| --- |
| base_model: distilbert/distilbert-base-uncased |
| library_name: sentence-transformers |
| model-index: |
| - name: prdev/mini-gte |
| results: |
| - dataset: |
| config: en |
| name: MTEB AmazonCounterfactualClassification (en) |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
| split: test |
| type: mteb/amazon_counterfactual |
| metrics: |
| - type: accuracy |
| value: 74.8955 |
| - type: f1 |
| value: 68.84209999999999 |
| - type: f1_weighted |
| value: 77.1819 |
| - type: ap |
| value: 37.731500000000004 |
| - type: ap_weighted |
| value: 37.731500000000004 |
| - type: main_score |
| value: 74.8955 |
| task: |
| type: Classification |
| - dataset: |
| config: default |
| name: MTEB AmazonPolarityClassification (default) |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
| split: test |
| type: mteb/amazon_polarity |
| metrics: |
| - type: accuracy |
| value: 92.9424 |
| - type: f1 |
| value: 92.9268 |
| - type: f1_weighted |
| value: 92.9268 |
| - type: ap |
| value: 89.2255 |
| - type: ap_weighted |
| value: 89.2255 |
| - type: main_score |
| value: 92.9424 |
| task: |
| type: Classification |
| - dataset: |
| config: en |
| name: MTEB AmazonReviewsClassification (en) |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| split: test |
| type: mteb/amazon_reviews_multi |
| metrics: |
| - type: accuracy |
| value: 53.09199999999999 |
| - type: f1 |
| value: 52.735299999999995 |
| - type: f1_weighted |
| value: 52.735299999999995 |
| - type: main_score |
| value: 53.09199999999999 |
| task: |
| type: Classification |
| - dataset: |
| config: default |
| name: MTEB ArguAna (default) |
| revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
| split: test |
| type: mteb/arguana |
| metrics: |
| - type: ndcg_at_1 |
| value: 31.791999999999998 |
| - type: ndcg_at_3 |
| value: 47.205999999999996 |
| - type: ndcg_at_5 |
| value: 51.842999999999996 |
| - type: ndcg_at_10 |
| value: 56.614 |
| - type: ndcg_at_20 |
| value: 59.211999999999996 |
| - type: ndcg_at_100 |
| value: 60.148999999999994 |
| - type: ndcg_at_1000 |
| value: 60.231 |
| - type: map_at_1 |
| value: 31.791999999999998 |
| - type: map_at_3 |
| value: 43.35 |
| - type: map_at_5 |
| value: 45.928000000000004 |
| - type: map_at_10 |
| value: 47.929 |
| - type: map_at_20 |
| value: 48.674 |
| - type: map_at_100 |
| value: 48.825 |
| - type: map_at_1000 |
| value: 48.827999999999996 |
| - type: recall_at_1 |
| value: 31.791999999999998 |
| - type: recall_at_3 |
| value: 58.392999999999994 |
| - type: recall_at_5 |
| value: 69.63000000000001 |
| - type: recall_at_10 |
| value: 84.211 |
| - type: recall_at_20 |
| value: 94.23899999999999 |
| - type: recall_at_100 |
| value: 99.004 |
| - type: recall_at_1000 |
| value: 99.644 |
| - type: precision_at_1 |
| value: 31.791999999999998 |
| - type: precision_at_3 |
| value: 19.464000000000002 |
| - type: precision_at_5 |
| value: 13.926 |
| - type: precision_at_10 |
| value: 8.421 |
| - type: precision_at_20 |
| value: 4.712000000000001 |
| - type: precision_at_100 |
| value: 0.9900000000000001 |
| - type: precision_at_1000 |
| value: 0.1 |
| - type: mrr_at_1 |
| value: 32.4324 |
| - type: mrr_at_3 |
| value: 43.6463 |
| - type: mrr_at_5 |
| value: 46.1569 |
| - type: mrr_at_10 |
| value: 48.1582 |
| - type: mrr_at_20 |
| value: 48.9033 |
| - type: mrr_at_100 |
| value: 49.0537 |
| - type: mrr_at_1000 |
| value: 49.0569 |
| - type: nauc_ndcg_at_1_max |
| value: -4.8705 |
| - type: nauc_ndcg_at_1_std |
| value: -9.1757 |
| - type: nauc_ndcg_at_1_diff1 |
| value: 17.743000000000002 |
| - type: nauc_ndcg_at_3_max |
| value: -3.916 |
| - type: nauc_ndcg_at_3_std |
| value: -10.424 |
| - type: nauc_ndcg_at_3_diff1 |
| value: 12.3928 |
| - type: nauc_ndcg_at_5_max |
| value: -2.5090000000000003 |
| - type: nauc_ndcg_at_5_std |
| value: -10.1328 |
| - type: nauc_ndcg_at_5_diff1 |
| value: 13.3086 |
| - type: nauc_ndcg_at_10_max |
| value: -1.4653 |
| - type: nauc_ndcg_at_10_std |
| value: -9.3154 |
| - type: nauc_ndcg_at_10_diff1 |
| value: 13.7827 |
| - type: nauc_ndcg_at_20_max |
| value: -2.4534000000000002 |
| - type: nauc_ndcg_at_20_std |
| value: -9.0213 |
| - type: nauc_ndcg_at_20_diff1 |
| value: 13.764399999999998 |
| - type: nauc_ndcg_at_100_max |
| value: -2.8207 |
| - type: nauc_ndcg_at_100_std |
| value: -9.0492 |
| - type: nauc_ndcg_at_100_diff1 |
| value: 14.3422 |
| - type: nauc_ndcg_at_1000_max |
| value: -3.0108 |
| - type: nauc_ndcg_at_1000_std |
| value: -9.2507 |
| - type: nauc_ndcg_at_1000_diff1 |
| value: 14.2345 |
| - type: nauc_map_at_1_max |
| value: -4.8705 |
| - type: nauc_map_at_1_std |
| value: -9.1757 |
| - type: nauc_map_at_1_diff1 |
| value: 17.743000000000002 |
| - type: nauc_map_at_3_max |
| value: -4.2874 |
| - type: nauc_map_at_3_std |
| value: -10.1539 |
| - type: nauc_map_at_3_diff1 |
| value: 13.6101 |
| - type: nauc_map_at_5_max |
| value: -3.5856 |
| - type: nauc_map_at_5_std |
| value: -9.9657 |
| - type: nauc_map_at_5_diff1 |
| value: 14.1354 |
| - type: nauc_map_at_10_max |
| value: -3.2553 |
| - type: nauc_map_at_10_std |
| value: -9.6771 |
| - type: nauc_map_at_10_diff1 |
| value: 14.402899999999999 |
| - type: nauc_map_at_20_max |
| value: -3.5541000000000005 |
| - type: nauc_map_at_20_std |
| value: -9.6286 |
| - type: nauc_map_at_20_diff1 |
| value: 14.3927 |
| - type: nauc_map_at_100_max |
| value: -3.5811999999999995 |
| - type: nauc_map_at_100_std |
| value: -9.6278 |
| - type: nauc_map_at_100_diff1 |
| value: 14.4922 |
| - type: nauc_map_at_1000_max |
| value: -3.5881000000000003 |
| - type: nauc_map_at_1000_std |
| value: -9.6335 |
| - type: nauc_map_at_1000_diff1 |
| value: 14.488400000000002 |
| - type: nauc_recall_at_1_max |
| value: -4.8705 |
| - type: nauc_recall_at_1_std |
| value: -9.1757 |
| - type: nauc_recall_at_1_diff1 |
| value: 17.743000000000002 |
| - type: nauc_recall_at_3_max |
| value: -2.7195 |
| - type: nauc_recall_at_3_std |
| value: -11.2342 |
| - type: nauc_recall_at_3_diff1 |
| value: 8.7116 |
| - type: nauc_recall_at_5_max |
| value: 1.7492 |
| - type: nauc_recall_at_5_std |
| value: -10.6963 |
| - type: nauc_recall_at_5_diff1 |
| value: 10.569 |
| - type: nauc_recall_at_10_max |
| value: 10.7433 |
| - type: nauc_recall_at_10_std |
