diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -12,6925 +12,6 @@ tags: - Qwen2-VL - sentence-similarity - vidore -model-index: -- name: gme-Qwen2-VL-7B-Instruct - results: - - task: - type: STS - dataset: - type: C-MTEB/AFQMC - name: MTEB AFQMC - config: default - split: validation - revision: b44c3b011063adb25877c13823db83bb193913c4 - metrics: - - type: cos_sim_pearson - value: 55.46303883144227 - - type: cos_sim_spearman - value: 59.66708815497073 - - type: euclidean_pearson - value: 57.81360946949099 - - type: euclidean_spearman - value: 59.66710825926347 - - type: manhattan_pearson - value: 57.723697562189344 - - type: manhattan_spearman - value: 59.55004095814257 - - task: - type: STS - dataset: - type: C-MTEB/ATEC - name: MTEB ATEC - config: default - split: test - revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865 - metrics: - - type: cos_sim_pearson - value: 52.381881068686894 - - type: cos_sim_spearman - value: 55.468235529709766 - - type: euclidean_pearson - value: 56.974786979175086 - - type: euclidean_spearman - value: 55.468231026153745 - - type: manhattan_pearson - value: 56.944671325662576 - - type: manhattan_spearman - value: 55.39037386224014 - - task: - type: Classification - dataset: - type: mteb/amazon_counterfactual - name: MTEB AmazonCounterfactualClassification (en) - config: en - split: test - revision: e8379541af4e31359cca9fbcf4b00f2671dba205 - metrics: - - type: accuracy - value: 77.61194029850746 - - type: ap - value: 41.29789064067677 - - type: f1 - value: 71.69633278678522 - - task: - type: Classification - dataset: - type: mteb/amazon_polarity - name: MTEB AmazonPolarityClassification - config: default - split: test - revision: e2d317d38cd51312af73b3d32a06d1a08b442046 - metrics: - - type: accuracy - value: 97.3258 - - type: ap - value: 95.91845683387056 - - type: f1 - value: 97.32526074864263 - - task: - type: Classification - dataset: - type: mteb/amazon_reviews_multi - name: MTEB AmazonReviewsClassification (en) - config: en - split: test - revision: 1399c76144fd37290681b995c656ef9b2e06e26d - metrics: - - type: accuracy - value: 64.794 - - type: f1 - value: 63.7329780206882 - - task: - type: Retrieval - dataset: - type: mteb/arguana - name: MTEB ArguAna - config: default - split: test - revision: c22ab2a51041ffd869aaddef7af8d8215647e41a - metrics: - - type: map_at_1 - value: 40.541 - - type: map_at_10 - value: 56.315000000000005 - - type: map_at_100 - value: 56.824 - - type: map_at_1000 - value: 56.825 - - type: map_at_3 - value: 51.778 - - type: map_at_5 - value: 54.623 - - type: mrr_at_1 - value: 41.038000000000004 - - type: mrr_at_10 - value: 56.532000000000004 - - type: mrr_at_100 - value: 57.034 - - type: mrr_at_1000 - value: 57.034 - - type: mrr_at_3 - value: 52.015 - - type: mrr_at_5 - value: 54.835 - - type: ndcg_at_1 - value: 40.541 - - type: ndcg_at_10 - value: 64.596 - - type: ndcg_at_100 - value: 66.656 - - type: ndcg_at_1000 - value: 66.666 - - type: ndcg_at_3 - value: 55.415000000000006 - - type: ndcg_at_5 - value: 60.527 - - type: precision_at_1 - value: 40.541 - - type: precision_at_10 - value: 9.083 - - type: precision_at_100 - value: 0.996 - - type: precision_at_1000 - value: 0.1 - - type: precision_at_3 - value: 21.977 - - type: precision_at_5 - value: 15.661 - - type: recall_at_1 - value: 40.541 - - type: recall_at_10 - value: 90.825 - - type: recall_at_100 - value: 99.57300000000001 - - type: recall_at_1000 - value: 99.644 - - type: recall_at_3 - value: 65.932 - - type: recall_at_5 - value: 78.307 - - task: - type: Clustering - dataset: - type: mteb/arxiv-clustering-p2p - name: MTEB ArxivClusteringP2P - config: default - split: test - revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d - metrics: - - type: v_measure - value: 54.96111428218386 - - task: - type: Clustering - dataset: - type: mteb/arxiv-clustering-s2s - name: MTEB ArxivClusteringS2S - config: default - split: test - revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 - metrics: - - type: v_measure - value: 50.637711388838945 - - task: - type: Reranking - dataset: - type: mteb/askubuntudupquestions-reranking - name: MTEB AskUbuntuDupQuestions - config: default - split: test - revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 - metrics: - - type: map - value: 64.0741897266483 - - type: mrr - value: 76.11440882909028 - - task: - type: STS - dataset: - type: mteb/biosses-sts - name: MTEB BIOSSES - config: default - split: test - revision: d3fb88f8f02e40887cd149695127462bbcf29b4a - metrics: - - type: cos_sim_pearson - value: 86.2557839280406 - - type: cos_sim_spearman - value: 82.58200216886888 - - type: euclidean_pearson - value: 84.80588838508498 - - type: euclidean_spearman - value: 82.58200216886888 - - type: manhattan_pearson - value: 84.53082035185592 - - type: manhattan_spearman - value: 82.4964580510134 - - task: - type: STS - dataset: - type: C-MTEB/BQ - name: MTEB BQ - config: default - split: test - revision: e3dda5e115e487b39ec7e618c0c6a29137052a55 - metrics: - - type: cos_sim_pearson - value: 65.53432474956654 - - type: cos_sim_spearman - value: 66.8014310403835 - - type: euclidean_pearson - value: 65.59442518434007 - - type: euclidean_spearman - value: 66.80144143248799 - - type: manhattan_pearson - value: 65.55990611112435 - - type: manhattan_spearman - value: 66.77720657746703 - - task: - type: Classification - dataset: - type: mteb/banking77 - name: MTEB Banking77Classification - config: default - split: test - revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 - metrics: - - type: accuracy - value: 84.76298701298703 - - type: f1 - value: 84.24881789367576 - - task: - type: Clustering - dataset: - type: mteb/biorxiv-clustering-p2p - name: MTEB BiorxivClusteringP2P - config: default - split: test - revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 - metrics: - - type: v_measure - value: 46.86757924102047 - - task: - type: Clustering - dataset: - type: mteb/biorxiv-clustering-s2s - name: MTEB BiorxivClusteringS2S - config: default - split: test - revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 - metrics: - - type: v_measure - value: 43.86043680479362 - - task: - type: Clustering - dataset: - type: C-MTEB/CLSClusteringP2P - name: MTEB CLSClusteringP2P - config: default - split: test - revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476 - metrics: - - type: v_measure - value: 45.684222588040605 - - task: - type: Clustering - dataset: - type: C-MTEB/CLSClusteringS2S - name: MTEB CLSClusteringS2S - config: default - split: test - revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f - metrics: - - type: v_measure - value: 45.45639765303432 - - task: - type: Reranking - dataset: - type: C-MTEB/CMedQAv1-reranking - name: MTEB CMedQAv1 - config: default - split: test - revision: 8d7f1e942507dac42dc58017c1a001c3717da7df - metrics: - - type: map - value: 88.7058672660788 - - type: mrr - value: 90.5795634920635 - - task: - type: Reranking - dataset: - type: C-MTEB/CMedQAv2-reranking - name: MTEB CMedQAv2 - config: default - split: test - revision: 23d186750531a14a0357ca22cd92d712fd512ea0 - metrics: - - type: map - value: 90.50750030424048 - - type: mrr - value: 92.3970634920635 - - task: - type: Retrieval - dataset: - type: BeIR/cqadupstack - name: MTEB CQADupstackAndroidRetrieval - config: default - split: test - revision: f46a197baaae43b4f621051089b82a364682dfeb - metrics: - - type: map_at_1 - value: 28.848000000000003 - - type: map_at_10 - value: 40.453 - - type: map_at_100 - value: 42.065000000000005 - - type: map_at_1000 - value: 42.176 - - type: map_at_3 - value: 36.697 - - type: map_at_5 - value: 38.855000000000004 - - type: mrr_at_1 - value: 34.764 - - type: mrr_at_10 - value: 45.662000000000006 - - type: mrr_at_100 - value: 46.56 - - type: mrr_at_1000 - value: 46.597 - - type: mrr_at_3 - value: 42.632 - - type: mrr_at_5 - value: 44.249 - - type: ndcg_at_1 - value: 34.764 - - type: ndcg_at_10 - value: 47.033 - - type: ndcg_at_100 - value: 53.089 - - type: ndcg_at_1000 - value: 54.818 - - type: ndcg_at_3 - value: 41.142 - - type: ndcg_at_5 - value: 43.928 - - type: precision_at_1 - value: 34.764 - - type: precision_at_10 - value: 9.027000000000001 - - type: precision_at_100 - value: 1.465 - - type: precision_at_1000 - value: 0.192 - - type: precision_at_3 - value: 19.695 - - type: precision_at_5 - value: 14.535 - - type: recall_at_1 - value: 28.848000000000003 - - type: recall_at_10 - value: 60.849 - - type: recall_at_100 - value: 85.764 - - type: recall_at_1000 - value: 96.098 - - type: recall_at_3 - value: 44.579 - - type: recall_at_5 - value: 51.678999999999995 - - task: - type: Retrieval - dataset: - type: BeIR/cqadupstack - name: MTEB CQADupstackEnglishRetrieval - config: default - split: test - revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 - metrics: - - type: map_at_1 - value: 30.731 - - type: map_at_10 - value: 41.859 - - type: map_at_100 - value: 43.13 - - type: map_at_1000 - value: 43.257 - - type: map_at_3 - value: 38.384 - - type: map_at_5 - value: 40.284 - - type: mrr_at_1 - value: 38.471 - - type: mrr_at_10 - value: 47.531 - - type: mrr_at_100 - value: 48.199 - - type: mrr_at_1000 - value: 48.24 - - type: mrr_at_3 - value: 44.989000000000004 - - type: mrr_at_5 - value: 46.403 - - type: ndcg_at_1 - value: 38.471 - - type: ndcg_at_10 - value: 48.022999999999996 - - type: ndcg_at_100 - value: 52.32599999999999 - - type: ndcg_at_1000 - value: 54.26 - - type: ndcg_at_3 - value: 42.986999999999995 - - type: ndcg_at_5 - value: 45.23 - - type: precision_at_1 - value: 38.471 - - type: precision_at_10 - value: 9.248000000000001 - - type: precision_at_100 - value: 1.469 - - type: precision_at_1000 - value: 0.193 - - type: precision_at_3 - value: 20.892 - - type: precision_at_5 - value: 14.892 - - type: recall_at_1 - value: 30.731 - - type: recall_at_10 - value: 59.561 - - type: recall_at_100 - value: 77.637 - - type: recall_at_1000 - value: 89.64999999999999 - - type: recall_at_3 - value: 44.897999999999996 - - type: recall_at_5 - value: 51.181 - - task: - type: Retrieval - dataset: - type: BeIR/cqadupstack - name: MTEB CQADupstackGamingRetrieval - config: default - split: test - revision: 4885aa143210c98657558c04aaf3dc47cfb54340 - metrics: - - type: map_at_1 - value: 34.949000000000005 - - type: map_at_10 - value: 48.117 - - type: map_at_100 - value: 49.355 - - type: map_at_1000 - value: 49.409 - - type: map_at_3 - value: 44.732 - - type: map_at_5 - value: 46.555 - - type: mrr_at_1 - value: 40.188 - - type: mrr_at_10 - value: 51.452 - - type: mrr_at_100 - value: 52.219 - - type: mrr_at_1000 - value: 52.24100000000001 - - type: mrr_at_3 - value: 48.642 - - type: mrr_at_5 - value: 50.134 - - type: ndcg_at_1 - value: 40.188 - - type: ndcg_at_10 - value: 54.664 - - type: ndcg_at_100 - value: 59.38099999999999 - - type: ndcg_at_1000 - value: 60.363 - - type: ndcg_at_3 - value: 48.684 - - type: ndcg_at_5 - value: 51.406 - - type: precision_at_1 - value: 40.188 - - type: precision_at_10 - value: 9.116 - - type: precision_at_100 - value: 1.248 - - type: precision_at_1000 - value: 0.13699999999999998 - - type: precision_at_3 - value: 22.236 - - type: precision_at_5 - value: 15.310000000000002 - - type: recall_at_1 - value: 34.949000000000005 - - type: recall_at_10 - value: 70.767 - - type: recall_at_100 - value: 90.79 - - type: recall_at_1000 - value: 97.57900000000001 - - type: recall_at_3 - value: 54.723 - - type: recall_at_5 - value: 61.404 - - task: - type: Retrieval - dataset: - type: BeIR/cqadupstack - name: MTEB CQADupstackGisRetrieval - config: default - split: test - revision: 5003b3064772da1887988e05400cf3806fe491f2 - metrics: - - type: map_at_1 - value: 25.312 - - type: map_at_10 - value: 34.799 - - type: map_at_100 - value: 35.906 - - type: map_at_1000 - value: 35.983 - - type: map_at_3 - value: 31.582 - - type: map_at_5 - value: 33.507999999999996 - - type: mrr_at_1 - value: 27.232 - - type: mrr_at_10 - value: 36.82 - - type: mrr_at_100 - value: 37.733 - - type: mrr_at_1000 - value: 37.791000000000004 - - type: mrr_at_3 - value: 33.804 - - type: mrr_at_5 - value: 35.606 - - type: ndcg_at_1 - value: 27.232 - - type: ndcg_at_10 - value: 40.524 - - type: ndcg_at_100 - value: 45.654 - - type: ndcg_at_1000 - value: 47.557 - - type: ndcg_at_3 - value: 34.312 - - type: ndcg_at_5 - value: 37.553 - - type: precision_at_1 - value: 27.232 - - type: precision_at_10 - value: 6.52 - - type: precision_at_100 - value: 0.9530000000000001 - - type: precision_at_1000 - value: 0.11399999999999999 - - type: precision_at_3 - value: 14.915000000000001 - - type: precision_at_5 - value: 10.847 - - type: recall_at_1 - value: 25.312 - - type: recall_at_10 - value: 56.169000000000004 - - type: recall_at_100 - value: 79.16499999999999 - - type: recall_at_1000 - value: 93.49300000000001 - - type: recall_at_3 - value: 39.5 - - type: recall_at_5 - value: 47.288999999999994 - - task: - type: Retrieval - dataset: - type: BeIR/cqadupstack - name: MTEB CQADupstackMathematicaRetrieval - config: default - split: test - revision: 90fceea13679c63fe563ded68f3b6f06e50061de - metrics: - - type: map_at_1 - value: 17.153 - - type: map_at_10 - value: 27.671 - - type: map_at_100 - value: 29.186 - - type: map_at_1000 - value: 29.299999999999997 - - type: map_at_3 - value: 24.490000000000002 - - type: map_at_5 - value: 26.178 - - type: mrr_at_1 - value: 21.144 - - type: mrr_at_10 - value: 32.177 - - type: mrr_at_100 - value: 33.247 - - type: mrr_at_1000 - value: 33.306000000000004 - - type: mrr_at_3 - value: 29.187 - - type: mrr_at_5 - value: 30.817 - - type: ndcg_at_1 - value: 21.144 - - type: ndcg_at_10 - value: 33.981 - - type: ndcg_at_100 - value: 40.549 - - type: ndcg_at_1000 - value: 43.03 - - type: ndcg_at_3 - value: 28.132 - - type: ndcg_at_5 - value: 30.721999999999998 - - type: precision_at_1 - value: 21.144 - - type: precision_at_10 - value: 6.666999999999999 - - type: precision_at_100 - value: 1.147 - - type: precision_at_1000 - value: 0.149 - - type: precision_at_3 - value: 14.302999999999999 - - type: precision_at_5 - value: 10.423 - - type: recall_at_1 - value: 17.153 - - type: recall_at_10 - value: 48.591 - - type: recall_at_100 - value: 76.413 - - type: recall_at_1000 - value: 93.8 - - type: recall_at_3 - value: 32.329 - - type: recall_at_5 - value: 38.958999999999996 - - task: - type: Retrieval - dataset: - type: BeIR/cqadupstack - name: MTEB CQADupstackPhysicsRetrieval - config: default - split: test - revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 - metrics: - - type: map_at_1 - value: 27.909 - - type: map_at_10 - value: 40.168 - - type: map_at_100 - value: 41.524 - - type: map_at_1000 - value: 41.626000000000005 - - type: map_at_3 - value: 36.274 - - type: map_at_5 - value: 38.411 - - type: mrr_at_1 - value: 34.649 - - type: mrr_at_10 - value: 45.613 - - type: mrr_at_100 - value: 46.408 - - type: mrr_at_1000 - value: 46.444 - - type: mrr_at_3 - value: 42.620999999999995 - - type: mrr_at_5 - value: 44.277 - - type: ndcg_at_1 - value: 34.649 - - type: ndcg_at_10 - value: 47.071000000000005 - - type: ndcg_at_100 - value: 52.559999999999995 - - type: ndcg_at_1000 - value: 54.285000000000004 - - type: ndcg_at_3 - value: 40.63 - - type: ndcg_at_5 - value: 43.584 - - type: precision_at_1 - value: 34.649 - - type: precision_at_10 - value: 8.855 - - type: precision_at_100 - value: 1.361 - - type: precision_at_1000 - value: 0.167 - - type: precision_at_3 - value: 19.538 - - type: precision_at_5 - value: 14.187 - - type: recall_at_1 - value: 27.909 - - type: recall_at_10 - value: 62.275000000000006 - - type: recall_at_100 - value: 84.95 - - type: recall_at_1000 - value: 96.02000000000001 - - type: recall_at_3 - value: 44.767 - - type: recall_at_5 - value: 52.03 - - task: - type: Retrieval - dataset: - type: BeIR/cqadupstack - name: MTEB CQADupstackProgrammersRetrieval - config: default - split: test - revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 - metrics: - - type: map_at_1 - value: 25.846000000000004 - - type: