | 69.39 | 73.69 | 76.73 | +| Udever-bloom-1b1 | 78.76 | 72.85 | 97.67 | 82.77 | 74.38 | 78.97 | 80.90 | +| Udever-bloom-3b | 80.63 | 75.40 | 98.02 | 83.88 | 76.18 | 79.67 | 82.29 | +| Udever-bloom-7b1 | 79.37 | 76.59 | 98.38 | 84.68 | 77.49 | 80.03 | 82.76 | + + +### Table 3: Chinese multi-domain retrieval [Multi-cpr](https://dl.acm.org/doi/10.1145/3477495.3531736) + +| | | |E-commerce | | Entertainment video | | Medical | | +|--|--|--|--|--|--|--|--|--| +| Model | Train | Backbone | MRR@10 | Recall@1k | MRR@10 | Recall@1k | MRR@10 | Recall@1k | +|| +| BM25 | - | - | 0.225 | 0.815 | 0.225 | 0.780 | 0.187 | 0.482 | +| Doc2Query | - | - | 0.239 | 0.826 | 0.238 | 0.794 | 0.210 | 0.505 | +| DPR-1 | In-Domain | BERT | 0.270 | 0.921 | 0.254 | 0.934 | 0.327 | 0.747 | +| DPR-2 | In-Domain | BERT-CT | 0.289 | **0.926** | 0.263 | **0.935** | 0.339 | **0.769** | +| text-embedding-ada-002 | General | GPT | 0.183 | 0.825 | 0.159 | 0.786 | 0.245 | 0.593 | +| sgpt-bloom-7b1-msmarco | General | BLOOM | 0.242 | 0.840 | 0.227 | 0.829 | 0.311 | 0.675 | +|| + | Udever-bloom-560m | General | BLOOM | 0.156 | 0.802 | 0.149 | 0.749 | 0.245 | 0.571 | + | Udever-bloom-1b1 | General | BLOOM | 0.244 | 0.863 | 0.208 | 0.815 | 0.241 | 0.557 | + | Udever-bloom-3b | General | BLOOM | 0.267 | 0.871 | 0.228 | 0.836 | 0.288 | 0.619 | + | Udever-bloom-7b1 | General | BLOOM | **0.296** | 0.889 | **0.267** | 0.907 | **0.343** | 0.705 | + +#### More results refer to [paper](https://arxiv.org/pdf/2310.08232.pdf) section 3. + + + +## Technical Specifications + +### Model Architecture and Objective + +- Model: [bigscience/bloom-7b1](https://huggingface.co/bigscience/bloom-7b1). +- Objective: Constrastive loss with hard negatives (refer to [paper](https://arxiv.org/pdf/2310.08232.pdf) section 2.2). + + +### Compute Infrastructure + +- Nvidia A100 SXM4 80GB. +- torch 2.0.0, transformers 4.29.2. + + +## Citation + +**BibTeX:** + +```BibTeX +@article{zhang2023language, + title={Language Models are Universal Embedders}, + author={Zhang, Xin and Li, Zehan and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan and Zhang, Min}, + journal={arXiv preprint arXiv:2310.08232}, + year={2023} +} +```