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--- |
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language: |
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- en |
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license: mit |
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tags: |
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- sentence-transformers |
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- feature-extraction |
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- sentence-similarity |
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- transformers |
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- mteb |
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- inferentia2 |
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- neuron |
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model-index: |
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- name: bge-base-en-v1.5 |
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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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name: MTEB AmazonCounterfactualClassification (en) |
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type: mteb/amazon_counterfactual |
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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: 76.14925373134328 |
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- type: ap |
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value: 39.32336517995478 |
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- type: f1 |
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value: 70.16902252611425 |
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- task: |
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type: Classification |
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dataset: |
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name: MTEB AmazonPolarityClassification |
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type: mteb/amazon_polarity |
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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 |
|
value: 93.386825 |
|
- type: ap |
|
value: 90.21276917991995 |
|
- type: f1 |
|
value: 93.37741030006174 |
|
- task: |
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type: Classification |
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dataset: |
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name: MTEB AmazonReviewsClassification (en) |
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type: mteb/amazon_reviews_multi |
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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: 48.846000000000004 |
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- type: f1 |
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value: 48.14646269778261 |
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- task: |
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type: Retrieval |
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dataset: |
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name: MTEB ArguAna |
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type: arguana |
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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: 40.754000000000005 |
|
- type: map_at_10 |
|
value: 55.761 |
|
- type: map_at_100 |
|
value: 56.330999999999996 |
|
- type: map_at_1000 |
|
value: 56.333999999999996 |
|
- type: map_at_3 |
|
value: 51.92 |
|
- type: map_at_5 |
|
value: 54.010999999999996 |
|
- type: mrr_at_1 |
|
value: 41.181 |
|
- type: mrr_at_10 |
|
value: 55.967999999999996 |
|
- type: mrr_at_100 |
|
value: 56.538 |
|
- type: mrr_at_1000 |
|
value: 56.542 |
|
- type: mrr_at_3 |
|
value: 51.980000000000004 |
|
- type: mrr_at_5 |
|
value: 54.208999999999996 |
|
- type: ndcg_at_1 |
|
value: 40.754000000000005 |
|
- type: ndcg_at_10 |
|
value: 63.605000000000004 |
|
- type: ndcg_at_100 |
|
value: 66.05199999999999 |
|
- type: ndcg_at_1000 |
|
value: 66.12 |
|
- type: ndcg_at_3 |
|
value: 55.708 |
|
- type: ndcg_at_5 |
|
value: 59.452000000000005 |
|
- type: precision_at_1 |
|
value: 40.754000000000005 |
|
- type: precision_at_10 |
|
value: 8.841000000000001 |
|
- type: precision_at_100 |
|
value: 0.991 |
|
- type: precision_at_1000 |
|
value: 0.1 |
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- type: precision_at_3 |
|
value: 22.238 |
|
- type: precision_at_5 |
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value: 15.149000000000001 |
|
- type: recall_at_1 |
|
value: 40.754000000000005 |
|
- type: recall_at_10 |
|
value: 88.407 |
|
- type: recall_at_100 |
|
value: 99.14699999999999 |
|
- type: recall_at_1000 |
|
value: 99.644 |
|
- type: recall_at_3 |
|
value: 66.714 |
|
- type: recall_at_5 |
|
value: 75.747 |
|
- task: |
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type: Clustering |
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dataset: |
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name: MTEB ArxivClusteringP2P |
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type: mteb/arxiv-clustering-p2p |
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config: default |
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split: test |
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
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metrics: |
|
- type: v_measure |
|
value: 48.74884539679369 |
|
- task: |
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type: Clustering |
|
dataset: |
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name: MTEB ArxivClusteringS2S |
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type: mteb/arxiv-clustering-s2s |
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config: default |
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split: test |
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
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metrics: |
|
- type: v_measure |
|
value: 42.8075893810716 |
|
- task: |
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type: Reranking |
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dataset: |
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name: MTEB AskUbuntuDupQuestions |
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type: mteb/askubuntudupquestions-reranking |
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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: 62.128470519187736 |
|
- type: mrr |
|
value: 74.28065778481289 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB BIOSSES |
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type: mteb/biosses-sts |
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config: default |
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split: test |
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 89.24629081484655 |
|
- type: cos_sim_spearman |
|
value: 86.93752309911496 |
|
- type: euclidean_pearson |
|
value: 87.58589628573816 |
|
- type: euclidean_spearman |
|
value: 88.05622328825284 |
|
- type: manhattan_pearson |
|
value: 87.5594959805773 |
|
- type: manhattan_spearman |
|
value: 88.19658793233961 |
|
- task: |
|
type: Classification |
|
dataset: |
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name: MTEB Banking77Classification |
|
type: mteb/banking77 |
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config: default |
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split: test |
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
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metrics: |
|
- type: accuracy |
|
value: 86.9512987012987 |
|
- type: f1 |
|
value: 86.92515357973708 |
|
- task: |
