|
--- |
|
pipeline_tag: sentence-similarity |
|
tags: |
|
- sentence-transformers |
|
- feature-extraction |
|
- sentence-similarity |
|
- mteb |
|
model-index: |
|
- name: SGPT-5.8B-weightedmean-nli-bitfit |
|
results: |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 74.07462686567165 |
|
- type: ap |
|
value: 37.44692407529112 |
|
- type: f1 |
|
value: 68.28971003916419 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification (de) |
|
config: de |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 66.63811563169165 |
|
- type: ap |
|
value: 78.57252079915924 |
|
- type: f1 |
|
value: 64.5543087846584 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification (en-ext) |
|
config: en-ext |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 77.21889055472263 |
|
- type: ap |
|
value: 25.663426367826712 |
|
- type: f1 |
|
value: 64.26265688503176 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification (ja) |
|
config: ja |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 58.06209850107067 |
|
- type: ap |
|
value: 14.028219107023915 |
|
- type: f1 |
|
value: 48.10387189660778 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_polarity |
|
name: MTEB AmazonPolarityClassification |
|
config: default |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 82.30920000000002 |
|
- type: ap |
|
value: 76.88786578621213 |
|
- type: f1 |
|
value: 82.15455656065011 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 41.584 |
|
- type: f1 |
|
value: 41.203137944390114 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (de) |
|
config: de |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 35.288000000000004 |
|
- type: f1 |
|
value: 34.672995558518096 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (es) |
|
config: es |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 38.34 |
|
- type: f1 |
|
value: 37.608755629529455 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (fr) |
|
config: fr |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 37.839999999999996 |
|
- type: f1 |
|
value: 36.86898201563507 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (ja) |
|
config: ja |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 30.936000000000003 |
|
- type: f1 |
|
value: 30.49401738527071 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (zh) |
|
config: zh |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 33.75 |
|
- type: f1 |
|
value: 33.38338946025617 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: arguana |
|
name: MTEB ArguAna |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.727 |
|
- type: map_at_10 |
|
value: 26.740000000000002 |
|
- type: map_at_100 |
|
value: 28.218 |
|
- type: map_at_1000 |
|
value: 28.246 |
|
- type: map_at_3 |
|
value: 21.728 |
|
- type: map_at_5 |
|
value: 24.371000000000002 |
|
- type: ndcg_at_1 |
|
value: 13.727 |
|
- type: ndcg_at_10 |
|
value: 35.07 |
|
- type: ndcg_at_100 |
|
value: 41.947 |
|
- type: ndcg_at_1000 |
|
value: 42.649 |
|
- type: ndcg_at_3 |
|
value: 24.484 |
|
- type: ndcg_at_5 |
|
value: 29.282999999999998 |
|
- type: precision_at_1 |
|
value: 13.727 |
|
- type: precision_at_10 |
|
value: 6.223 |
|
- type: precision_at_100 |
|
value: 0.9369999999999999 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 10.835 |
|
- type: precision_at_5 |
|
value: 8.848 |
|
- type: recall_at_1 |
|
value: 13.727 |
|
- type: recall_at_10 |
|
value: 62.233000000000004 |
|
- type: recall_at_100 |
|
value: 93.67 |
|
- type: recall_at_1000 |
|
value: 99.14699999999999 |
|
- type: recall_at_3 |
|
value: 32.504 |
|
- type: recall_at_5 |
|
value: 44.239 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-p2p |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
metrics: |
|
- type: v_measure |
|
value: 40.553923271901695 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-s2s |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
metrics: |
|
- type: v_measure |
|
value: 32.49323183712211 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/askubuntudupquestions-reranking |
|
name: MTEB AskUbuntuDupQuestions |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map |
|
value: 55.89811361443445 |
|
- type: mrr |
|
value: 70.16235764850724 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/biosses-sts |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.50506557805856 |
|
- type: cos_sim_spearman |
|
value: 79.50000423261176 |
|
- type: euclidean_pearson |
|
value: 75.76190885392926 |
|
- type: euclidean_spearman |
|
value: 76.7330737163434 |
|
- type: manhattan_pearson |
|
value: 75.825318036112 |
|
- type: manhattan_spearman |
|
value: 76.7415076434559 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/bucc-bitext-mining |
|
name: MTEB BUCC (de-en) |
|
config: de-en |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 75.49060542797494 |
|
- type: f1 |
|
value: 75.15379262352123 |
|
- type: precision |
|
value: 74.99391092553932 |
|
- type: recall |
|
value: 75.49060542797494 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/bucc-bitext-mining |
|
name: MTEB BUCC (fr-en) |
|
config: fr-en |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 0.4182258419546555 |
|
- type: f1 |
|
value: 0.4182258419546555 |
|
- type: precision |
|
value: 0.4182258419546555 |
|
- type: recall |
|
value: 0.4182258419546555 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/bucc-bitext-mining |
|
name: MTEB BUCC (ru-en) |
|
config: ru-en |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 0.013855213023900243 |
|
- type: f1 |
|
value: 0.0115460108532502 |
|
- type: precision |
|
value: 0.010391409767925183 |
|
- type: recall |
|
value: 0.013855213023900243 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/bucc-bitext-mining |
|
name: MTEB BUCC (zh-en) |
|
config: zh-en |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 0.315955766192733 |
|
- type: f1 |
|
value: 0.315955766192733 |
|
- type: precision |
|
value: 0.315955766192733 |
|
- type: recall |
|
value: 0.315955766192733 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/banking77 |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 81.74025974025973 |
|
- type: f1 |
|
value: 81.66568824876 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-p2p |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
metrics: |
|
- type: v_measure |
|
value: 33.59451202614059 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-s2s |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
