|
--- |
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tags: |
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- mteb |
|
- sparse |
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- sparsity |
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- quantized |
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- onnx |
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- embeddings |
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- int8 |
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- deepsparse |
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model-index: |
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- name: bge-small-en-v1.5-quant |
|
results: |
|
- 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 |
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metrics: |
|
- type: accuracy |
|
value: 74.19402985074626 |
|
- type: ap |
|
value: 37.562368912364036 |
|
- type: f1 |
|
value: 68.47046663470138 |
|
- 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: 91.89432499999998 |
|
- type: ap |
|
value: 88.64572979375352 |
|
- type: f1 |
|
value: 91.87171177424113 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
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split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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metrics: |
|
- type: accuracy |
|
value: 46.71799999999999 |
|
- type: f1 |
|
value: 46.25791412217894 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: arguana |
|
name: MTEB ArguAna |
|
config: default |
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split: test |
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revision: None |
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metrics: |
|
- type: map_at_1 |
|
value: 34.424 |
|
- type: map_at_10 |
|
value: 49.63 |
|
- type: map_at_100 |
|
value: 50.477000000000004 |
|
- type: map_at_1000 |
|
value: 50.483 |
|
- type: map_at_3 |
|
value: 45.389 |
|
- type: map_at_5 |
|
value: 47.888999999999996 |
|
- type: mrr_at_1 |
|
value: 34.78 |
|
- type: mrr_at_10 |
|
value: 49.793 |
|
- type: mrr_at_100 |
|
value: 50.632999999999996 |
|
- type: mrr_at_1000 |
|
value: 50.638000000000005 |
|
- type: mrr_at_3 |
|
value: 45.531 |
|
- type: mrr_at_5 |
|
value: 48.010000000000005 |
|
- type: ndcg_at_1 |
|
value: 34.424 |
|
- type: ndcg_at_10 |
|
value: 57.774 |
|
- type: ndcg_at_100 |
|
value: 61.248000000000005 |
|
- type: ndcg_at_1000 |
|
value: 61.378 |
|
- type: ndcg_at_3 |
|
value: 49.067 |
|
- type: ndcg_at_5 |
|
value: 53.561 |
|
- type: precision_at_1 |
|
value: 34.424 |
|
- type: precision_at_10 |
|
value: 8.364 |
|
- type: precision_at_100 |
|
value: 0.985 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 19.915 |
|
- type: precision_at_5 |
|
value: 14.124999999999998 |
|
- type: recall_at_1 |
|
value: 34.424 |
|
- type: recall_at_10 |
|
value: 83.64200000000001 |
|
- type: recall_at_100 |
|
value: 98.506 |
|
- type: recall_at_1000 |
|
value: 99.502 |
|
- type: recall_at_3 |
|
value: 59.744 |
|
- type: recall_at_5 |
|
value: 70.626 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-p2p |
|
name: MTEB ArxivClusteringP2P |
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config: default |
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split: test |
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 46.91874634333147 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-s2s |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
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split: test |
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 39.1201020016146 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/askubuntudupquestions-reranking |
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name: MTEB AskUbuntuDupQuestions |
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config: default |
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split: test |
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
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metrics: |
|
- type: map |
|
value: 62.40334669601722 |
|
- type: mrr |
|
value: 75.33175042870333 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/biosses-sts |
|
name: MTEB BIOSSES |
|
config: default |
