diff --git "a/README.md" "b/README.md"
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+++ "b/README.md"
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+---
+license: apache-2.0
+base_model:
+- Qwen/Qwen2-VL-7B-Instruct
+language:
+- en
+- zh
+tags:
+- mteb
+- sentence-transformers
+- transformers
+- 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
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+ name: MTEB CQADupstackStatsRetrieval
+ config: default
+ split: test
+ revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
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+ dataset:
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+ name: MTEB CQADupstackTexRetrieval
+ config: default
+ split: test
+ revision: 46989137a86843e03a6195de44b09deda022eec7
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+ dataset:
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+ name: MTEB CQADupstackUnixRetrieval
+ config: default
+ split: test
+ revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
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+ - task:
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+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackWebmastersRetrieval
+ config: default
+ split: test
+ revision: 160c094312a0e1facb97e55eeddb698c0abe3571
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+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackWordpressRetrieval
+ config: default
+ split: test
+ revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
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+ - task:
+ type: Retrieval
+ dataset:
+ type: mteb/climate-fever
+ name: MTEB ClimateFEVER
+ config: default
+ split: test
+ revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
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+ - task:
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+ dataset:
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+ name: MTEB CmedqaRetrieval
+ config: default
+ split: dev
+ revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
+ metrics:
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+ - type: recall_at_3
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+ - type: recall_at_5
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+ type: PairClassification
+ dataset:
+ type: C-MTEB/CMNLI
+ name: MTEB Cmnli
+ config: default
+ split: validation
+ revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
+ metrics:
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+ - type: dot_f1
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+ - type: dot_precision
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+ - type: euclidean_accuracy
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+ - type: euclidean_precision
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+ - type: euclidean_recall
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+ - type: manhattan_accuracy
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+ - type: max_accuracy
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+ - type: max_ap
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+ - type: max_f1
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+ - task:
+ type: Retrieval
+ dataset:
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+ name: MTEB CovidRetrieval
+ config: default
+ split: dev
+ revision: 1271c7809071a13532e05f25fb53511ffce77117
+ metrics:
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+ - type: precision_at_1
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+ - type: recall_at_1
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+ - type: recall_at_1000
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+ - type: recall_at_3
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+ - type: recall_at_5
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+ - task:
+ type: Retrieval
+ dataset:
+ type: mteb/dbpedia
+ name: MTEB DBPedia
+ config: default
+ split: test
+ revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
+ metrics:
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+ - type: recall_at_3
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+ - type: recall_at_5
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+ - task:
+ type: Retrieval
+ dataset:
+ type: C-MTEB/DuRetrieval
+ name: MTEB DuRetrieval
+ config: default
+ split: dev
+ revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
+ metrics:
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+ - type: recall_at_3
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+ - type: recall_at_5
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+ - task:
+ type: Retrieval
+ dataset:
+ type: C-MTEB/EcomRetrieval
+ name: MTEB EcomRetrieval
+ config: default
+ split: dev
+ revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
+ metrics:
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
+ value: 63.3
+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - type: recall_at_1000
+ value: 98.0
+ - type: recall_at_3
+ value: 72.5
+ - type: recall_at_5
+ value: 79.7
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/emotion
+ name: MTEB EmotionClassification
+ config: default
+ split: test
+ revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+ metrics:
+ - 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
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
+ value: 94.794
+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
+ value: 93.914
+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
+ value: 21.542
+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
+ value: 98.839
+ - type: recall_at_1000
+ value: 99.682
+ - type: recall_at_3
+ value: 94.741
+ - type: recall_at_5
+ value: 96.03
+ - task:
+ type: Retrieval
+ dataset:
+ type: mteb/fiqa
+ name: MTEB FiQA2018
+ config: default
+ split: test
+ revision: 27a168819829fe9bcd655c2df245fb19452e8e06
+ metrics:
+ - type: map_at_1
+ value: 29.561999999999998
+ - type: map_at_10
+ value: 48.52
+ - type: map_at_100
+ value: 50.753
+ - type: map_at_1000
+ value: 50.878
+ - type: map_at_3
+ value: 42.406
+ - type: map_at_5
+ value: 45.994
+ - type: mrr_at_1
+ value: 54.784
+ - type: mrr_at_10
+ value: 64.51400000000001
+ - type: mrr_at_100
+ value: 65.031
+ - type: mrr_at_1000
+ value: 65.05199999999999
+ - type: mrr_at_3
+ value: 62.474
+ - type: mrr_at_5
+ value: 63.562
+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
+ value: 63.666999999999994
+ - type: ndcg_at_1000
+ value: 65.379
+ - type: ndcg_at_3
+ value: 52.589
+ - type: ndcg_at_5
+ value: 54.32599999999999
+ - type: precision_at_1
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+ - type: precision_at_10
+ value: 15.693999999999999
+ - type: precision_at_100
+ value: 2.259
+ - type: precision_at_1000
+ value: 0.256
+ - type: precision_at_3
+ value: 34.774
+ - type: precision_at_5
+ value: 25.772000000000002
+ - type: recall_at_1
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+ - type: recall_at_10
+ value: 64.708
+ - type: recall_at_100
+ value: 87.958
+ - type: recall_at_1000
+ value: 97.882
+ - type: recall_at_3
+ value: 48.394
+ - type: recall_at_5
+ value: 56.101
+ - task:
+ type: Retrieval
+ dataset:
+ type: mteb/hotpotqa
+ name: MTEB HotpotQA
+ config: default
+ split: test
+ revision: ab518f4d6fcca38d87c25209f94beba119d02014
+ metrics:
+ - type: map_at_1
+ value: 43.72
+ - type: map_at_10
+ value: 71.905
+ - type: map_at_100
+ value: 72.685
+ - type: map_at_1000
+ value: 72.72800000000001
+ - type: map_at_3
+ value: 68.538
+ - type: map_at_5
+ value: 70.675
+ - type: mrr_at_1
+ value: 87.441
+ - type: mrr_at_10
+ value: 91.432
+ - type: mrr_at_100
+ value: 91.512
+ - type: mrr_at_1000
+ value: 91.513
+ - type: mrr_at_3
+ value: 90.923
+ - type: mrr_at_5
+ value: 91.252
+ - type: ndcg_at_1
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+ - type: ndcg_at_10
+ value: 79.212
+ - type: ndcg_at_100
+ value: 81.694
+ - type: ndcg_at_1000
+ value: 82.447
+ - type: ndcg_at_3
+ value: 74.746
+ - type: ndcg_at_5
+ value: 77.27199999999999
+ - type: precision_at_1
+ value: 87.441
+ - type: precision_at_10
+ value: 16.42
+ - type: precision_at_100
+ value: 1.833
+ - type: precision_at_1000
+ value: 0.193
+ - type: precision_at_3
+ 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
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+ - type: ndcg_at_10
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+ - 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
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+ - 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 (en)
+ config: en
+ split: test
+ revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+ metrics:
+ - type: accuracy
+ value: 83.49024882313383
+ - type: f1
+ value: 81.44067057564666