metrics: |
|
- type: v_measure |
|
value: 29.128241446157165 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.715 |
|
- type: map_at_10 |
|
value: 35.007 |
|
- type: map_at_100 |
|
value: 36.352000000000004 |
|
- type: map_at_1000 |
|
value: 36.51 |
|
- type: map_at_3 |
|
value: 32.257999999999996 |
|
- type: map_at_5 |
|
value: 33.595000000000006 |
|
- type: ndcg_at_1 |
|
value: 33.906 |
|
- type: ndcg_at_10 |
|
value: 40.353 |
|
- type: ndcg_at_100 |
|
value: 45.562999999999995 |
|
- type: ndcg_at_1000 |
|
value: 48.454 |
|
- type: ndcg_at_3 |
|
value: 36.349 |
|
- type: ndcg_at_5 |
|
value: 37.856 |
|
- type: precision_at_1 |
|
value: 33.906 |
|
- type: precision_at_10 |
|
value: 7.854 |
|
- type: precision_at_100 |
|
value: 1.29 |
|
- type: precision_at_1000 |
|
value: 0.188 |
|
- type: precision_at_3 |
|
value: 17.549 |
|
- type: precision_at_5 |
|
value: 12.561 |
|
- type: recall_at_1 |
|
value: 26.715 |
|
- type: recall_at_10 |
|
value: 49.508 |
|
- type: recall_at_100 |
|
value: 71.76599999999999 |
|
- type: recall_at_1000 |
|
value: 91.118 |
|
- type: recall_at_3 |
|
value: 37.356 |
|
- type: recall_at_5 |
|
value: 41.836 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 19.663 |
|
- type: map_at_10 |
|
value: 27.086 |
|
- type: map_at_100 |
|
value: 28.066999999999997 |
|
- type: map_at_1000 |
|
value: 28.18 |
|
- type: map_at_3 |
|
value: 24.819 |
|
- type: map_at_5 |
|
value: 26.332 |
|
- type: ndcg_at_1 |
|
value: 25.732 |
|
- type: ndcg_at_10 |
|
value: 31.613999999999997 |
|
- type: ndcg_at_100 |
|
value: 35.757 |
|
- type: ndcg_at_1000 |
|
value: 38.21 |
|
- type: ndcg_at_3 |
|
value: 28.332 |
|
- type: ndcg_at_5 |
|
value: 30.264000000000003 |
|
- type: precision_at_1 |
|
value: 25.732 |
|
- type: precision_at_10 |
|
value: 6.038 |
|
- type: precision_at_100 |
|
value: 1.034 |
|
- type: precision_at_1000 |
|
value: 0.149 |
|
- type: precision_at_3 |
|
value: 13.864 |
|
- type: precision_at_5 |
|
value: 10.241999999999999 |
|
- type: recall_at_1 |
|
value: 19.663 |
|
- type: recall_at_10 |
|
value: 39.585 |
|
- type: recall_at_100 |
|
value: 57.718 |
|
- type: recall_at_1000 |
|
value: 74.26700000000001 |
|
- type: recall_at_3 |
|
value: 29.845 |
|
- type: recall_at_5 |
|
value: 35.105 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 30.125 |
|
- type: map_at_10 |
|
value: 39.824 |
|
- type: map_at_100 |
|
value: 40.935 |
|
- type: map_at_1000 |
|
value: 41.019 |
|
- type: map_at_3 |
|
value: 37.144 |
|
- type: map_at_5 |
|
value: 38.647999999999996 |
|
- type: ndcg_at_1 |
|
value: 34.922 |
|
- type: ndcg_at_10 |
|
value: 45.072 |
|
- type: ndcg_at_100 |
|
value: 50.046 |
|
- type: ndcg_at_1000 |
|
value: 51.895 |
|
- type: ndcg_at_3 |
|
value: 40.251 |
|
- type: ndcg_at_5 |
|
value: 42.581 |
|
- type: precision_at_1 |
|
value: 34.922 |
|
- type: precision_at_10 |
|
value: 7.303999999999999 |
|
- type: precision_at_100 |
|
value: 1.0739999999999998 |
|
- type: precision_at_1000 |
|
value: 0.13 |
|
- type: precision_at_3 |
|
value: 17.994 |
|
- type: precision_at_5 |
|
value: 12.475999999999999 |
|
- type: recall_at_1 |
|
value: 30.125 |
|
- type: recall_at_10 |
|
value: 57.253 |
|
- type: recall_at_100 |
|
value: 79.35799999999999 |
|
- type: recall_at_1000 |
|
value: 92.523 |
|
- type: recall_at_3 |
|
value: 44.088 |
|
- type: recall_at_5 |
|
value: 49.893 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 16.298000000000002 |
|
- type: map_at_10 |
|
value: 21.479 |
|
- type: map_at_100 |
|
value: 22.387 |
|
- type: map_at_1000 |
|
value: 22.483 |
|
- type: map_at_3 |
|
value: 19.743 |
|
- type: map_at_5 |
|
value: 20.444000000000003 |
|
- type: ndcg_at_1 |
|
value: 17.740000000000002 |
|
- type: ndcg_at_10 |
|
value: 24.887 |
|
- type: ndcg_at_100 |
|
value: 29.544999999999998 |
|
- type: ndcg_at_1000 |
|
value: 32.417 |
|
- type: ndcg_at_3 |
|
value: 21.274 |
|
- type: ndcg_at_5 |
|
value: 22.399 |
|
- type: precision_at_1 |
|
value: 17.740000000000002 |
|
- type: precision_at_10 |
|
value: 3.932 |
|
- type: precision_at_100 |
|
value: 0.666 |
|
- type: precision_at_1000 |
|
value: 0.094 |
|
- type: precision_at_3 |
|
value: 8.927 |
|
- type: precision_at_5 |
|
value: 6.056 |
|
- type: recall_at_1 |
|
value: 16.298000000000002 |
|
- type: recall_at_10 |
|
value: 34.031 |
|
- type: recall_at_100 |
|
value: 55.769000000000005 |
|
- type: recall_at_1000 |
|
value: 78.19500000000001 |
|
- type: recall_at_3 |
|
value: 23.799999999999997 |
|
- type: recall_at_5 |
|
value: 26.562 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.958 |
|
- type: map_at_10 |
|
value: 16.999 |
|
- type: map_at_100 |
|
value: 17.979 |
|
- type: map_at_1000 |
|
value: 18.112000000000002 |
|
- type: map_at_3 |
|
value: 15.010000000000002 |
|
- type: map_at_5 |
|
value: 16.256999999999998 |
|
- type: ndcg_at_1 |
|
value: 14.179 |
|
- type: ndcg_at_10 |
|
value: 20.985 |
|
- type: ndcg_at_100 |
|
value: 26.216 |
|
- type: ndcg_at_1000 |
|
value: 29.675 |
|
- type: ndcg_at_3 |
|
value: 17.28 |
|
- type: ndcg_at_5 |
|
value: 19.301 |
|
- type: precision_at_1 |
|
value: 14.179 |
|
- type: precision_at_10 |
|
value: 3.968 |
|
- type: precision_at_100 |
|
value: 0.784 |
|
- type: precision_at_1000 |
|
value: 0.121 |
|
- type: precision_at_3 |
|
value: 8.541 |
|
- type: precision_at_5 |
|
value: 6.468 |
|
- type: recall_at_1 |
|
value: 10.958 |
|
- type: recall_at_10 |
|
value: 29.903000000000002 |
|
- type: recall_at_100 |
|
value: 53.413 |
|
- type: recall_at_1000 |
|
value: 78.74799999999999 |
|
- type: recall_at_3 |
|
value: 19.717000000000002 |
|
- type: recall_at_5 |
|
value: 24.817 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.217 |
|
- type: map_at_10 |
|
value: 29.677 |
|
- type: map_at_100 |
|
value: 30.928 |
|
- type: map_at_1000 |
|
value: 31.063000000000002 |
|
- type: map_at_3 |
|
value: 26.611 |
|
- type: map_at_5 |
|
value: 28.463 |
|
- type: ndcg_at_1 |
|
value: 26.083000000000002 |
|
- type: ndcg_at_10 |
|
value: 35.217 |
|
- type: ndcg_at_100 |
|
value: 40.715 |
|
- type: ndcg_at_1000 |
|
value: 43.559 |
|
- type: ndcg_at_3 |
|
value: 30.080000000000002 |
|
- type: ndcg_at_5 |
|
value: 32.701 |
|
- type: precision_at_1 |
|
value: 26.083000000000002 |
|
- type: precision_at_10 |
|
value: 6.622 |
|
- type: precision_at_100 |
|
value: 1.115 |
|
- type: precision_at_1000 |
|
value: 0.156 |
|
- type: precision_at_3 |
|
