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--- |
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pipeline_tag: sentence-similarity |
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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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- mteb |
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model-index: |
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- name: sgpt-bloom-7b1-msmarco |
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results: |
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- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
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name: MTEB AmazonCounterfactualClassification (en) |
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config: en |
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split: test |
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revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996 |
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metrics: |
|
- type: accuracy |
|
value: 68.05970149253731 |
|
- type: ap |
|
value: 31.640363460776193 |
|
- type: f1 |
|
value: 62.50025574145796 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification (de) |
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config: de |
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split: test |
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revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996 |
|
metrics: |
|
- type: accuracy |
|
value: 61.34903640256959 |
|
- type: ap |
|
value: 75.18797161500426 |
|
- type: f1 |
|
value: 59.04772570730417 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification (en-ext) |
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config: en-ext |
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split: test |
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revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996 |
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metrics: |
|
- type: accuracy |
|
value: 67.78110944527737 |
|
- type: ap |
|
value: 19.218916023322706 |
|
- type: f1 |
|
value: 56.24477391445512 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification (ja) |
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config: ja |
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split: test |
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revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996 |
|
metrics: |
|
- type: accuracy |
|
value: 58.23340471092078 |
|
- type: ap |
|
value: 13.20222967424681 |
|
- type: f1 |
|
value: 47.511718095460296 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_polarity |
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name: MTEB AmazonPolarityClassification |
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config: default |
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split: test |
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revision: 80714f8dcf8cefc218ef4f8c5a966dd83f75a0e1 |
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metrics: |
|
- type: accuracy |
|
value: 68.97232499999998 |
|
- type: ap |
|
value: 63.53632885535693 |
|
- type: f1 |
|
value: 68.62038513152868 |
|
- task: |
|
type: Classification |
|
dataset: |
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type: mteb/amazon_reviews_multi |
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name: MTEB AmazonReviewsClassification (en) |
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config: en |
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split: test |
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revision: c379a6705fec24a2493fa68e011692605f44e119 |
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metrics: |
|
- type: accuracy |
|
value: 33.855999999999995 |
|
- type: f1 |
|
value: 33.43468222830134 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
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name: MTEB AmazonReviewsClassification (de) |
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config: de |
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split: test |
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revision: c379a6705fec24a2493fa68e011692605f44e119 |
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metrics: |
|
- type: accuracy |
|
value: 29.697999999999997 |
|
- type: f1 |
|
value: 29.39935388885501 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (es) |
|
config: es |
|
split: test |
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revision: c379a6705fec24a2493fa68e011692605f44e119 |
|
metrics: |
|
- type: accuracy |
|
value: 35.974000000000004 |
|
- type: f1 |
|
value: 35.25910820714383 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (fr) |
|
config: fr |
|
split: test |
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revision: c379a6705fec24a2493fa68e011692605f44e119 |
|
metrics: |
|
- type: accuracy |
|
value: 35.922 |
|
- type: f1 |
|
value: 35.38637028933444 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (ja) |
|
config: ja |
|
split: test |
|
revision: c379a6705fec24a2493fa68e011692605f44e119 |
|
metrics: |
|
- type: accuracy |
|
value: 27.636 |
|
- type: f1 |
|
value: 27.178349955978266 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (zh) |
|
config: zh |
|
split: test |
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revision: c379a6705fec24a2493fa68e011692605f44e119 |
|
metrics: |
|
- type: accuracy |
|
value: 32.632 |
|
- type: f1 |
|
value: 32.08014766494587 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: arguana |
|
name: MTEB ArguAna |
|
config: default |
|
split: test |
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revision: 5b3e3697907184a9b77a3c99ee9ea1a9cbb1e4e3 |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.684 |
|
- type: map_at_10 |
|
value: 38.507999999999996 |
|
- type: map_at_100 |
|
value: 39.677 |
|
- type: map_at_1000 |
|
value: 39.690999999999995 |
|
- type: map_at_3 |
|
value: 33.369 |
|
- type: map_at_5 |
|
value: 36.15 |
|
- type: mrr_at_1 |
|
value: 24.04 |
|
- type: mrr_at_10 |
|
value: 38.664 |
|
- type: mrr_at_100 |
|
value: 39.833 |
|
- type: mrr_at_1000 |
|
value: 39.847 |
|
- type: mrr_at_3 |
|
value: 33.476 |
|
- type: mrr_at_5 |
|
value: 36.306 |
|
- type: ndcg_at_1 |
|
value: 23.684 |
|
- type: ndcg_at_10 |
|
value: 47.282000000000004 |
|
- type: ndcg_at_100 |
|
value: 52.215 |
|
- type: ndcg_at_1000 |
|
value: 52.551 |
|
- type: ndcg_at_3 |
|
value: 36.628 |
|
- type: ndcg_at_5 |
|
value: 41.653 |
|
- type: precision_at_1 |
|
value: 23.684 |
|
- type: precision_at_10 |
|
value: 7.553 |
|
- type: precision_at_100 |
|
value: 0.97 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 15.363 |
|
- type: precision_at_5 |
|
value: 11.664 |
|
- type: recall_at_1 |
|
value: 23.684 |
|
- type: recall_at_10 |
|
value: 75.533 |
|
- type: recall_at_100 |
|
value: 97.013 |
|
- type: recall_at_1000 |
|
value: 99.57300000000001 |
|
- type: recall_at_3 |
|
value: 46.088 |
|
- type: recall_at_5 |
|
value: 58.321 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-p2p |
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name: MTEB ArxivClusteringP2P |
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config: default |
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split: test |
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revision: 0bbdb47bcbe3a90093699aefeed338a0f28a7ee8 |
|
metrics: |
|
- type: v_measure |
|
value: 44.59375023881131 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-s2s |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
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split: test |
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revision: b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3 |
|
metrics: |
|
- type: v_measure |
|
value: 38.02921907752556 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/askubuntudupquestions-reranking |
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name: MTEB AskUbuntuDupQuestions |
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config: default |
|
split: test |
|
revision: 4d853f94cd57d85ec13805aeeac3ae3e5eb4c49c |
|
metrics: |
|
- type: map |
|
value: 59.97321570342109 |
|
- type: mrr |
|
value: 73.18284746955106 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/biosses-sts |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: 9ee918f184421b6bd48b78f6c714d86546106103 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 89.09091435741429 |
|
- type: cos_sim_spearman |
|
value: 85.31459455332202 |
|
- type: euclidean_pearson |
|
value: 79.3587681410798 |
|
- type: euclidean_spearman |
|
value: 76.8174129874685 |
|
- type: manhattan_pearson |
|
value: 79.57051762121769 |
|
- type: manhattan_spearman |
|
value: 76.75837549768094 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/bucc-bitext-mining |
|
name: MTEB BUCC (de-en) |
|
config: de-en |
|
split: test |
|
revision: d51519689f32196a32af33b075a01d0e7c51e252 |
|
metrics: |
|
- type: accuracy |
|
value: 54.27974947807933 |
|
- type: f1 |
|
value: 54.00144411132214 |
|
- type: precision |
|
value: 53.87119374071357 |
|
- type: recall |
|
value: 54.27974947807933 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/bucc-bitext-mining |
|
name: MTEB BUCC (fr-en) |
|
config: fr-en |
|
split: test |
|
revision: d51519689f32196a32af33b075a01d0e7c51e252 |
|
metrics: |
|
- type: accuracy |
|
value: 97.3365617433414 |
|
- type: f1 |
|
value: 97.06141316310809 |
|
- type: precision |
|
value: 96.92567319685965 |
|
- type: recall |
|
value: 97.3365617433414 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/bucc-bitext-mining |
|
name: MTEB BUCC (ru-en) |
|
config: ru-en |
|
split: test |
|
revision: d51519689f32196a32af33b075a01d0e7c51e252 |
|
metrics: |
|
- type: accuracy |
|
value: 46.05472809144441 |
|
- type: f1 |
|
value: 45.30319274690595 |
|
- type: precision |
|
value: 45.00015469655234 |
|
- type: recall |
|
value: 46.05472809144441 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/bucc-bitext-mining |
|
name: MTEB BUCC (zh-en) |
|
config: zh-en |
|
split: test |
|
revision: d51519689f32196a32af33b075a01d0e7c51e252 |
|
metrics: |
|
- type: accuracy |
|
value: 98.10426540284361 |
|
- type: f1 |
|
value: 97.96384061786905 |
|
- type: precision |
|
value: 97.89362822538178 |
|
- type: recall |
|
value: 98.10426540284361 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/banking77 |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 44fa15921b4c889113cc5df03dd4901b49161ab7 |
|
metrics: |
|
- type: accuracy |
|
value: 84.33441558441558 |
|
- type: f1 |
|
value: 84.31653077470322 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-p2p |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 11d0121201d1f1f280e8cc8f3d98fb9c4d9f9c55 |
|
metrics: |
|
- type: v_measure |
|
value: 36.025318694698086 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-s2s |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: c0fab014e1bcb8d3a5e31b2088972a1e01547dc1 |
|
metrics: |
|
- type: v_measure |
|
value: 32.484889034590346 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 30.203999999999997 |
|
- type: map_at_10 |
|
value: 41.314 |
|
- type: map_at_100 |
|
value: 42.66 |
|
- type: map_at_1000 |
|
value: 42.775999999999996 |
|
- type: map_at_3 |
|
value: 37.614999999999995 |
|
- type: map_at_5 |
|
value: 39.643 |
|
- type: mrr_at_1 |
|
value: 37.482 |
|
- type: mrr_at_10 |
|
value: 47.075 |
|
- type: mrr_at_100 |
|
value: 47.845 |
|
- type: mrr_at_1000 |
|
value: 47.887 |
|
- type: mrr_at_3 |
|
value: 44.635000000000005 |
|
- type: mrr_at_5 |
|
value: 45.966 |
|
- type: ndcg_at_1 |
|
value: 37.482 |
|
- type: ndcg_at_10 |
|
value: 47.676 |
|
- type: ndcg_at_100 |
|
value: 52.915 |
|
- type: ndcg_at_1000 |
|
value: 54.82900000000001 |
|
- type: ndcg_at_3 |
|
value: 42.562 |
|
- type: ndcg_at_5 |
|
value: 44.852 |
|
- type: precision_at_1 |
|
value: 37.482 |
|
- type: precision_at_10 |
|
value: 9.142 |
|
- type: precision_at_100 |
|
value: 1.436 |
|
- type: precision_at_1000 |
|
value: 0.189 |
|
- type: precision_at_3 |
|
value: 20.458000000000002 |
|
- type: precision_at_5 |
|
value: 14.821000000000002 |
|
- type: recall_at_1 |
|
value: 30.203999999999997 |
|
- type: recall_at_10 |
|
value: 60.343 |
|
- type: recall_at_100 |
|
value: 82.58 |
|
- type: recall_at_1000 |
|
value: 94.813 |
|
- type: recall_at_3 |
|
value: 45.389 |
|
- type: recall_at_5 |
|
value: 51.800999999999995 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 30.889 |
|
- type: map_at_10 |
|
value: 40.949999999999996 |
|
- type: map_at_100 |
|
value: 42.131 |
|
- type: map_at_1000 |
|
value: 42.253 |
|
- type: map_at_3 |
|
value: 38.346999999999994 |
|
- type: map_at_5 |
|
