--- pipeline_tag: text-generation inference: true license: apache-2.0 datasets: - GritLM/tulu2 tags: - mteb model-index: - name: GritLM-8x7B results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 80.47761194029852 - type: ap value: 44.38751347932197 - type: f1 value: 74.33580162208256 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 96.32155000000002 - type: ap value: 94.8026654593679 - type: f1 value: 96.3209869463974 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 57.18400000000001 - type: f1 value: 55.945160479400954 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 34.353 - type: map_at_10 value: 50.773 - type: map_at_100 value: 51.515 - type: map_at_1000 value: 51.517 - type: map_at_3 value: 46.29 - type: map_at_5 value: 48.914 - type: mrr_at_1 value: 35.135 - type: mrr_at_10 value: 51.036 - type: mrr_at_100 value: 51.785000000000004 - type: mrr_at_1000 value: 51.787000000000006 - type: mrr_at_3 value: 46.562 - type: mrr_at_5 value: 49.183 - type: ndcg_at_1 value: 34.353 - type: ndcg_at_10 value: 59.492 - type: ndcg_at_100 value: 62.395999999999994 - type: ndcg_at_1000 value: 62.44499999999999 - type: ndcg_at_3 value: 50.217 - type: ndcg_at_5 value: 54.98499999999999 - type: precision_at_1 value: 34.353 - type: precision_at_10 value: 8.72 - type: precision_at_100 value: 0.993 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 20.531 - type: precision_at_5 value: 14.651 - type: recall_at_1 value: 34.353 - type: recall_at_10 value: 87.198 - type: recall_at_100 value: 99.289 - type: recall_at_1000 value: 99.644 - type: recall_at_3 value: 61.592999999999996 - type: recall_at_5 value: 73.257 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 50.720077577006286 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 48.01021098734129 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 65.59672236627206 - type: mrr value: 78.01191575429802 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 89.52452252271826 - type: cos_sim_spearman value: 87.34415887061094 - type: euclidean_pearson value: 87.46187616533932 - type: euclidean_spearman value: 85.44712769366146 - type: manhattan_pearson value: 87.56696679505373 - type: manhattan_spearman value: 86.01581535039067 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 87.4577922077922 - type: f1 value: 87.38432712848123 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 41.41290357360428 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 38.67213605633667 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 37.545 - type: map_at_10 value: 50.015 - type: map_at_100 value: 51.763999999999996 - type: map_at_1000 value: 51.870000000000005 - type: map_at_3 value: 46.129999999999995 - type: map_at_5 value: 48.473 - type: mrr_at_1 value: 47.638999999999996 - type: mrr_at_10 value: 56.913000000000004 - type: mrr_at_100 value: 57.619 - type: mrr_at_1000 value: 57.648999999999994 - type: mrr_at_3 value: 54.435 - type: mrr_at_5 value: 56.059000000000005 - type: ndcg_at_1 value: 47.638999999999996 - type: ndcg_at_10 value: 56.664 - type: ndcg_at_100 value: 62.089000000000006 - type: ndcg_at_1000 value: 63.415 - type: ndcg_at_3 value: 51.842999999999996 - type: ndcg_at_5 value: 54.30199999999999 - type: precision_at_1 value: 47.638999999999996 - type: precision_at_10 value: 10.886999999999999 - type: precision_at_100 value: 1.722 - type: precision_at_1000 value: 0.212 - type: precision_at_3 value: 25.179000000000002 - type: precision_at_5 value: 18.226 - type: recall_at_1 value: 37.545 - type: recall_at_10 value: 68.118 - type: recall_at_100 value: 90.381 - type: recall_at_1000 value: 98.556 - type: recall_at_3 value: 53.319 - type: recall_at_5 value: 60.574 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 37.066 - type: map_at_10 value: 49.464000000000006 - type: map_at_100 value: 50.79900000000001 - type: map_at_1000 value: 50.928 - type: map_at_3 value: 46.133 - type: map_at_5 value: 47.941 - type: mrr_at_1 value: 48.025 - type: mrr_at_10 value: 56.16100000000001 - type: mrr_at_100 value: 56.725 - type: mrr_at_1000 value: 56.757000000000005 - type: mrr_at_3 value: 54.31 - type: mrr_at_5 value: 55.285 - type: ndcg_at_1 value: 48.025 - type: ndcg_at_10 value: 55.467 - type: ndcg_at_100 value: 59.391000000000005 - type: ndcg_at_1000 value: 61.086 - type: ndcg_at_3 value: 51.733 - type: ndcg_at_5 value: 53.223 - type: precision_at_1 value: 48.025 - type: precision_at_10 value: 10.656 - type: precision_at_100 value: 1.6070000000000002 - type: precision_at_1000 value: 0.20600000000000002 - type: precision_at_3 value: 25.499 - type: precision_at_5 value: 17.771 - type: recall_at_1 value: 37.066 - type: recall_at_10 value: 65.062 - type: recall_at_100 value: 81.662 - type: recall_at_1000 value: 91.913 - type: recall_at_3 value: 52.734 - type: recall_at_5 value: 57.696999999999996 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 46.099000000000004 - type: map_at_10 value: 59.721999999999994 - type: map_at_100 value: 60.675000000000004 - type: map_at_1000 value: 60.708 - type: map_at_3 value: 55.852000000000004 - type: map_at_5 value: 58.426 - type: mrr_at_1 value: 53.417 - type: mrr_at_10 value: 63.597 - type: mrr_at_100 value: 64.12299999999999 - type: mrr_at_1000 value: 64.13799999999999 - type: mrr_at_3 value: 61.149 - type: mrr_at_5 value: 62.800999999999995 - type: ndcg_at_1 value: 53.417 - type: ndcg_at_10 value: 65.90899999999999 - type: ndcg_at_100 value: 69.312 - type: ndcg_at_1000 value: 69.89 - type: ndcg_at_3 value: 60.089999999999996 - type: ndcg_at_5 value: 63.575 - type: precision_at_1 value: 53.417 - type: precision_at_10 value: 10.533 - type: precision_at_100 value: 1.313 - type: precision_at_1000 value: 0.13899999999999998 - type: precision_at_3 value: 26.667 - type: precision_at_5 value: 18.671 - type: recall_at_1 value: 46.099000000000004 - type: recall_at_10 value: 80.134 - type: recall_at_100 value: 94.536 - type: recall_at_1000 value: 98.543 - type: recall_at_3 value: 65.026 - type: recall_at_5 value: 73.462 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 28.261999999999997 - type: map_at_10 value: 38.012 - type: map_at_100 value: 39.104 - type: map_at_1000 value: 39.177 - type: map_at_3 value: 35.068 - type: map_at_5 value: 36.620000000000005 - type: mrr_at_1 value: 30.847 - type: mrr_at_10 value: 40.251999999999995 - type: mrr_at_100 value: 41.174 - type: mrr_at_1000 value: 41.227999999999994 - type: mrr_at_3 value: 37.74 - type: mrr_at_5 value: 38.972 - type: ndcg_at_1 value: 30.847 - type: ndcg_at_10 value: 43.513000000000005 - type: ndcg_at_100 value: 48.771 - type: ndcg_at_1000 value: 50.501 - type: ndcg_at_3 value: 37.861 - type: ndcg_at_5 value: 40.366 - type: precision_at_1 value: 30.847 - type: precision_at_10 value: 6.7909999999999995 - type: precision_at_100 value: 0.992 - type: precision_at_1000 value: 0.117 - type: precision_at_3 value: 16.234 - type: precision_at_5 value: 11.254 - type: recall_at_1 value: 28.261999999999997 - type: recall_at_10 value: 58.292 - type: recall_at_100 value: 82.24000000000001 - type: recall_at_1000 value: 95.042 - type: recall_at_3 value: 42.955 - type: recall_at_5 value: 48.973 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 18.281 - type: map_at_10 value: 27.687 - type: map_at_100 value: 28.9 - type: map_at_1000 value: 29.019000000000002 - type: map_at_3 value: 24.773 - type: map_at_5 value: 26.180999999999997 - type: mrr_at_1 value: 23.01 - type: mrr_at_10 value: 32.225 - type: mrr_at_100 value: 33.054 - type: mrr_at_1000 value: 33.119 - type: mrr_at_3 value: 29.353 - type: mrr_at_5 value: 30.846 - type: ndcg_at_1 value: 23.01 - type: ndcg_at_10 value: 33.422000000000004 - type: ndcg_at_100 value: 39.108 - type: ndcg_at_1000 value: 41.699999999999996 - type: ndcg_at_3 value: 28.083999999999996 - type: ndcg_at_5 value: 30.164 - type: precision_at_1 value: 23.01 - type: precision_at_10 value: 6.493 - type: precision_at_100 value: 1.077 - type: precision_at_1000 value: 0.14100000000000001 - type: precision_at_3 value: 13.930000000000001 - type: precision_at_5 value: 10.075000000000001 - type: recall_at_1 value: 18.281 - type: recall_at_10 value: 46.318 - type: recall_at_100 value: 71.327 - type: recall_at_1000 value: 89.716 - type: recall_at_3 value: 31.517 - type: recall_at_5 value: 36.821 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 36.575 - type: map_at_10 value: 49.235 - type: map_at_100 value: 50.723 - type: map_at_1000 value: 50.809000000000005 - type: map_at_3 value: 45.696999999999996 - type: map_at_5 value: 47.588 - type: mrr_at_1 value: 45.525 - type: mrr_at_10 value: 55.334 - type: mrr_at_100 value: 56.092 - type: mrr_at_1000 value: 56.118 - type: mrr_at_3 value: 53.032000000000004 - type: mrr_at_5 value: 54.19199999999999 - type: ndcg_at_1 value: 45.525 - type: ndcg_at_10 value: 55.542 - type: ndcg_at_100 value: 60.879000000000005 - type: ndcg_at_1000 value: 62.224999999999994 - type: ndcg_at_3 value: 50.688 - type: ndcg_at_5 value: 52.76499999999999 - type: precision_at_1 value: 45.525 - type: precision_at_10 value: 10.067 - type: precision_at_100 value: 1.471 - type: precision_at_1000 value: 0.173 - type: precision_at_3 value: 24.382 - type: precision_at_5 value: 16.919999999999998 - type: recall_at_1 value: 36.575 - type: recall_at_10 value: 67.903 - type: recall_at_100 value: 89.464 - type: recall_at_1000 value: 97.799 - type: recall_at_3 value: 53.493 - type: recall_at_5 value: 59.372 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 29.099000000000004 - type: map_at_10 value: 42.147 - type: map_at_100 value: 43.522 - type: map_at_1000 value: 43.624 - type: map_at_3 value: 38.104 - type: map_at_5 value: 40.435 - type: mrr_at_1 value: 36.416 - type: mrr_at_10 value: 47.922 - type: mrr_at_100 value: 48.664 - type: mrr_at_1000 value: 48.709 - type: mrr_at_3 value: 44.977000000000004 - type: mrr_at_5 value: 46.838 - type: ndcg_at_1 value: 36.416 - type: ndcg_at_10 value: 49.307 - type: ndcg_at_100 value: 54.332 - type: ndcg_at_1000 value: 56.145 - type: ndcg_at_3 value: 42.994 - type: ndcg_at_5 value: 46.119 - type: precision_at_1 value: 36.416 - type: precision_at_10 value: 9.452 - type: precision_at_100 value: 1.4080000000000001 - type: precision_at_1000 value: 0.172 - type: precision_at_3 value: 21.081 - type: precision_at_5 value: 15.501999999999999 - type: recall_at_1 value: 29.099000000000004 - type: recall_at_10 value: 64.485 - type: recall_at_100 value: 84.753 - type: recall_at_1000 value: 96.875 - type: recall_at_3 value: 47.06 - type: recall_at_5 value: 55.077 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 30.69458333333333 - type: map_at_10 value: 41.65291666666666 - type: map_at_100 value: 42.95775 - type: map_at_1000 value: 43.06258333333333 - type: map_at_3 value: 38.335750000000004 - type: map_at_5 value: 40.20941666666666 - type: mrr_at_1 value: 37.013000000000005 - type: mrr_at_10 value: 46.30600000000001 - type: mrr_at_100 value: 47.094666666666676 - type: mrr_at_1000 value: 47.139583333333334 - type: mrr_at_3 value: 43.805749999999996 - type: mrr_at_5 value: 45.22366666666666 - type: ndcg_at_1 value: 37.013000000000005 - type: ndcg_at_10 value: 47.63491666666667 - type: ndcg_at_100 value: 52.71083333333334 - type: ndcg_at_1000 value: 54.493583333333326 - type: ndcg_at_3 value: 42.43616666666666 - type: ndcg_at_5 value: 44.87583333333334 - type: precision_at_1 value: 37.013000000000005 - type: precision_at_10 value: 8.481583333333333 - type: precision_at_100 value: 1.3073333333333337 - type: precision_at_1000 value: 0.16341666666666668 - type: precision_at_3 value: 19.811833333333333 - type: precision_at_5 value: 14.07691666666667 - type: recall_at_1 value: 30.69458333333333 - type: recall_at_10 value: 60.462083333333325 - type: recall_at_100 value: 82.42325000000001 - type: recall_at_1000 value: 94.53291666666667 - type: recall_at_3 value: 45.7405 - type: recall_at_5 value: 52.14025 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 27.833000000000002 - type: map_at_10 value: 36.55 - type: map_at_100 value: 37.524 - type: map_at_1000 value: 37.613 - type: map_at_3 value: 33.552 - type: map_at_5 value: 35.173 - type: mrr_at_1 value: 31.135 - type: mrr_at_10 value: 39.637 - type: mrr_at_100 value: 40.361000000000004 - type: mrr_at_1000 value: 40.422000000000004 - type: mrr_at_3 value: 36.887 - type: mrr_at_5 value: 38.428000000000004 - type: ndcg_at_1 value: 31.135 - type: ndcg_at_10 value: 42.007 - type: ndcg_at_100 value: 46.531 - type: ndcg_at_1000 value: 48.643 - type: ndcg_at_3 value: 36.437999999999995 - type: ndcg_at_5 value: 39.021 - type: precision_at_1 value: 31.135 - type: precision_at_10 value: 6.856 - type: precision_at_100 value: 0.988 - type: precision_at_1000 value: 0.125 - type: precision_at_3 value: 15.9 - type: precision_at_5 value: 11.227 - type: recall_at_1 value: 27.833000000000002 - type: recall_at_10 value: 55.711 - type: recall_at_100 value: 76.255 - type: recall_at_1000 value: 91.51899999999999 - type: recall_at_3 value: 40.22 - type: recall_at_5 value: 46.69 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 21.274 - type: map_at_10 value: 29.925 - type: map_at_100 value: 31.171 - type: map_at_1000 value: 31.296000000000003 - type: map_at_3 value: 27.209 - type: map_at_5 value: 28.707 - type: mrr_at_1 value: 26.462000000000003 - type: mrr_at_10 value: 34.604 - type: mrr_at_100 value: 35.554 - type: mrr_at_1000 value: 35.622 - type: mrr_at_3 value: 32.295 - type: mrr_at_5 value: 33.598 - type: ndcg_at_1 value: 26.462000000000003 - type: ndcg_at_10 value: 35.193000000000005 - type: ndcg_at_100 value: 40.876000000000005 - type: ndcg_at_1000 value: 43.442 - type: ndcg_at_3 value: 30.724 - type: ndcg_at_5 value: 32.735 - type: precision_at_1 value: 26.462000000000003 - type: precision_at_10 value: 6.438000000000001 - type: precision_at_100 value: 1.093 - type: precision_at_1000 value: 0.15 - type: precision_at_3 value: 14.636 - type: precision_at_5 value: 10.496 - type: recall_at_1 value: 21.274 - type: recall_at_10 value: 46.322 - type: recall_at_100 value: 71.702 - type: recall_at_1000 value: 89.405 - type: recall_at_3 value: 33.444 - type: recall_at_5 value: 38.83 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 31.174000000000003 - type: map_at_10 value: 42.798 - type: map_at_100 value: 43.996 - type: map_at_1000 value: 44.088 - type: map_at_3 value: 39.255 - type: map_at_5 value: 41.336 - type: mrr_at_1 value: 37.22 - type: mrr_at_10 value: 47.035 - type: mrr_at_100 value: 47.833999999999996 - type: mrr_at_1000 value: 47.88 - type: mrr_at_3 value: 44.248 - type: mrr_at_5 value: 45.815 - type: ndcg_at_1 value: 37.22 - type: ndcg_at_10 value: 48.931999999999995 - type: ndcg_at_100 value: 53.991 - type: ndcg_at_1000 value: 55.825 - type: ndcg_at_3 value: 43.144 - type: ndcg_at_5 value: 45.964 - type: precision_at_1 value: 37.22 - type: precision_at_10 value: 8.451 - type: precision_at_100 value: 1.2189999999999999 - type: precision_at_1000 value: 0.149 - type: precision_at_3 value: 20.087 - type: precision_at_5 value: 14.235000000000001 - type: recall_at_1 value: 31.174000000000003 - type: recall_at_10 value: 63.232 - type: recall_at_100 value: 84.747 - type: recall_at_1000 value: 97.006 - type: recall_at_3 value: 47.087 - type: recall_at_5 value: 54.493 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 29.628 - type: map_at_10 value: 39.995999999999995 - type: map_at_100 value: 41.899 - type: map_at_1000 value: 42.125 - type: map_at_3 value: 36.345 - type: map_at_5 value: 38.474000000000004 - type: mrr_at_1 value: 36.364000000000004 - type: mrr_at_10 value: 45.293 - type: mrr_at_100 value: 