|
--- |
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tags: |
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- mteb |
|
- sparse sparsity quantized onnx embeddings int8 |
|
model-index: |
|
- name: bge-small-en-v1.5-sparse |
|
results: |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
|
split: test |
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 70.71641791044776 |
|
- type: ap |
|
value: 32.850850647310004 |
|
- type: f1 |
|
value: 64.48101916414805 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_polarity |
|
name: MTEB AmazonPolarityClassification |
|
config: default |
|
split: test |
|
revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 83.33962500000001 |
|
- type: ap |
|
value: 78.28706349240106 |
|
- type: f1 |
|
value: 83.27426715603062 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
|
split: test |
|
revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 40.988 |
|
- type: f1 |
|
value: 40.776679545648506 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: arguana |
|
name: MTEB ArguAna |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.101999999999997 |
|
- type: map_at_10 |
|
value: 40.754000000000005 |
|
- type: map_at_100 |
|
value: 41.83 |
|
- type: map_at_1000 |
|
value: 41.845 |
|
- type: map_at_3 |
|
value: 36.178 |
|
- type: map_at_5 |
|
value: 38.646 |
|
- type: mrr_at_1 |
|
value: 26.6 |
|
- type: mrr_at_10 |
|
value: 40.934 |
|
- type: mrr_at_100 |
|
value: 42.015 |
|
- type: mrr_at_1000 |
|
value: 42.03 |
|
- type: mrr_at_3 |
|
value: 36.344 |
|
- type: mrr_at_5 |
|
value: 38.848 |
|
- type: ndcg_at_1 |
|
value: 26.101999999999997 |
|
- type: ndcg_at_10 |
|
value: 49.126999999999995 |
|
- type: ndcg_at_100 |
|
value: 53.815999999999995 |
|
- type: ndcg_at_1000 |
|
value: 54.178000000000004 |
|
- type: ndcg_at_3 |
|
value: 39.607 |
|
- type: ndcg_at_5 |
|
value: 44.086999999999996 |
|
- type: precision_at_1 |
|
value: 26.101999999999997 |
|
- type: precision_at_10 |
|
value: 7.596 |
|
- type: precision_at_100 |
|
value: 0.967 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 16.524 |
|
- type: precision_at_5 |
|
value: 12.105 |
|
- type: recall_at_1 |
|
value: 26.101999999999997 |
|
- type: recall_at_10 |
|
value: 75.96000000000001 |
|
- type: recall_at_100 |
|
value: 96.65700000000001 |
|
- type: recall_at_1000 |
|
value: 99.431 |
|
- type: recall_at_3 |
|
value: 49.573 |
|
- type: recall_at_5 |
|
value: 60.526 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-p2p |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 43.10651535441929 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-s2s |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 34.41095293826606 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/askubuntudupquestions-reranking |
|
name: MTEB AskUbuntuDupQuestions |
|
config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 56.96575970919239 |
|
- type: mrr |
|
value: 69.92503187794047 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/biosses-sts |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.64892774481326 |
|
- type: cos_sim_spearman |
|
value: 78.953003817029 |
|
- type: euclidean_pearson |
|
value: 78.92456838230683 |
|
- type: euclidean_spearman |
|
value: 78.56504316985354 |
|
- type: manhattan_pearson |
|
value: 79.21436359014227 |
|
- type: manhattan_spearman |
|
value: 78.66263575501259 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/banking77 |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 81.25 |
|
- type: f1 |
|
value: 81.20841448916138 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-p2p |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 34.69545244587236 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-s2s |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 28.84301739171936 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.401 |