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type: Clustering |
|
dataset: |
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name: MTEB BiorxivClusteringP2P |
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type: mteb/biorxiv-clustering-p2p |
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config: default |
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split: test |
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 39.10263762928872 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB BiorxivClusteringS2S |
|
type: mteb/biorxiv-clustering-s2s |
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config: default |
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split: test |
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
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- type: v_measure |
|
value: 36.69711517426737 |
|
- task: |
|
type: Retrieval |
|
dataset: |
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name: MTEB CQADupstackAndroidRetrieval |
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type: BeIR/cqadupstack |
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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: 32.327 |
|
- type: map_at_10 |
|
value: 44.099 |
|
- type: map_at_100 |
|
value: 45.525 |
|
- type: map_at_1000 |
|
value: 45.641999999999996 |
|
- type: map_at_3 |
|
value: 40.47 |
|
- type: map_at_5 |
|
value: 42.36 |
|
- type: mrr_at_1 |
|
value: 39.199 |
|
- type: mrr_at_10 |
|
value: 49.651 |
|
- type: mrr_at_100 |
|
value: 50.29 |
|
- type: mrr_at_1000 |
|
value: 50.329 |
|
- type: mrr_at_3 |
|
value: 46.924 |
|
- type: mrr_at_5 |
|
value: 48.548 |
|
- type: ndcg_at_1 |
|
value: 39.199 |
|
- type: ndcg_at_10 |
|
value: 50.773 |
|
- type: ndcg_at_100 |
|
value: 55.67999999999999 |
|
- type: ndcg_at_1000 |
|
value: 57.495 |
|
- type: ndcg_at_3 |
|
value: 45.513999999999996 |
|
- type: ndcg_at_5 |
|
value: 47.703 |
|
- type: precision_at_1 |
|
value: 39.199 |
|
- type: precision_at_10 |
|
value: 9.914000000000001 |
|
- type: precision_at_100 |
|
value: 1.5310000000000001 |
|
- type: precision_at_1000 |
|
value: 0.198 |
|
- type: precision_at_3 |
|
value: 21.984 |
|
- type: precision_at_5 |
|
value: 15.737000000000002 |
|
- type: recall_at_1 |
|
value: 32.327 |
|
- type: recall_at_10 |
|
value: 63.743 |
|
- type: recall_at_100 |
|
value: 84.538 |
|
- type: recall_at_1000 |
|
value: 96.089 |
|
- type: recall_at_3 |
|
value: 48.065000000000005 |
|
- type: recall_at_5 |
|
value: 54.519 |
|
- type: map_at_1 |
|
value: 32.671 |
|
- type: map_at_10 |
|
value: 42.954 |
|
- type: map_at_100 |
|
value: 44.151 |
|
- type: map_at_1000 |
|
value: 44.287 |
|
- type: map_at_3 |
|
value: 39.912 |
|
- type: map_at_5 |
|
value: 41.798 |
|
- type: mrr_at_1 |
|
value: 41.465 |
|
- type: mrr_at_10 |
|
value: 49.351 |
|
- type: mrr_at_100 |
|
value: 49.980000000000004 |
|
- type: mrr_at_1000 |
|
value: 50.016000000000005 |
|
- type: mrr_at_3 |
|
value: 47.144000000000005 |
|
- type: mrr_at_5 |
|
value: 48.592999999999996 |
|
- type: ndcg_at_1 |
|
value: 41.465 |
|
- type: ndcg_at_10 |
|
value: 48.565999999999995 |
|
- type: ndcg_at_100 |
|
value: 52.76499999999999 |
|
- type: ndcg_at_1000 |
|
value: 54.749 |
|
- type: ndcg_at_3 |
|
value: 44.57 |
|
- type: ndcg_at_5 |
|
value: 46.759 |
|
- type: precision_at_1 |
|
value: 41.465 |
|
- type: precision_at_10 |
|
value: 9.107999999999999 |
|
- type: precision_at_100 |
|
value: 1.433 |
|
- type: precision_at_1000 |
|
value: 0.191 |
|
- type: precision_at_3 |
|
value: 21.423000000000002 |
|
- type: precision_at_5 |
|
value: 15.414 |
|
- type: recall_at_1 |
|
value: 32.671 |
|
- type: recall_at_10 |
|
value: 57.738 |
|
- type: recall_at_100 |
|
value: 75.86500000000001 |
|
- type: recall_at_1000 |
|
value: 88.36 |
|
- type: recall_at_3 |
|
value: 45.626 |
|
- type: recall_at_5 |
|
value: 51.812000000000005 |
|
- type: map_at_1 |
|
value: 41.185 |
|
- type: map_at_10 |
|
value: 53.929 |
|
- type: map_at_100 |
|
value: 54.92 |
|
- type: map_at_1000 |
|
value: 54.967999999999996 |
|
- type: map_at_3 |
|
value: 50.70400000000001 |
|
- type: map_at_5 |
|
value: 52.673 |
|
- type: mrr_at_1 |
|
value: 47.398 |
|
- type: mrr_at_10 |
|
value: 57.303000000000004 |
|
- type: mrr_at_100 |
|
value: 57.959 |
|
- type: mrr_at_1000 |
|
value: 57.985 |
|
- type: mrr_at_3 |
|
value: 54.932 |
|
- type: mrr_at_5 |
|
value: 56.464999999999996 |
|
- type: ndcg_at_1 |
|
value: 47.398 |
|
- type: ndcg_at_10 |
|
value: 59.653 |
|
- type: ndcg_at_100 |
|
value: 63.627 |
|
- type: ndcg_at_1000 |
|
value: 64.596 |
|
- type: ndcg_at_3 |
|
value: 54.455 |
|
- type: ndcg_at_5 |
|
value: 57.245000000000005 |
|
- type: precision_at_1 |
|
value: 47.398 |
|
- type: precision_at_10 |
|
value: 9.524000000000001 |
|
- type: precision_at_100 |
|
value: 1.243 |
|
- type: precision_at_1000 |
|
value: 0.13699999999999998 |
|
- type: precision_at_3 |
|
value: 24.389 |
|
- type: precision_at_5 |
|
value: 16.752 |
|
- type: recall_at_1 |
|
value: 41.185 |
|
- type: recall_at_10 |
|
value: 73.193 |
|
- type: recall_at_100 |
|
value: 90.357 |
|
- type: recall_at_1000 |
|
value: 97.253 |
|
- type: recall_at_3 |
|
value: 59.199999999999996 |
|
- type: recall_at_5 |
|
value: 66.118 |
|
- type: map_at_1 |
|
value: 27.27 |
|
- type: map_at_10 |
|
value: 36.223 |
|
- type: map_at_100 |
|
value: 37.218 |
|
- type: map_at_1000 |
|
value: 37.293 |
|
- type: map_at_3 |
|
value: 33.503 |
|
- type: map_at_5 |
|
value: 35.097 |
|
- type: mrr_at_1 |
|
value: 29.492 |
|
- type: mrr_at_10 |
|
value: 38.352000000000004 |
|
- type: mrr_at_100 |
|
value: 39.188 |
|
- type: mrr_at_1000 |
|
value: 39.247 |
|
- type: mrr_at_3 |
|
value: 35.876000000000005 |
|
- type: mrr_at_5 |
|
value: 37.401 |
|
- type: ndcg_at_1 |
|
value: 29.492 |
|
- type: ndcg_at_10 |
|
value: 41.239 |
|
- type: ndcg_at_100 |
|
value: 46.066 |
|
- type: ndcg_at_1000 |
|
value: 47.992000000000004 |
|
- type: ndcg_at_3 |
|
value: 36.11 |
|
- type: ndcg_at_5 |
|
value: 38.772 |
|
- type: precision_at_1 |
|
value: 29.492 |
|
- type: precision_at_10 |
|
value: 6.260000000000001 |
|
- type: precision_at_100 |
|
value: 0.914 |
|
- type: precision_at_1000 |
|
value: 0.11100000000000002 |
|
- type: precision_at_3 |
|
value: 15.104000000000001 |
|
- type: precision_at_5 |
|
value: 10.644 |
|
- type: recall_at_1 |
|
value: 27.27 |
|
- type: recall_at_10 |
|
value: 54.589 |
|
- type: recall_at_100 |
|
value: 76.70700000000001 |
|
- type: recall_at_1000 |
|
value: 91.158 |
|
- type: recall_at_3 |
|
value: 40.974 |
|
- type: recall_at_5 |
|
value: 47.327000000000005 |
|
- type: map_at_1 |
|
value: 17.848 |
|
- type: map_at_10 |
|
value: 26.207 |
|
- type: map_at_100 |
|
value: 27.478 |
|
- type: map_at_1000 |
|
value: 27.602 |
|
- type: map_at_3 |
|
value: 23.405 |
|
- type: map_at_5 |
|
value: 24.98 |
|
- type: mrr_at_1 |
|
value: 21.891 |
|
- type: mrr_at_10 |
|
value: 31.041999999999998 |
|
- type: mrr_at_100 |
|
value: 32.092 |
|
- type: mrr_at_1000 |
|
value: 32.151999999999994 |
|
- type: mrr_at_3 |
|
value: 28.358 |
|
- type: mrr_at_5 |
|
value: 29.969 |
|
- type: ndcg_at_1 |
|
value: 21.891 |
|
- type: ndcg_at_10 |
|
value: 31.585 |
|
- type: ndcg_at_100 |
|
value: 37.531 |
|
- type: ndcg_at_1000 |
|
value: 40.256 |
|
- type: ndcg_at_3 |
|
value: 26.508 |
|
- type: ndcg_at_5 |
|
value: 28.894 |
|
- type: precision_at_1 |
|
value: 21.891 |
|
- type: precision_at_10 |
|
value: 5.795999999999999 |
|
- type: precision_at_100 |
|
value: 0.9990000000000001 |
|
- type: precision_at_1000 |
|
value: 0.13799999999999998 |
|
- type: precision_at_3 |
|
value: 12.769 |
|
- type: precision_at_5 |
|
value: 9.279 |
|
- type: recall_at_1 |
|
value: 17.848 |
|
- type: recall_at_10 |
|
value: 43.452 |
|
- type: recall_at_100 |
|
value: 69.216 |
|
- type: recall_at_1000 |
