--- model-index: - name: Quark-Emb-8B results: - dataset: config: default name: MTEB AFQMC (default) revision: latest2023 split: validation type: C-MTEB/AFQMC metrics: - type: cosine_pearson value: 52.87704664791064 - type: cosine_spearman value: 53.567003436521375 - type: manhattan_pearson value: 52.07472780799189 - type: manhattan_spearman value: 53.5368469974003 - type: euclidean_pearson value: 52.074186684368016 - type: euclidean_spearman value: 53.515536447088074 - type: main_score value: 53.567003436521375 task: type: STS - dataset: config: default name: MTEB ATEC (default) revision: latest2023 split: test type: C-MTEB/ATEC metrics: - type: cosine_pearson value: 59.13301114775821 - type: cosine_spearman value: 53.42152760117668 - type: manhattan_pearson value: 60.05185745744783 - type: manhattan_spearman value: 53.36914545708813 - type: euclidean_pearson value: 60.17725014927802 - type: euclidean_spearman value: 53.431110991334485 - type: main_score value: 53.42152760117668 task: type: STS - dataset: config: zh name: MTEB AmazonReviewsClassification (zh) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: test type: mteb/amazon_reviews_multi metrics: - type: accuracy value: 54.74600000000001 - type: accuracy_stderr value: 1.060492338491892 - type: f1 value: 53.49846112279175 - type: f1_stderr value: 1.729174511160517 - type: main_score value: 54.74600000000001 task: type: Classification - dataset: config: zh name: MTEB AmazonReviewsClassification (zh) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: validation type: mteb/amazon_reviews_multi metrics: - type: accuracy value: 53.468 - type: accuracy_stderr value: 1.0129639677698308 - type: f1 value: 52.21987651679265 - type: f1_stderr value: 1.7016822177116173 - type: main_score value: 53.468 task: type: Classification - dataset: config: default name: MTEB BQ (default) revision: latest2023 split: test type: C-MTEB/BQ metrics: - type: cosine_pearson value: 69.640366232364 - type: cosine_spearman value: 70.65881213017273 - type: manhattan_pearson value: 67.76837799100343 - type: manhattan_spearman value: 70.5046111101055 - type: euclidean_pearson value: 67.83004194158737 - type: euclidean_spearman value: 70.60927547682859 - type: main_score value: 70.65881213017273 task: type: STS - dataset: config: default name: MTEB CLSClusteringP2P (default) revision: latest2023 split: test type: C-MTEB/CLSClusteringP2P metrics: - type: v_measure value: 62.32714079793593 - type: v_measure_std value: 1.5782386182731478 - type: main_score value: 62.32714079793593 task: type: Clustering - dataset: config: default name: MTEB CLSClusteringS2S (default) revision: latest2023 split: test type: C-MTEB/CLSClusteringS2S metrics: - type: v_measure value: 59.29532340833129 - type: v_measure_std value: 1.5258658358346424 - type: main_score value: 59.29532340833129 task: type: Clustering - dataset: config: default name: MTEB CMedQAv1 revision: latest2023 split: test type: C-MTEB/CMedQAv1-reranking metrics: - type: map value: 88.02263756085355 - type: mrr value: 90.18928571428572 - type: main_score value: 88.02263756085355 task: type: Reranking - dataset: config: default name: MTEB CMedQAv2 revision: latest2023 split: test type: C-MTEB/CMedQAv2-reranking metrics: - type: map value: 88.81199829110464 - type: mrr value: 90.81817460317461 - type: main_score value: 88.81199829110464 task: type: Reranking - dataset: config: default name: MTEB CmedqaRetrieval (default) revision: latest2023 split: dev type: C-MTEB/CmedqaRetrieval metrics: - type: map_at_1 value: 27.448 - type: map_at_10 value: 40.794000000000004 - type: map_at_100 value: 42.606 - type: map_at_1000 value: 42.711 - type: map_at_20 value: 41.778 - type: map_at_3 value: 36.429 - type: map_at_5 value: 38.841 - type: mrr_at_1 value: 41.510000000000005 - type: mrr_at_10 value: 49.986999999999995 - type: mrr_at_100 value: 50.908 - type: mrr_at_1000 value: 50.946000000000005 - type: mrr_at_20 value: 50.531000000000006 - type: mrr_at_3 value: 47.562 - type: mrr_at_5 value: 48.882 - type: ndcg_at_1 value: 41.510000000000005 - type: ndcg_at_10 value: 47.620000000000005 - type: ndcg_at_100 value: 54.586999999999996 - type: ndcg_at_1000 value: 56.324 - type: ndcg_at_20 value: 50.332 - type: ndcg_at_3 value: 42.27 - type: ndcg_at_5 value: 44.421 - type: precision_at_1 value: 41.510000000000005 - type: precision_at_10 value: 10.45 - type: precision_at_100 value: 1.6179999999999999 - type: precision_at_1000 value: 0.184 - type: precision_at_20 value: 6.1339999999999995 - type: precision_at_3 value: 23.823 - type: precision_at_5 value: 17.089 - type: recall_at_1 value: 27.448 - type: recall_at_10 value: 58.629 - type: recall_at_100 value: 87.26899999999999 - type: recall_at_1000 value: 98.713 - type: recall_at_20 value: 67.929 - type: recall_at_3 value: 42.331 - type: recall_at_5 value: 49.193999999999996 - type: main_score value: 47.620000000000005 task: type: Retrieval - dataset: config: default name: MTEB Cmnli (default) revision: latest2023 split: validation type: C-MTEB/CMNLI metrics: - type: cos_sim_accuracy value: 91.040288634997 - type: cos_sim_accuracy_threshold value: 96.31753556207411 - type: cos_sim_ap value: 95.94857244353375 - type: cos_sim_f1 value: 91.47971901200997 - type: cos_sim_f1_threshold value: 96.01236110428391 - type: cos_sim_precision value: 88.74477907232358 - type: cos_sim_recall value: 94.388590133271 - type: dot_accuracy value: 80.7696933253157 - type: dot_accuracy_threshold value: 58.4022485296251 - type: dot_ap value: 89.17817373664943 - type: dot_f1 value: 81.62572172534811 - type: dot_f1_threshold value: 58.18378730482039 - type: dot_precision value: 79.12642669007901 - type: dot_recall value: 84.28805237315876 - type: euclidean_accuracy value: 90.92002405291642 - type: euclidean_accuracy_threshold value: 21.553298629922512 - type: euclidean_ap value: 95.90941014786691 - type: euclidean_f1 value: 91.45241317095173 - type: euclidean_f1_threshold value: 22.109074422645463 - type: euclidean_precision value: 88.32498366368982 - type: euclidean_recall value: 94.80944587327565 - type: manhattan_accuracy value: 90.94407696933253 - type: manhattan_accuracy_threshold value: 524.1466620016906 - type: manhattan_ap value: 95.89310684813798 - type: manhattan_f1 value: 91.50400541577343 - type: manhattan_f1_threshold value: 525.5181014869215 - type: manhattan_precision value: 88.4212821631051 - type: manhattan_recall value: 94.80944587327565 - type: max_accuracy value: 91.040288634997 - type: max_ap value: 95.94857244353375 - type: max_f1 value: 91.50400541577343 task: type: PairClassification - dataset: config: default name: MTEB CovidRetrieval (default) revision: latest2023 split: dev type: C-MTEB/CovidRetrieval metrics: - type: map_at_1 value: 78.82000000000001 - type: map_at_10 value: 85.51100000000001 - type: map_at_100 value: 85.67099999999999 - type: map_at_1000 value: 85.672 - type: map_at_20 value: 85.641 - type: map_at_3 value: 84.321 - type: map_at_5 value: 85.048 - type: mrr_at_1 value: 78.925 - type: mrr_at_10 value: 85.548 - type: mrr_at_100 value: 85.698 - type: mrr_at_1000 value: 85.699 - type: mrr_at_20 value: 85.669 - type: mrr_at_3 value: 84.45700000000001 - type: mrr_at_5 value: 85.12100000000001 - type: ndcg_at_1 value: 