|
--- |
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tags: |
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- mteb |
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- transformers.js |
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- transformers |
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model-index: |
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- name: mxbai-embed-2d-large-v1 |
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results: |
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- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
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split: test |
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 74.76119402985074 |
|
- type: ap |
|
value: 37.90611182084586 |
|
- type: f1 |
|
value: 68.80795400445113 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_polarity |
|
name: MTEB AmazonPolarityClassification |
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config: default |
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split: test |
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revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 93.255525 |
|
- type: ap |
|
value: 90.06886124154308 |
|
- type: f1 |
|
value: 93.24785420201029 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
|
split: test |
|
revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 46.162000000000006 |
|
- type: f1 |
|
value: 45.66989189593428 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: arguana |
|
name: MTEB ArguAna |
|
config: default |
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split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 37.980000000000004 |
|
- type: map_at_10 |
|
value: 54.918 |
|
- type: map_at_100 |
|
value: 55.401 |
|
- type: map_at_1000 |
|
value: 55.403000000000006 |
|
- type: map_at_3 |
|
value: 50.249 |
|
- type: map_at_5 |
|
value: 53.400000000000006 |
|
- type: mrr_at_1 |
|
value: 38.834 |
|
- type: mrr_at_10 |
|
value: 55.24 |
|
- type: mrr_at_100 |
|
value: 55.737 |
|
- type: mrr_at_1000 |
|
value: 55.738 |
|
- type: mrr_at_3 |
|
value: 50.580999999999996 |
|
- type: mrr_at_5 |
|
value: 53.71 |
|
- type: ndcg_at_1 |
|
value: 37.980000000000004 |
|
- type: ndcg_at_10 |
|
value: 63.629000000000005 |
|
- type: ndcg_at_100 |
|
value: 65.567 |
|
- type: ndcg_at_1000 |
|
value: 65.61399999999999 |
|
- type: ndcg_at_3 |
|
value: 54.275 |
|
- type: ndcg_at_5 |
|
value: 59.91 |
|
- type: precision_at_1 |
|
value: 37.980000000000004 |
|
- type: precision_at_10 |
|
value: 9.110999999999999 |
|
- type: precision_at_100 |
|
value: 0.993 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 21.977 |
|
- type: precision_at_5 |
|
value: 15.903 |
|
- type: recall_at_1 |
|
value: 37.980000000000004 |
|
- type: recall_at_10 |
|
value: 91.11 |
|
- type: recall_at_100 |
|
value: 99.289 |
|
- type: recall_at_1000 |
|
value: 99.644 |
|
- type: recall_at_3 |
|
value: 65.932 |
|
- type: recall_at_5 |
|
value: 79.51599999999999 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-p2p |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 48.28746486562395 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-s2s |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 42.335244985544165 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/askubuntudupquestions-reranking |
|
name: MTEB AskUbuntuDupQuestions |
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config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 63.771155681602096 |
|
- type: mrr |
|
value: 76.55993052807459 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/biosses-sts |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 89.76152904846916 |
|
- type: cos_sim_spearman |
|
value: 88.05622328825284 |
|
- type: euclidean_pearson |
|
value: 88.2821986323439 |
|
- type: euclidean_spearman |
|
value: 88.05622328825284 |
|
- type: manhattan_pearson |
|
value: 87.98419111117559 |
|
- type: manhattan_spearman |
|
value: 87.905617446958 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/banking77 |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 86.65259740259741 |
|
- type: f1 |
|
value: 86.62044951853902 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-p2p |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 39.7270855384167 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-s2s |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 36.95365397158872 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
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split: test |
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revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 30.604 |
|
- type: map_at_10 |
|
value: 42.126999999999995 |
|
- type: map_at_100 |
|
value: 43.702999999999996 |
|
- type: map_at_1000 |
|
value: 43.851 |
|
- type: map_at_3 |
|
value: 38.663 |
|
- type: map_at_5 |
|
value: 40.67 |
|
- type: mrr_at_1 |
|
value: 37.625 |
|
- type: mrr_at_10 |
|
value: 48.203 |
|
- type: mrr_at_100 |
|
value: 48.925000000000004 |
|
- type: mrr_at_1000 |
|
value: 48.979 |
|
- type: mrr_at_3 |
|
value: 45.494 |
|
- type: mrr_at_5 |
|
value: 47.288999999999994 |
|
- type: ndcg_at_1 |
|
value: 37.625 |
|
- type: ndcg_at_10 |
|
value: 48.649 |
|
- type: ndcg_at_100 |
|
value: 54.041 |
|
- type: ndcg_at_1000 |
|
value: 56.233999999999995 |
|
- type: ndcg_at_3 |
|
value: 43.704 |
|
- type: ndcg_at_5 |
|
value: 46.172999999999995 |
|
- type: precision_at_1 |
|
value: 37.625 |
|
- type: precision_at_10 |
|
value: 9.371 |
|
- type: precision_at_100 |
|
value: 1.545 |
|
- type: precision_at_1000 |
|
value: 0.20400000000000001 |
|
- type: precision_at_3 |
|
value: 21.364 |
|
- type: precision_at_5 |
|
value: 15.421999999999999 |
|
- type: recall_at_1 |
|
value: 30.604 |
|
- type: recall_at_10 |
|
value: 60.94199999999999 |
|
- type: recall_at_100 |
|
value: 82.893 |
|
- type: recall_at_1000 |
|
value: 96.887 |
|
- type: recall_at_3 |
|
value: 46.346 |
|
- type: recall_at_5 |
|
value: 53.495000000000005 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 29.959000000000003 |
|
- type: map_at_10 |
|
value: 40.217999999999996 |
|
- type: map_at_100 |
|
value: 41.337 |
|
- type: map_at_1000 |
|
value: 41.471999999999994 |
|
- type: map_at_3 |
|
value: 37.029 |
|
- type: map_at_5 |
|
value: 38.873000000000005 |
|
- type: mrr_at_1 |
|
value: 37.325 |
|
- type: mrr_at_10 |
|
value: 45.637 |
|
- type: mrr_at_100 |
|
value: 46.243 |
|
- type: mrr_at_1000 |
|
value: 46.297 |
|
- type: mrr_at_3 |
|
value: 43.323 |
|
- type: mrr_at_5 |
|
value: 44.734 |
|
- type: ndcg_at_1 |
|
value: 37.325 |
|
- type: ndcg_at_10 |
|
value: 45.864 |
|
- type: ndcg_at_100 |
|
value: 49.832 |
|
- type: ndcg_at_1000 |
|
value: 52.056000000000004 |
|
- type: ndcg_at_3 |
|
value: 41.329 |
|
- type: ndcg_at_5 |
|
value: 43.547000000000004 |
|
- type: precision_at_1 |
|
value: 37.325 |
|
- type: precision_at_10 |
|
value: 8.732 |
|
- type: precision_at_100 |
|
value: 1.369 |
|
- type: precision_at_1000 |
|
value: 0.185 |
|
- type: precision_at_3 |
|
value: 19.936 |
|
- type: precision_at_5 |
|
value: 14.306 |
|
- type: recall_at_1 |
|
value: 29.959000000000003 |
|
- type: recall_at_10 |
|
value: 56.113 |
|
- type: recall_at_100 |
|
value: 73.231 |
|
- type: recall_at_1000 |
|
value: 87.373 |
|
- type: recall_at_3 |
|
value: 42.88 |
|
- type: recall_at_5 |
|
value: 49.004 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 38.679 |
|
- type: map_at_10 |
|
value: 50.696 |
|
- type: map_at_100 |
|
value: 51.788000000000004 |
|
- type: map_at_1000 |
|
value: 51.849999999999994 |
|
- type: map_at_3 |
|
value: 47.414 |
|
- type: map_at_5 |
|
value: 49.284 |
|
- type: mrr_at_1 |
|
value: 44.263000000000005 |
|
- type: mrr_at_10 |
|
value: 54.03 |
|
- type: mrr_at_100 |
|
value: 54.752 |
|