|
value: 88.102 |
|
- type: recall_at_3 |
|
value: 29.18 |
|
- type: recall_at_5 |
|
value: 35.347 |
|
- type: map_at_1 |
|
value: 30.94 |
|
- type: map_at_10 |
|
value: 41.248000000000005 |
|
- type: map_at_100 |
|
value: 42.495 |
|
- type: map_at_1000 |
|
value: 42.602000000000004 |
|
- type: map_at_3 |
|
value: 37.939 |
|
- type: map_at_5 |
|
value: 39.924 |
|
- type: mrr_at_1 |
|
value: 37.824999999999996 |
|
- type: mrr_at_10 |
|
value: 47.041 |
|
- type: mrr_at_100 |
|
value: 47.83 |
|
- type: mrr_at_1000 |
|
value: 47.878 |
|
- type: mrr_at_3 |
|
value: 44.466 |
|
- type: mrr_at_5 |
|
value: 46.111999999999995 |
|
- type: ndcg_at_1 |
|
value: 37.824999999999996 |
|
- type: ndcg_at_10 |
|
value: 47.223 |
|
- type: ndcg_at_100 |
|
value: 52.394 |
|
- type: ndcg_at_1000 |
|
value: 54.432 |
|
- type: ndcg_at_3 |
|
value: 42.032000000000004 |
|
- type: ndcg_at_5 |
|
value: 44.772 |
|
- type: precision_at_1 |
|
value: 37.824999999999996 |
|
- type: precision_at_10 |
|
value: 8.393 |
|
- type: precision_at_100 |
|
value: 1.2890000000000001 |
|
- type: precision_at_1000 |
|
value: 0.164 |
|
- type: precision_at_3 |
|
value: 19.698 |
|
- type: precision_at_5 |
|
value: 14.013 |
|
- type: recall_at_1 |
|
value: 30.94 |
|
- type: recall_at_10 |
|
value: 59.316 |
|
- type: recall_at_100 |
|
value: 80.783 |
|
- type: recall_at_1000 |
|
value: 94.15400000000001 |
|
- type: recall_at_3 |
|
value: 44.712 |
|
- type: recall_at_5 |
|
value: 51.932 |
|
- type: map_at_1 |
|
value: 27.104 |
|
- type: map_at_10 |
|
value: 36.675999999999995 |
|
- type: map_at_100 |
|
value: 38.076 |
|
- type: map_at_1000 |
|
value: 38.189 |
|
- type: map_at_3 |
|
value: 33.733999999999995 |
|
- type: map_at_5 |
|
value: 35.287 |
|
- type: mrr_at_1 |
|
value: 33.904 |
|
- type: mrr_at_10 |
|
value: 42.55 |
|
- type: mrr_at_100 |
|
value: 43.434 |
|
- type: mrr_at_1000 |
|
value: 43.494 |
|
- type: mrr_at_3 |
|
value: 40.126 |
|
- type: mrr_at_5 |
|
value: 41.473 |
|
- type: ndcg_at_1 |
|
value: 33.904 |
|
- type: ndcg_at_10 |
|
value: 42.414 |
|
- type: ndcg_at_100 |
|
value: 48.203 |
|
- type: ndcg_at_1000 |
|
value: 50.437 |
|
- type: ndcg_at_3 |
|
value: 37.633 |
|
- type: ndcg_at_5 |
|
value: 39.67 |
|
- type: precision_at_1 |
|
value: 33.904 |
|
- type: precision_at_10 |
|
value: 7.82 |
|
- type: precision_at_100 |
|
value: 1.2409999999999999 |
|
- type: precision_at_1000 |
|
value: 0.159 |
|
- type: precision_at_3 |
|
value: 17.884 |
|
- type: precision_at_5 |
|
value: 12.648000000000001 |
|
- type: recall_at_1 |
|
value: 27.104 |
|
- type: recall_at_10 |
|
value: 53.563 |
|
- type: recall_at_100 |
|
value: 78.557 |
|
- type: recall_at_1000 |
|
value: 93.533 |
|
- type: recall_at_3 |
|
value: 39.92 |
|
- type: recall_at_5 |
|
value: 45.457 |
|
- type: map_at_1 |
|
value: 27.707749999999997 |
|
- type: map_at_10 |
|
value: 36.961 |
|
- type: map_at_100 |
|
value: 38.158833333333334 |
|
- type: map_at_1000 |
|
value: 38.270333333333326 |
|
- type: map_at_3 |
|
value: 34.07183333333334 |
|
- type: map_at_5 |
|
value: 35.69533333333334 |
|
- type: mrr_at_1 |
|
value: 32.81875 |
|
- type: mrr_at_10 |
|
value: 41.293 |
|
- type: mrr_at_100 |
|
value: 42.116499999999995 |
|
- type: mrr_at_1000 |
|
value: 42.170249999999996 |
|
- type: mrr_at_3 |
|
value: 38.83983333333333 |
|
- type: mrr_at_5 |
|
value: 40.29775 |
|
- type: ndcg_at_1 |
|
value: 32.81875 |
|
- type: ndcg_at_10 |
|
value: 42.355 |
|
- type: ndcg_at_100 |
|
value: 47.41374999999999 |
|
- type: ndcg_at_1000 |
|
value: 49.5805 |
|
- type: ndcg_at_3 |
|
value: 37.52825 |
|
- type: ndcg_at_5 |
|
value: 39.83266666666667 |
|
- type: precision_at_1 |
|
value: 32.81875 |
|
- type: precision_at_10 |
|
value: 7.382416666666666 |
|
- type: precision_at_100 |
|
value: 1.1640833333333334 |
|
- type: precision_at_1000 |
|
value: 0.15383333333333335 |
|
- type: precision_at_3 |
|
value: 17.134166666666665 |
|
- type: precision_at_5 |
|
value: 12.174833333333336 |
|
- type: recall_at_1 |
|
value: 27.707749999999997 |
|
- type: recall_at_10 |
|
value: 53.945 |
|
- type: recall_at_100 |
|
value: 76.191 |
|
- type: recall_at_1000 |
|
value: 91.101 |
|
- type: recall_at_3 |
|
value: 40.39083333333334 |
|
- type: recall_at_5 |
|
value: 46.40083333333333 |
|
- type: map_at_1 |
|
value: 26.482 |
|
- type: map_at_10 |
|
value: 33.201 |
|
- type: map_at_100 |
|
value: 34.107 |
|
- type: map_at_1000 |
|
value: 34.197 |
|
- type: map_at_3 |
|
value: 31.174000000000003 |
|
- type: map_at_5 |
|
value: 32.279 |
|
- type: mrr_at_1 |
|
value: 29.908 |
|
- type: mrr_at_10 |
|
value: 36.235 |
|
- type: mrr_at_100 |
|
value: 37.04 |
|
- type: mrr_at_1000 |
|
value: 37.105 |
|
- type: mrr_at_3 |
|
value: 34.355999999999995 |
|
- type: mrr_at_5 |
|
value: 35.382999999999996 |
|
- type: ndcg_at_1 |
|
value: 29.908 |
|
- type: ndcg_at_10 |
|
value: 37.325 |
|
- type: ndcg_at_100 |
|
value: 41.795 |
|
- type: ndcg_at_1000 |
|
value: 44.105 |
|
- type: ndcg_at_3 |
|
value: 33.555 |
|
- type: ndcg_at_5 |
|
value: 35.266999999999996 |
|
- type: precision_at_1 |
|
value: 29.908 |
|
- type: precision_at_10 |
|
value: 5.721 |
|
- type: precision_at_100 |
|
value: 0.8630000000000001 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 14.008000000000001 |
|
- type: precision_at_5 |
|
value: 9.754999999999999 |
|
- type: recall_at_1 |
|
value: 26.482 |
|
- type: recall_at_10 |
|
value: 47.072 |
|
- type: recall_at_100 |
|
value: 67.27 |
|
- type: recall_at_1000 |
|
value: 84.371 |
|
- type: recall_at_3 |
|
value: 36.65 |
|
- type: recall_at_5 |
|
value: 40.774 |
|
- type: map_at_1 |
|
value: 18.815 |
|
- type: map_at_10 |
|
value: 26.369999999999997 |
|
- type: map_at_100 |
|
value: 27.458 |
|
- type: map_at_1000 |
|
value: 27.588 |
|
- type: map_at_3 |
|
value: 23.990000000000002 |
|
- type: map_at_5 |
|
value: 25.345000000000002 |
|
- type: mrr_at_1 |
|
value: 22.953000000000003 |
|
- type: mrr_at_10 |
|
value: 30.342999999999996 |
|
- type: mrr_at_100 |
|
value: 31.241000000000003 |
|
- type: mrr_at_1000 |
|
value: 31.319000000000003 |
|
- type: mrr_at_3 |
|
value: 28.16 |
|
- type: mrr_at_5 |
|
value: 29.406 |
|
- type: ndcg_at_1 |
|
value: 22.953000000000003 |
|
- type: ndcg_at_10 |
|
value: 31.151 |
|
- type: ndcg_at_100 |
|
value: 36.309000000000005 |
|
- type: ndcg_at_1000 |
|
value: 39.227000000000004 |
|
- type: ndcg_at_3 |
|
value: 26.921 |
|
- type: ndcg_at_5 |
|
value: 28.938000000000002 |
|
- type: precision_at_1 |
|
value: 22.953000000000003 |
|
- type: precision_at_10 |
|
value: 5.602 |
|
- type: precision_at_100 |
|
value: 0.9530000000000001 |
|
- type: precision_at_1000 |
|
value: 0.13899999999999998 |
|
- type: precision_at_3 |
|
value: 12.606 |
|
- type: precision_at_5 |
|
value: 9.119 |
|
- type: recall_at_1 |
|
value: 18.815 |
|
- type: recall_at_10 |
|
value: 41.574 |
|
- type: recall_at_100 |
|
value: 64.84400000000001 |
|
- type: recall_at_1000 |
|
value: 85.406 |
|
- type: recall_at_3 |
|
value: 29.694 |
|
- type: recall_at_5 |
|
value: 34.935 |
|
- type: map_at_1 |
|
value: 27.840999999999998 |
|
- type: map_at_10 |
|
value: 36.797999999999995 |
|
- type: map_at_100 |
|
value: 37.993 |
|
- type: map_at_1000 |
|
value: 38.086999999999996 |
|
- type: map_at_3 |
|
value: 34.050999999999995 |
|
- type: map_at_5 |
|
value: 35.379 |
|
- type: mrr_at_1 |
|
value: 32.649 |
|
- type: mrr_at_10 |
|
value: 41.025 |
|
- type: mrr_at_100 |
|
value: 41.878 |
|
- type: mrr_at_1000 |
|
value: 41.929 |
|
- type: mrr_at_3 |
|
value: 38.573 |
|
- type: mrr_at_5 |
|
value: 39.715 |
|
- type: ndcg_at_1 |
|
value: 32.649 |
|
- type: ndcg_at_10 |
|
value: 42.142 |
|
- type: ndcg_at_100 |
|
value: 47.558 |
|
- type: ndcg_at_1000 |
|
value: 49.643 |
|
- type: ndcg_at_3 |
|
value: 37.12 |
|
- type: ndcg_at_5 |
|
value: 38.983000000000004 |
