metadata
tags:
- mteb
model-index:
- name: windberta
results:
- task:
type: STS
dataset:
type: C-MTEB/AFQMC
name: MTEB AFQMC
config: default
split: validation
revision: None
metrics:
- type: cos_sim_pearson
value: 42.33337754104733
- type: cos_sim_spearman
value: 46.77492896615997
- type: euclidean_pearson
value: 45.485443713440205
- type: euclidean_spearman
value: 46.77492896615997
- type: manhattan_pearson
value: 45.47908853063357
- type: manhattan_spearman
value: 46.78349339487035
- task:
type: STS
dataset:
type: C-MTEB/ATEC
name: MTEB ATEC
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 42.4857636418899
- type: cos_sim_spearman
value: 50.1796711684779
- type: euclidean_pearson
value: 50.19857844860528
- type: euclidean_spearman
value: 50.17966891674149
- type: manhattan_pearson
value: 50.189134647291425
- type: manhattan_spearman
value: 50.186194448855524
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (zh)
config: zh
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 43.32
- type: f1
value: 41.656310147227025
- task:
type: STS
dataset:
type: C-MTEB/BQ
name: MTEB BQ
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 53.71954834756843
- type: cos_sim_spearman
value: 55.24915785430301
- type: euclidean_pearson
value: 54.51293350057512
- type: euclidean_spearman
value: 55.249150926099745
- type: manhattan_pearson
value: 54.47449996486367
- type: manhattan_spearman
value: 55.2105677621172
- task:
type: Clustering
dataset:
type: C-MTEB/CLSClusteringP2P
name: MTEB CLSClusteringP2P
config: default
split: test
revision: None
metrics:
- type: v_measure
value: 42.45793696381908
- task:
type: Clustering
dataset:
type: C-MTEB/CLSClusteringS2S
name: MTEB CLSClusteringS2S
config: default
split: test
revision: None
metrics:
- type: v_measure
value: 40.378561138339656
- task:
type: Reranking
dataset:
type: C-MTEB/CMedQAv1-reranking
name: MTEB CMedQAv1
config: default
split: test
revision: None
metrics:
- type: map
value: 77.41779986882574
- type: mrr
value: 81.09345238095239
- task:
type: Reranking
dataset:
type: C-MTEB/CMedQAv2-reranking
name: MTEB CMedQAv2
config: default
split: test
revision: None
metrics:
- type: map
value: 77.84113571204598
- type: mrr
value: 81.18206349206349
- task:
type: Retrieval
dataset:
type: C-MTEB/CmedqaRetrieval
name: MTEB CmedqaRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 18.706
- type: map_at_10
value: 27.782
- type: map_at_100
value: 29.482000000000003
- type: map_at_1000
value: 29.64
- type: map_at_3
value: 24.606
- type: map_at_5
value: 26.32
- type: mrr_at_1
value: 29.307
- type: mrr_at_10
value: 36.226
- type: mrr_at_100
value: 37.262
- type: mrr_at_1000
value: 37.335
- type: mrr_at_3
value: 33.928999999999995
- type: mrr_at_5
value: 35.181000000000004
- type: ndcg_at_1
value: 29.307
- type: ndcg_at_10
value: 33.452
- type: ndcg_at_100
value: 40.747
- type: ndcg_at_1000
value: 43.881
- type: ndcg_at_3
value: 29.186
- type: ndcg_at_5
value: 30.866
- type: precision_at_1
value: 29.307
- type: precision_at_10
value: 7.632
- type: precision_at_100
value: 1.357
- type: precision_at_1000
value: 0.17600000000000002
- type: precision_at_3
value: 16.688
- type: precision_at_5
value: 12.173
- type: recall_at_1
value: 18.706
- type: recall_at_10
value: 41.925000000000004
- type: recall_at_100
value: 72.817
- type: recall_at_1000
value: 94.33500000000001
- type: recall_at_3
value: 28.968
- type: recall_at_5
value: 34.29
- task:
type: PairClassification
dataset:
type: C-MTEB/CMNLI
name: MTEB Cmnli
config: default
split: validation
revision: None
metrics:
- type: cos_sim_accuracy
value: 79.84365604329525
- type: cos_sim_ap
value: 87.54800685674849
- type: cos_sim_f1
value: 81.0654184776552
- type: cos_sim_precision
value: 77.4488926746167
- type: cos_sim_recall
value: 85.0362403553893
- type: dot_accuracy
value: 79.84365604329525
- type: dot_ap
value: 87.55923139984687
- type: dot_f1
value: 81.0654184776552
- type: dot_precision
value: 77.4488926746167
- type: dot_recall
value: 85.0362403553893
- type: euclidean_accuracy
value: 79.84365604329525
- type: euclidean_ap
value: 87.54800685674849
- type: euclidean_f1
value: 81.0654184776552