value: 39.782000000000004 |
|
- type: mrr_at_1 |
|
value: 38.79 |
|
- type: mrr_at_10 |
|
value: 46.944 |
|
- type: mrr_at_100 |
|
value: 47.61 |
|
- type: mrr_at_1000 |
|
value: 47.650999999999996 |
|
- type: mrr_at_3 |
|
value: 45.053 |
|
- type: mrr_at_5 |
|
value: 46.101 |
|
- type: ndcg_at_1 |
|
value: 38.79 |
|
- type: ndcg_at_10 |
|
value: 46.286 |
|
- type: ndcg_at_100 |
|
value: 50.637 |
|
- type: ndcg_at_1000 |
|
value: 52.649 |
|
- type: ndcg_at_3 |
|
value: 42.851 |
|
- type: ndcg_at_5 |
|
value: 44.311 |
|
- type: precision_at_1 |
|
value: 38.79 |
|
- type: precision_at_10 |
|
value: 8.516 |
|
- type: precision_at_100 |
|
value: 1.3679999999999999 |
|
- type: precision_at_1000 |
|
value: 0.183 |
|
- type: precision_at_3 |
|
value: 20.637 |
|
- type: precision_at_5 |
|
value: 14.318 |
|
- type: recall_at_1 |
|
value: 30.889 |
|
- type: recall_at_10 |
|
value: 55.327000000000005 |
|
- type: recall_at_100 |
|
value: 74.091 |
|
- type: recall_at_1000 |
|
value: 86.75500000000001 |
|
- type: recall_at_3 |
|
value: 44.557 |
|
- type: recall_at_5 |
|
value: 49.064 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 39.105000000000004 |
|
- type: map_at_10 |
|
value: 50.928 |
|
- type: map_at_100 |
|
value: 51.958000000000006 |
|
- type: map_at_1000 |
|
value: 52.017 |
|
- type: map_at_3 |
|
value: 47.638999999999996 |
|
- type: map_at_5 |
|
value: 49.624 |
|
- type: mrr_at_1 |
|
value: 44.639 |
|
- type: mrr_at_10 |
|
value: 54.261 |
|
- type: mrr_at_100 |
|
value: 54.913999999999994 |
|
- type: mrr_at_1000 |
|
value: 54.945 |
|
- type: mrr_at_3 |
|
value: 51.681999999999995 |
|
- type: mrr_at_5 |
|
value: 53.290000000000006 |
|
- type: ndcg_at_1 |
|
value: 44.639 |
|
- type: ndcg_at_10 |
|
value: 56.678 |
|
- type: ndcg_at_100 |
|
value: 60.649 |
|
- type: ndcg_at_1000 |
|
value: 61.855000000000004 |
|
- type: ndcg_at_3 |
|
value: 51.092999999999996 |
|
- type: ndcg_at_5 |
|
value: 54.096999999999994 |
|
- type: precision_at_1 |
|
value: 44.639 |
|
- type: precision_at_10 |
|
value: 9.028 |
|
- type: precision_at_100 |
|
value: 1.194 |
|
- type: precision_at_1000 |
|
value: 0.135 |
|
- type: precision_at_3 |
|
value: 22.508 |
|
- type: precision_at_5 |
|
value: 15.661 |
|
- type: recall_at_1 |
|
value: 39.105000000000004 |
|
- type: recall_at_10 |
|
value: 70.367 |
|
- type: recall_at_100 |
|
value: 87.359 |
|
- type: recall_at_1000 |
|
value: 95.88 |
|
- type: recall_at_3 |
|
value: 55.581 |
|
- type: recall_at_5 |
|
value: 62.821000000000005 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.777 |
|
- type: map_at_10 |
|
value: 32.297 |
|
- type: map_at_100 |
|
value: 33.516 |
|
- type: map_at_1000 |
|
value: 33.592 |
|
- type: map_at_3 |
|
value: 30.001 |
|
- type: map_at_5 |
|
value: 31.209999999999997 |
|
- type: mrr_at_1 |
|
value: 25.989 |
|
- type: mrr_at_10 |
|
value: 34.472 |
|
- type: mrr_at_100 |
|
value: 35.518 |
|
- type: mrr_at_1000 |
|
value: 35.577 |
|
- type: mrr_at_3 |
|
value: 32.185 |
|
- type: mrr_at_5 |
|
value: 33.399 |
|
- type: ndcg_at_1 |
|
value: 25.989 |
|
- type: ndcg_at_10 |
|
value: 37.037 |
|
- type: ndcg_at_100 |
|
value: 42.699 |
|
- type: ndcg_at_1000 |
|
value: 44.725 |
|
- type: ndcg_at_3 |
|
value: 32.485 |
|
- type: ndcg_at_5 |
|
value: 34.549 |
|
- type: precision_at_1 |
|
value: 25.989 |
|
- type: precision_at_10 |
|
value: 5.718 |
|
- type: precision_at_100 |
|
value: 0.89 |
|
- type: precision_at_1000 |
|
value: 0.11 |
|
- type: precision_at_3 |
|
value: 14.049 |
|
- type: precision_at_5 |
|
value: 9.672 |
|
- type: recall_at_1 |
|
value: 23.777 |
|
- type: recall_at_10 |
|
value: 49.472 |
|
- type: recall_at_100 |
|
value: 74.857 |
|
- type: recall_at_1000 |
|
value: 90.289 |
|
- type: recall_at_3 |
|
value: 37.086000000000006 |
|
- type: recall_at_5 |
|
value: 42.065999999999995 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.377 |
|
- type: map_at_10 |
|
value: 21.444 |
|
- type: map_at_100 |
|
value: 22.663 |
|
- type: map_at_1000 |
|
value: 22.8 |
|
- type: map_at_3 |
|
value: 18.857 |
|
- type: map_at_5 |
|
value: 20.426 |
|
- type: mrr_at_1 |
|
value: 16.542 |
|
- type: mrr_at_10 |
|
value: 25.326999999999998 |
|
- type: mrr_at_100 |
|
value: 26.323 |
|
- type: mrr_at_1000 |
|
value: 26.406000000000002 |
|
- type: mrr_at_3 |
|
value: 22.823 |
|
- type: mrr_at_5 |
|
value: 24.340999999999998 |
|
- type: ndcg_at_1 |
|
value: 16.542 |
|
- type: ndcg_at_10 |
|
value: 26.479000000000003 |
|
- type: ndcg_at_100 |
|
value: 32.29 |
|
- type: ndcg_at_1000 |
|
value: 35.504999999999995 |
|
- type: ndcg_at_3 |
|
value: 21.619 |
|
- type: ndcg_at_5 |
|
value: 24.19 |
|
- type: precision_at_1 |
|
value: 16.542 |
|
- type: precision_at_10 |
|
value: 5.075 |
|
- type: precision_at_100 |
|
value: 0.9339999999999999 |
|
- type: precision_at_1000 |
|
value: 0.135 |
|
- type: precision_at_3 |
|
value: 10.697 |
|
- type: precision_at_5 |
|
value: 8.134 |
|
- type: recall_at_1 |
|
value: 13.377 |
|
- type: recall_at_10 |
|
value: 38.027 |
|
- type: recall_at_100 |
|
value: 63.439 |
|
- type: recall_at_1000 |
|
value: 86.354 |
|
- type: recall_at_3 |
|
value: 25.0 |
|
- type: recall_at_5 |
|
value: 31.306 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 28.368 |
|
- type: map_at_10 |
|
value: 39.305 |
|
- type: map_at_100 |
|
value: 40.637 |
|
- type: map_at_1000 |
|
value: 40.753 |
|
- type: map_at_3 |
|
value: 36.077999999999996 |
|
- type: map_at_5 |
|
value: 37.829 |
|
- type: mrr_at_1 |
|
value: 34.937000000000005 |
|
- type: mrr_at_10 |
|
value: 45.03 |
|
- type: mrr_at_100 |
|
value: 45.78 |
|
- type: mrr_at_1000 |
|
value: 45.827 |
|
- type: mrr_at_3 |
|
value: 42.348 |
|
- type: mrr_at_5 |
|
value: 43.807 |
|
- type: ndcg_at_1 |
|
value: 34.937000000000005 |
|
- type: ndcg_at_10 |
|
value: 45.605000000000004 |
|
- type: ndcg_at_100 |
|
value: 50.941 |
|
- type: ndcg_at_1000 |
|
value: 52.983000000000004 |
|
- type: ndcg_at_3 |
|
value: 40.366 |
|
- type: ndcg_at_5 |
|
value: 42.759 |
|
- type: precision_at_1 |
|
value: 34.937000000000005 |
|
- type: precision_at_10 |
|
value: 8.402 |
|
- type: precision_at_100 |
|
value: 1.2959999999999998 |
|
- type: precision_at_1000 |
|
value: 0.164 |
|
- type: precision_at_3 |
|
value: 19.217000000000002 |
|
- type: precision_at_5 |
|
value: 13.725000000000001 |
|
- type: recall_at_1 |
|
value: 28.368 |
|
- type: recall_at_10 |
|
value: 58.5 |
|
- type: recall_at_100 |
|
value: 80.67999999999999 |
|
- type: recall_at_1000 |
|
value: 93.925 |
|
- type: recall_at_3 |
|
value: 43.956 |
|
- type: recall_at_5 |
|
value: 50.065000000000005 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.851 |
|
- type: map_at_10 |
|
value: 34.758 |
|
- type: map_at_100 |
|
value: 36.081 |
|
- type: map_at_1000 |
|
value: 36.205999999999996 |
|
- type: map_at_3 |
|
value: 31.678 |
|
- type: map_at_5 |
|
value: 33.398 |
|
- type: mrr_at_1 |
|
value: 31.279 |
|
- type: mrr_at_10 |
|
value: 40.138 |
|
- type: mrr_at_100 |
|
value: 41.005 |
|
- type: mrr_at_1000 |
|
value: 41.065000000000005 |
|
- type: mrr_at_3 |
|
value: 37.519000000000005 |
|
- type: mrr_at_5 |
|
value: 38.986 |
|
- type: ndcg_at_1 |
|
value: 31.279 |
|
- type: ndcg_at_10 |
|
value: 40.534 |
|
- type: ndcg_at_100 |
|
value: 46.093 |
|
- type: ndcg_at_1000 |
|
value: 48.59 |
|
- type: ndcg_at_3 |
|
value: 35.473 |
|
- type: ndcg_at_5 |
|
value: 37.801 |
|
- type: precision_at_1 |
|
value: 31.279 |
|
- type: precision_at_10 |
|
value: 7.477 |
|
- type: precision_at_100 |
|
value: 1.2 |
|
- type: precision_at_1000 |
|
value: 0.159 |
|
- type: precision_at_3 |
|
value: 17.047 |
|
- type: precision_at_5 |
|
value: 12.306000000000001 |
|
- type: recall_at_1 |
|
value: 24.851 |
|
- type: recall_at_10 |
|
value: 52.528 |
|
- type: recall_at_100 |
|
value: 76.198 |
|
- type: recall_at_1000 |
|
value: 93.12 |
|
- type: recall_at_3 |
|
value: 38.257999999999996 |
|
- type: recall_at_5 |
|
value: 44.440000000000005 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.289833333333334 |
|
- type: map_at_10 |
|
value: 34.379333333333335 |
|
- type: map_at_100 |
|
value: 35.56916666666666 |
|
- type: map_at_1000 |
|
value: 35.68633333333333 |
|
- type: map_at_3 |
|
value: 31.63916666666666 |
|
- type: map_at_5 |
|
value: 33.18383333333334 |
|
- type: mrr_at_1 |
|
value: 30.081749999999996 |
|
- type: mrr_at_10 |
|
value: 38.53658333333333 |
|
- type: mrr_at_100 |
|
value: 39.37825 |
|
- type: mrr_at_1000 |
|
value: 39.43866666666666 |
|
- type: mrr_at_3 |
|
value: 36.19025 |
|
- type: mrr_at_5 |
|
value: 37.519749999999995 |
|
- type: ndcg_at_1 |
|
value: 30.081749999999996 |
|
- type: ndcg_at_10 |
|
value: 39.62041666666667 |
|
- type: ndcg_at_100 |
|
value: 44.74825 |
|
- type: ndcg_at_1000 |
|
value: 47.11366666666667 |
|
- type: ndcg_at_3 |
|
value: 35.000499999999995 |
|
- type: ndcg_at_5 |
|
value: 37.19283333333333 |
|
- type: precision_at_1 |
|
value: 30.081749999999996 |
|
- type: precision_at_10 |
|
value: 6.940249999999999 |
|
- type: precision_at_100 |
|
value: 1.1164166666666668 |
|
- type: precision_at_1000 |
|
value: 0.15025000000000002 |
|
- type: precision_at_3 |
|
value: 16.110416666666666 |
|
- type: precision_at_5 |
|
value: 11.474416666666668 |
|
- type: recall_at_1 |
|
value: 25.289833333333334 |
|
- type: recall_at_10 |
|
value: 51.01591666666667 |
|
- type: recall_at_100 |
|
value: 73.55275000000002 |
|
- type: recall_at_1000 |
|
value: 90.02666666666667 |
|
- type: recall_at_3 |
|
value: 38.15208333333334 |
|
- type: recall_at_5 |
|
value: 43.78458333333334 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.479 |
|
- type: map_at_10 |
|
value: 31.2 |
|
- type: map_at_100 |
|
value: 32.11 |
|
- type: map_at_1000 |
|
value: 32.214 |
|
- type: map_at_3 |
|
value: 29.093999999999998 |
|
- type: map_at_5 |
|
value: 30.415 |
|
- type: mrr_at_1 |
|
value: 26.840000000000003 |
|
- type: mrr_at_10 |
|
value: 34.153 |
|
- type: mrr_at_100 |
|
value: 34.971000000000004 |
|
- type: mrr_at_1000 |
|
value: 35.047 |
|
- type: mrr_at_3 |
|
value: 32.285000000000004 |
|
- type: mrr_at_5 |
|
value: 33.443 |
|
- type: ndcg_at_1 |
|
value: 26.840000000000003 |
|
- type: ndcg_at_10 |
|
value: 35.441 |
|
- type: ndcg_at_100 |
|
value: 40.150000000000006 |
|
- type: ndcg_at_1000 |
|
value: 42.74 |
|
- type: ndcg_at_3 |
|
value: 31.723000000000003 |
|
- type: ndcg_at_5 |
|
value: 33.71 |
|
- type: precision_at_1 |
|
value: 26.840000000000003 |
|
- type: precision_at_10 |
|
value: 5.552 |
|
- type: precision_at_100 |
|
value: 0.859 |
|
- type: precision_at_1000 |
|
value: 0.11499999999999999 |
|
- type: precision_at_3 |
|
value: 13.804 |
|
- type: precision_at_5 |
|
value: 9.600999999999999 |
|
- type: recall_at_1 |
|
value: 23.479 |
|
- type: recall_at_10 |
|
value: 45.442 |
|
- type: recall_at_100 |
|
value: 67.465 |
|
- type: recall_at_1000 |
|
value: 86.53 |
|
- type: recall_at_3 |
|
value: 35.315999999999995 |
|
- type: recall_at_5 |
|
value: 40.253 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 16.887 |
|
- type: map_at_10 |
|
value: 23.805 |
|
- type: map_at_100 |
|
value: 24.804000000000002 |
|
- type: map_at_1000 |
|
value: 24.932000000000002 |
|
- type: map_at_3 |
|
value: 21.632 |
|
- type: map_at_5 |
|
value: 22.845 |
|
- type: mrr_at_1 |
|
value: 20.75 |
|
- type: mrr_at_10 |
|
value: 27.686 |
|
- type: mrr_at_100 |
|
value: 28.522 |
|
- type: mrr_at_1000 |
|
value: 28.605000000000004 |
|
- type: mrr_at_3 |
|
value: 25.618999999999996 |
|
- type: mrr_at_5 |
|
value: 26.723999999999997 |
|
- type: ndcg_at_1 |
|
value: 20.75 |
|
- type: ndcg_at_10 |
|
value: 28.233000000000004 |
|
- type: ndcg_at_100 |
|
value: 33.065 |
|
- type: ndcg_at_1000 |
|
value: 36.138999999999996 |
|
- type: ndcg_at_3 |
|
value: 24.361 |
|
- type: ndcg_at_5 |
|
value: 26.111 |
|
- type: precision_at_1 |
|
value: 20.75 |
|
- type: precision_at_10 |
|
value: 5.124 |
|
- type: precision_at_100 |
|
value: 0.8750000000000001 |
|
- type: precision_at_1000 |
|
value: 0.131 |
|
- type: precision_at_3 |
|
value: 11.539000000000001 |
|
- type: precision_at_5 |
|
value: 8.273 |
|
- type: recall_at_1 |
|
value: 16.887 |
|
- type: recall_at_10 |
|
value: 37.774 |
|
- type: recall_at_100 |
|
value: 59.587 |
|
- type: recall_at_1000 |
|
value: 81.523 |
|
- type: recall_at_3 |
|
value: 26.837 |
|
- type: recall_at_5 |
|
value: 31.456 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.534000000000002 |
|
- type: map_at_10 |
|
value: 33.495999999999995 |
|
- type: map_at_100 |
|
value: 34.697 |
|
- type: map_at_1000 |
|
value: 34.805 |
|
- type: map_at_3 |
|
value: 31.22 |
|
- type: map_at_5 |
|
value: 32.277 |
|
- type: mrr_at_1 |
|
value: 29.944 |
|
- type: mrr_at_10 |
|
value: 37.723 |
|
- type: mrr_at_100 |
|
value: 38.645 |
|
- type: mrr_at_1000 |
|
value: 38.712999999999994 |
|
- type: mrr_at_3 |
|
value: 35.665 |
|
- type: mrr_at_5 |
|