|
- type: precision_at_1 |
|
value: 32.649 |
|
- type: precision_at_10 |
|
value: 7.08 |
|
- type: precision_at_100 |
|
value: 1.1039999999999999 |
|
- type: precision_at_1000 |
|
value: 0.13899999999999998 |
|
- type: precision_at_3 |
|
value: 16.698 |
|
- type: precision_at_5 |
|
value: 11.511000000000001 |
|
- type: recall_at_1 |
|
value: 27.840999999999998 |
|
- type: recall_at_10 |
|
value: 54.245 |
|
- type: recall_at_100 |
|
value: 77.947 |
|
- type: recall_at_1000 |
|
value: 92.36999999999999 |
|
- type: recall_at_3 |
|
value: 40.146 |
|
- type: recall_at_5 |
|
value: 44.951 |
|
- type: map_at_1 |
|
value: 26.529000000000003 |
|
- type: map_at_10 |
|
value: 35.010000000000005 |
|
- type: map_at_100 |
|
value: 36.647 |
|
- type: map_at_1000 |
|
value: 36.857 |
|
- type: map_at_3 |
|
value: 31.968000000000004 |
|
- type: map_at_5 |
|
value: 33.554 |
|
- type: mrr_at_1 |
|
value: 31.818 |
|
- type: mrr_at_10 |
|
value: 39.550999999999995 |
|
- type: mrr_at_100 |
|
value: 40.54 |
|
- type: mrr_at_1000 |
|
value: 40.596 |
|
- type: mrr_at_3 |
|
value: 36.726 |
|
- type: mrr_at_5 |
|
value: 38.416 |
|
- type: ndcg_at_1 |
|
value: 31.818 |
|
- type: ndcg_at_10 |
|
value: 40.675 |
|
- type: ndcg_at_100 |
|
value: 46.548 |
|
- type: ndcg_at_1000 |
|
value: 49.126 |
|
- type: ndcg_at_3 |
|
value: 35.829 |
|
- type: ndcg_at_5 |
|
value: 38.0 |
|
- type: precision_at_1 |
|
value: 31.818 |
|
- type: precision_at_10 |
|
value: 7.826 |
|
- type: precision_at_100 |
|
value: 1.538 |
|
- type: precision_at_1000 |
|
value: 0.24 |
|
- type: precision_at_3 |
|
value: 16.601 |
|
- type: precision_at_5 |
|
value: 12.095 |
|
- type: recall_at_1 |
|
value: 26.529000000000003 |
|
- type: recall_at_10 |
|
value: 51.03 |
|
- type: recall_at_100 |
|
value: 77.556 |
|
- type: recall_at_1000 |
|
value: 93.804 |
|
- type: recall_at_3 |
|
value: 36.986000000000004 |
|
- type: recall_at_5 |
|
value: 43.096000000000004 |
|
- type: map_at_1 |
|
value: 23.480999999999998 |
|
- type: map_at_10 |
|
value: 30.817 |
|
- type: map_at_100 |
|
value: 31.838 |
|
- type: map_at_1000 |
|
value: 31.932 |
|
- type: map_at_3 |
|
value: 28.011999999999997 |
|
- type: map_at_5 |
|
value: 29.668 |
|
- type: mrr_at_1 |
|
value: 25.323 |
|
- type: mrr_at_10 |
|
value: 33.072 |
|
- type: mrr_at_100 |
|
value: 33.926 |
|
- type: mrr_at_1000 |
|
value: 33.993 |
|
- type: mrr_at_3 |
|
value: 30.436999999999998 |
|
- type: mrr_at_5 |
|
value: 32.092 |
|
- type: ndcg_at_1 |
|
value: 25.323 |
|
- type: ndcg_at_10 |
|
value: 35.514 |
|
- type: ndcg_at_100 |
|
value: 40.489000000000004 |
|
- type: ndcg_at_1000 |
|
value: 42.908 |
|
- type: ndcg_at_3 |
|
value: 30.092000000000002 |
|
- type: ndcg_at_5 |
|
value: 32.989000000000004 |
|
- type: precision_at_1 |
|
value: 25.323 |
|
- type: precision_at_10 |
|
value: 5.545 |
|
- type: precision_at_100 |
|
value: 0.861 |
|
- type: precision_at_1000 |
|
value: 0.117 |
|
- type: precision_at_3 |
|
value: 12.446 |
|
- type: precision_at_5 |
|
value: 9.131 |
|
- type: recall_at_1 |
|
value: 23.480999999999998 |
|
- type: recall_at_10 |
|
value: 47.825 |
|
- type: recall_at_100 |
|
value: 70.652 |
|
- type: recall_at_1000 |
|
value: 88.612 |
|
- type: recall_at_3 |
|
value: 33.537 |
|
- type: recall_at_5 |
|
value: 40.542 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB ClimateFEVER |
|
type: climate-fever |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.333999999999998 |
|
- type: map_at_10 |
|
value: 22.524 |
|
- type: map_at_100 |
|
value: 24.506 |
|
- type: map_at_1000 |
|
value: 24.715 |
|
- type: map_at_3 |
|
value: 19.022 |
|
- type: map_at_5 |
|
value: 20.693 |
|
- type: mrr_at_1 |
|
value: 29.186 |
|
- type: mrr_at_10 |
|
value: 41.22 |
|
- type: mrr_at_100 |
|
value: 42.16 |
|
- type: mrr_at_1000 |
|
value: 42.192 |
|
- type: mrr_at_3 |
|
value: 38.013000000000005 |
|
- type: mrr_at_5 |
|
value: 39.704 |
|
- type: ndcg_at_1 |
|
value: 29.186 |
|
- type: ndcg_at_10 |
|
value: 31.167 |
|
- type: ndcg_at_100 |
|
value: 38.879000000000005 |
|
- type: ndcg_at_1000 |
|
value: 42.376000000000005 |
|
- type: ndcg_at_3 |
|
value: 25.817 |
|
- type: ndcg_at_5 |
|
value: 27.377000000000002 |
|
- type: precision_at_1 |
|
value: 29.186 |
|
- type: precision_at_10 |
|
value: 9.693999999999999 |
|
- type: precision_at_100 |
|
value: 1.8030000000000002 |
|
- type: precision_at_1000 |
|
value: 0.246 |
|
- type: precision_at_3 |
|
value: 19.11 |
|
- type: precision_at_5 |
|
value: 14.344999999999999 |
|
- type: recall_at_1 |
|
value: 13.333999999999998 |
|
- type: recall_at_10 |
|
value: 37.092000000000006 |
|
- type: recall_at_100 |
|
value: 63.651 |
|
- type: recall_at_1000 |
|
value: 83.05 |
|
- type: recall_at_3 |
|
value: 23.74 |
|
- type: recall_at_5 |
|
value: 28.655 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB DBPedia |
|
type: dbpedia-entity |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 9.151 |
|
- type: map_at_10 |
|
value: 19.653000000000002 |
|
- type: map_at_100 |
|
value: 28.053 |
|
- type: map_at_1000 |
|
value: 29.709000000000003 |
|
- type: map_at_3 |
|
value: 14.191 |
|
- type: map_at_5 |
|
value: 16.456 |
|
- type: mrr_at_1 |
|
value: 66.25 |
|
- type: mrr_at_10 |
|
value: 74.4 |
|
- type: mrr_at_100 |
|
value: 74.715 |
|
- type: mrr_at_1000 |
|
value: 74.726 |
|
- type: mrr_at_3 |
|
value: 72.417 |
|
- type: mrr_at_5 |
|
value: 73.667 |
|
- type: ndcg_at_1 |
|
value: 54.25 |
|
- type: ndcg_at_10 |
|
value: 40.77 |
|
- type: ndcg_at_100 |
|
value: 46.359 |
|
- type: ndcg_at_1000 |
|
value: 54.193000000000005 |
|
- type: ndcg_at_3 |
|
value: 44.832 |
|
- type: ndcg_at_5 |
|
value: 42.63 |
|
- type: precision_at_1 |
|
value: 66.25 |
|
- type: precision_at_10 |
|
value: 32.175 |
|
- type: precision_at_100 |
|
value: 10.668 |
|
- type: precision_at_1000 |
|
value: 2.067 |
|
- type: precision_at_3 |
|
value: 47.667 |
|
- type: precision_at_5 |
|
value: 41.3 |
|
- type: recall_at_1 |
|
value: 9.151 |
|
- type: recall_at_10 |
|
value: 25.003999999999998 |
|
- type: recall_at_100 |
|
value: 52.976 |
|
- type: recall_at_1000 |
|
value: 78.315 |
|
- type: recall_at_3 |
|
value: 15.487 |
|
- type: recall_at_5 |
|
value: 18.999 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB EmotionClassification |
|
type: mteb/emotion |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 51.89999999999999 |
|
- type: f1 |
|
value: 46.47777925067403 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB FEVER |
|
type: fever |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 73.706 |
|
- type: map_at_10 |
|
value: 82.423 |
|
- type: map_at_100 |
|
value: 82.67999999999999 |
|
- type: map_at_1000 |
|
value: 82.694 |
|
- type: map_at_3 |
|
value: 81.328 |
|
- type: map_at_5 |
|
value: 82.001 |
|
- type: mrr_at_1 |
|
value: 79.613 |
|
- type: mrr_at_10 |
|
value: 87.07000000000001 |
|
- type: mrr_at_100 |
|
value: 87.169 |
|
- type: mrr_at_1000 |
|
value: 87.17 |
|
- type: mrr_at_3 |
|
value: 86.404 |
|
- type: mrr_at_5 |
|
value: 86.856 |
|
- type: ndcg_at_1 |
|
value: 79.613 |
|
- type: ndcg_at_10 |
|
value: 86.289 |
|
- type: ndcg_at_100 |
|
value: 87.201 |
|
- type: ndcg_at_1000 |
|
value: 87.428 |
|
- type: ndcg_at_3 |
|
value: 84.625 |
|
- type: ndcg_at_5 |
|
value: 85.53699999999999 |
|
- type: precision_at_1 |
|
value: 79.613 |
|
- type: precision_at_10 |
|
value: 10.399 |
|
- type: precision_at_100 |
|
value: 1.1079999999999999 |
|
- type: precision_at_1000 |
|
value: 0.11499999999999999 |
|
- type: precision_at_3 |
|
value: 32.473 |
|
- type: precision_at_5 |
|
value: 20.132 |
|
- type: recall_at_1 |
|
value: 73.706 |
|
- type: recall_at_10 |
|
value: 93.559 |
|
- type: recall_at_100 |
|
value: 97.188 |
|
- type: recall_at_1000 |
|
value: 98.555 |
|
- type: recall_at_3 |
|
value: 88.98700000000001 |