- type: euclidean_precision
value: 77.4488926746167
- type: euclidean_recall
value: 85.0362403553893
- type: manhattan_accuracy
value: 79.7714972940469
- type: manhattan_ap
value: 87.55523320840679
- type: manhattan_f1
value: 80.99598034836983
- type: manhattan_precision
value: 77.51656336824108
- type: manhattan_recall
value: 84.80243161094225
- type: max_accuracy
value: 79.84365604329525
- type: max_ap
value: 87.55923139984687
- type: max_f1
value: 81.0654184776552
- task:
type: Retrieval
dataset:
type: C-MTEB/CovidRetrieval
name: MTEB CovidRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 60.589999999999996
- type: map_at_10
value: 69.27600000000001
- type: map_at_100
value: 69.812
- type: map_at_1000
value: 69.82300000000001
- type: map_at_3
value: 67.448
- type: map_at_5
value: 68.537
- type: mrr_at_1
value: 60.695
- type: mrr_at_10
value: 69.32300000000001
- type: mrr_at_100
value: 69.854
- type: mrr_at_1000
value: 69.865
- type: mrr_at_3
value: 67.545
- type: mrr_at_5
value: 68.625
- type: ndcg_at_1
value: 60.695
- type: ndcg_at_10
value: 73.36
- type: ndcg_at_100
value: 75.78200000000001
- type: ndcg_at_1000
value: 76.077
- type: ndcg_at_3
value: 69.639
- type: ndcg_at_5
value: 71.59400000000001
- type: precision_at_1
value: 60.695
- type: precision_at_10
value: 8.704
- type: precision_at_100
value: 0.98
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 25.430000000000003
- type: precision_at_5
value: 16.27
- type: recall_at_1
value: 60.589999999999996
- type: recall_at_10
value: 86.038
- type: recall_at_100
value: 96.944
- type: recall_at_1000
value: 99.262
- type: recall_at_3
value: 75.869
- type: recall_at_5
value: 80.55799999999999
- task:
type: Retrieval
dataset:
type: C-MTEB/DuRetrieval
name: MTEB DuRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 23.294999999999998
- type: map_at_10
value: 70.99499999999999
- type: map_at_100
value: 74.126
- type: map_at_1000
value: 74.205
- type: map_at_3
value: 48.845
- type: map_at_5
value: 61.551
- type: mrr_at_1
value: 83.3
- type: mrr_at_10
value: 88.446
- type: mrr_at_100
value: 88.564
- type: mrr_at_1000
value: 88.57000000000001
- type: mrr_at_3
value: 88
- type: mrr_at_5
value: 88.25
- type: ndcg_at_1
value: 83.3
- type: ndcg_at_10
value: 80.128
- type: ndcg_at_100
value: 84.009
- type: ndcg_at_1000
value: 84.798
- type: ndcg_at_3
value: 78.79
- type: ndcg_at_5
value: 77.405
- type: precision_at_1
value: 83.3
- type: precision_at_10
value: 38.82
- type: precision_at_100
value: 4.657
- type: precision_at_1000
value: 0.484
- type: precision_at_3
value: 70.89999999999999
- type: precision_at_5
value: 59.550000000000004
- type: recall_at_1
value: 23.294999999999998
- type: recall_at_10
value: 82.12
- type: recall_at_100
value: 94.223
- type: recall_at_1000
value: 98.264
- type: recall_at_3
value: 51.946000000000005
- type: recall_at_5
value: 67.54299999999999
- task:
type: Retrieval
dataset:
type: C-MTEB/EcomRetrieval
name: MTEB EcomRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 42
- type: map_at_10
value: 51.207
- type: map_at_100
value: 51.964
- type: map_at_1000
value: 51.993
- type: map_at_3
value: 48.9
- type: map_at_5
value: 50.239999999999995
- type: mrr_at_1
value: 42
- type: mrr_at_10
value: 51.207
- type: mrr_at_100
value: 51.964
- type: mrr_at_1000
value: 51.993
- type: mrr_at_3
value: 48.9
- type: mrr_at_5
value: 50.239999999999995
- type: ndcg_at_1
value: 42
- type: ndcg_at_10
value: 55.886
- type: ndcg_at_100
value: 59.622
- type: ndcg_at_1000
value: 60.480999999999995
- type: ndcg_at_3
value: 51.112
- type: ndcg_at_5
value: 53.513
- type: precision_at_1
value: 42
- type: precision_at_10
value: 7.07
- type: precision_at_100
value: 0.8829999999999999
- type: precision_at_1000
value: 0.095
- type: precision_at_3
value: 19.167
- type: precision_at_5
value: 12.659999999999998
- type: recall_at_1
value: 42
- type: recall_at_10
value: 70.7
- type: recall_at_100
value: 88.3
- type: recall_at_1000
value: 95.19999999999999
- type: recall_at_3
value: 57.49999999999999
- type: recall_at_5
value: 63.3
- task:
type: Classification
dataset:
type: C-MTEB/IFlyTek-classification
name: MTEB IFlyTek