value: 14.629 |
|
- type: precision_at_5 |
|
value: 10.837 |
|
- type: recall_at_1 |
|
value: 21.217 |
|
- type: recall_at_10 |
|
value: 47.031 |
|
- type: recall_at_100 |
|
value: 70.378 |
|
- type: recall_at_1000 |
|
value: 89.704 |
|
- type: recall_at_3 |
|
value: 32.427 |
|
- type: recall_at_5 |
|
value: 39.31 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 19.274 |
|
- type: map_at_10 |
|
value: 26.398 |
|
- type: map_at_100 |
|
value: 27.711000000000002 |
|
- type: map_at_1000 |
|
value: 27.833000000000002 |
|
- type: map_at_3 |
|
value: 24.294 |
|
- type: map_at_5 |
|
value: 25.385 |
|
- type: ndcg_at_1 |
|
value: 24.886 |
|
- type: ndcg_at_10 |
|
value: 30.909 |
|
- type: ndcg_at_100 |
|
value: 36.941 |
|
- type: ndcg_at_1000 |
|
value: 39.838 |
|
- type: ndcg_at_3 |
|
value: 27.455000000000002 |
|
- type: ndcg_at_5 |
|
value: 28.828 |
|
- type: precision_at_1 |
|
value: 24.886 |
|
- type: precision_at_10 |
|
value: 5.6739999999999995 |
|
- type: precision_at_100 |
|
value: 1.0290000000000001 |
|
- type: precision_at_1000 |
|
value: 0.146 |
|
- type: precision_at_3 |
|
value: 13.242 |
|
- type: precision_at_5 |
|
value: 9.292 |
|
- type: recall_at_1 |
|
value: 19.274 |
|
- type: recall_at_10 |
|
value: 39.643 |
|
- type: recall_at_100 |
|
value: 66.091 |
|
- type: recall_at_1000 |
|
value: 86.547 |
|
- type: recall_at_3 |
|
value: 29.602 |
|
- type: recall_at_5 |
|
value: 33.561 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.653666666666666 |
|
- type: map_at_10 |
|
value: 25.606666666666666 |
|
- type: map_at_100 |
|
value: 26.669333333333334 |
|
- type: map_at_1000 |
|
value: 26.795833333333334 |
|
- type: map_at_3 |
|
value: 23.43433333333333 |
|
- type: map_at_5 |
|
value: 24.609666666666666 |
|
- type: ndcg_at_1 |
|
value: 22.742083333333333 |
|
- type: ndcg_at_10 |
|
value: 29.978333333333335 |
|
- type: ndcg_at_100 |
|
value: 34.89808333333333 |
|
- type: ndcg_at_1000 |
|
value: 37.806583333333336 |
|
- type: ndcg_at_3 |
|
value: 26.223666666666674 |
|
- type: ndcg_at_5 |
|
value: 27.91033333333333 |
|
- type: precision_at_1 |
|
value: 22.742083333333333 |
|
- type: precision_at_10 |
|
value: 5.397083333333334 |
|
- type: precision_at_100 |
|
value: 0.9340000000000002 |
|
- type: precision_at_1000 |
|
value: 0.13691666666666663 |
|
- type: precision_at_3 |
|
value: 12.331083333333332 |
|
- type: precision_at_5 |
|
value: 8.805499999999999 |
|
- type: recall_at_1 |
|
value: 18.653666666666666 |
|
- type: recall_at_10 |
|
value: 39.22625000000001 |
|
- type: recall_at_100 |
|
value: 61.31049999999999 |
|
- type: recall_at_1000 |
|
value: 82.19058333333334 |
|
- type: recall_at_3 |
|
value: 28.517333333333333 |
|
- type: recall_at_5 |
|
value: 32.9565 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 16.07 |
|
- type: map_at_10 |
|
value: 21.509 |
|
- type: map_at_100 |
|
value: 22.335 |
|
- type: map_at_1000 |
|
value: 22.437 |
|
- type: map_at_3 |
|
value: 19.717000000000002 |
|
- type: map_at_5 |
|
value: 20.574 |
|
- type: ndcg_at_1 |
|
value: 18.865000000000002 |
|
- type: ndcg_at_10 |
|
value: 25.135999999999996 |
|
- type: ndcg_at_100 |
|
value: 29.483999999999998 |
|
- type: ndcg_at_1000 |
|
value: 32.303 |
|
- type: ndcg_at_3 |
|
value: 21.719 |
|
- type: ndcg_at_5 |
|
value: 23.039 |
|
- type: precision_at_1 |
|
value: 18.865000000000002 |
|
- type: precision_at_10 |
|
value: 4.263999999999999 |
|
- type: precision_at_100 |
|
value: 0.696 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 9.866999999999999 |
|
- type: precision_at_5 |
|
value: 6.902 |
|
- type: recall_at_1 |
|
value: 16.07 |
|
- type: recall_at_10 |
|
value: 33.661 |
|
- type: recall_at_100 |
|
value: 54.001999999999995 |
|
- type: recall_at_1000 |
|
value: 75.564 |
|
- type: recall_at_3 |
|
value: 23.956 |
|
- type: recall_at_5 |
|
value: 27.264 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.847 |
|
- type: map_at_10 |
|
value: 15.518 |
|
- type: map_at_100 |
|
value: 16.384 |
|
- type: map_at_1000 |
|
value: 16.506 |
|
- type: map_at_3 |
|
value: 14.093 |
|
- type: map_at_5 |
|
value: 14.868 |
|
- type: ndcg_at_1 |
|
value: 13.764999999999999 |
|
- type: ndcg_at_10 |
|
value: 18.766 |
|
- type: ndcg_at_100 |
|
value: 23.076 |
|
- type: ndcg_at_1000 |
|
value: 26.344 |
|
- type: ndcg_at_3 |
|
value: 16.150000000000002 |
|
- type: ndcg_at_5 |
|
value: 17.373 |
|
- type: precision_at_1 |
|
value: 13.764999999999999 |
|
- type: precision_at_10 |
|
value: 3.572 |
|
- type: precision_at_100 |
|
value: 0.6779999999999999 |
|
- type: precision_at_1000 |
|
value: 0.11199999999999999 |
|
- type: precision_at_3 |
|
value: 7.88 |
|
- type: precision_at_5 |
|
value: 5.712 |
|
- type: recall_at_1 |
|
value: 10.847 |
|
- type: recall_at_10 |
|
value: 25.141999999999996 |
|
- type: recall_at_100 |
|
value: 44.847 |
|
- type: recall_at_1000 |
|
value: 68.92099999999999 |
|
- type: recall_at_3 |
|
value: 17.721999999999998 |
|
- type: recall_at_5 |
|
value: 20.968999999999998 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.377 |
|
- type: map_at_10 |
|
value: 26.005 |
|
- type: map_at_100 |
|
value: 26.996 |
|
- type: map_at_1000 |
|
value: 27.116 |
|
- type: map_at_3 |
|
value: 23.712 |
|
- type: map_at_5 |
|
value: 24.859 |
|
- type: ndcg_at_1 |
|
value: 22.201 |
|
- type: ndcg_at_10 |
|
value: 30.635 |
|
- type: ndcg_at_100 |
|
value: 35.623 |
|
- type: ndcg_at_1000 |
|
value: 38.551 |
|
- type: ndcg_at_3 |
|
value: 26.565 |
|
- type: ndcg_at_5 |
|
value: 28.28 |
|
- type: precision_at_1 |
|
value: 22.201 |
|
- type: precision_at_10 |
|
value: 5.41 |
|
- type: precision_at_100 |
|
value: 0.88 |
|
- type: precision_at_1000 |
|
value: 0.125 |
|
- type: precision_at_3 |
|
value: 12.531 |
|
- type: precision_at_5 |
|
value: 8.806 |
|
- type: recall_at_1 |
|
value: 18.377 |
|
- type: recall_at_10 |
|
value: 40.908 |
|
- type: recall_at_100 |
|
value: 63.563 |
|
- type: recall_at_1000 |
|
value: 84.503 |
|
- type: recall_at_3 |
|
value: 29.793999999999997 |
|
- type: recall_at_5 |
|
value: 34.144999999999996 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.246 |
|
- type: map_at_10 |
|
value: 27.528000000000002 |
|
- type: map_at_100 |
|
value: 28.78 |
|
- type: map_at_1000 |
|
value: 29.002 |
|
- type: map_at_3 |
|
value: 25.226 |
|
- type: map_at_5 |
|
value: 26.355 |
|
- type: ndcg_at_1 |
|
value: 25.099 |
|
- type: ndcg_at_10 |
|
value: 32.421 |
|
- type: ndcg_at_100 |
|
value: 37.2 |
|