|
- type: recall_at_5 |
|
value: 91.373 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB FiQA2018 |
|
type: fiqa |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 19.841 |
|
- type: map_at_10 |
|
value: 32.643 |
|
- type: map_at_100 |
|
value: 34.575 |
|
- type: map_at_1000 |
|
value: 34.736 |
|
- type: map_at_3 |
|
value: 28.317999999999998 |
|
- type: map_at_5 |
|
value: 30.964000000000002 |
|
- type: mrr_at_1 |
|
value: 39.660000000000004 |
|
- type: mrr_at_10 |
|
value: 48.620000000000005 |
|
- type: mrr_at_100 |
|
value: 49.384 |
|
- type: mrr_at_1000 |
|
value: 49.415 |
|
- type: mrr_at_3 |
|
value: 45.988 |
|
- type: mrr_at_5 |
|
value: 47.361 |
|
- type: ndcg_at_1 |
|
value: 39.660000000000004 |
|
- type: ndcg_at_10 |
|
value: 40.646 |
|
- type: ndcg_at_100 |
|
value: 47.657 |
|
- type: ndcg_at_1000 |
|
value: 50.428 |
|
- type: ndcg_at_3 |
|
value: 36.689 |
|
- type: ndcg_at_5 |
|
value: 38.211 |
|
- type: precision_at_1 |
|
value: 39.660000000000004 |
|
- type: precision_at_10 |
|
value: 11.235000000000001 |
|
- type: precision_at_100 |
|
value: 1.8530000000000002 |
|
- type: precision_at_1000 |
|
value: 0.23600000000000002 |
|
- type: precision_at_3 |
|
value: 24.587999999999997 |
|
- type: precision_at_5 |
|
value: 18.395 |
|
- type: recall_at_1 |
|
value: 19.841 |
|
- type: recall_at_10 |
|
value: 48.135 |
|
- type: recall_at_100 |
|
value: 74.224 |
|
- type: recall_at_1000 |
|
value: 90.826 |
|
- type: recall_at_3 |
|
value: 33.536 |
|
- type: recall_at_5 |
|
value: 40.311 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB HotpotQA |
|
type: hotpotqa |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 40.358 |
|
- type: map_at_10 |
|
value: 64.497 |
|
- type: map_at_100 |
|
value: 65.362 |
|
- type: map_at_1000 |
|
value: 65.41900000000001 |
|
- type: map_at_3 |
|
value: 61.06700000000001 |
|
- type: map_at_5 |
|
value: 63.317 |
|
- type: mrr_at_1 |
|
value: 80.716 |
|
- type: mrr_at_10 |
|
value: 86.10799999999999 |
|
- type: mrr_at_100 |
|
value: 86.265 |
|
- type: mrr_at_1000 |
|
value: 86.27 |
|
- type: mrr_at_3 |
|
value: 85.271 |
|
- type: mrr_at_5 |
|
value: 85.82499999999999 |
|
- type: ndcg_at_1 |
|
value: 80.716 |
|
- type: ndcg_at_10 |
|
value: 72.597 |
|
- type: ndcg_at_100 |
|
value: 75.549 |
|
- type: ndcg_at_1000 |
|
value: 76.61 |
|
- type: ndcg_at_3 |
|
value: 67.874 |
|
- type: ndcg_at_5 |
|
value: 70.655 |
|
- type: precision_at_1 |
|
value: 80.716 |
|
- type: precision_at_10 |
|
value: 15.148 |
|
- type: precision_at_100 |
|
value: 1.745 |
|
- type: precision_at_1000 |
|
value: 0.188 |
|
- type: precision_at_3 |
|
value: 43.597 |
|
- type: precision_at_5 |
|
value: 28.351 |
|
- type: recall_at_1 |
|
value: 40.358 |
|
- type: recall_at_10 |
|
value: 75.739 |
|
- type: recall_at_100 |
|
value: 87.259 |
|
- type: recall_at_1000 |
|
value: 94.234 |
|
- type: recall_at_3 |
|
value: 65.39500000000001 |
|
- type: recall_at_5 |
|
value: 70.878 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB ImdbClassification |
|
type: mteb/imdb |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 90.80799999999998 |
|
- type: ap |
|
value: 86.81350378180757 |
|
- type: f1 |
|
value: 90.79901248314215 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB MSMARCO |
|
type: msmarco |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.096 |
|
- type: map_at_10 |
|
value: 34.384 |
|
- type: map_at_100 |
|
value: 35.541 |
|
- type: map_at_1000 |
|
value: 35.589999999999996 |
|
- type: map_at_3 |
|
value: 30.496000000000002 |
|
- type: map_at_5 |
|
value: 32.718 |
|
- type: mrr_at_1 |
|
value: 22.750999999999998 |
|
- type: mrr_at_10 |
|
value: 35.024 |
|
- type: mrr_at_100 |
|
value: 36.125 |
|
- type: mrr_at_1000 |
|
value: 36.168 |
|
- type: mrr_at_3 |
|
value: 31.225 |
|
- type: mrr_at_5 |
|
value: 33.416000000000004 |
|
- type: ndcg_at_1 |
|
value: 22.750999999999998 |
|
- type: ndcg_at_10 |
|
value: 41.351 |
|
- type: ndcg_at_100 |
|
value: 46.92 |
|
- type: ndcg_at_1000 |
|
value: 48.111 |
|
- type: ndcg_at_3 |
|
value: 33.439 |
|
- type: ndcg_at_5 |
|
value: 37.407000000000004 |
|
- type: precision_at_1 |
|
value: 22.750999999999998 |
|
- type: precision_at_10 |
|
value: 6.564 |
|
- type: precision_at_100 |
|
value: 0.935 |
|
- type: precision_at_1000 |
|
value: 0.104 |
|
- type: precision_at_3 |
|
value: 14.288 |
|
- type: precision_at_5 |
|
value: 10.581999999999999 |
|
- type: recall_at_1 |
|
value: 22.096 |
|
- type: recall_at_10 |
|
value: 62.771 |
|
- type: recall_at_100 |
|
value: 88.529 |
|
- type: recall_at_1000 |
|
value: 97.55 |
|
- type: recall_at_3 |
|
value: 41.245 |
|
- type: recall_at_5 |
|
value: 50.788 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPDomainClassification (en) |
|
type: mteb/mtop_domain |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 94.16780665754673 |
|
- type: f1 |
|
value: 93.96331194859894 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPIntentClassification (en) |
|
type: mteb/mtop_intent |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 76.90606475148198 |
|
- type: f1 |
|
value: 58.58344986604187 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (en) |
|
type: mteb/amazon_massive_intent |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 76.14660390047075 |
|
- type: f1 |
|
value: 74.31533923533614 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveScenarioClassification (en) |
|
type: mteb/amazon_massive_scenario |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 80.16139878950908 |
|
- type: f1 |
|
value: 80.18532656824924 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB MedrxivClusteringP2P |
|
type: mteb/medrxiv-clustering-p2p |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 32.949880906135085 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB MedrxivClusteringS2S |
|
type: mteb/medrxiv-clustering-s2s |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 31.56300351524862 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB MindSmallReranking |
|
type: mteb/mind_small |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 31.196521894371315 |
|
- type: mrr |
|
value: 32.22644231694389 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB NFCorpus |
|
type: nfcorpus |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.783 |
|
- type: map_at_10 |
|
value: 14.549000000000001 |
|
- type: map_at_100 |
|
value: 18.433 |
|
- type: map_at_1000 |
|
value: 19.949 |
|
- type: map_at_3 |
|
value: 10.936 |
|
- type: map_at_5 |
|
value: 12.514 |
|
- type: mrr_at_1 |
|
value: 47.368 |
|
- type: mrr_at_10 |
|
value: 56.42 |
|
- type: mrr_at_100 |
|
value: 56.908 |
|
- type: mrr_at_1000 |
|
value: 56.95 |
|
- type: mrr_at_3 |
|
value: 54.283 |
|
- type: mrr_at_5 |
|
value: 55.568 |
|
- type: ndcg_at_1 |
|
value: 45.666000000000004 |
|
- type: ndcg_at_10 |
|
value: 37.389 |
|
- type: ndcg_at_100 |
|
value: 34.253 |
|
- type: ndcg_at_1000 |
|
value: 43.059999999999995 |
|
- type: ndcg_at_3 |
|
value: 42.725 |
|
- type: ndcg_at_5 |
|
value: 40.193 |
|
- type: precision_at_1 |
|
value: 47.368 |
|
- type: precision_at_10 |
|
value: 27.988000000000003 |
|
- type: precision_at_100 |
|
value: 8.672 |
|
- type: precision_at_1000 |
|
value: 2.164 |
|
- type: precision_at_3 |
|
value: 40.248 |
|
- type: precision_at_5 |
|
value: 34.737 |
|
- type: recall_at_1 |
|
value: 6.783 |
|
- type: recall_at_10 |
|
value: 17.838 |
|
- type: recall_at_100 |
|
value: 33.672000000000004 |
|
- type: recall_at_1000 |
|
value: 66.166 |
|
- type: recall_at_3 |
|
value: 11.849 |
|
- type: recall_at_5 |
|
value: 14.205000000000002 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB NQ |
|
type: nq |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 31.698999999999998 |
|
- type: map_at_10 |
|
value: 46.556 |
|