map_at_10 - value: 36.870999999999995 - - type: map_at_100 - value: 38.294 - - type: map_at_1000 - value: 38.401 - - type: map_at_3 - value: 33.163 - - type: map_at_5 - value: 35.177 - - type: mrr_at_1 - value: 31.849 - - type: mrr_at_10 - value: 41.681000000000004 - - type: mrr_at_100 - value: 42.658 - - type: mrr_at_1000 - value: 42.71 - - type: mrr_at_3 - value: 39.003 - - type: mrr_at_5 - value: 40.436 - - type: ndcg_at_1 - value: 31.849 - - type: ndcg_at_10 - value: 43.291000000000004 - - type: ndcg_at_100 - value: 49.136 - - type: ndcg_at_1000 - value: 51.168 - - type: ndcg_at_3 - value: 37.297999999999995 - - type: ndcg_at_5 - value: 39.934 - - type: precision_at_1 - value: 31.849 - - type: precision_at_10 - value: 8.219 - - type: precision_at_100 - value: 1.318 - - type: precision_at_1000 - value: 0.167 - - type: precision_at_3 - value: 18.151 - - type: precision_at_5 - value: 13.242 - - type: recall_at_1 - value: 25.846000000000004 - - type: recall_at_10 - value: 57.642 - - type: recall_at_100 - value: 82.069 - - type: recall_at_1000 - value: 95.684 - - type: recall_at_3 - value: 40.778999999999996 - - type: recall_at_5 - value: 47.647 - - task: - type: Retrieval - dataset: - type: BeIR/cqadupstack - name: MTEB CQADupstackStatsRetrieval - config: default - split: test - revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a - metrics: - - type: map_at_1 - value: 25.102000000000004 - - type: map_at_10 - value: 33.31 - - type: map_at_100 - value: 34.443 - - type: map_at_1000 - value: 34.547 - - type: map_at_3 - value: 30.932 - - type: map_at_5 - value: 32.126 - - type: mrr_at_1 - value: 28.221 - - type: mrr_at_10 - value: 36.519 - - type: mrr_at_100 - value: 37.425000000000004 - - type: mrr_at_1000 - value: 37.498 - - type: mrr_at_3 - value: 34.254 - - type: mrr_at_5 - value: 35.388999999999996 - - type: ndcg_at_1 - value: 28.221 - - type: ndcg_at_10 - value: 38.340999999999994 - - type: ndcg_at_100 - value: 43.572 - - type: ndcg_at_1000 - value: 45.979 - - type: ndcg_at_3 - value: 33.793 - - type: ndcg_at_5 - value: 35.681000000000004 - - type: precision_at_1 - value: 28.221 - - type: precision_at_10 - value: 6.135 - - type: precision_at_100 - value: 0.946 - - type: precision_at_1000 - value: 0.123 - - type: precision_at_3 - value: 14.519000000000002 - - type: precision_at_5 - value: 9.969 - - type: recall_at_1 - value: 25.102000000000004 - - type: recall_at_10 - value: 50.639 - - type: recall_at_100 - value: 74.075 - - type: recall_at_1000 - value: 91.393 - - type: recall_at_3 - value: 37.952000000000005 - - type: recall_at_5 - value: 42.71 - - task: - type: Retrieval - dataset: - type: BeIR/cqadupstack - name: MTEB CQADupstackTexRetrieval - config: default - split: test - revision: 46989137a86843e03a6195de44b09deda022eec7 - metrics: - - type: map_at_1 - value: 18.618000000000002 - - type: map_at_10 - value: 26.714 - - type: map_at_100 - value: 27.929 - - type: map_at_1000 - value: 28.057 - - type: map_at_3 - value: 24.134 - - type: map_at_5 - value: 25.575 - - type: mrr_at_1 - value: 22.573999999999998 - - type: mrr_at_10 - value: 30.786 - - type: mrr_at_100 - value: 31.746000000000002 - - type: mrr_at_1000 - value: 31.822 - - type: mrr_at_3 - value: 28.412 - - type: mrr_at_5 - value: 29.818 - - type: ndcg_at_1 - value: 22.573999999999998 - - type: ndcg_at_10 - value: 31.852000000000004 - - type: ndcg_at_100 - value: 37.477 - - type: ndcg_at_1000 - value: 40.331 - - type: ndcg_at_3 - value: 27.314 - - type: ndcg_at_5 - value: 29.485 - - type: precision_at_1 - value: 22.573999999999998 - - type: precision_at_10 - value: 5.86 - - type: precision_at_100 - value: 1.012 - - type: precision_at_1000 - value: 0.146 - - type: precision_at_3 - value: 13.099 - - type: precision_at_5 - value: 9.56 - - type: recall_at_1 - value: 18.618000000000002 - - type: recall_at_10 - value: 43.134 - - type: recall_at_100 - value: 68.294 - - type: recall_at_1000 - value: 88.283 - - type: recall_at_3 - value: 30.397999999999996 - - type: recall_at_5 - value: 35.998000000000005 - - task: - type: Retrieval - dataset: - type: BeIR/cqadupstack - name: MTEB CQADupstackUnixRetrieval - config: default - split: test - revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 - 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- type: accuracy - value: 67.39500000000001 - - type: f1 - value: 62.01837785021389 - - task: - type: Retrieval - dataset: - type: mteb/fever - name: MTEB FEVER - config: default - split: test - revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 - metrics: - - type: map_at_1 - value: 86.27 - - type: map_at_10 - value: 92.163 - - type: map_at_100 - value: 92.351 - - type: map_at_1000 - value: 92.36 - - type: map_at_3 - value: 91.36 - - type: map_at_5 - value: 91.888 - - type: mrr_at_1 - value: 92.72399999999999 - - type: mrr_at_10 - value: 95.789 - - type: mrr_at_100 - value: 95.80300000000001 - - type: mrr_at_1000 - value: 95.804 - - type: mrr_at_3 - value: 95.64200000000001 - - type: mrr_at_5 - value: 95.75 - - type: ndcg_at_1 - value: 92.72399999999999 - - type: ndcg_at_10 - value: 94.269 - - type: ndcg_at_100 - value: 94.794 - - type: ndcg_at_1000 - value: 94.94 - - type: ndcg_at_3 - value: 93.427 - - type: ndcg_at_5 - value: 93.914 - - type: precision_at_1 - value: 92.72399999999999 - 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value: 