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/amazon_massive_scenario
+ name: MTEB MassiveScenarioClassification (en)
+ config: en
+ split: test
+ revision: 7d571f92784cd94a019292a1f45445077d0ef634
+ metrics:
+ - type: accuracy
+ value: 87.23268325487558
+ - type: f1
+ value: 86.36737921996752
+ - 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
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+ - 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
+ - type: mrr_at_10
+ value: 43.325
+ - type: mrr_at_100
+ value: 44.281
+ - type: mrr_at_1000
+ value: 44.31
+ - type: mrr_at_3
+ value: 39.300000000000004
+ - type: mrr_at_5
+ value: 41.730000000000004
+ - type: ndcg_at_1
+ value: 30.599999999999998
+ - type: ndcg_at_10
+ value: 27.378000000000004
+ - type: ndcg_at_100
+ value: 37.768
+ - type: ndcg_at_1000
+ value: 43.275000000000006
+ - type: ndcg_at_3
+ value: 25.167
+ - type: ndcg_at_5
+ value: 22.537
+ - type: precision_at_1
+ value: 30.599999999999998
+ - type: precision_at_10
+ value: 14.46
+ - type: precision_at_100
+ value: 2.937
+ - type: precision_at_1000
+ value: 0.424
+ - type: precision_at_3
+ value: 23.666999999999998
+ - type: precision_at_5
+ value: 20.14
+ - type: recall_at_1
+ value: 6.208
+ - type: recall_at_10
+ value: 29.29
+ - type: recall_at_100
+ value: 59.565
+ - type: recall_at_1000
+ value: 85.963
+ - type: recall_at_3
+ value: 14.407
+ - type: recall_at_5
+ value: 20.412
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sickr-sts
+ name: MTEB SICK-R
+ config: default
+ split: test
+ revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+ metrics:
+ - type: cos_sim_pearson
+ value: 82.65489797062479
+ - type: cos_sim_spearman
+ value: 75.34808277034776
+ - type: euclidean_pearson
+ value: 79.28097508609059
+ - type: euclidean_spearman
+ value: 75.3480824481771
+ - type: manhattan_pearson
+ value: 78.83529262858895
+ - type: manhattan_spearman
+ value: 74.96318170787025
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts12-sts
+ name: MTEB STS12
+ config: default
+ split: test
+ revision: a0d554a64d88156834ff5ae9920b964011b16384
+ metrics:
+ - type: cos_sim_pearson
+ value: 85.06920163624117
+ - type: cos_sim_spearman
+ value: 77.24549887905519
+ - type: euclidean_pearson
+ value: 85.58740280635266
+ - type: euclidean_spearman
+ value: 77.24652170306867
+ - type: manhattan_pearson
+ value: 85.77917470895854
+ - type: manhattan_spearman
+ value: 77.54426264008778
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts13-sts
+ name: MTEB STS13
+ config: default
+ split: test
+ revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+ metrics:
+ - type: cos_sim_pearson
+ value: 80.9762185094084
+ - type: cos_sim_spearman
+ value: 80.98090253728394
+ - type: euclidean_pearson
+ value: 80.88451512135202
+ - type: euclidean_spearman
+ value: 80.98090253728394
+ - type: manhattan_pearson
+ value: 80.7606664599805
+ - type: manhattan_spearman
+ value: 80.87197716950068
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts14-sts
+ name: MTEB STS14
+ config: default
+ split: test
+ revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+ metrics:
+ - type: cos_sim_pearson
+ value: 81.91239166620251
+ - type: cos_sim_spearman
+ value: 76.36798509005328
+ - type: euclidean_pearson
+ value: 80.6393872615655
+ - type: euclidean_spearman
+ value: 76.36798836339655
+ - type: manhattan_pearson
+ value: 80.50765898709096
+ - type: manhattan_spearman
+ value: 76.31958999372227
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts15-sts
+ name: MTEB STS15
+ config: default
+ split: test
+ revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+ metrics:
+ - type: cos_sim_pearson
+ value: 83.68800355225011
+ - type: cos_sim_spearman
+ value: 84.47549220803403
+ - type: euclidean_pearson
+ value: 83.86859896384159
+ - type: euclidean_spearman
+ value: 84.47551564954756
+ - type: manhattan_pearson
+ value: 83.74201103044383
+ - type: manhattan_spearman
+ value: 84.39903759718152
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts16-sts
+ name: MTEB STS16
+ config: default
+ split: test
+ revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+ metrics:
+ - type: cos_sim_pearson
+ value: 78.24197302553398
+ - type: cos_sim_spearman
+ value: 79.44526946553684
+ - type: euclidean_pearson
+ value: 79.12747636563053
+ - type: euclidean_spearman
+ value: 79.44526946553684
+ - type: manhattan_pearson
+ value: 78.94407504115144
+ - type: manhattan_spearman
+ value: 79.24858249553934
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts17-crosslingual-sts
+ name: MTEB STS17 (en-en)
+ config: en-en
+ split: test
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+ metrics:
+ - type: cos_sim_pearson
+ value: 89.15329071763895
+ - type: cos_sim_spearman
+ value: 88.67251952242073
+ - type: euclidean_pearson
+ value: 89.16908249259637
+ - type: euclidean_spearman
+ value: 88.67251952242073
+ - type: manhattan_pearson
+ value: 89.1279735094785
+ - type: manhattan_spearman
+ value: 88.81731953658254
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts22-crosslingual-sts
+ name: MTEB STS22 (en)
+ config: en
+ split: test
+ revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+ metrics:
+ - type: cos_sim_pearson
+ value: 69.44962535524695
+ - type: cos_sim_spearman
+ value: 71.75861316291065
+ - type: euclidean_pearson
+ value: 72.42347748883483
+ - type: euclidean_spearman
+ value: 71.75861316291065
+ - type: manhattan_pearson
+ value: 72.57545073534365
+ - type: manhattan_spearman
+ value: 71.90087671205625
+ - task:
+ type: STS
+ dataset:
+ type: C-MTEB/STSB
+ name: MTEB STSB
+ config: default
+ split: test
+ revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
+ metrics:
+ - type: cos_sim_pearson
+ value: 77.39283860361535
+ - type: cos_sim_spearman
+ value: 77.14577975930179
+ - type: euclidean_pearson
+ value: 76.64560889817044
+ - type: euclidean_spearman
+ value: 77.14577975930179
+ - type: manhattan_pearson
+ value: 76.82848456242104
+ - type: manhattan_spearman
+ value: 77.37708521460667
+ - task:
+ type: STS
+ dataset:
+ type: mteb/stsbenchmark-sts
+ name: MTEB STSBenchmark
+ config: default
+ split: test
+ revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+ metrics:
+ - type: cos_sim_pearson
+ value: 84.14036697885552
+ - type: cos_sim_spearman
+ value: 83.10901632378086
+ - type: euclidean_pearson
+ value: 83.59991244380554
+ - type: euclidean_spearman
+ value: 83.10901632378086
+ - type: manhattan_pearson
+ value: 83.56632266895113
+ - type: manhattan_spearman
+ value: 83.17610542379353
+ - task:
+ type: Reranking
+ dataset:
+ type: mteb/scidocs-reranking
+ name: MTEB SciDocsRR
+ config: default
+ split: test
+ revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+ metrics:
+ - type: map
+ value: 88.98026856845443
+ - type: mrr
+ value: 96.80987494712984
+ - task:
+ type: Retrieval
+ dataset:
+ type: mteb/scifact
+ name: MTEB SciFact
+ config: default
+ split: test
+ revision: 0228b52cf27578f30900b9e5271d331663a030d7
+ metrics:
+ - type: map_at_1
+ value: 41.661
+ - type: map_at_10
+ value: 55.492
+ - type: map_at_100
+ value: 56.237
+ - type: map_at_1000
+ value: 56.255
+ - type: map_at_3
+ value: 51.05
+ - type: map_at_5
+ value: 54.01200000000001
+ - type: mrr_at_1
+ value: 44.0
+ - type: mrr_at_10
+ value: 56.443
+ - type: mrr_at_100
+ value: 57.13700000000001
+ - type: mrr_at_1000
+ value: 57.152
+ - type: mrr_at_3
+ value: 52.944
+ - type: mrr_at_5
+ value: 55.37800000000001
+ - type: ndcg_at_1
+ value: 44.0
+ - type: ndcg_at_10
+ value: 62.312999999999995
+ - type: ndcg_at_100
+ value: 65.63900000000001
+ - type: ndcg_at_1000
+ value: 66.019
+ - type: ndcg_at_3
+ value: 54.67999999999999
+ - type: ndcg_at_5
+ value: 59.284000000000006
+ - type: precision_at_1
+ value: 44.0
+ - type: precision_at_10
+ value: 9.367
+ - type: precision_at_100
+ value: 1.0999999999999999
+ - type: precision_at_1000
+ value: 0.11299999999999999
+ - type: precision_at_3
+ value: 22.778000000000002
+ - type: precision_at_5
+ value: 16.467000000000002
+ - type: recall_at_1
+ value: 41.661
+ - type: recall_at_10
+ value: 82.306
+ - type: recall_at_100
+ value: 97.167
+ - type: recall_at_1000
+ value: 100.0
+ - type: recall_at_3
+ value: 62.461
+ - type: recall_at_5
+ value: 73.411
+ - task:
+ type: PairClassification
+ dataset:
+ type: mteb/sprintduplicatequestions-pairclassification
+ name: MTEB SprintDuplicateQuestions
+ config: default
+ split: test
+ revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+ metrics:
+ - type: cos_sim_accuracy
+ value: 99.90693069306931
+ - type: cos_sim_ap
+ value: 97.86562522779887
+ - type: cos_sim_f1
+ value: 95.27162977867204
+ - type: cos_sim_precision
+ value: 95.8502024291498
+ - type: cos_sim_recall
+ value: 94.69999999999999
+ - type: dot_accuracy
+ value: 99.90693069306931
+ - type: dot_ap
