--- model-index: - name: Quark-Emb-1.5b results: - dataset: config: default name: MTEB AFQMC revision: None split: validation type: C-MTEB/AFQMC metrics: - type: cosine_pearson value: 47.14285927987258 - type: cosine_spearman value: 48.161200368263025 - type: manhattan_pearson value: 46.852921578928694 - type: manhattan_spearman value: 48.0768829644805 - type: euclidean_pearson value: 46.934710408297846 - type: euclidean_spearman value: 48.161200368263025 - type: main_score value: 48.161200368263025 task: type: STS - dataset: config: default name: MTEB ATEC revision: None split: test type: C-MTEB/ATEC metrics: - type: cosine_pearson value: 53.31694395347832 - type: cosine_spearman value: 50.82142054857025 - type: manhattan_pearson value: 55.63018022546727 - type: manhattan_spearman value: 50.808925663235286 - type: euclidean_pearson value: 55.630897902214585 - type: euclidean_spearman value: 50.82142054857025 - type: main_score value: 50.82142054857025 task: type: STS - dataset: config: zh name: MTEB AmazonReviewsClassification (zh) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: test type: mteb/amazon_reviews_multi metrics: - type: accuracy value: 51.93800000000001 - type: accuracy_stderr value: 1.6225030046197138 - type: f1 value: 49.36480272612989 - type: f1_stderr value: 2.402473535325102 - type: main_score value: 51.93800000000001 task: type: Classification - dataset: config: zh name: MTEB AmazonReviewsClassification (zh) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: validation type: mteb/amazon_reviews_multi metrics: - type: accuracy value: 50.757999999999996 - type: accuracy_stderr value: 1.1949041802588176 - type: f1 value: 48.18542841607346 - type: f1_stderr value: 2.025507464835368 - type: main_score value: 50.757999999999996 task: type: Classification - dataset: config: default name: MTEB BQ revision: None split: test type: C-MTEB/BQ metrics: - type: cosine_pearson value: 66.94471481392273 - type: cosine_spearman value: 67.86811107045457 - type: manhattan_pearson value: 65.56778188873142 - type: manhattan_spearman value: 67.83060870618156 - type: euclidean_pearson value: 65.63668085779311 - type: euclidean_spearman value: 67.86811107045457 - type: main_score value: 67.86811107045457 task: type: STS - dataset: config: default name: MTEB CLSClusteringP2P revision: None split: test type: C-MTEB/CLSClusteringP2P metrics: - type: v_measure value: 58.53706905558472 - type: v_measure_std value: 1.3628784531981595 - type: main_score value: 58.53706905558472 task: type: Clustering - dataset: config: default name: MTEB CLSClusteringS2S revision: None split: test type: C-MTEB/CLSClusteringS2S metrics: - type: v_measure value: 54.70969139354621 - type: v_measure_std value: 1.938384688132648 - type: main_score value: 54.70969139354621 task: type: Clustering - dataset: config: default name: MTEB CMedQAv1 revision: None split: test type: C-MTEB/CMedQAv1-reranking metrics: - type: map value: 87.79521046311835 - type: mrr value: 90.01547619047618 - type: main_score value: 87.79521046311835 task: type: Reranking - dataset: config: default name: MTEB CMedQAv2 revision: None split: test type: C-MTEB/CMedQAv2-reranking metrics: - type: map value: 87.89916670870878 - type: mrr value: 89.92595238095238 - type: main_score value: 87.89916670870878 task: type: Reranking - dataset: config: default name: MTEB CmedqaRetrieval revision: None split: dev type: C-MTEB/CmedqaRetrieval metrics: - type: map_at_1 value: 25.444 - type: map_at_10 value: 37.763999999999996 - type: map_at_100 value: 39.641999999999996 - type: map_at_1000 value: 39.756 - type: map_at_3 value: 33.742 - type: map_at_5 value: 35.906 - type: mrr_at_1 value: 38.71 - type: mrr_at_10 value: 46.744 - type: mrr_at_100 value: 47.745 - type: mrr_at_1000 value: 47.791 - type: mrr_at_3 value: 44.324000000000005 - type: mrr_at_5 value: 45.696 - type: ndcg_at_1 