config: default
split: validation
revision: None
metrics:
- type: accuracy
value: 47.07964601769912
- type: f1
value: 35.71948030119852
- task:
type: Classification
dataset:
type: C-MTEB/JDReview-classification
name: MTEB JDReview
config: default
split: test
revision: None
metrics:
- type: accuracy
value: 84.48405253283303
- type: ap
value: 51.641044322555516
- type: f1
value: 79.09258868144057
- task:
type: STS
dataset:
type: C-MTEB/LCQMC
name: MTEB LCQMC
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 68.02458550340191
- type: cos_sim_spearman
value: 74.28734803466209
- type: euclidean_pearson
value: 73.34335009219284
- type: euclidean_spearman
value: 74.28734803466209
- type: manhattan_pearson
value: 73.34314353425192
- type: manhattan_spearman
value: 74.28417768884727
- task:
type: Reranking
dataset:
type: C-MTEB/Mmarco-reranking
name: MTEB MMarcoReranking
config: default
split: dev
revision: None
metrics:
- type: map
value: 30.17193800028175
- type: mrr
value: 29.161904761904765
- task:
type: Retrieval
dataset:
type: C-MTEB/MMarcoRetrieval
name: MTEB MMarcoRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 61.039
- type: map_at_10
value: 70.19999999999999
- type: map_at_100
value: 70.602
- type: map_at_1000
value: 70.62
- type: map_at_3
value: 68.133
- type: map_at_5
value: 69.503
- type: mrr_at_1
value: 63.066
- type: mrr_at_10
value: 70.831
- type: mrr_at_100
value: 71.186
- type: mrr_at_1000
value: 71.202
- type: mrr_at_3
value: 69.00699999999999
- type: mrr_at_5
value: 70.22699999999999
- type: ndcg_at_1
value: 63.066
- type: ndcg_at_10
value: 74.141
- type: ndcg_at_100
value: 75.976
- type: ndcg_at_1000
value: 76.462
- type: ndcg_at_3
value: 70.242
- type: ndcg_at_5
value: 72.58099999999999
- type: precision_at_1
value: 63.066
- type: precision_at_10
value: 9.097
- type: precision_at_100
value: 1.001
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 26.571
- type: precision_at_5
value: 17.166
- type: recall_at_1
value: 61.039
- type: recall_at_10
value: 85.666
- type: recall_at_100
value: 94.017
- type: recall_at_1000
value: 97.819
- type: recall_at_3
value: 75.45100000000001
- type: recall_at_5
value: 81.02000000000001
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (af)
config: af
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 28.813046402151986
- type: f1
value: 26.66771458648628
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (am)
config: am
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 3.0363147276395432
- type: f1
value: 2.1282632958878023
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (ar)
config: ar
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 6.745124411566914
- type: f1
value: 4.64897627862169
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (az)
config: az
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 27.004034969737727
- type: f1
value: 24.50373453583708
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (bn)
config: bn
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 3.24142568930733
- type: f1
value: 1.4440829714459096
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (cy)
config: cy
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 31.176866173503697
- type: f1
value: 27.449943893371536
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (da)
config: da
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 35.52790854068594
- type: f1
value: 32.284095877219734
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (de)
config: de
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 30.64895763281775
- type: f1
value: 27.273098137670022
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (el)
config: el
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 18.167451244115668
- type: f1
value: 14.717271932824833
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 54.76126429051782
- type: f1
value: 50.43678929170829
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (es)
config: es
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 32.53194351042367
- type: f1
value: 30.922864615091562
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (fa)
config: fa