- type: map_at_100 |
|
value: 47.652 |
|
- type: map_at_1000 |
|
value: 47.68 |
|
- type: map_at_3 |
|
value: 42.492000000000004 |
|
- type: map_at_5 |
|
value: 44.763999999999996 |
|
- type: mrr_at_1 |
|
value: 35.747 |
|
- type: mrr_at_10 |
|
value: 49.242999999999995 |
|
- type: mrr_at_100 |
|
value: 50.052 |
|
- type: mrr_at_1000 |
|
value: 50.068 |
|
- type: mrr_at_3 |
|
value: 45.867000000000004 |
|
- type: mrr_at_5 |
|
value: 47.778999999999996 |
|
- type: ndcg_at_1 |
|
value: 35.717999999999996 |
|
- type: ndcg_at_10 |
|
value: 54.14600000000001 |
|
- type: ndcg_at_100 |
|
value: 58.672999999999995 |
|
- type: ndcg_at_1000 |
|
value: 59.279 |
|
- type: ndcg_at_3 |
|
value: 46.407 |
|
- type: ndcg_at_5 |
|
value: 50.181 |
|
- type: precision_at_1 |
|
value: 35.717999999999996 |
|
- type: precision_at_10 |
|
value: 8.844000000000001 |
|
- type: precision_at_100 |
|
value: 1.139 |
|
- type: precision_at_1000 |
|
value: 0.12 |
|
- type: precision_at_3 |
|
value: 20.993000000000002 |
|
- type: precision_at_5 |
|
value: 14.791000000000002 |
|
- type: recall_at_1 |
|
value: 31.698999999999998 |
|
- type: recall_at_10 |
|
value: 74.693 |
|
- type: recall_at_100 |
|
value: 94.15299999999999 |
|
- type: recall_at_1000 |
|
value: 98.585 |
|
- type: recall_at_3 |
|
value: 54.388999999999996 |
|
- type: recall_at_5 |
|
value: 63.08200000000001 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB QuoraRetrieval |
|
type: quora |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 71.283 |
|
- type: map_at_10 |
|
value: 85.24000000000001 |
|
- type: map_at_100 |
|
value: 85.882 |
|
- type: map_at_1000 |
|
value: 85.897 |
|
- type: map_at_3 |
|
value: 82.326 |
|
- type: map_at_5 |
|
value: 84.177 |
|
- type: mrr_at_1 |
|
value: 82.21000000000001 |
|
- type: mrr_at_10 |
|
value: 88.228 |
|
- type: mrr_at_100 |
|
value: 88.32 |
|
- type: mrr_at_1000 |
|
value: 88.32 |
|
- type: mrr_at_3 |
|
value: 87.323 |
|
- type: mrr_at_5 |
|
value: 87.94800000000001 |
|
- type: ndcg_at_1 |
|
value: 82.17999999999999 |
|
- type: ndcg_at_10 |
|
value: 88.9 |
|
- type: ndcg_at_100 |
|
value: 90.079 |
|
- type: ndcg_at_1000 |
|
value: 90.158 |
|
- type: ndcg_at_3 |
|
value: 86.18299999999999 |
|
- type: ndcg_at_5 |
|
value: 87.71799999999999 |
|
- type: precision_at_1 |
|
value: 82.17999999999999 |
|
- type: precision_at_10 |
|
value: 13.464 |
|
- type: precision_at_100 |
|
value: 1.533 |
|
- type: precision_at_1000 |
|
value: 0.157 |
|
- type: precision_at_3 |
|
value: 37.693 |
|
- type: precision_at_5 |
|
value: 24.792 |
|
- type: recall_at_1 |
|
value: 71.283 |
|
- type: recall_at_10 |
|
value: 95.742 |
|
- type: recall_at_100 |
|
value: 99.67200000000001 |
|
- type: recall_at_1000 |
|
value: 99.981 |
|
- type: recall_at_3 |
|
value: 87.888 |
|
- type: recall_at_5 |
|
value: 92.24 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB RedditClustering |
|
type: mteb/reddit-clustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 56.24267063669042 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB RedditClusteringP2P |
|
type: mteb/reddit-clustering-p2p |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 62.88056988932578 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB SCIDOCS |
|
type: scidocs |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.903 |
|
- type: map_at_10 |
|
value: 13.202 |
|
- type: map_at_100 |
|
value: 15.5 |
|
- type: map_at_1000 |
|
value: 15.870999999999999 |
|
- type: map_at_3 |
|
value: 9.407 |
|
- type: map_at_5 |
|
value: 11.238 |
|
- type: mrr_at_1 |
|
value: 24.2 |
|
- type: mrr_at_10 |
|
value: 35.867 |
|
- type: mrr_at_100 |
|
value: 37.001 |
|
- type: mrr_at_1000 |
|
value: 37.043 |
|
- type: mrr_at_3 |
|
value: 32.5 |
|
- type: mrr_at_5 |
|
value: 34.35 |
|
- type: ndcg_at_1 |
|
value: 24.2 |
|
- type: ndcg_at_10 |
|
value: 21.731 |
|
- type: ndcg_at_100 |
|
value: 30.7 |
|
- type: ndcg_at_1000 |
|
value: 36.618 |
|
- type: ndcg_at_3 |
|
value: 20.72 |
|
- type: ndcg_at_5 |
|
value: 17.954 |
|
- type: precision_at_1 |
|
value: 24.2 |
|
- type: precision_at_10 |
|
value: 11.33 |
|
- type: precision_at_100 |
|
value: 2.4410000000000003 |
|
- type: precision_at_1000 |
|
value: 0.386 |
|
- type: precision_at_3 |
|
value: 19.667 |
|
- type: precision_at_5 |
|
value: 15.86 |
|
- type: recall_at_1 |
|
value: 4.903 |
|
- type: recall_at_10 |
|
value: 22.962 |
|
- type: recall_at_100 |
|
value: 49.563 |
|
- type: recall_at_1000 |
|
value: 78.238 |
|
- type: recall_at_3 |
|
value: 11.953 |
|
- type: recall_at_5 |
|
value: 16.067999999999998 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB SICK-R |
|
type: mteb/sickr-sts |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.12694254604078 |
|
- type: cos_sim_spearman |
|
value: 80.30141815181918 |
|
- type: euclidean_pearson |
|
value: 81.34015449877128 |
|
- type: euclidean_spearman |
|
value: 80.13984197010849 |
|
- type: manhattan_pearson |
|
value: 81.31767068124086 |
|
- type: manhattan_spearman |
|
value: 80.11720513114103 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS12 |
|
type: mteb/sts12-sts |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.13112984010417 |
|
- type: cos_sim_spearman |
|
value: 78.03063573402875 |
|
- type: euclidean_pearson |
|
value: 83.51928418844804 |
|
- type: euclidean_spearman |
|
value: 78.4045235411144 |
|
- type: manhattan_pearson |
|
value: 83.49981637388689 |
|
- type: manhattan_spearman |
|
value: 78.4042575139372 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS13 |
|
type: mteb/sts13-sts |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.50327987379504 |
|
- type: cos_sim_spearman |
|
value: 84.18556767756205 |
|
- type: euclidean_pearson |
|
value: 82.69684424327679 |
|
- type: euclidean_spearman |
|
value: 83.5368106038335 |
|
- type: manhattan_pearson |
|
value: 82.57967581007374 |
|
- type: manhattan_spearman |
|
value: 83.43009053133697 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS14 |
|
type: mteb/sts14-sts |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.50756863007814 |
|
- type: cos_sim_spearman |
|
value: 82.27204331279108 |
|
- type: euclidean_pearson |
|
value: 81.39535251429741 |
|
- type: euclidean_spearman |
|
value: 81.84386626336239 |
|
- type: manhattan_pearson |
|
value: 81.34281737280695 |
|
- type: manhattan_spearman |
|
value: 81.81149375673166 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS15 |
|
type: mteb/sts15-sts |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.8727714856726 |
|
- type: cos_sim_spearman |
|
value: 87.95738287792312 |
|
- type: euclidean_pearson |
|
value: 86.62920602795887 |
|
- type: euclidean_spearman |
|
value: 87.05207355381243 |
|
- type: manhattan_pearson |
|
value: 86.53587918472225 |
|
- type: manhattan_spearman |
|
value: 86.95382961029586 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS16 |
|
type: mteb/sts16-sts |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.52240359769479 |
|
- type: cos_sim_spearman |
|
value: 85.47685776238286 |
|
- type: euclidean_pearson |
|
value: 84.25815333483058 |
|
- type: euclidean_spearman |
|
value: 85.27415639683198 |
|
- type: manhattan_pearson |
|
value: 84.29127757025637 |
|
- type: manhattan_spearman |
|
value: 85.30226224917351 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS17 (en-en) |
|
type: mteb/sts17-crosslingual-sts |
|
config: en-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.42501708915708 |
|
- type: cos_sim_spearman |
|
value: 86.42276182795041 |
|
- type: euclidean_pearson |
|
value: 86.5408207354761 |
|
- type: euclidean_spearman |
|
value: 85.46096321750838 |
|
- type: manhattan_pearson |
|
value: 86.54177303026881 |
|
- type: manhattan_spearman |
|
value: 85.50313151916117 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (en) |
|