|
- type: map_at_10 |
|
value: 32.451 |
|
- type: map_at_100 |
|
value: 33.891 |
|
- type: map_at_1000 |
|
value: 34.01 |
|
- type: map_at_3 |
|
value: 29.365999999999996 |
|
- type: map_at_5 |
|
value: 31.240000000000002 |
|
- type: mrr_at_1 |
|
value: 29.9 |
|
- type: mrr_at_10 |
|
value: 38.590999999999994 |
|
- type: mrr_at_100 |
|
value: 39.587 |
|
- type: mrr_at_1000 |
|
value: 39.637 |
|
- type: mrr_at_3 |
|
value: 36.028 |
|
- type: mrr_at_5 |
|
value: 37.673 |
|
- type: ndcg_at_1 |
|
value: 29.9 |
|
- type: ndcg_at_10 |
|
value: 38.251000000000005 |
|
- type: ndcg_at_100 |
|
value: 44.354 |
|
- type: ndcg_at_1000 |
|
value: 46.642 |
|
- type: ndcg_at_3 |
|
value: 33.581 |
|
- type: ndcg_at_5 |
|
value: 35.96 |
|
- type: precision_at_1 |
|
value: 29.9 |
|
- type: precision_at_10 |
|
value: 7.439 |
|
- type: precision_at_100 |
|
value: 1.28 |
|
- type: precision_at_1000 |
|
value: 0.17700000000000002 |
|
- type: precision_at_3 |
|
value: 16.404 |
|
- type: precision_at_5 |
|
value: 12.046 |
|
- type: recall_at_1 |
|
value: 23.401 |
|
- type: recall_at_10 |
|
value: 49.305 |
|
- type: recall_at_100 |
|
value: 75.885 |
|
- type: recall_at_1000 |
|
value: 90.885 |
|
- type: recall_at_3 |
|
value: 35.341 |
|
- type: recall_at_5 |
|
value: 42.275 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.103 |
|
- type: map_at_10 |
|
value: 29.271 |
|
- type: map_at_100 |
|
value: 30.151 |
|
- type: map_at_1000 |
|
value: 30.276999999999997 |
|
- type: map_at_3 |
|
value: 27.289 |
|
- type: map_at_5 |
|
value: 28.236 |
|
- type: mrr_at_1 |
|
value: 26.943 |
|
- type: mrr_at_10 |
|
value: 33.782000000000004 |
|
- type: mrr_at_100 |
|
value: 34.459 |
|
- type: mrr_at_1000 |
|
value: 34.525 |
|
- type: mrr_at_3 |
|
value: 31.985000000000003 |
|
- type: mrr_at_5 |
|
value: 32.909 |
|
- type: ndcg_at_1 |
|
value: 26.943 |
|
- type: ndcg_at_10 |
|
value: 33.616 |
|
- type: ndcg_at_100 |
|
value: 37.669000000000004 |
|
- type: ndcg_at_1000 |
|
value: 40.247 |
|
- type: ndcg_at_3 |
|
value: 30.482 |
|
- type: ndcg_at_5 |
|
value: 31.615 |
|
- type: precision_at_1 |
|
value: 26.943 |
|
- type: precision_at_10 |
|
value: 6.146 |
|
- type: precision_at_100 |
|
value: 1.038 |
|
- type: precision_at_1000 |
|
value: 0.151 |
|
- type: precision_at_3 |
|
value: 14.521999999999998 |
|
- type: precision_at_5 |
|
value: 10.038 |
|
- type: recall_at_1 |
|
value: 22.103 |
|
- type: recall_at_10 |
|
value: 41.754999999999995 |
|
- type: recall_at_100 |
|
value: 59.636 |
|
- type: recall_at_1000 |
|
value: 76.801 |
|
- type: recall_at_3 |
|
value: 32.285000000000004 |
|
- type: recall_at_5 |
|
value: 35.684 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 32.565 |
|
- type: map_at_10 |
|
value: 43.07 |
|
- type: map_at_100 |
|
value: 44.102999999999994 |
|
- type: map_at_1000 |
|
value: 44.175 |
|
- type: map_at_3 |
|
value: 40.245 |
|
- type: map_at_5 |
|
value: 41.71 |
|
- type: mrr_at_1 |
|
value: 37.429 |
|
- type: mrr_at_10 |
|
value: 46.358 |
|
- type: mrr_at_100 |
|
value: 47.146 |
|
- type: mrr_at_1000 |
|
value: 47.187 |
|
- type: mrr_at_3 |
|
value: 44.086 |
|
- type: mrr_at_5 |
|
value: 45.318000000000005 |
|
- type: ndcg_at_1 |
|
value: 37.429 |
|
- type: ndcg_at_10 |
|
value: 48.398 |
|
- type: ndcg_at_100 |
|
value: 52.90899999999999 |
|
- type: ndcg_at_1000 |
|
value: 54.478 |
|
- type: ndcg_at_3 |
|
value: 43.418 |
|
- type: ndcg_at_5 |
|
value: 45.578 |
|
- type: precision_at_1 |
|
value: 37.429 |
|
- type: precision_at_10 |
|
value: 7.856000000000001 |
|
- type: precision_at_100 |
|
value: 1.093 |
|
- type: precision_at_1000 |
|
value: 0.129 |
|
- type: precision_at_3 |
|
value: 19.331 |
|
- type: precision_at_5 |
|
value: 13.191 |
|
- type: recall_at_1 |
|
value: 32.565 |
|
- type: recall_at_10 |
|
value: 61.021 |
|
- type: recall_at_100 |
|
value: 81.105 |