- type: mrr_at_1000 |
|
value: 54.784 |
|
- type: mrr_at_3 |
|
value: 51.661 |
|
- type: mrr_at_5 |
|
value: 53.047 |
|
- type: ndcg_at_1 |
|
value: 44.263000000000005 |
|
- type: ndcg_at_10 |
|
value: 56.452999999999996 |
|
- type: ndcg_at_100 |
|
value: 60.736999999999995 |
|
- type: ndcg_at_1000 |
|
value: 61.982000000000006 |
|
- type: ndcg_at_3 |
|
value: 51.085 |
|
- type: ndcg_at_5 |
|
value: 53.715999999999994 |
|
- type: precision_at_1 |
|
value: 44.263000000000005 |
|
- type: precision_at_10 |
|
value: 9.129 |
|
- type: precision_at_100 |
|
value: 1.218 |
|
- type: precision_at_1000 |
|
value: 0.13699999999999998 |
|
- type: precision_at_3 |
|
value: 22.8 |
|
- type: precision_at_5 |
|
value: 15.674 |
|
- type: recall_at_1 |
|
value: 38.679 |
|
- type: recall_at_10 |
|
value: 70.1 |
|
- type: recall_at_100 |
|
value: 88.649 |
|
- type: recall_at_1000 |
|
value: 97.48 |
|
- type: recall_at_3 |
|
value: 55.757999999999996 |
|
- type: recall_at_5 |
|
value: 62.244 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.796999999999997 |
|
- type: map_at_10 |
|
value: 34.011 |
|
- type: map_at_100 |
|
value: 35.103 |
|
- type: map_at_1000 |
|
value: 35.187000000000005 |
|
- type: map_at_3 |
|
value: 31.218 |
|
- type: map_at_5 |
|
value: 32.801 |
|
- type: mrr_at_1 |
|
value: 28.022999999999996 |
|
- type: mrr_at_10 |
|
value: 36.108000000000004 |
|
- type: mrr_at_100 |
|
value: 37.094 |
|
- type: mrr_at_1000 |
|
value: 37.158 |
|
- type: mrr_at_3 |
|
value: 33.635 |
|
- type: mrr_at_5 |
|
value: 35.081 |
|
- type: ndcg_at_1 |
|
value: 28.022999999999996 |
|
- type: ndcg_at_10 |
|
value: 38.887 |
|
- type: ndcg_at_100 |
|
value: 44.159 |
|
- type: ndcg_at_1000 |
|
value: 46.300000000000004 |
|
- type: ndcg_at_3 |
|
value: 33.623 |
|
- type: ndcg_at_5 |
|
value: 36.281 |
|
- type: precision_at_1 |
|
value: 28.022999999999996 |
|
- type: precision_at_10 |
|
value: 6.010999999999999 |
|
- type: precision_at_100 |
|
value: 0.901 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 14.124 |
|
- type: precision_at_5 |
|
value: 10.034 |
|
- type: recall_at_1 |
|
value: 25.796999999999997 |
|
- type: recall_at_10 |
|
value: 51.86300000000001 |
|
- type: recall_at_100 |
|
value: 75.995 |
|
- type: recall_at_1000 |
|
value: 91.93299999999999 |
|
- type: recall_at_3 |
|
value: 37.882 |
|
- type: recall_at_5 |
|
value: 44.34 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 15.468000000000002 |
|
- type: map_at_10 |
|
value: 24.026 |
|
- type: map_at_100 |
|
value: 25.237 |
|
- type: map_at_1000 |
|
value: 25.380000000000003 |
|
- type: map_at_3 |
|
value: 21.342 |
|
- type: map_at_5 |
|
value: 22.843 |
|
- type: mrr_at_1 |
|
value: 19.154 |
|
- type: mrr_at_10 |
|
value: 28.429 |
|
- type: mrr_at_100 |
|
value: 29.416999999999998 |
|
- type: mrr_at_1000 |
|
value: 29.491 |
|
- type: mrr_at_3 |
|
value: 25.746000000000002 |
|
- type: mrr_at_5 |
|
value: 27.282 |
|
- type: ndcg_at_1 |
|
value: 19.154 |
|
- type: ndcg_at_10 |
|
value: 29.512 |
|
- type: ndcg_at_100 |
|
value: 35.331 |
|
- type: ndcg_at_1000 |
|
value: 38.435 |
|
- type: ndcg_at_3 |
|
value: 24.566 |
|
- type: ndcg_at_5 |
|
value: 26.891 |
|
- type: precision_at_1 |
|
value: 19.154 |
|
- type: precision_at_10 |
|
value: 5.647 |
|
- type: precision_at_100 |
|
value: 0.984 |
|
- type: precision_at_1000 |
|
value: 0.13899999999999998 |
|
- type: precision_at_3 |
|
value: 12.065 |
|
- type: precision_at_5 |
|
value: 8.98 |
|
- type: recall_at_1 |
|
value: 15.468000000000002 |
|
- type: recall_at_10 |
|
value: 41.908 |
|
- type: recall_at_100 |
|
value: 67.17 |
|
- type: recall_at_1000 |
|
value: 89.05499999999999 |
|
- type: recall_at_3 |
|
value: 28.436 |
|
- type: recall_at_5 |
|
value: 34.278 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 28.116000000000003 |
|
- type: map_at_10 |
|
value: 39.034 |
|
- type: map_at_100 |
|
value: 40.461000000000006 |
|
- type: map_at_1000 |
|
value: 40.563 |
|
- type: map_at_3 |
|
value: 35.742000000000004 |
|
- type: map_at_5 |
|
value: 37.762 |
|
- type: mrr_at_1 |
|
value: 34.264 |
|
- type: mrr_at_10 |
|
value: 44.173 |
|
- type: mrr_at_100 |
|
value: 45.111000000000004 |
|
- type: mrr_at_1000 |
|
value: 45.149 |
|
- type: mrr_at_3 |
|
value: 41.626999999999995 |
|
- type: mrr_at_5 |
|
value: 43.234 |
|
- type: ndcg_at_1 |
|
value: 34.264 |
|
- type: ndcg_at_10 |
|
value: 45.011 |
|
- type: ndcg_at_100 |
|
value: 50.91 |
|
- type: ndcg_at_1000 |
|
value: 52.886 |
|
- type: ndcg_at_3 |
|
value: 39.757999999999996 |
|
- type: ndcg_at_5 |
|
value: 42.569 |
|
- type: precision_at_1 |
|
value: 34.264 |
|
- type: precision_at_10 |
|
value: 8.114 |
|
- type: precision_at_100 |
|
value: 1.2890000000000001 |
|
- type: precision_at_1000 |
|
value: 0.163 |
|
- type: precision_at_3 |
|
value: 18.864 |
|
- type: precision_at_5 |
|
value: 13.628000000000002 |
|
- type: recall_at_1 |
|
value: 28.116000000000003 |
|
- type: recall_at_10 |
|
value: 57.764 |
|
- type: recall_at_100 |
|
value: 82.393 |
|
- type: recall_at_1000 |
|
value: 95.345 |
|
- type: recall_at_3 |
|
value: 43.35 |
|
- type: recall_at_5 |
|
value: 50.368 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.557 |
|
- type: map_at_10 |
|
value: 33.94 |
|
- type: map_at_100 |
|
value: 35.382000000000005 |
|
- type: map_at_1000 |
|
value: 35.497 |
|
- type: map_at_3 |
|
value: 30.635 |
|
- type: map_at_5 |
|
value: 32.372 |
|
- type: mrr_at_1 |
|
value: 29.224 |
|
- type: mrr_at_10 |
|
value: 39.017 |
|
- type: mrr_at_100 |
|
value: 39.908 |
|
- type: mrr_at_1000 |
|
value: 39.96 |
|
- type: mrr_at_3 |
|
value: 36.225 |
|
- type: mrr_at_5 |
|
value: 37.869 |
|
- type: ndcg_at_1 |
|
value: 29.224 |
|
- type: ndcg_at_10 |
|
value: 40.097 |
|
- type: ndcg_at_100 |
|
value: 46.058 |
|
- type: ndcg_at_1000 |
|
value: 48.309999999999995 |
|
- type: ndcg_at_3 |
|
value: 34.551 |
|
- type: ndcg_at_5 |
|
value: 36.937 |
|
- type: precision_at_1 |
|
value: 29.224 |
|
- type: precision_at_10 |
|
value: 7.6259999999999994 |
|
- type: precision_at_100 |
|
value: 1.226 |
|
- type: precision_at_1000 |
|
value: 0.161 |
|
- type: precision_at_3 |
|
value: 16.781 |
|
- type: precision_at_5 |
|
value: 12.26 |
|
- type: recall_at_1 |
|
value: 23.557 |
|
- type: recall_at_10 |
|
value: 53.46300000000001 |
|
- type: recall_at_100 |
|
value: 78.797 |
|
- type: recall_at_1000 |
|
value: 93.743 |
|
- type: recall_at_3 |
|
value: 37.95 |
|
- type: recall_at_5 |
|
value: 44.121 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.81583333333333 |
|
- type: map_at_10 |
|
value: 34.057833333333335 |
|
- type: map_at_100 |
|
value: 35.29658333333334 |
|
- type: map_at_1000 |
|
value: 35.418666666666674 |
|
- type: map_at_3 |
|
value: 31.16416666666667 |
|
- type: map_at_5 |
|
value: 32.797 |
|
- type: mrr_at_1 |
|
value: 29.40216666666667 |
|
- type: mrr_at_10 |
|
value: 38.11191666666667 |
|
- type: mrr_at_100 |
|
value: 38.983250000000005 |
|
- type: mrr_at_1000 |
|
value: 39.043 |
|
- type: mrr_at_3 |
|
value: 35.663333333333334 |
|
- type: mrr_at_5 |
|
value: 37.08975 |
|
- type: ndcg_at_1 |
|
value: 29.40216666666667 |
|
- type: ndcg_at_10 |
|
value: 39.462416666666655 |
|
- type: ndcg_at_100 |
|
value: 44.74341666666666 |
|
- type: ndcg_at_1000 |
|
value: 47.12283333333333 |
|
- type: ndcg_at_3 |
|
value: 34.57383333333334 |
|
- type: ndcg_at_5 |
|
value: 36.91816666666667 |
|
- type: precision_at_1 |
|
value: 29.40216666666667 |
|
- type: precision_at_10 |
|
value: 7.008416666666667 |
|
- type: precision_at_100 |
|
value: 1.143333333333333 |
|
- type: precision_at_1000 |
|
value: 0.15391666666666665 |
|
- type: precision_at_3 |
|
value: 16.011083333333335 |
|
- type: precision_at_5 |
|
value: 11.506666666666664 |
|
- type: recall_at_1 |
|
value: 24.81583333333333 |
|
- type: recall_at_10 |
|
value: 51.39391666666666 |
|
- type: recall_at_100 |