| value: -6.339599999999999 |
| - type: nauc_recall_at_10_diff1 |
| value: 10.6275 |
| - type: nauc_recall_at_20_max |
| value: 14.802499999999998 |
| - type: nauc_recall_at_20_std |
| value: 3.9196 |
| - type: nauc_recall_at_20_diff1 |
| value: 6.0286 |
| - type: nauc_recall_at_100_max |
| value: 40.8859 |
| - type: nauc_recall_at_100_std |
| value: 57.965500000000006 |
| - type: nauc_recall_at_100_diff1 |
| value: 30.7703 |
| - type: nauc_recall_at_1000_max |
| value: 24.2175 |
| - type: nauc_recall_at_1000_std |
| value: 70.9234 |
| - type: nauc_recall_at_1000_diff1 |
| value: 5.9272 |
| - type: nauc_precision_at_1_max |
| value: -4.8705 |
| - type: nauc_precision_at_1_std |
| value: -9.1757 |
| - type: nauc_precision_at_1_diff1 |
| value: 17.743000000000002 |
| - type: nauc_precision_at_3_max |
| value: -2.7195 |
| - type: nauc_precision_at_3_std |
| value: -11.2342 |
| - type: nauc_precision_at_3_diff1 |
| value: 8.7116 |
| - type: nauc_precision_at_5_max |
| value: 1.7492 |
| - type: nauc_precision_at_5_std |
| value: -10.6963 |
| - type: nauc_precision_at_5_diff1 |
| value: 10.569 |
| - type: nauc_precision_at_10_max |
| value: 10.7433 |
| - type: nauc_precision_at_10_std |
| value: -6.339599999999999 |
| - type: nauc_precision_at_10_diff1 |
| value: 10.6275 |
| - type: nauc_precision_at_20_max |
| value: 14.802499999999998 |
| - type: nauc_precision_at_20_std |
| value: 3.9196 |
| - type: nauc_precision_at_20_diff1 |
| value: 6.0286 |
| - type: nauc_precision_at_100_max |
| value: 40.8859 |
| - type: nauc_precision_at_100_std |
| value: 57.965500000000006 |
| - type: nauc_precision_at_100_diff1 |
| value: 30.7703 |
| - type: nauc_precision_at_1000_max |
| value: 24.2175 |
| - type: nauc_precision_at_1000_std |
| value: 70.9234 |
| - type: nauc_precision_at_1000_diff1 |
| value: 5.9272 |
| - type: nauc_mrr_at_1_max |
| value: -5.1491 |
| - type: nauc_mrr_at_1_std |
| value: -8.8127 |
| - type: nauc_mrr_at_1_diff1 |
| value: 15.857099999999999 |
| - type: nauc_mrr_at_3_max |
| value: -5.083200000000001 |
| - type: nauc_mrr_at_3_std |
| value: -9.8967 |
| - type: nauc_mrr_at_3_diff1 |
| value: 11.9042 |
| - type: nauc_mrr_at_5_max |
| value: -4.530399999999999 |
| - type: nauc_mrr_at_5_std |
| value: -9.900599999999999 |
| - type: nauc_mrr_at_5_diff1 |
| value: 12.2957 |
| - type: nauc_mrr_at_10_max |
| value: -4.2387 |
| - type: nauc_mrr_at_10_std |
| value: -9.6123 |
| - type: nauc_mrr_at_10_diff1 |
| value: 12.4769 |
| - type: nauc_mrr_at_20_max |
| value: -4.5254 |
| - type: nauc_mrr_at_20_std |
| value: -9.5502 |
| - type: nauc_mrr_at_20_diff1 |
| value: 12.4674 |
| - type: nauc_mrr_at_100_max |
| value: -4.5576 |
| - type: nauc_mrr_at_100_std |
| value: -9.549100000000001 |
| - type: nauc_mrr_at_100_diff1 |
| value: 12.556899999999999 |
| - type: nauc_mrr_at_1000_max |
| value: -4.5645999999999995 |
| - type: nauc_mrr_at_1000_std |
| value: -9.5548 |
| - type: nauc_mrr_at_1000_diff1 |
| value: 12.552900000000001 |
| - type: main_score |
| value: 56.614 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB ArxivClusteringP2P (default) |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| split: test |
| type: mteb/arxiv-clustering-p2p |
| metrics: |
| - type: v_measure |
| value: 47.2524 |
| - type: v_measure_std |
| value: 13.7772 |
| - type: main_score |
| value: 47.2524 |
| task: |
| type: Clustering |
| - dataset: |
| config: default |
| name: MTEB ArxivClusteringS2S (default) |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
| split: test |
| type: mteb/arxiv-clustering-s2s |
| metrics: |
| - type: v_measure |
| value: 40.7262 |
| - type: v_measure_std |
| value: 14.125499999999999 |
| - type: main_score |
| value: 40.7262 |
| task: |
| type: Clustering |
| - dataset: |
| config: default |
| name: MTEB AskUbuntuDupQuestions (default) |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
| split: test |
| type: mteb/askubuntudupquestions-reranking |
| metrics: |
| - type: map |
| value: 61.57319999999999 |
| - type: mrr |
| value: 74.6714 |
| - type: nAUC_map_max |
| value: 21.8916 |
| - type: nAUC_map_std |
| value: 17.9941 |
| - type: nAUC_map_diff1 |
| value: 1.5548 |
| - type: nAUC_mrr_max |
| value: 34.139399999999995 |
| - type: nAUC_mrr_std |
| value: 18.133499999999998 |
| - type: nAUC_mrr_diff1 |
| value: 13.3597 |
| - type: main_score |
| value: 61.57319999999999 |
| task: |
| type: Reranking |
| - dataset: |
| config: default |
| name: MTEB BIOSSES (default) |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
| split: test |
| type: mteb/biosses-sts |
| metrics: |
| - type: pearson |
| value: 86.7849 |
| - type: spearman |
| value: 84.7302 |
| - type: cosine_pearson |
| value: 86.7849 |
| - type: cosine_spearman |
| value: 84.7302 |
| - type: manhattan_pearson |
| value: 84.48179999999999 |
| - type: manhattan_spearman |
| value: 84.0507 |
| - type: euclidean_pearson |
| value: 84.8613 |
| - type: euclidean_spearman |
| value: 84.6266 |
| - type: main_score |
| value: 84.7302 |
| task: |
| type: STS |
| - dataset: |
| config: default |
| name: MTEB Banking77Classification (default) |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| split: test |
| type: mteb/banking77 |
| metrics: |
| - type: accuracy |
| value: 85.7175 |
| - type: f1 |
| value: 85.6781 |
| - type: f1_weighted |
| value: 85.6781 |
| - type: main_score |
| value: 85.7175 |
| task: |
| type: Classification |
| - dataset: |
| config: default |
| name: MTEB BiorxivClusteringP2P (default) |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| split: test |
| type: mteb/biorxiv-clustering-p2p |
| metrics: |
| - type: v_measure |
| value: 40.0588 |
| - type: v_measure_std |
| value: 0.8872 |
| - type: main_score |
| value: 40.0588 |
| task: |
| type: Clustering |
| - dataset: |
| config: default |
| name: MTEB BiorxivClusteringS2S (default) |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
| split: test |
| type: mteb/biorxiv-clustering-s2s |
| metrics: |
| - type: v_measure |
| value: 36.382799999999996 |
| - type: v_measure_std |
| value: 1.167 |
| - type: main_score |
| value: 36.382799999999996 |
| task: |
| type: Clustering |
| - dataset: |
| config: default |
| name: MTEB CQADupstackAndroidRetrieval (default) |
| revision: f46a197baaae43b4f621051089b82a364682dfeb |