78.925 - type: ndcg_at_10 value: 88.359 - type: ndcg_at_100 value: 88.98899999999999 - type: ndcg_at_1000 value: 89.017 - type: ndcg_at_20 value: 88.776 - type: ndcg_at_3 value: 86.086 - type: ndcg_at_5 value: 87.336 - type: precision_at_1 value: 78.925 - type: precision_at_10 value: 9.789 - type: precision_at_100 value: 1.0070000000000001 - type: precision_at_1000 value: 0.101 - type: precision_at_20 value: 4.979 - type: precision_at_3 value: 30.488 - type: precision_at_5 value: 18.925 - type: recall_at_1 value: 78.82000000000001 - type: recall_at_10 value: 96.997 - type: recall_at_100 value: 99.684 - type: recall_at_1000 value: 99.895 - type: recall_at_20 value: 98.52499999999999 - type: recall_at_3 value: 91.01700000000001 - type: recall_at_5 value: 93.994 - type: main_score value: 88.359 task: type: Retrieval - dataset: config: default name: MTEB DuRetrieval (default) revision: latest2023 split: dev type: C-MTEB/DuRetrieval metrics: - type: map_at_1 value: 28.03 - type: map_at_10 value: 85.60600000000001 - type: map_at_100 value: 88.14800000000001 - type: map_at_1000 value: 88.169 - type: map_at_20 value: 87.591 - type: map_at_3 value: 60.06 - type: map_at_5 value: 75.564 - type: mrr_at_1 value: 94.05 - type: mrr_at_10 value: 96.043 - type: mrr_at_100 value: 96.075 - type: mrr_at_1000 value: 96.077 - type: mrr_at_20 value: 96.06099999999999 - type: mrr_at_3 value: 95.875 - type: mrr_at_5 value: 96.017 - type: ndcg_at_1 value: 94.05 - type: ndcg_at_10 value: 91.58800000000001 - type: ndcg_at_100 value: 93.536 - type: ndcg_at_1000 value: 93.726 - type: ndcg_at_20 value: 92.64099999999999 - type: ndcg_at_3 value: 90.865 - type: ndcg_at_5 value: 89.972 - type: precision_at_1 value: 94.05 - type: precision_at_10 value: 43.19 - type: precision_at_100 value: 4.859 - type: precision_at_1000 value: 0.49 - type: precision_at_20 value: 23.3 - type: precision_at_3 value: 81.0 - type: precision_at_5 value: 68.36 - type: recall_at_1 value: 28.03 - type: recall_at_10 value: 92.095 - type: recall_at_100 value: 98.764 - type: recall_at_1000 value: 99.71 - type: recall_at_20 value: 95.87 - type: recall_at_3 value: 61.949 - type: recall_at_5 value: 79.41 - type: main_score value: 91.58800000000001 task: type: Retrieval - dataset: config: default name: MTEB EcomRetrieval (default) revision: latest2023 split: dev type: C-MTEB/EcomRetrieval metrics: - type: map_at_1 value: 58.599999999999994 - type: map_at_10 value: 68.88499999999999 - type: map_at_100 value: 69.269 - type: map_at_1000 value: 69.274 - type: map_at_20 value: 69.17699999999999 - type: map_at_3 value: 66.167 - type: map_at_5 value: 68.082 - type: mrr_at_1 value: 58.599999999999994 - type: mrr_at_10 value: 68.88499999999999 - type: mrr_at_100 value: 69.269 - type: mrr_at_1000 value: 69.274 - type: mrr_at_20 value: 69.17699999999999 - type: mrr_at_3 value: 66.167 - type: mrr_at_5 value: 68.082 - type: ndcg_at_1 value: 58.599999999999994 - type: ndcg_at_10 value: 74.018 - type: ndcg_at_100 value: 75.72 - type: ndcg_at_1000 value: 75.851 - type: ndcg_at_20 value: 75.08 - type: ndcg_at_3 value: 68.64 - type: ndcg_at_5 value: 72.075 - type: precision_at_1 value: 58.599999999999994 - type: precision_at_10 value: 9.01 - type: precision_at_100 value: 0.9769999999999999 - type: precision_at_1000 value: 0.099 - type: precision_at_20 value: 4.715 - type: precision_at_3 value: 25.267 - type: precision_at_5 value: 16.82 - type: recall_at_1 value: 58.599999999999994 - type: recall_at_10 value: 90.10000000000001 - type: recall_at_100 value: 97.7 - type: recall_at_1000 value: 98.7 - type: recall_at_20 value: 94.3 - type: recall_at_3 value: 