|
value: 74.52983333333333 |
|
- type: recall_at_1000 |
|
value: 91.00650000000002 |
|
- type: recall_at_3 |
|
value: 37.87458333333334 |
|
- type: recall_at_5 |
|
value: 43.865833333333335 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.04 |
|
- type: map_at_10 |
|
value: 30.651 |
|
- type: map_at_100 |
|
value: 31.561 |
|
- type: map_at_1000 |
|
value: 31.667 |
|
- type: map_at_3 |
|
value: 28.358 |
|
- type: map_at_5 |
|
value: 29.644 |
|
- type: mrr_at_1 |
|
value: 26.840000000000003 |
|
- type: mrr_at_10 |
|
value: 33.397 |
|
- type: mrr_at_100 |
|
value: 34.166999999999994 |
|
- type: mrr_at_1000 |
|
value: 34.252 |
|
- type: mrr_at_3 |
|
value: 31.339 |
|
- type: mrr_at_5 |
|
value: 32.451 |
|
- type: ndcg_at_1 |
|
value: 26.840000000000003 |
|
- type: ndcg_at_10 |
|
value: 34.821999999999996 |
|
- type: ndcg_at_100 |
|
value: 39.155 |
|
- type: ndcg_at_1000 |
|
value: 41.837999999999994 |
|
- type: ndcg_at_3 |
|
value: 30.55 |
|
- type: ndcg_at_5 |
|
value: 32.588 |
|
- type: precision_at_1 |
|
value: 26.840000000000003 |
|
- type: precision_at_10 |
|
value: 5.383 |
|
- type: precision_at_100 |
|
value: 0.827 |
|
- type: precision_at_1000 |
|
value: 0.11199999999999999 |
|
- type: precision_at_3 |
|
value: 12.986 |
|
- type: precision_at_5 |
|
value: 9.11 |
|
- type: recall_at_1 |
|
value: 24.04 |
|
- type: recall_at_10 |
|
value: 45.133 |
|
- type: recall_at_100 |
|
value: 64.519 |
|
- type: recall_at_1000 |
|
value: 84.397 |
|
- type: recall_at_3 |
|
value: 33.465 |
|
- type: recall_at_5 |
|
value: 38.504 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 15.744 |
|
- type: map_at_10 |
|
value: 22.557 |
|
- type: map_at_100 |
|
value: 23.705000000000002 |
|
- type: map_at_1000 |
|
value: 23.833 |
|
- type: map_at_3 |
|
value: 20.342 |
|
- type: map_at_5 |
|
value: 21.584 |
|
- type: mrr_at_1 |
|
value: 19.133 |
|
- type: mrr_at_10 |
|
value: 26.316 |
|
- type: mrr_at_100 |
|
value: 27.285999999999998 |
|
- type: mrr_at_1000 |
|
value: 27.367 |
|
- type: mrr_at_3 |
|
value: 24.214 |
|
- type: mrr_at_5 |
|
value: 25.419999999999998 |
|
- type: ndcg_at_1 |
|
value: 19.133 |
|
- type: ndcg_at_10 |
|
value: 27.002 |
|
- type: ndcg_at_100 |
|
value: 32.544000000000004 |
|
- type: ndcg_at_1000 |
|
value: 35.624 |
|
- type: ndcg_at_3 |
|
value: 23.015 |
|
- type: ndcg_at_5 |
|
value: 24.916 |
|
- type: precision_at_1 |
|
value: 19.133 |
|
- type: precision_at_10 |
|
value: 4.952 |
|
- type: precision_at_100 |
|
value: 0.918 |
|
- type: precision_at_1000 |
|
value: 0.136 |
|
- type: precision_at_3 |
|
value: 10.908 |
|
- type: precision_at_5 |
|
value: 8.004 |
|
- type: recall_at_1 |
|
value: 15.744 |
|
- type: recall_at_10 |
|
value: 36.63 |
|
- type: recall_at_100 |
|
value: 61.58 |
|
- type: recall_at_1000 |
|
value: 83.648 |
|
- type: recall_at_3 |
|
value: 25.545 |
|
- type: recall_at_5 |
|
value: 30.392000000000003 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.944 |
|
- type: map_at_10 |
|
value: 33.611000000000004 |
|
- type: map_at_100 |
|
value: 34.737 |
|
- type: map_at_1000 |
|
value: 34.847 |
|
- type: map_at_3 |
|
value: 30.746000000000002 |
|
- type: map_at_5 |
|
value: 32.357 |
|
- type: mrr_at_1 |
|
value: 29.198 |
|
- type: mrr_at_10 |
|
value: 37.632 |
|
- type: mrr_at_100 |
|
value: 38.53 |
|
- type: mrr_at_1000 |
|
value: 38.59 |
|
- type: mrr_at_3 |
|
value: 35.292 |
|
- type: mrr_at_5 |
|
value: 36.519 |
|
- type: ndcg_at_1 |
|
value: 29.198 |
|
- type: ndcg_at_10 |
|
value: 38.946999999999996 |
|
- type: ndcg_at_100 |
|
value: 44.348 |
|
- type: ndcg_at_1000 |
|
value: 46.787 |
|
- type: ndcg_at_3 |
|
value: 33.794999999999995 |
|
- type: ndcg_at_5 |
|
value: 36.166 |
|
- type: precision_at_1 |
|
value: 29.198 |
|
- type: precision_at_10 |
|
value: 6.595 |
|
- type: precision_at_100 |
|
value: 1.055 |
|
- type: precision_at_1000 |
|
value: 0.13899999999999998 |
|
- type: precision_at_3 |
|
value: 15.235999999999999 |
|
- type: precision_at_5 |
|
value: 10.896 |
|
- type: recall_at_1 |
|
value: 24.944 |
|
- type: recall_at_10 |
|
value: 51.284 |
|
- type: recall_at_100 |
|
value: 75.197 |
|
- type: recall_at_1000 |
|
value: 92.10000000000001 |
|
- type: recall_at_3 |
|
value: 37.213 |
|
- type: recall_at_5 |
|
value: 43.129 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.979000000000003 |
|
- type: map_at_10 |
|
value: 31.349 |
|
- type: map_at_100 |
|
value: 32.969 |
|
- type: map_at_1000 |
|
value: 33.2 |
|
- type: map_at_3 |
|
value: 28.237000000000002 |
|
- type: map_at_5 |
|
value: 30.09 |
|
- type: mrr_at_1 |
|
value: 27.075 |
|
- type: mrr_at_10 |
|
value: 35.946 |
|
- type: mrr_at_100 |
|
value: 36.897000000000006 |
|
- type: mrr_at_1000 |
|
value: 36.951 |
|
- type: mrr_at_3 |
|
value: 32.971000000000004 |
|
- type: mrr_at_5 |
|
value: 34.868 |
|
- type: ndcg_at_1 |
|
value: 27.075 |
|
- type: ndcg_at_10 |
|
value: 37.317 |
|
- type: ndcg_at_100 |
|
value: 43.448 |
|
- type: ndcg_at_1000 |
|
value: 45.940999999999995 |
|
- type: ndcg_at_3 |
|
value: 32.263 |
|
- type: ndcg_at_5 |
|
value: 34.981 |
|
- type: precision_at_1 |
|
value: 27.075 |
|
- type: precision_at_10 |
|
value: 7.568999999999999 |
|
- type: precision_at_100 |
|
value: 1.5650000000000002 |
|
- type: precision_at_1000 |
|
value: 0.241 |
|
- type: precision_at_3 |
|
value: 15.547 |
|
- type: precision_at_5 |
|
value: 11.818 |
|
- type: recall_at_1 |
|
value: 21.979000000000003 |
|
- type: recall_at_10 |
|
value: 48.522999999999996 |
|
- type: recall_at_100 |
|
value: 76.51 |
|
- type: recall_at_1000 |
|
value: 92.168 |
|
- type: recall_at_3 |
|
value: 34.499 |
|
- type: recall_at_5 |
|
value: 41.443999999999996 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.903 |
|
- type: map_at_10 |
|
value: 26.473999999999997 |
|
- type: map_at_100 |
|
value: 27.576 |
|
- type: map_at_1000 |
|
value: 27.677000000000003 |
|
- type: map_at_3 |
|
value: 24.244 |
|
- type: map_at_5 |
|
value: 25.284000000000002 |
|
- type: mrr_at_1 |
|
value: 20.702 |
|
- type: mrr_at_10 |
|
value: 28.455000000000002 |
|
- type: mrr_at_100 |
|
value: 29.469 |
|
- type: mrr_at_1000 |
|
value: 29.537999999999997 |
|
- type: mrr_at_3 |
|
value: 26.433 |
|
- type: mrr_at_5 |
|
value: 27.283 |
|
- type: ndcg_at_1 |
|
value: 20.702 |
|
- type: ndcg_at_10 |
|
value: 30.988 |
|
- type: ndcg_at_100 |
|
value: 36.358000000000004 |
|
- type: ndcg_at_1000 |
|
value: 39.080999999999996 |
|
- type: ndcg_at_3 |
|
value: 26.647 |
|
- type: ndcg_at_5 |
|
value: 28.253 |
|
- type: precision_at_1 |
|
value: 20.702 |
|
- type: precision_at_10 |
|
value: 4.972 |
|
- type: precision_at_100 |
|
value: 0.823 |
|
- type: precision_at_1000 |
|
value: 0.117 |
|
- type: precision_at_3 |
|
value: 11.522 |
|
- type: precision_at_5 |
|
value: 7.9479999999999995 |
|
- type: recall_at_1 |
|
value: 18.903 |
|
- type: recall_at_10 |
|
value: 43.004 |
|
- type: recall_at_100 |
|
value: 67.42399999999999 |
|
- type: recall_at_1000 |
|
value: 87.949 |
|
- type: recall_at_3 |
|
value: 31.171 |
|
- type: recall_at_5 |
|
value: 35.071000000000005 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: climate-fever |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 12.942 |
|
- type: map_at_10 |
|
value: 22.017999999999997 |
|
- type: map_at_100 |
|
value: 23.968 |
|
- type: map_at_1000 |
|
value: 24.169 |
|
- type: map_at_3 |
|
value: 18.282 |
|
- type: map_at_5 |
|
value: 20.191 |
|
- type: mrr_at_1 |
|
value: 29.121000000000002 |
|
- type: mrr_at_10 |
|
value: 40.897 |
|
- type: mrr_at_100 |
|
value: 41.787 |
|
- type: mrr_at_1000 |
|
value: 41.819 |
|
- type: mrr_at_3 |
|
value: 37.535000000000004 |
|
- type: mrr_at_5 |
|
value: 39.626 |
|
- type: ndcg_at_1 |
|
value: 29.121000000000002 |
|
- type: ndcg_at_10 |
|
value: 30.728 |
|
- type: ndcg_at_100 |
|
value: 38.231 |
|
- type: ndcg_at_1000 |
|