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split: test |
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 88.00433892980047 |
|
- type: cos_sim_spearman |
|
value: 86.65558896421105 |
|
- type: euclidean_pearson |
|
value: 85.98927300398377 |
|
- type: euclidean_spearman |
|
value: 86.0905158476729 |
|
- type: manhattan_pearson |
|
value: 86.0272425017433 |
|
- type: manhattan_spearman |
|
value: 85.8929209838941 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/banking77 |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 85.1038961038961 |
|
- type: f1 |
|
value: 85.06851570045757 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-p2p |
|
name: MTEB BiorxivClusteringP2P |
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config: default |
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split: test |
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 37.42637694389153 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-s2s |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 33.89440321125906 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
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name: MTEB CQADupstackAndroidRetrieval |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: map_at_1 |
|
value: 28.111000000000004 |
|
- type: map_at_10 |
|
value: 39.067 |
|
- type: map_at_100 |
|
value: 40.519 |
|
- type: map_at_1000 |
|
value: 40.652 |
|
- type: map_at_3 |
|
value: 35.571999999999996 |
|
- type: map_at_5 |
|
value: 37.708999999999996 |
|
- type: mrr_at_1 |
|
value: 34.335 |
|
- type: mrr_at_10 |
|
value: 44.868 |
|
- type: mrr_at_100 |
|
value: 45.607 |
|
- type: mrr_at_1000 |
|
value: 45.655 |
|
- type: mrr_at_3 |
|
value: 41.798 |
|
- type: mrr_at_5 |
|
value: 43.786 |
|
- type: ndcg_at_1 |
|
value: 34.335 |
|
- type: ndcg_at_10 |
|
value: 45.513 |
|
- type: ndcg_at_100 |
|
value: 51.037 |
|
- type: ndcg_at_1000 |
|
value: 53.171 |
|
- type: ndcg_at_3 |
|
value: 40.131 |
|
- type: ndcg_at_5 |
|
value: 43.027 |
|
- type: precision_at_1 |
|
value: 34.335 |
|
- type: precision_at_10 |
|
value: 8.784 |
|
- type: precision_at_100 |
|
value: 1.4460000000000002 |
|
- type: precision_at_1000 |
|
value: 0.193 |
|
- type: precision_at_3 |
|
value: 19.361 |
|
- type: precision_at_5 |
|
value: 14.249 |
|
- type: recall_at_1 |
|
value: 28.111000000000004 |
|
- type: recall_at_10 |
|
value: 58.372 |
|
- type: recall_at_100 |
|
value: 81.631 |
|
- type: recall_at_1000 |
|
value: 95.192 |
|
- type: recall_at_3 |
|
value: 42.863 |
|
- type: recall_at_5 |
|
value: 50.924 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackEnglishRetrieval |
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config: default |
|
split: test |
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revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 28.437 |
|
- type: map_at_10 |
|
value: 37.942 |
|
- type: map_at_100 |
|
value: 39.108 |
|
- type: map_at_1000 |
|
value: 39.242 |
|
- type: map_at_3 |
|
value: 35.419 |
|
- type: map_at_5 |
|
value: 36.825 |
|
- type: mrr_at_1 |
|
value: 35.35 |
|
- type: mrr_at_10 |
|
value: 43.855 |
|
- type: mrr_at_100 |
|
value: 44.543 |
|
- type: mrr_at_1000 |
|
value: 44.588 |
|
- type: mrr_at_3 |
|
value: 41.826 |
|
- type: mrr_at_5 |
|
value: 42.937 |
|
- type: ndcg_at_1 |
|
value: 35.35 |
|
- type: ndcg_at_10 |
|
value: 43.32 |
|
- type: ndcg_at_100 |
|
value: 47.769 |
|
- type: ndcg_at_1000 |
|
value: 49.979 |
|
- type: ndcg_at_3 |
|
value: 39.709 |
|
- type: ndcg_at_5 |
|
value: 41.316 |
|
- type: precision_at_1 |
|
value: 35.35 |
|
- type: precision_at_10 |
|
value: 7.994 |
|
- type: precision_at_100 |
|
value: 1.323 |
|
- type: precision_at_1000 |
|
value: 0.182 |
|
- type: precision_at_3 |
|
value: 18.96 |
|
- type: precision_at_5 |
|
value: 13.236 |
|
- type: recall_at_1 |
|
value: 28.437 |
|
- type: recall_at_10 |
|
value: 52.531000000000006 |
|
- type: recall_at_100 |
|
value: 71.79299999999999 |
|
- type: recall_at_1000 |
|
value: 85.675 |
|
- type: recall_at_3 |
|
value: 41.605 |
|
- type: recall_at_5 |
|
value: 46.32 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 37.364999999999995 |
|
- type: map_at_10 |
|
value: 49.324 |
|
- type: map_at_100 |
|
value: 50.458999999999996 |
|
- type: map_at_1000 |
|
value: 50.512 |
|
- type: map_at_3 |
|