| split: test |
| type: mteb/cqadupstack-android |
| metrics: |
| - type: ndcg_at_1 |
| value: 37.196 |
| - type: ndcg_at_3 |
| value: 42.778 |
| - type: ndcg_at_5 |
| value: 45.013999999999996 |
| - type: ndcg_at_10 |
| value: 47.973 |
| - type: ndcg_at_20 |
| value: 50.141000000000005 |
| - type: ndcg_at_100 |
| value: 53.31399999999999 |
| - type: ndcg_at_1000 |
| value: 55.52 |
| - type: map_at_1 |
| value: 30.598 |
| - type: map_at_3 |
| value: 38.173 |
| - type: map_at_5 |
| value: 40.093 |
| - type: map_at_10 |
| value: 41.686 |
| - type: map_at_20 |
| value: 42.522 |
| - type: map_at_100 |
| value: 43.191 |
| - type: map_at_1000 |
| value: 43.328 |
| - type: recall_at_1 |
| value: 30.598 |
| - type: recall_at_3 |
| value: 45.019999999999996 |
| - type: recall_at_5 |
| value: 51.357 |
| - type: recall_at_10 |
| value: 60.260000000000005 |
| - type: recall_at_20 |
| value: 67.93299999999999 |
| - type: recall_at_100 |
| value: 82.07 |
| - type: recall_at_1000 |
| value: 96.345 |
| - type: precision_at_1 |
| value: 37.196 |
| - type: precision_at_3 |
| value: 20.552999999999997 |
| - type: precision_at_5 |
| value: 14.707 |
| - type: precision_at_10 |
| value: 9.213000000000001 |
| - type: precision_at_20 |
| value: 5.522 |
| - type: precision_at_100 |
| value: 1.4949999999999999 |
| - type: precision_at_1000 |
| value: 0.198 |
| - type: mrr_at_1 |
| value: 37.196 |
| - type: mrr_at_3 |
| value: 44.4683 |
| - type: mrr_at_5 |
| value: 45.9776 |
| - type: mrr_at_10 |
| value: 47.1884 |
| - type: mrr_at_20 |
| value: 47.6763 |
| - type: mrr_at_100 |
| value: 47.957 |
| - type: mrr_at_1000 |
| value: 48.0103 |
| - type: nauc_ndcg_at_1_max |
| value: 38.1056 |
| - type: nauc_ndcg_at_1_std |
| value: -1.5731 |
| - type: nauc_ndcg_at_1_diff1 |
| value: 52.3965 |
| - type: nauc_ndcg_at_3_max |
| value: 35.8655 |
| - type: nauc_ndcg_at_3_std |
| value: 0.2057 |
| - type: nauc_ndcg_at_3_diff1 |
| value: 46.299600000000005 |
| - type: nauc_ndcg_at_5_max |
| value: 36.3806 |
| - type: nauc_ndcg_at_5_std |
| value: 1.542 |
| - type: nauc_ndcg_at_5_diff1 |
| value: 45.3674 |
| - type: nauc_ndcg_at_10_max |
| value: 36.6053 |
| - type: nauc_ndcg_at_10_std |
| value: 2.7934 |
| - type: nauc_ndcg_at_10_diff1 |
| value: 45.3474 |
| - type: nauc_ndcg_at_20_max |
| value: 37.2333 |
| - type: nauc_ndcg_at_20_std |
| value: 3.3346 |
| - type: nauc_ndcg_at_20_diff1 |
| value: 45.6105 |
| - type: nauc_ndcg_at_100_max |
| value: 38.168400000000005 |
| - type: nauc_ndcg_at_100_std |
| value: 4.618 |
| - type: nauc_ndcg_at_100_diff1 |
| value: 45.7041 |
| - type: nauc_ndcg_at_1000_max |
| value: 37.911 |
| - type: nauc_ndcg_at_1000_std |
| value: 4.2068 |
| - type: nauc_ndcg_at_1000_diff1 |
| value: 46.0349 |
| - type: nauc_map_at_1_max |
| value: 33.6794 |
| - type: nauc_map_at_1_std |
| value: -0.7946 |
| - type: nauc_map_at_1_diff1 |
| value: 55.799699999999994 |
| - type: nauc_map_at_3_max |
| value: 35.216300000000004 |
| - type: nauc_map_at_3_std |
| value: -0.3286 |
| - type: nauc_map_at_3_diff1 |
| value: 49.5727 |
| - type: nauc_map_at_5_max |
| value: 35.583999999999996 |
| - type: nauc_map_at_5_std |
| value: 0.4626 |
| - type: nauc_map_at_5_diff1 |
| value: 48.621900000000004 |
| - type: nauc_map_at_10_max |
| value: 35.837 |
| - type: nauc_map_at_10_std |
| value: 1.1462999999999999 |
| - type: nauc_map_at_10_diff1 |
| value: 48.302499999999995 |
| - type: nauc_map_at_20_max |
| value: 36.1877 |
| - type: nauc_map_at_20_std |
| value: 1.5263 |
| - type: nauc_map_at_20_diff1 |
| value: 48.2105 |
| - type: nauc_map_at_100_max |
| value: 36.452 |
| - type: nauc_map_at_100_std |
| value: 1.958 |
| - type: nauc_map_at_100_diff1 |
| value: 48.1781 |
| - type: nauc_map_at_1000_max |
| value: 36.4422 |
| - type: nauc_map_at_1000_std |
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| name: MTEB EmotionClassification (default) |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
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| type: Classification |
| - dataset: |
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| revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
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| value: 76.69930000000001 |
| - type: nauc_mrr_at_20_max |
| value: 39.4583 |
| - type: nauc_mrr_at_20_std |
| value: -38.6556 |
| - type: nauc_mrr_at_20_diff1 |
| value: 76.7297 |
| - type: nauc_mrr_at_100_max |
| value: 39.434799999999996 |
| - type: nauc_mrr_at_100_std |
| value: -38.647999999999996 |
| - type: nauc_mrr_at_100_diff1 |
| value: 76.7332 |
| - type: nauc_mrr_at_1000_max |
| value: 39.433299999999996 |
| - type: nauc_mrr_at_1000_std |
| value: -38.6493 |
| - type: nauc_mrr_at_1000_diff1 |
| value: 76.7332 |
| - type: main_score |
| value: 87.774 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB RedditClustering (default) |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| split: test |
| type: mteb/reddit-clustering |
| metrics: |
| - type: v_measure |
| value: 56.1172 |
| - type: v_measure_std |
| value: 4.1773 |
| - type: main_score |
| value: 56.1172 |
| task: |
| type: Clustering |
| - dataset: |
| config: default |
| name: MTEB RedditClusteringP2P (default) |
| revision: 385e3cb46b4cfa89021f56c4380204149d0efe33 |
| split: test |
| type: mteb/reddit-clustering-p2p |
| metrics: |
| - type: v_measure |
| value: 65.1415 |
| - type: v_measure_std |
| value: 12.804499999999999 |
| - type: main_score |
| value: 65.1415 |
| task: |
| type: Clustering |
| - dataset: |
| config: default |
| name: MTEB SCIDOCS (default) |
| revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88 |
| split: test |
| type: mteb/scidocs |
| metrics: |
| - type: ndcg_at_1 |
| value: 24.3 |
| - type: ndcg_at_3 |
| value: 20.275000000000002 |
| - type: ndcg_at_5 |
| value: 17.712 |
| - type: ndcg_at_10 |
| value: 21.317 |
| - type: ndcg_at_20 |
| value: 24.355 |
| - type: ndcg_at_100 |
| value: 30.115 |
| - type: ndcg_at_1000 |
| value: 35.803000000000004 |
| - type: map_at_1 |
| value: 4.928 |
| - type: map_at_3 |
| value: 9.15 |
| - type: map_at_5 |
| value: 10.914 |
| - type: map_at_10 |
| value: 12.808 |
| - type: map_at_20 |
| value: 13.968 |
| - type: map_at_100 |
| value: 15.113999999999999 |