value: 36.681999999999995 |
|
- type: ndcg_at_1 |
|
value: 29.944 |
|
- type: ndcg_at_10 |
|
value: 38.407000000000004 |
|
- type: ndcg_at_100 |
|
value: 43.877 |
|
- type: ndcg_at_1000 |
|
value: 46.312 |
|
- type: ndcg_at_3 |
|
value: 34.211000000000006 |
|
- type: ndcg_at_5 |
|
value: 35.760999999999996 |
|
- type: precision_at_1 |
|
value: 29.944 |
|
- type: precision_at_10 |
|
value: 6.343 |
|
- type: precision_at_100 |
|
value: 1.023 |
|
- type: precision_at_1000 |
|
value: 0.133 |
|
- type: precision_at_3 |
|
value: 15.360999999999999 |
|
- type: precision_at_5 |
|
value: 10.428999999999998 |
|
- type: recall_at_1 |
|
value: 25.534000000000002 |
|
- type: recall_at_10 |
|
value: 49.204 |
|
- type: recall_at_100 |
|
value: 72.878 |
|
- type: recall_at_1000 |
|
value: 89.95 |
|
- type: recall_at_3 |
|
value: 37.533 |
|
- type: recall_at_5 |
|
value: 41.611 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.291999999999998 |
|
- type: map_at_10 |
|
value: 35.245 |
|
- type: map_at_100 |
|
value: 36.762 |
|
- type: map_at_1000 |
|
value: 36.983 |
|
- type: map_at_3 |
|
value: 32.439 |
|
- type: map_at_5 |
|
value: 33.964 |
|
- type: mrr_at_1 |
|
value: 31.423000000000002 |
|
- type: mrr_at_10 |
|
value: 39.98 |
|
- type: mrr_at_100 |
|
value: 40.791 |
|
- type: mrr_at_1000 |
|
value: 40.854 |
|
- type: mrr_at_3 |
|
value: 37.451 |
|
- type: mrr_at_5 |
|
value: 38.854 |
|
- type: ndcg_at_1 |
|
value: 31.423000000000002 |
|
- type: ndcg_at_10 |
|
value: 40.848 |
|
- type: ndcg_at_100 |
|
value: 46.35 |
|
- type: ndcg_at_1000 |
|
value: 49.166 |
|
- type: ndcg_at_3 |
|
value: 36.344 |
|
- type: ndcg_at_5 |
|
value: 38.36 |
|
- type: precision_at_1 |
|
value: 31.423000000000002 |
|
- type: precision_at_10 |
|
value: 7.767 |
|
- type: precision_at_100 |
|
value: 1.498 |
|
- type: precision_at_1000 |
|
value: 0.23700000000000002 |
|
- type: precision_at_3 |
|
value: 16.733 |
|
- type: precision_at_5 |
|
value: 12.213000000000001 |
|
- type: recall_at_1 |
|
value: 26.291999999999998 |
|
- type: recall_at_10 |
|
value: 51.184 |
|
- type: recall_at_100 |
|
value: 76.041 |
|
- type: recall_at_1000 |
|
value: 94.11500000000001 |
|
- type: recall_at_3 |
|
value: 38.257000000000005 |
|
- type: recall_at_5 |
|
value: 43.68 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.715 |
|
- type: map_at_10 |
|
value: 27.810000000000002 |
|
- type: map_at_100 |
|
value: 28.810999999999996 |
|
- type: map_at_1000 |
|
value: 28.904999999999998 |
|
- type: map_at_3 |
|
value: 25.069999999999997 |
|
- type: map_at_5 |
|
value: 26.793 |
|
- type: mrr_at_1 |
|
value: 22.366 |
|
- type: mrr_at_10 |
|
value: 29.65 |
|
- type: mrr_at_100 |
|
value: 30.615 |
|
- type: mrr_at_1000 |
|
value: 30.686999999999998 |
|
- type: mrr_at_3 |
|
value: 27.017999999999997 |
|
- type: mrr_at_5 |
|
value: 28.644 |
|
- type: ndcg_at_1 |
|
value: 22.366 |
|
- type: ndcg_at_10 |
|
value: 32.221 |
|
- type: ndcg_at_100 |
|
value: 37.313 |
|
- type: ndcg_at_1000 |
|
value: 39.871 |
|
- type: ndcg_at_3 |
|
value: 26.918 |
|
- type: ndcg_at_5 |
|
value: 29.813000000000002 |
|
- type: precision_at_1 |
|
value: 22.366 |
|
- type: precision_at_10 |
|
value: 5.139 |
|
- type: precision_at_100 |
|
value: 0.8240000000000001 |
|
- type: precision_at_1000 |
|
value: 0.11199999999999999 |
|
- type: precision_at_3 |
|
value: 11.275 |
|
- type: precision_at_5 |
|
value: 8.540000000000001 |
|
- type: recall_at_1 |
|
value: 20.715 |
|
- type: recall_at_10 |
|
value: 44.023 |
|
- type: recall_at_100 |
|
value: 67.458 |
|
- type: recall_at_1000 |
|
value: 87.066 |
|
- type: recall_at_3 |
|
value: 30.055 |
|
- type: recall_at_5 |
|
value: 36.852000000000004 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: climate-fever |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: 392b78eb68c07badcd7c2cd8f39af108375dfcce |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.859 |
|
- type: map_at_10 |
|
value: 20.625 |
|
- type: map_at_100 |
|
value: 22.5 |
|
- type: map_at_1000 |
|
value: 22.689 |
|
- type: map_at_3 |
|
value: 16.991 |
|
- type: map_at_5 |
|
value: 18.781 |
|
- type: mrr_at_1 |
|
value: 26.906000000000002 |
|
- type: mrr_at_10 |
|
value: 39.083 |
|
- type: mrr_at_100 |
|
value: 39.978 |
|
- type: mrr_at_1000 |
|
value: 40.014 |
|
- type: mrr_at_3 |
|
value: 35.44 |
|
- type: mrr_at_5 |
|
value: 37.619 |
|
- type: ndcg_at_1 |
|
value: 26.906000000000002 |
|
- type: ndcg_at_10 |
|
value: 29.386000000000003 |
|
- type: ndcg_at_100 |
|
value: 36.510999999999996 |
|
- type: ndcg_at_1000 |
|
value: 39.814 |
|
- type: ndcg_at_3 |
|
value: 23.558 |
|
- type: ndcg_at_5 |
|
value: 25.557999999999996 |
|
- type: precision_at_1 |
|
value: 26.906000000000002 |
|
- type: precision_at_10 |
|
value: 9.342 |
|
- type: precision_at_100 |
|
value: 1.6969999999999998 |
|
- type: precision_at_1000 |
|
value: 0.231 |
|
- type: precision_at_3 |
|
value: 17.503 |
|
- type: precision_at_5 |
|
value: 13.655000000000001 |
|
- type: recall_at_1 |
|
value: 11.859 |
|
- type: recall_at_10 |
|
value: 35.929 |
|
- type: recall_at_100 |
|
value: 60.21300000000001 |
|
- type: recall_at_1000 |
|
value: 78.606 |
|
- type: recall_at_3 |
|
value: 21.727 |
|
- type: recall_at_5 |
|
value: 27.349 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: dbpedia-entity |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: f097057d03ed98220bc7309ddb10b71a54d667d6 |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.627 |
|
- type: map_at_10 |
|
value: 18.248 |
|
- type: map_at_100 |
|
value: 25.19 |
|
- type: map_at_1000 |
|
value: 26.741 |
|
- type: map_at_3 |
|
value: 13.286000000000001 |
|
- type: map_at_5 |
|
value: 15.126000000000001 |
|
- type: mrr_at_1 |
|
value: 64.75 |
|
- type: mrr_at_10 |
|
value: 71.865 |
|
- type: mrr_at_100 |
|
value: 72.247 |
|
- type: mrr_at_1000 |
|
value: 72.255 |
|
- type: mrr_at_3 |
|
value: 69.958 |
|
- type: mrr_at_5 |
|
value: 71.108 |
|
- type: ndcg_at_1 |
|
value: 53.25 |
|
- type: ndcg_at_10 |
|
value: 39.035 |
|
- type: ndcg_at_100 |
|
value: 42.735 |
|
- type: ndcg_at_1000 |
|
value: 50.166 |
|
- type: ndcg_at_3 |
|
value: 43.857 |
|
- type: ndcg_at_5 |
|
value: 40.579 |
|
- type: precision_at_1 |
|
value: 64.75 |
|
- type: precision_at_10 |
|
value: 30.75 |
|
- type: precision_at_100 |
|
value: 9.54 |
|
- type: precision_at_1000 |
|
value: 2.035 |
|
- type: precision_at_3 |
|
value: 47.333 |
|
- type: precision_at_5 |
|
value: 39.0 |
|
- type: recall_at_1 |
|
value: 8.627 |
|
- type: recall_at_10 |
|
value: 23.413 |
|
- type: recall_at_100 |
|
value: 48.037 |
|
- type: recall_at_1000 |
|
value: 71.428 |
|
- type: recall_at_3 |
|
value: 14.158999999999999 |
|
- type: recall_at_5 |
|
value: 17.002 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/emotion |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 829147f8f75a25f005913200eb5ed41fae320aa1 |
|
metrics: |
|
- type: accuracy |
|
value: 44.865 |
|
- type: f1 |
|
value: 41.56625743266997 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fever |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: 1429cf27e393599b8b359b9b72c666f96b2525f9 |
|
metrics: |
|
- type: map_at_1 |
|
value: 57.335 |
|
- type: map_at_10 |
|
value: 68.29499999999999 |
|
- type: map_at_100 |
|
value: 68.69800000000001 |
|
- type: map_at_1000 |
|
value: 68.714 |
|
- type: map_at_3 |
|
value: 66.149 |
|
- type: map_at_5 |
|
value: 67.539 |
|
- type: mrr_at_1 |
|
value: 61.656 |
|
- type: mrr_at_10 |
|
value: 72.609 |
|
- type: mrr_at_100 |
|
value: 72.923 |
|
- type: mrr_at_1000 |
|
value: 72.928 |
|
- type: mrr_at_3 |
|
value: 70.645 |
|
- type: mrr_at_5 |
|
value: 71.938 |
|
- type: ndcg_at_1 |
|
value: 61.656 |
|
- type: ndcg_at_10 |
|
value: 73.966 |
|
- type: ndcg_at_100 |
|
value: 75.663 |
|
- type: ndcg_at_1000 |
|
value: 75.986 |
|
- type: ndcg_at_3 |
|
value: 69.959 |
|
- type: ndcg_at_5 |
|
value: 72.269 |
|
- type: precision_at_1 |
|
value: 61.656 |
|
- type: precision_at_10 |
|
value: 9.581000000000001 |
|
- type: precision_at_100 |
|
value: 1.054 |
|
- type: precision_at_1000 |
|
value: 0.11 |
|
- type: precision_at_3 |
|
value: 27.743000000000002 |
|
- type: precision_at_5 |
|
value: 17.939 |
|
- type: recall_at_1 |
|
value: 57.335 |
|
- type: recall_at_10 |
|
value: 87.24300000000001 |
|
- type: recall_at_100 |
|
value: 94.575 |
|
- type: recall_at_1000 |
|
value: 96.75399999999999 |
|
- type: recall_at_3 |
|
value: 76.44800000000001 |
|
- type: recall_at_5 |
|
value: 82.122 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fiqa |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: 41b686a7f28c59bcaaa5791efd47c67c8ebe28be |
|
metrics: |
|
- type: map_at_1 |
|
value: 17.014000000000003 |
|
- type: map_at_10 |
|
value: 28.469 |
|
- type: map_at_100 |
|
value: 30.178 |
|
- type: map_at_1000 |
|
value: 30.369 |
|
- type: map_at_3 |
|
value: 24.63 |
|
- type: map_at_5 |
|
value: 26.891 |
|
- type: mrr_at_1 |
|
value: 34.259 |
|
- type: mrr_at_10 |
|
value: 43.042 |
|
- type: mrr_at_100 |
|
value: 43.91 |
|
- type: mrr_at_1000 |
|
value: 43.963 |
|
- type: mrr_at_3 |
|
value: 40.483999999999995 |
|
- type: mrr_at_5 |
|
value: 42.135 |
|
- type: ndcg_at_1 |
|
value: 34.259 |
|
- type: ndcg_at_10 |
|
value: 35.836 |
|
- type: ndcg_at_100 |
|
value: 42.488 |
|
- type: ndcg_at_1000 |
|
value: 45.902 |
|
- type: ndcg_at_3 |
|
value: 32.131 |
|
- type: ndcg_at_5 |
|
value: 33.697 |
|
- type: precision_at_1 |
|
value: 34.259 |
|
- type: precision_at_10 |
|
value: 10.0 |
|
- type: precision_at_100 |
|
value: 1.699 |
|
- type: precision_at_1000 |
|
value: 0.22999999999999998 |
|
- type: precision_at_3 |
|
value: 21.502 |
|
- type: precision_at_5 |
|
value: 16.296 |
|
- type: recall_at_1 |
|
value: 17.014000000000003 |
|
- type: recall_at_10 |
|
value: 42.832 |
|
- type: recall_at_100 |
|
value: 67.619 |
|
- type: recall_at_1000 |
|
value: 88.453 |
|
- type: recall_at_3 |
|
value: 29.537000000000003 |
|
- type: recall_at_5 |
|
value: 35.886 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: hotpotqa |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: 766870b35a1b9ca65e67a0d1913899973551fc6c |
|
metrics: |
|
- type: map_at_1 |
|
value: 34.558 |
|
- type: map_at_10 |
|
value: 48.039 |
|
- type: map_at_100 |
|
value: 48.867 |
|
- type: map_at_1000 |
|
value: 48.941 |
|
- type: map_at_3 |
|
value: 45.403 |
|
- type: map_at_5 |
|
value: 46.983999999999995 |
|
- type: mrr_at_1 |
|
value: 69.11500000000001 |
|
- type: mrr_at_10 |
|
value: 75.551 |
|
- type: mrr_at_100 |
|
value: 75.872 |
|
- type: mrr_at_1000 |
|
value: 75.887 |
|
- type: mrr_at_3 |
|
value: 74.447 |
|
- type: mrr_at_5 |
|
value: 75.113 |
|
- type: ndcg_at_1 |
|
value: 69.11500000000001 |
|
- type: ndcg_at_10 |
|
value: 57.25599999999999 |
|
- type: ndcg_at_100 |
|
value: 60.417 |
|
- type: ndcg_at_1000 |
|
value: 61.976 |
|
- type: ndcg_at_3 |
|
value: 53.258 |
|
- type: ndcg_at_5 |
|
value: 55.374 |
|
- type: precision_at_1 |
|
value: 69.11500000000001 |
|
- type: precision_at_10 |
|
value: 11.689 |
|
- type: precision_at_100 |
|
value: 1.418 |
|
- type: precision_at_1000 |
|
value: 0.163 |
|
- type: precision_at_3 |
|
value: 33.018 |
|
- type: precision_at_5 |
|
value: 21.488 |
|
- type: recall_at_1 |
|
value: 34.558 |
|
- type: recall_at_10 |
|
value: 58.447 |
|
- type: recall_at_100 |
|
value: 70.91199999999999 |
|
- type: recall_at_1000 |
|
value: 81.31 |
|
- type: recall_at_3 |
|
value: 49.527 |
|
- type: recall_at_5 |
|
value: 53.72 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/imdb |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 8d743909f834c38949e8323a8a6ce8721ea6c7f4 |
|
metrics: |
|
- type: accuracy |
|
value: 61.772000000000006 |
|
- type: ap |
|
value: 57.48217702943605 |
|
- type: f1 |
|
value: 61.20495351356274 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: msmarco |
|
name: MTEB MSMARCO |
|
config: default |
|
split: validation |
|
revision: e6838a846e2408f22cf5cc337ebc83e0bcf77849 |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.044 |
|
- type: map_at_10 |
|
value: 34.211000000000006 |
|
- type: map_at_100 |
|
value: 35.394 |
|
- type: map_at_1000 |
|
value: 35.443000000000005 |
|
- type: map_at_3 |
|
value: 30.318 |
|
- type: map_at_5 |
|
value: 32.535 |
|
- type: mrr_at_1 |
|
value: 22.722 |
|
- type: mrr_at_10 |
|
value: 34.842 |
|
- type: mrr_at_100 |
|
value: 35.954 |
|
- type: mrr_at_1000 |
|
value: 35.997 |
|
- type: mrr_at_3 |
|
value: 30.991000000000003 |
|
- type: mrr_at_5 |
|
value: 33.2 |
|
- type: ndcg_at_1 |
|
value: 22.722 |
|
- type: ndcg_at_10 |
|
value: 41.121 |
|
- type: ndcg_at_100 |
|
value: 46.841 |
|
- type: ndcg_at_1000 |
|
value: 48.049 |
|
- type: ndcg_at_3 |
|
value: 33.173 |
|
- type: ndcg_at_5 |
|
value: 37.145 |
|
- type: precision_at_1 |
|
value: 22.722 |
|
- type: precision_at_10 |
|
value: 6.516 |
|
- type: precision_at_100 |
|