- type: ndcg_at_1000 |
|
value: 40.693 |
|
- type: ndcg_at_3 |
|
value: 28.768 |
|
- type: ndcg_at_5 |
|
value: 30.23 |
|
- type: precision_at_1 |
|
value: 25.099 |
|
- type: precision_at_10 |
|
value: 6.245 |
|
- type: precision_at_100 |
|
value: 1.269 |
|
- type: precision_at_1000 |
|
value: 0.218 |
|
- type: precision_at_3 |
|
value: 13.767999999999999 |
|
- type: precision_at_5 |
|
value: 9.881 |
|
- type: recall_at_1 |
|
value: 20.246 |
|
- type: recall_at_10 |
|
value: 41.336 |
|
- type: recall_at_100 |
|
value: 63.098 |
|
- type: recall_at_1000 |
|
value: 86.473 |
|
- type: recall_at_3 |
|
value: 30.069000000000003 |
|
- type: recall_at_5 |
|
value: 34.262 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.054 |
|
- type: map_at_10 |
|
value: 20.25 |
|
- type: map_at_100 |
|
value: 21.178 |
|
- type: map_at_1000 |
|
value: 21.288999999999998 |
|
- type: map_at_3 |
|
value: 18.584999999999997 |
|
- type: map_at_5 |
|
value: 19.536 |
|
- type: ndcg_at_1 |
|
value: 15.527 |
|
- type: ndcg_at_10 |
|
value: 23.745 |
|
- type: ndcg_at_100 |
|
value: 28.610999999999997 |
|
- type: ndcg_at_1000 |
|
value: 31.740000000000002 |
|
- type: ndcg_at_3 |
|
value: 20.461 |
|
- type: ndcg_at_5 |
|
value: 22.072 |
|
- type: precision_at_1 |
|
value: 15.527 |
|
- type: precision_at_10 |
|
value: 3.882 |
|
- type: precision_at_100 |
|
value: 0.6930000000000001 |
|
- type: precision_at_1000 |
|
value: 0.104 |
|
- type: precision_at_3 |
|
value: 9.181000000000001 |
|
- type: precision_at_5 |
|
value: 6.433 |
|
- type: recall_at_1 |
|
value: 14.054 |
|
- type: recall_at_10 |
|
value: 32.714 |
|
- type: recall_at_100 |
|
value: 55.723 |
|
- type: recall_at_1000 |
|
value: 79.72399999999999 |
|
- type: recall_at_3 |
|
value: 23.832 |
|
- type: recall_at_5 |
|
value: 27.754 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: climate-fever |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.122 |
|
- type: map_at_10 |
|
value: 11.556 |
|
- type: map_at_100 |
|
value: 12.998000000000001 |
|
- type: map_at_1000 |
|
value: 13.202 |
|
- type: map_at_3 |
|
value: 9.657 |
|
- type: map_at_5 |
|
value: 10.585 |
|
- type: ndcg_at_1 |
|
value: 15.049000000000001 |
|
- type: ndcg_at_10 |
|
value: 17.574 |
|
- type: ndcg_at_100 |
|
value: 24.465999999999998 |
|
- type: ndcg_at_1000 |
|
value: 28.511999999999997 |
|
- type: ndcg_at_3 |
|
value: 13.931 |
|
- type: ndcg_at_5 |
|
value: 15.112 |
|
- type: precision_at_1 |
|
value: 15.049000000000001 |
|
- type: precision_at_10 |
|
value: 5.831 |
|
- type: precision_at_100 |
|
value: 1.322 |
|
- type: precision_at_1000 |
|
value: 0.20500000000000002 |
|
- type: precision_at_3 |
|
value: 10.749 |
|
- type: precision_at_5 |
|
value: 8.365 |
|
- type: recall_at_1 |
|
value: 6.122 |
|
- type: recall_at_10 |
|
value: 22.207 |
|
- type: recall_at_100 |
|
value: 47.08 |
|
- type: recall_at_1000 |
|
value: 70.182 |
|
- type: recall_at_3 |
|
value: 13.416 |
|
- type: recall_at_5 |
|
value: 16.672 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: dbpedia-entity |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.672 |
|
- type: map_at_10 |
|
value: 10.534 |
|
- type: map_at_100 |
|
value: 14.798 |
|
- type: map_at_1000 |
|
value: 15.927 |
|
- type: map_at_3 |
|
value: 7.317 |
|
- type: map_at_5 |
|
value: 8.726 |
|
- type: ndcg_at_1 |
|
value: 36.5 |
|
- type: ndcg_at_10 |
|
value: 26.098 |
|
- type: ndcg_at_100 |
|
value: 29.215999999999998 |
|
- type: ndcg_at_1000 |
|
value: 36.254999999999995 |
|
- type: ndcg_at_3 |
|
value: 29.247 |
|
- type: ndcg_at_5 |
|
value: 27.692 |
|
- type: precision_at_1 |
|
value: 47.25 |
|
- type: precision_at_10 |
|
value: 22.625 |
|
- type: precision_at_100 |
|
value: 7.042 |
|
- type: precision_at_1000 |
|
value: 1.6129999999999998 |
|
- type: precision_at_3 |
|
value: 34.083000000000006 |
|
- type: precision_at_5 |
|
value: 29.5 |
|
- type: recall_at_1 |
|
value: 4.672 |
|
- type: recall_at_10 |
|
value: 15.638 |
|
- type: recall_at_100 |
|
value: 36.228 |
|
- type: recall_at_1000 |
|
value: 58.831 |
|
- type: recall_at_3 |
|
value: 8.578 |
|
- type: recall_at_5 |
|
value: 11.18 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/emotion |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 49.919999999999995 |
|
- type: f1 |
|
value: 45.37973678791632 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fever |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.801000000000002 |
|
- type: map_at_10 |
|
value: 33.941 |
|
- type: map_at_100 |
|
value: 34.73 |
|
- type: map_at_1000 |
|
value: 34.793 |
|
- type: map_at_3 |
|
value: 31.705 |
|
- type: map_at_5 |
|
value: 33.047 |
|
- type: ndcg_at_1 |
|
value: 27.933000000000003 |
|
- type: ndcg_at_10 |
|
value: 38.644 |
|
- type: ndcg_at_100 |
|
value: 42.594 |
|
- type: ndcg_at_1000 |
|
value: 44.352000000000004 |
|
- type: ndcg_at_3 |
|
value: 34.199 |
|
- type: ndcg_at_5 |
|
value: 36.573 |
|
- type: precision_at_1 |
|
value: 27.933000000000003 |
|
- type: precision_at_10 |
|
value: 5.603000000000001 |
|
- type: precision_at_100 |
|
value: 0.773 |
|
- type: precision_at_1000 |
|
value: 0.094 |
|
- type: precision_at_3 |
|
value: 14.171 |
|
- type: precision_at_5 |
|
value: 9.786999999999999 |
|
- type: recall_at_1 |
|
value: 25.801000000000002 |
|
- type: recall_at_10 |
|
value: 50.876 |
|
- type: recall_at_100 |
|
value: 69.253 |
|
- type: recall_at_1000 |
|
value: 82.907 |
|
- type: recall_at_3 |
|
value: 38.879000000000005 |
|
- type: recall_at_5 |
|
value: 44.651999999999994 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fiqa |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 9.142 |
|
- type: map_at_10 |
|
value: 13.841999999999999 |
|
- type: map_at_100 |
|
value: 14.960999999999999 |
|
- type: map_at_1000 |
|
value: 15.187000000000001 |
|
- type: map_at_3 |
|
value: 11.966000000000001 |
|
- type: map_at_5 |
|
value: 12.921 |
|
- type: ndcg_at_1 |
|
value: 18.364 |
|
- type: ndcg_at_10 |
|
value: 18.590999999999998 |
|
- type: ndcg_at_100 |
|
value: 24.153 |
|
- type: ndcg_at_1000 |
|
value: 29.104000000000003 |
|
- type: ndcg_at_3 |
|
value: 16.323 |
|
- type: ndcg_at_5 |
|
value: 17.000999999999998 |
|
- type: precision_at_1 |
|
value: 18.364 |
|
- type: precision_at_10 |
|
value: 5.216 |
|
- type: precision_at_100 |
|
value: 1.09 |
|
- type: precision_at_1000 |
|
value: 0.193 |
|
- type: precision_at_3 |
|
value: 10.751 |
|
- type: precision_at_5 |
|
value: 7.932 |
