Update README.md

README.md

@@ -50,6 +50,62 @@ model-index:
       value: 45.494
     - type: f1
       value: 44.917953161904805
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 46.50495921726095
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 40.080055890804836
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 60.22880715757138
+    - type: mrr
+      value: 73.11227630479708
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.9542549153515
+    - type: cos_sim_spearman
+      value: 83.93865958725257
+    - type: euclidean_pearson
+      value: 86.00372707912037
+    - type: euclidean_spearman
+      value: 84.97302050526537
+    - type: manhattan_pearson
+      value: 85.63207676453459
+    - type: manhattan_spearman
+      value: 84.82542678079645
   - task:
       type: Classification
     dataset:
@@ -63,6 +119,28 @@ model-index:
       value: 84.29545454545455
     - type: f1
       value: 84.26780483160312
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 36.78678386185847
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 34.42462869304013
   - task:
       type: Classification
     dataset:
@@ -143,6 +221,342 @@ model-index:
       value: 77.5353059852051
     - type: f1
       value: 77.42427561340143
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 32.00163251745748
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 30.37879992380756
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 50.99679402527969
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 59.28024721612242
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.54645068673153
+    - type: cos_sim_spearman
+      value: 78.64401947043316
+    - type: euclidean_pearson
+      value: 82.36873285307261
+    - type: euclidean_spearman
+      value: 78.57406974337181
+    - type: manhattan_pearson
+      value: 82.33000263843067
+    - type: manhattan_spearman
+      value: 78.51127629983256
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.3001843293691
+    - type: cos_sim_spearman
+      value: 74.87989254109124
+    - type: euclidean_pearson
+      value: 80.88523322810525
+    - type: euclidean_spearman
+      value: 75.6469299496058
+    - type: manhattan_pearson
+      value: 80.8921104008781
+    - type: manhattan_spearman
+      value: 75.65942956132456
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.40319855455617
+    - type: cos_sim_spearman
+      value: 83.63807375781141
+    - type: euclidean_pearson
+      value: 83.28557187260904
+    - type: euclidean_spearman
+      value: 83.65223617817439
+    - type: manhattan_pearson
+      value: 83.30411918680012
+    - type: manhattan_spearman
+      value: 83.69204806663276
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.08942420708404
+    - type: cos_sim_spearman
+      value: 80.39991846857053
+    - type: euclidean_pearson
+      value: 82.68275416568997
+    - type: euclidean_spearman
+      value: 80.49626214786178
+    - type: manhattan_pearson
+      value: 82.62993414444689
+    - type: manhattan_spearman
+      value: 80.44148684748403
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.70365000096972
+    - type: cos_sim_spearman
+      value: 88.00515486253518
+    - type: euclidean_pearson
+      value: 87.65142168651604
+    - type: euclidean_spearman
+      value: 88.05834854642737
+    - type: manhattan_pearson
+      value: 87.59548659661925
+    - type: manhattan_spearman
+      value: 88.00573237576926
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.47886818876728
+    - type: cos_sim_spearman
+      value: 84.30874770680975
+    - type: euclidean_pearson
+      value: 83.74580951498133
+    - type: euclidean_spearman
+      value: 84.60595431454789
+    - type: manhattan_pearson
+      value: 83.74122023121615
+    - type: manhattan_spearman
+      value: 84.60549899361064
+  - 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: 87.60257252565631
+    - type: cos_sim_spearman
+      value: 88.29577246271319
+    - type: euclidean_pearson
+      value: 88.25434138634807
+    - type: euclidean_spearman
+      value: 88.06678743723845
+    - type: manhattan_pearson
+      value: 88.3651048848073
+    - type: manhattan_spearman
+      value: 88.23688291108866
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+      config: en
+      split: test
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+    metrics:
+    - type: cos_sim_pearson
+      value: 61.666254720687206
+    - type: cos_sim_spearman
+      value: 63.83700525419119
+    - type: euclidean_pearson
+      value: 64.36325040161177
+    - type: euclidean_spearman
+      value: 63.99833771224718
+    - type: manhattan_pearson
+      value: 64.01356576965371
+    - type: manhattan_spearman
+      value: 63.7201674202641
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.14584232139909
+    - type: cos_sim_spearman
+      value: 85.92570762612142
+    - type: euclidean_pearson
+      value: 86.34291503630607
+    - type: euclidean_spearman
+      value: 86.12670269109282
+    - type: manhattan_pearson
+      value: 86.26109450032494