value: 45.96 |
|
- type: map_at_5 |
|
value: 47.934 |
|
- type: mrr_at_1 |
|
value: 43.009 |
|
- type: mrr_at_10 |
|
value: 52.946000000000005 |
|
- type: mrr_at_100 |
|
value: 53.74100000000001 |
|
- type: mrr_at_1000 |
|
value: 53.76800000000001 |
|
- type: mrr_at_3 |
|
value: 50.554 |
|
- type: mrr_at_5 |
|
value: 51.964 |
|
- type: ndcg_at_1 |
|
value: 43.009 |
|
- type: ndcg_at_10 |
|
value: 55.143 |
|
- type: ndcg_at_100 |
|
value: 59.653999999999996 |
|
- type: ndcg_at_1000 |
|
value: 60.805 |
|
- type: ndcg_at_3 |
|
value: 49.605 |
|
- type: ndcg_at_5 |
|
value: 52.437 |
|
- type: precision_at_1 |
|
value: 43.009 |
|
- type: precision_at_10 |
|
value: 8.984 |
|
- type: precision_at_100 |
|
value: 1.209 |
|
- type: precision_at_1000 |
|
value: 0.135 |
|
- type: precision_at_3 |
|
value: 22.09 |
|
- type: precision_at_5 |
|
value: 15.423 |
|
- type: recall_at_1 |
|
value: 37.364999999999995 |
|
- type: recall_at_10 |
|
value: 68.657 |
|
- type: recall_at_100 |
|
value: 88.155 |
|
- type: recall_at_1000 |
|
value: 96.48400000000001 |
|
- type: recall_at_3 |
|
value: 54.186 |
|
- type: recall_at_5 |
|
value: 60.848 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.827 |
|
- type: map_at_10 |
|
value: 31.721 |
|
- type: map_at_100 |
|
value: 32.812999999999995 |
|
- type: map_at_1000 |
|
value: 32.89 |
|
- type: map_at_3 |
|
value: 29.238999999999997 |
|
- type: map_at_5 |
|
value: 30.584 |
|
- type: mrr_at_1 |
|
value: 25.650000000000002 |
|
- type: mrr_at_10 |
|
value: 33.642 |
|
- type: mrr_at_100 |
|
value: 34.595 |
|
- type: mrr_at_1000 |
|
value: 34.650999999999996 |
|
- type: mrr_at_3 |
|
value: 31.205 |
|
- type: mrr_at_5 |
|
value: 32.499 |
|
- type: ndcg_at_1 |
|
value: 25.650000000000002 |
|
- type: ndcg_at_10 |
|
value: 36.366 |
|
- type: ndcg_at_100 |
|
value: 41.766 |
|
- type: ndcg_at_1000 |
|
value: 43.735 |
|
- type: ndcg_at_3 |
|
value: 31.447000000000003 |
|
- type: ndcg_at_5 |
|
value: 33.701 |
|
- type: precision_at_1 |
|
value: 25.650000000000002 |
|
- type: precision_at_10 |
|
value: 5.582 |
|
- type: precision_at_100 |
|
value: 0.872 |
|
- type: precision_at_1000 |
|
value: 0.108 |
|
- type: precision_at_3 |
|
value: 13.107 |
|
- type: precision_at_5 |
|
value: 9.198 |
|
- type: recall_at_1 |
|
value: 23.827 |
|
- type: recall_at_10 |
|
value: 48.9 |
|
- type: recall_at_100 |
|
value: 73.917 |
|
- type: recall_at_1000 |
|
value: 88.787 |
|
- type: recall_at_3 |
|
value: 35.498000000000005 |
|
- type: recall_at_5 |
|
value: 40.929 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 15.47 |
|
- type: map_at_10 |
|
value: 22.679 |
|
- type: map_at_100 |
|
value: 23.823 |
|
- type: map_at_1000 |
|
value: 23.94 |
|
- type: map_at_3 |
|
value: 20.535999999999998 |
|
- type: map_at_5 |
|
value: 21.61 |
|
- type: mrr_at_1 |
|
value: 18.781 |
|
- type: mrr_at_10 |
|
value: 26.979 |
|
- type: mrr_at_100 |
|
value: 27.945999999999998 |
|
- type: mrr_at_1000 |
|
value: 28.016000000000002 |
|
- type: mrr_at_3 |
|
value: 24.648 |
|
- type: mrr_at_5 |
|
value: 25.947 |
|
- type: ndcg_at_1 |
|
value: 18.781 |
|
- type: ndcg_at_10 |
|
value: 27.55 |
|
- type: ndcg_at_100 |
|
value: 33.176 |
|
- type: ndcg_at_1000 |
|
value: 36.150999999999996 |
|
- type: ndcg_at_3 |
|
value: 23.456 |
|
- type: ndcg_at_5 |
|
value: 25.16 |
|
- type: precision_at_1 |
|
value: 18.781 |
|
- type: precision_at_10 |
|
value: 5.050000000000001 |
|
- type: precision_at_100 |
|
value: 0.9039999999999999 |
|
- type: precision_at_1000 |
|
value: 0.129 |
|
- type: precision_at_3 |
|
value: 11.235000000000001 |
|
- type: precision_at_5 |
|
value: 8.01 |
|
- type: recall_at_1 |
|
value: 15.47 |
|
- type: recall_at_10 |
|
value: 38.446000000000005 |
|
- type: recall_at_100 |
|
value: 63.199000000000005 |
|
- type: recall_at_1000 |
|
value: 84.719 |
|
- type: recall_at_3 |
|
value: 26.687 |
|
- type: recall_at_5 |
|
value: 31.196 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.285999999999998 |
|
- type: map_at_10 |
|
value: 35.701 |
|
- type: map_at_100 |
|
value: 37.062 |
|
- type: map_at_1000 |
|
value: 37.175999999999995 |
|
- type: map_at_3 |
|
value: 32.65 |
|
- type: map_at_5 |
|
value: 34.129 |
|
- type: mrr_at_1 |
|
value: 32.05 |
|
- type: mrr_at_10 |
|
value: 41.105000000000004 |
|
- type: mrr_at_100 |
|
