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--- |
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tags: |
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- mteb |
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- sparse sparsity quantized onnx embeddings int8 |
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model-index: |
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- name: bge-small-en-v1.5-sparse |
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results: |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_counterfactual |
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name: MTEB AmazonCounterfactualClassification (en) |
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config: en |
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split: test |
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
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metrics: |
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- type: accuracy |
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value: 70.71641791044776 |
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- type: ap |
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value: 32.850850647310004 |
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- type: f1 |
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value: 64.48101916414805 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_polarity |
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name: MTEB AmazonPolarityClassification |
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config: default |
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split: test |
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revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
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metrics: |
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- type: accuracy |
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value: 83.33962500000001 |
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- type: ap |
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value: 78.28706349240106 |
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- type: f1 |
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value: 83.27426715603062 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_reviews_multi |
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name: MTEB AmazonReviewsClassification (en) |
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config: en |
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split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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metrics: |
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- type: accuracy |
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value: 40.988 |
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- type: f1 |
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value: 40.776679545648506 |
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- task: |
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type: STS |
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dataset: |
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type: mteb/biosses-sts |
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name: MTEB BIOSSES |
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config: default |
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split: test |
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
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metrics: |
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- type: cos_sim_pearson |
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value: 79.64892774481326 |
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- type: cos_sim_spearman |
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value: 78.953003817029 |
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- type: euclidean_pearson |
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value: 78.92456838230683 |
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- type: euclidean_spearman |
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value: 78.56504316985354 |
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- type: manhattan_pearson |
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value: 79.21436359014227 |
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- type: manhattan_spearman |
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value: 78.66263575501259 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/banking77 |
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name: MTEB Banking77Classification |
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config: default |
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split: test |
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
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metrics: |
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- type: accuracy |
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value: 81.25 |
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- type: f1 |
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value: 81.20841448916138 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/emotion |
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name: MTEB EmotionClassification |
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config: default |
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split: test |
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revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
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metrics: |
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- type: accuracy |
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value: 41.665 |
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- type: f1 |
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value: 37.601137843331244 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/imdb |
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name: MTEB ImdbClassification |
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config: default |
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split: test |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
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metrics: |
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- type: accuracy |
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value: 74.8052 |
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- type: ap |
|
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value: 68.92588517572685 |
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- type: f1 |
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value: 74.66801685854456 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/mtop_domain |
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name: MTEB MTOPDomainClassification (en) |
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config: en |
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split: test |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
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metrics: |
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- type: accuracy |
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value: 91.2220702234382 |
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- type: f1 |
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value: 90.81687856852439 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/mtop_intent |
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name: MTEB MTOPIntentClassification (en) |
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config: en |
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split: test |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
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metrics: |
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- type: accuracy |
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value: 69.39124487004105 |
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- type: f1 |
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value: 51.8350043424968 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_massive_intent |
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name: MTEB MassiveIntentClassification (en) |
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config: en |
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split: test |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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metrics: |
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- type: accuracy |
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value: 69.80497646267652 |
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- type: f1 |
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value: 67.34213899244814 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_massive_scenario |
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name: MTEB MassiveScenarioClassification (en) |
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config: en |
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split: test |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
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metrics: |
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- type: accuracy |
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value: 74.54270342972428 |
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- type: f1 |
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value: 74.02802500235784 |
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- task: |
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type: STS |
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dataset: |
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type: mteb/sickr-sts |
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name: MTEB SICK-R |
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config: default |
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split: test |
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revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
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metrics: |
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- type: cos_sim_pearson |
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value: 80.89215288990194 |
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- type: cos_sim_spearman |
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value: 74.386413188675 |
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- type: euclidean_pearson |
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value: 78.83679563989534 |
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- type: euclidean_spearman |
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value: 74.29328198771996 |
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- type: manhattan_pearson |
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value: 78.77968796707641 |
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- type: manhattan_spearman |
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value: 74.20887429784696 |
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- task: |
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type: STS |
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dataset: |
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type: mteb/sts12-sts |
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name: MTEB STS12 |
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config: default |
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split: test |
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revision: a0d554a64d88156834ff5ae9920b964011b16384 |
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metrics: |
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- type: cos_sim_pearson |
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value: 78.31858821914498 |