|
- type: recall_at_1000 |
|
value: 92.251 |
|
- type: recall_at_3 |
|
value: 47.637 |
|
- type: recall_at_5 |
|
value: 52.871 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.108 |
|
- type: map_at_10 |
|
value: 24.613 |
|
- type: map_at_100 |
|
value: 25.624000000000002 |
|
- type: map_at_1000 |
|
value: 25.721 |
|
- type: map_at_3 |
|
value: 22.271 |
|
- type: map_at_5 |
|
value: 23.681 |
|
- type: mrr_at_1 |
|
value: 19.435 |
|
- type: mrr_at_10 |
|
value: 26.124000000000002 |
|
- type: mrr_at_100 |
|
value: 27.07 |
|
- type: mrr_at_1000 |
|
value: 27.145999999999997 |
|
- type: mrr_at_3 |
|
value: 23.748 |
|
- type: mrr_at_5 |
|
value: 25.239 |
|
- type: ndcg_at_1 |
|
value: 19.435 |
|
- type: ndcg_at_10 |
|
value: 28.632 |
|
- type: ndcg_at_100 |
|
value: 33.988 |
|
- type: ndcg_at_1000 |
|
value: 36.551 |
|
- type: ndcg_at_3 |
|
value: 24.035999999999998 |
|
- type: ndcg_at_5 |
|
value: 26.525 |
|
- type: precision_at_1 |
|
value: 19.435 |
|
- type: precision_at_10 |
|
value: 4.565 |
|
- type: precision_at_100 |
|
value: 0.771 |
|
- type: precision_at_1000 |
|
value: 0.10200000000000001 |
|
- type: precision_at_3 |
|
value: 10.169 |
|
- type: precision_at_5 |
|
value: 7.571 |
|
- type: recall_at_1 |
|
value: 18.108 |
|
- type: recall_at_10 |
|
value: 39.533 |
|
- type: recall_at_100 |
|
value: 64.854 |
|
- type: recall_at_1000 |
|
value: 84.421 |
|
- type: recall_at_3 |
|
value: 27.500000000000004 |
|
- type: recall_at_5 |
|
value: 33.314 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.087 |
|
- type: map_at_10 |
|
value: 17.323 |
|
- type: map_at_100 |
|
value: 18.569 |
|
- type: map_at_1000 |
|
value: 18.694 |
|
- type: map_at_3 |
|
value: 15.370000000000001 |
|
- type: map_at_5 |
|
value: 16.538 |
|
- type: mrr_at_1 |
|
value: 13.557 |
|
- type: mrr_at_10 |
|
value: 21.041 |
|
- type: mrr_at_100 |
|
value: 22.134 |
|
- type: mrr_at_1000 |
|
value: 22.207 |
|
- type: mrr_at_3 |
|
value: 18.843 |
|
- type: mrr_at_5 |
|
value: 20.236 |
|
- type: ndcg_at_1 |
|
value: 13.557 |
|
- type: ndcg_at_10 |
|
value: 21.571 |
|
- type: ndcg_at_100 |
|
value: 27.678000000000004 |
|
- type: ndcg_at_1000 |
|
value: 30.8 |
|
- type: ndcg_at_3 |
|
value: 17.922 |
|
- type: ndcg_at_5 |
|
value: 19.826 |
|
- type: precision_at_1 |
|
value: 13.557 |
|
- type: precision_at_10 |
|
value: 4.1290000000000004 |
|
- type: precision_at_100 |
|
value: 0.8370000000000001 |
|
- type: precision_at_1000 |
|
value: 0.125 |
|
- type: precision_at_3 |
|
value: 8.914 |
|
- type: precision_at_5 |
|
value: 6.691999999999999 |
|
- type: recall_at_1 |
|
value: 11.087 |
|
- type: recall_at_10 |
|
value: 30.94 |
|
- type: recall_at_100 |
|
value: 57.833999999999996 |
|
- type: recall_at_1000 |
|
value: 80.365 |
|
- type: recall_at_3 |
|
value: 20.854 |
|
- type: recall_at_5 |
|
value: 25.695 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.708 |
|
- type: map_at_10 |
|
value: 30.422 |
|
- type: map_at_100 |
|
value: 31.713 |
|
- type: map_at_1000 |
|
value: 31.842 |
|
- type: map_at_3 |
|
value: 27.424 |
|
- type: map_at_5 |
|
value: 29.17 |
|
- type: mrr_at_1 |
|
value: 26.756 |
|
- type: mrr_at_10 |
|
value: 35.304 |
|
- type: mrr_at_100 |
|
value: 36.296 |
|
- type: mrr_at_1000 |
|
value: 36.359 |
|
- type: mrr_at_3 |
|
value: 32.692 |
|
- type: mrr_at_5 |
|
value: 34.288999999999994 |
|
- type: ndcg_at_1 |
|
value: 26.756 |
|
- type: ndcg_at_10 |
|
value: 35.876000000000005 |
|
- type: ndcg_at_100 |
|
value: 41.708 |
|
- type: ndcg_at_1000 |
|
value: 44.359 |
|
- type: ndcg_at_3 |
|
value: 30.946 |
|
- type: ndcg_at_5 |
|
value: 33.404 |
|
- type: precision_at_1 |
|
value: 26.756 |
|
- type: precision_at_10 |
|
value: 6.795 |
|
- type: precision_at_100 |
|
value: 1.138 |
|
- type: precision_at_1000 |
|
value: 0.155 |
|
- type: precision_at_3 |
|
value: 15.046999999999999 |
|