value: 0.9400000000000001 |
|
- type: precision_at_1000 |
|
value: 0.104 |
|
- type: precision_at_3 |
|
value: 14.093 |
|
- type: precision_at_5 |
|
value: 10.473 |
|
- type: recall_at_1 |
|
value: 22.044 |
|
- type: recall_at_10 |
|
value: 62.382000000000005 |
|
- type: recall_at_100 |
|
value: 88.914 |
|
- type: recall_at_1000 |
|
value: 98.099 |
|
- type: recall_at_3 |
|
value: 40.782000000000004 |
|
- type: recall_at_5 |
|
value: 50.322 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3 |
|
metrics: |
|
- type: accuracy |
|
value: 93.68217054263563 |
|
- type: f1 |
|
value: 93.25810075739523 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (de) |
|
config: de |
|
split: test |
|
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3 |
|
metrics: |
|
- type: accuracy |
|
value: 82.05409974640745 |
|
- type: f1 |
|
value: 80.42814140324903 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (es) |
|
config: es |
|
split: test |
|
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3 |
|
metrics: |
|
- type: accuracy |
|
value: 93.54903268845896 |
|
- type: f1 |
|
value: 92.8909878077932 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (fr) |
|
config: fr |
|
split: test |
|
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3 |
|
metrics: |
|
- type: accuracy |
|
value: 90.98340119010334 |
|
- type: f1 |
|
value: 90.51522537281313 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (hi) |
|
config: hi |
|
split: test |
|
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3 |
|
metrics: |
|
- type: accuracy |
|
value: 89.33309429903191 |
|
- type: f1 |
|
value: 88.60371305209185 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (th) |
|
config: th |
|
split: test |
|
revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3 |
|
metrics: |
|
- type: accuracy |
|
value: 60.4882459312839 |
|
- type: f1 |
|
value: 59.02590456131682 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 6299947a7777084cc2d4b64235bf7190381ce755 |
|
metrics: |
|
- type: accuracy |
|
value: 71.34290925672595 |
|
- type: f1 |
|
value: 54.44803151449109 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (de) |
|
config: de |
|
split: test |
|
revision: 6299947a7777084cc2d4b64235bf7190381ce755 |
|
metrics: |
|
- type: accuracy |
|
value: 61.92448577063963 |
|
- type: f1 |
|
value: 43.125939975781854 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (es) |
|
config: es |
|
split: test |
|
revision: 6299947a7777084cc2d4b64235bf7190381ce755 |
|
metrics: |
|
- type: accuracy |
|
value: 74.48965977318213 |
|
- type: f1 |
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|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 48.036314727639535 |
|
- type: f1 |
|
value: 46.43480413383716 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (sq) |
|
config: sq |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 50.05716207128445 |
|
- type: f1 |
|
value: 48.85821859948888 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (sv) |
|
config: sv |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 51.728312037659705 |
|
- type: f1 |
|
value: 49.89292996950847 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (sw) |
|
config: sw |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 54.21990585070613 |
|
- type: f1 |
|
value: 52.8711542984193 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (ta) |
|
config: ta |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 62.770679219905844 |
|
- type: f1 |
|
value: 63.09441501491594 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (te) |
|
config: te |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 62.58574310692671 |
|
- type: f1 |
|
value: 61.61370697612978 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (th) |
|
config: th |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 45.17821116341628 |
|
- type: f1 |
|
value: 43.85143229183324 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (tl) |
|
config: tl |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 52.064559515803644 |
|
- type: f1 |
|
value: 50.94356892049626 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (tr) |
|
config: tr |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 47.205783456624076 |
|
- type: f1 |
|
value: 47.04223644120489 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (ur) |
|
config: ur |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 64.25689307330195 |
|
- type: f1 |
|
value: 63.89944944984115 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (vi) |
|
config: vi |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 70.60524546065905 |
|
- type: f1 |
|
value: 71.5634157334358 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (zh-CN) |
|
config: zh-CN |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 73.95427034297242 |
|
- type: f1 |
|
value: 74.39706882311063 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (zh-TW) |
|
config: zh-TW |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 70.29926025554808 |
|
- type: f1 |
|
value: 71.32045932560297 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-p2p |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: dcefc037ef84348e49b0d29109e891c01067226b |
|
metrics: |
|
- type: v_measure |
|
value: 31.054474964883806 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-s2s |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 3cd0e71dfbe09d4de0f9e5ecba43e7ce280959dc |
|
metrics: |
|
- type: v_measure |
|
value: 29.259725940477523 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/mind_small |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 31.785007883256572 |
|
- type: mrr |
|
value: 32.983556622438456 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nfcorpus |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: 7eb63cc0c1eb59324d709ebed25fcab851fa7610 |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.742 |
|
- type: map_at_10 |
|
value: 13.074 |
|
- type: map_at_100 |
|
value: 16.716 |
|
- type: map_at_1000 |
|
value: 18.238 |
|
- type: map_at_3 |
|
value: 9.600999999999999 |
|
- type: map_at_5 |
|
value: 11.129999999999999 |
|
- type: mrr_at_1 |
|
value: 47.988 |
|
- type: mrr_at_10 |
|
value: 55.958 |
|
- type: mrr_at_100 |
|
value: 56.58800000000001 |
|
- type: mrr_at_1000 |
|
value: 56.620000000000005 |
|
- type: mrr_at_3 |
|
value: 54.025 |
|
- type: mrr_at_5 |
|
value: 55.31 |
|
- type: ndcg_at_1 |
|
value: 46.44 |
|
- type: ndcg_at_10 |
|
value: 35.776 |
|
- type: ndcg_at_100 |
|
value: 32.891999999999996 |
|
- type: ndcg_at_1000 |
|
value: 41.835 |
|
- type: ndcg_at_3 |
|
value: 41.812 |
|
- type: ndcg_at_5 |
|
value: 39.249 |
|
- type: precision_at_1 |
|
value: 48.297000000000004 |
|
- type: precision_at_10 |
|
value: 26.687 |
|
- type: precision_at_100 |
|
value: 8.511000000000001 |
|
- type: precision_at_1000 |
|
value: 2.128 |
|
- type: precision_at_3 |
|
value: 39.009 |
|
- type: precision_at_5 |
|
value: 33.994 |
|
- type: recall_at_1 |
|
value: 5.742 |
|
- type: recall_at_10 |
|
value: 16.993 |
|
- type: recall_at_100 |
|
value: 33.69 |
|
- type: recall_at_1000 |
|
value: 66.75 |
|
- type: recall_at_3 |
|
value: 10.817 |
|
- type: recall_at_5 |
|
value: 13.256 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nq |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: 6062aefc120bfe8ece5897809fb2e53bfe0d128c |
|
metrics: |
|
- type: map_at_1 |
|
value: 30.789 |
|
- type: map_at_10 |
|
value: 45.751999999999995 |
|
- type: map_at_100 |
|
value: 46.766000000000005 |
|
- type: map_at_1000 |
|
value: 46.798 |
|
- type: map_at_3 |
|
value: 41.746 |
|
- type: map_at_5 |
|
value: 44.046 |
|
- type: mrr_at_1 |
|
value: 34.618 |
|
- type: mrr_at_10 |
|
value: 48.288 |
|
- type: mrr_at_100 |
|
value: 49.071999999999996 |
|
- type: mrr_at_1000 |
|
value: 49.094 |
|
- type: mrr_at_3 |
|
value: 44.979 |
|
- type: mrr_at_5 |
|
value: 46.953 |
|
- type: ndcg_at_1 |
|
value: 34.589 |
|
- type: ndcg_at_10 |
|
value: 53.151 |
|
- type: ndcg_at_100 |
|
value: 57.537000000000006 |
|
- type: ndcg_at_1000 |
|
value: 58.321999999999996 |
|
- type: ndcg_at_3 |
|
value: 45.628 |
|
- type: ndcg_at_5 |
|
value: 49.474000000000004 |
|
- type: precision_at_1 |
|
value: 34.589 |
|
- type: precision_at_10 |
|
value: 8.731 |
|
- type: precision_at_100 |
|
value: 1.119 |
|
- type: precision_at_1000 |
|
value: 0.11900000000000001 |
|
- type: precision_at_3 |
|
value: 20.819 |
|
- type: precision_at_5 |
|
value: 14.728 |
|
- type: recall_at_1 |
|
value: 30.789 |
|
- type: recall_at_10 |
|
value: 73.066 |
|
- type: recall_at_100 |
|
value: 92.27 |
|
- type: recall_at_1000 |
|
value: 98.18 |
|
- type: recall_at_3 |
|
value: 53.632999999999996 |
|
- type: recall_at_5 |
|
value: 62.476 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: quora |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: 6205996560df11e3a3da9ab4f926788fc30a7db4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 54.993 |
|
- type: map_at_10 |
|
value: 69.07600000000001 |
|
- type: map_at_100 |
|
value: 70.05799999999999 |
|
- type: map_at_1000 |
|
value: 70.09 |
|
- type: map_at_3 |
|
value: 65.456 |
|
- type: map_at_5 |
|
value: 67.622 |
|
- type: mrr_at_1 |
|
value: 63.07000000000001 |
|
- type: mrr_at_10 |
|
value: 72.637 |
|
- type: mrr_at_100 |
|
value: 73.029 |
|
- type: mrr_at_1000 |
|
value: 73.033 |
|
- type: mrr_at_3 |
|
value: 70.572 |
|
- type: mrr_at_5 |
|
value: 71.86399999999999 |
|
- type: ndcg_at_1 |
|
value: 63.07000000000001 |
|
- type: ndcg_at_10 |
|
value: 74.708 |
|
- type: ndcg_at_100 |
|
value: 77.579 |
|
- type: ndcg_at_1000 |
|
value: 77.897 |
|
- type: ndcg_at_3 |
|
value: 69.69999999999999 |
|
- type: ndcg_at_5 |
|
value: 72.321 |
|
- type: precision_at_1 |
|
value: 63.07000000000001 |
|
- type: precision_at_10 |
|
value: 11.851 |
|
- type: precision_at_100 |
|
value: 1.481 |
|
- type: precision_at_1000 |
|
value: 0.156 |
|
- type: precision_at_3 |
|
value: 30.747000000000003 |
|
- type: precision_at_5 |
|
value: 20.830000000000002 |
|
- type: recall_at_1 |
|
value: 54.993 |
|
- type: recall_at_10 |
|
value: 87.18900000000001 |
|
- type: recall_at_100 |
|
value: 98.137 |
|
- type: recall_at_1000 |
|
value: 99.833 |
|
- type: recall_at_3 |
|
value: 73.654 |
|
- type: recall_at_5 |
|
value: 80.36 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: b2805658ae38990172679479369a78b86de8c390 |
|
metrics: |
|
- type: v_measure |
|
value: 35.53178375429036 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering-p2p |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33 |
|
metrics: |
|
- type: v_measure |
|
value: 54.520782970558265 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scidocs |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: 5c59ef3e437a0a9651c8fe6fde943e7dce59fba5 |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.3229999999999995 |
|
- type: map_at_10 |
|
value: 10.979999999999999 |
|
- type: map_at_100 |
|
value: 12.867 |
|
- type: map_at_1000 |
|
value: 13.147 |
|
- type: map_at_3 |
|
value: 7.973 |
|
- type: map_at_5 |
|
value: 9.513 |
|
- type: mrr_at_1 |
|
value: 21.3 |
|
- type: mrr_at_10 |
|
value: 32.34 |
|
- type: mrr_at_100 |
|
value: 33.428999999999995 |
|
- type: mrr_at_1000 |
|
value: 33.489999999999995 |
|
- type: mrr_at_3 |
|
value: 28.999999999999996 |
|
- type: mrr_at_5 |
|
value: 31.019999999999996 |
|
- type: ndcg_at_1 |
|
value: 21.3 |
|
- type: ndcg_at_10 |
|
value: 18.619 |
|
- type: ndcg_at_100 |
|
value: 26.108999999999998 |
|
- type: ndcg_at_1000 |
|
value: 31.253999999999998 |
|
- type: ndcg_at_3 |
|
value: 17.842 |
|
- type: ndcg_at_5 |
|
value: 15.673 |
|
- type: precision_at_1 |
|
value: 21.3 |
|
- type: precision_at_10 |
|
value: 9.55 |
|
- type: precision_at_100 |
|
value: 2.0340000000000003 |
|
- type: precision_at_1000 |
|
value: 0.327 |
|
- type: precision_at_3 |
|
value: 16.667 |
|
- type: precision_at_5 |
|
value: 13.76 |
|
- type: recall_at_1 |
|
value: 4.3229999999999995 |
|
- type: recall_at_10 |
|
value: 19.387 |
|
- type: recall_at_100 |
|
value: 41.307 |
|
- type: recall_at_1000 |
|
value: 66.475 |
|
- type: recall_at_3 |
|
value: 10.143 |
|
- type: recall_at_5 |
|
value: 14.007 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sickr-sts |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 78.77975189382573 |
|
- type: cos_sim_spearman |
|
value: 69.81522686267631 |
|
- type: euclidean_pearson |
|
value: 71.37617936889518 |
|
- type: euclidean_spearman |
|
value: 65.71738481148611 |
|
- type: manhattan_pearson |
|
value: 71.58222165832424 |
|
- type: manhattan_spearman |
|
value: 65.86851365286654 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts12-sts |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: fdf84275bb8ce4b49c971d02e84dd1abc677a50f |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.75509450443367 |
|
- type: cos_sim_spearman |