+ value: 97.86562522779887
+ - type: dot_f1
+ value: 95.27162977867204
+ - type: dot_precision
+ value: 95.8502024291498
+ - type: dot_recall
+ value: 94.69999999999999
+ - type: euclidean_accuracy
+ value: 99.90693069306931
+ - type: euclidean_ap
+ value: 97.86562522779887
+ - type: euclidean_f1
+ value: 95.27162977867204
+ - type: euclidean_precision
+ value: 95.8502024291498
+ - type: euclidean_recall
+ value: 94.69999999999999
+ - type: manhattan_accuracy
+ value: 99.90693069306931
+ - type: manhattan_ap
+ value: 97.85527044211135
+ - type: manhattan_f1
+ value: 95.27638190954774
+ - type: manhattan_precision
+ value: 95.75757575757575
+ - type: manhattan_recall
+ value: 94.8
+ - type: max_accuracy
+ value: 99.90693069306931
+ - type: max_ap
+ value: 97.86562522779887
+ - type: max_f1
+ value: 95.27638190954774
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/stackexchange-clustering
+ name: MTEB StackExchangeClustering
+ config: default
+ split: test
+ revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+ metrics:
+ - type: v_measure
+ value: 78.89230351770412
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/stackexchange-clustering-p2p
+ name: MTEB StackExchangeClusteringP2P
+ config: default
+ split: test
+ revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+ metrics:
+ - type: v_measure
+ value: 47.52328347080355
+ - task:
+ type: Reranking
+ dataset:
+ type: mteb/stackoverflowdupquestions-reranking
+ name: MTEB StackOverflowDupQuestions
+ config: default
+ split: test
+ revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+ metrics:
+ - type: map
+ value: 57.74702024461137
+ - type: mrr
+ value: 58.88074548001018
+ - task:
+ type: Summarization
+ dataset:
+ type: mteb/summeval
+ name: MTEB SummEval
+ config: default
+ split: test
+ revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+ metrics:
+ - type: cos_sim_pearson
+ value: 30.047929797503592
+ - type: cos_sim_spearman
+ value: 29.465371781983567
+ - type: dot_pearson
+ value: 30.047927690552335
+ - type: dot_spearman
+ value: 29.465371781983567
+ - task:
+ type: Classification
+ dataset:
+ type: C-MTEB/TNews-classification
+ name: MTEB TNews
+ config: default
+ split: validation
+ revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
+ metrics:
+ - type: accuracy
+ value: 56.691999999999986
+ - type: f1
+ value: 54.692084702788065
+ - task:
+ type: Retrieval
+ dataset:
+ type: mteb/trec-covid
+ name: MTEB TRECCOVID
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 0.181
+ - type: map_at_10
+ value: 1.2
+ - type: map_at_100
+ value: 6.078
+ - type: map_at_1000
+ value: 14.940000000000001
+ - type: map_at_3
+ value: 0.45599999999999996
+ - type: map_at_5
+ value: 0.692
+ - type: mrr_at_1
+ value: 66.0
+ - type: mrr_at_10
+ value: 75.819
+ - type: mrr_at_100
+ value: 76.168
+ - type: mrr_at_1000
+ value: 76.168
+ - type: mrr_at_3
+ value: 72.667
+ - type: mrr_at_5
+ value: 74.86699999999999
+ - type: ndcg_at_1
+ value: 59.0
+ - type: ndcg_at_10
+ value: 52.60399999999999
+ - type: ndcg_at_100
+ value: 38.049
+ - type: ndcg_at_1000
+ value: 38.576
+ - type: ndcg_at_3
+ value: 57.235
+ - type: ndcg_at_5
+ value: 56.147000000000006
+ - type: precision_at_1
+ value: 66.0
+ - type: precision_at_10
+ value: 55.2
+ - type: precision_at_100
+ value: 38.78
+ - type: precision_at_1000
+ value: 16.986
+ - type: precision_at_3
+ value: 62.666999999999994
+ - type: precision_at_5
+ value: 60.8
+ - type: recall_at_1
+ value: 0.181
+ - type: recall_at_10
+ value: 1.471
+ - type: recall_at_100
+ value: 9.748999999999999
+ - type: recall_at_1000
+ value: 37.667
+ - type: recall_at_3
+ value: 0.49300000000000005
+ - type: recall_at_5
+ value: 0.7979999999999999
+ - task:
+ type: Clustering
+ dataset:
+ type: C-MTEB/ThuNewsClusteringS2S
+ name: MTEB ThuNewsClusteringS2S
+ config: default
+ split: test
+ revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
+ metrics:
+ - type: v_measure
+ value: 77.04148998956299
+ - task:
+ type: Retrieval
+ dataset:
+ type: mteb/touche2020
+ name: MTEB Touche2020
+ config: default
+ split: test
+ revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
+ metrics:
+ - type: map_at_1
+ value: 1.936
+ - type: map_at_10
+ value: 8.942
+ - type: map_at_100
+ value: 14.475999999999999
+ - type: map_at_1000
+ value: 16.156000000000002
+ - type: map_at_3
+ value: 4.865
+ - type: map_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - type: recall_at_1000
+ value: 83.269
+ - type: recall_at_3
+ value: 6.442
+ - type: recall_at_5
+ value: 9.151
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/toxic_conversations_50k
+ name: MTEB ToxicConversationsClassification
+ config: default
+ split: test
+ revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+ metrics:
+ - type: accuracy
+ value: 86.564
+ - type: ap
+ value: 34.58766846081731
+ - type: f1
+ value: 72.32759831978161
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/tweet_sentiment_extraction
+ name: MTEB TweetSentimentExtractionClassification
+ config: default
+ split: test
+ revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+ metrics:
+ - type: accuracy
+ value: 77.80418788907753
+ - type: f1
+ value: 78.1047638421972
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/twentynewsgroups-clustering
+ name: MTEB TwentyNewsgroupsClustering
+ config: default
+ split: test
+ revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+ metrics:
+ - type: v_measure
+ value: 59.20888659980063
+ - task:
+ type: PairClassification
+ dataset:
+ type: mteb/twittersemeval2015-pairclassification
+ name: MTEB TwitterSemEval2015
+ config: default
+ split: test
+ revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+ metrics:
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+ - type: cos_sim_ap
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+ - type: cos_sim_f1
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+ - type: cos_sim_precision
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+ - type: cos_sim_recall
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+ - type: dot_accuracy
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+ - type: dot_ap
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+ - type: dot_f1
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+ - type: dot_precision
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+ - type: dot_recall
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+ - type: euclidean_accuracy
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+ - type: euclidean_ap
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+ - type: euclidean_f1
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+ - type: euclidean_precision
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+ - type: euclidean_recall
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+ - type: manhattan_accuracy
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+ - type: manhattan_ap
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+ - type: manhattan_f1
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+ - type: manhattan_precision
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+ - type: manhattan_recall
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+ - type: max_accuracy
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+ - type: max_ap
+ value: 72.25574305366213
+ - type: max_f1
+ value: 66.0611487783037
+ - task:
+ type: PairClassification
+ dataset:
+ type: mteb/twitterurlcorpus-pairclassification
+ name: MTEB TwitterURLCorpus
+ config: default
+ split: test
+ revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+ metrics:
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+ value: 88.34167733923235
+ - type: cos_sim_ap
+ value: 84.58587730660244
+ - type: cos_sim_f1
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+ - type: cos_sim_precision
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+ - type: cos_sim_recall
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+ - type: dot_accuracy
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+ - type: dot_ap
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+ - type: dot_f1
+ value: 77.14170010676287
+ - type: dot_precision
+ value: 73.91181657848324
+ - type: dot_recall
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+ - type: euclidean_accuracy
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+ - type: euclidean_ap
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+ - type: euclidean_f1
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+ - type: euclidean_precision
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+ - type: euclidean_recall
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+ - type: manhattan_accuracy
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+ - type: manhattan_ap