value: 41.735 |
|
- type: ndcg_at_3 |
|
value: 25.141000000000002 |
|
- type: ndcg_at_5 |
|
value: 27.093 |
|
- type: precision_at_1 |
|
value: 29.121000000000002 |
|
- type: precision_at_10 |
|
value: 9.674000000000001 |
|
- type: precision_at_100 |
|
value: 1.775 |
|
- type: precision_at_1000 |
|
value: 0.243 |
|
- type: precision_at_3 |
|
value: 18.826999999999998 |
|
- type: precision_at_5 |
|
value: 14.515 |
|
- type: recall_at_1 |
|
value: 12.942 |
|
- type: recall_at_10 |
|
value: 36.692 |
|
- type: recall_at_100 |
|
value: 62.688 |
|
- type: recall_at_1000 |
|
value: 82.203 |
|
- type: recall_at_3 |
|
value: 22.820999999999998 |
|
- type: recall_at_5 |
|
value: 28.625 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: dbpedia-entity |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.6 |
|
- type: map_at_10 |
|
value: 18.672 |
|
- type: map_at_100 |
|
value: 27.199 |
|
- type: map_at_1000 |
|
value: 29.032999999999998 |
|
- type: map_at_3 |
|
value: 13.045000000000002 |
|
- type: map_at_5 |
|
value: 15.271 |
|
- type: mrr_at_1 |
|
value: 69 |
|
- type: mrr_at_10 |
|
value: 75.304 |
|
- type: mrr_at_100 |
|
value: 75.68 |
|
- type: mrr_at_1000 |
|
value: 75.688 |
|
- type: mrr_at_3 |
|
value: 73.708 |
|
- type: mrr_at_5 |
|
value: 74.333 |
|
- type: ndcg_at_1 |
|
value: 56.25 |
|
- type: ndcg_at_10 |
|
value: 40.741 |
|
- type: ndcg_at_100 |
|
value: 45.933 |
|
- type: ndcg_at_1000 |
|
value: 53.764 |
|
- type: ndcg_at_3 |
|
value: 44.664 |
|
- type: ndcg_at_5 |
|
value: 42.104 |
|
- type: precision_at_1 |
|
value: 69 |
|
- type: precision_at_10 |
|
value: 33 |
|
- type: precision_at_100 |
|
value: 10.75 |
|
- type: precision_at_1000 |
|
value: 2.1999999999999997 |
|
- type: precision_at_3 |
|
value: 48.167 |
|
- type: precision_at_5 |
|
value: 41.099999999999994 |
|
- type: recall_at_1 |
|
value: 8.6 |
|
- type: recall_at_10 |
|
value: 24.447 |
|
- type: recall_at_100 |
|
value: 52.697 |
|
- type: recall_at_1000 |
|
value: 77.717 |
|
- type: recall_at_3 |
|
value: 14.13 |
|
- type: recall_at_5 |
|
value: 17.485999999999997 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/emotion |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 49.32 |
|
- type: f1 |
|
value: 43.92815810776849 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fever |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 68.987 |
|
- type: map_at_10 |
|
value: 78.025 |
|
- type: map_at_100 |
|
value: 78.28500000000001 |
|
- type: map_at_1000 |
|
value: 78.3 |
|
- type: map_at_3 |
|
value: 76.735 |
|
- type: map_at_5 |
|
value: 77.558 |
|
- type: mrr_at_1 |
|
value: 74.482 |
|
- type: mrr_at_10 |
|
value: 82.673 |
|
- type: mrr_at_100 |
|
value: 82.799 |
|
- type: mrr_at_1000 |
|
value: 82.804 |
|
- type: mrr_at_3 |
|
value: 81.661 |
|
- type: mrr_at_5 |
|
value: 82.369 |
|
- type: ndcg_at_1 |
|
value: 74.482 |
|
- type: ndcg_at_10 |
|
value: 82.238 |
|
- type: ndcg_at_100 |
|
value: 83.245 |
|
- type: ndcg_at_1000 |
|
value: 83.557 |
|
- type: ndcg_at_3 |
|
value: 80.066 |
|
- type: ndcg_at_5 |
|
value: 81.316 |
|
- type: precision_at_1 |
|
value: 74.482 |
|
- type: precision_at_10 |
|
value: 10.006 |
|
- type: precision_at_100 |
|
value: 1.0699999999999998 |
|
- type: precision_at_1000 |
|
value: 0.11100000000000002 |
|
- type: precision_at_3 |
|
value: 30.808000000000003 |
|
- type: precision_at_5 |
|
value: 19.256 |
|
- type: recall_at_1 |
|
value: 68.987 |
|
- type: recall_at_10 |
|
value: 90.646 |
|
- type: recall_at_100 |
|
value: 94.85900000000001 |
|
- type: recall_at_1000 |
|
value: 96.979 |
|
- type: recall_at_3 |
|
value: 84.76599999999999 |
|
- type: recall_at_5 |
|
value: 87.929 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fiqa |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.3 |
|
- type: map_at_10 |
|
value: 33.499 |
|
- type: map_at_100 |
|
value: 35.510000000000005 |
|
- type: map_at_1000 |
|
value: 35.693999999999996 |
|
- type: map_at_3 |
|
value: 29.083 |
|
- type: map_at_5 |
|
value: 31.367 |
|
- type: mrr_at_1 |
|
value: 39.660000000000004 |
|
- type: mrr_at_10 |
|
value: 49.517 |
|
- type: mrr_at_100 |
|
value: 50.18899999999999 |
|
- type: mrr_at_1000 |
|
value: 50.224000000000004 |
|
- type: mrr_at_3 |
|
value: 46.965 |
|
- type: mrr_at_5 |
|
value: 48.184 |
|
- type: ndcg_at_1 |
|
value: 39.660000000000004 |
|
- type: ndcg_at_10 |
|
value: 41.75 |
|
- type: ndcg_at_100 |
|
value: 48.477 |
|
- type: ndcg_at_1000 |
|
value: 51.373999999999995 |
|
- type: ndcg_at_3 |
|
value: 37.532 |
|
- type: ndcg_at_5 |
|
value: 38.564 |
|
- type: precision_at_1 |
|
value: 39.660000000000004 |
|
- type: precision_at_10 |
|
value: 11.774999999999999 |
|
- type: precision_at_100 |
|
value: 1.883 |
|
- type: precision_at_1000 |
|
value: 0.23900000000000002 |
|
- type: precision_at_3 |
|
value: 25.102999999999998 |
|
- type: precision_at_5 |
|
value: 18.395 |
|
- type: recall_at_1 |
|
value: 20.3 |
|
- type: recall_at_10 |
|
value: 49.633 |
|
- type: recall_at_100 |
|
value: 73.932 |
|
- type: recall_at_1000 |
|
value: 91.174 |
|
- type: recall_at_3 |
|
value: 34.516999999999996 |
|
- type: recall_at_5 |
|
value: 40.217000000000006 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: hotpotqa |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 34.699999999999996 |
|
- type: map_at_10 |
|
value: 54.400000000000006 |
|
- type: map_at_100 |
|
value: 55.45 |
|
- type: map_at_1000 |
|
value: 55.525999999999996 |
|
- type: map_at_3 |
|
value: 50.99 |
|
- type: map_at_5 |
|
value: 53.054 |
|
- type: mrr_at_1 |
|
value: 69.399 |
|
- type: mrr_at_10 |
|
value: 76.454 |
|
- type: mrr_at_100 |
|
value: 76.771 |
|
- type: mrr_at_1000 |
|
value: 76.783 |
|
- type: mrr_at_3 |
|
value: 75.179 |
|
- type: mrr_at_5 |
|
value: 75.978 |
|
- type: ndcg_at_1 |
|
value: 69.399 |
|
- type: ndcg_at_10 |
|
value: 63.001 |
|
- type: ndcg_at_100 |
|
value: 66.842 |
|
- type: ndcg_at_1000 |
|
value: 68.33500000000001 |
|
- type: ndcg_at_3 |
|
value: 57.961 |
|
- type: ndcg_at_5 |
|
value: 60.67700000000001 |
|
- type: precision_at_1 |
|
value: 69.399 |
|
- type: precision_at_10 |
|
value: 13.4 |
|
- type: precision_at_100 |
|
value: 1.6420000000000001 |
|
- type: precision_at_1000 |
|
value: 0.184 |
|
- type: precision_at_3 |
|
value: 37.218 |
|
- type: precision_at_5 |
|
value: 24.478 |
|
- type: recall_at_1 |
|
value: 34.699999999999996 |
|
- type: recall_at_10 |
|
value: 67.002 |
|
- type: recall_at_100 |
|
value: 82.113 |
|
- type: recall_at_1000 |
|
value: 91.945 |
|
- type: recall_at_3 |
|
value: 55.827000000000005 |
|
- type: recall_at_5 |
|
value: 61.195 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/imdb |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 90.40480000000001 |
|
- type: ap |
|
value: 86.34472513785936 |
|
- type: f1 |
|
value: 90.3766943422773 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: msmarco |
|
name: MTEB MSMARCO |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 19.796 |
|
- type: map_at_10 |
|
value: 31.344 |
|
- type: map_at_100 |
|
value: 32.525999999999996 |
|
- type: map_at_1000 |
|
value: 32.582 |
|
- type: map_at_3 |
|
value: 27.514 |
|
- type: map_at_5 |
|
value: 29.683 |
|
- type: mrr_at_1 |
|
value: 20.358 |
|
- type: mrr_at_10 |
|
value: 31.924999999999997 |
|
- type: mrr_at_100 |
|
value: 33.056000000000004 |
|
- type: mrr_at_1000 |
|
value: 33.105000000000004 |
|
- type: mrr_at_3 |
|
value: 28.149 |
|
- type: mrr_at_5 |
|
value: 30.303 |
|
- type: ndcg_at_1 |
|
value: 20.372 |
|
- type: ndcg_at_10 |
|
value: 38.025999999999996 |
|
- type: ndcg_at_100 |
|
value: 43.813 |
|
- type: ndcg_at_1000 |
|
value: 45.21 |
|
- type: ndcg_at_3 |
|
value: 30.218 |
|
- type: ndcg_at_5 |
|
value: 34.088 |
|
- type: precision_at_1 |
|
value: 20.372 |
|
- type: precision_at_10 |
|
value: 6.123 |
|
- type: precision_at_100 |
|