| - type: map_at_1000 |
| value: 15.463 |
| - type: recall_at_1 |
| value: 4.928 |
| - type: recall_at_3 |
| value: 11.643 |
| - type: recall_at_5 |
| value: 15.873000000000001 |
| - type: recall_at_10 |
| value: 22.472 |
| - type: recall_at_20 |
| value: 29.612 |
| - type: recall_at_100 |
| value: 48.323 |
| - type: recall_at_1000 |
| value: 75.98 |
| - type: precision_at_1 |
| value: 24.3 |
| - type: precision_at_3 |
| value: 19.167 |
| - type: precision_at_5 |
| value: 15.659999999999998 |
| - type: precision_at_10 |
| value: 11.08 |
| - type: precision_at_20 |
| value: 7.3 |
| - type: precision_at_100 |
| value: 2.382 |
| - type: precision_at_1000 |
| value: 0.374 |
| - type: mrr_at_1 |
| value: 24.3 |
| - type: mrr_at_3 |
| value: 32.2 |
| - type: mrr_at_5 |
| value: 34.25 |
| - type: mrr_at_10 |
| value: 35.6749 |
| - type: mrr_at_20 |
| value: 36.326 |
| - type: mrr_at_100 |
| value: 36.804199999999994 |
| - type: mrr_at_1000 |
| value: 36.850899999999996 |
| - type: nauc_ndcg_at_1_max |
| value: 24.935499999999998 |
| - type: nauc_ndcg_at_1_std |
| value: 8.174299999999999 |
| - type: nauc_ndcg_at_1_diff1 |
| value: 20.6462 |
| - type: nauc_ndcg_at_3_max |
| value: 26.8438 |
| - type: nauc_ndcg_at_3_std |
| value: 12.5593 |
| - type: nauc_ndcg_at_3_diff1 |
| value: 16.1086 |
| - type: nauc_ndcg_at_5_max |
| value: 28.050199999999997 |
| - type: nauc_ndcg_at_5_std |
| value: 15.6557 |
| - type: nauc_ndcg_at_5_diff1 |
| value: 14.2624 |
| - type: nauc_ndcg_at_10_max |
| value: 29.183999999999997 |
| - type: nauc_ndcg_at_10_std |
| value: 18.8626 |
| - type: nauc_ndcg_at_10_diff1 |
| value: 12.1979 |
| - type: nauc_ndcg_at_20_max |
| value: 30.128 |
| - type: nauc_ndcg_at_20_std |
| value: 22.264400000000002 |
| - type: nauc_ndcg_at_20_diff1 |
| value: 12.0184 |
| - type: nauc_ndcg_at_100_max |
| value: 31.5267 |
| - type: nauc_ndcg_at_100_std |
| value: 27.067000000000004 |
| - type: nauc_ndcg_at_100_diff1 |
| value: 12.964500000000001 |
| - type: nauc_ndcg_at_1000_max |
| value: 31.4219 |
| - type: nauc_ndcg_at_1000_std |
| value: 26.9349 |
| - type: nauc_ndcg_at_1000_diff1 |
| value: 13.322600000000001 |
| - type: nauc_map_at_1_max |
| value: 24.7756 |
| - type: nauc_map_at_1_std |
| value: 8.1475 |
| - type: nauc_map_at_1_diff1 |
| value: 20.5305 |
| - type: nauc_map_at_3_max |
| value: 27.1559 |
| - type: nauc_map_at_3_std |
| value: 10.626199999999999 |
| - type: nauc_map_at_3_diff1 |
| value: 17.2136 |
| - type: nauc_map_at_5_max |
| value: 28.149800000000003 |
| - type: nauc_map_at_5_std |
| value: 13.549800000000001 |
| - type: nauc_map_at_5_diff1 |
| value: 14.9097 |
| - type: nauc_map_at_10_max |
| value: 29.041299999999996 |
| - type: nauc_map_at_10_std |
| value: 16.6128 |
| - type: nauc_map_at_10_diff1 |
| value: 13.232199999999999 |
| - type: nauc_map_at_20_max |
| value: 29.8518 |
| - type: nauc_map_at_20_std |
| value: 18.9557 |
| - type: nauc_map_at_20_diff1 |
| value: 13.1546 |
| - type: nauc_map_at_100_max |
| value: 30.426399999999997 |
| - type: nauc_map_at_100_std |
| value: 20.7314 |
| - type: nauc_map_at_100_diff1 |
| value: 13.3874 |
| - type: nauc_map_at_1000_max |
| value: 30.4659 |
| - type: nauc_map_at_1000_std |
| value: 20.938200000000002 |
| - type: nauc_map_at_1000_diff1 |
| value: 13.3881 |
| - type: nauc_recall_at_1_max |
| value: 24.7756 |
| - type: nauc_recall_at_1_std |
| value: 8.1475 |
| - type: nauc_recall_at_1_diff1 |
| value: 20.5305 |
| - type: nauc_recall_at_3_max |
| value: 27.020300000000002 |
| - type: nauc_recall_at_3_std |
| value: 13.8467 |
| - type: nauc_recall_at_3_diff1 |
| value: 13.849400000000001 |
| - type: nauc_recall_at_5_max |
| value: 27.685 |
| - type: nauc_recall_at_5_std |
| value: 18.287300000000002 |
| - type: nauc_recall_at_5_diff1 |
| value: 10.401 |
| - type: nauc_recall_at_10_max |
| value: 28.5451 |
| - type: nauc_recall_at_10_std |
| value: 23.0846 |
| - type: nauc_recall_at_10_diff1 |
| value: 6.751500000000001 |
| - type: nauc_recall_at_20_max |
| value: 28.4084 |
| - type: nauc_recall_at_20_std |
| value: 28.245700000000003 |
| - type: nauc_recall_at_20_diff1 |
| value: 6.3271 |
| - type: nauc_recall_at_100_max |
| value: 28.331200000000003 |
| - type: nauc_recall_at_100_std |
| value: 37.9775 |
| - type: nauc_recall_at_100_diff1 |
| value: 7.408399999999999 |
| - type: nauc_recall_at_1000_max |
| value: 24.3488 |
| - type: nauc_recall_at_1000_std |
| value: 38.596799999999995 |
| - type: nauc_recall_at_1000_diff1 |
| value: 6.427099999999999 |
| - type: nauc_precision_at_1_max |
| value: 24.935499999999998 |
| - type: nauc_precision_at_1_std |
| value: 8.174299999999999 |
| - type: nauc_precision_at_1_diff1 |
| value: 20.6462 |
| - type: nauc_precision_at_3_max |
| value: 27.107300000000002 |
| - type: nauc_precision_at_3_std |
| value: 13.9846 |
| - type: nauc_precision_at_3_diff1 |
| value: 14.025199999999998 |
| - type: nauc_precision_at_5_max |
| value: 27.940199999999997 |
| - type: nauc_precision_at_5_std |
| value: 18.523500000000002 |
| - type: nauc_precision_at_5_diff1 |
| value: 10.6452 |
| - type: nauc_precision_at_10_max |
| value: 28.9679 |
| - type: nauc_precision_at_10_std |
| value: 23.2788 |
| - type: nauc_precision_at_10_diff1 |
| value: 7.0396 |
| - type: nauc_precision_at_20_max |
| value: 28.799200000000003 |
| - type: nauc_precision_at_20_std |
| value: 28.2269 |
| - type: nauc_precision_at_20_diff1 |
| value: 6.6255999999999995 |
| - type: nauc_precision_at_100_max |
| value: 28.6629 |
| - type: nauc_precision_at_100_std |
| value: 37.5551 |
| - type: nauc_precision_at_100_diff1 |
| value: 7.858999999999999 |
| - type: nauc_precision_at_1000_max |
| value: 25.0545 |
| - type: nauc_precision_at_1000_std |
| value: 37.301899999999996 |
| - type: nauc_precision_at_1000_diff1 |
| value: 7.5589 |
| - type: nauc_mrr_at_1_max |
| value: 24.935499999999998 |
| - type: nauc_mrr_at_1_std |
| value: 8.174299999999999 |
| - type: nauc_mrr_at_1_diff1 |
| value: 20.6462 |
| - type: nauc_mrr_at_3_max |
| value: 26.037 |
| - type: nauc_mrr_at_3_std |
| value: 13.3379 |
| - type: nauc_mrr_at_3_diff1 |
| value: 16.713 |
| - type: nauc_mrr_at_5_max |
| value: 26.512200000000004 |
| - type: nauc_mrr_at_5_std |
| value: 14.1804 |
| - type: nauc_mrr_at_5_diff1 |