|
- type: recall_at_1 |
|
value: 9.142 |
|
- type: recall_at_10 |
|
value: 22.747 |
|
- type: recall_at_100 |
|
value: 44.585 |
|
- type: recall_at_1000 |
|
value: 75.481 |
|
- type: recall_at_3 |
|
value: 14.602 |
|
- type: recall_at_5 |
|
value: 17.957 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: hotpotqa |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.677 |
|
- type: map_at_10 |
|
value: 26.616 |
|
- type: map_at_100 |
|
value: 27.605 |
|
- type: map_at_1000 |
|
value: 27.711999999999996 |
|
- type: map_at_3 |
|
value: 24.396 |
|
- type: map_at_5 |
|
value: 25.627 |
|
- type: ndcg_at_1 |
|
value: 37.352999999999994 |
|
- type: ndcg_at_10 |
|
value: 33.995 |
|
- type: ndcg_at_100 |
|
value: 38.423 |
|
- type: ndcg_at_1000 |
|
value: 40.947 |
|
- type: ndcg_at_3 |
|
value: 29.885 |
|
- type: ndcg_at_5 |
|
value: 31.874999999999996 |
|
- type: precision_at_1 |
|
value: 37.352999999999994 |
|
- type: precision_at_10 |
|
value: 7.539999999999999 |
|
- type: precision_at_100 |
|
value: 1.107 |
|
- type: precision_at_1000 |
|
value: 0.145 |
|
- type: precision_at_3 |
|
value: 18.938 |
|
- type: precision_at_5 |
|
value: 12.943 |
|
- type: recall_at_1 |
|
value: 18.677 |
|
- type: recall_at_10 |
|
value: 37.698 |
|
- type: recall_at_100 |
|
value: 55.354000000000006 |
|
- type: recall_at_1000 |
|
value: 72.255 |
|
- type: recall_at_3 |
|
value: 28.406 |
|
- type: recall_at_5 |
|
value: 32.357 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/imdb |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 74.3292 |
|
- type: ap |
|
value: 68.30186110189658 |
|
- type: f1 |
|
value: 74.20709636944783 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: msmarco |
|
name: MTEB MSMARCO |
|
config: default |
|
split: validation |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.889000000000001 |
|
- type: map_at_10 |
|
value: 12.321 |
|
- type: map_at_100 |
|
value: 13.416 |
|
- type: map_at_1000 |
|
value: 13.525 |
|
- type: map_at_3 |
|
value: 10.205 |
|
- type: map_at_5 |
|
value: 11.342 |
|
- type: ndcg_at_1 |
|
value: 7.092 |
|
- type: ndcg_at_10 |
|
value: 15.827 |
|
- type: ndcg_at_100 |
|
value: 21.72 |
|
- type: ndcg_at_1000 |
|
value: 24.836 |
|
- type: ndcg_at_3 |
|
value: 11.393 |
|
- type: ndcg_at_5 |
|
value: 13.462 |
|
- type: precision_at_1 |
|
value: 7.092 |
|
- type: precision_at_10 |
|
value: 2.7969999999999997 |
|
- type: precision_at_100 |
|
value: 0.583 |
|
- type: precision_at_1000 |
|
value: 0.08499999999999999 |
|
- type: precision_at_3 |
|
value: 5.019 |
|
- type: precision_at_5 |
|
value: 4.06 |
|
- type: recall_at_1 |
|
value: 6.889000000000001 |
|
- type: recall_at_10 |
|
value: 26.791999999999998 |
|
- type: recall_at_100 |
|
value: 55.371 |
|
- type: recall_at_1000 |
|
value: 80.12899999999999 |
|
- type: recall_at_3 |
|
value: 14.573 |
|
- type: recall_at_5 |
|
value: 19.557 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 89.6374829001368 |
|
- type: f1 |
|
value: 89.20878379358307 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (de) |
|
config: de |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 84.54212454212454 |
|
- type: f1 |
|
value: 82.81080100037023 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (es) |
|
config: es |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 86.46430953969313 |
|
- type: f1 |
|
value: 86.00019824223267 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (fr) |
|
config: fr |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 81.31850923896022 |
|
- type: f1 |
|
value: 81.07860454762863 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (hi) |
|
config: hi |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 58.23234134098243 |
|
- type: f1 |
|
value: 56.63845098081841 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (th) |
|
config: th |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 72.28571428571429 |
|
- type: f1 |
|
value: 70.95796714592039 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 70.68171454628363 |
|
- type: f1 |
|
value: 52.57188062729139 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (de) |
|
config: de |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 60.521273598196665 |
|
- type: f1 |
|
value: 42.70492970339204 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (es) |
|
config: es |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 64.32288192128087 |
|
- type: f1 |
|
value: 45.97360620220273 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (fr) |
|
config: fr |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 58.67209520826808 |
|
- type: f1 |
|
value: 42.82844991304579 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (hi) |
|
config: hi |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 41.95769092864826 |
|
- type: f1 |
|
value: 28.914127631431263 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (th) |
|
config: th |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 55.28390596745027 |
|
- type: f1 |
|
value: 38.33899250561289 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 70.00336247478144 |
|
- type: f1 |
|
value: 68.72041942191649 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 75.0268997982515 |
|
- type: f1 |
|
value: 75.29844481506652 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-p2p |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
metrics: |
|
- type: v_measure |
|
value: 30.327566856300813 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-s2s |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
metrics: |
|
- type: v_measure |
|
value: 28.01650210863619 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/mind_small |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map |
|
value: 31.11041256752524 |
|
- type: mrr |
|
value: 32.14172939750204 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nfcorpus |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 3.527 |
|
- type: map_at_10 |
|
value: 9.283 |
|
- type: map_at_100 |
|
value: 11.995000000000001 |
|
- type: map_at_1000 |
|
value: 13.33 |
|
- type: map_at_3 |
|
value: 6.223 |
|
- type: map_at_5 |
|
value: 7.68 |
|
- type: ndcg_at_1 |
|
value: 36.223 |
|
- type: ndcg_at_10 |
|
value: 28.255999999999997 |
|
- type: ndcg_at_100 |
|
value: 26.355 |
|
- type: ndcg_at_1000 |
|
value: 35.536 |
|
- type: ndcg_at_3 |
|
value: 31.962000000000003 |
|
- type: ndcg_at_5 |
|
value: 30.61 |
|
- type: precision_at_1 |
|