value: 0.903 |
|
- type: precision_at_1000 |
|
value: 0.10200000000000001 |
|
- type: precision_at_3 |
|
value: 12.918 |
|
- type: precision_at_5 |
|
value: 9.702 |
|
- type: recall_at_1 |
|
value: 19.796 |
|
- type: recall_at_10 |
|
value: 58.644 |
|
- type: recall_at_100 |
|
value: 85.611 |
|
- type: recall_at_1000 |
|
value: 96.314 |
|
- type: recall_at_3 |
|
value: 37.419999999999995 |
|
- type: recall_at_5 |
|
value: 46.697 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 93.0984952120383 |
|
- type: f1 |
|
value: 92.9409029889071 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 73.24441404468764 |
|
- type: f1 |
|
value: 54.66568676132254 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 73.86684599865501 |
|
- type: f1 |
|
value: 72.16086061041996 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 78.16745124411568 |
|
- type: f1 |
|
value: 78.76361933295068 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-p2p |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 33.66329421728342 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-s2s |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 32.21637418682758 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/mind_small |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 31.85308363141191 |
|
- type: mrr |
|
value: 33.06713899953772 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nfcorpus |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.392 |
|
- type: map_at_10 |
|
value: 14.539 |
|
- type: map_at_100 |
|
value: 18.811 |
|
- type: map_at_1000 |
|
value: 20.471 |
|
- type: map_at_3 |
|
value: 10.26 |
|
- type: map_at_5 |
|
value: 12.224 |
|
- type: mrr_at_1 |
|
value: 46.749 |
|
- type: mrr_at_10 |
|
value: 55.72200000000001 |
|
- type: mrr_at_100 |
|
value: 56.325 |
|
- type: mrr_at_1000 |
|
value: 56.35 |
|
- type: mrr_at_3 |
|
value: 53.30200000000001 |
|
- type: mrr_at_5 |
|
value: 54.742000000000004 |
|
- type: ndcg_at_1 |
|
value: 44.891999999999996 |
|
- type: ndcg_at_10 |
|
value: 37.355 |
|
- type: ndcg_at_100 |
|
value: 35.285 |
|
- type: ndcg_at_1000 |
|
value: 44.246 |
|
- type: ndcg_at_3 |
|
value: 41.291 |
|
- type: ndcg_at_5 |
|
value: 39.952 |
|
- type: precision_at_1 |
|
value: 46.749 |
|
- type: precision_at_10 |
|
value: 28.111000000000004 |
|
- type: precision_at_100 |
|
value: 9.127 |
|
- type: precision_at_1000 |
|
value: 2.23 |
|
- type: precision_at_3 |
|
value: 38.803 |
|
- type: precision_at_5 |
|
value: 35.046 |
|
- type: recall_at_1 |
|
value: 6.392 |
|
- type: recall_at_10 |
|
value: 19.066 |
|
- type: recall_at_100 |
|
value: 37.105 |
|
- type: recall_at_1000 |
|
value: 69.37299999999999 |
|
- type: recall_at_3 |
|
value: 11.213 |
|
- type: recall_at_5 |
|
value: 14.648 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nq |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 31.387999999999998 |
|
- type: map_at_10 |
|
value: 47.172 |
|
- type: map_at_100 |
|
value: 48.158 |
|
- type: map_at_1000 |
|
value: 48.186 |
|
- type: map_at_3 |
|
value: 42.952 |
|
- type: map_at_5 |
|
value: 45.405 |
|
- type: mrr_at_1 |
|
value: 35.458 |
|
- type: mrr_at_10 |
|
value: 49.583 |
|
- type: mrr_at_100 |
|
value: 50.324999999999996 |
|
- type: mrr_at_1000 |
|
value: 50.344 |
|
- type: mrr_at_3 |
|
value: 46.195 |
|
- type: mrr_at_5 |
|
value: 48.258 |
|
- type: ndcg_at_1 |
|
value: 35.458 |
|
- type: ndcg_at_10 |
|
value: 54.839000000000006 |
|
- type: ndcg_at_100 |
|
value: 58.974000000000004 |
|
- type: ndcg_at_1000 |
|
value: 59.64699999999999 |
|
- type: ndcg_at_3 |
|
value: 47.012 |
|
- type: ndcg_at_5 |
|
value: 51.080999999999996 |
|
- type: precision_at_1 |
|
value: 35.458 |
|
- type: precision_at_10 |
|
value: 9.056000000000001 |
|
- type: precision_at_100 |
|
value: 1.137 |
|
- type: precision_at_1000 |
|
value: 0.12 |
|
- type: precision_at_3 |
|
value: 21.582 |
|
- type: precision_at_5 |
|
value: 15.295 |
|
- type: recall_at_1 |
|
value: 31.387999999999998 |
|
- type: recall_at_10 |
|
value: 75.661 |
|
- type: recall_at_100 |
|
value: 93.605 |
|
- type: recall_at_1000 |
|
value: 98.658 |
|
- type: recall_at_3 |
|
value: 55.492 |
|
- type: recall_at_5 |
|
value: 64.85600000000001 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: quora |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 70.547 |
|
- type: map_at_10 |
|
value: 84.495 |
|
- type: map_at_100 |
|
value: 85.14 |
|
- type: map_at_1000 |
|
value: 85.15599999999999 |
|
- type: map_at_3 |
|
value: 81.606 |
|
- type: map_at_5 |
|
value: 83.449 |
|
- type: mrr_at_1 |
|
value: 81.22 |
|
- type: mrr_at_10 |
|
value: 87.31 |
|
- type: mrr_at_100 |
|
value: 87.436 |
|
- type: mrr_at_1000 |
|
value: 87.437 |
|
- type: mrr_at_3 |
|
value: 86.363 |
|
- type: mrr_at_5 |
|
value: 87.06 |
|
- type: ndcg_at_1 |
|
value: 81.24 |
|
- type: ndcg_at_10 |
|
value: 88.145 |
|
- type: ndcg_at_100 |
|
value: 89.423 |
|
- type: ndcg_at_1000 |
|
value: 89.52799999999999 |
|
- type: ndcg_at_3 |
|
value: 85.435 |
|
- type: ndcg_at_5 |
|
value: 87 |
|
- type: precision_at_1 |
|
value: 81.24 |
|
- type: precision_at_10 |
|
value: 13.381000000000002 |
|
- type: precision_at_100 |
|
value: 1.529 |
|
- type: precision_at_1000 |
|
value: 0.157 |
|
- type: precision_at_3 |
|
value: 37.44 |
|
- type: precision_at_5 |
|
value: 24.62 |
|
- type: recall_at_1 |
|
value: 70.547 |
|
- type: recall_at_10 |
|
value: 95.083 |
|
- type: recall_at_100 |
|
value: 99.50099999999999 |
|
- type: recall_at_1000 |
|
value: 99.982 |
|
- type: recall_at_3 |
|
value: 87.235 |
|
- type: recall_at_5 |
|
value: 91.701 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 57.93101384071724 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering-p2p |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 62.46951126228829 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scidocs |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.018000000000001 |
|
- type: map_at_10 |
|
value: 13.818 |
|
- type: map_at_100 |
|
value: 16.346 |
|
- type: map_at_1000 |
|
value: 16.744999999999997 |
|
- type: map_at_3 |
|
value: 9.456000000000001 |
|
- type: map_at_5 |
|
value: 11.879000000000001 |
|
- type: mrr_at_1 |
|
value: 24.8 |
|
- type: mrr_at_10 |
|
value: 37.092000000000006 |
|
- type: mrr_at_100 |
|
value: 38.199 |
|
- type: mrr_at_1000 |
|
value: 38.243 |
|
- type: mrr_at_3 |
|
value: 33.517 |
|
- type: mrr_at_5 |
|
value: 35.692 |
|
- type: ndcg_at_1 |
|
value: 24.8 |
|
- type: ndcg_at_10 |
|
value: 22.782 |
|
- type: ndcg_at_100 |
|
value: 32.072 |
|
- type: ndcg_at_1000 |
|
value: 38.163000000000004 |
|
- type: ndcg_at_3 |
|
value: 21.046 |
|
- type: ndcg_at_5 |
|
value: 19.134 |
|
- type: precision_at_1 |
|
value: 24.8 |
|
- type: precision_at_10 |
|
value: 12 |
|
- type: precision_at_100 |
|
value: 2.5420000000000003 |
|
- type: precision_at_1000 |
|
value: 0.39899999999999997 |
|
- type: precision_at_3 |
|
value: 20 |
|
- type: precision_at_5 |
|
value: 17.4 |
|
- type: recall_at_1 |
|
value: 5.018000000000001 |
|
- type: recall_at_10 |
|
value: 24.34 |
|
- type: recall_at_100 |
|
value: 51.613 |
|
- type: recall_at_1000 |
|
value: 80.95 |
|
- type: recall_at_3 |
|
value: 12.153 |
|
- type: recall_at_5 |
|
value: 17.648 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sickr-sts |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.28259142800503 |
|
- type: cos_sim_spearman |
|
value: 82.04792579356291 |
|
- type: euclidean_pearson |
|
value: 83.7755858026306 |
|
- type: euclidean_spearman |
|
value: 82.04789872846196 |
|
- type: manhattan_pearson |
|
value: 83.79937122515567 |
|
- type: manhattan_spearman |
|
value: 82.05076966288574 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts12-sts |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.37773414195387 |
|
- type: cos_sim_spearman |
|
value: 78.76929696642694 |
|