| value: 17.1186 |
| - type: nauc_mrr_at_10_max |
| value: 26.7938 |
| - type: nauc_mrr_at_10_std |
| value: 14.458699999999999 |
| - type: nauc_mrr_at_10_diff1 |
| value: 16.531299999999998 |
| - type: nauc_mrr_at_20_max |
| value: 26.628 |
| - type: nauc_mrr_at_20_std |
| value: 14.593200000000001 |
| - type: nauc_mrr_at_20_diff1 |
| value: 16.4492 |
| - type: nauc_mrr_at_100_max |
| value: 26.6627 |
| - type: nauc_mrr_at_100_std |
| value: 14.5648 |
| - type: nauc_mrr_at_100_diff1 |
| value: 16.614 |
| - type: nauc_mrr_at_1000_max |
| value: 26.6506 |
| - type: nauc_mrr_at_1000_std |
| value: 14.5124 |
| - type: nauc_mrr_at_1000_diff1 |
| value: 16.6315 |
| - type: main_score |
| value: 21.317 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB SICK-R (default) |
| revision: 20a6d6f312dd54037fe07a32d58e5e168867909d |
| split: test |
| type: mteb/sickr-sts |
| metrics: |
| - type: pearson |
| value: 85.2236 |
| - type: spearman |
| value: 79.55109999999999 |
| - type: cosine_pearson |
| value: 85.2236 |
| - type: cosine_spearman |
| value: 79.55109999999999 |
| - type: manhattan_pearson |
| value: 82.441 |
| - type: manhattan_spearman |
| value: 79.65100000000001 |
| - type: euclidean_pearson |
| value: 82.461 |
| - type: euclidean_spearman |
| value: 79.58460000000001 |
| - type: main_score |
| value: 79.55109999999999 |
| task: |
| type: STS |
| - dataset: |
| config: default |
| name: MTEB STS12 (default) |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| split: test |
| type: mteb/sts12-sts |
| metrics: |
| - type: pearson |
| value: 82.6754 |
| - type: spearman |
| value: 74.3345 |
| - type: cosine_pearson |
| value: 82.6754 |
| - type: cosine_spearman |
| value: 74.3336 |
| - type: manhattan_pearson |
| value: 78.64330000000001 |
| - type: manhattan_spearman |
| value: 74.23769999999999 |
| - type: euclidean_pearson |
| value: 78.589 |
| - type: euclidean_spearman |
| value: 74.1178 |
| - type: main_score |
| value: 74.3336 |
| task: |
| type: STS |
| - dataset: |
| config: default |
| name: MTEB STS13 (default) |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| split: test |
| type: mteb/sts13-sts |
| metrics: |
| - type: pearson |
| value: 82.4438 |
| - type: spearman |
| value: 83.5213 |
| - type: cosine_pearson |
| value: 82.4438 |
| - type: cosine_spearman |
| value: 83.5213 |
| - type: manhattan_pearson |
| value: 83.1769 |
| - type: manhattan_spearman |
| value: 83.29039999999999 |
| - type: euclidean_pearson |
| value: 83.0053 |
| - type: euclidean_spearman |
| value: 83.1047 |
| - type: main_score |
| value: 83.5213 |
| task: |
| type: STS |
| - dataset: |
| config: default |
| name: MTEB STS14 (default) |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| split: test |
| type: mteb/sts14-sts |
| metrics: |
| - type: pearson |
| value: 82.8843 |
| - type: spearman |
| value: 80.6162 |
| - type: cosine_pearson |
| value: 82.8843 |
| - type: cosine_spearman |
| value: 80.6161 |
| - type: manhattan_pearson |
| value: 82.446 |
| - type: manhattan_spearman |
| value: 80.5926 |
| - type: euclidean_pearson |
| value: 82.33840000000001 |
| - type: euclidean_spearman |
| value: 80.4619 |
| - type: main_score |
| value: 80.6161 |
| task: |
| type: STS |
| - dataset: |
| config: default |
| name: MTEB STS15 (default) |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| split: test |
| type: mteb/sts15-sts |
| metrics: |
| - type: pearson |
| value: 85.7467 |
| - type: spearman |
| value: 86.85690000000001 |
| - type: cosine_pearson |
| value: 85.7467 |
| - type: cosine_spearman |
| value: 86.85690000000001 |
| - type: manhattan_pearson |
| value: 86.469 |
| - type: manhattan_spearman |
| value: 86.751 |
| - type: euclidean_pearson |
| value: 86.4531 |
| - type: euclidean_spearman |
| value: 86.7053 |
| - type: main_score |
| value: 86.85690000000001 |
| task: |
| type: STS |
| - dataset: |
| config: default |
| name: MTEB STS16 (default) |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| split: test |
| type: mteb/sts16-sts |
| metrics: |
| - type: pearson |
| value: 84.143 |
| - type: spearman |
| value: 85.4366 |
| - type: cosine_pearson |
| value: 84.143 |
| - type: cosine_spearman |
| value: 85.4367 |
| - type: manhattan_pearson |
| value: 84.6762 |
| - type: manhattan_spearman |
| value: 85.1846 |
| - type: euclidean_pearson |
| value: 84.6233 |
| - type: euclidean_spearman |
| value: 85.1252 |
| - type: main_score |
| value: 85.4367 |
| task: |
| type: STS |
| - dataset: |
| config: en-en |
| name: MTEB STS17 (en-en) |
| revision: faeb762787bd10488a50c8b5be4a3b82e411949c |
| split: test |
| type: mteb/sts17-crosslingual-sts |
| metrics: |
| - type: pearson |
| value: 89.10820000000001 |
| - type: spearman |
| value: 89.7621 |
| - type: cosine_pearson |
| value: 89.10820000000001 |
| - type: cosine_spearman |
| value: 89.7621 |
| - type: manhattan_pearson |
| value: 89.3624 |
| - type: manhattan_spearman |
| value: 89.6515 |
| - type: euclidean_pearson |
| value: 89.3729 |
| - type: euclidean_spearman |
| value: 89.6836 |
| - type: main_score |
| value: 89.7621 |
| task: |
| type: STS |
| - dataset: |
| config: en |
| name: MTEB STS22 (en) |
| revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 |
| split: test |
| type: mteb/sts22-crosslingual-sts |
| metrics: |
| - type: pearson |
| value: 68.44019999999999 |
| - type: spearman |
| value: 68.3308 |
| - type: cosine_pearson |
| value: 68.4403 |
| - type: cosine_spearman |
| value: 68.3308 |
| - type: manhattan_pearson |
| value: 69.8199 |
| - type: manhattan_spearman |
| value: 68.754 |
| - type: euclidean_pearson |
| value: 69.5629 |
| - type: euclidean_spearman |
| value: 68.55630000000001 |
| - type: main_score |
| value: 68.3308 |
| task: |
| type: STS |
| - dataset: |
| config: default |
| name: MTEB STSBenchmark (default) |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
| split: test |
| type: mteb/stsbenchmark-sts |
| metrics: |
| - type: pearson |
| value: 86.0748 |
| - type: spearman |
| value: 86.2486 |
| - type: cosine_pearson |
| value: 86.0748 |
| - type: cosine_spearman |
| value: 86.2486 |
| - type: manhattan_pearson |
| value: 86.2053 |
| - type: manhattan_spearman |
| value: 86.0544 |
| - type: euclidean_pearson |