|
value: 69.66180222442091 |
|
- type: euclidean_pearson |
|
value: 74.98512779786111 |
|
- type: euclidean_spearman |
|
value: 69.5997451409469 |
|
- type: manhattan_pearson |
|
value: 75.50135090962459 |
|
- type: manhattan_spearman |
|
value: 69.94984748475302 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts13-sts |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 1591bfcbe8c69d4bf7fe2a16e2451017832cafb9 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.42363892383264 |
|
- type: cos_sim_spearman |
|
value: 79.66529244176742 |
|
- type: euclidean_pearson |
|
value: 79.50429208135942 |
|
- type: euclidean_spearman |
|
value: 80.44767586416276 |
|
- type: manhattan_pearson |
|
value: 79.58563944997708 |
|
- type: manhattan_spearman |
|
value: 80.51452267103 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts14-sts |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: e2125984e7df8b7871f6ae9949cf6b6795e7c54b |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.2749401478149 |
|
- type: cos_sim_spearman |
|
value: 74.6076920702392 |
|
- type: euclidean_pearson |
|
value: 73.3302002952881 |
|
- type: euclidean_spearman |
|
value: 70.67029803077013 |
|
- type: manhattan_pearson |
|
value: 73.52699344010296 |
|
- type: manhattan_spearman |
|
value: 70.8517556194297 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts15-sts |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: 1cd7298cac12a96a373b6a2f18738bb3e739a9b6 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.20884740785921 |
|
- type: cos_sim_spearman |
|
value: 83.80600789090722 |
|
- type: euclidean_pearson |
|
value: 74.9154089816344 |
|
- type: euclidean_spearman |
|
value: 75.69243899592276 |
|
- type: manhattan_pearson |
|
value: 75.0312832634451 |
|
- type: manhattan_spearman |
|
value: 75.78324960357642 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts16-sts |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 360a0b2dff98700d09e634a01e1cc1624d3e42cd |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.63194141000497 |
|
- type: cos_sim_spearman |
|
value: 80.40118418350866 |
|
- type: euclidean_pearson |
|
value: 72.07354384551088 |
|
- type: euclidean_spearman |
|
value: 72.28819150373845 |
|
- type: manhattan_pearson |
|
value: 72.08736119834145 |
|
- type: manhattan_spearman |
|
value: 72.28347083261288 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (ko-ko) |
|
config: ko-ko |
|
split: test |
|
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 66.78512789499386 |
|
- type: cos_sim_spearman |
|
value: 66.89125587193288 |
|
- type: euclidean_pearson |
|
value: 58.74535708627959 |
|
- type: euclidean_spearman |
|
value: 59.62103716794647 |
|
- type: manhattan_pearson |
|
value: 59.00494529143961 |
|
- type: manhattan_spearman |
|
value: 59.832257846799806 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (ar-ar) |
|
config: ar-ar |
|
split: test |
|
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 75.48960503523992 |
|
- type: cos_sim_spearman |
|
value: 76.4223037534204 |
|
- type: euclidean_pearson |
|
value: 64.93966381820944 |
|
- type: euclidean_spearman |
|
value: 62.39697395373789 |
|
- type: manhattan_pearson |
|
value: 65.54480770061505 |
|
- type: manhattan_spearman |
|
value: 62.944204863043105 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (en-ar) |
|
config: en-ar |
|
split: test |
|
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.7331440643619 |
|
- type: cos_sim_spearman |
|
value: 78.0748413292835 |
|
- type: euclidean_pearson |
|
value: 38.533108233460304 |
|
- type: euclidean_spearman |
|
value: 35.37638615280026 |
|
- type: manhattan_pearson |
|
value: 41.0639726746513 |
|
- type: manhattan_spearman |
|
value: 37.688161243671765 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (en-de) |
|
config: en-de |
|
split: test |
|
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 58.4628923720782 |
|
- type: cos_sim_spearman |
|
value: 59.10093128795948 |
|
- type: euclidean_pearson |
|
value: 30.422902393436836 |
|
- type: euclidean_spearman |
|
value: 27.837806030497457 |
|
- type: manhattan_pearson |
|
value: 32.51576984630963 |
|
- type: manhattan_spearman |
|
value: 29.181887010982514 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (en-en) |
|
config: en-en |
|
split: test |
|
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.87447904613737 |
|
- type: cos_sim_spearman |
|
value: 87.06554974065622 |
|
- type: euclidean_pearson |
|
value: 76.82669047851108 |
|
- type: euclidean_spearman |
|
value: 75.45711985511991 |
|
- type: manhattan_pearson |
|
value: 77.46644556452847 |
|
- type: manhattan_spearman |
|
value: 76.0249120007112 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (en-tr) |
|
config: en-tr |
|
split: test |
|
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 17.784495723497468 |
|
- type: cos_sim_spearman |
|
value: 11.79629537128697 |
|
- type: euclidean_pearson |
|
value: -4.354328445994008 |
|
- type: euclidean_spearman |
|
value: -6.984566116230058 |
|
- type: manhattan_pearson |
|
value: -4.166751901507852 |
|
- type: manhattan_spearman |
|
value: -6.984143198323786 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (es-en) |
|
config: es-en |
|
split: test |
|
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 76.9009642643449 |
|
- type: cos_sim_spearman |
|
value: 78.21764726338341 |
|
- type: euclidean_pearson |
|
value: 50.578959144342925 |
|
- type: euclidean_spearman |
|
value: 51.664379260719606 |
|
- type: manhattan_pearson |
|
value: 53.95690880393329 |
|
- type: manhattan_spearman |
|
value: 54.910058464050785 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (es-es) |
|
config: es-es |
|
split: test |
|
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.41638022270219 |
|
- type: cos_sim_spearman |
|
value: 86.00477030366811 |
|
- type: euclidean_pearson |
|
value: 79.7224037788285 |
|
- type: euclidean_spearman |
|
value: 79.21417626867616 |
|
- type: manhattan_pearson |
|
value: 80.29412412756984 |
|
- type: manhattan_spearman |
|
value: 79.49460867616206 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (fr-en) |
|
config: fr-en |
|
split: test |
|
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.90432664091082 |
|
- type: cos_sim_spearman |
|
value: 80.46007940700204 |
|
- type: euclidean_pearson |
|
value: 49.25348015214428 |
|
- type: euclidean_spearman |
|
value: 47.13113020475859 |
|
- type: manhattan_pearson |
|
value: 54.57291204043908 |
|
- type: manhattan_spearman |
|
value: 51.98559736896087 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (it-en) |
|
config: it-en |
|
split: test |
|
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 52.55164822309034 |
|
- type: cos_sim_spearman |
|
value: 51.57629192137736 |
|
- type: euclidean_pearson |
|
value: 16.63360593235354 |
|
- type: euclidean_spearman |
|
value: 14.479679923782912 |
|
- type: manhattan_pearson |
|
value: 18.524867185117472 |
|
- type: manhattan_spearman |
|
value: 16.65940056664755 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (nl-en) |
|
config: nl-en |
|
split: test |
|
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 46.83690919715875 |
|
- type: cos_sim_spearman |
|
value: 45.84993650002922 |
|
- type: euclidean_pearson |
|
value: 6.173128686815117 |
|
- type: euclidean_spearman |
|
value: 6.260781946306191 |
|
- type: manhattan_pearson |
|
value: 7.328440452367316 |
|
- type: manhattan_spearman |
|
value: 7.370842306497447 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (en) |
|
config: en |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 64.97916914277232 |
|
- type: cos_sim_spearman |
|
value: 66.13392188807865 |
|
- type: euclidean_pearson |
|
value: 65.3921146908468 |
|
- type: euclidean_spearman |
|
value: 65.8381588635056 |
|
- type: manhattan_pearson |
|
value: 65.8866165769975 |
|
- type: manhattan_spearman |
|
value: 66.27774050472219 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (de) |
|
config: de |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 25.605130445111545 |
|
- type: cos_sim_spearman |
|
value: 30.054844562369254 |
|
- type: euclidean_pearson |
|
value: 23.890611005408196 |
|
- type: euclidean_spearman |
|
value: 29.07902600726761 |
|
- type: manhattan_pearson |
|
value: 24.239478426621833 |
|
- type: manhattan_spearman |
|
value: 29.48547576782375 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (es) |
|
config: es |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 61.6665616159781 |
|
- type: cos_sim_spearman |
|
value: 65.41310206289988 |
|
- type: euclidean_pearson |
|
value: 68.38805493215008 |
|
- type: euclidean_spearman |
|
value: 65.22777377603435 |
|
- type: manhattan_pearson |
|
value: 69.37445390454346 |
|
- type: manhattan_spearman |
|
value: 66.02437701858754 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (pl) |
|
config: pl |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 15.302891825626372 |
|
- type: cos_sim_spearman |
|
value: 31.134517255070097 |
|
- type: euclidean_pearson |
|
value: 12.672592658843143 |
|
- type: euclidean_spearman |
|
value: 29.14881036784207 |
|
- type: manhattan_pearson |
|
value: 13.528545327757735 |
|
- type: manhattan_spearman |
|
value: 29.56217928148797 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (tr) |
|
config: tr |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 28.79299114515319 |
|
- type: cos_sim_spearman |
|
value: 47.135864983626206 |
|
- type: euclidean_pearson |
|
value: 40.66410787594309 |
|
- type: euclidean_spearman |
|
value: 45.09585593138228 |
|
- type: manhattan_pearson |
|
value: 42.02561630700308 |
|
- type: manhattan_spearman |
|
value: 45.43979983670554 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (ar) |
|
config: ar |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 46.00096625052943 |
|
- type: cos_sim_spearman |
|
value: 58.67147426715496 |
|
- type: euclidean_pearson |
|
value: 54.7154367422438 |
|
- type: euclidean_spearman |
|
value: 59.003235142442634 |
|
- type: manhattan_pearson |
|
value: 56.3116235357115 |
|
- type: manhattan_spearman |
|
value: 60.12956331404423 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (ru) |
|
config: ru |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 29.3396354650316 |
|
- type: cos_sim_spearman |
|
value: 43.3632935734809 |
|
- type: euclidean_pearson |
|
value: 31.18506539466593 |
|
- type: euclidean_spearman |
|
value: 37.531745324803815 |
|
- type: manhattan_pearson |
|
value: 32.829038232529015 |
|
- type: manhattan_spearman |
|
value: 38.04574361589953 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (zh) |
|
config: zh |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 62.9596148375188 |
|
- type: cos_sim_spearman |
|
value: 66.77653412402461 |
|
- type: euclidean_pearson |
|
value: 64.53156585980886 |
|
- type: euclidean_spearman |
|
value: 66.2884373036083 |
|
- type: manhattan_pearson |
|
value: 65.2831035495143 |
|
- type: manhattan_spearman |
|
value: 66.83641945244322 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (fr) |
|
config: fr |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.9138821493919 |
|
- type: cos_sim_spearman |
|
value: 80.38097535004677 |
|
- type: euclidean_pearson |
|
value: 76.2401499094322 |
|
- type: euclidean_spearman |
|
value: 77.00897050735907 |
|
- type: manhattan_pearson |
|
value: 76.69531453728563 |
|
- type: manhattan_spearman |
|
value: 77.83189696428695 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (de-en) |
|
config: de-en |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 51.27009640779202 |
|
- type: cos_sim_spearman |
|
value: 51.16120562029285 |
|
- type: euclidean_pearson |
|
value: 52.20594985566323 |
|
- type: euclidean_spearman |
|
value: 52.75331049709882 |
|
- type: manhattan_pearson |
|
value: 52.2725118792549 |
|
- type: manhattan_spearman |
|
value: 53.614847968995115 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (es-en) |
|
config: es-en |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 70.46044814118835 |
|
- type: cos_sim_spearman |
|
value: 75.05760236668672 |
|
- type: euclidean_pearson |
|
value: 72.80128921879461 |
|
- type: euclidean_spearman |
|
value: 73.81164755219257 |
|
- type: manhattan_pearson |
|
value: 72.7863795809044 |
|
- type: manhattan_spearman |
|
value: 73.65932033818906 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (it) |
|
config: it |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 61.89276840435938 |
|
- type: cos_sim_spearman |
|
value: 65.65042955732055 |
|
- type: euclidean_pearson |
|
value: 61.22969491863841 |
|
- type: euclidean_spearman |
|
value: 63.451215637904724 |
|
- type: manhattan_pearson |
|
value: 61.16138956945465 |
|
- type: manhattan_spearman |
|