- type: euclidean_pearson |
|
value: 85.75861298616339 |
|
- type: euclidean_spearman |
|
value: 78.76607739031363 |
|
- type: manhattan_pearson |
|
value: 85.74412868736295 |
|
- type: manhattan_spearman |
|
value: 78.74388526796852 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts13-sts |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 89.6176449076649 |
|
- type: cos_sim_spearman |
|
value: 90.39810997063387 |
|
- type: euclidean_pearson |
|
value: 89.753863994154 |
|
- type: euclidean_spearman |
|
value: 90.39810989027997 |
|
- type: manhattan_pearson |
|
value: 89.67750819879801 |
|
- type: manhattan_spearman |
|
value: 90.3286558059104 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts14-sts |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.7488246203373 |
|
- type: cos_sim_spearman |
|
value: 85.44794976383963 |
|
- type: euclidean_pearson |
|
value: 87.33205836313964 |
|
- type: euclidean_spearman |
|
value: 85.44793954377185 |
|
- type: manhattan_pearson |
|
value: 87.30760291906203 |
|
- type: manhattan_spearman |
|
value: 85.4308413187653 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts15-sts |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 88.6937750952719 |
|
- type: cos_sim_spearman |
|
value: 90.01162604967037 |
|
- type: euclidean_pearson |
|
value: 89.35321306629116 |
|
- type: euclidean_spearman |
|
value: 90.01161406477627 |
|
- type: manhattan_pearson |
|
value: 89.31351907042307 |
|
- type: manhattan_spearman |
|
value: 89.97264644642166 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts16-sts |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 85.49107564294891 |
|
- type: cos_sim_spearman |
|
value: 87.42092493144571 |
|
- type: euclidean_pearson |
|
value: 86.88112016705634 |
|
- type: euclidean_spearman |
|
value: 87.42092430260175 |
|
- type: manhattan_pearson |
|
value: 86.85846210123235 |
|
- type: manhattan_spearman |
|
value: 87.40059575522972 |
|
- 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: 88.71766466521638 |
|
- type: cos_sim_spearman |
|
value: 88.80244555668372 |
|
- type: euclidean_pearson |
|
value: 89.59428700746064 |
|
- type: euclidean_spearman |
|
value: 88.80244555668372 |
|
- type: manhattan_pearson |
|
value: 89.62272396580352 |
|
- type: manhattan_spearman |
|
value: 88.77584531534937 |
|
- 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: 67.7743776239708 |
|
- type: cos_sim_spearman |
|
value: 68.79768249749681 |
|
- type: euclidean_pearson |
|
value: 70.16430919697441 |
|
- type: euclidean_spearman |
|
value: 68.79768249749681 |
|
- type: manhattan_pearson |
|
value: 70.17205038967042 |
|
- type: manhattan_spearman |
|
value: 68.89740094589914 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsbenchmark-sts |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.9087137484716 |
|
- type: cos_sim_spearman |
|
value: 89.19783009521629 |
|
- type: euclidean_pearson |
|
value: 88.89888500166009 |
|
- type: euclidean_spearman |
|
value: 89.19783009521629 |
|
- type: manhattan_pearson |
|
value: 88.88400033783687 |
|
- type: manhattan_spearman |
|
value: 89.16299162200889 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/scidocs-reranking |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 86.9799916253683 |
|
- type: mrr |
|
value: 96.0708200659181 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scifact |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 59.928000000000004 |
|
- type: map_at_10 |
|
value: 69.56400000000001 |
|
- type: map_at_100 |
|
value: 70.125 |
|
- type: map_at_1000 |
|
value: 70.148 |
|
- type: map_at_3 |
|
value: 66.774 |
|
- type: map_at_5 |
|
value: 68.267 |
|
- type: mrr_at_1 |
|
value: 62.666999999999994 |
|
- type: mrr_at_10 |
|
value: 70.448 |
|
- type: mrr_at_100 |
|
value: 70.94 |
|
- type: mrr_at_1000 |
|
value: 70.962 |
|
- type: mrr_at_3 |
|
value: 68.389 |
|
- type: mrr_at_5 |
|
value: 69.65599999999999 |
|
- type: ndcg_at_1 |
|
value: 62.666999999999994 |
|
- type: ndcg_at_10 |
|
value: 74.117 |
|
- type: ndcg_at_100 |
|
value: 76.248 |
|
- type: ndcg_at_1000 |
|
value: 76.768 |
|
- type: ndcg_at_3 |
|
value: 69.358 |
|
- type: ndcg_at_5 |
|
value: 71.574 |
|
- type: precision_at_1 |
|
value: 62.666999999999994 |
|
- type: precision_at_10 |
|
value: 9.933 |
|
- type: precision_at_100 |
|
value: 1.09 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 27.222 |
|
- type: precision_at_5 |
|
value: 17.867 |
|
- type: recall_at_1 |
|
value: 59.928000000000004 |
|
- type: recall_at_10 |
|
value: 87.156 |
|
- type: recall_at_100 |
|
value: 96.167 |
|
- type: recall_at_1000 |
|
value: 100 |
|
- type: recall_at_3 |
|
value: 74.117 |
|
- type: recall_at_5 |
|
value: 79.80000000000001 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.83762376237624 |
|
- type: cos_sim_ap |
|
value: 96.05077689253707 |
|
- type: cos_sim_f1 |
|
value: 91.75879396984925 |
|
- type: cos_sim_precision |
|
value: 92.22222222222223 |
|
- type: cos_sim_recall |
|
value: 91.3 |
|
- type: dot_accuracy |
|
value: 99.83762376237624 |
|
- type: dot_ap |
|
value: 96.05082513542375 |
|
- type: dot_f1 |
|
value: 91.75879396984925 |
|
- type: dot_precision |
|
value: 92.22222222222223 |
|
- type: dot_recall |
|
value: 91.3 |
|
- type: euclidean_accuracy |
|
value: 99.83762376237624 |
|
- type: euclidean_ap |
|
value: 96.05077689253707 |
|
- type: euclidean_f1 |
|
value: 91.75879396984925 |
|
- type: euclidean_precision |
|
value: 92.22222222222223 |
|
- type: euclidean_recall |
|
value: 91.3 |
|
- type: manhattan_accuracy |
|
value: 99.83861386138614 |
|
- type: manhattan_ap |
|
value: 96.07646831090695 |
|
- type: manhattan_f1 |
|
value: 91.86220668996505 |
|
- type: manhattan_precision |
|
value: 91.72482552342971 |
|
- type: manhattan_recall |
|
value: 92 |
|
- type: max_accuracy |
|
value: 99.83861386138614 |
|
- type: max_ap |
|
value: 96.07646831090695 |
|
- type: max_f1 |
|
value: 91.86220668996505 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 66.40672513062134 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering-p2p |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 35.31519237029376 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/stackoverflowdupquestions-reranking |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 53.15764586446943 |
|
- type: mrr |
|
value: 53.981596426449364 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: mteb/summeval |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 30.92935724124931 |
|
- type: cos_sim_spearman |
|
value: 31.54589922149803 |
|
- type: dot_pearson |
|
value: 30.929365687857675 |
|
- type: dot_spearman |
|
value: 31.54589922149803 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: trec-covid |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.22100000000000003 |
|
- type: map_at_10 |
|
value: 1.791 |
|
- type: map_at_100 |
|
value: 9.404 |
|
- type: map_at_1000 |
|
value: 22.932 |
|
- type: map_at_3 |
|
value: 0.601 |
|
- type: map_at_5 |
|
value: 1.001 |
|
- type: mrr_at_1 |
|
value: 76 |
|
- type: mrr_at_10 |
|
value: 85.667 |
|
- type: mrr_at_100 |
|
value: 85.667 |
|
- type: mrr_at_1000 |
|
value: 85.667 |
|
- type: mrr_at_3 |
|
value: 84.667 |
|
- type: mrr_at_5 |
|
value: 85.667 |
|
- type: ndcg_at_1 |
|
value: 72 |
|
- type: ndcg_at_10 |
|
value: 68.637 |
|
- type: ndcg_at_100 |
|
value: 51.418 |
|
- type: ndcg_at_1000 |
|
value: 47.75 |
|
- type: ndcg_at_3 |
|
value: 70.765 |
|
- type: ndcg_at_5 |
|
value: 71.808 |
|
- type: precision_at_1 |
|
value: 76 |
|
- type: precision_at_10 |
|
value: 73.8 |
|
- type: precision_at_100 |
|
value: 52.68000000000001 |
|
- type: precision_at_1000 |
|
value: 20.9 |
|
- type: precision_at_3 |
|
value: 74.667 |
|
- type: precision_at_5 |
|
value: 78 |
|
- type: recall_at_1 |
|
value: 0.22100000000000003 |
|