46.278999999999996 - type: mrr_at_1000 value: 46.318 - type: mrr_at_3 value: 42.522999999999996 - type: mrr_at_5 value: 44.104 - type: ndcg_at_1 value: 36.364000000000004 - type: ndcg_at_10 value: 46.622 - type: ndcg_at_100 value: 52.617000000000004 - type: ndcg_at_1000 value: 54.529 - type: ndcg_at_3 value: 40.971999999999994 - type: ndcg_at_5 value: 43.738 - type: precision_at_1 value: 36.364000000000004 - type: precision_at_10 value: 9.110999999999999 - type: precision_at_100 value: 1.846 - type: precision_at_1000 value: 0.256 - type: precision_at_3 value: 19.236 - type: precision_at_5 value: 14.269000000000002 - type: recall_at_1 value: 29.628 - type: recall_at_10 value: 58.706 - type: recall_at_100 value: 85.116 - type: recall_at_1000 value: 97.258 - type: recall_at_3 value: 42.655 - type: recall_at_5 value: 49.909 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 25.499 - type: map_at_10 value: 34.284 - type: map_at_100 value: 35.416 - type: map_at_1000 value: 35.494 - type: map_at_3 value: 31.911 - type: map_at_5 value: 33.159 - type: mrr_at_1 value: 28.096 - type: mrr_at_10 value: 36.699 - type: mrr_at_100 value: 37.657000000000004 - type: mrr_at_1000 value: 37.714999999999996 - type: mrr_at_3 value: 34.72 - type: mrr_at_5 value: 35.746 - type: ndcg_at_1 value: 28.096 - type: ndcg_at_10 value: 39.041 - type: ndcg_at_100 value: 44.633 - type: ndcg_at_1000 value: 46.522000000000006 - type: ndcg_at_3 value: 34.663 - type: ndcg_at_5 value: 36.538 - type: precision_at_1 value: 28.096 - type: precision_at_10 value: 6.0440000000000005 - type: precision_at_100 value: 0.9520000000000001 - type: precision_at_1000 value: 0.121 - type: precision_at_3 value: 14.911 - type: precision_at_5 value: 10.277 - type: recall_at_1 value: 25.499 - type: recall_at_10 value: 51.26199999999999 - type: recall_at_100 value: 76.896 - type: recall_at_1000 value: 90.763 - type: recall_at_3 value: 39.376 - type: recall_at_5 value: 43.785000000000004 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 10.532 - type: map_at_10 value: 19.911 - type: map_at_100 value: 21.926000000000002 - type: map_at_1000 value: 22.113 - type: map_at_3 value: 16.118 - type: map_at_5 value: 18.043 - type: mrr_at_1 value: 23.909 - type: mrr_at_10 value: 37.029 - type: mrr_at_100 value: 38.015 - type: mrr_at_1000 value: 38.054 - type: mrr_at_3 value: 33.29 - type: mrr_at_5 value: 35.446 - type: ndcg_at_1 value: 23.909 - type: ndcg_at_10 value: 28.691 - type: ndcg_at_100 value: 36.341 - type: ndcg_at_1000 value: 39.644 - type: ndcg_at_3 value: 22.561 - type: ndcg_at_5 value: 24.779999999999998 - type: precision_at_1 value: 23.909 - type: precision_at_10 value: 9.433 - type: precision_at_100 value: 1.763 - type: precision_at_1000 value: 0.23800000000000002 - type: precision_at_3 value: 17.438000000000002 - type: precision_at_5 value: 13.758999999999999 - type: recall_at_1 value: 10.532 - type: recall_at_10 value: 36.079 - type: recall_at_100 value: 62.156 - type: recall_at_1000 value: 80.53099999999999 - type: recall_at_3 value: 21.384 - type: recall_at_5 value: 27.29 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 9.483 - type: map_at_10 value: 21.986 - type: map_at_100 value: 31.319000000000003 - type: map_at_1000 value: 33.231 - type: map_at_3 value: 15.193000000000001 - type: map_at_5 value: 18.116 - type: mrr_at_1 value: 74.0 - type: mrr_at_10 value: 80.047 - type: mrr_at_100 value: 80.406 - type: mrr_at_1000 value: 80.414 - type: mrr_at_3 value: 78.667 - type: mrr_at_5 value: 79.467 - type: ndcg_at_1 value: 61.875 - type: ndcg_at_10 value: 46.544999999999995 - type: ndcg_at_100 value: 51.097 - type: ndcg_at_1000 value: 58.331999999999994 - type: ndcg_at_3 value: 51.622 - type: ndcg_at_5 value: 49.016 - type: precision_at_1 value: 74.0 - type: precision_at_10 value: 37.325 - type: precision_at_100 value: 11.743 - type: precision_at_1000 value: 2.423 - type: precision_at_3 value: 54.75 - type: precision_at_5 value: 47.699999999999996 - type: recall_at_1 value: 9.483 - type: recall_at_10 value: 27.477 - type: recall_at_100 value: 57.099999999999994 - type: recall_at_1000 value: 80.56 - type: recall_at_3 value: 16.543 - type: recall_at_5 value: 20.830000000000002 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 50.06 - type: f1 value: 44.99375486940016 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 70.94 - type: map_at_10 value: 80.854 - type: map_at_100 value: 81.096 - type: map_at_1000 value: 81.109 - type: map_at_3 value: 79.589 - type: map_at_5 value: 80.431 - type: mrr_at_1 value: 76.44800000000001 - type: mrr_at_10 value: 85.07000000000001 - type: mrr_at_100 value: 85.168 - type: mrr_at_1000 value: 85.17 - type: mrr_at_3 value: 84.221 - type: mrr_at_5 value: 84.832 - type: ndcg_at_1 value: 76.44800000000001 - type: ndcg_at_10 value: 85.019 - type: ndcg_at_100 value: 85.886 - type: ndcg_at_1000 value: 86.09400000000001 - type: ndcg_at_3 value: 83.023 - type: ndcg_at_5 value: 84.223 - type: precision_at_1 value: 76.44800000000001 - type: precision_at_10 value: 10.405000000000001 - type: precision_at_100 value: 1.105 - type: precision_at_1000 value: 0.11399999999999999 - type: precision_at_3 value: 32.208 - type: precision_at_5 value: 