- type: precision_at_5 |
|
value: 10.972 |
|
- type: recall_at_1 |
|
value: 21.708 |
|
- type: recall_at_10 |
|
value: 47.315000000000005 |
|
- type: recall_at_100 |
|
value: 72.313 |
|
- type: recall_at_1000 |
|
value: 90.199 |
|
- type: recall_at_3 |
|
value: 33.528999999999996 |
|
- type: recall_at_5 |
|
value: 39.985 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.902 |
|
- type: map_at_10 |
|
value: 26.166 |
|
- type: map_at_100 |
|
value: 27.368 |
|
- type: map_at_1000 |
|
value: 27.493000000000002 |
|
- type: map_at_3 |
|
value: 23.505000000000003 |
|
- type: map_at_5 |
|
value: 25.019000000000002 |
|
- type: mrr_at_1 |
|
value: 23.402 |
|
- type: mrr_at_10 |
|
value: 30.787 |
|
- type: mrr_at_100 |
|
value: 31.735000000000003 |
|
- type: mrr_at_1000 |
|
value: 31.806 |
|
- type: mrr_at_3 |
|
value: 28.33 |
|
- type: mrr_at_5 |
|
value: 29.711 |
|
- type: ndcg_at_1 |
|
value: 23.402 |
|
- type: ndcg_at_10 |
|
value: 30.971 |
|
- type: ndcg_at_100 |
|
value: 36.61 |
|
- type: ndcg_at_1000 |
|
value: 39.507999999999996 |
|
- type: ndcg_at_3 |
|
value: 26.352999999999998 |
|
- type: ndcg_at_5 |
|
value: 28.488000000000003 |
|
- type: precision_at_1 |
|
value: 23.402 |
|
- type: precision_at_10 |
|
value: 5.799 |
|
- type: precision_at_100 |
|
value: 1.0 |
|
- type: precision_at_1000 |
|
value: 0.14100000000000001 |
|
- type: precision_at_3 |
|
value: 12.633 |
|
- type: precision_at_5 |
|
value: 9.269 |
|
- type: recall_at_1 |
|
value: 18.902 |
|
- type: recall_at_10 |
|
value: 40.929 |
|
- type: recall_at_100 |
|
value: 65.594 |
|
- type: recall_at_1000 |
|
value: 85.961 |
|
- type: recall_at_3 |
|
value: 28.121000000000002 |
|
- type: recall_at_5 |
|
value: 33.638 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 19.168 |
|
- type: map_at_10 |
|
value: 25.142999999999997 |
|
- type: map_at_100 |
|
value: 25.993 |
|
- type: map_at_1000 |
|
value: 26.076 |
|
- type: map_at_3 |
|
value: 23.179 |
|
- type: map_at_5 |
|
value: 24.322 |
|
- type: mrr_at_1 |
|
value: 21.933 |
|
- type: mrr_at_10 |
|
value: 27.72 |
|
- type: mrr_at_100 |
|
value: 28.518 |
|
- type: mrr_at_1000 |
|
value: 28.582 |
|
- type: mrr_at_3 |
|
value: 25.791999999999998 |
|
- type: mrr_at_5 |
|
value: 26.958 |
|
- type: ndcg_at_1 |
|
value: 21.933 |
|
- type: ndcg_at_10 |
|
value: 28.866999999999997 |
|
- type: ndcg_at_100 |
|
value: 33.285 |
|
- type: ndcg_at_1000 |
|
value: 35.591 |
|
- type: ndcg_at_3 |
|
value: 25.202999999999996 |
|
- type: ndcg_at_5 |
|
value: 27.045 |
|
- type: precision_at_1 |
|
value: 21.933 |
|
- type: precision_at_10 |
|
value: 4.632 |
|
- type: precision_at_100 |
|
value: 0.733 |
|
- type: precision_at_1000 |
|
value: 0.101 |
|
- type: precision_at_3 |
|
value: 10.992 |
|
- type: precision_at_5 |
|
value: 7.853000000000001 |
|
- type: recall_at_1 |
|
value: 19.168 |
|
- type: recall_at_10 |
|
value: 37.899 |
|
- type: recall_at_100 |
|
value: 58.54899999999999 |
|
- type: recall_at_1000 |
|
value: 75.666 |
|
- type: recall_at_3 |
|
value: 27.831 |
|
- type: recall_at_5 |
|
value: 32.336 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 12.764000000000001 |
|
- type: map_at_10 |
|
value: 17.757 |
|
- type: map_at_100 |
|
value: 18.677 |
|
- type: map_at_1000 |
|
value: 18.813 |
|
- type: map_at_3 |
|
value: 16.151 |
|
- type: map_at_5 |
|
value: 16.946 |
|
- type: mrr_at_1 |
|
value: 15.726 |
|
- type: mrr_at_10 |
|
value: 21.019 |
|
- type: mrr_at_100 |
|
value: 21.856 |
|
- type: mrr_at_1000 |
|
value: 21.954 |
|
- type: mrr_at_3 |
|
value: 19.282 |
|
- type: mrr_at_5 |
|
value: 20.189 |
|
- type: ndcg_at_1 |
|
value: 15.726 |
|
- type: ndcg_at_10 |
|
value: 21.259 |
|
- type: ndcg_at_100 |
|
value: 25.868999999999996 |
|
- type: ndcg_at_1000 |
|
value: 29.425 |
|
- type: ndcg_at_3 |
|
value: 18.204 |
|
- type: ndcg_at_5 |
|
value: 19.434 |
|
- type: precision_at_1 |