75.8 - type: recall_at_5 value: 84.1 - type: main_score value: 74.018 task: type: Retrieval - dataset: config: default name: MTEB IFlyTek (default) revision: latest2023 split: validation type: C-MTEB/IFlyTek-classification metrics: - type: accuracy value: 55.79838399384378 - type: accuracy_stderr value: 0.273588131352537 - type: f1 value: 42.23811666656058 - type: f1_stderr value: 0.2317340030986553 - type: main_score value: 55.79838399384378 task: type: Classification - dataset: config: default name: MTEB JDReview (default) revision: latest2023 split: test type: C-MTEB/JDReview-classification metrics: - type: accuracy value: 89.11819887429644 - type: accuracy_stderr value: 1.5149440328845287 - type: ap value: 60.17445086411222 - type: ap_stderr value: 3.4864563160430384 - type: f1 value: 84.14324891240739 - type: f1_stderr value: 1.804154595730216 - type: main_score value: 89.11819887429644 task: type: Classification - dataset: config: default name: MTEB LCQMC (default) revision: latest2023 split: test type: C-MTEB/LCQMC metrics: - type: cosine_pearson value: 80.86541640109346 - type: cosine_spearman value: 79.60409318173409 - type: manhattan_pearson value: 81.12725142112909 - type: manhattan_spearman value: 79.61120096401483 - type: euclidean_pearson value: 81.1558178459699 - type: euclidean_spearman value: 79.63206760369867 - type: main_score value: 79.60409318173409 task: type: STS - dataset: config: default name: MTEB MMarcoReranking (default) revision: latest2023 split: dev type: C-MTEB/Mmarco-reranking metrics: - type: map value: 30.290346963620866 - type: mrr value: 29.661507936507935 - type: main_score value: 30.290346963620866 task: type: Reranking - dataset: config: default name: MTEB MMarcoRetrieval (default) revision: latest2023 split: dev type: C-MTEB/MMarcoRetrieval metrics: - type: map_at_1 value: 67.801 - type: map_at_10 value: 76.771 - type: map_at_100 value: 77.08 - type: map_at_1000 value: 77.091 - type: map_at_20 value: 76.982 - type: map_at_3 value: 75.035 - type: map_at_5 value: 76.171 - type: mrr_at_1 value: 70.057 - type: mrr_at_10 value: 77.387 - type: mrr_at_100 value: 77.65100000000001 - type: mrr_at_1000 value: 77.661 - type: mrr_at_20 value: 77.566 - type: mrr_at_3 value: 75.90299999999999 - type: mrr_at_5 value: 76.848 - type: ndcg_at_1 value: 70.057 - type: ndcg_at_10 value: 80.37100000000001 - type: ndcg_at_100 value: 81.71300000000001 - type: ndcg_at_1000 value: 81.982 - type: ndcg_at_20 value: 81.074 - type: ndcg_at_3 value: 77.12 - type: ndcg_at_5 value: 79.00500000000001 - type: precision_at_1 value: 70.057 - type: precision_at_10 value: 9.643 - type: precision_at_100 value: 1.031 - type: precision_at_1000 value: 0.105 - type: precision_at_20 value: 4.973000000000001 - type: precision_at_3 value: 28.959000000000003 - type: precision_at_5 value: 18.384 - type: recall_at_1 value: 67.801 - type: recall_at_10 value: 90.821 - type: recall_at_100 value: 96.809 - type: recall_at_1000 value: 98.87899999999999 - type: recall_at_20 value: 93.49300000000001 - type: recall_at_3 value: 82.26 - type: recall_at_5 value: 86.725 - type: main_score value: 80.37100000000001 task: type: Retrieval - dataset: config: zh-CN name: MTEB MassiveIntentClassification (zh-CN) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics: - type: accuracy value: 81.4862138533961 - type: accuracy_stderr value: 1.024666951162929 - type: f1 value: 78.57865898474617 - type: f1_stderr value: 1.1662766217911715 - type: main_score value: 81.4862138533961 task: type: Classification - dataset: config: zh-CN name: MTEB MassiveScenarioClassification (zh-CN) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics: - type: accuracy value: 86.43913920645595 - type: accuracy_stderr value: 0.6198364524624383 - type: f1 value: 85.45514450914429 - type: f1_stderr value: 0.775295463718716 - type: main_score value: 86.43913920645595 task: type: Classification - dataset: config: default name: MTEB MedicalRetrieval (default) revision: latest2023 split: dev type: C-MTEB/MedicalRetrieval metrics: - type: map_at_1 value: 60.0 - type: map_at_10 value: 66.673 - type: map_at_100 value: 67.239 - type: map_at_1000 value: 67.26299999999999 - type: map_at_20 value: 67.01899999999999 - type: map_at_3 value: 65.333 - type: map_at_5 value: 66.063 - type: mrr_at_1 value: 60.099999999999994 - type: mrr_at_10 value: 66.739 - type: mrr_at_100 value: 67.306 - type: mrr_at_1000 value: 67.33 - type: mrr_at_20 value: 67.086 - type: mrr_at_3 value: 65.4 - type: mrr_at_5 value: 66.13 - type: ndcg_at_1 value: 60.0 - type: ndcg_at_10 value: 69.786 - type: ndcg_at_100 value: 72.693 - type: ndcg_at_1000 value: 73.373 - type: ndcg_at_20 value: 71.032 - type: ndcg_at_3 value: 67.024 - type: ndcg_at_5 value: 68.34 - type: precision_at_1 value: 60.0 - type: precision_at_10 value: 7.95 - type: precision_at_100 value: 0.935 - type: precision_at_1000 value: 0.099 - type: precision_at_20 value: 4.22 - type: precision_at_3 value: 23.967 - type: precision_at_5 value: 15.02 - type: recall_at_1 value: 60.0 - type: recall_at_10 value: 79.5 - type: recall_at_100 value: 93.5 - type: recall_at_1000 value: 98.9 - type: recall_at_20 value: 84.39999999999999 - type: recall_at_3 value: 71.89999999999999 - type: recall_at_5 value: 75.1 - type: main_score value: 69.786 task: type: Retrieval - dataset: config: default name: MTEB MultilingualSentiment (default) revision: latest2023 split: validation type: C-MTEB/MultilingualSentiment-classification metrics: - type: accuracy value: 81.19666666666667 - type: accuracy_stderr value: 0.6507175526550155 - type: f1 value: 81.3717120301294 - type: f1_stderr value: 0.629161893845245 - type: main_score value: 81.19666666666667 task: type: Classification - dataset: config: default name: MTEB Ocnli (default) revision: latest2023 split: validation type: C-MTEB/OCNLI metrics: - type: cos_sim_accuracy value: 89.92961559285327 - type: cos_sim_accuracy_threshold value: 95.72410743295985 - type: cos_sim_ap value: 94.04072585697942 - type: cos_sim_f1 value: 90.6060606060606 - type: cos_sim_f1_threshold value: 95.71085030120679 - type: cos_sim_precision value: 86.83446272991287 - type: cos_sim_recall value: 94.72016895459345 - type: dot_accuracy value: 84.29886302111532 - type: dot_accuracy_threshold value: 58.39834018444028 - type: dot_ap value: 90.71149047430606 - type: dot_f1 value: 84.83263598326361 - type: dot_f1_threshold value: 58.39834018444028 - type: dot_precision value: 84.04145077720207 - type: dot_recall value: 85.6388595564942 - type: euclidean_accuracy value: 89.87547374120194 - type: euclidean_accuracy_threshold value: 22.827705768877962 - type: euclidean_ap value: 93.87312138426815 - type: euclidean_f1 value: 90.5982905982906 - type: euclidean_f1_threshold value: 22.940558234199905 - type: euclidean_precision value: 86.468330134357 - type: euclidean_recall value: 95.14255543822597 - type: manhattan_accuracy value: 89.44233892799134 - type: manhattan_accuracy_threshold value: 544.6256417358975 - type: manhattan_ap value: 93.8313800715528 - type: manhattan_f1 value: 90.16641452344932 - type: manhattan_f1_threshold value: 544.6256417358975 - type: manhattan_precision value: 86.2934362934363 - type: manhattan_recall value: 94.40337909186906 - type: max_accuracy