type: mteb/sts22-crosslingual-sts |
|
config: en |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 64.86521089250766 |
|
- type: cos_sim_spearman |
|
value: 65.94868540323003 |
|
- type: euclidean_pearson |
|
value: 67.16569626533084 |
|
- type: euclidean_spearman |
|
value: 66.37667004134917 |
|
- type: manhattan_pearson |
|
value: 67.1482365102333 |
|
- type: manhattan_spearman |
|
value: 66.53240122580029 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STSBenchmark |
|
type: mteb/stsbenchmark-sts |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.64746265365318 |
|
- type: cos_sim_spearman |
|
value: 86.41888825906786 |
|
- type: euclidean_pearson |
|
value: 85.27453642725811 |
|
- type: euclidean_spearman |
|
value: 85.94095796602544 |
|
- type: manhattan_pearson |
|
value: 85.28643660505334 |
|
- type: manhattan_spearman |
|
value: 85.95028003260744 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB SciDocsRR |
|
type: mteb/scidocs-reranking |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 87.48903153618527 |
|
- type: mrr |
|
value: 96.41081503826601 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB SciFact |
|
type: scifact |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 58.594 |
|
- type: map_at_10 |
|
value: 69.296 |
|
- type: map_at_100 |
|
value: 69.782 |
|
- type: map_at_1000 |
|
value: 69.795 |
|
- type: map_at_3 |
|
value: 66.23 |
|
- type: map_at_5 |
|
value: 68.293 |
|
- type: mrr_at_1 |
|
value: 61.667 |
|
- type: mrr_at_10 |
|
value: 70.339 |
|
- type: mrr_at_100 |
|
value: 70.708 |
|
- type: mrr_at_1000 |
|
value: 70.722 |
|
- type: mrr_at_3 |
|
value: 68.0 |
|
- type: mrr_at_5 |
|
value: 69.56700000000001 |
|
- type: ndcg_at_1 |
|
value: 61.667 |
|
- type: ndcg_at_10 |
|
value: 74.039 |
|
- type: ndcg_at_100 |
|
value: 76.103 |
|
- type: ndcg_at_1000 |
|
value: 76.47800000000001 |
|
- type: ndcg_at_3 |
|
value: 68.967 |
|
- type: ndcg_at_5 |
|
value: 71.96900000000001 |
|
- type: precision_at_1 |
|
value: 61.667 |
|
- type: precision_at_10 |
|
value: 9.866999999999999 |
|
- type: precision_at_100 |
|
value: 1.097 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 27.111 |
|
- type: precision_at_5 |
|
value: 18.2 |
|
- type: recall_at_1 |
|
value: 58.594 |
|
- type: recall_at_10 |
|
value: 87.422 |
|
- type: recall_at_100 |
|
value: 96.667 |
|
- type: recall_at_1000 |
|
value: 99.667 |
|
- type: recall_at_3 |
|
value: 74.217 |
|
- type: recall_at_5 |
|
value: 81.539 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
name: MTEB SprintDuplicateQuestions |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.85049504950496 |
|
- type: cos_sim_ap |
|
value: 96.33111544137081 |
|
- type: cos_sim_f1 |
|
value: 92.35443037974684 |
|
- type: cos_sim_precision |
|
value: 93.53846153846153 |
|
- type: cos_sim_recall |
|
value: 91.2 |
|
- type: dot_accuracy |
|
value: 99.82376237623762 |
|
- type: dot_ap |
|
value: 95.38082527310888 |
|
- type: dot_f1 |
|
value: 90.90909090909092 |
|
- type: dot_precision |
|
value: 92.90187891440502 |
|
- type: dot_recall |
|
value: 89.0 |
|
- type: euclidean_accuracy |
|
value: 99.84851485148515 |
|
- type: euclidean_ap |
|
value: 96.32316003996347 |
|
- type: euclidean_f1 |
|
value: 92.2071392659628 |
|
- type: euclidean_precision |
|
value: 92.71991911021233 |
|
- type: euclidean_recall |
|
value: 91.7 |
|
- type: manhattan_accuracy |
|
value: 99.84851485148515 |
|
- type: manhattan_ap |
|
value: 96.3655668249217 |
|
- type: manhattan_f1 |
|
value: 92.18356026222895 |
|
- type: manhattan_precision |
|
value: 92.98067141403867 |
|
- type: manhattan_recall |
|
value: 91.4 |
|
- type: max_accuracy |
|
value: 99.85049504950496 |
|
- type: max_ap |
|
value: 96.3655668249217 |
|
- type: max_f1 |
|
value: 92.35443037974684 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB StackExchangeClustering |
|
type: mteb/stackexchange-clustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 65.94861371629051 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB StackExchangeClusteringP2P |
|
type: mteb/stackexchange-clustering-p2p |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 35.009430451385 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB StackOverflowDupQuestions |
|
type: mteb/stackoverflowdupquestions-reranking |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 54.61164066427969 |
|
- type: mrr |
|
value: 55.49710603938544 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
name: MTEB SummEval |
|
type: mteb/summeval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 30.622620124907662 |
|
- type: cos_sim_spearman |
|
value: 31.0678351356163 |
|
- type: dot_pearson |
|
value: 30.863727693306814 |
|
- type: dot_spearman |
|
value: 31.230306567021255 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB TRECCOVID |
|
type: trec-covid |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.22 |
|
- type: map_at_10 |
|
value: 2.011 |
|
- type: map_at_100 |
|
value: 10.974 |
|
- type: map_at_1000 |
|
value: 25.819 |
|
- type: map_at_3 |
|
value: 0.6649999999999999 |
|
- type: map_at_5 |
|
value: 1.076 |
|
- type: mrr_at_1 |
|
value: 86.0 |
|
- type: mrr_at_10 |
|
value: 91.8 |
|
- type: mrr_at_100 |
|
value: 91.8 |
|
- type: mrr_at_1000 |
|
value: 91.8 |
|
- type: mrr_at_3 |
|
value: 91.0 |
|
- type: mrr_at_5 |
|
value: 91.8 |
|
- type: ndcg_at_1 |
|
value: 82.0 |
|
- type: ndcg_at_10 |
|
value: 78.07300000000001 |
|
- type: ndcg_at_100 |
|
value: 58.231 |
|
- type: ndcg_at_1000 |
|
value: 51.153000000000006 |
|
- type: ndcg_at_3 |
|
value: 81.123 |
|
- type: ndcg_at_5 |
|
value: 81.059 |
|
- type: precision_at_1 |
|
value: 86.0 |
|
- type: precision_at_10 |
|
value: 83.0 |
|
- type: precision_at_100 |
|
value: 59.38 |
|
- type: precision_at_1000 |
|
value: 22.55 |
|
- type: precision_at_3 |
|
value: 87.333 |
|
- type: precision_at_5 |
|
value: 86.8 |
|
- type: recall_at_1 |
|
value: 0.22 |
|
- type: recall_at_10 |
|
value: 2.2079999999999997 |
|
- type: recall_at_100 |
|
value: 14.069 |
|
- type: recall_at_1000 |
|
value: 47.678 |
|
- type: recall_at_3 |
|
value: 0.7040000000000001 |
|
- type: recall_at_5 |
|
value: 1.161 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB Touche2020 |
|
type: webis-touche2020 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.809 |
|
- type: map_at_10 |
|
value: 10.394 |
|
- type: map_at_100 |
|
value: 16.598 |
|
- type: map_at_1000 |
|
value: 18.142 |
|
- type: map_at_3 |
|
value: 5.572 |
|
- type: map_at_5 |
|
value: 7.1370000000000005 |
|
- type: mrr_at_1 |
|
value: 32.653 |
|
- type: mrr_at_10 |
|
value: 46.564 |
|
- type: mrr_at_100 |
|
value: 47.469 |
|
- type: mrr_at_1000 |
|
value: 47.469 |
|
- type: mrr_at_3 |
|
value: 42.177 |
|
- type: mrr_at_5 |
|
value: 44.524 |
|
- type: ndcg_at_1 |
|
value: 30.612000000000002 |
|
- type: ndcg_at_10 |
|
value: 25.701 |
|
- type: ndcg_at_100 |
|
value: 37.532 |
|
- type: ndcg_at_1000 |
|
value: 48.757 |
|
- type: ndcg_at_3 |
|
value: 28.199999999999996 |
|
- type: ndcg_at_5 |
|
value: 25.987 |
|
- type: precision_at_1 |
|
value: 32.653 |
|
- type: precision_at_10 |
|
value: 23.469 |
|
- type: precision_at_100 |
|
value: 7.9799999999999995 |
|
- type: precision_at_1000 |
|
value: 1.5350000000000001 |
|
- type: precision_at_3 |
|
value: 29.932 |
|
- type: precision_at_5 |
|
value: 26.122 |
|
- type: recall_at_1 |
|
value: 2.809 |
|
- type: recall_at_10 |
|
value: 16.887 |
|
- type: recall_at_100 |
|
value: 48.67 |
|
- type: recall_at_1000 |
|
value: 82.89699999999999 |
|
- type: recall_at_3 |
|
value: 6.521000000000001 |
|
- type: recall_at_5 |
|
value: 9.609 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB ToxicConversationsClassification |
|
type: mteb/toxic_conversations_50k |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 71.57860000000001 |