|
value: 15.726 |
|
- type: precision_at_10 |
|
value: 3.8920000000000003 |
|
- type: precision_at_100 |
|
value: 0.741 |
|
- type: precision_at_1000 |
|
value: 0.121 |
|
- type: precision_at_3 |
|
value: 8.58 |
|
- type: precision_at_5 |
|
value: 6.132 |
|
- type: recall_at_1 |
|
value: 12.764000000000001 |
|
- type: recall_at_10 |
|
value: 28.639 |
|
- type: recall_at_100 |
|
value: 49.639 |
|
- type: recall_at_1000 |
|
value: 75.725 |
|
- type: recall_at_3 |
|
value: 19.883 |
|
- type: recall_at_5 |
|
value: 23.141000000000002 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.98 |
|
- type: map_at_10 |
|
value: 25.2 |
|
- type: map_at_100 |
|
value: 26.279000000000003 |
|
- type: map_at_1000 |
|
value: 26.399 |
|
- type: map_at_3 |
|
value: 23.399 |
|
- type: map_at_5 |
|
value: 24.284 |
|
- type: mrr_at_1 |
|
value: 22.015 |
|
- type: mrr_at_10 |
|
value: 28.555000000000003 |
|
- type: mrr_at_100 |
|
value: 29.497 |
|
- type: mrr_at_1000 |
|
value: 29.574 |
|
- type: mrr_at_3 |
|
value: 26.788 |
|
- type: mrr_at_5 |
|
value: 27.576 |
|
- type: ndcg_at_1 |
|
value: 22.015 |
|
- type: ndcg_at_10 |
|
value: 29.266 |
|
- type: ndcg_at_100 |
|
value: 34.721000000000004 |
|
- type: ndcg_at_1000 |
|
value: 37.659 |
|
- type: ndcg_at_3 |
|
value: 25.741000000000003 |
|
- type: ndcg_at_5 |
|
value: 27.044 |
|
- type: precision_at_1 |
|
value: 22.015 |
|
- type: precision_at_10 |
|
value: 4.897 |
|
- type: precision_at_100 |
|
value: 0.8540000000000001 |
|
- type: precision_at_1000 |
|
value: 0.122 |
|
- type: precision_at_3 |
|
value: 11.567 |
|
- type: precision_at_5 |
|
value: 7.9479999999999995 |
|
- type: recall_at_1 |
|
value: 18.98 |
|
- type: recall_at_10 |
|
value: 38.411 |
|
- type: recall_at_100 |
|
value: 63.164 |
|
- type: recall_at_1000 |
|
value: 84.292 |
|
- type: recall_at_3 |
|
value: 28.576 |
|
- type: recall_at_5 |
|
value: 31.789 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.372 |
|
- type: map_at_10 |
|
value: 27.161 |
|
- type: map_at_100 |
|
value: 28.364 |
|
- type: map_at_1000 |
|
value: 28.554000000000002 |
|
- type: map_at_3 |
|
value: 25.135 |
|
- type: map_at_5 |
|
value: 26.200000000000003 |
|
- type: mrr_at_1 |
|
value: 24.704 |
|
- type: mrr_at_10 |
|
value: 31.219 |
|
- type: mrr_at_100 |
|
value: 32.092 |
|
- type: mrr_at_1000 |
|
value: 32.181 |
|
- type: mrr_at_3 |
|
value: 29.282000000000004 |
|
- type: mrr_at_5 |
|
value: 30.359 |
|
- type: ndcg_at_1 |
|
value: 24.704 |
|
- type: ndcg_at_10 |
|
value: 31.622 |
|
- type: ndcg_at_100 |
|
value: 36.917 |
|
- type: ndcg_at_1000 |
|
value: 40.357 |
|
- type: ndcg_at_3 |
|
value: 28.398 |
|
- type: ndcg_at_5 |
|
value: 29.764000000000003 |
|
- type: precision_at_1 |
|
value: 24.704 |
|
- type: precision_at_10 |
|
value: 5.81 |
|
- type: precision_at_100 |
|
value: 1.208 |
|
- type: precision_at_1000 |
|
value: 0.209 |
|
- type: precision_at_3 |
|
value: 13.241 |
|
- type: precision_at_5 |
|
value: 9.407 |
|
- type: recall_at_1 |
|
value: 20.372 |
|
- type: recall_at_10 |
|
value: 40.053 |
|
- type: recall_at_100 |
|
value: 64.71000000000001 |
|
- type: recall_at_1000 |
|
value: 87.607 |
|
- type: recall_at_3 |
|
value: 29.961 |
|
- type: recall_at_5 |
|
value: 34.058 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.424000000000001 |
|
- type: map_at_10 |
|
value: 20.541999999999998 |
|
- type: map_at_100 |
|
value: 21.495 |
|
- type: map_at_1000 |
|
value: 21.604 |
|
- type: map_at_3 |
|
value: 18.608 |
|
- type: map_at_5 |
|
value: 19.783 |
|
- type: mrr_at_1 |
|
value: 15.895999999999999 |
|
- type: mrr_at_10 |
|
value: 22.484 |
|
- type: mrr_at_100 |
|
value: 23.376 |
|
- type: mrr_at_1000 |
|
value: 23.467 |
|
- type: mrr_at_3 |
|
value: 20.548 |
|
- type: mrr_at_5 |
|
value: 21.731 |
|
- type: ndcg_at_1 |
|
value: 15.895999999999999 |
|
- type: ndcg_at_10 |
|