| value: 86.1504 |
| - type: euclidean_spearman |
| value: 85.985 |
| - type: main_score |
| value: 86.2486 |
| task: |
| type: STS |
| - dataset: |
| config: default |
| name: MTEB SciDocsRR (default) |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| split: test |
| type: mteb/scidocs-reranking |
| metrics: |
| - type: map |
| value: 84.4152 |
| - type: mrr |
| value: 95.4755 |
| - type: nAUC_map_max |
| value: 55.565799999999996 |
| - type: nAUC_map_std |
| value: 71.4307 |
| - type: nAUC_map_diff1 |
| value: 1.0619 |
| - type: nAUC_mrr_max |
| value: 87.11959999999999 |
| - type: nAUC_mrr_std |
| value: 82.7146 |
| - type: nAUC_mrr_diff1 |
| value: 44.2384 |
| - type: main_score |
| value: 84.4152 |
| task: |
| type: Reranking |
| - dataset: |
| config: default |
| name: MTEB SciFact (default) |
| revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
| split: test |
| type: mteb/scifact |
| metrics: |
| - type: ndcg_at_1 |
| value: 62.333000000000006 |
| - type: ndcg_at_3 |
| value: 67.297 |
| - type: ndcg_at_5 |
| value: 69.24900000000001 |
| - type: ndcg_at_10 |
| value: 72.63199999999999 |
| - type: ndcg_at_20 |
| value: 73.6 |
| - type: ndcg_at_100 |
| value: 74.888 |
| - type: ndcg_at_1000 |
| value: 75.452 |
| - type: map_at_1 |
| value: 59.733000000000004 |
| - type: map_at_3 |
| value: 65.194 |
| - type: map_at_5 |
| value: 66.616 |
| - type: map_at_10 |
| value: 68.158 |
| - type: map_at_20 |
| value: 68.464 |
| - type: map_at_100 |
| value: 68.685 |
| - type: map_at_1000 |
| value: 68.704 |
| - type: recall_at_1 |
| value: 59.733000000000004 |
| - type: recall_at_3 |
| value: 70.61699999999999 |
| - type: recall_at_5 |
| value: 75.5 |
| - type: recall_at_10 |
| value: 85.51100000000001 |
| - type: recall_at_20 |
| value: 89.133 |
| - type: recall_at_100 |
| value: 95.5 |
| - type: recall_at_1000 |
| value: 100 |
| - type: precision_at_1 |
| value: 62.333000000000006 |
| - type: precision_at_3 |
| value: 25.667 |
| - type: precision_at_5 |
| value: 16.8 |
| - type: precision_at_10 |
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| name: MTEB StackExchangeClusteringP2P (default) |
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| name: MTEB StackOverflowDupQuestions (default) |
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| - type: nauc_precision_at_100_std |
| value: 82.3103 |
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| value: 48.0414 |
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| value: 54.315599999999996 |
| - type: nauc_precision_at_1000_diff1 |
| value: 8.9054 |
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| value: 45.5245 |
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| - type: nauc_mrr_at_3_max |
| value: 61.1547 |
| - type: nauc_mrr_at_3_std |
| value: 52.5639 |
| - type: nauc_mrr_at_3_diff1 |
| value: -23.9503 |
| - type: nauc_mrr_at_5_max |
| value: 59.0374 |
| - type: nauc_mrr_at_5_std |
| value: 49.9784 |
| - type: nauc_mrr_at_5_diff1 |
| value: -15.771799999999999 |
| - type: nauc_mrr_at_10_max |
| value: 59.0374 |
| - type: nauc_mrr_at_10_std |
| value: 49.9784 |
| - type: nauc_mrr_at_10_diff1 |
| value: -15.771799999999999 |
| - type: nauc_mrr_at_20_max |
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| - type: nauc_mrr_at_20_std |
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| - type: nauc_mrr_at_20_diff1 |
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| - type: nauc_mrr_at_100_max |
| value: 59.0374 |
| - type: nauc_mrr_at_100_std |
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| - type: nauc_mrr_at_100_diff1 |
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| - type: nauc_mrr_at_1000_diff1 |
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| - type: main_score |
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| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB Touche2020 (default) |
| revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
| split: test |
| type: mteb/touche2020 |
| metrics: |
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| value: 26.531 |
| - type: ndcg_at_3 |
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| - type: ndcg_at_5 |
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| - type: ndcg_at_10 |
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| - type: ndcg_at_20 |
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| - type: ndcg_at_100 |
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| - type: ndcg_at_1000 |
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| - type: map_at_3 |
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| - type: map_at_5 |
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| - type: map_at_10 |
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| - type: map_at_20 |
| value: 11.928999999999998 |
| - type: map_at_100 |
| value: 15.082 |
| - type: map_at_1000 |
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| - type: recall_at_1 |
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| - type: recall_at_3 |
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| - type: recall_at_5 |
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| - type: recall_at_10 |
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| - type: recall_at_20 |
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| - type: recall_at_100 |
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| - type: recall_at_1000 |
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| - type: precision_at_1 |
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| - type: precision_at_3 |
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| - type: precision_at_5 |
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| - type: precision_at_10 |
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| - type: precision_at_20 |
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| - type: precision_at_100 |
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| - type: precision_at_1000 |
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| - type: mrr_at_1 |
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| - type: mrr_at_3 |
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| - type: mrr_at_5 |
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| - type: mrr_at_10 |