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 8.715534633490249
- type: f1
value: 5.943557212598054
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (fi)
config: fi
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 31.785474108944182
- type: f1
value: 28.416607289904295
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (fr)
config: fr
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 33.16072629455279
- type: f1
value: 31.78249030156056
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (he)
config: he
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 3.026227303295226
- type: f1
value: 1.0249360076972784
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (hi)
config: hi
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 3.611297915265635
- type: f1
value: 1.8805751299306375
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (hu)
config: hu
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 30.470746469401476
- type: f1
value: 27.326274554457026
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (hy)
config: hy
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 5.346334902488231
- type: f1
value: 2.0115115171706197
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (id)
config: id
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 32.454606590450574
- type: f1
value: 31.8382002228813
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (is)
config: is
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 30.11768661735037
- type: f1
value: 27.934697686003663
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (it)
config: it
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 36.32145258910558
- type: f1
value: 34.47615722242413
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (ja)
config: ja
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 41.08944182918628
- type: f1
value: 39.27783199703022
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (jv)
config: jv
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 30.423671822461333
- type: f1
value: 28.09995717285775
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (ka)
config: ka
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
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dataset:
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name: MTEB MassiveScenarioClassification (sl)
config: sl
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 35.299260255548084
- type: f1
value: 31.765574086767216
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (sq)
config: sq
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 41.956960322797585
- type: f1
value: 38.574130779247525
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (sv)
config: sv
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 37.19233355749832
- type: f1
value: 33.81282301018017
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (sw)
config: sw
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 38.87693342299933
- type: f1
value: 36.374284150293924
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (ta)
config: ta
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 8.5137861466039
- type: f1
value: 3.77604514028691
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (te)
config: te
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 7.347007397444519
- type: f1
value: 4.316679614648472
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (th)
config: th
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 10.104236718224612
- type: f1
value: 7.587154404252399
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (tl)
config: tl
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 35.907868190988566
- type: f1
value: 32.42532534803655
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (tr)
config: tr
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 32.07800941492939
- type: f1
value: 31.072741162550983
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (ur)
config: ur
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 10.373234700739745
- type: f1
value: 7.124408430261137
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (vi)
config: vi