|
- type: ap |
|
value: 13.82629211536393 |
|
- type: f1 |
|
value: 54.59860966183956 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB TweetSentimentExtractionClassification |
|
type: mteb/tweet_sentiment_extraction |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 59.38030560271647 |
|
- type: f1 |
|
value: 59.69685552567865 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB TwentyNewsgroupsClustering |
|
type: mteb/twentynewsgroups-clustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 51.4736717043405 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
name: MTEB TwitterSemEval2015 |
|
type: mteb/twittersemeval2015-pairclassification |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 86.92853311080646 |
|
- type: cos_sim_ap |
|
value: 77.67872502591382 |
|
- type: cos_sim_f1 |
|
value: 70.33941236068895 |
|
- type: cos_sim_precision |
|
value: 67.63273258645884 |
|
- type: cos_sim_recall |
|
value: 73.27176781002639 |
|
- type: dot_accuracy |
|
value: 85.79603027954938 |
|
- type: dot_ap |
|
value: 73.73786190233379 |
|
- type: dot_f1 |
|
value: 67.3437901774235 |
|
- type: dot_precision |
|
value: 65.67201604814443 |
|
- type: dot_recall |
|
value: 69.10290237467018 |
|
- type: euclidean_accuracy |
|
value: 86.94045419324074 |
|
- type: euclidean_ap |
|
value: 77.6687791535167 |
|
- type: euclidean_f1 |
|
value: 70.47209214023542 |
|
- type: euclidean_precision |
|
value: 67.7207492094381 |
|
- type: euclidean_recall |
|
value: 73.45646437994723 |
|
- type: manhattan_accuracy |
|
value: 86.87488823985218 |
|
- type: manhattan_ap |
|
value: 77.63373392430728 |
|
- type: manhattan_f1 |
|
value: 70.40920716112532 |
|
- type: manhattan_precision |
|
value: 68.31265508684864 |
|
- type: manhattan_recall |
|
value: 72.63852242744063 |
|
- type: max_accuracy |
|
value: 86.94045419324074 |
|
- type: max_ap |
|
value: 77.67872502591382 |
|
- type: max_f1 |
|
value: 70.47209214023542 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
name: MTEB TwitterURLCorpus |
|
type: mteb/twitterurlcorpus-pairclassification |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.67155664221679 |
|
- type: cos_sim_ap |
|
value: 85.64591703003417 |
|
- type: cos_sim_f1 |
|
value: 77.59531005352656 |
|
- type: cos_sim_precision |
|
value: 73.60967184801382 |
|
- type: cos_sim_recall |
|
value: 82.03726516784724 |
|
- type: dot_accuracy |
|
value: 88.41541506578181 |
|
- type: dot_ap |
|
value: 84.6482788957769 |
|
- type: dot_f1 |
|
value: 77.04748541466657 |
|
- type: dot_precision |
|
value: 74.02440754931176 |
|
- type: dot_recall |
|
value: 80.3279950723745 |
|
- type: euclidean_accuracy |
|
value: 88.63080684596576 |
|
- type: euclidean_ap |
|
value: 85.44570045321562 |
|
- type: euclidean_f1 |
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value: 77.28769403336106 |
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- type: euclidean_precision |
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value: 72.90600040958427 |
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- type: euclidean_recall |
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value: 82.22975053895904 |
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- type: manhattan_accuracy |
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value: 88.59393798269105 |
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- type: manhattan_ap |
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value: 85.40271361038187 |
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- type: manhattan_f1 |
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value: 77.17606419344392 |
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- type: manhattan_precision |
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value: 72.4447747078295 |
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- type: manhattan_recall |
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value: 82.5685247921158 |
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- type: max_accuracy |
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value: 88.67155664221679 |
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- type: max_ap |
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value: 85.64591703003417 |
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- type: max_f1 |
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value: 77.59531005352656 |
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--- |
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# Neuronx model for [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) |
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This repository contains are [**AWS Inferentia2**](https://aws.amazon.com/ec2/instance-types/inf2/) and [`neuronx`](https://awsdocs-neuron.readthedocs-hosted.com/en/latest/) compatible checkpoint for [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5). You can find detailed information about the base model on its [Model Card](https://huggingface.co/BAAI/bge-base-en-v1.5). |
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## Usage on Amazon SageMaker |
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_coming soon_ |
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## Usage with optimum-neuron |
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```python |
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from optimum.neuron import NeuronModelForFeatureExtraction |
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from transformers import AutoTokenizer |
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import torch |
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import torch_neuronx |
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# Load Model from Hugging Face repository |
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model = NeuronModelForFeatureExtraction.from_pretrained("aws-neuron/bge-base-en-v1-5-seqlen-384-bs-1") |
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tokenizer = AutoTokenizer.from_pretrained("aws-neuron/bge-base-en-v1-5-seqlen-384-bs-1") |
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# sentence input |
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inputs = "Hello, my dog is cute" |
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# Tokenize sentences |
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encoded_input = tokenizer(inputs,return_tensors="pt",truncation=True,max_length=model.config.neuron["static_sequence_length"]) |
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# Compute embeddings |
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with torch.no_grad(): |
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model_output = model(*tuple(encoded_input.values())) |
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# Perform pooling. In this case, cls pooling. |
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sentence_embeddings = model_output[0][:, 0] |
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# normalize embeddings |
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sentence_embeddings = torch.nn.functional.normalize(sentence_embeddings, p=2, dim=1) |
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``` |
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**input_shapes** |
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```json |
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{ |
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"sequence_length": 384, |
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"batch_size": 1 |
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} |
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``` |
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