value: 37.771 |
|
- type: precision_at_10 |
|
value: 21.889 |
|
- type: precision_at_100 |
|
value: 7.1080000000000005 |
|
- type: precision_at_1000 |
|
value: 1.989 |
|
- type: precision_at_3 |
|
value: 30.857 |
|
- type: precision_at_5 |
|
value: 27.307 |
|
- type: recall_at_1 |
|
value: 3.527 |
|
- type: recall_at_10 |
|
value: 14.015 |
|
- type: recall_at_100 |
|
value: 28.402 |
|
- type: recall_at_1000 |
|
value: 59.795 |
|
- type: recall_at_3 |
|
value: 7.5969999999999995 |
|
- type: recall_at_5 |
|
value: 10.641 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nq |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.631 |
|
- type: map_at_10 |
|
value: 19.532 |
|
- type: map_at_100 |
|
value: 20.821 |
|
- type: map_at_1000 |
|
value: 20.910999999999998 |
|
- type: map_at_3 |
|
value: 16.597 |
|
- type: map_at_5 |
|
value: 18.197 |
|
- type: ndcg_at_1 |
|
value: 13.413 |
|
- type: ndcg_at_10 |
|
value: 24.628 |
|
- type: ndcg_at_100 |
|
value: 30.883 |
|
- type: ndcg_at_1000 |
|
value: 33.216 |
|
- type: ndcg_at_3 |
|
value: 18.697 |
|
- type: ndcg_at_5 |
|
value: 21.501 |
|
- type: precision_at_1 |
|
value: 13.413 |
|
- type: precision_at_10 |
|
value: 4.571 |
|
- type: precision_at_100 |
|
value: 0.812 |
|
- type: precision_at_1000 |
|
value: 0.10300000000000001 |
|
- type: precision_at_3 |
|
value: 8.845 |
|
- type: precision_at_5 |
|
value: 6.889000000000001 |
|
- type: recall_at_1 |
|
value: 11.631 |
|
- type: recall_at_10 |
|
value: 38.429 |
|
- type: recall_at_100 |
|
value: 67.009 |
|
- type: recall_at_1000 |
|
value: 84.796 |
|
- type: recall_at_3 |
|
value: 22.74 |
|
- type: recall_at_5 |
|
value: 29.266 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: quora |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 66.64 |
|
- type: map_at_10 |
|
value: 80.394 |
|
- type: map_at_100 |
|
value: 81.099 |
|
- type: map_at_1000 |
|
value: 81.122 |
|
- type: map_at_3 |
|
value: 77.289 |
|
- type: map_at_5 |
|
value: 79.25999999999999 |
|
- type: ndcg_at_1 |
|
value: 76.85 |
|
- type: ndcg_at_10 |
|
value: 84.68 |
|
- type: ndcg_at_100 |
|
value: 86.311 |
|
- type: ndcg_at_1000 |
|
value: 86.49900000000001 |
|
- type: ndcg_at_3 |
|
value: 81.295 |
|
- type: ndcg_at_5 |
|
value: 83.199 |
|
- type: precision_at_1 |
|
value: 76.85 |
|
- type: precision_at_10 |
|
value: 12.928999999999998 |
|
- type: precision_at_100 |
|
value: 1.51 |
|
- type: precision_at_1000 |
|
value: 0.156 |
|
- type: precision_at_3 |
|
value: 35.557 |
|
- type: precision_at_5 |
|
value: 23.576 |
|
- type: recall_at_1 |
|
value: 66.64 |
|
- type: recall_at_10 |
|
value: 93.059 |
|
- type: recall_at_100 |
|
value: 98.922 |
|
- type: recall_at_1000 |
|
value: 99.883 |
|
- type: recall_at_3 |
|
value: 83.49499999999999 |
|
- type: recall_at_5 |
|
value: 88.729 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
metrics: |
|
- type: v_measure |
|
value: 42.17131361041068 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering-p2p |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
metrics: |
|
- type: v_measure |
|
value: 48.01815621479994 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scidocs |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 3.198 |
|
- type: map_at_10 |
|
value: 7.550999999999999 |
|
- type: map_at_100 |
|
value: 9.232 |
|
- type: map_at_1000 |
|
value: 9.51 |
|
- type: map_at_3 |
|
value: 5.2940000000000005 |
|
- type: map_at_5 |
|
value: 6.343999999999999 |
|
- type: ndcg_at_1 |
|
value: 15.8 |
|
- type: ndcg_at_10 |
|
value: 13.553999999999998 |
|
- type: ndcg_at_100 |
|
value: 20.776 |
|
- type: ndcg_at_1000 |
|
value: 26.204 |
|
- type: ndcg_at_3 |
|
value: 12.306000000000001 |
|
- type: ndcg_at_5 |
|
value: 10.952 |
|
- type: precision_at_1 |
|
value: 15.8 |
|
- type: precision_at_10 |
|
value: 7.180000000000001 |
|
- type: precision_at_100 |
|
value: 1.762 |
|
- type: precision_at_1000 |
|
value: 0.307 |
|
- type: precision_at_3 |
|
value: 11.333 |
|
- type: precision_at_5 |
|
value: 9.62 |
|
- type: recall_at_1 |
|
value: 3.198 |
|
- type: recall_at_10 |
|
value: 14.575 |
|
- type: recall_at_100 |
|
value: 35.758 |
|
- type: recall_at_1000 |
|
value: 62.317 |
|
- type: recall_at_3 |
|
value: 6.922000000000001 |
|
- type: recall_at_5 |
|
value: 9.767000000000001 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sickr-sts |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.5217161312271 |
|
- type: cos_sim_spearman |
|
value: 79.58562467776268 |
|
- type: euclidean_pearson |
|
value: 76.69364353942403 |
|
- type: euclidean_spearman |
|
value: 74.68959282070473 |
|
- type: manhattan_pearson |
|
value: 76.81159265133732 |
|
- type: manhattan_spearman |
|
value: 74.7519444048176 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts12-sts |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.70403706922605 |
|
- type: cos_sim_spearman |
|
value: 74.28502198729447 |
|
- type: euclidean_pearson |
|
value: 83.32719404608066 |
|
- type: euclidean_spearman |
|
value: 75.92189433460788 |
|
- type: manhattan_pearson |
|
value: 83.35841543005293 |
|
- type: manhattan_spearman |
|
value: 75.94458615451978 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts13-sts |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.94127878986795 |
|
- type: cos_sim_spearman |
|
value: 85.35148434923192 |
|
- type: euclidean_pearson |
|
value: 81.71127467071571 |
|
- type: euclidean_spearman |
|
value: 82.88240481546771 |
|
- type: manhattan_pearson |
|
value: 81.72826221967252 |
|
- type: manhattan_spearman |
|
value: 82.90725064625128 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts14-sts |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.1474704168523 |
|
- type: cos_sim_spearman |
|
value: 79.20612995350827 |
|
- type: euclidean_pearson |
|
value: 78.85993329596555 |
|
- type: euclidean_spearman |
|
value: 78.91956572744715 |
|
- type: manhattan_pearson |
|
value: 78.89999720522347 |
|
- type: manhattan_spearman |
|
value: 78.93956842550107 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts15-sts |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.81255514055894 |
|
- type: cos_sim_spearman |
|
value: 85.5217140762934 |
|
- type: euclidean_pearson |
|
value: 82.15024353784499 |
|
- type: euclidean_spearman |
|
value: 83.04155334389833 |
|
- type: manhattan_pearson |
|
value: 82.18598945053624 |
|
- type: manhattan_spearman |
|