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+ - type: manhattan_f1
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+ - type: manhattan_precision
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+ - type: manhattan_recall
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+ - type: max_accuracy
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+ - type: max_ap
+ value: 84.5858781355044
+ - type: max_f1
+ value: 77.14170010676287
+ - task:
+ type: Retrieval
+ dataset:
+ type: C-MTEB/VideoRetrieval
+ name: MTEB VideoRetrieval
+ config: default
+ split: dev
+ revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
+ metrics:
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+ - type: map_at_10
+ value: 75.238
+ - type: map_at_100
+ value: 75.559
+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: map_at_5
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - 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:
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+ value: 91.13
+ - type: ap
+ value: 79.55231335947015
+ - type: f1
+ value: 89.63091922203914
+ - 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_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 (zh)
+ config: zh
+ split: test
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+ metrics:
+ - type: accuracy
+ value: 55.099999999999994
+ - type: f1
+ value: 53.115528412999666
+ - 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
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+ - type: mrr_at_10
+ value: 56.532000000000004
+ - type: mrr_at_100
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+ - 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
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+ - type: ndcg_at_10
+ value: 64.596
+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
+ value: 60.527
+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
+ value: 0.996
+ - type: precision_at_1000
+ value: 0.1
+ - type: precision_at_3
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+ - type: precision_at_5
+ value: 15.661
+ - type: recall_at_1
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+ - 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
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+ - type: map_at_100
+ value: 42.065000000000005
+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: map_at_5
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - 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:
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+ value: 30.731
+ - type: map_at_10
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+ - type: map_at_100
+ value: 43.13
+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: map_at_5
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - 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
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+ - type: map_at_10
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+ - type: map_at_100
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+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: map_at_5
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: recall_at_5
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+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackGisRetrieval
+ config: default
+ split: test
+ revision: 5003b3064772da1887988e05400cf3806fe491f2
+ metrics:
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+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackMathematicaRetrieval
+ config: default
+ split: test
+ revision: 90fceea13679c63fe563ded68f3b6f06e50061de
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+ - type: recall_at_1000
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+ - type: recall_at_5
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+ type: Retrieval
+ dataset:
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+ name: MTEB CQADupstackPhysicsRetrieval
+ config: default
+ split: test
+ revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
+ metrics:
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+ - type: recall_at_5
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+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackProgrammersRetrieval
+ config: default
+ split: test
+ revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
+ metrics:
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+ - type: recall_at_5
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+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackStatsRetrieval
+ config: default
+ split: test
+ revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
+ metrics:
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+ - type: recall_at_5
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+ - task:
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+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackTexRetrieval
+ config: default
+ split: test
+ revision: 46989137a86843e03a6195de44b09deda022eec7
+ metrics:
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+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackUnixRetrieval
+ config: default
+ split: test
+ revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
+ metrics:
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+ - type: recall_at_5
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+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackWebmastersRetrieval
+ config: default
+ split: test
+ revision: 160c094312a0e1facb97e55eeddb698c0abe3571
+ metrics:
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+ - type: recall_at_100
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+ - type: recall_at_1000
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+ - type: recall_at_3
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+ - type: recall_at_5
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+ - task:
+ type: Retrieval
+ dataset:
+ type: BeIR/cqadupstack
+ name: MTEB CQADupstackWordpressRetrieval
+ config: default
+ split: test
+ revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
+ metrics:
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+ - type: map_at_10
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+ - type: map_at_100
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+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: ndcg_at_1
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: recall_at_1000
+ value: 88.895
+ - type: recall_at_3
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+ - type: recall_at_5
+ value: 37.862
+ - task:
+ type: Retrieval
+ dataset:
+ type: mteb/climate-fever
+ name: MTEB ClimateFEVER
+ config: default
+ split: test
+ revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
+ metrics:
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+ - type: map_at_10
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+ - type: map_at_100
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+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: ndcg_at_1000
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+ - type: recall_at_1
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+ - type: recall_at_100
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+ - type: recall_at_1000
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+ - type: recall_at_3
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+ - type: recall_at_5
+ value: 42.309000000000005
+ - task:
+ type: Retrieval
+ dataset:
+ type: C-MTEB/CmedqaRetrieval
+ name: MTEB CmedqaRetrieval
+ config: default
+ split: dev
+ revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
+ metrics:
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+ - type: map_at_100
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+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: mrr_at_3
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - type: recall_at_1000
+ value: 98.914
+ - type: recall_at_3
+ value: 43.322
+ - type: recall_at_5
+ value: 50.409000000000006
+ - task:
+ type: PairClassification
+ dataset:
+ type: C-MTEB/CMNLI
+ name: MTEB Cmnli
+ config: default
+ split: validation
+ revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
+ metrics:
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+ value: 79.03788334335539
+ - type: cos_sim_ap
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+ - type: cos_sim_f1
+ value: 79.87784187309127
+ - type: cos_sim_precision
+ value: 77.36634531113059
+ - type: cos_sim_recall
+ value: 82.55786766425064
+ - type: dot_accuracy
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+ - type: max_ap
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+ - type: max_f1
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+ - task:
+ type: Retrieval
+ dataset:
+ type: C-MTEB/CovidRetrieval
+ name: MTEB CovidRetrieval