value: 24.343 |
|
- type: ndcg_at_100 |
|
value: 29.181 |
|
- type: ndcg_at_1000 |
|
value: 32.330999999999996 |
|
- type: ndcg_at_3 |
|
value: 20.518 |
|
- type: ndcg_at_5 |
|
value: 22.561999999999998 |
|
- type: precision_at_1 |
|
value: 15.895999999999999 |
|
- type: precision_at_10 |
|
value: 3.9739999999999998 |
|
- type: precision_at_100 |
|
value: 0.6799999999999999 |
|
- type: precision_at_1000 |
|
value: 0.105 |
|
- type: precision_at_3 |
|
value: 9.057 |
|
- type: precision_at_5 |
|
value: 6.654 |
|
- type: recall_at_1 |
|
value: 14.424000000000001 |
|
- type: recall_at_10 |
|
value: 34.079 |
|
- type: recall_at_100 |
|
value: 56.728 |
|
- type: recall_at_1000 |
|
value: 80.765 |
|
- type: recall_at_3 |
|
value: 23.993000000000002 |
|
- type: recall_at_5 |
|
value: 28.838 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/emotion |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 41.665 |
|
- type: f1 |
|
value: 37.601137843331244 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/imdb |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 74.8052 |
|
- type: ap |
|
value: 68.92588517572685 |
|
- type: f1 |
|
value: 74.66801685854456 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 91.2220702234382 |
|
- type: f1 |
|
value: 90.81687856852439 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 69.39124487004105 |
|
- type: f1 |
|
value: 51.8350043424968 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 69.80497646267652 |
|
- type: f1 |
|
value: 67.34213899244814 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 74.54270342972428 |
|
- type: f1 |
|
value: 74.02802500235784 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-p2p |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 30.488580544269002 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-s2s |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 28.80426879476371 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/mind_small |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 31.37970068676043 |
|
- type: mrr |
|
value: 32.48523694064166 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 42.862710845031565 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering-p2p |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 54.270000736385626 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sickr-sts |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 80.89215288990194 |
|
- type: cos_sim_spearman |
|
value: 74.386413188675 |
|
- type: euclidean_pearson |
|
value: 78.83679563989534 |
|
- type: euclidean_spearman |
|
value: 74.29328198771996 |
|
- type: manhattan_pearson |
|
value: 78.77968796707641 |
|
- type: manhattan_spearman |
|
value: 74.20887429784696 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts12-sts |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 78.31858821914498 |
|
- type: cos_sim_spearman |
|
value: 72.2217008523832 |
|
- type: euclidean_pearson |
|
value: 75.38901061978429 |
|
- type: euclidean_spearman |
|
value: 71.81255767675184 |
|
- type: manhattan_pearson |
|
value: 75.49472202181288 |
|
- type: manhattan_spearman |
|
value: 71.96322588726144 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts13-sts |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.48334648997455 |
|
- type: cos_sim_spearman |
|
value: 80.99654029572798 |
|
- type: euclidean_pearson |
|
value: 80.46546523970035 |
|
- type: euclidean_spearman |
|
value: 80.90646216980744 |
|
- type: manhattan_pearson |
|
value: 80.35474057857608 |
|
- type: manhattan_spearman |
|
value: 80.8141299909659 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts14-sts |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.73826970784727 |
|
- type: cos_sim_spearman |
|
value: 76.9926870133034 |
|
- type: euclidean_pearson |
|
value: 79.6386542120984 |
|
- type: euclidean_spearman |