value: 41.996 |
|
- type: mrr_at_1000 |
|
value: 42.047000000000004 |
|
- type: mrr_at_3 |
|
value: 38.466 |
|
- type: mrr_at_5 |
|
value: 39.766 |
|
- type: ndcg_at_1 |
|
value: 32.05 |
|
- type: ndcg_at_10 |
|
value: 41.516999999999996 |
|
- type: ndcg_at_100 |
|
value: 47.083999999999996 |
|
- type: ndcg_at_1000 |
|
value: 49.309 |
|
- type: ndcg_at_3 |
|
value: 36.254999999999995 |
|
- type: ndcg_at_5 |
|
value: 38.346999999999994 |
|
- type: precision_at_1 |
|
value: 32.05 |
|
- type: precision_at_10 |
|
value: 7.536 |
|
- type: precision_at_100 |
|
value: 1.202 |
|
- type: precision_at_1000 |
|
value: 0.158 |
|
- type: precision_at_3 |
|
value: 17.004 |
|
- type: precision_at_5 |
|
value: 11.973 |
|
- type: recall_at_1 |
|
value: 26.285999999999998 |
|
- type: recall_at_10 |
|
value: 53.667 |
|
- type: recall_at_100 |
|
value: 76.97 |
|
- type: recall_at_1000 |
|
value: 91.691 |
|
- type: recall_at_3 |
|
value: 38.571 |
|
- type: recall_at_5 |
|
value: 44.131 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.595000000000002 |
|
- type: map_at_10 |
|
value: 31.352000000000004 |
|
- type: map_at_100 |
|
value: 32.652 |
|
- type: map_at_1000 |
|
value: 32.774 |
|
- type: map_at_3 |
|
value: 28.238000000000003 |
|
- type: map_at_5 |
|
value: 30.178 |
|
- type: mrr_at_1 |
|
value: 27.626 |
|
- type: mrr_at_10 |
|
value: 36.351 |
|
- type: mrr_at_100 |
|
value: 37.297000000000004 |
|
- type: mrr_at_1000 |
|
value: 37.362 |
|
- type: mrr_at_3 |
|
value: 33.885 |
|
- type: mrr_at_5 |
|
value: 35.358000000000004 |
|
- type: ndcg_at_1 |
|
value: 27.626 |
|
- type: ndcg_at_10 |
|
value: 36.795 |
|
- type: ndcg_at_100 |
|
value: 42.808 |
|
- type: ndcg_at_1000 |
|
value: 45.417 |
|
- type: ndcg_at_3 |
|
value: 31.744 |
|
- type: ndcg_at_5 |
|
value: 34.407 |
|
- type: precision_at_1 |
|
value: 27.626 |
|
- type: precision_at_10 |
|
value: 6.781 |
|
- type: precision_at_100 |
|
value: 1.159 |
|
- type: precision_at_1000 |
|
value: 0.155 |
|
- type: precision_at_3 |
|
value: 15.221000000000002 |
|
- type: precision_at_5 |
|
value: 11.279 |
|
- type: recall_at_1 |
|
value: 22.595000000000002 |
|
- type: recall_at_10 |
|
value: 48.126000000000005 |
|
- type: recall_at_100 |
|
value: 74.24300000000001 |
|
- type: recall_at_1000 |
|
value: 92.276 |
|
- type: recall_at_3 |
|
value: 34.346 |
|
- type: recall_at_5 |
|
value: 41.065000000000005 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.237000000000002 |
|
- type: map_at_10 |
|
value: 28.626 |
|
- type: map_at_100 |
|
value: 29.494999999999997 |
|
- type: map_at_1000 |
|
value: 29.587999999999997 |
|
- type: map_at_3 |
|
value: 26.747 |
|
- type: map_at_5 |
|
value: 27.903 |
|
- type: mrr_at_1 |
|
value: 24.847 |
|
- type: mrr_at_10 |
|
value: 31.091 |
|
- type: mrr_at_100 |
|
value: 31.91 |
|
- type: mrr_at_1000 |
|
value: 31.977 |
|
- type: mrr_at_3 |
|
value: 29.218 |
|
- type: mrr_at_5 |
|
value: 30.391000000000002 |
|
- type: ndcg_at_1 |
|
value: 24.847 |
|
- type: ndcg_at_10 |
|
value: 32.452999999999996 |
|
- type: ndcg_at_100 |
|
value: 37.009 |
|
- type: ndcg_at_1000 |
|
value: 39.425 |
|
- type: ndcg_at_3 |
|
value: 28.848000000000003 |
|
- type: ndcg_at_5 |
|
value: 30.752000000000002 |
|
- type: precision_at_1 |
|
value: 24.847 |
|
- type: precision_at_10 |
|
value: 4.968999999999999 |
|
- type: precision_at_100 |
|
value: 0.8009999999999999 |
|
- type: precision_at_1000 |
|
value: 0.107 |
|
- type: precision_at_3 |
|
value: 12.321 |
|
- type: precision_at_5 |
|
value: 8.62 |
|
- type: recall_at_1 |
|
value: 22.237000000000002 |
|
- type: recall_at_10 |
|
value: 41.942 |
|
- type: recall_at_100 |
|
value: 62.907000000000004 |
|
- type: recall_at_1000 |
|
value: 81.035 |
|
- type: recall_at_3 |
|
value: 32.05 |
|
- type: recall_at_5 |
|
value: 36.695 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.835 |
|
- type: map_at_10 |
|
value: 21.124000000000002 |
|
- type: map_at_100 |
|
value: 22.133 |
|
- type: map_at_1000 |
|
value: 22.258 |
|
- type: map_at_3 |
|
value: 19.076999999999998 |
|
- type: map_at_5 |
|
value: 20.18 |
|
- type: mrr_at_1 |
|
value: 17.791 |
|
- type: mrr_at_10 |
|
value: 24.438 |
|
- type: mrr_at_100 |
|
value: 25.332 |
|
- type: mrr_at_1000 |
|
value: 25.417 |
|
- type: mrr_at_3 |
|
value: 22.425 |
|
- type: mrr_at_5 |
|