+ config: default
+ split: dev
+ revision: 1271c7809071a13532e05f25fb53511ffce77117
+ metrics:
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+ - type: map_at_10
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_1000
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+ - type: precision_at_5
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+ - type: recall_at_1000
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+ - type: recall_at_3
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+ - type: recall_at_5
+ value: 86.407
+ - task:
+ type: Retrieval
+ dataset:
+ type: mteb/dbpedia
+ name: MTEB DBPedia
+ config: default
+ split: test
+ revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
+ metrics:
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+ - type: map_at_100
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+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: map_at_5
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - type: recall_at_1000
+ value: 85.463
+ - type: recall_at_3
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+ - type: recall_at_5
+ value: 21.89
+ - task:
+ type: Retrieval
+ dataset:
+ type: C-MTEB/DuRetrieval
+ name: MTEB DuRetrieval
+ config: default
+ split: dev
+ revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
+ metrics:
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+ value: 25.608999999999998
+ - type: map_at_10
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+ - type: map_at_100
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+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: mrr_at_1
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: ndcg_at_1
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
+ value: 64.01
+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - type: recall_at_1000
+ value: 99.555
+ - type: recall_at_3
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+ - type: recall_at_5
+ value: 74.118
+ - task:
+ type: Retrieval
+ dataset:
+ type: C-MTEB/EcomRetrieval
+ name: MTEB EcomRetrieval
+ config: default
+ split: dev
+ revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
+ metrics:
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+ - type: map_at_10
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+ - type: map_at_100
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+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_3
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - type: recall_at_1000
+ value: 98.0
+ - type: recall_at_3
+ value: 72.5
+ - type: recall_at_5
+ value: 79.7
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/emotion
+ name: MTEB EmotionClassification
+ config: default
+ split: test
+ revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+ metrics:
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+ 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:
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+ 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
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - type: recall_at_1000
+ value: 99.682
+ - type: recall_at_3
+ value: 94.741
+ - type: recall_at_5
+ value: 96.03
+ - task:
+ type: Retrieval
+ dataset:
+ type: mteb/fiqa
+ name: MTEB FiQA2018
+ config: default
+ split: test
+ revision: 27a168819829fe9bcd655c2df245fb19452e8e06
+ metrics:
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+ value: 29.561999999999998
+ - type: map_at_10
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+ - type: map_at_100
+ value: 50.753
+ - type: map_at_1000
+ value: 50.878
+ - type: map_at_3
+ value: 42.406
+ - type: map_at_5
+ value: 45.994
+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: precision_at_1
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
+ value: 87.958
+ - type: recall_at_1000
+ value: 97.882
+ - type: recall_at_3
+ value: 48.394
+ - type: recall_at_5
+ value: 56.101
+ - task:
+ type: Retrieval
+ dataset:
+ type: mteb/hotpotqa
+ name: MTEB HotpotQA
+ config: default
+ split: test
+ revision: ab518f4d6fcca38d87c25209f94beba119d02014
+ metrics:
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+ value: 43.72
+ - type: map_at_10
+ value: 71.905
+ - type: map_at_100
+ value: 72.685
+ - type: map_at_1000
+ value: 72.72800000000001
+ - type: map_at_3
+ value: 68.538
+ - type: map_at_5
+ value: 70.675
+ - type: mrr_at_1
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+ - type: mrr_at_10
+ value: 91.432
+ - type: mrr_at_100
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+ - type: mrr_at_1000
+ value: 91.513
+ - type: mrr_at_3
+ value: 90.923
+ - type: mrr_at_5
+ value: 91.252
+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
+ value: 82.447
+ - type: ndcg_at_3
+ value: 74.746
+ - type: ndcg_at_5
+ value: 77.27199999999999
+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
+ value: 0.193
+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
+ value: 82.1
+ - type: recall_at_100
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+ - 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
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - 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
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+ - 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
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+ - 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
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+ - 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
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+ - 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
+ - type: mrr_at_10
+ value: 43.325
+ - type: mrr_at_100
+ value: 44.281
+ - type: mrr_at_1000
+ value: 44.31
+ - type: mrr_at_3
+ value: 39.300000000000004
+ - type: mrr_at_5
+ value: 41.730000000000004
+ - type: ndcg_at_1
+ value: 30.599999999999998
+ - type: ndcg_at_10
+ value: 27.378000000000004
+ - type: ndcg_at_100
+ value: 37.768
+ - type: ndcg_at_1000
+ value: 43.275000000000006
+ - type: ndcg_at_3
+ value: 25.167
+ - type: ndcg_at_5
+ value: 22.537
+ - type: precision_at_1
+ value: 30.599999999999998
+ - type: precision_at_10
+ value: 14.46
+ - type: precision_at_100
+ value: 2.937
+ - type: precision_at_1000
+ value: 0.424
+ - type: precision_at_3
+ value: 23.666999999999998
+ - type: precision_at_5
+ value: 20.14
+ - type: recall_at_1
+ value: 6.208
+ - type: recall_at_10
+ value: 29.29
+ - type: recall_at_100
+ value: 59.565
+ - type: recall_at_1000
+ value: 85.963
+ - type: recall_at_3
+ value: 14.407
+ - type: recall_at_5
+ value: 20.412
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sickr-sts
+ name: MTEB SICK-R
+ config: default
+ split: test
+ revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+ metrics:
+ - type: cos_sim_pearson
+ value: 82.65489797062479
+ - type: cos_sim_spearman
+ value: 75.34808277034776
+ - type: euclidean_pearson
+ value: 79.28097508609059
+ - type: euclidean_spearman
+ value: 75.3480824481771
+ - type: manhattan_pearson
+ value: 78.83529262858895
+ - type: manhattan_spearman
+ value: 74.96318170787025
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts12-sts
+ name: MTEB STS12
+ config: default
+ split: test
+ revision: a0d554a64d88156834ff5ae9920b964011b16384
+ metrics:
+ - type: cos_sim_pearson
+ value: 85.06920163624117
+ - type: cos_sim_spearman
+ value: 77.24549887905519
+ - type: euclidean_pearson
+ value: 85.58740280635266
+ - type: euclidean_spearman
+ value: 77.24652170306867
+ - type: manhattan_pearson
+ value: 85.77917470895854
+ - type: manhattan_spearman
+ value: 77.54426264008778
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts13-sts
+ name: MTEB STS13
+ config: default
+ split: test
+ revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+ metrics:
+ - type: cos_sim_pearson
+ value: 80.9762185094084
+ - type: cos_sim_spearman
+ value: 80.98090253728394
+ - type: euclidean_pearson
+ value: 80.88451512135202
+ - type: euclidean_spearman
+ value: 80.98090253728394
+ - type: manhattan_pearson
+ value: 80.7606664599805
+ - type: manhattan_spearman
+ value: 80.87197716950068
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts14-sts
+ name: MTEB STS14
+ config: default
+ split: test
+ revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+ metrics:
+ - type: cos_sim_pearson
+ value: 81.91239166620251
+ - type: cos_sim_spearman
+ value: 76.36798509005328
+ - type: euclidean_pearson
+ value: 80.6393872615655
+ - type: euclidean_spearman
+ value: 76.36798836339655
+ - type: manhattan_pearson
+ value: 80.50765898709096
+ - type: manhattan_spearman
+ value: 76.31958999372227
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts15-sts
+ name: MTEB STS15
+ config: default
+ split: test
+ revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+ metrics:
+ - type: cos_sim_pearson