+    - type: manhattan_spearman
+      value: 86.07665628498633
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 84.46430478723548
+    - type: mrr
+      value: 95.63907044299201
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.82178217821782
+    - type: cos_sim_ap
+      value: 95.49612561375889
+    - type: cos_sim_f1
+      value: 91.02691924227318
+    - type: cos_sim_precision
+      value: 90.75546719681908
+    - type: cos_sim_recall
+      value: 91.3
+    - type: dot_accuracy
+      value: 99.67821782178218
+    - type: dot_ap
+      value: 90.55740832326241
+    - type: dot_f1
+      value: 83.30765279917823
+    - type: dot_precision
+      value: 85.6388595564942
+    - type: dot_recall
+      value: 81.10000000000001
+    - type: euclidean_accuracy
+      value: 99.82475247524752
+    - type: euclidean_ap
+      value: 95.4739426775874
+    - type: euclidean_f1
+      value: 91.07413010590017
+    - type: euclidean_precision
+      value: 91.8616480162767
+    - type: euclidean_recall
+      value: 90.3
+    - type: manhattan_accuracy
+      value: 99.82376237623762
+    - type: manhattan_ap
+      value: 95.48506891694475
+    - type: manhattan_f1
+      value: 91.02822580645163
+    - type: manhattan_precision
+      value: 91.76829268292683
+    - type: manhattan_recall
+      value: 90.3
+    - type: max_accuracy
+      value: 99.82475247524752
+    - type: max_ap
+      value: 95.49612561375889
+    - type: max_f1
+      value: 91.07413010590017
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 60.92486258951404
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 32.97511013092965
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 52.31647363355174
+    - type: mrr
+      value: 53.26469792462439
   - task:
       type: Classification
     dataset:
@@ -171,6 +585,127 @@ model-index:
       value: 59.49349179400113
     - type: f1
       value: 59.815392064510775
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 47.29662657485732
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 85.74834594981225
+    - type: cos_sim_ap
+      value: 72.92449226447182
+    - type: cos_sim_f1
+      value: 68.14611644433363
+    - type: cos_sim_precision
+      value: 64.59465847317419
+    - type: cos_sim_recall
+      value: 72.1108179419525
+    - type: dot_accuracy
+      value: 82.73827263515527
+    - type: dot_ap
+      value: 63.27505594570806
+    - type: dot_f1
+      value: 61.717543651265
+    - type: dot_precision
+      value: 56.12443292287751
+    - type: dot_recall
+      value: 68.54881266490766
+    - type: euclidean_accuracy
+      value: 85.90332002145796
+    - type: euclidean_ap
+      value: 73.08299660990401
+    - type: euclidean_f1
+      value: 67.9050313691721
+    - type: euclidean_precision
+      value: 63.6091265268495
+    - type: euclidean_recall
+      value: 72.82321899736148
+    - type: manhattan_accuracy
+      value: 85.87351731537224
+    - type: manhattan_ap
+      value: 73.02205874497865
+    - type: manhattan_f1
+      value: 67.87532596547871
+    - type: manhattan_precision
+      value: 64.109781843772
+    - type: manhattan_recall
+      value: 72.1108179419525
+    - type: max_accuracy
+      value: 85.90332002145796
+    - type: max_ap
+      value: 73.08299660990401
+    - type: max_f1
+      value: 68.14611644433363
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.84231769317343
+    - type: cos_sim_ap
+      value: 85.65683184516553
+    - type: cos_sim_f1
+      value: 77.60567077973222
+    - type: cos_sim_precision
+      value: 75.6563071297989
+    - type: cos_sim_recall
+      value: 79.65814598090545
+    - type: dot_accuracy
+      value: 86.85333954282609
+    - type: dot_ap
+      value: 80.79899186896125
+    - type: dot_f1
+      value: 74.15220098146928
+    - type: dot_precision
+      value: 70.70819946919961
+    - type: dot_recall
+      value: 77.94887588543271
+    - type: euclidean_accuracy
+      value: 88.77634183257655
+    - type: euclidean_ap
+      value: 85.67411484805298
+    - type: euclidean_f1
+      value: 77.61566374357423
+    - type: euclidean_precision
+      value: 76.23255123255123
+    - type: euclidean_recall
+      value: 79.04989220819218
+    - type: manhattan_accuracy
+      value: 88.79962743043428
+    - type: manhattan_ap
+      value: 85.6494795781639
+    - type: manhattan_f1
+      value: 77.54222877224805
+    - type: manhattan_precision
+      value: 76.14100185528757
+    - type: manhattan_recall
+      value: 78.99599630428088
+    - type: max_accuracy
+      value: 88.84231769317343
+    - type: max_ap
+      value: 85.67411484805298
+    - type: max_f1
+      value: 77.61566374357423
 ---
 This is the sparsified ONNX variant of the [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) embeddings model created with [DeepSparse Optimum](https://github.com/neuralmagic/optimum-deepsparse) for ONNX export/inference pipeline and Neural Magic's [Sparsify](https://github.com/neuralmagic/sparsify) for one-shot quantization (INT8) and unstructured pruning (50%).