value: 23.524 |
|
- type: ndcg_at_1 |
|
value: 17.791 |
|
- type: ndcg_at_10 |
|
value: 25.27 |
|
- type: ndcg_at_100 |
|
value: 30.362000000000002 |
|
- type: ndcg_at_1000 |
|
value: 33.494 |
|
- type: ndcg_at_3 |
|
value: 21.474 |
|
- type: ndcg_at_5 |
|
value: 23.189999999999998 |
|
- type: precision_at_1 |
|
value: 17.791 |
|
- type: precision_at_10 |
|
value: 4.58 |
|
- type: precision_at_100 |
|
value: 0.839 |
|
- type: precision_at_1000 |
|
value: 0.128 |
|
- type: precision_at_3 |
|
value: 10.071 |
|
- type: precision_at_5 |
|
value: 7.337000000000001 |
|
- type: recall_at_1 |
|
value: 14.835 |
|
- type: recall_at_10 |
|
value: 34.534 |
|
- type: recall_at_100 |
|
value: 57.812 |
|
- type: recall_at_1000 |
|
value: 80.467 |
|
- type: recall_at_3 |
|
value: 23.938000000000002 |
|
- type: recall_at_5 |
|
value: 28.269 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.400000000000002 |
|
- type: map_at_10 |
|
value: 31.55 |
|
- type: map_at_100 |
|
value: 32.72 |
|
- type: map_at_1000 |
|
value: 32.830999999999996 |
|
- type: map_at_3 |
|
value: 28.942 |
|
- type: map_at_5 |
|
value: 30.403000000000002 |
|
- type: mrr_at_1 |
|
value: 27.705000000000002 |
|
- type: mrr_at_10 |
|
value: 35.778 |
|
- type: mrr_at_100 |
|
value: 36.705 |
|
- type: mrr_at_1000 |
|
value: 36.773 |
|
- type: mrr_at_3 |
|
value: 33.458 |
|
- type: mrr_at_5 |
|
value: 34.778 |
|
- type: ndcg_at_1 |
|
value: 27.705000000000002 |
|
- type: ndcg_at_10 |
|
value: 36.541000000000004 |
|
- type: ndcg_at_100 |
|
value: 42.016999999999996 |
|
- type: ndcg_at_1000 |
|
value: 44.571 |
|
- type: ndcg_at_3 |
|
value: 31.845000000000002 |
|
- type: ndcg_at_5 |
|
value: 34.056 |
|
- type: precision_at_1 |
|
value: 27.705000000000002 |
|
- type: precision_at_10 |
|
value: 6.166 |
|
- type: precision_at_100 |
|
value: 0.993 |
|
- type: precision_at_1000 |
|
value: 0.132 |
|
- type: precision_at_3 |
|
value: 14.302999999999999 |
|
- type: precision_at_5 |
|
value: 10.187 |
|
- type: recall_at_1 |
|
value: 23.400000000000002 |
|
- type: recall_at_10 |
|
value: 47.61 |
|
- type: recall_at_100 |
|
value: 71.69200000000001 |
|
- type: recall_at_1000 |
|
value: 89.652 |
|
- type: recall_at_3 |
|
value: 35.026 |
|
- type: recall_at_5 |
|
value: 40.48 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.409 |
|
- type: map_at_10 |
|
value: 29.642000000000003 |
|
- type: map_at_100 |
|
value: 31.213 |
|
- type: map_at_1000 |
|
value: 31.418000000000003 |
|
- type: map_at_3 |
|
value: 26.811 |
|
- type: map_at_5 |
|
value: 28.433999999999997 |
|
- type: mrr_at_1 |
|
value: 25.494 |
|
- type: mrr_at_10 |
|
value: 33.735 |
|
- type: mrr_at_100 |
|
value: 34.791 |
|
- type: mrr_at_1000 |
|
value: 34.848 |
|
- type: mrr_at_3 |
|
value: 31.225 |
|
- type: mrr_at_5 |
|
value: 32.688 |
|
- type: ndcg_at_1 |
|
value: 25.494 |
|
- type: ndcg_at_10 |
|
value: 35.038000000000004 |
|
- type: ndcg_at_100 |
|
value: 41.499 |
|
- type: ndcg_at_1000 |
|
value: 44.183 |
|
- type: ndcg_at_3 |
|
value: 30.305 |
|
- type: ndcg_at_5 |
|
value: 32.607 |
|
- type: precision_at_1 |
|
value: 25.494 |
|
- type: precision_at_10 |
|
value: 6.739000000000001 |
|
- type: precision_at_100 |
|
value: 1.439 |
|
- type: precision_at_1000 |
|
value: 0.233 |
|
- type: precision_at_3 |
|
value: 14.163 |
|
- type: precision_at_5 |
|
value: 10.474 |
|
- type: recall_at_1 |
|
value: 21.409 |
|
- type: recall_at_10 |
|
value: 46.033 |
|
- type: recall_at_100 |
|
value: 74.932 |
|
- type: recall_at_1000 |
|
value: 92.35600000000001 |
|
- type: recall_at_3 |
|
value: 32.858 |
|
- type: recall_at_5 |
|
value: 38.675 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.145 |
|
- type: map_at_10 |
|
value: 24.712 |
|
- type: map_at_100 |
|
value: 25.813000000000002 |
|
- type: map_at_1000 |
|
value: 25.935000000000002 |
|
- type: map_at_3 |
|
value: 22.33 |
|
- type: map_at_5 |
|
value: 23.524 |
|
- type: mrr_at_1 |
|
value: 19.224 |
|
- type: mrr_at_10 |
|
value: 26.194 |
|
- type: mrr_at_100 |
|
value: 27.208 |
|
- type: mrr_at_1000 |
|
value: 27.3 |
|
- type: mrr_at_3 |
|
value: 23.906 |
|
- type: mrr_at_5 |
|
value: 24.988 |
|
- type: ndcg_at_1 |
|
value: 19.224 |
|
- type: ndcg_at_10 |
|
value: 29.015 |
|
- type: ndcg_at_100 |
|
value: 34.224 |
|
- type: ndcg_at_1000 |
|
value: 37.235 |
|