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- type: cos_sim_spearman |
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value: 72.2217008523832 |
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- type: euclidean_pearson |
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value: 75.38901061978429 |
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- type: euclidean_spearman |
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value: 71.81255767675184 |
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- type: manhattan_pearson |
|
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value: 75.49472202181288 |
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- type: manhattan_spearman |
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value: 71.96322588726144 |
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- task: |
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type: STS |
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dataset: |
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type: mteb/sts13-sts |
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name: MTEB STS13 |
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config: default |
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split: test |
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revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
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metrics: |
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- type: cos_sim_pearson |
|
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value: 79.48334648997455 |
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- type: cos_sim_spearman |
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value: 80.99654029572798 |
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- type: euclidean_pearson |
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value: 80.46546523970035 |
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- type: euclidean_spearman |
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value: 80.90646216980744 |
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- type: manhattan_pearson |
|
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value: 80.35474057857608 |
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- type: manhattan_spearman |
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value: 80.8141299909659 |
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- task: |
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type: STS |
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dataset: |
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type: mteb/sts14-sts |
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name: MTEB STS14 |
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config: default |
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split: test |
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revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
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metrics: |
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- type: cos_sim_pearson |
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value: 79.73826970784727 |
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- type: cos_sim_spearman |
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value: 76.9926870133034 |
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- type: euclidean_pearson |
|
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value: 79.6386542120984 |
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- type: euclidean_spearman |
|
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value: 77.05041986942253 |
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- type: manhattan_pearson |
|
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value: 79.61799508502459 |
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- type: manhattan_spearman |
|
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value: 77.07169617647067 |
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- task: |
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type: STS |
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dataset: |
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type: mteb/sts15-sts |
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name: MTEB STS15 |
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config: default |
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split: test |
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revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
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metrics: |
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- type: cos_sim_pearson |
|
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value: 83.93999019426069 |
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- type: cos_sim_spearman |
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value: 85.21166521594695 |
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- type: euclidean_pearson |
|
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value: 84.97207676326357 |
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- type: euclidean_spearman |
|
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value: 85.40726578482739 |
|
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- type: manhattan_pearson |
|
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value: 85.0386693192183 |
|
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- type: manhattan_spearman |
|
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value: 85.49230945586409 |
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- task: |
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type: STS |
|
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dataset: |
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type: mteb/sts16-sts |
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name: MTEB STS16 |
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config: default |
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split: test |
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revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
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metrics: |
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|
- type: cos_sim_pearson |
|
|
value: 80.8133974034008 |
|
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- 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 |
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- task: |
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type: STS |
|
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dataset: |
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|
type: mteb/sts17-crosslingual-sts |
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name: MTEB STS17 (en-en) |
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|
config: en-en |
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split: test |
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revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
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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 |
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|
- task: |
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type: STS |
|
|
dataset: |
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type: mteb/sts22-crosslingual-sts |
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name: MTEB STS22 (en) |
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config: en |
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split: test |
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revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
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metrics: |
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|
- type: cos_sim_pearson |
|
|
value: 58.82824030232733 |
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- type: cos_sim_spearman |
|
|
value: 64.17079382633538 |
|
|
- type: euclidean_pearson |
|
|
value: 61.31505225602925 |
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|
- type: euclidean_spearman |
|
|
value: 64.05080034530694 |
|
|
- type: manhattan_pearson |
|
|
value: 61.77095758943306 |
|
|
- type: manhattan_spearman |
|
|
value: 64.14475973774933 |
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|
- task: |
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type: STS |
|
|
dataset: |
|
|
type: mteb/stsbenchmark-sts |
|
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name: MTEB STSBenchmark |
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config: default |
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split: test |
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revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
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metrics: |
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|
- 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 |
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- task: |
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type: PairClassification |
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dataset: |
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type: mteb/sprintduplicatequestions-pairclassification |
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name: MTEB SprintDuplicateQuestions |
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config: default |
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split: test |
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revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
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metrics: |
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- type: cos_sim_accuracy |
|
|
value: 99.8019801980198 |
|
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- 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: 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: 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 |
|
|
--- |
|
|
This is the sparse ONNX variant of the [bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) embeddings model created with [DeepSparse Optimum](https://github.com/neuralmagic/optimum-deepsparse) for ONNX export and Neural Magic's [Sparsify](https://account.neuralmagic.com/signin?client_id=d04a5f0c-983d-11ed-88a6-971073f187d3&return_to=https%3A//accounts.neuralmagic.com/v1/connect/authorize%3Fscope%3Dsparsify%3Aread%2Bsparsify%3Awrite%2Buser%3Aapi-key%3Aread%2Buser%3Aprofile%3Awrite%2Buser%3Aprofile%3Aread%26response_type%3Dcode%26code_challenge_method%3DS256%26redirect_uri%3Dhttps%3A//apps.neuralmagic.com/sparsify/oidc/callback.html%26state%3Da9b466a6193c4a7b92cba469408d2495%26client_id%3Dd04a5f0c-983d-11ed-88a6-971073f187d3%26code_challenge%3DP0EkmKBpplTb7crJOGS8YLSwT8UH-BeuD0wuE4JTORQ%26response_mode%3Dquery) for One-Shot quantization and unstructured pruning (50%). |
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|
|
Current up-to-date list of sparse and quantized bge ONNX models: |
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|
|
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[zeroshot/bge-large-en-v1.5-sparse](https://huggingface.co/zeroshot/bge-large-en-v1.5-sparse) |
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[zeroshot/bge-large-en-v1.5-quant](https://huggingface.co/zeroshot/bge-large-en-v1.5-quant) |
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[zeroshot/bge-base-en-v1.5-sparse](https://huggingface.co/zeroshot/bge-base-en-v1.5-sparse) |
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[zeroshot/bge-base-en-v1.5-quant](https://huggingface.co/zeroshot/bge-base-en-v1.5-quant) |
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[zeroshot/bge-small-en-v1.5-sparse](https://huggingface.co/zeroshot/bge-small-en-v1.5-sparse) |
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[zeroshot/bge-small-en-v1.5-quant](https://huggingface.co/zeroshot/bge-small-en-v1.5-quant) |