value: 83.07248357693301 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts16-sts |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 80.63248465157822 |
|
- type: cos_sim_spearman |
|
value: 82.53853238521991 |
|
- type: euclidean_pearson |
|
value: 78.33936863828221 |
|
- type: euclidean_spearman |
|
value: 79.16305579487414 |
|
- type: manhattan_pearson |
|
value: 78.3888359870894 |
|
- type: manhattan_spearman |
|
value: 79.18504473136467 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (en-en) |
|
config: en-en |
|
split: test |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 90.09066290639687 |
|
- type: cos_sim_spearman |
|
value: 90.43893699357069 |
|
- type: euclidean_pearson |
|
value: 82.39520777222396 |
|
- type: euclidean_spearman |
|
value: 81.23948185395952 |
|
- type: manhattan_pearson |
|
value: 82.35529784653383 |
|
- type: manhattan_spearman |
|
value: 81.12681522483975 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (en) |
|
config: en |
|
split: test |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 63.52752323046846 |
|
- type: cos_sim_spearman |
|
value: 63.19719780439462 |
|
- type: euclidean_pearson |
|
value: 58.29085490641428 |
|
- type: euclidean_spearman |
|
value: 58.975178656335046 |
|
- type: manhattan_pearson |
|
value: 58.183542772416985 |
|
- type: manhattan_spearman |
|
value: 59.190630462178994 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsbenchmark-sts |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 85.45100366635687 |
|
- type: cos_sim_spearman |
|
value: 85.66816193002651 |
|
- type: euclidean_pearson |
|
value: 81.87976731329091 |
|
- type: euclidean_spearman |
|
value: 82.01382867690964 |
|
- type: manhattan_pearson |
|
value: 81.88260155706726 |
|
- type: manhattan_spearman |
|
value: 82.05258597906492 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/scidocs-reranking |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map |
|
value: 77.53549990038017 |
|
- type: mrr |
|
value: 93.37474163454556 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scifact |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 31.167 |
|
- type: map_at_10 |
|
value: 40.778 |
|
- type: map_at_100 |
|
value: 42.063 |
|
- type: map_at_1000 |
|
value: 42.103 |
|
- type: map_at_3 |
|
value: 37.12 |
|
- type: map_at_5 |
|
value: 39.205 |
|
- type: ndcg_at_1 |
|
value: 33.667 |
|
- type: ndcg_at_10 |
|
value: 46.662 |
|
- type: ndcg_at_100 |
|
value: 51.995999999999995 |
|
- type: ndcg_at_1000 |
|
value: 53.254999999999995 |
|
- type: ndcg_at_3 |
|
value: 39.397999999999996 |
|
- type: ndcg_at_5 |
|
value: 42.934 |
|
- type: precision_at_1 |
|
value: 33.667 |
|
- type: precision_at_10 |
|
value: 7.1 |
|
- type: precision_at_100 |
|
value: 0.993 |
|
- type: precision_at_1000 |
|
value: 0.11 |
|
- type: precision_at_3 |
|
value: 16.111 |
|
- type: precision_at_5 |
|
value: 11.600000000000001 |
|
- type: recall_at_1 |
|
value: 31.167 |
|
- type: recall_at_10 |
|
value: 63.744 |
|
- type: recall_at_100 |
|
value: 87.156 |
|
- type: recall_at_1000 |
|
value: 97.556 |
|
- type: recall_at_3 |
|
value: 44.0 |
|
- type: recall_at_5 |
|
value: 52.556000000000004 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.55148514851486 |
|
- type: cos_sim_ap |
|
value: 80.535236573428 |
|
- type: cos_sim_f1 |
|
value: 75.01331912626532 |
|
- type: cos_sim_precision |
|
value: 80.27366020524515 |
|
- type: cos_sim_recall |
|
value: 70.39999999999999 |
|
- type: dot_accuracy |
|
value: 99.04851485148515 |
|
- type: dot_ap |
|
value: 28.505358821499726 |
|
- type: dot_f1 |
|
value: 36.36363636363637 |
|
- type: dot_precision |
|
value: 37.160751565762006 |
|
- type: dot_recall |
|
value: 35.6 |
|
- type: euclidean_accuracy |
|
value: 99.4990099009901 |
|
- type: euclidean_ap |
|
value: 74.95819047075476 |
|
- type: euclidean_f1 |
|
value: 71.15489874110564 |
|
- type: euclidean_precision |
|
value: 78.59733978234583 |
|
- type: euclidean_recall |
|
value: 65.0 |
|
- type: manhattan_accuracy |
|
value: 99.50198019801981 |
|
- type: manhattan_ap |
|
value: 75.02070096015086 |
|
- type: manhattan_f1 |
|
value: 71.20535714285712 |
|
- type: manhattan_precision |
|
value: 80.55555555555556 |
|
- type: manhattan_recall |
|
value: 63.800000000000004 |
|
- type: max_accuracy |
|
value: 99.55148514851486 |
|
- type: max_ap |
|
value: 80.535236573428 |
|
- type: max_f1 |
|
value: 75.01331912626532 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
metrics: |
|
- type: v_measure |
|
value: 54.13314692311623 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering-p2p |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
metrics: |
|
- type: v_measure |
|
value: 31.115181648287145 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/stackoverflowdupquestions-reranking |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map |
|
value: 44.771112666694336 |
|
- type: mrr |
|
value: 45.30415764790765 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: mteb/summeval |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 30.849429597669374 |
|
- type: cos_sim_spearman |
|
value: 30.384175038360194 |
|
- type: dot_pearson |
|
value: 29.030383429536823 |
|
- type: dot_spearman |
|
value: 28.03273624951732 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: trec-covid |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.19499999999999998 |
|
- type: map_at_10 |
|
value: 1.0959999999999999 |
|
- type: map_at_100 |
|
value: 5.726 |
|
- type: map_at_1000 |
|
value: 13.611999999999998 |
|
- type: map_at_3 |
|
value: 0.45399999999999996 |
|
- type: map_at_5 |
|
value: 0.67 |
|
- type: ndcg_at_1 |
|
value: 71.0 |
|
- type: ndcg_at_10 |
|
value: 55.352999999999994 |
|
- type: ndcg_at_100 |
|
value: 40.797 |
|
- type: ndcg_at_1000 |
|
value: 35.955999999999996 |
|
- type: ndcg_at_3 |
|
value: 63.263000000000005 |
|
- type: ndcg_at_5 |
|
value: 60.14000000000001 |
|
- type: precision_at_1 |
|
value: 78.0 |
|
- type: precision_at_10 |
|
value: 56.99999999999999 |
|
- type: precision_at_100 |
|
value: 41.199999999999996 |
|
- type: precision_at_1000 |
|
value: 16.154 |
|
- type: precision_at_3 |
|
value: 66.667 |
|
- type: precision_at_5 |
|
value: 62.8 |
|
- type: recall_at_1 |
|
value: 0.19499999999999998 |
|
- type: recall_at_10 |
|
value: 1.3639999999999999 |
|
- type: recall_at_100 |
|
value: 9.317 |
|
- type: recall_at_1000 |
|
value: 33.629999999999995 |
|
- type: recall_at_3 |
|