- type: ndcg_at_3 |
|
value: 24.22 |
|
- type: ndcg_at_5 |
|
value: 26.176 |
|
- type: precision_at_1 |
|
value: 19.224 |
|
- type: precision_at_10 |
|
value: 4.713 |
|
- type: precision_at_100 |
|
value: 0.787 |
|
- type: precision_at_1000 |
|
value: 0.11499999999999999 |
|
- type: precision_at_3 |
|
value: 10.290000000000001 |
|
- type: precision_at_5 |
|
value: 7.32 |
|
- type: recall_at_1 |
|
value: 18.145 |
|
- type: recall_at_10 |
|
value: 40.875 |
|
- type: recall_at_100 |
|
value: 64.371 |
|
- type: recall_at_1000 |
|
value: 86.67399999999999 |
|
- type: recall_at_3 |
|
value: 27.717000000000002 |
|
- type: recall_at_5 |
|
value: 32.381 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/emotion |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 46.845 |
|
- type: f1 |
|
value: 41.70045120106269 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/imdb |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 89.3476 |
|
- type: ap |
|
value: 85.26891728027032 |
|
- type: f1 |
|
value: 89.33488973832894 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 92.67441860465115 |
|
- type: f1 |
|
value: 92.48821366022861 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 74.02872777017784 |
|
- type: f1 |
|
value: 57.28822860484337 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 74.01479488903833 |
|
- type: f1 |
|
value: 71.83716204573571 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 77.95897780766644 |
|
- type: f1 |
|
value: 77.80380046125542 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-p2p |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 31.897956840478948 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-s2s |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 30.71493744677591 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/mind_small |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 31.279419910393734 |
|
- type: mrr |
|
value: 32.41989483774563 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 50.49612915002382 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering-p2p |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 60.29912718965653 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sickr-sts |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.86793477948164 |
|
- type: cos_sim_spearman |
|
value: 79.43675709317894 |
|
- type: euclidean_pearson |
|
value: 81.42564463337872 |
|
- type: euclidean_spearman |
|
value: 79.39138648510273 |
|
- type: manhattan_pearson |
|
value: 81.31167449689285 |
|
- type: manhattan_spearman |
|
value: 79.28411420758785 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts12-sts |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.43490408077298 |
|
- type: cos_sim_spearman |
|
value: 76.16878340109265 |
|
- type: euclidean_pearson |
|
value: 80.6016219080782 |
|
- type: euclidean_spearman |
|
value: 75.67063072565917 |
|
- type: manhattan_pearson |
|
value: 80.7238920179759 |
|
- type: manhattan_spearman |
|
value: 75.85631683403953 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts13-sts |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.03882477767792 |
|
- type: cos_sim_spearman |
|
value: 84.15171505206217 |
|
- type: euclidean_pearson |
|
value: 84.11692506470922 |
|
- type: euclidean_spearman |
|
value: 84.78589046217311 |
|
- type: manhattan_pearson |
|
value: 83.98651139454486 |
|
- type: manhattan_spearman |
|
value: 84.64928563751276 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts14-sts |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.11158600428418 |
|
- type: cos_sim_spearman |
|
value: 81.48561519933875 |
|
- type: euclidean_pearson |
|
value: 83.21025907155807 |
|
- type: euclidean_spearman |
|
value: 81.68699235487654 |
|
- type: manhattan_pearson |
|
value: 83.16704771658094 |
|
- type: manhattan_spearman |
|
value: 81.7133110412898 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts15-sts |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.1514510686502 |
|
- type: cos_sim_spearman |
|
value: 88.11449450494452 |
|
- type: euclidean_pearson |
|
value: 87.75854949349939 |
|
- type: euclidean_spearman |
|
value: 88.4055148221637 |
|
- type: manhattan_pearson |
|
value: 87.71487828059706 |
|
- type: manhattan_spearman |
|