value: 89.92961559285327 - type: max_ap value: 94.04072585697942 - type: max_f1 value: 90.6060606060606 task: type: PairClassification - dataset: config: default name: MTEB OnlineShopping (default) revision: latest2023 split: test type: C-MTEB/OnlineShopping-classification metrics: - type: accuracy value: 93.83999999999999 - type: accuracy_stderr value: 0.4521061822182879 - type: ap value: 92.19373645628713 - type: ap_stderr value: 0.2927396159644918 - type: f1 value: 93.83158946571204 - type: f1_stderr value: 0.4472553159438725 - type: main_score value: 93.83999999999999 task: type: Classification - dataset: config: default name: MTEB PAWSX (default) revision: latest2023 split: test type: C-MTEB/PAWSX metrics: - type: cosine_pearson value: 50.30680596662101 - type: cosine_spearman value: 52.41534063346883 - type: manhattan_pearson value: 51.81137421589127 - type: manhattan_spearman value: 52.40332176267904 - type: euclidean_pearson value: 51.842454511431235 - type: euclidean_spearman value: 52.4062829337432 - type: main_score value: 52.41534063346883 task: type: STS - dataset: config: default name: MTEB QBQTC (default) revision: latest2023 split: test type: C-MTEB/QBQTC metrics: - type: cosine_pearson value: 58.31070289198933 - type: cosine_spearman value: 57.966010447080684 - type: manhattan_pearson value: 54.99874211888254 - type: manhattan_spearman value: 57.796012247889195 - type: euclidean_pearson value: 55.138798573277455 - type: euclidean_spearman value: 57.95150876116391 - type: main_score value: 57.966010447080684 task: type: STS - dataset: config: zh name: MTEB STS22 (zh) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts metrics: - type: cosine_pearson value: 75.26028549682404 - type: cosine_spearman value: 73.9002967678025 - type: manhattan_pearson value: 73.47220514464013 - type: manhattan_spearman value: 73.74093326288234 - type: euclidean_pearson value: 73.59040445366989 - type: euclidean_spearman value: 73.9002967678025 - type: main_score value: 73.9002967678025 task: type: STS - dataset: config: default name: MTEB STSB (default) revision: latest2023 split: test type: C-MTEB/STSB metrics: - type: cosine_pearson value: 78.17081373176123 - type: cosine_spearman value: 78.61566426272397 - type: manhattan_pearson value: 77.66643088697434 - type: manhattan_spearman value: 78.94692354474782 - type: euclidean_pearson value: 77.69471041307843 - type: euclidean_spearman value: 78.92513847741967 - type: main_score value: 78.61566426272397 task: type: STS - dataset: config: default name: MTEB T2Reranking (default) revision: latest2023 split: dev type: C-MTEB/T2Reranking metrics: - type: map value: 68.13018101639273 - type: mrr value: 79.13973922902494 - type: main_score value: 68.13018101639273 task: type: Reranking - dataset: config: default name: MTEB T2Retrieval (default) revision: latest2023 split: dev type: C-MTEB/T2Retrieval metrics: - type: map_at_1 value: 28.591 - type: map_at_10 value: 80.979 - type: map_at_100 value: 84.411 - type: map_at_1000 value: 84.458 - type: map_at_20 value: 83.68100000000001 - type: map_at_3 value: 56.967999999999996 - type: map_at_5 value: 70.098 - type: mrr_at_1 value: 92.12700000000001 - type: mrr_at_10 value: 94.094 - type: mrr_at_100 value: 94.161 - type: mrr_at_1000 value: 94.164 - type: mrr_at_20 value: 94.14 - type: mrr_at_3 value: 93.753 - type: mrr_at_5 value: 93.98100000000001 - type: ndcg_at_1 value: 92.12700000000001 - type: ndcg_at_10 value: 87.586 - type: ndcg_at_100 value: 90.58500000000001 - type: ndcg_at_1000 value: 91.05 - type: ndcg_at_20 value: 89.132 - type: ndcg_at_3 value: 88.86800000000001 - type: ndcg_at_5 value: 87.673 - type: precision_at_1 value: 92.12700000000001 - type: precision_at_10 value: 43.35 - type: precision_at_100 value: 5.06 - type: precision_at_1000 value: 0.517 - type: precision_at_20 value: 23.895 - type: precision_at_3 value: 77.664 - type: precision_at_5 value: 65.231 - type: recall_at_1 value: 28.591 - type: recall_at_10 value: 86.342 - type: recall_at_100 value: 96.274 - type: recall_at_1000 value: 98.666 - type: recall_at_20 value: 91.741 - type: recall_at_3 value: 58.386 - type: recall_at_5 value: 72.942 - type: main_score value: 87.586 task: type: Retrieval - dataset: config: default name: MTEB TNews (default) revision: latest2023 split: validation type: C-MTEB/TNews-classification metrics: - type: accuracy value: 58.057 - type: accuracy_stderr value: 0.4056365368159032 - type: f1 value: 56.16542257610506 - type: f1_stderr value: 0.49560443919264746 - type: main_score value: 58.057 task: type: Classification - dataset: config: default name: MTEB ThuNewsClusteringP2P (default) revision: latest2023 split: test type: C-MTEB/ThuNewsClusteringP2P metrics: - type: v_measure value: 83.43086890900754 - type: v_measure_std value: 1.3242733220406704 - type: main_score value: 83.43086890900754 task: type: Clustering - dataset: config: default name: MTEB ThuNewsClusteringS2S (default) revision: latest2023 split: test type: C-MTEB/ThuNewsClusteringS2S metrics: - type: v_measure value: 80.17922689954183 - type: v_measure_std value: 2.1732975942130612 - type: main_score value: 80.17922689954183 task: type: Clustering - dataset: config: default name: MTEB VideoRetrieval (default) revision: latest2023 split: dev type: C-MTEB/VideoRetrieval metrics: - type: map_at_1 value: 68.60000000000001 - type: map_at_10 value: 77.518 - type: map_at_100 value: 77.815 - type: map_at_1000 value: 77.82 - type: map_at_20 value: 77.73299999999999 - type: map_at_3 value: 76.167 - type: map_at_5 value: 76.932 - type: mrr_at_1 value: 68.60000000000001 - type: mrr_at_10 value: 77.518 - type: mrr_at_100 value: 77.815 - type: mrr_at_1000 value: 77.82 - type: mrr_at_20 value: 77.73299999999999 - type: mrr_at_3 value: 76.167 - type: mrr_at_5 value: 76.932 - type: ndcg_at_1 value: 68.60000000000001 - type: ndcg_at_10 value: 81.339 - type: ndcg_at_100 value: 82.646 - type: ndcg_at_1000 value: 82.76599999999999 - type: ndcg_at_20 value: 82.107 - type: ndcg_at_3 value: 78.569 - type: ndcg_at_5 value: 79.937 - type: precision_at_1 value: 68.60000000000001 - type: precision_at_10 value: 9.31 - type: precision_at_100 value: 0.989 - type: precision_at_1000 value: 0.1 - type: precision_at_20 value: 4.805000000000001 - type: precision_at_3 value: 28.499999999999996 - type: precision_at_5 value: 17.76 - type: recall_at_1 value: 68.60000000000001 - type: recall_at_10 value: 93.10000000000001 - type: recall_at_100 value: 98.9 - type: recall_at_1000 value: 99.8 - type: recall_at_20 value: 96.1 - type: recall_at_3 value: 85.5 - type: recall_at_5 value: 88.8 - type: main_score value: 81.339 task: type: Retrieval - dataset: config: default name: MTEB Waimai (default) revision: latest2023 split: test type: C-MTEB/waimai-classification metrics: - type: accuracy value: 90.63000000000001 - type: accuracy_stderr value: 0.49203658400570216 - type: ap value: 77.93466200571231 - type: ap_stderr value: 1.2006502477223735 - type: f1 value: 89.36361097500829 - type: f1_stderr value: 0.43660966359249054 - type: main_score value: 90.63000000000001 task: type: Classification tags: - mteb --- # Quark-Emb-8B - Chinese Text Embedding Model developed by Alibaba Quark-LLM Team. Details will be published later.