- type: recall_at_10 |
|
value: 2.027 |
|
- type: recall_at_100 |
|
value: 12.831000000000001 |
|
- type: recall_at_1000 |
|
value: 44.996 |
|
- type: recall_at_3 |
|
value: 0.635 |
|
- type: recall_at_5 |
|
value: 1.097 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: webis-touche2020 |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.289 |
|
- type: map_at_10 |
|
value: 10.475 |
|
- type: map_at_100 |
|
value: 16.993 |
|
- type: map_at_1000 |
|
value: 18.598 |
|
- type: map_at_3 |
|
value: 5.891 |
|
- type: map_at_5 |
|
value: 7.678999999999999 |
|
- type: mrr_at_1 |
|
value: 32.653 |
|
- type: mrr_at_10 |
|
value: 49.475 |
|
- type: mrr_at_100 |
|
value: 50.483 |
|
- type: mrr_at_1000 |
|
value: 50.499 |
|
- type: mrr_at_3 |
|
value: 45.918 |
|
- type: mrr_at_5 |
|
value: 48.469 |
|
- type: ndcg_at_1 |
|
value: 29.592000000000002 |
|
- type: ndcg_at_10 |
|
value: 25.891 |
|
- type: ndcg_at_100 |
|
value: 38.106 |
|
- type: ndcg_at_1000 |
|
value: 49.873 |
|
- type: ndcg_at_3 |
|
value: 29.915999999999997 |
|
- type: ndcg_at_5 |
|
value: 27.982000000000003 |
|
- type: precision_at_1 |
|
value: 32.653 |
|
- type: precision_at_10 |
|
value: 22.448999999999998 |
|
- type: precision_at_100 |
|
value: 7.837 |
|
- type: precision_at_1000 |
|
value: 1.5730000000000002 |
|
- type: precision_at_3 |
|
value: 31.293 |
|
- type: precision_at_5 |
|
value: 27.755000000000003 |
|
- type: recall_at_1 |
|
value: 2.289 |
|
- type: recall_at_10 |
|
value: 16.594 |
|
- type: recall_at_100 |
|
value: 48.619 |
|
- type: recall_at_1000 |
|
value: 85.467 |
|
- type: recall_at_3 |
|
value: 7.144 |
|
- type: recall_at_5 |
|
value: 10.465 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/toxic_conversations_50k |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 71.5268 |
|
- type: ap |
|
value: 14.763212211567907 |
|
- type: f1 |
|
value: 55.200562727472736 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/tweet_sentiment_extraction |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 59.25297113752123 |
|
- type: f1 |
|
value: 59.55315247947331 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/twentynewsgroups-clustering |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 51.47685515092062 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twittersemeval2015-pairclassification |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 86.73183525064076 |
|
- type: cos_sim_ap |
|
value: 76.08498196190112 |
|
- type: cos_sim_f1 |
|
value: 69.4834471209584 |
|
- type: cos_sim_precision |
|
value: 67.88321167883211 |
|
- type: cos_sim_recall |
|
value: 71.16094986807387 |
|
- type: dot_accuracy |
|
value: 86.73183525064076 |
|
- type: dot_ap |
|
value: 76.08503499590553 |
|
- type: dot_f1 |
|
value: 69.4834471209584 |
|
- type: dot_precision |
|
value: 67.88321167883211 |
|
- type: dot_recall |
|
value: 71.16094986807387 |
|
- type: euclidean_accuracy |
|
value: 86.73183525064076 |
|
- type: euclidean_ap |
|
value: 76.08500172594562 |
|
- type: euclidean_f1 |
|
value: 69.4834471209584 |
|
- type: euclidean_precision |
|
value: 67.88321167883211 |
|
- type: euclidean_recall |
|
value: 71.16094986807387 |
|
- type: manhattan_accuracy |
|
value: 86.6960720033379 |
|
- type: manhattan_ap |
|
value: 76.00885156192993 |
|
- type: manhattan_f1 |
|
value: 69.24488725747247 |
|
- type: manhattan_precision |
|
value: 68.8118811881188 |
|
- type: manhattan_recall |
|
value: 69.68337730870712 |
|
- type: max_accuracy |
|
value: 86.73183525064076 |
|
- type: max_ap |
|
value: 76.08503499590553 |
|
- type: max_f1 |
|
value: 69.4834471209584 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twitterurlcorpus-pairclassification |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.74529436876625 |
|
- type: cos_sim_ap |
|
value: 85.53503158777171 |
|
- type: cos_sim_f1 |
|
value: 77.68167368965773 |
|
- type: cos_sim_precision |
|
value: 74.70496232048912 |
|
- type: cos_sim_recall |
|
value: 80.9054511857099 |
|
- type: dot_accuracy |
|
value: 88.74529436876625 |
|
- type: dot_ap |
|
value: 85.5350158446314 |
|
- type: dot_f1 |
|
value: 77.68167368965773 |
|
- type: dot_precision |
|
value: 74.70496232048912 |
|
- type: dot_recall |
|
value: 80.9054511857099 |
|
- type: euclidean_accuracy |
|
value: 88.74529436876625 |
|
- type: euclidean_ap |
|
value: 85.53503846009764 |
|
- type: euclidean_f1 |
|
value: 77.68167368965773 |
|
- type: euclidean_precision |
|
value: 74.70496232048912 |
|
- type: euclidean_recall |
|
value: 80.9054511857099 |
|
- type: manhattan_accuracy |
|
value: 88.73753250281368 |
|
- type: manhattan_ap |
|
value: 85.53197689629393 |
|
- type: manhattan_f1 |
|
value: 77.58753437213566 |
|
- type: manhattan_precision |
|
value: 74.06033456988871 |
|
- type: manhattan_recall |
|
value: 81.46750846935633 |
|
- type: max_accuracy |
|
value: 88.74529436876625 |
|
- type: max_ap |
|
value: 85.53503846009764 |
|
- type: max_f1 |
|
value: 77.68167368965773 |
|
license: apache-2.0 |
|
language: |
|
- en |
|
library_name: sentence-transformers |
|
--- |
|
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|
<br><br> |
|
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|
<p align="center"> |
|
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</p> |
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<p align="center"> |
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<b>The crispy sentence embedding family from <a href="https://mixedbread.ai"><b>mixedbread ai</b></a>.</b> |
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</p> |
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# 🪆mxbai-embed-2d-large-v1🪆 |
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This is our [2DMSE](https://arxiv.org/abs/2402.14776) sentence embedding model. It supports the adaptive transformer layer and embedding size. Find out more in our [blog post](https://mixedbread.ai/blog/mxbai-embed-2d-large-v1). |
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TLDR: TLDR: 2D-🪆 allows you to shrink the model and the embeddings layer. Shrinking only the embeddings model yields competetive results to other models like [nomics embeddings model](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5). Shrinking the model to ~50% maintains upto 85% of the performance without further training. |
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## Quickstart |
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Here, we provide several ways to produce sentence embeddings with adaptive layers and embedding sizes. **For this version, it is recommended to set adaptive layers from 20 to 24.** |
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### sentence-transformers |
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Currently, the best way to use our models is with the most recent version of sentence-transformers. |
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```bash |
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python -m pip install -U sentence-transformers |
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``` |
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```python |
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from sentence_transformers import models, SentenceTransformer |
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from sentence_transformers.util import cos_sim |
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# 1. load model with `cls` pooling |
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model = SentenceTransformer("mixedbread-ai/mxbai-embed-2d-large-v1") |
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# 2. set adaptive layer and embedding size. |
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# it is recommended to set layers from 20 to 24. |
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new_num_layers = 22 # 1D: set layer size |