value: 88.35301381116254 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts16-sts |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.36838640113687 |
|
- type: cos_sim_spearman |
|
value: 84.98776974283366 |
|
- type: euclidean_pearson |
|
value: 84.0617526427129 |
|
- type: euclidean_spearman |
|
value: 85.04234805662242 |
|
- type: manhattan_pearson |
|
value: 83.87433162971784 |
|
- type: manhattan_spearman |
|
value: 84.87174280390242 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (en-en) |
|
config: en-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.72465270691285 |
|
- type: cos_sim_spearman |
|
value: 87.97672332532184 |
|
- type: euclidean_pearson |
|
value: 88.78764701492182 |
|
- type: euclidean_spearman |
|
value: 88.3509718074474 |
|
- type: manhattan_pearson |
|
value: 88.73024739256215 |
|
- type: manhattan_spearman |
|
value: 88.24149566970154 |
|
- 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: 64.65195562203238 |
|
- type: cos_sim_spearman |
|
value: 65.0726777678982 |
|
- type: euclidean_pearson |
|
value: 65.84698245675273 |
|
- type: euclidean_spearman |
|
value: 65.13121502162804 |
|
- type: manhattan_pearson |
|
value: 65.96149904857049 |
|
- type: manhattan_spearman |
|
value: 65.39983948112955 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsbenchmark-sts |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 85.2642818050049 |
|
- type: cos_sim_spearman |
|
value: 86.30633382439257 |
|
- type: euclidean_pearson |
|
value: 86.46510435905633 |
|
- type: euclidean_spearman |
|
value: 86.62650496446 |
|
- type: manhattan_pearson |
|
value: 86.2546330637872 |
|
- type: manhattan_spearman |
|
value: 86.46309860938591 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/scidocs-reranking |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 85.009977767778 |
|
- type: mrr |
|
value: 95.59795143128476 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.84257425742574 |
|
- type: cos_sim_ap |
|
value: 96.25445889914926 |
|
- type: cos_sim_f1 |
|
value: 92.03805708562844 |
|
- type: cos_sim_precision |
|
value: 92.1765295887663 |
|
- type: cos_sim_recall |
|
value: 91.9 |
|
- type: dot_accuracy |
|
value: 99.83069306930693 |
|
- type: dot_ap |
|
value: 96.00517778550396 |
|
- type: dot_f1 |
|
value: 91.27995920448751 |
|
- type: dot_precision |
|
value: 93.1321540062435 |
|
- type: dot_recall |
|
value: 89.5 |
|
- type: euclidean_accuracy |
|
value: 99.84455445544555 |
|
- type: euclidean_ap |
|
value: 96.14761524546034 |
|
- type: euclidean_f1 |
|
value: 91.97751660705163 |
|
- type: euclidean_precision |
|
value: 94.04388714733543 |
|
- type: euclidean_recall |
|
value: 90 |
|
- type: manhattan_accuracy |
|
value: 99.84158415841584 |
|
- type: manhattan_ap |
|
value: 96.17014673429341 |
|
- type: manhattan_f1 |
|
value: 91.93790686029043 |
|
- type: manhattan_precision |
|
value: 92.07622868605817 |
|
- type: manhattan_recall |
|
value: 91.8 |
|
- type: max_accuracy |
|
value: 99.84455445544555 |
|
- type: max_ap |
|
value: 96.25445889914926 |
|
- type: max_f1 |
|
value: 92.03805708562844 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 59.26454683321409 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering-p2p |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 33.75520575713765 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/stackoverflowdupquestions-reranking |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 52.74607778008495 |
|
- type: mrr |
|
value: 53.55101699770818 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/toxic_conversations_50k |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 69.5008 |
|
- type: ap |
|
value: 13.64158304183089 |
|
- type: f1 |
|
value: 53.50073331072236 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/tweet_sentiment_extraction |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 60.01980758347483 |
|
- type: f1 |
|
value: 60.35679678249753 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/twentynewsgroups-clustering |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 45.09419243325077 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twittersemeval2015-pairclassification |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 85.68874053764081 |
|
- type: cos_sim_ap |
|
value: 73.26334732095694 |
|