20.122999999999998 - type: recall_at_1 value: 70.94 - type: recall_at_10 value: 93.508 - type: recall_at_100 value: 96.962 - type: recall_at_1000 value: 98.24300000000001 - type: recall_at_3 value: 88.17099999999999 - type: recall_at_5 value: 91.191 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 23.844 - type: map_at_10 value: 41.629 - type: map_at_100 value: 43.766 - type: map_at_1000 value: 43.916 - type: map_at_3 value: 35.992000000000004 - type: map_at_5 value: 39.302 - type: mrr_at_1 value: 45.988 - type: mrr_at_10 value: 56.050999999999995 - type: mrr_at_100 value: 56.741 - type: mrr_at_1000 value: 56.767999999999994 - type: mrr_at_3 value: 53.498000000000005 - type: mrr_at_5 value: 55.071999999999996 - type: ndcg_at_1 value: 45.988 - type: ndcg_at_10 value: 49.891999999999996 - type: ndcg_at_100 value: 56.727000000000004 - type: ndcg_at_1000 value: 58.952000000000005 - type: ndcg_at_3 value: 45.09 - type: ndcg_at_5 value: 46.943 - type: precision_at_1 value: 45.988 - type: precision_at_10 value: 13.980999999999998 - type: precision_at_100 value: 2.136 - type: precision_at_1000 value: 0.252 - type: precision_at_3 value: 30.556 - type: precision_at_5 value: 22.778000000000002 - type: recall_at_1 value: 23.844 - type: recall_at_10 value: 58.46 - type: recall_at_100 value: 82.811 - type: recall_at_1000 value: 96.084 - type: recall_at_3 value: 41.636 - type: recall_at_5 value: 49.271 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 40.108 - type: map_at_10 value: 65.846 - type: map_at_100 value: 66.691 - type: map_at_1000 value: 66.743 - type: map_at_3 value: 62.09 - type: map_at_5 value: 64.412 - type: mrr_at_1 value: 80.216 - type: mrr_at_10 value: 85.768 - type: mrr_at_100 value: 85.92699999999999 - type: mrr_at_1000 value: 85.932 - type: mrr_at_3 value: 85.012 - type: mrr_at_5 value: 85.495 - type: ndcg_at_1 value: 80.216 - type: ndcg_at_10 value: 73.833 - type: ndcg_at_100 value: 76.68 - type: ndcg_at_1000 value: 77.639 - type: ndcg_at_3 value: 68.7 - type: ndcg_at_5 value: 71.514 - type: precision_at_1 value: 80.216 - type: precision_at_10 value: 15.616 - type: precision_at_100 value: 1.783 - type: precision_at_1000 value: 0.191 - type: precision_at_3 value: 44.483 - type: precision_at_5 value: 28.904999999999998 - type: recall_at_1 value: 40.108 - type: recall_at_10 value: 78.082 - type: recall_at_100 value: 89.129 - type: recall_at_1000 value: 95.381 - type: recall_at_3 value: 66.725 - type: recall_at_5 value: 72.262 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 94.3208 - type: ap value: 91.64852216825692 - type: f1 value: 94.31672442494217 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 16.954 - type: map_at_10 value: 28.605000000000004 - type: map_at_100 value: 29.875 - type: map_at_1000 value: 29.934 - type: map_at_3 value: 24.57 - type: map_at_5 value: 26.845000000000002 - type: mrr_at_1 value: 17.407 - type: mrr_at_10 value: 29.082 - type: mrr_at_100 value: 30.309 - type: mrr_at_1000 value: 30.361 - type: mrr_at_3 value: 25.112000000000002 - type: mrr_at_5 value: 27.37 - type: ndcg_at_1 value: 17.407 - type: ndcg_at_10 value: 35.555 - type: ndcg_at_100 value: 41.808 - type: ndcg_at_1000 value: 43.277 - type: ndcg_at_3 value: 27.291999999999998 - type: ndcg_at_5 value: 31.369999999999997 - type: precision_at_1 value: 17.407 - type: precision_at_10 value: 5.9670000000000005 - type: precision_at_100 value: 0.9119999999999999 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 11.939 - type: precision_at_5 value: 9.223 - type: recall_at_1 value: 16.954 - type: recall_at_10 value: 57.216 - type: recall_at_100 value: 86.384 - type: recall_at_1000 value: 97.64 - type: recall_at_3 value: 34.660999999999994 - type: recall_at_5 value: 44.484 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 95.29183766529867 - type: f1 value: 95.01282555921513 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 87.07934336525307 - type: f1 value: 69.58693991783085 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 79.71755211835911 - type: f1 value: 77.08207736007755 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 81.08607935440484 - type: f1 value: 80.71191664406739 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 36.5355083590869 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 37.24173539348128 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 32.84293003435578 - type: mrr value: 34.09721970493348 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 6.369 - type: map_at_10 value: 14.892 - type: map_at_100 value: 18.884999999999998 - type: map_at_1000 value: 20.43 - type: map_at_3 value: 10.735999999999999 - type: map_at_5 value: 12.703000000000001 - type: mrr_at_1 value: 50.15500000000001 - type: mrr_at_10 value: 59.948 - type: mrr_at_100 value: 60.422 - type: mrr_at_1000 value: 60.455999999999996 - type: mrr_at_3 value: 58.204 - type: mrr_at_5 value: 59.35 - type: ndcg_at_1 value: 47.678 - type: ndcg_at_10 value: 39.050000000000004 - type: ndcg_at_100 value: 35.905 - type: ndcg_at_1000 value: 44.662 - type: ndcg_at_3 value: 44.781 - type: ndcg_at_5 value: 42.549 - type: precision_at_1 value: 49.226 - type: precision_at_10 value: 28.762 - type: precision_at_100 