+ value: 83.68800355225011
+ - type: cos_sim_spearman
+ value: 84.47549220803403
+ - type: euclidean_pearson
+ value: 83.86859896384159
+ - type: euclidean_spearman
+ value: 84.47551564954756
+ - type: manhattan_pearson
+ value: 83.74201103044383
+ - type: manhattan_spearman
+ value: 84.39903759718152
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts16-sts
+ name: MTEB STS16
+ config: default
+ split: test
+ revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+ metrics:
+ - type: cos_sim_pearson
+ value: 78.24197302553398
+ - type: cos_sim_spearman
+ value: 79.44526946553684
+ - type: euclidean_pearson
+ value: 79.12747636563053
+ - type: euclidean_spearman
+ value: 79.44526946553684
+ - type: manhattan_pearson
+ value: 78.94407504115144
+ - type: manhattan_spearman
+ value: 79.24858249553934
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts17-crosslingual-sts
+ name: MTEB STS17 (en-en)
+ config: en-en
+ split: test
+ revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+ metrics:
+ - type: cos_sim_pearson
+ value: 89.15329071763895
+ - type: cos_sim_spearman
+ value: 88.67251952242073
+ - type: euclidean_pearson
+ value: 89.16908249259637
+ - type: euclidean_spearman
+ value: 88.67251952242073
+ - type: manhattan_pearson
+ value: 89.1279735094785
+ - type: manhattan_spearman
+ value: 88.81731953658254
+ - task:
+ type: STS
+ dataset:
+ type: mteb/sts22-crosslingual-sts
+ name: MTEB STS22 (en)
+ config: en
+ split: test
+ revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+ metrics:
+ - type: cos_sim_pearson
+ value: 69.44962535524695
+ - type: cos_sim_spearman
+ value: 71.75861316291065
+ - type: euclidean_pearson
+ value: 72.42347748883483
+ - type: euclidean_spearman
+ value: 71.75861316291065
+ - type: manhattan_pearson
+ value: 72.57545073534365
+ - type: manhattan_spearman
+ value: 71.90087671205625
+ - task:
+ type: STS
+ dataset:
+ type: C-MTEB/STSB
+ name: MTEB STSB
+ config: default
+ split: test
+ revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
+ metrics:
+ - type: cos_sim_pearson
+ value: 77.39283860361535
+ - type: cos_sim_spearman
+ value: 77.14577975930179
+ - type: euclidean_pearson
+ value: 76.64560889817044
+ - type: euclidean_spearman
+ value: 77.14577975930179
+ - type: manhattan_pearson
+ value: 76.82848456242104
+ - type: manhattan_spearman
+ value: 77.37708521460667
+ - task:
+ type: STS
+ dataset:
+ type: mteb/stsbenchmark-sts
+ name: MTEB STSBenchmark
+ config: default
+ split: test
+ revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+ metrics:
+ - type: cos_sim_pearson
+ value: 84.14036697885552
+ - type: cos_sim_spearman
+ value: 83.10901632378086
+ - type: euclidean_pearson
+ value: 83.59991244380554
+ - type: euclidean_spearman
+ value: 83.10901632378086
+ - type: manhattan_pearson
+ value: 83.56632266895113
+ - type: manhattan_spearman
+ value: 83.17610542379353
+ - task:
+ type: Reranking
+ dataset:
+ type: mteb/scidocs-reranking
+ name: MTEB SciDocsRR
+ config: default
+ split: test
+ revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+ metrics:
+ - type: map
+ value: 88.98026856845443
+ - type: mrr
+ value: 96.80987494712984
+ - task:
+ type: Retrieval
+ dataset:
+ type: mteb/scifact
+ name: MTEB SciFact
+ config: default
+ split: test
+ revision: 0228b52cf27578f30900b9e5271d331663a030d7
+ metrics:
+ - type: map_at_1
+ value: 41.661
+ - type: map_at_10
+ value: 55.492
+ - type: map_at_100
+ value: 56.237
+ - type: map_at_1000
+ value: 56.255
+ - type: map_at_3
+ value: 51.05
+ - type: map_at_5
+ value: 54.01200000000001
+ - type: mrr_at_1
+ value: 44.0
+ - type: mrr_at_10
+ value: 56.443
+ - type: mrr_at_100
+ value: 57.13700000000001
+ - type: mrr_at_1000
+ value: 57.152
+ - type: mrr_at_3
+ value: 52.944
+ - type: mrr_at_5
+ value: 55.37800000000001
+ - type: ndcg_at_1
+ value: 44.0
+ - type: ndcg_at_10
+ value: 62.312999999999995
+ - type: ndcg_at_100
+ value: 65.63900000000001
+ - type: ndcg_at_1000
+ value: 66.019
+ - type: ndcg_at_3
+ value: 54.67999999999999
+ - type: ndcg_at_5
+ value: 59.284000000000006
+ - type: precision_at_1
+ value: 44.0
+ - type: precision_at_10
+ value: 9.367
+ - type: precision_at_100
+ value: 1.0999999999999999
+ - type: precision_at_1000
+ value: 0.11299999999999999
+ - type: precision_at_3
+ value: 22.778000000000002
+ - type: precision_at_5
+ value: 16.467000000000002
+ - type: recall_at_1
+ value: 41.661
+ - type: recall_at_10
+ value: 82.306
+ - type: recall_at_100
+ value: 97.167
+ - type: recall_at_1000
+ value: 100.0
+ - type: recall_at_3
+ value: 62.461
+ - type: recall_at_5
+ value: 73.411
+ - task:
+ type: PairClassification
+ dataset:
+ type: mteb/sprintduplicatequestions-pairclassification
+ name: MTEB SprintDuplicateQuestions
+ config: default
+ split: test
+ revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+ metrics:
+ - type: cos_sim_accuracy
+ value: 99.90693069306931
+ - type: cos_sim_ap
+ value: 97.86562522779887
+ - type: cos_sim_f1
+ value: 95.27162977867204
+ - type: cos_sim_precision
+ value: 95.8502024291498
+ - type: cos_sim_recall
+ value: 94.69999999999999
+ - type: dot_accuracy
+ value: 99.90693069306931
+ - type: dot_ap
+ value: 97.86562522779887
+ - type: dot_f1
+ value: 95.27162977867204
+ - type: dot_precision
+ value: 95.8502024291498
+ - type: dot_recall
+ value: 94.69999999999999
+ - type: euclidean_accuracy
+ value: 99.90693069306931
+ - type: euclidean_ap
+ value: 97.86562522779887
+ - type: euclidean_f1
+ value: 95.27162977867204
+ - type: euclidean_precision
+ value: 95.8502024291498
+ - type: euclidean_recall
+ value: 94.69999999999999
+ - type: manhattan_accuracy
+ value: 99.90693069306931
+ - type: manhattan_ap
+ value: 97.85527044211135
+ - type: manhattan_f1
+ value: 95.27638190954774
+ - type: manhattan_precision
+ value: 95.75757575757575
+ - type: manhattan_recall
+ value: 94.8
+ - type: max_accuracy
+ value: 99.90693069306931
+ - type: max_ap
+ value: 97.86562522779887
+ - type: max_f1
+ value: 95.27638190954774
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/stackexchange-clustering
+ name: MTEB StackExchangeClustering
+ config: default
+ split: test
+ revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+ metrics:
+ - type: v_measure
+ value: 78.89230351770412
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/stackexchange-clustering-p2p
+ name: MTEB StackExchangeClusteringP2P
+ config: default
+ split: test
+ revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+ metrics:
+ - type: v_measure
+ value: 47.52328347080355
+ - task:
+ type: Reranking
+ dataset:
+ type: mteb/stackoverflowdupquestions-reranking
+ name: MTEB StackOverflowDupQuestions
+ config: default
+ split: test
+ revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+ metrics:
+ - type: map
+ value: 57.74702024461137
+ - type: mrr
+ value: 58.88074548001018
+ - task:
+ type: Summarization
+ dataset:
+ type: mteb/summeval
+ name: MTEB SummEval
+ config: default
+ split: test
+ revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+ metrics:
+ - type: cos_sim_pearson
+ value: 30.047929797503592
+ - type: cos_sim_spearman
+ value: 29.465371781983567
+ - type: dot_pearson
+ value: 30.047927690552335
+ - type: dot_spearman
+ value: 29.465371781983567
+ - task:
+ type: Reranking
+ dataset:
+ type: C-MTEB/T2Reranking
+ name: MTEB T2Reranking
+ config: default
+ split: dev
+ revision: 76631901a18387f85eaa53e5450019b87ad58ef9
+ metrics:
+ - type: map
+ value: 66.54177017978034
+ - type: mrr
+ value: 76.76094292377299
+ - task:
+ type: Retrieval
+ dataset:
+ type: C-MTEB/T2Retrieval
+ name: MTEB T2Retrieval
+ config: default
+ split: dev
+ revision: 8731a845f1bf500a4f111cf1070785c793d10e64
+ metrics:
+ - type: map_at_1
+ value: 28.608
+ - type: map_at_10
+ value: 81.266
+ - type: map_at_100
+ value: 84.714
+ - type: map_at_1000
+ value: 84.758
+ - type: map_at_3
+ value: 56.967
+ - type: map_at_5
+ value: 70.14
+ - type: mrr_at_1
+ value: 91.881
+ - type: mrr_at_10
+ value: 94.11699999999999
+ - type: mrr_at_100
+ value: 94.178
+ - type: mrr_at_1000
+ value: 94.181
+ - type: mrr_at_3
+ value: 93.772
+ - type: mrr_at_5
+ value: 93.997
+ - type: ndcg_at_1
+ value: 91.881
+ - type: ndcg_at_10
+ value: 87.954
+ - type: ndcg_at_100
+ value: 90.904
+ - type: ndcg_at_1000
+ value: 91.326
+ - type: ndcg_at_3
+ value: 88.838
+ - type: ndcg_at_5
+ value: 87.764
+ - type: precision_at_1
+ value: 91.881
+ - type: precision_at_10
+ value: 43.628
+ - type: precision_at_100
+ value: 5.082
+ - type: precision_at_1000
+ value: 0.518
+ - type: precision_at_3
+ value: 77.62400000000001
+ - type: precision_at_5
+ value: 65.269
+ - type: recall_at_1
+ value: 28.608
+ - type: recall_at_10
+ value: 87.06
+ - type: recall_at_100
+ value: 96.815
+ - type: recall_at_1000
+ value: 98.969
+ - type: recall_at_3
+ value: 58.506