|
value: 77.05041986942253 |
|
- type: manhattan_pearson |
|
value: 79.61799508502459 |
|
- type: manhattan_spearman |
|
value: 77.07169617647067 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts15-sts |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.93999019426069 |
|
- type: cos_sim_spearman |
|
value: 85.21166521594695 |
|
- type: euclidean_pearson |
|
value: 84.97207676326357 |
|
- type: euclidean_spearman |
|
value: 85.40726578482739 |
|
- type: manhattan_pearson |
|
value: 85.0386693192183 |
|
- type: manhattan_spearman |
|
value: 85.49230945586409 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts16-sts |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 80.8133974034008 |
|
- type: cos_sim_spearman |
|
value: 82.82919022688844 |
|
- type: euclidean_pearson |
|
value: 81.92587923760179 |
|
- type: euclidean_spearman |
|
value: 82.86629450518863 |
|
- type: manhattan_pearson |
|
value: 81.98232365999253 |
|
- type: manhattan_spearman |
|
value: 82.94313939920296 |
|
- 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: 86.12872422642363 |
|
- type: cos_sim_spearman |
|
value: 87.77672179979807 |
|
- type: euclidean_pearson |
|
value: 87.76172961705947 |
|
- type: euclidean_spearman |
|
value: 87.9891393339215 |
|
- type: manhattan_pearson |
|
value: 87.78863663568221 |
|
- type: manhattan_spearman |
|
value: 88.08297053203866 |
|
- 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: 58.82824030232733 |
|
- type: cos_sim_spearman |
|
value: 64.17079382633538 |
|
- type: euclidean_pearson |
|
value: 61.31505225602925 |
|
- type: euclidean_spearman |
|
value: 64.05080034530694 |
|
- type: manhattan_pearson |
|
value: 61.77095758943306 |
|
- type: manhattan_spearman |
|
value: 64.14475973774933 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsbenchmark-sts |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 81.39239803497064 |
|
- type: cos_sim_spearman |
|
value: 81.76637354520439 |
|
- type: euclidean_pearson |
|
value: 82.98008209033587 |
|
- type: euclidean_spearman |
|
value: 82.18662536188657 |
|
- type: manhattan_pearson |
|
value: 82.9630328314908 |
|
- type: manhattan_spearman |
|
value: 82.13726553603003 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/scidocs-reranking |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 79.45753132898741 |
|
- type: mrr |
|
value: 93.84029822755313 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.8019801980198 |
|
- type: cos_sim_ap |
|
value: 94.58629018512772 |
|
- type: cos_sim_f1 |
|
value: 89.84771573604061 |
|
- type: cos_sim_precision |
|
value: 91.23711340206185 |
|
- type: cos_sim_recall |
|
value: 88.5 |
|
- type: dot_accuracy |
|
value: 99.74950495049505 |
|
- type: dot_ap |
|
value: 92.5761214576951 |
|
- type: dot_f1 |
|
value: 87.09841917389087 |
|
- type: dot_precision |
|
value: 88.86576482830385 |
|
- type: dot_recall |
|
value: 85.39999999999999 |
|
- type: euclidean_accuracy |
|
value: 99.80495049504951 |
|
- type: euclidean_ap |
|
value: 94.56231673602272 |
|
- type: euclidean_f1 |
|
value: 90.02531645569621 |
|
- type: euclidean_precision |
|
value: 91.17948717948718 |
|
- type: euclidean_recall |
|
value: 88.9 |
|
- type: manhattan_accuracy |
|
value: 99.8009900990099 |
|
- type: manhattan_ap |
|
value: 94.5775591647447 |
|
- type: manhattan_f1 |
|
value: 89.86384266263238 |
|
- type: manhattan_precision |
|
value: 90.64089521871821 |
|
- type: manhattan_recall |
|
value: 89.1 |
|
- type: max_accuracy |
|
value: 99.80495049504951 |
|
- type: max_ap |
|
value: 94.58629018512772 |
|
- type: max_f1 |
|
value: 90.02531645569621 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 53.088941385715735 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering-p2p |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 33.146129414825744 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/stackoverflowdupquestions-reranking |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 48.7511362739003 |