82.1 - - type: recall_at_100 - value: 91.62700000000001 - - type: recall_at_1000 - value: 96.556 - - type: recall_at_3 - value: 72.275 - - type: recall_at_5 - value: 77.24499999999999 - - task: - type: Classification - dataset: - type: C-MTEB/IFlyTek-classification - name: MTEB IFlyTek - config: default - split: validation - revision: 421605374b29664c5fc098418fe20ada9bd55f8a - metrics: - - type: accuracy - value: 54.520969603693736 - - type: f1 - value: 42.359043311419626 - - task: - type: Classification - dataset: - type: mteb/imdb - name: MTEB ImdbClassification - config: default - split: test - revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 - metrics: - - type: accuracy - value: 96.72559999999999 - - type: ap - value: 95.01759461773742 - - type: f1 - value: 96.72429945397575 - - task: - type: Classification - dataset: - type: C-MTEB/JDReview-classification - name: MTEB JDReview - config: default - split: test - revision: b7c64bd89eb87f8ded463478346f76731f07bf8b - metrics: - 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split: dev - revision: 539bbde593d947e2a124ba72651aafc09eb33fc2 - metrics: - - type: map_at_1 - value: 71.242 - - type: map_at_10 - value: 80.01 - - type: map_at_100 - value: 80.269 - - type: map_at_1000 - value: 80.276 - - type: map_at_3 - value: 78.335 - - type: map_at_5 - value: 79.471 - - type: mrr_at_1 - value: 73.668 - - type: mrr_at_10 - value: 80.515 - - type: mrr_at_100 - value: 80.738 - - type: mrr_at_1000 - value: 80.744 - - type: mrr_at_3 - value: 79.097 - - type: mrr_at_5 - value: 80.045 - - type: ndcg_at_1 - value: 73.668 - - type: ndcg_at_10 - value: 83.357 - - type: ndcg_at_100 - value: 84.442 - - type: ndcg_at_1000 - value: 84.619 - - type: ndcg_at_3 - value: 80.286 - - type: ndcg_at_5 - value: 82.155 - - type: precision_at_1 - value: 73.668 - - type: precision_at_10 - value: 9.905 - - type: precision_at_100 - value: 1.043 - - type: precision_at_1000 - value: 0.106 - - type: precision_at_3 - value: 30.024 - - type: precision_at_5 - value: 19.017 - - type: recall_at_1 - 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- type: map_at_10 - value: 63.438 - - type: map_at_100 - value: 63.956 - - type: map_at_1000 - value: 63.991 - - type: map_at_3 - value: 61.983 - - type: map_at_5 - value: 62.778 - - type: mrr_at_1 - value: 56.99999999999999 - - type: mrr_at_10 - value: 63.483000000000004 - - type: mrr_at_100 - value: 63.993 - - type: mrr_at_1000 - value: 64.02799999999999 - - type: mrr_at_3 - value: 62.017 - - type: mrr_at_5 - value: 62.812 - - type: ndcg_at_1 - value: 56.89999999999999 - - type: ndcg_at_10 - value: 66.61 - - type: ndcg_at_100 - value: 69.387 - - type: ndcg_at_1000 - value: 70.327 - - type: ndcg_at_3 - value: 63.583999999999996 - - type: ndcg_at_5 - value: 65.0 - - type: precision_at_1 - value: 56.89999999999999 - - type: precision_at_10 - value: 7.66 - - type: precision_at_100 - value: 0.902 - - type: precision_at_1000 - value: 0.098 - - type: precision_at_3 - value: 22.733 - - type: precision_at_5 - value: 14.32 - - type: recall_at_1 - value: 56.89999999999999 - - type: recall_at_10 - value: 76.6 - - type: recall_at_100 - value: 90.2 - - type: recall_at_1000 - value: 97.6 - - type: recall_at_3 - value: 68.2 - - type: recall_at_5 - value: 71.6 - - task: - type: Clustering - dataset: - type: mteb/medrxiv-clustering-p2p - name: MTEB MedrxivClusteringP2P - config: default - split: test - revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 - metrics: - - type: v_measure - value: 40.32149153753394 - - task: - type: Clustering - dataset: - type: mteb/medrxiv-clustering-s2s - name: MTEB MedrxivClusteringS2S - config: default - split: test - revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 - metrics: - - type: v_measure - value: 39.40319973495386 - - task: - type: Reranking - dataset: - type: mteb/mind_small - name: MTEB MindSmallReranking - config: default - split: test - revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 - metrics: - - type: map - value: 33.9769104898534 - - type: mrr - value: 35.32831430710564 - - task: - type: Classification - dataset: - type: C-MTEB/MultilingualSentiment-classification - 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value: 48.184 - - type: precision_at_5 - value: 30.897999999999996 - - type: recall_at_1 - value: 43.72 - - type: recall_at_10 - value: 82.1 - - type: recall_at_100 - value: 91.62700000000001 - - type: recall_at_1000 - value: 96.556 - - type: recall_at_3 - value: 72.275 - - type: recall_at_5 - value: 77.24499999999999 - - task: - type: Classification - dataset: - type: C-MTEB/IFlyTek-classification - name: MTEB IFlyTek - config: default - split: validation - revision: 421605374b29664c5fc098418fe20ada9bd55f8a - metrics: - - type: accuracy - value: 54.520969603693736 - - type: f1 - value: 42.359043311419626 - - task: - type: Classification - dataset: - type: mteb/imdb - name: MTEB ImdbClassification - config: default - split: test - revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 - metrics: - - type: accuracy - value: 96.72559999999999 - - type: ap - value: 95.01759461773742 - - type: f1 - value: 96.72429945397575 - - task: - type: Classification - dataset: - type: C-MTEB/JDReview-classification - name: MTEB JDReview - config: default - split: test - revision: b7c64bd89eb87f8ded463478346f76731f07bf8b - metrics: - - type: accuracy - value: 90.1688555347092 - - type: ap - value: 63.36583667477521 - - type: f1 - value: 85.6845016521436 - - task: - type: STS - dataset: - type: C-MTEB/LCQMC - name: MTEB LCQMC - config: default - split: test - revision: 17f9b096f80380fce5ed12a9be8be7784b337daf - metrics: - - type: cos_sim_pearson - value: 68.8503997749679 - - type: cos_sim_spearman - value: 74.15059291199371 - - type: euclidean_pearson - value: 73.01105331948172 - - type: euclidean_spearman - value: 74.15059069348803 - - type: manhattan_pearson - value: 72.80856655624557 - - type: manhattan_spearman - value: 73.95174793448955 - - task: - type: Reranking - dataset: - type: C-MTEB/Mmarco-reranking - name: MTEB MMarcoReranking - config: default - split: dev - revision: 8e0c766dbe9e16e1d221116a3f36795fbade07f6 - metrics: - - type: map - value: 32.68592539803807 - - type: mrr - value: 31.58968253968254 - - task: - type: Retrieval - dataset: - type: C-MTEB/MMarcoRetrieval - name: MTEB MMarcoRetrieval - config: default - split: dev - revision: 539bbde593d947e2a124ba72651aafc09eb33fc2 - metrics: - - type: map_at_1 - value: 71.242 - - type: map_at_10 - value: 80.01 - - type: map_at_100 - value: 80.269 - - type: map_at_1000 - value: 80.276 - - type: map_at_3 - value: 78.335 - - type: map_at_5 - value: 79.471 - - type: mrr_at_1 - value: 73.668 - - type: mrr_at_10 - value: 80.515 - - type: mrr_at_100 - value: 80.738 - - type: mrr_at_1000 - value: 80.744 - - type: mrr_at_3 - value: 79.097 - - type: mrr_at_5 - value: 80.045 - - type: ndcg_at_1 - value: 73.668 - - type: ndcg_at_10 - value: 83.357 - - type: ndcg_at_100 - value: 84.442 - - type: ndcg_at_1000 - value: 84.619 - - type: ndcg_at_3 - value: 80.286 - - type: ndcg_at_5 - value: 82.155 - - type: precision_at_1 - value: 73.668 - - type: precision_at_10 - value: 9.905 - - type: precision_at_100 - value: 1.043 - - type: precision_at_1000 - value: 0.106 - - type: precision_at_3 - value: 30.024 - - type: precision_at_5 - value: 19.017 - - type: recall_at_1 - value: 71.242 - - type: recall_at_10 - value: 93.11 - - type: recall_at_100 - value: 97.85000000000001 - - type: recall_at_1000 - value: 99.21900000000001 - - type: recall_at_3 - value: 85.137 - - type: recall_at_5 - value: 89.548 - - task: - type: Retrieval - dataset: - type: mteb/msmarco - name: MTEB MSMARCO - config: default - split: dev - revision: c5a29a104738b98a9e76336939199e264163d4a0 - metrics: - - type: map_at_1 - value: 22.006999999999998 - - type: map_at_10 - value: 34.994 - - type: map_at_100 - value: 36.183 - - type: map_at_1000 - value: 36.227 - - type: map_at_3 - value: 30.75 - - type: map_at_5 - value: 33.155 - - type: mrr_at_1 - value: 22.679 - - type: mrr_at_10 - value: 35.619 - - type: mrr_at_100 - value: 36.732 - - type: mrr_at_1000 - value: 36.77 - - type: mrr_at_3 - value: 31.44 - - type: mrr_at_5 - value: 33.811 - - type: ndcg_at_1 - value: 22.679 - - type: ndcg_at_10 - value: 42.376000000000005 - - type: ndcg_at_100 - value: 48.001 - - type: ndcg_at_1000 - value: 49.059999999999995 - - type: ndcg_at_3 - value: 33.727000000000004 - - type: ndcg_at_5 - value: 38.013000000000005 - - type: precision_at_1 - value: 22.679 - - type: precision_at_10 - value: 6.815 - - type: precision_at_100 - value: 0.962 - - type: precision_at_1000 - value: 0.105 - - type: precision_at_3 - value: 14.441 - - type: precision_at_5 - value: 10.817 - - type: recall_at_1 - value: 22.006999999999998 - - type: recall_at_10 - value: 65.158 - - type: recall_at_100 - value: 90.997 - - type: recall_at_1000 - value: 98.996 - - type: recall_at_3 - value: 41.646 - - type: recall_at_5 - value: 51.941 - - task: - type: Classification - dataset: - type: mteb/mtop_domain - name: MTEB MTOPDomainClassification (en) - config: en - split: test - revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf - metrics: - - type: accuracy - value: 97.55129958960327 - - type: f1 - value: 97.43464802675416 - - task: - type: Classification - dataset: - type: mteb/mtop_intent - name: MTEB MTOPIntentClassification (en) - config: en - split: test - revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba - metrics: - - type: accuracy - value: 90.4719562243502 - - type: f1 - value: 70.76460034443902 - - task: - type: Classification - dataset: - type: mteb/amazon_massive_intent - name: MTEB MassiveIntentClassification (zh-CN) - config: zh-CN - split: test - revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 - metrics: - - type: accuracy - value: 79.88231338264963 - - type: f1 - value: 77.13536609019927 - - task: - type: Classification - dataset: - type: mteb/amazon_massive_scenario - name: MTEB MassiveScenarioClassification (zh-CN) - config: zh-CN - split: test - revision: 7d571f92784cd94a019292a1f45445077d0ef634 - metrics: - - type: accuracy - value: 84.50571620712844 - - type: f1 - value: 83.4128768262944 - - task: - type: Retrieval - dataset: - type: C-MTEB/MedicalRetrieval - name: MTEB MedicalRetrieval - config: default - split: dev - revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6 - metrics: - - type: map_at_1 - value: 56.89999999999999 - - type: map_at_10 - value: 63.438 - - type: map_at_100 - value: 63.956 - - type: map_at_1000 - value: 63.991 - - type: map_at_3 - value: 61.983 - - type: map_at_5 - value: 62.778 - - type: mrr_at_1 - value: 