value: 63.34966179331079 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (pl-en) |
|
config: pl-en |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 56.377577221753626 |
|
- type: cos_sim_spearman |
|
value: 53.31223653270353 |
|
- type: euclidean_pearson |
|
value: 26.488793041564307 |
|
- type: euclidean_spearman |
|
value: 19.524551741701472 |
|
- type: manhattan_pearson |
|
value: 24.322868054606474 |
|
- type: manhattan_spearman |
|
value: 19.50371443994939 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (zh-en) |
|
config: zh-en |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 69.3634693673425 |
|
- type: cos_sim_spearman |
|
value: 68.45051245419702 |
|
- type: euclidean_pearson |
|
value: 56.1417414374769 |
|
- type: euclidean_spearman |
|
value: 55.89891749631458 |
|
- type: manhattan_pearson |
|
value: 57.266417430882925 |
|
- type: manhattan_spearman |
|
value: 56.57927102744128 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (es-it) |
|
config: es-it |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 60.04169437653179 |
|
- type: cos_sim_spearman |
|
value: 65.49531007553446 |
|
- type: euclidean_pearson |
|
value: 58.583860732586324 |
|
- type: euclidean_spearman |
|
value: 58.80034792537441 |
|
- type: manhattan_pearson |
|
value: 59.02513161664622 |
|
- type: manhattan_spearman |
|
value: 58.42942047904558 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (de-fr) |
|
config: de-fr |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 48.81035211493999 |
|
- type: cos_sim_spearman |
|
value: 53.27599246786967 |
|
- type: euclidean_pearson |
|
value: 52.25710699032889 |
|
- type: euclidean_spearman |
|
value: 55.22995695529873 |
|
- type: manhattan_pearson |
|
value: 51.894901893217884 |
|
- type: manhattan_spearman |
|
value: 54.95919975149795 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (de-pl) |
|
config: de-pl |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 36.75993101477816 |
|
- type: cos_sim_spearman |
|
value: 43.050156692479355 |
|
- type: euclidean_pearson |
|
value: 51.49021084746248 |
|
- type: euclidean_spearman |
|
value: 49.54771253090078 |
|
- type: manhattan_pearson |
|
value: 54.68410760796417 |
|
- type: manhattan_spearman |
|
value: 48.19277197691717 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (fr-pl) |
|
config: fr-pl |
|
split: test |
|
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 48.553763306386486 |
|
- type: cos_sim_spearman |
|
value: 28.17180849095055 |
|
- type: euclidean_pearson |
|
value: 17.50739087826514 |
|
- type: euclidean_spearman |
|
value: 16.903085094570333 |
|
- type: manhattan_pearson |
|
value: 20.750046512534112 |
|
- type: manhattan_spearman |
|
value: 5.634361698190111 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsbenchmark-sts |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: 8913289635987208e6e7c72789e4be2fe94b6abd |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.17107190594417 |
|
- type: cos_sim_spearman |
|
value: 80.89611873505183 |
|
- type: euclidean_pearson |
|
value: 71.82491561814403 |
|
- type: euclidean_spearman |
|
value: 70.33608835403274 |
|
- type: manhattan_pearson |
|
value: 71.89538332420133 |
|
- type: manhattan_spearman |
|
value: 70.36082395775944 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/scidocs-reranking |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: 56a6d0140cf6356659e2a7c1413286a774468d44 |
|
metrics: |
|
- type: map |
|
value: 79.77047154974562 |
|
- type: mrr |
|
value: 94.25887021475256 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scifact |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: a75ae049398addde9b70f6b268875f5cbce99089 |
|
metrics: |
|
- type: map_at_1 |
|
value: 56.328 |
|
- type: map_at_10 |
|
value: 67.167 |
|
- type: map_at_100 |
|
value: 67.721 |
|
- type: map_at_1000 |
|
value: 67.735 |
|
- type: map_at_3 |
|
value: 64.20400000000001 |
|
- type: map_at_5 |
|
value: 65.904 |
|
- type: mrr_at_1 |
|
value: 59.667 |
|
- type: mrr_at_10 |
|
value: 68.553 |
|
- type: mrr_at_100 |
|
value: 68.992 |
|
- type: mrr_at_1000 |
|
value: 69.004 |
|
- type: mrr_at_3 |
|
value: 66.22200000000001 |
|
- type: mrr_at_5 |
|
value: 67.739 |
|
- type: ndcg_at_1 |
|
value: 59.667 |
|
- type: ndcg_at_10 |
|
value: 72.111 |
|
- type: ndcg_at_100 |
|
value: 74.441 |
|
- type: ndcg_at_1000 |
|
value: 74.90599999999999 |
|
- type: ndcg_at_3 |
|
value: 67.11399999999999 |
|
- type: ndcg_at_5 |
|
value: 69.687 |
|
- type: precision_at_1 |
|
value: 59.667 |
|
- type: precision_at_10 |
|
value: 9.733 |
|
- type: precision_at_100 |
|
value: 1.09 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 26.444000000000003 |
|
- type: precision_at_5 |
|
value: 17.599999999999998 |
|
- type: recall_at_1 |
|
value: 56.328 |
|
- type: recall_at_10 |
|
value: 85.8 |
|
- type: recall_at_100 |
|
value: 96.167 |
|
- type: recall_at_1000 |
|
value: 100.0 |
|
- type: recall_at_3 |
|
value: 72.433 |
|
- type: recall_at_5 |
|
value: 78.972 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: 5a8256d0dff9c4bd3be3ba3e67e4e70173f802ea |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.8019801980198 |
|
- type: cos_sim_ap |
|
value: 94.92527097094644 |
|
- type: cos_sim_f1 |
|
value: 89.91935483870968 |
|
- type: cos_sim_precision |
|
value: 90.65040650406505 |
|
- type: cos_sim_recall |
|
value: 89.2 |
|
- type: dot_accuracy |
|
value: 99.51782178217822 |
|
- type: dot_ap |
|
value: 81.30756869559929 |
|
- type: dot_f1 |
|
value: 75.88235294117648 |
|
- type: dot_precision |
|
value: 74.42307692307692 |
|
- type: dot_recall |
|
value: 77.4 |
|
- type: euclidean_accuracy |
|
value: 99.73069306930694 |
|
- type: euclidean_ap |
|
value: 91.05040371796932 |
|
- type: euclidean_f1 |
|
value: 85.7889237199582 |
|
- type: euclidean_precision |
|
value: 89.82494529540482 |
|
- type: euclidean_recall |
|
value: 82.1 |
|
- type: manhattan_accuracy |
|
value: 99.73762376237623 |
|
- type: manhattan_ap |
|
value: 91.4823412839869 |
|
- type: manhattan_f1 |
|
value: 86.39836984207845 |
|
- type: manhattan_precision |
|
value: 88.05815160955348 |
|
- type: manhattan_recall |
|
value: 84.8 |
|
- type: max_accuracy |
|
value: 99.8019801980198 |
|
- type: max_ap |
|
value: 94.92527097094644 |
|
- type: max_f1 |
|
value: 89.91935483870968 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 70a89468f6dccacc6aa2b12a6eac54e74328f235 |
|
metrics: |
|
- type: v_measure |
|
value: 55.13046832022158 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering-p2p |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: d88009ab563dd0b16cfaf4436abaf97fa3550cf0 |
|
metrics: |
|
- type: v_measure |
|
value: 34.31252463546675 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/stackoverflowdupquestions-reranking |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: ef807ea29a75ec4f91b50fd4191cb4ee4589a9f9 |
|
metrics: |
|
- type: map |
|
value: 51.06639688231414 |
|
- type: mrr |
|
value: 51.80205415499534 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: mteb/summeval |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: 8753c2788d36c01fc6f05d03fe3f7268d63f9122 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 31.963331462886957 |
|
- type: cos_sim_spearman |
|
value: 33.59510652629926 |
|
- type: dot_pearson |
|
value: 29.033733540882123 |
|
- type: dot_spearman |
|
value: 31.550290638315504 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: trec-covid |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: 2c8041b2c07a79b6f7ba8fe6acc72e5d9f92d217 |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.23600000000000002 |
|
- type: map_at_10 |
|
value: 2.09 |
|
- type: map_at_100 |
|
value: 12.466000000000001 |
|
- type: map_at_1000 |
|
value: 29.852 |
|
- type: map_at_3 |
|
value: 0.6859999999999999 |
|
- type: map_at_5 |
|
value: 1.099 |
|
- type: mrr_at_1 |
|
value: 88.0 |
|
- type: mrr_at_10 |
|
value: 94.0 |
|
- type: mrr_at_100 |
|
value: 94.0 |
|
- type: mrr_at_1000 |
|
value: 94.0 |
|
- type: mrr_at_3 |
|
value: 94.0 |
|
- type: mrr_at_5 |
|
value: 94.0 |
|
- type: ndcg_at_1 |
|
value: 86.0 |
|
- type: ndcg_at_10 |
|
value: 81.368 |
|
- type: ndcg_at_100 |
|
value: 61.879 |
|
- type: ndcg_at_1000 |
|
value: 55.282 |
|
- type: ndcg_at_3 |
|
value: 84.816 |
|
- type: ndcg_at_5 |
|
value: 82.503 |
|
- type: precision_at_1 |
|
value: 88.0 |
|
- type: precision_at_10 |
|
value: 85.6 |
|
- type: precision_at_100 |
|
value: 63.85999999999999 |
|
- type: precision_at_1000 |
|
value: 24.682000000000002 |
|
- type: precision_at_3 |
|
value: 88.667 |
|
- type: precision_at_5 |
|
value: 86.0 |
|
- type: recall_at_1 |
|
value: 0.23600000000000002 |
|
- type: recall_at_10 |
|
value: 2.25 |
|
- type: recall_at_100 |
|
value: 15.488 |
|
- type: recall_at_1000 |
|
value: 52.196 |
|
- type: recall_at_3 |
|
value: 0.721 |
|
- type: recall_at_5 |
|
value: 1.159 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (sqi-eng) |
|
config: sqi-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 12.7 |
|
- type: f1 |
|
value: 10.384182044950325 |
|
- type: precision |
|
value: 9.805277385275312 |
|
- type: recall |
|
value: 12.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (fry-eng) |
|
config: fry-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 30.63583815028902 |
|
- type: f1 |
|
value: 24.623726947426373 |
|
- type: precision |
|
value: 22.987809919828013 |
|
- type: recall |
|
value: 30.63583815028902 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (kur-eng) |
|
config: kur-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 10.487804878048781 |
|
- type: f1 |
|
value: 8.255945048627975 |
|
- type: precision |
|
value: 7.649047253615001 |
|
- type: recall |
|
value: 10.487804878048781 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (tur-eng) |
|
config: tur-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 8.5 |
|
- type: f1 |
|
value: 6.154428783776609 |
|
- type: precision |
|
value: 5.680727638128585 |
|
- type: recall |
|
value: 8.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (deu-eng) |
|
config: deu-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 73.0 |
|
- type: f1 |
|
value: 70.10046605876393 |
|
- type: precision |
|
value: 69.0018253968254 |
|
- type: recall |
|
value: 73.0 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (nld-eng) |
|
config: nld-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 32.7 |
|
- type: f1 |
|
value: 29.7428583868239 |
|
- type: precision |
|
value: 28.81671359506905 |
|
- type: recall |
|
value: 32.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ron-eng) |
|
config: ron-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 31.5 |
|
- type: f1 |
|
value: 27.228675552174003 |
|
- type: precision |
|
value: 25.950062299847747 |
|
- type: recall |
|
value: 31.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ang-eng) |
|
config: ang-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 35.82089552238806 |
|
- type: f1 |
|
value: 28.75836980510979 |
|
- type: precision |
|
value: 26.971643613434658 |
|
- type: recall |
|
value: 35.82089552238806 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ido-eng) |
|
config: ido-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 49.8 |
|
- type: f1 |
|
value: 43.909237401451776 |
|
- type: precision |
|
value: 41.944763440988936 |
|
- type: recall |
|
value: 49.8 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (jav-eng) |
|
config: jav-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 18.536585365853657 |
|
- type: f1 |
|
value: 15.020182570246751 |
|
- type: precision |
|
value: 14.231108073213337 |
|
- type: recall |
|
value: 18.536585365853657 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (isl-eng) |
|
config: isl-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 8.7 |
|
- type: f1 |
|
value: 6.2934784902885355 |
|
- type: precision |
|
value: 5.685926293425392 |
|
- type: recall |
|
value: 8.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (slv-eng) |
|
config: slv-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 12.879708383961116 |
|
- type: f1 |
|
value: 10.136118341751114 |
|
- type: precision |
|
value: 9.571444036679436 |
|
- type: recall |
|
value: 12.879708383961116 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (cym-eng) |
|
config: cym-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 9.217391304347826 |
|
- type: f1 |
|
value: 6.965003297761793 |
|
- type: precision |
|
value: 6.476093529199119 |
|
- type: recall |
|
value: 9.217391304347826 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (kaz-eng) |
|
config: kaz-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 4.3478260869565215 |
|
- type: f1 |
|
value: 3.3186971707677397 |
|
- type: precision |
|
value: 3.198658632552104 |
|
- type: recall |
|