value: 38.71 - type: ndcg_at_10 value: 44.285000000000004 - type: ndcg_at_100 value: 51.69200000000001 - type: ndcg_at_1000 value: 53.669999999999995 - type: ndcg_at_3 value: 39.273 - type: ndcg_at_5 value: 41.254000000000005 - type: precision_at_1 value: 38.71 - type: precision_at_10 value: 9.825000000000001 - type: precision_at_100 value: 1.583 - type: precision_at_1000 value: 0.183 - type: precision_at_3 value: 22.197 - type: precision_at_5 value: 16.019 - type: recall_at_1 value: 25.444 - type: recall_at_10 value: 54.535999999999994 - type: recall_at_100 value: 85.307 - type: recall_at_1000 value: 98.473 - type: recall_at_3 value: 39.274 - type: recall_at_5 value: 45.580999999999996 - type: main_score value: 44.285000000000004 task: type: Retrieval - dataset: config: default name: MTEB Cmnli revision: None split: validation type: C-MTEB/CMNLI metrics: - type: cos_sim_accuracy value: 89.58508719182201 - type: cos_sim_accuracy_threshold value: 97.09511288861569 - type: cos_sim_ap value: 95.12338246323735 - type: cos_sim_f1 value: 90.19211324570271 - type: cos_sim_f1_threshold value: 97.02014138938755 - type: cos_sim_precision value: 86.80795847750865 - type: cos_sim_recall value: 93.85083002104278 - type: dot_accuracy value: 89.58508719182201 - type: dot_accuracy_threshold value: 97.0951128886157 - type: dot_ap value: 95.13959275940286 - type: dot_f1 value: 90.19211324570271 - type: dot_f1_threshold value: 97.02014138938755 - type: dot_precision value: 86.80795847750865 - type: dot_recall value: 93.85083002104278 - type: euclidean_accuracy value: 89.58508719182201 - type: euclidean_accuracy_threshold value: 24.103473235790947 - type: euclidean_ap value: 95.12338246323735 - type: euclidean_f1 value: 90.19211324570271 - type: euclidean_f1_threshold value: 24.412531977088996 - type: euclidean_precision value: 86.80795847750865 - type: euclidean_recall value: 93.85083002104278 - type: manhattan_accuracy value: 89.57306073361396 - type: manhattan_accuracy_threshold value: 729.1211254739587 - type: manhattan_ap value: 95.12388319543341 - type: manhattan_f1 value: 90.13956654941563 - type: manhattan_f1_threshold value: 733.155723492131 - type: manhattan_precision value: 87.56613756613757 - type: manhattan_recall value: 92.8688332943652 - type: max_accuracy value: 89.58508719182201 - type: max_ap value: 95.13959275940286 - type: max_f1 value: 90.19211324570271 task: type: PairClassification - dataset: config: default name: MTEB CovidRetrieval revision: None split: dev type: C-MTEB/CovidRetrieval metrics: - type: map_at_1 value: 75.29 - type: map_at_10 value: 82.392 - type: map_at_100 value: 82.581 - type: map_at_1000 value: 82.585 - type: map_at_3 value: 80.88300000000001 - type: map_at_5 value: 81.71199999999999 - type: mrr_at_1 value: 75.553 - type: mrr_at_10 value: 82.422 - type: mrr_at_100 value: 82.6 - type: mrr_at_1000 value: 82.604 - type: mrr_at_3 value: 80.927 - type: mrr_at_5 value: 81.765 - type: ndcg_at_1 value: 75.44800000000001 - type: ndcg_at_10 value: 85.655 - type: ndcg_at_100 value: 86.435 - type: ndcg_at_1000 value: 86.541 - type: ndcg_at_3 value: 82.60300000000001 - type: ndcg_at_5 value: 84.062 - type: precision_at_1 value: 75.44800000000001 - type: precision_at_10 value: 9.663 - type: precision_at_100 value: 1.002 - type: precision_at_1000 value: 0.101 - type: precision_at_3 value: 29.329 - type: precision_at_5 value: 18.314 - type: recall_at_1 value: 75.29 - type: recall_at_10 value: 95.838 - type: recall_at_100 value: 99.157 - type: recall_at_1000 value: 100.0 - type: recall_at_3 value: 87.566 - type: recall_at_5 value: 90.991 - type: main_score value: 85.655 task: type: Retrieval - dataset: config: default name: MTEB DuRetrieval revision: None split: dev type: C-MTEB/DuRetrieval metrics: - type: map_at_1 value: 27.584999999999997 - type: map_at_10 value: 85.112 - type: map_at_100 value: 87.632 - type: map_at_1000 value: 87.654 - type: map_at_3 value: 59.504999999999995 - type: map_at_5 value: 75.029 - type: mrr_at_1 value: 93.30000000000001 - type: mrr_at_10 value: 95.44200000000001 - type: mrr_at_100 value: 95.498 - type: mrr_at_1000 value: 95.5 - type: mrr_at_3 value: 95.258 - type: mrr_at_5 value: 95.36099999999999 - type: ndcg_at_1 value: 93.30000000000001 - type: ndcg_at_10 value: 91.086 - type: ndcg_at_100 value: 93.089 - type: ndcg_at_1000 value: 93.297 - type: ndcg_at_3 value: 90.432 - type: ndcg_at_5 value: 89.361 - type: precision_at_1 value: 93.30000000000001 - type: precision_at_10 value: 43.21 - type: precision_at_100 value: 4.857 - type: precision_at_1000 value: 0.49 - type: precision_at_3 value: 81.0 - type: precision_at_5 value: 68.28999999999999 - type: recall_at_1 value: 27.584999999999997 - type: recall_at_10 value: 91.73599999999999 - type: recall_at_100 value: 98.648 - type: recall_at_1000 value: 99.751 - type: recall_at_3 value: 61.378 - type: recall_at_5 value: 78.672 - type: main_score value: 91.086 task: type: Retrieval - dataset: config: default name: MTEB EcomRetrieval revision: None split: dev type: C-MTEB/EcomRetrieval metrics: - type: map_at_1 value: 55.1 - type: map_at_10 value: 65.268 - type: map_at_100 value: 65.756 - type: map_at_1000 value: 65.765 - type: map_at_3 value: 63.132999999999996 - type: map_at_5 value: 64.25800000000001 - type: mrr_at_1 value: 55.1 - type: mrr_at_10 value: 65.268 - type: mrr_at_100 value: 65.756 - type: mrr_at_1000 value: 65.765 - type: mrr_at_3 value: 63.132999999999996 - type: mrr_at_5 value: 64.25800000000001 - type: ndcg_at_1 value: 55.1 - type: ndcg_at_10 value: 70.15599999999999 - type: ndcg_at_100 value: 72.368 - type: ndcg_at_1000 value: 72.635 - type: ndcg_at_3 value: 65.697 - type: ndcg_at_5 value: 67.741 - type: precision_at_1 value: 55.1 - type: precision_at_10 value: 8.55 - type: precision_at_100 value: 0.955 - type: precision_at_1000 value: 0.098 - type: precision_at_3 value: 24.367 - type: precision_at_5 value: 15.620000000000001 - type: recall_at_1 value: 55.1 - type: recall_at_10 value: 85.5 - type: recall_at_100 value: 95.5 - type: recall_at_1000 value: 97.6 - type: recall_at_3 value: 73.1 - type: recall_at_5 value: 78.10000000000001 - type: main_score value: 70.15599999999999 task: type: Retrieval - dataset: config: default name: MTEB IFlyTek revision: None split: validation type: C-MTEB/IFlyTek-classification metrics: - type: accuracy value: 52.743362831858406 - type: accuracy_stderr value: 0.4449967616714387 - type: f1 value: 40.13427504900375 - type: f1_stderr value: 0.17565290177989018 - type: main_score value: 52.743362831858406 task: type: Classification - dataset: config: default name: MTEB JDReview revision: None split: test type: C-MTEB/JDReview-classification metrics: - type: accuracy value: 90.13133208255161 - type: accuracy_stderr value: 0.9647249630155678 - type: ap value: 62.848199712439765 - type: ap_stderr value: 1.986859492917626 - type: f1 value: 85.48543445690254 - type: f1_stderr value: 1.0490059319804828 - type: main_score value: 90.13133208255161 task: type: Classification - dataset: config: default name: MTEB LCQMC revision: None split: test type: C-MTEB/LCQMC metrics: - type: cosine_pearson value: 77.75677384428634 - type: cosine_spearman value: 78.86284859566986 - type: manhattan_pearson value: 79.8032754323316 - type: manhattan_spearman value: 78.85558562163624 - type: euclidean_pearson value: 79.82552324704292 - type: euclidean_spearman value: 78.86284859566986 - type: main_score value: 78.86284859566986 task: type: STS - dataset: config: default name: MTEB MMarcoReranking revision: None split: dev type: C-MTEB/Mmarco-reranking metrics: - type: map value: 30.737025407798523 - type: mrr value: 29.26111111111111 - type: main_score value: 30.737025407798523 task: type: Reranking - dataset: config: default name: MTEB MMarcoRetrieval revision: None split: dev type: C-MTEB/MMarcoRetrieval metrics: - type: map_at_1 value: 70.244 - type: map_at_10 value: 78.975 - type: map_at_100 value: 79.253 - type: map_at_1000 value: 79.26100000000001 - type: map_at_3 value: 77.363 - type: map_at_5 value: 78.364 - type: mrr_at_1 value: 72.521 - type: mrr_at_10 value: 79.514 - type: mrr_at_100 value: 79.75 - type: mrr_at_1000 value: 79.757 - type: mrr_at_3 value: 78.095 - type: mrr_at_5 value: 78.987 - type: ndcg_at_1 value: 72.521 - type: ndcg_at_10 value: 82.395 - type: ndcg_at_100 value: 83.554 - type: ndcg_at_1000 value: 83.774 - type: ndcg_at_3 value: 79.341 - type: ndcg_at_5 value: 81.036 - type: precision_at_1 value: 72.521 - type: precision_at_10 value: 9.812 - type: precision_at_100 value: 1.038 - type: precision_at_1000 value: 0.106 - type: precision_at_3 value: 29.694 - type: precision_at_5 value: 18.712999999999997 - type: recall_at_1 value: 70.244 - type: recall_at_10 value: 92.35 - type: recall_at_100 value: 97.419 - type: recall_at_1000 value: 99.16199999999999 - type: recall_at_3 value: 84.303 - type: recall_at_5 value: 88.325 - type: main_score value: 82.395 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: 76.3752521856086 - type: accuracy_stderr value: 1.3911220977886072 - type: f1 value: 73.38330839246518 - type: f1_stderr value: 0.9864886479418102 - type: main_score value: 76.3752521856086 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: 81.8022864828514 - type: accuracy_stderr value: 1.4060452754762354 - type: f1 value: 80.85164585310973 - type: f1_stderr value: 1.2664399398388577 - type: main_score value: 81.8022864828514 task: type: Classification - dataset: config: default name: MTEB MedicalRetrieval revision: None split: dev type: C-MTEB/MedicalRetrieval metrics: - type: map_at_1 value: 57.199999999999996 - type: map_at_10 value: 63.346999999999994 - type: map_at_100 value: 63.852 - type: map_at_1000 value: 63.88700000000001 - type: map_at_3 value: 61.967000000000006 - type: map_at_5 value: 62.66199999999999 - type: mrr_at_1 value: 57.3 - type: mrr_at_10 value: 63.397000000000006 - type: mrr_at_100 value: 63.902 - type: mrr_at_1000 value: 63.937 - type: mrr_at_3 value: 62.017 - type: mrr_at_5 value: 62.712 - type: ndcg_at_1 value: 57.199999999999996 - type: ndcg_at_10 value: 66.38300000000001 - type: ndcg_at_100 value: 69.267 - type: ndcg_at_1000 value: 70.233 - type: ndcg_at_3 value: 63.44499999999999 - type: ndcg_at_5 value: 64.71000000000001 - type: precision_at_1 value: 57.199999999999996 - type: precision_at_10 value: 7.6 - type: precision_at_100 value: 0.905 - type: precision_at_1000 value: 0.098 - type: precision_at_3 value: 22.567 - type: precision_at_5 value: 14.16 - type: recall_at_1 value: 57.199999999999996 - type: recall_at_10 value: 76.0 - type: recall_at_100 value: 90.5 - type: recall_at_1000 value: 98.2 - type: recall_at_3 value: 67.7 - type: recall_at_5 value: 70.8 - type: main_score value: 66.38300000000001 task: type: Retrieval - dataset: config: default name: MTEB MultilingualSentiment revision: None split: validation type: C-MTEB/MultilingualSentiment-classification metrics: - type: accuracy value: 80.12333333333335 - type: accuracy_stderr value: 0.31377628265303376 - type: f1 value: 80.26166732998303 - type: f1_stderr value: 0.2836457609943486 - type: main_score value: 80.12333333333335 task: type: Classification - dataset: config: default name: MTEB Ocnli revision: None split: validation type: C-MTEB/OCNLI metrics: - type: cos_sim_accuracy value: 87.54737412019492 - type: cos_sim_accuracy_threshold value: 96.99121475650863 - type: cos_sim_ap value: 91.71816430648396 - type: cos_sim_f1 value: 88.27655310621243 - type: cos_sim_f1_threshold value: 96.8697507135398 - type: cos_sim_precision value: 83.98474737845567 - type: cos_sim_recall value: 93.03062302006336 - type: dot_accuracy value: 87.54737412019492 - type: dot_accuracy_threshold value: 96.99121475650863 - type: dot_ap value: 91.71816430648396 - type: dot_f1 value: 88.27655310621243 - type: dot_f1_threshold value: 96.86975071353979 - type: dot_precision value: 83.98474737845567 - type: dot_recall value: 93.03062302006336 - type: euclidean_accuracy value: 87.54737412019492 - type: euclidean_accuracy_threshold value: 24.530733065589622 - type: euclidean_ap value: 91.71816430648396 - type: euclidean_f1 value: 88.27655310621243 - type: euclidean_f1_threshold value: 25.020988098238107 - type: euclidean_precision value: 83.98474737845567 - type: euclidean_recall value: 93.03062302006336 - type: manhattan_accuracy value: 87.27666486193829 - type: manhattan_accuracy_threshold value: 752.4905438529156 - type: manhattan_ap value: 91.70647280240597 - type: manhattan_f1 value: 88.08920425747591 - type: manhattan_f1_threshold value: 752.4905438529156 - type: manhattan_precision value: 84.69785575048732 - type: manhattan_recall value: 91.76346356916578 - type: max_accuracy value: 87.54737412019492 - type: max_ap value: 91.71816430648396 - type: max_f1 value: 88.27655310621243 task: type: PairClassification - dataset: config: default name: MTEB OnlineShopping revision: None split: test type: C-MTEB/OnlineShopping-classification metrics: - type: accuracy value: 94.46999999999998 - type: accuracy_stderr value: 0.2865309756378883 - type: ap value: 93.00417328431348 - type: ap_stderr value: 0.5383352662551945 - type: f1 value: 94.4618263222835 - type: f1_stderr value: 0.2840342094212124 - type: main_score value: 94.46999999999998 task: type: Classification - dataset: config: default name: MTEB PAWSX revision: None split: test type: C-MTEB/PAWSX metrics: - type: cosine_pearson value: 46.85211982536296 - type: cosine_spearman value: 49.917839688145996 - type: manhattan_pearson value: 49.66820248148123 - type: manhattan_spearman value: 49.94013555794742 - type: euclidean_pearson value: 49.63608491973345 - type: euclidean_spearman value: 49.917839688145996 - type: main_score value: 49.917839688145996 task: type: STS - dataset: config: default name: MTEB QBQTC revision: None split: test type: C-MTEB/QBQTC metrics: - type: cosine_pearson value: 55.18355221701257 - type: cosine_spearman value: 54.67390932826382 - type: manhattan_pearson value: 53.32847494683504 - type: manhattan_spearman value: 54.61660160532041 - type: euclidean_pearson value: 53.405599174765364 - type: euclidean_spearman value: 54.67390932826382 - type: main_score value: 54.67390932826382 task: type: STS - dataset: config: zh name: MTEB STS22 (zh) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts metrics: - type: cosine_pearson value: 67.89319522460808 - type: cosine_spearman value: 68.98524514928238 - type: manhattan_pearson value: 67.65257700660463 - type: manhattan_spearman value: 69.17199742136434 - type: euclidean_pearson value: 67.52535570217756 - type: euclidean_spearman value: 68.98524514928238 - type: main_score value: 68.98524514928238 task: type: STS - dataset: config: default name: MTEB STSB revision: None split: test type: C-MTEB/STSB metrics: - type: cosine_pearson value: 75.4871803618505 - type: cosine_spearman value: 76.17471665593993 - type: manhattan_pearson value: 75.73597640243183 - type: manhattan_spearman value: 76.20048941210949 - type: euclidean_pearson value: 75.66172628182565 - type: euclidean_spearman value: 76.17471665593993 - type: main_score value: 76.17471665593993 task: type: STS - dataset: config: default name: MTEB T2Reranking revision: None split: dev type: C-MTEB/T2Reranking metrics: - type: map value: 67.45036855302303 - type: mrr value: 78.15107441080697 - type: main_score value: 67.45036855302303 task: type: Reranking - dataset: config: default name: MTEB T2Retrieval revision: None split: dev type: C-MTEB/T2Retrieval metrics: - type: map_at_1 value: 28.094 - type: map_at_10 value: 79.367 - type: map_at_100 value: 82.89800000000001 - type: map_at_1000 value: 82.953 - type: map_at_3 value: 55.782 - type: map_at_5 value: 68.667 - type: mrr_at_1 value: 91.237 - type: mrr_at_10 value: 93.399 - type: mrr_at_100 value: 93.479 - type: mrr_at_1000 value: 93.482 - type: mrr_at_3 value: 93.029 - type: mrr_at_5 value: 93.273 - type: ndcg_at_1 value: 91.237 - type: ndcg_at_10 value: 86.368 - type: ndcg_at_100 value: 89.637 - type: ndcg_at_1000 value: 90.16300000000001 - type: ndcg_at_3 value: 87.691 - type: ndcg_at_5 value: 86.462 - type: precision_at_1 value: 91.237 - type: precision_at_10 value: 42.841 - type: precision_at_100 value: 5.047 - type: precision_at_1000 value: 0.517 - type: precision_at_3 value: 76.708 - type: precision_at_5 value: 64.428 - type: recall_at_1 value: 28.094 - type: recall_at_10 value: 85.181 - type: recall_at_100 value: 95.953 - type: recall_at_1000 value: 98.63 - type: recall_at_3 value: 57.267999999999994 - type: recall_at_5 value: 71.75399999999999 - type: main_score value: 86.368 task: type: Retrieval - dataset: config: default name: MTEB TNews revision: None split: validation type: C-MTEB/TNews-classification metrics: - type: accuracy value: 55.482 - type: accuracy_stderr value: 0.3268577672321692 - type: f1 value: 53.57211848235611 - type: f1_stderr value: 0.3511138517262321 - type: main_score value: 55.482 task: type: Classification - dataset: config: default name: MTEB ThuNewsClusteringP2P revision: None split: test type: C-MTEB/ThuNewsClusteringP2P metrics: - type: v_measure value: 79.44895384385426 - type: v_measure_std value: 2.315777338929376 - type: main_score value: 79.44895384385426 task: type: Clustering - dataset: config: default name: MTEB ThuNewsClusteringS2S revision: None split: test type: C-MTEB/ThuNewsClusteringS2S metrics: - type: v_measure value: 76.95904984506356 - type: v_measure_std value: 2.244801218820472 - type: main_score value: 76.95904984506356 task: type: Clustering - dataset: config: default name: MTEB VideoRetrieval revision: None split: dev type: C-MTEB/VideoRetrieval metrics: - type: map_at_1 value: 65.60000000000001 - type: map_at_10 value: 75.24499999999999 - type: map_at_100 value: 75.51 - type: map_at_1000 value: 75.519 - type: map_at_3 value: 73.68299999999999 - type: map_at_5 value: 74.638 - type: mrr_at_1 value: 65.60000000000001 - type: mrr_at_10 value: 75.24499999999999 - type: mrr_at_100 value: 75.51 - type: mrr_at_1000 value: 75.519 - type: mrr_at_3 value: 73.68299999999999 - type: mrr_at_5 value: 74.638 - type: ndcg_at_1 value: 65.60000000000001 - type: ndcg_at_10 value: 79.338 - type: ndcg_at_100 value: 80.585 - type: ndcg_at_1000 value: 80.772 - type: ndcg_at_3 value: 76.189 - type: ndcg_at_5 value: 77.915 - type: precision_at_1 value: 65.60000000000001 - type: precision_at_10 value: 9.19 - type: precision_at_100 value: 0.976 - type: precision_at_1000 value: 0.099 - type: precision_at_3 value: 27.800000000000004 - type: precision_at_5 value: 17.52 - type: recall_at_1 value: 65.60000000000001 - type: recall_at_10 value: 91.9 - type: recall_at_100 value: 97.6 - type: recall_at_1000 value: 99.0 - type: recall_at_3 value: 83.39999999999999 - type: recall_at_5 value: 87.6 - type: main_score value: 79.338 task: type: Retrieval - dataset: config: default name: MTEB Waimai revision: None split: test type: C-MTEB/waimai-classification metrics: - type: accuracy value: 89.9 - type: accuracy_stderr value: 0.7861297602813425 - type: ap value: 76.33068327298966 - type: ap_stderr value: 1.6404446239337744 - type: f1 value: 88.66175970131309 - type: f1_stderr value: 0.7269675835542363 - type: main_score value: 89.9 task: type: Classification tags: - mteb --- # quark-llm-embedding-1.5B - Chinese Text Embedding Model developed by Alibaba Quark-LLM Team. Details will be published later.