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| - type: mrr_at_20 |
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| - type: mrr_at_100 |
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| - type: mrr_at_1000 |
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| - type: nauc_ndcg_at_1_max |
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| - type: nauc_ndcg_at_1_diff1 |
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| - type: nauc_ndcg_at_3_max |
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| - type: nauc_recall_at_20_max |
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| - type: nauc_recall_at_100_max |
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| - type: nauc_recall_at_100_std |
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| - type: nauc_recall_at_100_diff1 |
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| - type: nauc_recall_at_1000_max |
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| - type: nauc_recall_at_1000_std |
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| - type: nauc_recall_at_1000_diff1 |
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| - type: nauc_precision_at_1_max |
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| - type: nauc_precision_at_1_diff1 |
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| - type: nauc_precision_at_3_std |
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| - type: nauc_precision_at_3_diff1 |
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| - type: nauc_precision_at_5_std |
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| - type: nauc_precision_at_5_diff1 |
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| - type: nauc_precision_at_10_std |
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| - type: nauc_precision_at_10_diff1 |
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| - type: nauc_precision_at_20_max |
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| - type: nauc_precision_at_20_std |
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| - type: nauc_precision_at_20_diff1 |
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| - type: nauc_precision_at_100_max |
| value: -11.4519 |
| - type: nauc_precision_at_100_std |
| value: 72.8881 |
| - type: nauc_precision_at_100_diff1 |
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| - type: nauc_precision_at_1000_max |
| value: 29.3926 |
| - type: nauc_precision_at_1000_std |
| value: 44.936 |
| - type: nauc_precision_at_1000_diff1 |
| value: -15.2011 |
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| value: -16.3352 |
| - type: nauc_mrr_at_1_diff1 |
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| - type: nauc_mrr_at_3_max |
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| - type: nauc_mrr_at_3_std |
| value: -8.757 |
| - type: nauc_mrr_at_3_diff1 |
| value: 6.916300000000001 |
| - type: nauc_mrr_at_5_max |
| value: -36.2749 |
| - type: nauc_mrr_at_5_std |
| value: -5.7966 |
| - type: nauc_mrr_at_5_diff1 |
| value: 4.8726 |
| - type: nauc_mrr_at_10_max |
| value: -39.0726 |
| - type: nauc_mrr_at_10_std |
| value: -6.830799999999999 |
| - type: nauc_mrr_at_10_diff1 |
| value: 5.1214 |
| - type: nauc_mrr_at_20_max |
| value: -38.6519 |
| - type: nauc_mrr_at_20_std |
| value: -8.6379 |
| - type: nauc_mrr_at_20_diff1 |
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| - type: nauc_mrr_at_100_max |
| value: -38.065599999999996 |
| - type: nauc_mrr_at_100_std |
| value: -8.444 |
| - type: nauc_mrr_at_100_diff1 |
| value: 6.2007 |
| - type: nauc_mrr_at_1000_max |
| value: -38.065599999999996 |
| - type: nauc_mrr_at_1000_std |
| value: -8.444 |
| - type: nauc_mrr_at_1000_diff1 |
| value: 6.2007 |
| - type: main_score |
| value: 23.86 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB ToxicConversationsClassification (default) |
| revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de |
| split: test |
| type: mteb/toxic_conversations_50k |
| metrics: |
| - type: accuracy |
| value: 78.21289999999999 |
| - type: f1 |
| value: 60.9322 |
| - type: f1_weighted |
| value: 82.69539999999999 |
| - type: ap |
| value: 19.0474 |
| - type: ap_weighted |
| value: 19.0474 |
| - type: main_score |
| value: 78.21289999999999 |
| task: |
| type: Classification |
| - dataset: |
| config: default |
| name: MTEB TweetSentimentExtractionClassification (default) |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| split: test |
| type: mteb/tweet_sentiment_extraction |
| metrics: |
| - type: accuracy |
| value: 61.3865 |
| - type: f1 |
| value: 61.8066 |
| - type: f1_weighted |
| value: 60.887 |
| - type: main_score |
| value: 61.3865 |
| task: |
| type: Classification |
| - dataset: |
| config: default |
| name: MTEB TwentyNewsgroupsClustering (default) |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| split: test |
| type: mteb/twentynewsgroups-clustering |
| metrics: |
| - type: v_measure |
| value: 49.3006 |
| - type: v_measure_std |
| value: 0.8814000000000001 |
| - type: main_score |
| value: 49.3006 |
| task: |
| type: Clustering |
| - dataset: |
| config: default |
| name: MTEB TwitterSemEval2015 (default) |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
| split: test |
| type: mteb/twittersemeval2015-pairclassification |
| metrics: |
| - type: similarity_accuracy |
| value: 85.96289999999999 |
| - type: similarity_accuracy_threshold |
| value: 81.7629 |
| - type: similarity_f1 |
| value: 67.1044 |
| - type: similarity_f1_threshold |
| value: 77.98479999999999 |
| - type: similarity_precision |
| value: 64.3497 |
| - type: similarity_recall |
| value: 70.10549999999999 |
| - type: similarity_ap |
| value: 73.406 |
| - type: cosine_accuracy |
| value: 85.96289999999999 |
| - type: cosine_accuracy_threshold |
| value: 81.7629 |
| - type: cosine_f1 |
| value: 67.1044 |
| - type: cosine_f1_threshold |
| value: 77.98479999999999 |
| - type: cosine_precision |
| value: 64.3497 |
| - type: cosine_recall |
| value: 70.10549999999999 |
| - type: cosine_ap |
| value: 73.406 |
| - type: manhattan_accuracy |
| value: 85.8735 |
| - type: manhattan_accuracy_threshold |
| value: 22606.6437 |
| - type: manhattan_f1 |
| value: 67.173 |
| - type: manhattan_f1_threshold |