56.99999999999999 - - type: mrr_at_10 - value: 63.483000000000004 - - type: mrr_at_100 - value: 63.993 - - type: mrr_at_1000 - value: 64.02799999999999 - - type: mrr_at_3 - value: 62.017 - - type: mrr_at_5 - value: 62.812 - - type: ndcg_at_1 - value: 56.89999999999999 - - type: ndcg_at_10 - value: 66.61 - - type: ndcg_at_100 - value: 69.387 - - type: ndcg_at_1000 - value: 70.327 - - type: ndcg_at_3 - value: 63.583999999999996 - - type: ndcg_at_5 - value: 65.0 - - type: precision_at_1 - value: 56.89999999999999 - - type: precision_at_10 - value: 7.66 - - type: precision_at_100 - value: 0.902 - - type: precision_at_1000 - value: 0.098 - - type: precision_at_3 - value: 22.733 - - type: precision_at_5 - value: 14.32 - - type: recall_at_1 - value: 56.89999999999999 - - type: recall_at_10 - value: 76.6 - - type: recall_at_100 - value: 90.2 - - type: recall_at_1000 - value: 97.6 - - type: recall_at_3 - value: 68.2 - - type: recall_at_5 - value: 71.6 - - task: - type: Clustering - dataset: - type: mteb/medrxiv-clustering-p2p - name: MTEB MedrxivClusteringP2P - config: default - split: test - revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 - metrics: - - type: v_measure - value: 40.32149153753394 - - task: - type: Clustering - dataset: - type: mteb/medrxiv-clustering-s2s - name: MTEB MedrxivClusteringS2S - config: default - split: test - revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 - metrics: - - type: v_measure - value: 39.40319973495386 - - task: - type: Reranking - dataset: - type: mteb/mind_small - name: MTEB MindSmallReranking - config: default - split: test - revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 - metrics: - - type: map - value: 33.9769104898534 - - type: mrr - value: 35.32831430710564 - - task: - type: Classification - dataset: - type: C-MTEB/MultilingualSentiment-classification - name: MTEB MultilingualSentiment - config: default - split: validation - revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a - metrics: - - type: accuracy - value: 81.80666666666667 - - type: f1 - value: 81.83278699395508 - - task: - type: Retrieval - dataset: - type: mteb/nfcorpus - name: MTEB NFCorpus - config: default - split: test - revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 - metrics: - - type: map_at_1 - value: 6.3 - - type: map_at_10 - value: 14.151 - - type: map_at_100 - value: 18.455 - - type: map_at_1000 - value: 20.186999999999998 - - type: map_at_3 - value: 10.023 - - type: map_at_5 - value: 11.736 - - type: mrr_at_1 - value: 49.536 - - type: mrr_at_10 - value: 58.516 - - type: mrr_at_100 - value: 59.084 - - type: mrr_at_1000 - value: 59.114 - - type: mrr_at_3 - value: 56.45 - - type: mrr_at_5 - value: 57.642 - - type: ndcg_at_1 - value: 47.522999999999996 - - type: ndcg_at_10 - value: 38.4 - - type: ndcg_at_100 - value: 35.839999999999996 - - type: ndcg_at_1000 - value: 44.998 - - type: ndcg_at_3 - value: 43.221 - - type: ndcg_at_5 - value: 40.784 - - type: precision_at_1 - value: 49.536 - - type: precision_at_10 - value: 28.977999999999998 - - type: precision_at_100 - value: 9.378 - - type: precision_at_1000 - value: 2.2769999999999997 - - type: precision_at_3 - value: 40.454 - - type: precision_at_5 - value: 35.418 - - type: recall_at_1 - value: 6.3 - - type: recall_at_10 - value: 19.085 - - type: recall_at_100 - value: 38.18 - - type: recall_at_1000 - value: 71.219 - - type: recall_at_3 - value: 11.17 - - type: recall_at_5 - value: 13.975999999999999 - - task: - type: Retrieval - dataset: - type: mteb/nq - name: MTEB NQ - config: default - split: test - revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 - metrics: - - type: map_at_1 - value: 43.262 - - type: map_at_10 - value: 60.387 - - type: map_at_100 - value: 61.102000000000004 - - type: map_at_1000 - value: 61.111000000000004 - - type: map_at_3 - value: 56.391999999999996 - - type: map_at_5 - value: 58.916000000000004 - - type: mrr_at_1 - value: 48.725 - - type: mrr_at_10 - value: 62.812999999999995 - - type: mrr_at_100 - value: 63.297000000000004 - - type: mrr_at_1000 - value: 63.304 - - type: mrr_at_3 - value: 59.955999999999996 - - type: mrr_at_5 - value: 61.785999999999994 - - type: ndcg_at_1 - value: 48.696 - - type: ndcg_at_10 - value: 67.743 - - type: ndcg_at_100 - value: 70.404 - - type: ndcg_at_1000 - value: 70.60600000000001 - - type: ndcg_at_3 - value: 60.712999999999994 - - type: ndcg_at_5 - value: 64.693 - - type: precision_at_1 - value: 48.696 - - type: precision_at_10 - value: 10.513 - - type: precision_at_100 - value: 1.196 - - type: precision_at_1000 - value: 0.121 - - type: precision_at_3 - value: 27.221 - - type: precision_at_5 - value: 18.701999999999998 - - type: recall_at_1 - value: 43.262 - - type: recall_at_10 - value: 87.35300000000001 - - type: recall_at_100 - value: 98.31299999999999 - - type: recall_at_1000 - value: 99.797 - - type: recall_at_3 - value: 69.643 - - type: recall_at_5 - value: 78.645 - - task: - type: PairClassification - dataset: - type: C-MTEB/OCNLI - name: MTEB Ocnli - config: default - split: validation - revision: 66e76a618a34d6d565d5538088562851e6daa7ec - metrics: - - type: cos_sim_accuracy - value: 72.65836491608013 - - type: cos_sim_ap - value: 78.75807247519593 - - type: cos_sim_f1 - value: 74.84662576687117 - - type: cos_sim_precision - value: 63.97003745318352 - - type: cos_sim_recall - value: 90.17951425554382 - - type: dot_accuracy - value: 72.65836491608013 - - type: dot_ap - value: 78.75807247519593 - - type: dot_f1 - value: 74.84662576687117 - - type: dot_precision - value: 63.97003745318352 - - type: dot_recall - value: 90.17951425554382 - - type: euclidean_accuracy - value: 72.65836491608013 - - type: euclidean_ap - value: 78.75807247519593 - - type: euclidean_f1 - value: 74.84662576687117 - - type: euclidean_precision - value: 63.97003745318352 - - type: euclidean_recall - value: 90.17951425554382 - - type: manhattan_accuracy - value: 72.00866269626421 - - type: manhattan_ap - value: 78.34663376353235 - - type: manhattan_f1 - value: 74.13234613604813 - - type: manhattan_precision - value: 65.98023064250413 - - type: manhattan_recall - value: 84.58289334741288 - - type: max_accuracy - value: 72.65836491608013 - - type: max_ap - value: 78.75807247519593 - - type: max_f1 - value: 74.84662576687117 - - task: - type: Classification - dataset: - type: C-MTEB/OnlineShopping-classification - name: MTEB OnlineShopping - config: default - split: test - revision: e610f2ebd179a8fda30ae534c3878750a96db120 - metrics: - - type: accuracy - value: 94.46999999999998 - - type: ap - value: 93.56401511160975 - - type: f1 - value: 94.46692790889986 - - task: - type: STS - dataset: - type: C-MTEB/PAWSX - name: MTEB PAWSX - config: default - split: test - revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1 - metrics: - - type: cos_sim_pearson - value: 15.232590709271829 - - type: cos_sim_spearman - value: 17.204830998481093 - - type: euclidean_pearson - value: 19.543519063265673 - - type: euclidean_spearman - value: 17.204830998481093 - - type: manhattan_pearson - value: 19.5722663367917 - - type: manhattan_spearman - value: 17.25656568963978 - - task: - type: STS - dataset: - type: C-MTEB/QBQTC - name: MTEB QBQTC - config: default - split: test - revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7 - metrics: - - type: cos_sim_pearson - value: 34.81965984725406 - - type: cos_sim_spearman - value: 37.697257783907645 - - type: euclidean_pearson - value: 35.87624912573427 - - type: euclidean_spearman - value: 37.69725778300291 - - type: manhattan_pearson - value: 35.69021326773646 - - type: manhattan_spearman - value: 37.54369033366458 - - task: - type: Retrieval - dataset: - type: mteb/quora - name: MTEB QuoraRetrieval - config: default - split: test - revision: None - metrics: - - type: map_at_1 - value: 69.952 - - type: map_at_10 - value: 84.134 - - type: map_at_100 - value: 84.795 - - type: map_at_1000 - value: 84.809 - - type: map_at_3 - value: 81.085 - - type: map_at_5 - value: 82.976 - - type: mrr_at_1 - value: 80.56 - - type: mrr_at_10 - value: 87.105 - - type: mrr_at_100 - value: 87.20700000000001 - - type: mrr_at_1000 - value: 87.208 - - type: mrr_at_3 - value: 86.118 - - type: mrr_at_5 - value: 86.79299999999999 - - type: ndcg_at_1 - value: 80.57 - - type: ndcg_at_10 - value: 88.047 - - type: ndcg_at_100 - value: 89.266 - - type: ndcg_at_1000 - value: 89.34299999999999 - - type: ndcg_at_3 - value: 85.052 - - type: ndcg_at_5 - value: 86.68299999999999 - - type: precision_at_1 - value: 80.57 - - type: precision_at_10 - value: 13.439 - - type: precision_at_100 - value: 1.536 - - type: precision_at_1000 - value: 0.157 - - type: precision_at_3 - value: 37.283 - - type: precision_at_5 - value: 24.558 - - type: recall_at_1 - value: 69.952 - - type: recall_at_10 - value: 95.599 - - type: recall_at_100 - value: 99.67099999999999 - - type: recall_at_1000 - value: 99.983 - - type: recall_at_3 - value: 87.095 - - type: recall_at_5 - value: 91.668 - - task: - type: Clustering - dataset: - type: mteb/reddit-clustering - name: MTEB RedditClustering - config: default - split: test - revision: 24640382cdbf8abc73003fb0fa6d111a705499eb - metrics: - - type: v_measure - value: 70.12802769698337 - - task: - type: Clustering - dataset: - type: mteb/reddit-clustering-p2p - name: MTEB RedditClusteringP2P - config: default - split: test - revision: 282350215ef01743dc01b456c7f5241fa8937f16 - metrics: - - type: v_measure - value: 71.19047621740276 - - task: - type: Retrieval - dataset: - type: mteb/scidocs - name: MTEB SCIDOCS - config: default - split: test - revision: None - metrics: - - type: map_at_1 - value: 6.208 - - type: map_at_10 - value: 17.036 - - type: map_at_100 - value: 20.162 - - type: map_at_1000 - value: 20.552 - - type: map_at_3 - value: 11.591999999999999 - - type: map_at_5 - value: 14.349 - - type: mrr_at_1 - value: 30.599999999999998 - 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value: 9.17 - - type: precision_at_100 - value: 0.983 - - type: precision_at_1000 - value: 0.099 - - type: precision_at_3 - value: 27.667 - - type: precision_at_5 - value: 17.419999999999998 - - type: recall_at_1 - value: 66.10000000000001 - - type: recall_at_10 - value: 91.7 - - type: recall_at_100 - value: 98.3 - - type: recall_at_1000 - value: 99.4 - - type: recall_at_3 - value: 83.0 - - type: recall_at_5 - value: 87.1 - - task: - type: Classification - dataset: - type: C-MTEB/waimai-classification - name: MTEB Waimai - config: default - split: test - revision: 339287def212450dcaa9df8c22bf93e9980c7023 - metrics: - - type: accuracy - value: 91.13 - - type: ap - value: 79.55231335947015 - - type: f1 - value: 89.63091922203914 ---