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model[0].auto_model.encoder.layer = model[0].auto_model.encoder.layer[:new_num_layers] |
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new_embedding_size = 768 # 2D: set embedding size |
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# 3. encode |
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embeddings = model.encode( |
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[ |
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'Who is german and likes bread?', |
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'Everybody in Germany.' |
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] |
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) |
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# Similarity of the first sentence with the other two |
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similarities = cos_sim(embeddings[0, :new_embedding_size], embeddings[1, :new_embedding_size]) |
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print('similarities:', similarities) |
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``` |
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### angle-emb |
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You can also use the lastest `angle-emb` for inference, as follows: |
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```bash |
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python -m pip install -U angle-emb |
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``` |
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```python |
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from angle_emb import AnglE |
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from sentence_transformers.util import cos_sim |
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# 1. load model |
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model = AnglE.from_pretrained("mixedbread-ai/mxbai-embed-2d-large-v1", pooling_strategy='cls').cuda() |
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# 2. set adaptive layer and embedding size. |
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# it is recommended to set layers from 20 to 24. |
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layer_index = 22 # 1d: layer |
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embedding_size = 768 # 2d: embedding size |
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# 3. encode |
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embeddings = model.encode([ |
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'Who is german and likes bread?', |
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'Everybody in Germany.' |
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], layer_index=layer_index, embedding_size=embedding_size) |
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similarities = cos_sim(embeddings[0], embeddings[1:]) |
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print('similarities:', similarities) |
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``` |
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### Transformers.js |
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If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@xenova/transformers) using: |
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```bash |
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npm i @xenova/transformers |
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``` |
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You can then use the model to compute embeddings as follows: |
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```js |
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import { pipeline, cos_sim } from '@xenova/transformers'; |
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// Create a feature-extraction pipeline |
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const extractor = await pipeline('feature-extraction', 'mixedbread-ai/mxbai-embed-2d-large-v1', { |
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quantized: false, // (Optional) remove this line to use the 8-bit quantized model |
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}); |
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// Compute sentence embeddings (with `cls` pooling) |
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const sentences = ['Who is german and likes bread?', 'Everybody in Germany.' ]; |
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const output = await extractor(sentences, { pooling: 'cls' }); |
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// Set embedding size and truncate embeddings |
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const new_embedding_size = 768; |
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const truncated = output.slice(null, [0, new_embedding_size]); |
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// Compute cosine similarity |
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console.log(cos_sim(truncated[0].data, truncated[1].data)); // 0.6979532021425204 |
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``` |
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### Using API |
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You can use the model via our API as follows: |
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```python |
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from mixedbread_ai.client import MixedbreadAI |
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from sklearn.metrics.pairwise import cosine_similarity |
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import os |
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mxbai = MixedbreadAI(api_key="{MIXEDBREAD_API_KEY}") |
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english_sentences = [ |
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'What is the capital of Australia?', |
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'Canberra is the capital of Australia.' |
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] |
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res = mxbai.embeddings( |
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input=english_sentences, |
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model="mixedbread-ai/mxbai-embed-2d-large-v1", |
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dimensions=512, |
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) |
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embeddings = [entry.embedding for entry in res.data] |
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similarities = cosine_similarity([embeddings[0]], [embeddings[1]]) |
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print(similarities) |
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``` |
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The API comes with native INT8 and binary quantization support! Check out the [docs](https://mixedbread.ai/docs) for more information. |
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## Evaluation |
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Please find more information in our [blog post](https://mixedbread.ai/blog/mxbai-embed-2d-large-v1). |
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## Community |
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Please join our [Discord Community](https://discord.gg/jDfMHzAVfU) and share your feedback and thoughts! We are here to help and also always happy to chat. |
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## License |
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Apache 2.0 |
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