+ - type: recall_at_5
+ value: 73.21600000000001
+ - task:
+ type: Classification
+ dataset:
+ type: C-MTEB/TNews-classification
+ name: MTEB TNews
+ config: default
+ split: validation
+ revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
+ metrics:
+ - type: accuracy
+ value: 56.691999999999986
+ - type: f1
+ value: 54.692084702788065
+ - task:
+ type: Retrieval
+ dataset:
+ type: mteb/trec-covid
+ name: MTEB TRECCOVID
+ config: default
+ split: test
+ revision: None
+ metrics:
+ - type: map_at_1
+ value: 0.181
+ - type: map_at_10
+ value: 1.2
+ - type: map_at_100
+ value: 6.078
+ - type: map_at_1000
+ value: 14.940000000000001
+ - type: map_at_3
+ value: 0.45599999999999996
+ - type: map_at_5
+ value: 0.692
+ - type: mrr_at_1
+ value: 66.0
+ - type: mrr_at_10
+ value: 75.819
+ - type: mrr_at_100
+ value: 76.168
+ - type: mrr_at_1000
+ value: 76.168
+ - type: mrr_at_3
+ value: 72.667
+ - type: mrr_at_5
+ value: 74.86699999999999
+ - type: ndcg_at_1
+ value: 59.0
+ - type: ndcg_at_10
+ value: 52.60399999999999
+ - type: ndcg_at_100
+ value: 38.049
+ - type: ndcg_at_1000
+ value: 38.576
+ - type: ndcg_at_3
+ value: 57.235
+ - type: ndcg_at_5
+ value: 56.147000000000006
+ - type: precision_at_1
+ value: 66.0
+ - type: precision_at_10
+ value: 55.2
+ - type: precision_at_100
+ value: 38.78
+ - type: precision_at_1000
+ value: 16.986
+ - type: precision_at_3
+ value: 62.666999999999994
+ - type: precision_at_5
+ value: 60.8
+ - type: recall_at_1
+ value: 0.181
+ - type: recall_at_10
+ value: 1.471
+ - type: recall_at_100
+ value: 9.748999999999999
+ - type: recall_at_1000
+ value: 37.667
+ - type: recall_at_3
+ value: 0.49300000000000005
+ - type: recall_at_5
+ value: 0.7979999999999999
+ - task:
+ type: Clustering
+ dataset:
+ type: C-MTEB/ThuNewsClusteringP2P
+ name: MTEB ThuNewsClusteringP2P
+ config: default
+ split: test
+ revision: 5798586b105c0434e4f0fe5e767abe619442cf93
+ metrics:
+ - type: v_measure
+ value: 78.68783858143624
+ - task:
+ type: Clustering
+ dataset:
+ type: C-MTEB/ThuNewsClusteringS2S
+ name: MTEB ThuNewsClusteringS2S
+ config: default
+ split: test
+ revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
+ metrics:
+ - type: v_measure
+ value: 77.04148998956299
+ - task:
+ type: Retrieval
+ dataset:
+ type: mteb/touche2020
+ name: MTEB Touche2020
+ config: default
+ split: test
+ revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
+ metrics:
+ - type: map_at_1
+ value: 1.936
+ - type: map_at_10
+ value: 8.942
+ - type: map_at_100
+ value: 14.475999999999999
+ - type: map_at_1000
+ value: 16.156000000000002
+ - type: map_at_3
+ value: 4.865
+ - type: map_at_5
+ value: 6.367000000000001
+ - type: mrr_at_1
+ value: 26.531
+ - type: mrr_at_10
+ value: 42.846000000000004
+ - type: mrr_at_100
+ value: 43.441
+ - type: mrr_at_1000
+ value: 43.441
+ - type: mrr_at_3
+ value: 36.735
+ - type: mrr_at_5
+ value: 40.510000000000005
+ - type: ndcg_at_1
+ value: 24.490000000000002
+ - type: ndcg_at_10
+ value: 23.262
+ - type: ndcg_at_100
+ value: 34.959
+ - type: ndcg_at_1000
+ value: 47.258
+ - type: ndcg_at_3
+ value: 25.27
+ - type: ndcg_at_5
+ value: 24.246000000000002
+ - type: precision_at_1
+ value: 26.531
+ - type: precision_at_10
+ value: 20.408
+ - type: precision_at_100
+ value: 7.306
+ - type: precision_at_1000
+ value: 1.541
+ - type: precision_at_3
+ value: 26.531
+ - type: precision_at_5
+ value: 24.082
+ - type: recall_at_1
+ value: 1.936
+ - type: recall_at_10
+ value: 15.712000000000002
+ - type: recall_at_100
+ value: 45.451
+ - type: recall_at_1000
+ value: 83.269
+ - type: recall_at_3
+ value: 6.442
+ - type: recall_at_5
+ value: 9.151
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/toxic_conversations_50k
+ name: MTEB ToxicConversationsClassification
+ config: default
+ split: test
+ revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+ metrics:
+ - type: accuracy
+ value: 86.564
+ - type: ap
+ value: 34.58766846081731
+ - type: f1
+ value: 72.32759831978161
+ - task:
+ type: Classification
+ dataset:
+ type: mteb/tweet_sentiment_extraction
+ name: MTEB TweetSentimentExtractionClassification
+ config: default
+ split: test
+ revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+ metrics:
+ - type: accuracy
+ value: 77.80418788907753
+ - type: f1
+ value: 78.1047638421972
+ - task:
+ type: Clustering
+ dataset:
+ type: mteb/twentynewsgroups-clustering
+ name: MTEB TwentyNewsgroupsClustering
+ config: default
+ split: test
+ revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+ metrics:
+ - type: v_measure
+ value: 59.20888659980063
+ - task:
+ type: PairClassification
+ dataset:
+ type: mteb/twittersemeval2015-pairclassification
+ name: MTEB TwitterSemEval2015
+ config: default
+ split: test
+ revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+ metrics:
+ - type: cos_sim_accuracy
+ value: 85.45627943017226
+ - type: cos_sim_ap
+ value: 72.25550061847534
+ - type: cos_sim_f1
+ value: 66.0611487783037
+ - type: cos_sim_precision
+ value: 64.11720884032779
+ - type: cos_sim_recall
+ value: 68.12664907651715
+ - type: dot_accuracy
+ value: 85.45627943017226
+ - type: dot_ap
+ value: 72.25574305366213
+ - type: dot_f1
+ value: 66.0611487783037
+ - type: dot_precision
+ value: 64.11720884032779
+ - type: dot_recall
+ value: 68.12664907651715
+ - type: euclidean_accuracy
+ value: 85.45627943017226
+ - type: euclidean_ap
+ value: 72.2557084446673
+ - type: euclidean_f1
+ value: 66.0611487783037
+ - type: euclidean_precision
+ value: 64.11720884032779
+ - type: euclidean_recall
+ value: 68.12664907651715
+ - type: manhattan_accuracy
+ value: 85.32514752339513
+ - type: manhattan_ap
+ value: 71.52919143472248
+ - type: manhattan_f1
+ value: 65.60288251190322
+ - type: manhattan_precision
+ value: 64.02913840743531
+ - type: manhattan_recall
+ value: 67.25593667546174
+ - type: max_accuracy
+ value: 85.45627943017226
+ - type: max_ap
+ value: 72.25574305366213
+ - type: max_f1
+ value: 66.0611487783037
+ - task:
+ type: PairClassification
+ dataset:
+ type: mteb/twitterurlcorpus-pairclassification
+ name: MTEB TwitterURLCorpus
+ config: default
+ split: test
+ revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+ metrics:
+ - type: cos_sim_accuracy
+ value: 88.34167733923235
+ - type: cos_sim_ap
+ value: 84.58587730660244
+ - type: cos_sim_f1
+ value: 77.14170010676287
+ - type: cos_sim_precision
+ value: 73.91181657848324
+ - type: cos_sim_recall
+ value: 80.66676932553126
+ - type: dot_accuracy
+ value: 88.34167733923235
+ - type: dot_ap
+ value: 84.58585083616217
+ - type: dot_f1
+ value: 77.14170010676287
+ - type: dot_precision
+ value: 73.91181657848324
+ - type: dot_recall
+ value: 80.66676932553126
+ - type: euclidean_accuracy
+ value: 88.34167733923235
+ - type: euclidean_ap
+ value: 84.5858781355044
+ - type: euclidean_f1
+ value: 77.14170010676287
+ - type: euclidean_precision
+ value: 73.91181657848324
+ - type: euclidean_recall
+ value: 80.66676932553126
+ - type: manhattan_accuracy
+ value: 88.28152287809989
+ - type: manhattan_ap
+ value: 84.53184837110165
+ - type: manhattan_f1
+ value: 77.13582823915313
+ - type: manhattan_precision
+ value: 74.76156069364161
+ - type: manhattan_recall
+ value: 79.66584539574993
+ - type: max_accuracy
+ value: 88.34167733923235
+ - type: max_ap
+ value: 84.5858781355044
+ - type: max_f1
+ value: 77.14170010676287
+ - task:
+ type: Retrieval
+ dataset:
+ type: C-MTEB/VideoRetrieval
+ name: MTEB VideoRetrieval
+ config: default
+ split: dev
+ revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
+ metrics:
+ - type: map_at_1
+ value: 66.10000000000001
+ - type: map_at_10
+ value: 75.238
+ - type: map_at_100
+ value: 75.559
+ - type: map_at_1000
+ value: 75.565
+ - type: map_at_3
+ value: 73.68299999999999
+ - type: map_at_5
+ value: 74.63300000000001
+ - type: mrr_at_1
+ value: 66.10000000000001
+ - type: mrr_at_10
+ value: 75.238
+ - type: mrr_at_100
+ value: 75.559
+ - type: mrr_at_1000
+ value: 75.565
+ - type: mrr_at_3
+ value: 73.68299999999999
+ - type: mrr_at_5
+ value: 74.63300000000001
+ - type: ndcg_at_1
+ value: 66.10000000000001
+ - type: ndcg_at_10
+ value: 79.25999999999999
+ - type: ndcg_at_100
+ value: 80.719
+ - type: ndcg_at_1000
+ value: 80.862
+ - type: ndcg_at_3
+ value: 76.08200000000001
+ - type: ndcg_at_5
+ value: 77.782
+ - type: precision_at_1
+ value: 66.10000000000001
+ - type: precision_at_10
+ 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
+---
+
+
+ 
+
+
+GME: General Multimodal Embeddings
+
+## gme-Qwen2-VL-7B-Instruct
+
+We are excited to present `GME-Qwen2VL` models, our first generation **multimodal embedding models** for text and images,
+which are based on advanced [Qwen2-VL](https://huggingface.co/collections/Qwen/qwen2-vl-66cee7455501d7126940800d) multimodal large language models (MLLMs).