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 33.91055817081373
- type: f1
value: 31.82496122405504
- 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: 74.94283792871552
- type: f1
value: 74.29520816825985
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (zh-TW)
config: zh-TW
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 70.99529253530599
- type: f1
value: 70.48943927686703
- task:
type: Retrieval
dataset:
type: C-MTEB/MedicalRetrieval
name: MTEB MedicalRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 42.199999999999996
- type: map_at_10
value: 47.774
- type: map_at_100
value: 48.324
- type: map_at_1000
value: 48.392
- type: map_at_3
value: 46.317
- type: map_at_5
value: 47.072
- type: mrr_at_1
value: 42.3
- type: mrr_at_10
value: 47.827
- type: mrr_at_100
value: 48.378
- type: mrr_at_1000
value: 48.446
- type: mrr_at_3
value: 46.367000000000004
- type: mrr_at_5
value: 47.142
- type: ndcg_at_1
value: 42.199999999999996
- type: ndcg_at_10
value: 50.671
- type: ndcg_at_100
value: 53.724000000000004
- type: ndcg_at_1000
value: 55.694
- type: ndcg_at_3
value: 47.625
- type: ndcg_at_5
value: 48.964
- type: precision_at_1
value: 42.199999999999996
- type: precision_at_10
value: 5.99
- type: precision_at_100
value: 0.751
- type: precision_at_1000
value: 0.091
- type: precision_at_3
value: 17.133000000000003
- type: precision_at_5
value: 10.92
- type: recall_at_1
value: 42.199999999999996
- type: recall_at_10
value: 59.9
- type: recall_at_100
value: 75.1
- type: recall_at_1000
value: 91
- type: recall_at_3
value: 51.4
- type: recall_at_5
value: 54.6
- task:
type: Classification
dataset:
type: C-MTEB/MultilingualSentiment-classification
name: MTEB MultilingualSentiment
config: default
split: validation
revision: None
metrics:
- type: accuracy
value: 72.68333333333334
- type: f1
value: 72.53084383657173
- task:
type: PairClassification
dataset:
type: C-MTEB/OCNLI
name: MTEB Ocnli
config: default
split: validation
revision: None
metrics:
- type: cos_sim_accuracy
value: 72.92907417433676
- type: cos_sim_ap
value: 77.2067217322648
- type: cos_sim_f1
value: 76.53631284916202
- type: cos_sim_precision
value: 68.44296419650291
- type: cos_sim_recall
value: 86.80042238648363
- type: dot_accuracy
value: 72.92907417433676
- type: dot_ap
value: 77.2067217322648
- type: dot_f1
value: 76.53631284916202
- type: dot_precision
value: 68.44296419650291
- type: dot_recall
value: 86.80042238648363
- type: euclidean_accuracy
value: 72.92907417433676
- type: euclidean_ap
value: 77.2067217322648
- type: euclidean_f1
value: 76.53631284916202
- type: euclidean_precision
value: 68.44296419650291
- type: euclidean_recall
value: 86.80042238648363
- type: manhattan_accuracy
value: 72.98321602598809
- type: manhattan_ap
value: 77.10385348859928
- type: manhattan_f1
value: 76.67134174848059
- type: manhattan_precision
value: 68.79194630872483
- type: manhattan_recall
value: 86.58922914466737
- type: max_accuracy
value: 72.98321602598809
- type: max_ap
value: 77.2067217322648
- type: max_f1
value: 76.67134174848059
- task:
type: Classification
dataset:
type: C-MTEB/OnlineShopping-classification
name: MTEB OnlineShopping
config: default
split: test
revision: None
metrics:
- type: accuracy
value: 92.11000000000003
- type: ap
value: 90.49414877664759
- type: f1
value: 92.10539417755511
- task:
type: STS
dataset:
type: C-MTEB/PAWSX
name: MTEB PAWSX
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 29.106919865870793
- type: cos_sim_spearman
value: 33.23892524348652
- type: euclidean_pearson
value: 33.62483348491917
- type: euclidean_spearman
value: 33.23892524348652
- type: manhattan_pearson
value: 33.63464275000747
- type: manhattan_spearman
value: 33.250596030941196
- task:
type: STS
dataset:
type: C-MTEB/QBQTC
name: MTEB QBQTC
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 28.83792748309052
- type: cos_sim_spearman
value: 30.92395949947476
- type: euclidean_pearson
value: 29.296076928835973
- type: euclidean_spearman
value: 30.92395949947476
- type: manhattan_pearson
value: 29.220578930008596
- type: manhattan_spearman
value: 30.848850181684227
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (zh)
config: zh