| value: 24147.3145 |
| - type: manhattan_precision |
| value: 65.5857 |
| - type: manhattan_recall |
| value: 68.8391 |
| - type: manhattan_ap |
| value: 73.4081 |
| - type: euclidean_accuracy |
| value: 85.94500000000001 |
| - type: euclidean_accuracy_threshold |
| value: 1019.4165999999999 |
| - type: euclidean_f1 |
| value: 67.0857 |
| - type: euclidean_f1_threshold |
| value: 1125.1016 |
| - type: euclidean_precision |
| value: 64.07300000000001 |
| - type: euclidean_recall |
| value: 70.3958 |
| - type: euclidean_ap |
| value: 73.3824 |
| - type: dot_accuracy |
| value: 85.3013 |
| - type: dot_accuracy_threshold |
| value: 23726.3916 |
| - type: dot_f1 |
| value: 65.8888 |
| - type: dot_f1_threshold |
| value: 22265.913399999998 |
| - type: dot_precision |
| value: 62.2128 |
| - type: dot_recall |
| value: 70.0264 |
| - type: dot_ap |
| value: 71.5363 |
| - type: max_accuracy |
| value: 85.96289999999999 |
| - type: max_f1 |
| value: 67.173 |
| - type: max_precision |
| value: 65.5857 |
| - type: max_recall |
| value: 70.3958 |
| - type: max_ap |
| value: 73.4081 |
| - type: main_score |
| value: 73.4081 |
| task: |
| type: PairClassification |
| - dataset: |
| config: default |
| name: MTEB TwitterURLCorpus (default) |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
| split: test |
| type: mteb/twitterurlcorpus-pairclassification |
| metrics: |
| - type: similarity_accuracy |
| value: 88.82100000000001 |
| - type: similarity_accuracy_threshold |
| value: 75.9351 |
| - type: similarity_f1 |
| value: 77.7423 |
| - type: similarity_f1_threshold |
| value: 72.788 |
| - type: similarity_precision |
| value: 74.2279 |
| - type: similarity_recall |
| value: 81.6061 |
| - type: similarity_ap |
| value: 85.4324 |
| - type: cosine_accuracy |
| value: 88.82100000000001 |
| - type: cosine_accuracy_threshold |
| value: 75.9351 |
| - type: cosine_f1 |
| value: 77.7423 |
| - type: cosine_f1_threshold |
| value: 72.788 |
| - type: cosine_precision |
| value: 74.2279 |
| - type: cosine_recall |
| value: 81.6061 |
| - type: cosine_ap |
| value: 85.4324 |
| - type: manhattan_accuracy |
| value: 88.786 |
| - type: manhattan_accuracy_threshold |
| value: 25561.4807 |
| - type: manhattan_f1 |
| value: 77.5953 |
| - type: manhattan_f1_threshold |
| value: 26504.0619 |
| - type: manhattan_precision |
| value: 76.1432 |
| - type: manhattan_recall |
| value: 79.1038 |
| - type: manhattan_ap |
| value: 85.3477 |
| - type: euclidean_accuracy |
| value: 88.76859999999999 |
| - type: euclidean_accuracy_threshold |
| value: 1181.4543 |
| - type: euclidean_f1 |
| value: 77.645 |
| - type: euclidean_f1_threshold |
| value: 1224.4793 |
| - type: euclidean_precision |
| value: 75.5925 |
| - type: euclidean_recall |
| value: 79.8121 |
| - type: euclidean_ap |
| value: 85.3781 |
| - type: dot_accuracy |
| value: 88.5707 |
| - type: dot_accuracy_threshold |
| value: 21387.7899 |
| - type: dot_f1 |
| value: 77.4888 |
| - type: dot_f1_threshold |
| value: 20875.6653 |
| - type: dot_precision |
| value: 75.58009999999999 |
| - type: dot_recall |
| value: 79.4965 |
| - type: dot_ap |
| value: 84.88550000000001 |
| - type: max_accuracy |
| value: 88.82100000000001 |
| - type: max_f1 |
| value: 77.7423 |
| - type: max_precision |
| value: 76.1432 |
| - type: max_recall |
| value: 81.6061 |
| - type: max_ap |
| value: 85.4324 |
| - type: main_score |
| value: 85.4324 |
| task: |
| type: PairClassification |
| pipeline_tag: sentence-similarity |
| tags: |
| - sentence-transformers |
| - sentence-similarity |
| - feature-extraction |
| - mteb |
| license: apache-2.0 |
| language: |
| - en |
| --- |
| |
| # Mini-GTE |
|
|
| <p align="center"> |
| <img src="./qtack_logo.png" alt="QTACK Logo" style="width:33%;"> |
| </p> |
|
|
| ## Overview |
| This is the first model developed by QTACK and serves as a proof of concept for our distillation approach! Built upon a distillbert-based architecture, Mini-GTE is distilled from GTE and designed for efficiency without sacrificing accuracy at only 66M parameters. As a standalone sentence transformer, it ranks 2nd on the MTEB classic leaderboard in the <100M parameter category and 63rd overall which makes it a strong choice for real-time query encoding, semantic search, and similarity tasks. |
|
|
| ## Model Details |
| - **Model Type:** Sentence Transformer |
| - **Base model:** [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) <!-- at revision 12040accade4e8a0f71eabdb258fecc2e7e948be --> |
| - **Maximum Sequence Length:** 512 tokens |
| - **Output Dimensionality:** 768 dimensions |
| - **Similarity Function:** Cosine Similarity |
|
|
| ## Usage |
| - Optimized for quick inference |
| - Great at quickly generating high quality encodings |
| - Easy to plug and play since it is distilled from GTE |
| - **We want to see how you’re using our model so we’ll give you a free coffee/$10 gift card if you get on call with us and show us what you’ve built!** |
|
|
| ## Getting Started |
| ### Installation |
| Mini-GTE is built on the [Sentence Transformers](https://www.sbert.net/) framework. To install the required packages, run: |
|
|
| ```bash |
| pip install -U sentence-transformers |
| ``` |
| ### Quick Start |
| Here's a quick example to get you started: |
|
|
| ```python |
| from sentence_transformers import SentenceTransformer |
| |
| # Download directly from Hugging Face |
| model = SentenceTransformer("sentence_transformers_model_id") |
| # Run inference |
| sentences = [ |
| 'The weather is lovely today.', |
| "It's so sunny outside!", |
| 'He drove to the stadium.', |
| ] |
| embeddings = model.encode(sentences) |
| print(embeddings.shape) # Expected: [3, 768] |
| |
| # Compute the similarity scores for the embeddings |
| similarities = model.similarity(embeddings, embeddings) |
| print(similarities.shape) # Expected: [3, 3] |
| ``` |
|
|
| ## Training Details |
| - Python: 3.10.12 |
| - Sentence Transformers: 3.3.1 |
| - Transformers: 4.48.0.dev0 |
| - PyTorch: 2.1.0a0+32f93b1 |
| - Accelerate: 1.2.0 |
| - Datasets: 2.21.0 |
| - Tokenizers: 0.21.0 |
|
|
| ## Getting Help |
|
|
| For any questions, suggestions, or issues, please contact the QTACK team directly through our [contact page](https://www.qtack.com/contact). |
|
|
|
|