+
+The `GME-Qwen2VL` models support three input forms: **text**, **image**, and **image-text pair**, all of which can produce universal vector representations and have powerful retrieval performance.
+
+- **High Performance**: Achieves state-of-the-art (SOTA) results in our universal multimodal retrieval benchmark (**UMRB**) and strong **MTEB** evaluation scores.
+- **Dynamic Image Resolution**: Benefiting from `Qwen2-VL` and our training data, GME models support dynamic resolution image input.
+Our models are able to perform leadingly in the **visual document retrieval** task which requires fine-grained understanding of document screenshots.
+You can control to balance performance and efficiency.
+
+**Developed by**: Tongyi Lab, Alibaba Group
+
+**Paper**: GME: Improving Universal Multimodal Retrieval by Multimodal LLMs
+
+
+## Model List
+| Models | Model Size | Max Seq. Length | Dimension | MTEB-en| UMRB |
+|:-----: | :-----: |:-----: |:-----: |:-----: | :-----: |
+|[`gme-Qwen2VL-2B`](https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-2B-Instruct) | 2.21B | 32768 | 1536 | - | 64.45 |
+|[`gme-Qwen2VL-7B`](https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-7B-Instruct) | 8.29B | 32768 | 3584 | - | 67.02 |
+
+## Usage
+
+**Use with custom code**
+
+```python
+# You can find the script gme_inference.py in https://huggingface.co/Alibaba-NLP/gme-Qwen2VL-2B/blob/main/scripts/gme_inference.py
+from gme_inference import GmeQwen2VL
+
+model = GmeQwen2VL('Alibaba-NLP/gme-Qwen2-VL-7B-Instruct')
+
+texts = [
+ "What kind of car is this?",
+ "The Tesla Cybertruck is a battery electric pickup truck built by Tesla, Inc. since 2023."
+]
+images = [
+ 'https://en.wikipedia.org/wiki/File:Tesla_Cybertruck_damaged_window.jpg',
+ 'https://en.wikipedia.org/wiki/File:2024_Tesla_Cybertruck_Foundation_Series,_front_left_(Greenwich).jpg',
+]
+
+# Single-modal embedding
+e_text = gme.get_text_embeddings(texts=texts)
+e_image = gme.get_image_embeddings(images=images)
+print((e_text * e_image).sum(-1))
+## tensor([0.1702, 0.5278], dtype=torch.float16)
+
+# How to set embedding instruction
+e_query = gme.get_text_embeddings(texts=texts, instruction='Find an image that matches the given text.')
+# If is_query=False, we always use the default instruction.
+e_corpus = gme.get_image_embeddings(images=images, is_query=False)
+print((e_query * e_corpus).sum(-1))
+## tensor([0.2000, 0.5752], dtype=torch.float16)
+
+# Fused-modal embedding
+e_fused = gme.get_fused_embeddings(texts=texts, images=images)
+print((e_fused[0] * e_fused[1]).sum())
+## tensor(0.6826, dtype=torch.float16)
+
+```
+
+
+
+## Evaluation
+
+We validated the performance on our universal multimodal retrieval benchmark (**UMRB**) among others.
+
+| | | Single-modal | | Cross-modal | | | Fused-modal | | | | Avg. |
+|--------------------|------|:------------:|:---------:|:-----------:|:-----------:|:---------:|:-----------:|:----------:|:----------:|:-----------:|:----------:|
+| | | T→T (16) | I→I (1) | T→I (4) | T→VD (10) | I→T (4) | T→IT (2) | IT→T (5) | IT→I (2) | IT→IT (3) | (47) |
+| VISTA | 0.2B | 55.15 | **31.98** | 32.88 | 10.12 | 31.23 | 45.81 | 53.32 | 8.97 | 26.26 | 36.74 |
+| CLIP-SF | 0.4B | 39.75 | 31.42 | 59.05 | 24.09 | 62.95 | 66.41 | 53.32 | 34.9 | 55.65 | 43.24 |
+| One-Peace | 4B | 43.54 | 31.27 | 61.38 | 42.9 | 65.59 | 42.72 | 28.29 | 6.73 | 23.41 | 42.03 |
+| DSE | 4.2B | 48.94 | 27.92 | 40.75 | 78.21 | 52.54 | 49.62 | 35.44 | 8.36 | 40.18 | 50.63 |
+| E5-V | 8.4B | 52.41 | 27.36 | 46.56 | 41.22 | 47.95 | 54.13 | 32.9 | 23.17 | 7.23 | 42.48 |
+| **GME-Qwen2VL-2B** | 2.2B | 55.93 | 29.86 | 57.36 | 87.84 | **61.93** | 76.47 | 64.58 | 37.02 | 66.47 | 64.45 |
+| **GME-Qwen2VL-7B** | 8.3B | **58.19** | 31.89 | **61.35** | **89.92** | 60.83 | **80.94** | **66.18** | **42.56** | **73.62** | **67.02** |
+
+The [MTEB Leaderboard](https://huggingface.co/spaces/mteb/leaderboard) English tab shows the text embeddings performence of our model.
+
+**More detailed experimental results can be found in the [paper](https://arxiv.org/pdf/2412.xxxxx)**.
+
+
+## Limitations
+
+- **Single Image Input**: In `Qwen2-VL`, an image could be converted into a very large number of visual tokens. We limit the number of visual tokens to 1024 to obtain a good training efficiency.
+Due to the lack of relevant data, our models and evaluations retain one single image.
+- **English-only Training**: Our models are trained on english data only. Although the `Qwen2-VL` models are multilingual, the multilingual-multimodal embedding performance are not guaranteed.
+
+We will extend to multi-image input, image-text interleaved data as well as multilingual data in the future version.
+
+
+## Redistribution and Use
+
+We welcome and appreciate various applications of GME models and further improvements to the GME models themselves.
+Following Llama license,
+1. if you distribute or make available the GME models (or any derivative works thereof),
+or a product or service (including another AI model) that contains any of them,
+you shall prominently display “Built with GME” on a related website, user interface, blogpost, about page, or product documentation;
+2. if you use the GME models or any outputs or results of them to create, train, fine tune, or otherwise improve an AI model,
+which is distributed or made available, you shall also include “GME” at the beginning of any such AI model name.
+
+
+## Cloud API Services
+
+In addition to the open-source [GME](https://huggingface.co/collections/Alibaba-NLP/gme-models) series models, GME series models are also available as commercial API services on Alibaba Cloud.
+
+- [MultiModal Embedding Models](https://help.aliyun.com/zh/model-studio/developer-reference/general-text-embedding/): The `multimodal-embedding-v1` model service is available.
+
+Note that the models behind the commercial APIs are not entirely identical to the open-source models.
+
+
+## Citation
+If you find our paper or models helpful, please consider cite:
+
+```
+@misc{zhang2024gme,
+ title={GME: Improving Universal Multimodal Retrieval by Multimodal LLMs},
+ author={Zhang, Xin and Zhang, Yanzhao and Xie, Wen and Li, Mingxin and Dai, Ziqi and Long, Dingkun and Xie, Pengjun and Zhang, Meishan and Li, Wenjie and Zhang, Min},
+ year={2024},
+ eprint={2412.xxxxx},
+ archivePrefix={arXiv},
+ primaryClass={cs.CL},
+ url={https://arxiv.org/abs/2412.xxxxx},
+}
+```