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson
value: 62.485183619582465
- type: cos_sim_spearman
value: 64.41414883218417
- type: euclidean_pearson
value: 63.53854165422046
- type: euclidean_spearman
value: 64.41414883218417
- type: manhattan_pearson
value: 63.57621522539751
- type: manhattan_spearman
value: 64.49062238421523
- task:
type: STS
dataset:
type: C-MTEB/STSB
name: MTEB STSB
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson
value: 78.96466421469466
- type: cos_sim_spearman
value: 79.74344126074892
- type: euclidean_pearson
value: 79.57588420768205
- type: euclidean_spearman
value: 79.74344126074892
- type: manhattan_pearson
value: 79.50301779470537
- type: manhattan_spearman
value: 79.67817007436709
- task:
type: Reranking
dataset:
type: C-MTEB/T2Reranking
name: MTEB T2Reranking
config: default
split: dev
revision: None
metrics:
- type: map
value: 65.85321176285859
- type: mrr
value: 75.72496534158688
- task:
type: Retrieval
dataset:
type: C-MTEB/T2Retrieval
name: MTEB T2Retrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 24.437
- type: map_at_10
value: 67.85799999999999
- type: map_at_100
value: 71.65599999999999
- type: map_at_1000
value: 71.771
- type: map_at_3
value: 47.752
- type: map_at_5
value: 58.620000000000005
- type: mrr_at_1
value: 83.776
- type: mrr_at_10
value: 87.36699999999999
- type: mrr_at_100
value: 87.529
- type: mrr_at_1000
value: 87.535
- type: mrr_at_3
value: 86.669
- type: mrr_at_5
value: 87.126
- type: ndcg_at_1
value: 83.776
- type: ndcg_at_10
value: 76.839
- type: ndcg_at_100
value: 81.547
- type: ndcg_at_1000
value: 82.723
- type: ndcg_at_3
value: 78.731
- type: ndcg_at_5
value: 76.982
- type: precision_at_1
value: 83.776
- type: precision_at_10
value: 38.507999999999996
- type: precision_at_100
value: 4.809
- type: precision_at_1000
value: 0.509
- type: precision_at_3
value: 69.151
- type: precision_at_5
value: 57.74399999999999
- type: recall_at_1
value: 24.437
- type: recall_at_10
value: 75.887
- type: recall_at_100
value: 91.104
- type: recall_at_1000
value: 97.024
- type: recall_at_3
value: 49.835
- type: recall_at_5
value: 62.854
- task:
type: Classification
dataset:
type: C-MTEB/TNews-classification
name: MTEB TNews
config: default
split: validation
revision: None
metrics:
- type: accuracy
value: 49.851
- type: f1
value: 48.115308719873006
- task:
type: Clustering
dataset:
type: C-MTEB/ThuNewsClusteringP2P
name: MTEB ThuNewsClusteringP2P
config: default
split: test
revision: None
metrics:
- type: v_measure
value: 58.53624772949936
- task:
type: Clustering
dataset:
type: C-MTEB/ThuNewsClusteringS2S
name: MTEB ThuNewsClusteringS2S
config: default
split: test
revision: None
metrics:
- type: v_measure
value: 54.145039782849956
- task:
type: Retrieval
dataset:
type: C-MTEB/VideoRetrieval
name: MTEB VideoRetrieval
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 49
- type: map_at_10
value: 58.888
- type: map_at_100
value: 59.512
- type: map_at_1000
value: 59.532
- type: map_at_3
value: 56.65
- type: map_at_5
value: 57.91
- type: mrr_at_1
value: 49
- type: mrr_at_10
value: 58.888
- type: mrr_at_100
value: 59.512
- type: mrr_at_1000
value: 59.532
- type: mrr_at_3
value: 56.65
- type: mrr_at_5
value: 57.91
- type: ndcg_at_1
value: 49
- type: ndcg_at_10
value: 63.656
- type: ndcg_at_100
value: 66.666
- type: ndcg_at_1000
value: 67.269
- type: ndcg_at_3
value: 59.082
- type: ndcg_at_5
value: 61.35
- type: precision_at_1
value: 49
- type: precision_at_10
value: 7.86
- type: precision_at_100
value: 0.9259999999999999
- type: precision_at_1000
value: 0.098
- type: precision_at_3
value: 22.033
- type: precision_at_5
value: 14.32
- type: recall_at_1
value: 49
- type: recall_at_10
value: 78.60000000000001
- type: recall_at_100
value: 92.60000000000001
- type: recall_at_1000
value: 97.5
- type: recall_at_3
value: 66.10000000000001
- type: recall_at_5
value: 71.6
- task:
type: Classification
dataset:
type: C-MTEB/waimai-classification
name: MTEB Waimai
config: default
split: test
revision: None
metrics:
- type: accuracy
value: 86.44000000000001
- type: ap
value: 69.51298270778649
- type: f1
value: 84.72728998827236