value: 4.3478260869565215 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (est-eng) |
|
config: est-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 6.9 |
|
- type: f1 |
|
value: 4.760708297894056 |
|
- type: precision |
|
value: 4.28409511756074 |
|
- type: recall |
|
value: 6.9 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (heb-eng) |
|
config: heb-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 2.1999999999999997 |
|
- type: f1 |
|
value: 1.6862703878117107 |
|
- type: precision |
|
value: 1.6048118233915603 |
|
- type: recall |
|
value: 2.1999999999999997 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (gla-eng) |
|
config: gla-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 3.0156815440289506 |
|
- type: f1 |
|
value: 2.0913257250659134 |
|
- type: precision |
|
value: 1.9072775486461648 |
|
- type: recall |
|
value: 3.0156815440289506 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (mar-eng) |
|
config: mar-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 49.0 |
|
- type: f1 |
|
value: 45.5254456536713 |
|
- type: precision |
|
value: 44.134609250398725 |
|
- type: recall |
|
value: 49.0 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (lat-eng) |
|
config: lat-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 33.5 |
|
- type: f1 |
|
value: 28.759893973182564 |
|
- type: precision |
|
value: 27.401259116024836 |
|
- type: recall |
|
value: 33.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (bel-eng) |
|
config: bel-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 10.2 |
|
- type: f1 |
|
value: 8.030039981676275 |
|
- type: precision |
|
value: 7.548748077210127 |
|
- type: recall |
|
value: 10.2 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (pms-eng) |
|
config: pms-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 38.095238095238095 |
|
- type: f1 |
|
value: 31.944999250262406 |
|
- type: precision |
|
value: 30.04452690166976 |
|
- type: recall |
|
value: 38.095238095238095 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (gle-eng) |
|
config: gle-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 4.8 |
|
- type: f1 |
|
value: 3.2638960786708067 |
|
- type: precision |
|
value: 3.0495382950729644 |
|
- type: recall |
|
value: 4.8 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (pes-eng) |
|
config: pes-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 15.8 |
|
- type: f1 |
|
value: 12.131087470371275 |
|
- type: precision |
|
value: 11.141304011547815 |
|
- type: recall |
|
value: 15.8 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (nob-eng) |
|
config: nob-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 23.3 |
|
- type: f1 |
|
value: 21.073044636921384 |
|
- type: precision |
|
value: 20.374220568287285 |
|
- type: recall |
|
value: 23.3 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (bul-eng) |
|
config: bul-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 24.9 |
|
- type: f1 |
|
value: 20.091060685364987 |
|
- type: precision |
|
value: 18.899700591081224 |
|
- type: recall |
|
value: 24.9 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (cbk-eng) |
|
config: cbk-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 70.1 |
|
- type: f1 |
|
value: 64.62940836940835 |
|
- type: precision |
|
value: 62.46559523809524 |
|
- type: recall |
|
value: 70.1 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (hun-eng) |
|
config: hun-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 7.199999999999999 |
|
- type: f1 |
|
value: 5.06613460576115 |
|
- type: precision |
|
value: 4.625224463391809 |
|
- type: recall |
|
value: 7.199999999999999 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (uig-eng) |
|
config: uig-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 1.7999999999999998 |
|
- type: f1 |
|
value: 1.2716249514772895 |
|
- type: precision |
|
value: 1.2107445914723798 |
|
- type: recall |
|
value: 1.7999999999999998 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (rus-eng) |
|
config: rus-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 65.5 |
|
- type: f1 |
|
value: 59.84399711399712 |
|
- type: precision |
|
value: 57.86349567099567 |
|
- type: recall |
|
value: 65.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (spa-eng) |
|
config: spa-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 95.7 |
|
- type: f1 |
|
value: 94.48333333333333 |
|
- type: precision |
|
value: 93.89999999999999 |
|
- type: recall |
|
value: 95.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (hye-eng) |
|
config: hye-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 0.8086253369272237 |
|
- type: f1 |
|
value: 0.4962046191492002 |
|
- type: precision |
|
value: 0.47272438578554393 |
|
- type: recall |
|
value: 0.8086253369272237 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (tel-eng) |
|
config: tel-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 69.23076923076923 |
|
- type: f1 |
|
value: 64.6227941099736 |
|
- type: precision |
|
value: 63.03795877325289 |
|
- type: recall |
|
value: 69.23076923076923 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (afr-eng) |
|
config: afr-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 20.599999999999998 |
|
- type: f1 |
|
value: 16.62410040660465 |
|
- type: precision |
|
value: 15.598352437967069 |
|
- type: recall |
|
value: 20.599999999999998 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (mon-eng) |
|
config: mon-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 4.318181818181818 |
|
- type: f1 |
|
value: 2.846721192535661 |
|
- type: precision |
|
value: 2.6787861417537147 |
|
- type: recall |
|
value: 4.318181818181818 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (arz-eng) |
|
config: arz-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 74.84276729559748 |
|
- type: f1 |
|
value: 70.6638714185884 |
|
- type: precision |
|
value: 68.86792452830188 |
|
- type: recall |
|
value: 74.84276729559748 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (hrv-eng) |
|
config: hrv-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 15.9 |
|
- type: f1 |
|
value: 12.793698974586706 |
|
- type: precision |
|
value: 12.088118017657736 |
|
- type: recall |
|
value: 15.9 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (nov-eng) |
|
config: nov-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 59.92217898832685 |
|
- type: f1 |
|
value: 52.23086900129701 |
|
- type: precision |
|
value: 49.25853869433636 |
|
- type: recall |
|
value: 59.92217898832685 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (gsw-eng) |
|
config: gsw-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 27.350427350427353 |
|
- type: f1 |
|
value: 21.033781033781032 |
|
- type: precision |
|
value: 19.337955491801644 |
|
- type: recall |
|
value: 27.350427350427353 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (nds-eng) |
|
config: nds-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 29.299999999999997 |
|
- type: f1 |
|
value: 23.91597452425777 |
|
- type: precision |
|
value: 22.36696598364942 |
|
- type: recall |
|
value: 29.299999999999997 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ukr-eng) |
|
config: ukr-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 27.3 |
|
- type: f1 |
|
value: 22.059393517688886 |
|
- type: precision |
|
value: 20.503235534170887 |
|
- type: recall |
|
value: 27.3 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (uzb-eng) |
|
config: uzb-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 8.177570093457943 |
|
- type: f1 |
|
value: 4.714367017906037 |
|
- type: precision |
|
value: 4.163882933965758 |
|
- type: recall |
|
value: 8.177570093457943 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (lit-eng) |
|
config: lit-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 5.800000000000001 |
|
- type: f1 |
|
value: 4.4859357432293825 |
|
- type: precision |
|
value: 4.247814465614043 |
|
- type: recall |
|
value: 5.800000000000001 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ina-eng) |
|
config: ina-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 78.4 |
|
- type: f1 |
|
value: 73.67166666666667 |
|
- type: precision |
|
value: 71.83285714285714 |
|
- type: recall |
|
value: 78.4 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (lfn-eng) |
|
config: lfn-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 50.3 |
|
- type: f1 |
|
value: 44.85221545883311 |
|
- type: precision |
|
value: 43.04913026243909 |
|
- type: recall |
|
value: 50.3 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (zsm-eng) |
|
config: zsm-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 83.5 |
|
- type: f1 |
|
value: 79.95151515151515 |
|
- type: precision |
|
value: 78.53611111111111 |
|
- type: recall |
|
value: 83.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ita-eng) |
|
config: ita-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 69.89999999999999 |
|
- type: f1 |
|
value: 65.03756269256269 |
|
- type: precision |
|
value: 63.233519536019536 |
|
- type: recall |
|
value: 69.89999999999999 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (cmn-eng) |
|
config: cmn-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 93.2 |
|
- type: f1 |
|
value: 91.44666666666666 |
|
- type: precision |
|
value: 90.63333333333333 |
|
- type: recall |
|
value: 93.2 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (lvs-eng) |
|
config: lvs-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 8.3 |
|
- type: f1 |
|
value: 6.553388144729963 |
|
- type: precision |
|
value: 6.313497782829976 |
|
- type: recall |
|
value: 8.3 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (glg-eng) |
|
config: glg-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 83.6 |
|
- type: f1 |
|
value: 79.86243107769424 |
|
- type: precision |
|
value: 78.32555555555555 |
|
- type: recall |
|
value: 83.6 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ceb-eng) |
|
config: ceb-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 9.166666666666666 |
|
- type: f1 |
|
value: 6.637753604420271 |
|
- type: precision |
|
value: 6.10568253585495 |
|
- type: recall |
|
value: 9.166666666666666 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (bre-eng) |
|
config: bre-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 7.3999999999999995 |
|
- type: f1 |
|
value: 4.6729483612322165 |
|
- type: precision |
|
value: 4.103844520292658 |
|
- type: recall |
|
value: 7.3999999999999995 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ben-eng) |
|
config: ben-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 80.30000000000001 |
|
- type: f1 |
|
value: 75.97666666666667 |
|
- type: precision |
|
value: 74.16 |
|
- type: recall |
|
value: 80.30000000000001 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (swg-eng) |
|
config: swg-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 23.214285714285715 |
|
- type: f1 |
|
value: 16.88988095238095 |
|
- type: precision |
|
value: 15.364937641723353 |
|
- type: recall |
|
value: 23.214285714285715 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (arq-eng) |
|
config: arq-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 33.15038419319429 |
|
- type: f1 |
|
value: 27.747873024072415 |
|
- type: precision |
|
value: 25.99320572578704 |
|
- type: recall |
|
value: 33.15038419319429 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (kab-eng) |
|
config: kab-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 2.6 |
|
- type: f1 |
|
value: 1.687059048752127 |
|
- type: precision |
|
value: 1.5384884521299 |
|
- type: recall |
|
value: 2.6 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (fra-eng) |
|
config: fra-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 93.30000000000001 |
|
- type: f1 |
|
value: 91.44000000000001 |
|
- type: precision |
|
value: 90.59166666666667 |
|
- type: recall |
|
value: 93.30000000000001 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (por-eng) |
|
config: por-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 94.1 |
|
- type: f1 |
|
value: 92.61666666666667 |
|
- type: precision |
|
value: 91.88333333333333 |
|
- type: recall |
|
value: 94.1 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (tat-eng) |
|
config: tat-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 5.0 |
|
- type: f1 |
|
value: 3.589591971281927 |
|
- type: precision |
|
value: 3.3046491614532854 |
|
- type: recall |
|
value: 5.0 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (oci-eng) |
|
config: oci-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 45.9 |
|
- type: f1 |
|
value: 40.171969141969136 |
|
- type: precision |
|
value: 38.30764368870302 |
|
- type: recall |
|
value: 45.9 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (pol-eng) |
|
config: pol-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 16.900000000000002 |
|
- type: f1 |
|