value: 8.767999999999999 - type: precision_at_1000 value: 2.169 - type: precision_at_3 value: 41.796 - type: precision_at_5 value: 37.09 - type: recall_at_1 value: 6.369 - type: recall_at_10 value: 19.842000000000002 - type: recall_at_100 value: 37.017 - type: recall_at_1000 value: 68.444 - type: recall_at_3 value: 12.446 - type: recall_at_5 value: 15.525 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 39.663 - type: map_at_10 value: 56.252 - type: map_at_100 value: 57.018 - type: map_at_1000 value: 57.031 - type: map_at_3 value: 52.020999999999994 - type: map_at_5 value: 54.626 - type: mrr_at_1 value: 44.699 - type: mrr_at_10 value: 58.819 - type: mrr_at_100 value: 59.351 - type: mrr_at_1000 value: 59.358 - type: mrr_at_3 value: 55.615 - type: mrr_at_5 value: 57.598000000000006 - type: ndcg_at_1 value: 44.699 - type: ndcg_at_10 value: 63.873999999999995 - type: ndcg_at_100 value: 66.973 - type: ndcg_at_1000 value: 67.23700000000001 - type: ndcg_at_3 value: 56.25599999999999 - type: ndcg_at_5 value: 60.44199999999999 - type: precision_at_1 value: 44.699 - type: precision_at_10 value: 10.075000000000001 - type: precision_at_100 value: 1.185 - type: precision_at_1000 value: 0.121 - type: precision_at_3 value: 25.202999999999996 - type: precision_at_5 value: 17.584 - type: recall_at_1 value: 39.663 - type: recall_at_10 value: 84.313 - type: recall_at_100 value: 97.56700000000001 - type: recall_at_1000 value: 99.44 - type: recall_at_3 value: 64.938 - type: recall_at_5 value: 74.515 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 69.708 - type: map_at_10 value: 83.86099999999999 - type: map_at_100 value: 84.513 - type: map_at_1000 value: 84.53 - type: map_at_3 value: 80.854 - type: map_at_5 value: 82.757 - type: mrr_at_1 value: 80.15 - type: mrr_at_10 value: 86.70400000000001 - type: mrr_at_100 value: 86.81400000000001 - type: mrr_at_1000 value: 86.815 - type: mrr_at_3 value: 85.658 - type: mrr_at_5 value: 86.37599999999999 - type: ndcg_at_1 value: 80.17 - type: ndcg_at_10 value: 87.7 - type: ndcg_at_100 value: 88.979 - type: ndcg_at_1000 value: 89.079 - type: ndcg_at_3 value: 84.71600000000001 - type: ndcg_at_5 value: 86.385 - type: precision_at_1 value: 80.17 - type: precision_at_10 value: 13.369 - type: precision_at_100 value: 1.53 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 37.123 - type: precision_at_5 value: 24.498 - type: recall_at_1 value: 69.708 - type: recall_at_10 value: 95.17099999999999 - type: recall_at_100 value: 99.529 - type: recall_at_1000 value: 99.97500000000001 - type: recall_at_3 value: 86.761 - type: recall_at_5 value: 91.34 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 63.005610557842786 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 65.85897055439158 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 5.388 - type: map_at_10 value: 14.087 - type: map_at_100 value: 16.618 - type: map_at_1000 value: 16.967 - type: map_at_3 value: 9.8 - type: map_at_5 value: 11.907 - type: mrr_at_1 value: 26.5 - type: mrr_at_10 value: 37.905 - type: mrr_at_100 value: 39.053 - type: mrr_at_1000 value: 39.091 - type: mrr_at_3 value: 34.567 - type: mrr_at_5 value: 36.307 - type: ndcg_at_1 value: 26.5 - type: ndcg_at_10 value: 23.06 - type: ndcg_at_100 value: 32.164 - type: ndcg_at_1000 value: 37.574000000000005 - type: ndcg_at_3 value: 21.623 - type: ndcg_at_5 value: 18.95 - type: precision_at_1 value: 26.5 - type: precision_at_10 value: 12.030000000000001 - type: precision_at_100 value: 2.5020000000000002 - type: precision_at_1000 value: 0.379 - type: precision_at_3 value: 20.200000000000003 - type: precision_at_5 value: 16.64 - type: recall_at_1 value: 5.388 - type: recall_at_10 value: 24.375 - type: recall_at_100 value: 50.818 - type: recall_at_1000 value: 76.86699999999999 - type: recall_at_3 value: 12.273 - type: recall_at_5 value: 16.858 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 85.09465497223438 - type: cos_sim_spearman value: 80.55601111843897 - type: euclidean_pearson value: 82.40135168520864 - type: euclidean_spearman value: 80.05606361845396 - type: manhattan_pearson value: 82.24092291787754 - type: manhattan_spearman value: 79.89739846820373 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 81.14210597635189 - type: cos_sim_spearman value: 73.69447481152118 - type: euclidean_pearson value: 75.08507068029972 - type: euclidean_spearman value: 71.04077458564372 - type: manhattan_pearson value: 75.64918699307383 - type: manhattan_spearman value: 71.61677355593945 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 85.41396417076866 - type: cos_sim_spearman value: 85.82245898186092 - type: euclidean_pearson value: 85.58527168297935 - type: euclidean_spearman value: 85.94613250938504 - type: manhattan_pearson value: 85.88114899068759 - type: manhattan_spearman value: 86.42494392145366 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 83.7431948980468 - type: cos_sim_spearman value: 82.05114289801895 - type: euclidean_pearson value: 83.06116666914892 - type: euclidean_spearman value: 81.82060562251957 - type: manhattan_pearson value: 83.1858437025367 - type: manhattan_spearman value: 82.09604293088852 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 