- type: cos_sim_f1 |
|
value: 68.01558376272465 |
|
- type: cos_sim_precision |
|
value: 64.93880489560834 |
|
- type: cos_sim_recall |
|
value: 71.39841688654354 |
|
- type: dot_accuracy |
|
value: 84.71121177802945 |
|
- type: dot_ap |
|
value: 70.33606362522605 |
|
- type: dot_f1 |
|
value: 65.0887573964497 |
|
- type: dot_precision |
|
value: 63.50401606425703 |
|
- type: dot_recall |
|
value: 66.75461741424802 |
|
- type: euclidean_accuracy |
|
value: 85.80795136198367 |
|
- type: euclidean_ap |
|
value: 73.43201285001163 |
|
- type: euclidean_f1 |
|
value: 68.33166833166834 |
|
- type: euclidean_precision |
|
value: 64.86486486486487 |
|
- type: euclidean_recall |
|
value: 72.18997361477572 |
|
- type: manhattan_accuracy |
|
value: 85.62317458425225 |
|
- type: manhattan_ap |
|
value: 73.21212085536185 |
|
- type: manhattan_f1 |
|
value: 68.01681314482232 |
|
- type: manhattan_precision |
|
value: 65.74735286875153 |
|
- type: manhattan_recall |
|
value: 70.44854881266491 |
|
- type: max_accuracy |
|
value: 85.80795136198367 |
|
- type: max_ap |
|
value: 73.43201285001163 |
|
- type: max_f1 |
|
value: 68.33166833166834 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twitterurlcorpus-pairclassification |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.81709162882757 |
|
- type: cos_sim_ap |
|
value: 85.63540257309367 |
|
- type: cos_sim_f1 |
|
value: 77.9091382258904 |
|
- type: cos_sim_precision |
|
value: 75.32710280373833 |
|
- type: cos_sim_recall |
|
value: 80.67446874037573 |
|
- type: dot_accuracy |
|
value: 88.04478596654636 |
|
- type: dot_ap |
|
value: 84.16371725220706 |
|
- type: dot_f1 |
|
value: 76.45949643213666 |
|
- type: dot_precision |
|
value: 73.54719396827655 |
|
- type: dot_recall |
|
value: 79.61194949183862 |
|
- type: euclidean_accuracy |
|
value: 88.9296386851399 |
|
- type: euclidean_ap |
|
value: 85.71894615274715 |
|
- type: euclidean_f1 |
|
value: 78.12952767313823 |
|
- type: euclidean_precision |
|
value: 73.7688098495212 |
|
- type: euclidean_recall |
|
value: 83.03818909762857 |
|
- type: manhattan_accuracy |
|
value: 88.89276982186519 |
|
- type: manhattan_ap |
|
value: 85.6838514059479 |
|
- type: manhattan_f1 |
|
value: 78.06861875184856 |
|
- type: manhattan_precision |
|
value: 75.09246088193457 |
|
- type: manhattan_recall |
|
value: 81.29042192793348 |
|
- type: max_accuracy |
|
value: 88.9296386851399 |
|
- type: max_ap |
|
value: 85.71894615274715 |
|
- type: max_f1 |
|
value: 78.12952767313823 |
|
license: mit |
|
language: |
|
- en |
|
--- |
|
|
|
# bge-small-en-v1.5-quant |
|
|
|
<div> |
|
<img src="https://huggingface.co/zeroshot/bge-small-en-v1.5-quant/resolve/main/latency.png" alt="latency" width="500" style="display:inline-block; margin-right:10px;"/> |
|
</div> |
|
|
|
DeepSparse is able to improve latency performance on a 10 core laptop by 3X and up to 5X on a 16 core AWS instance. |
|
|
|
## Usage |
|
|
|
This is the quantized (INT8) ONNX variant of the [bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) embeddings model accelerated with [Sparsify](https://github.com/neuralmagic/sparsify) for quantization and [DeepSparseSentenceTransformers](https://github.com/neuralmagic/deepsparse/tree/main/src/deepsparse/sentence_transformers) for inference. |
|
|
|
```bash |
|
pip install -U deepsparse-nightly[sentence_transformers] |
|
``` |
|
|
|
```python |
|
from deepsparse.sentence_transformers import DeepSparseSentenceTransformer |
|
model = DeepSparseSentenceTransformer('zeroshot/bge-small-en-v1.5-quant', export=False) |
|
|
|
# Our sentences we like to encode |
|
sentences = ['This framework generates embeddings for each input sentence', |
|
'Sentences are passed as a list of string.', |
|
'The quick brown fox jumps over the lazy dog.'] |
|
|
|
# Sentences are encoded by calling model.encode() |
|
embeddings = model.encode(sentences) |
|
|
|
# Print the embeddings |
|
for sentence, embedding in zip(sentences, embeddings): |
|
print("Sentence:", sentence) |
|
print("Embedding:", embedding.shape) |
|
print("") |
|
``` |
|
|
|
For general questions on these models and sparsification methods, reach out to the engineering team on our [community Slack](https://join.slack.com/t/discuss-neuralmagic/shared_invite/zt-q1a1cnvo-YBoICSIw3L1dmQpjBeDurQ). |