value: 0.49300000000000005 |
|
- type: recall_at_5 |
|
value: 0.756 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: webis-touche2020 |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
metrics: |
|
- type: map_at_1 |
|
value: 1.335 |
|
- type: map_at_10 |
|
value: 6.293 |
|
- type: map_at_100 |
|
value: 10.928 |
|
- type: map_at_1000 |
|
value: 12.359 |
|
- type: map_at_3 |
|
value: 3.472 |
|
- type: map_at_5 |
|
value: 4.935 |
|
- type: ndcg_at_1 |
|
value: 19.387999999999998 |
|
- type: ndcg_at_10 |
|
value: 16.178 |
|
- type: ndcg_at_100 |
|
value: 28.149 |
|
- type: ndcg_at_1000 |
|
value: 39.845000000000006 |
|
- type: ndcg_at_3 |
|
value: 19.171 |
|
- type: ndcg_at_5 |
|
value: 17.864 |
|
- type: precision_at_1 |
|
value: 20.408 |
|
- type: precision_at_10 |
|
value: 14.49 |
|
- type: precision_at_100 |
|
value: 6.306000000000001 |
|
- type: precision_at_1000 |
|
value: 1.3860000000000001 |
|
- type: precision_at_3 |
|
value: 21.088 |
|
- type: precision_at_5 |
|
value: 18.367 |
|
- type: recall_at_1 |
|
value: 1.335 |
|
- type: recall_at_10 |
|
value: 10.825999999999999 |
|
- type: recall_at_100 |
|
value: 39.251000000000005 |
|
- type: recall_at_1000 |
|
value: 74.952 |
|
- type: recall_at_3 |
|
value: 4.9110000000000005 |
|
- type: recall_at_5 |
|
value: 7.312 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/toxic_conversations_50k |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 69.93339999999999 |
|
- type: ap |
|
value: 13.87476602492533 |
|
- type: f1 |
|
value: 53.867357615848555 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/tweet_sentiment_extraction |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
metrics: |
|
- type: accuracy |
|
value: 62.43916242218449 |
|
- type: f1 |
|
value: 62.870386304954685 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/twentynewsgroups-clustering |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
metrics: |
|
- type: v_measure |
|
value: 37.202082549859796 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twittersemeval2015-pairclassification |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 83.65023544137807 |
|
- type: cos_sim_ap |
|
value: 65.99787692764193 |
|
- type: cos_sim_f1 |
|
value: 62.10650887573965 |
|
- type: cos_sim_precision |
|
value: 56.30901287553648 |
|
- type: cos_sim_recall |
|
value: 69.23482849604221 |
|
- type: dot_accuracy |
|
value: 79.10830303391549 |
|
- type: dot_ap |
|
value: 48.80109642320246 |
|
- type: dot_f1 |
|
value: 51.418744625967314 |
|
- type: dot_precision |
|
value: 40.30253107683091 |
|
- type: dot_recall |
|
value: 71.00263852242745 |
|
- type: euclidean_accuracy |
|
value: 82.45812719794957 |
|
- type: euclidean_ap |
|
value: 60.09969493259607 |
|
- type: euclidean_f1 |
|
value: 57.658573789246226 |
|
- type: euclidean_precision |
|
value: 55.62913907284768 |
|
- type: euclidean_recall |
|
value: 59.84168865435356 |
|
- type: manhattan_accuracy |
|
value: 82.46408773916671 |
|
- type: manhattan_ap |
|
value: 60.116199786815116 |
|
- type: manhattan_f1 |
|
value: 57.683903860160235 |
|
- type: manhattan_precision |
|
value: 53.41726618705036 |
|
- type: manhattan_recall |
|
value: 62.69129287598945 |
|
- type: max_accuracy |
|
value: 83.65023544137807 |
|
- type: max_ap |
|
value: 65.99787692764193 |
|
- type: max_f1 |
|
value: 62.10650887573965 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twitterurlcorpus-pairclassification |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.34943920518494 |
|
- type: cos_sim_ap |
|
value: 84.5428891020442 |
|
- type: cos_sim_f1 |
|
value: 77.09709933923172 |
|
- type: cos_sim_precision |
|
value: 74.83150952967607 |
|
- type: cos_sim_recall |
|
value: 79.50415768401602 |
|
- type: dot_accuracy |
|
value: 84.53448208949432 |
|
- type: dot_ap |
|
value: 73.96328242371995 |
|
- type: dot_f1 |
|
value: 70.00553786515299 |
|
- type: dot_precision |
|
value: 63.58777665995976 |
|
- type: dot_recall |
|
value: 77.86418232214352 |
|
- type: euclidean_accuracy |
|
value: 86.87662514068381 |
|
- type: euclidean_ap |
|
value: 81.45499631520235 |
|
- type: euclidean_f1 |
|
value: 73.46567109816063 |
|
- type: euclidean_precision |
|
value: 69.71037533697381 |
|
- type: euclidean_recall |
|
value: 77.6485987064983 |
|
- type: manhattan_accuracy |
|
value: 86.88244654014825 |
|
- type: manhattan_ap |
|
value: 81.47180273946366 |
|
- type: manhattan_f1 |
|
value: 73.44624393136418 |
|
- type: manhattan_precision |
|
value: 70.80385852090032 |
|
- type: manhattan_recall |
|
value: 76.29350169387126 |
|
- type: max_accuracy |
|
value: 88.34943920518494 |
|
- type: max_ap |
|
value: 84.5428891020442 |
|
- type: max_f1 |
|
value: 77.09709933923172 |
|
--- |
|
|
|
# SGPT-5.8B-weightedmean-msmarco-specb-bitfit |
|
|
|
## Usage |
|
|
|
For usage instructions, refer to our codebase: https://github.com/Muennighoff/sgpt |
|
|
|
## Evaluation Results |
|
|
|
For eval results, refer to our paper: https://arxiv.org/abs/2202.08904 |
|
|
|
## Training |
|
The model was trained with the parameters: |
|
|
|
**DataLoader**: |
|
|
|
`torch.utils.data.dataloader.DataLoader` of length 249592 with parameters: |
|
``` |
|
{'batch_size': 2, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'} |
|
``` |
|
|
|
**Loss**: |
|
|
|
`sentence_transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss` with parameters: |
|
``` |
|
{'scale': 20.0, 'similarity_fct': 'cos_sim'} |
|
``` |
|
|
|
Parameters of the fit()-Method: |
|
``` |
|
{ |
|
"epochs": 10, |
|
"evaluation_steps": 0, |
|
"evaluator": "NoneType", |
|
"max_grad_norm": 1, |
|
"optimizer_class": "<class 'transformers.optimization.AdamW'>", |
|
"optimizer_params": { |
|
"lr": 5e-05 |
|
}, |
|
"scheduler": "WarmupLinear", |
|
"steps_per_epoch": null, |
|
"warmup_steps": 1000, |
|
"weight_decay": 0.01 |
|
} |
|
``` |
|
|
|
|
|
## Full Model Architecture |
|
``` |
|
SentenceTransformer( |
|
(0): Transformer({'max_seq_length': 300, 'do_lower_case': False}) with Transformer model: GPTJModel |
|
(1): Pooling({'word_embedding_dimension': 4096, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': True, 'pooling_mode_lasttoken': False}) |
|
) |
|
``` |
|
|
|
## Citing & Authors |
|
|
|
```bibtex |
|
@article{muennighoff2022sgpt, |
|
title={SGPT: GPT Sentence Embeddings for Semantic Search}, |
|
author={Muennighoff, Niklas}, |
|
journal={arXiv preprint arXiv:2202.08904}, |
|
year={2022} |
|
} |
|
``` |
|
|