88.455985912287 - type: cos_sim_spearman value: 88.8044343107975 - type: euclidean_pearson value: 87.155336804123 - type: euclidean_spearman value: 87.79371420531842 - type: manhattan_pearson value: 87.5784376507174 - type: manhattan_spearman value: 88.429877987816 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 85.1631000795076 - type: cos_sim_spearman value: 86.20042158061408 - type: euclidean_pearson value: 84.88605965960737 - type: euclidean_spearman value: 85.45926745772432 - type: manhattan_pearson value: 85.18333987666729 - type: manhattan_spearman value: 85.86048911387192 - 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: 91.51301667439836 - type: cos_sim_spearman value: 91.46469919011143 - type: euclidean_pearson value: 91.15157693133415 - type: euclidean_spearman value: 91.02656400119739 - type: manhattan_pearson value: 91.08411259466446 - type: manhattan_spearman value: 90.84339904461068 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (en) config: en split: test revision: eea2b4fe26a775864c896887d910b76a8098ad3f metrics: - type: cos_sim_pearson value: 69.08993728439704 - type: cos_sim_spearman value: 69.20885645170797 - type: euclidean_pearson value: 69.65638507632245 - type: euclidean_spearman value: 68.69831912688514 - type: manhattan_pearson value: 69.86621764969294 - type: manhattan_spearman value: 69.05446631856769 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 86.96149243197495 - type: cos_sim_spearman value: 87.43145597912833 - type: euclidean_pearson value: 86.6762329641158 - type: euclidean_spearman value: 86.67085254401809 - type: manhattan_pearson value: 87.06412701458164 - type: manhattan_spearman value: 87.10197412769807 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 86.43440918697488 - type: mrr value: 96.3954826945023 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 60.494 - type: map_at_10 value: 72.074 - type: map_at_100 value: 72.475 - type: map_at_1000 value: 72.483 - type: map_at_3 value: 68.983 - type: map_at_5 value: 71.161 - type: mrr_at_1 value: 63.666999999999994 - type: mrr_at_10 value: 73.31299999999999 - type: mrr_at_100 value: 73.566 - type: mrr_at_1000 value: 73.574 - type: mrr_at_3 value: 71.111 - type: mrr_at_5 value: 72.72800000000001 - type: ndcg_at_1 value: 63.666999999999994 - type: ndcg_at_10 value: 77.024 - type: ndcg_at_100 value: 78.524 - type: ndcg_at_1000 value: 78.842 - type: ndcg_at_3 value: 72.019 - type: ndcg_at_5 value: 75.22999999999999 - type: precision_at_1 value: 63.666999999999994 - type: precision_at_10 value: 10.2 - type: precision_at_100 value: 1.103 - type: precision_at_1000 value: 0.11299999999999999 - type: precision_at_3 value: 28.111000000000004 - type: precision_at_5 value: 19.0 - type: recall_at_1 value: 60.494 - type: recall_at_10 value: 90.8 - type: recall_at_100 value: 97.333 - type: recall_at_1000 value: 100.0 - type: recall_at_3 value: 77.644 - type: recall_at_5 value: 85.694 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.68415841584158 - type: cos_sim_ap value: 91.23713949701548 - type: cos_sim_f1 value: 83.70221327967808 - type: cos_sim_precision value: 84.21052631578947 - type: cos_sim_recall value: 83.2 - type: dot_accuracy value: 99.5 - type: dot_ap value: 79.46312132270363 - type: dot_f1 value: 72.75320970042794 - type: dot_precision value: 69.35630099728014 - type: dot_recall value: 76.5 - type: euclidean_accuracy value: 99.69108910891089 - type: euclidean_ap value: 90.9016163254649 - type: euclidean_f1 value: 83.91752577319586 - type: euclidean_precision value: 86.59574468085106 - type: euclidean_recall value: 81.39999999999999 - type: manhattan_accuracy value: 99.7039603960396 - type: manhattan_ap value: 91.5593806619311 - type: manhattan_f1 value: 85.08124076809453 - type: manhattan_precision value: 83.80213385063045 - type: manhattan_recall value: 86.4 - type: max_accuracy value: 99.7039603960396 - type: max_ap value: 91.5593806619311 - type: max_f1 value: 85.08124076809453 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 74.40806543281603 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 38.51757703316821 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 54.33475593449746 - type: mrr value: 55.3374474789916 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 30.249926396023596 - type: cos_sim_spearman value: 29.820375700458158 - type: dot_pearson value: 28.820307635930355 - type: dot_spearman value: 28.824273052746825 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.233 - type: map_at_10 value: 2.061 - type: map_at_100 value: 12.607 - type: map_at_1000 value: 30.031000000000002 - type: map_at_3 value: 0.6669999999999999 - type: map_at_5 value: 1.091 - type: mrr_at_1 value: 88.0 - type: mrr_at_10 value: 93.067 - type: mrr_at_100 value: 93.067 - type: mrr_at_1000 value: 93.067 - type: mrr_at_3 value: 92.667 - type: mrr_at_5 value: 93.067 - type: ndcg_at_1 value: 84.0 - type: ndcg_at_10 value: 81.072 - type: ndcg_at_100 value: 62.875 - type: ndcg_at_1000 value: 55.641 - type: ndcg_at_3 value: 85.296 - type: ndcg_at_5 value: 84.10499999999999 - type: precision_at_1 value: 88.0 - type: precision_at_10 value: 83.39999999999999 - type: precision_at_100 value: 63.7 - type: precision_at_1000 value: 24.622 - type: precision_at_3 value: 88.0 - type: precision_at_5 value: 87.2 - type: recall_at_1 value: 0.233 - type: recall_at_10 value: 2.188 - type: recall_at_100 value: 15.52 - type: recall_at_1000 value: 52.05499999999999 - type: recall_at_3 value: 0.6859999999999999 - type: recall_at_5 value: 1.1440000000000001 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 3.19 - type: map_at_10 value: 11.491999999999999 - type: map_at_100 value: 17.251 - type: map_at_1000 value: 18.795 - type: map_at_3 value: 6.146 - type: map_at_5 value: 8.113 - type: mrr_at_1 value: 44.897999999999996 - type: mrr_at_10 value: 56.57 - type: mrr_at_100 value: 57.348 - type: mrr_at_1000 value: 57.357 - type: mrr_at_3 value: 52.041000000000004 - type: mrr_at_5 value: 55.408 - type: ndcg_at_1 value: 40.816 - type: ndcg_at_10 value: 27.968 - type: ndcg_at_100 value: 39.0 - type: ndcg_at_1000 value: 50.292 - type: ndcg_at_3 value: 31.256 - type: ndcg_at_5 value: 28.855999999999998 - type: precision_at_1 value: 44.897999999999996 - type: precision_at_10 value: 24.285999999999998 - type: precision_at_100 value: 7.898 - type: precision_at_1000 value: 1.541 - type: precision_at_3 value: 30.612000000000002 - type: precision_at_5 value: 27.346999999999998 - type: recall_at_1 value: 3.19 - type: recall_at_10 value: 17.954 - type: recall_at_100 value: 48.793 - type: recall_at_1000 value: 83.357 - type: recall_at_3 value: 6.973999999999999 - type: recall_at_5 value: 10.391 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 70.89139999999999 - type: ap value: 15.562539739828049 - type: f1 value: 55.38685639741247 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 62.48160724391625 - type: f1 value: 62.76700854121342 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 57.157071531498275 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 87.15503367705789 - type: cos_sim_ap value: 77.20584529783206 - type: cos_sim_f1 value: 71.3558088770313 - type: cos_sim_precision value: 66.02333931777379 - type: cos_sim_recall value: 77.62532981530343 - type: dot_accuracy value: 83.10186564940096 - type: dot_ap value: 64.34160146443133 - type: dot_f1 value: 63.23048153342683 - type: dot_precision value: 56.75618967687789 - type: dot_recall value: 71.37203166226914 - type: euclidean_accuracy value: 86.94045419324074 - type: euclidean_ap value: 76.08471767931738 - type: euclidean_f1 value: 71.41248592518455 - type: euclidean_precision value: 67.90387818225078 - type: euclidean_recall value: 75.30343007915567 - type: manhattan_accuracy value: 86.80932228646361 - type: manhattan_ap value: 76.03862870753638 - type: manhattan_f1 value: 71.2660917385327 - type: manhattan_precision value: 67.70363334124912 - type: manhattan_recall value: 75.22427440633246 - type: max_accuracy value: 87.15503367705789 - type: max_ap value: 77.20584529783206 - type: max_f1 value: 71.41248592518455 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 89.42639810610471 - type: cos_sim_ap value: 86.45196525133669 - type: cos_sim_f1 value: 79.25172592977508 - type: cos_sim_precision value: 76.50852802063925 - type: cos_sim_recall value: 82.19895287958116 - type: dot_accuracy value: 87.03768385919976 - type: dot_ap value: 80.86465404774172 - type: dot_f1 value: 74.50351637940457 - type: dot_precision value: 70.72293324109305 - type: dot_recall value: 78.71111795503542 - type: euclidean_accuracy value: 89.29056545193464 - type: euclidean_ap value: 86.25102188096191 - type: euclidean_f1 value: 79.05038057267126 - type: euclidean_precision value: 74.681550472538 - type: euclidean_recall value: 83.9621188789652 - type: manhattan_accuracy value: 89.34877944657896 - type: manhattan_ap value: 86.35336214205911 - type: manhattan_f1 value: 79.20192588269623 - type: manhattan_precision value: 75.24951483227058 - type: manhattan_recall value: 83.59254696643055 - type: max_accuracy value: 89.42639810610471 - type: max_ap value: 86.45196525133669 - type: max_f1 value: 79.25172592977508 --- # Model Summary > GritLM is a generative representational instruction tuned language model. It unifies text representation (embedding) and text generation into a single model achieving state-of-the-art performance on both types of tasks. - **Repository:** [ContextualAI/gritlm](https://github.com/ContextualAI/gritlm) - **Paper:** https://arxiv.org/abs/2402.09906 - **Logs:** https://wandb.ai/muennighoff/gritlm/runs/id130s1m/overview - **Script:** https://github.com/ContextualAI/gritlm/blob/main/scripts/training/train_gritlm_8x7b.sh | Model | Description | |-------|-------------| | [GritLM 7B](https://hf.co/GritLM/GritLM-7B) | Mistral 7B finetuned using GRIT | | [GritLM 8x7B](https://hf.co/GritLM/GritLM-8x7B) | Mixtral 8x7B finetuned using GRIT | # Use The model usage is documented [here](https://github.com/ContextualAI/gritlm?tab=readme-ov-file#inference). # Citation ```bibtex @misc{muennighoff2024generative, title={Generative Representational Instruction Tuning}, author={Niklas Muennighoff and Hongjin Su and Liang Wang and Nan Yang and Furu Wei and Tao Yu and Amanpreet Singh and Douwe Kiela}, year={2024}, eprint={2402.09906}, archivePrefix={arXiv}, primaryClass={cs.CL} } ```