|
- type: mrr |
|
value: 49.61682210763093 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/toxic_conversations_50k |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 67.43820000000001 |
|
- type: ap |
|
value: 12.899489312331003 |
|
- type: f1 |
|
value: 52.03468121072981 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/tweet_sentiment_extraction |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 57.475947934352 |
|
- type: f1 |
|
value: 57.77676730676238 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/twentynewsgroups-clustering |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 38.3463456299738 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twittersemeval2015-pairclassification |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 83.94230196101806 |
|
- type: cos_sim_ap |
|
value: 67.00916556336148 |
|
- type: cos_sim_f1 |
|
value: 63.046014257939085 |
|
- type: cos_sim_precision |
|
value: 61.961783439490446 |
|
- type: cos_sim_recall |
|
value: 64.16886543535621 |
|
- type: dot_accuracy |
|
value: 83.18531322644095 |
|
- type: dot_ap |
|
value: 63.112896030267066 |
|
- type: dot_f1 |
|
value: 59.06565656565657 |
|
- type: dot_precision |
|
value: 56.63438256658596 |
|
- type: dot_recall |
|
value: 61.715039577836414 |
|
- type: euclidean_accuracy |
|
value: 83.94230196101806 |
|
- type: euclidean_ap |
|
value: 67.19856676674463 |
|
- type: euclidean_f1 |
|
value: 63.08428413691571 |
|
- type: euclidean_precision |
|
value: 58.9543682641596 |
|
- type: euclidean_recall |
|
value: 67.83641160949868 |
|
- type: manhattan_accuracy |
|
value: 83.91845979614949 |
|
- type: manhattan_ap |
|
value: 66.9845327263072 |
|
- type: manhattan_f1 |
|
value: 62.693323274236135 |
|
- type: manhattan_precision |
|
value: 59.884698534710544 |
|
- type: manhattan_recall |
|
value: 65.77836411609499 |
|
- type: max_accuracy |
|
value: 83.94230196101806 |
|
- type: max_ap |
|
value: 67.19856676674463 |
|
- type: max_f1 |
|
value: 63.08428413691571 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twitterurlcorpus-pairclassification |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.0777738968448 |
|
- type: cos_sim_ap |
|
value: 84.19747786536 |
|
- type: cos_sim_f1 |
|
value: 75.91830995817077 |
|
- type: cos_sim_precision |
|
value: 69.84671107949033 |
|
- type: cos_sim_recall |
|
value: 83.14598090545118 |
|
- type: dot_accuracy |
|
value: 87.14246904955951 |
|
- type: dot_ap |
|
value: 82.37528804640529 |
|
- type: dot_f1 |
|
value: 74.40963166732163 |
|
- type: dot_precision |
|
value: 69.4127841098447 |
|
- type: dot_recall |
|
value: 80.18170619032954 |
|
- type: euclidean_accuracy |
|
value: 88.08359529630924 |
|
- type: euclidean_ap |
|
value: 84.22633217661986 |
|
- type: euclidean_f1 |
|
value: 76.09190339866403 |
|
- type: euclidean_precision |
|
value: 72.70304390517605 |
|
- type: euclidean_recall |
|
value: 79.81213427779488 |
|
- type: manhattan_accuracy |
|
value: 88.08359529630924 |
|
- type: manhattan_ap |
|
value: 84.18362004611083 |
|
- type: manhattan_f1 |
|
value: 76.08789625360231 |
|
- type: manhattan_precision |
|
value: 71.49336582724072 |
|
- type: manhattan_recall |
|
value: 81.3135201724669 |
|
- type: max_accuracy |
|
value: 88.08359529630924 |
|
- type: max_ap |
|
value: 84.22633217661986 |
|
- type: max_f1 |
|
value: 76.09190339866403 |
|
license: mit |
|
language: |
|
- en |
|
--- |
|
|
|
# bge-small-en-v1.5-sparse |
|
|
|
## Usage |
|
|
|
This is the sparse 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/pruning 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('neuralmagic/bge-small-en-v1.5-sparse', 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). |