value: 14.094365204207351 |
|
- type: precision |
|
value: 13.276519841269844 |
|
- type: recall |
|
value: 16.900000000000002 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (war-eng) |
|
config: war-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 12.8 |
|
- type: f1 |
|
value: 10.376574912567156 |
|
- type: precision |
|
value: 9.758423963284509 |
|
- type: recall |
|
value: 12.8 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (aze-eng) |
|
config: aze-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 8.1 |
|
- type: f1 |
|
value: 6.319455355175778 |
|
- type: precision |
|
value: 5.849948830628881 |
|
- type: recall |
|
value: 8.1 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (vie-eng) |
|
config: vie-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 95.5 |
|
- type: f1 |
|
value: 94.19666666666667 |
|
- type: precision |
|
value: 93.60000000000001 |
|
- type: recall |
|
value: 95.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (nno-eng) |
|
config: nno-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 19.1 |
|
- type: f1 |
|
value: 16.280080686081906 |
|
- type: precision |
|
value: 15.451573089395668 |
|
- type: recall |
|
value: 19.1 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (cha-eng) |
|
config: cha-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 30.656934306569344 |
|
- type: f1 |
|
value: 23.2568647897115 |
|
- type: precision |
|
value: 21.260309034031664 |
|
- type: recall |
|
value: 30.656934306569344 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (mhr-eng) |
|
config: mhr-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 2.1999999999999997 |
|
- type: f1 |
|
value: 1.556861047295521 |
|
- type: precision |
|
value: 1.4555993437238521 |
|
- type: recall |
|
value: 2.1999999999999997 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (dan-eng) |
|
config: dan-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 27.500000000000004 |
|
- type: f1 |
|
value: 23.521682636223492 |
|
- type: precision |
|
value: 22.345341306967683 |
|
- type: recall |
|
value: 27.500000000000004 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ell-eng) |
|
config: ell-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 7.3999999999999995 |
|
- type: f1 |
|
value: 5.344253880846173 |
|
- type: precision |
|
value: 4.999794279068863 |
|
- type: recall |
|
value: 7.3999999999999995 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (amh-eng) |
|
config: amh-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 0.5952380952380952 |
|
- type: f1 |
|
value: 0.026455026455026457 |
|
- type: precision |
|
value: 0.013528138528138528 |
|
- type: recall |
|
value: 0.5952380952380952 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (pam-eng) |
|
config: pam-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 7.3 |
|
- type: f1 |
|
value: 5.853140211779251 |
|
- type: precision |
|
value: 5.505563080945322 |
|
- type: recall |
|
value: 7.3 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (hsb-eng) |
|
config: hsb-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 13.250517598343686 |
|
- type: f1 |
|
value: 9.676349506190704 |
|
- type: precision |
|
value: 8.930392053553216 |
|
- type: recall |
|
value: 13.250517598343686 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (srp-eng) |
|
config: srp-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 14.499999999999998 |
|
- type: f1 |
|
value: 11.68912588067557 |
|
- type: precision |
|
value: 11.024716513105519 |
|
- type: recall |
|
value: 14.499999999999998 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (epo-eng) |
|
config: epo-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 30.099999999999998 |
|
- type: f1 |
|
value: 26.196880936315146 |
|
- type: precision |
|
value: 25.271714086169478 |
|
- type: recall |
|
value: 30.099999999999998 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (kzj-eng) |
|
config: kzj-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 6.4 |
|
- type: f1 |
|
value: 5.1749445942023335 |
|
- type: precision |
|
value: 4.975338142029625 |
|
- type: recall |
|
value: 6.4 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (awa-eng) |
|
config: awa-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 39.39393939393939 |
|
- type: f1 |
|
value: 35.005707393767096 |
|
- type: precision |
|
value: 33.64342032053631 |
|
- type: recall |
|
value: 39.39393939393939 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (fao-eng) |
|
config: fao-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 18.3206106870229 |
|
- type: f1 |
|
value: 12.610893447220345 |
|
- type: precision |
|
value: 11.079228765297467 |
|
- type: recall |
|
value: 18.3206106870229 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (mal-eng) |
|
config: mal-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 85.58951965065502 |
|
- type: f1 |
|
value: 83.30363944928548 |
|
- type: precision |
|
value: 82.40026591554977 |
|
- type: recall |
|
value: 85.58951965065502 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ile-eng) |
|
config: ile-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 65.7 |
|
- type: f1 |
|
value: 59.589642857142856 |
|
- type: precision |
|
value: 57.392826797385624 |
|
- type: recall |
|
value: 65.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (bos-eng) |
|
config: bos-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 18.07909604519774 |
|
- type: f1 |
|
value: 13.65194306689995 |
|
- type: precision |
|
value: 12.567953943826327 |
|
- type: recall |
|
value: 18.07909604519774 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (cor-eng) |
|
config: cor-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 4.6 |
|
- type: f1 |
|
value: 2.8335386392505013 |
|
- type: precision |
|
value: 2.558444143575722 |
|
- type: recall |
|
value: 4.6 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (cat-eng) |
|
config: cat-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 90.7 |
|
- type: f1 |
|
value: 88.30666666666666 |
|
- type: precision |
|
value: 87.195 |
|
- type: recall |
|
value: 90.7 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (eus-eng) |
|
config: eus-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 57.699999999999996 |
|
- type: f1 |
|
value: 53.38433067253876 |
|
- type: precision |
|
value: 51.815451335350346 |
|
- type: recall |
|
value: 57.699999999999996 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (yue-eng) |
|
config: yue-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 80.60000000000001 |
|
- type: f1 |
|
value: 77.0290354090354 |
|
- type: precision |
|
value: 75.61685897435898 |
|
- type: recall |
|
value: 80.60000000000001 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (swe-eng) |
|
config: swe-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 24.6 |
|
- type: f1 |
|
value: 19.52814960069739 |
|
- type: precision |
|
value: 18.169084599880502 |
|
- type: recall |
|
value: 24.6 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (dtp-eng) |
|
config: dtp-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 5.0 |
|
- type: f1 |
|
value: 3.4078491753102376 |
|
- type: precision |
|
value: 3.1757682319102387 |
|
- type: recall |
|
value: 5.0 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (kat-eng) |
|
config: kat-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 1.2064343163538873 |
|
- type: f1 |
|
value: 0.4224313053283095 |
|
- type: precision |
|
value: 0.3360484946842894 |
|
- type: recall |
|
value: 1.2064343163538873 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (jpn-eng) |
|
config: jpn-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 76.1 |
|
- type: f1 |
|
value: 71.36246031746032 |
|
- type: precision |
|
value: 69.5086544011544 |
|
- type: recall |
|
value: 76.1 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (csb-eng) |
|
config: csb-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 14.229249011857709 |
|
- type: f1 |
|
value: 10.026578603653704 |
|
- type: precision |
|
value: 9.09171178352764 |
|
- type: recall |
|
value: 14.229249011857709 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (xho-eng) |
|
config: xho-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 8.450704225352112 |
|
- type: f1 |
|
value: 5.51214407186151 |
|
- type: precision |
|
value: 4.928281812084629 |
|
- type: recall |
|
value: 8.450704225352112 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (orv-eng) |
|
config: orv-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 7.664670658682635 |
|
- type: f1 |
|
value: 5.786190079917295 |
|
- type: precision |
|
value: 5.3643643579244 |
|
- type: recall |
|
value: 7.664670658682635 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ind-eng) |
|
config: ind-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 90.5 |
|
- type: f1 |
|
value: 88.03999999999999 |
|
- type: precision |
|
value: 86.94833333333334 |
|
- type: recall |
|
value: 90.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (tuk-eng) |
|
config: tuk-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 7.389162561576355 |
|
- type: f1 |
|
value: 5.482366349556517 |
|
- type: precision |
|
value: 5.156814449917898 |
|
- type: recall |
|
value: 7.389162561576355 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (max-eng) |
|
config: max-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 41.54929577464789 |
|
- type: f1 |
|
value: 36.13520282534367 |
|
- type: precision |
|
value: 34.818226488560995 |
|
- type: recall |
|
value: 41.54929577464789 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (swh-eng) |
|
config: swh-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 20.76923076923077 |
|
- type: f1 |
|
value: 16.742497560177643 |
|
- type: precision |
|
value: 15.965759712090138 |
|
- type: recall |
|
value: 20.76923076923077 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (hin-eng) |
|
config: hin-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 88.1 |
|
- type: f1 |
|
value: 85.23176470588236 |
|
- type: precision |
|
value: 84.04458333333334 |
|
- type: recall |
|
value: 88.1 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (dsb-eng) |
|
config: dsb-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 11.899791231732777 |
|
- type: f1 |
|
value: 8.776706659565102 |
|
- type: precision |
|
value: 8.167815946521582 |
|
- type: recall |
|
value: 11.899791231732777 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ber-eng) |
|
config: ber-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 6.1 |
|
- type: f1 |
|
value: 4.916589537178435 |
|
- type: precision |
|
value: 4.72523017415345 |
|
- type: recall |
|
value: 6.1 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (tam-eng) |
|
config: tam-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 76.54723127035831 |
|
- type: f1 |
|
value: 72.75787187839306 |
|
- type: precision |
|
value: 71.43338442869005 |
|
- type: recall |
|
value: 76.54723127035831 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (slk-eng) |
|
config: slk-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 11.700000000000001 |
|
- type: f1 |
|
value: 9.975679190026007 |
|
- type: precision |
|
value: 9.569927715653522 |
|
- type: recall |
|
value: 11.700000000000001 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (tgl-eng) |
|
config: tgl-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 13.100000000000001 |
|
- type: f1 |
|
value: 10.697335850115408 |
|
- type: precision |
|
value: 10.113816082086341 |
|
- type: recall |
|
value: 13.100000000000001 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ast-eng) |
|
config: ast-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 76.37795275590551 |
|
- type: f1 |
|
value: 71.12860892388451 |
|
- type: precision |
|
value: 68.89763779527559 |
|
- type: recall |
|
value: 76.37795275590551 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (mkd-eng) |
|
config: mkd-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 13.700000000000001 |
|
- type: f1 |
|
value: 10.471861684067568 |
|
- type: precision |
|
value: 9.602902567641697 |
|
- type: recall |
|
value: 13.700000000000001 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (khm-eng) |
|
config: khm-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 0.554016620498615 |
|
- type: f1 |
|
value: 0.37034084643642423 |
|
- type: precision |
|
value: 0.34676040281208437 |
|
- type: recall |
|
value: 0.554016620498615 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ces-eng) |
|
config: ces-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 12.4 |
|
- type: f1 |
|
value: 9.552607451092534 |
|
- type: precision |
|
value: 8.985175505050504 |
|
- type: recall |
|
value: 12.4 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (tzl-eng) |
|
config: tzl-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 33.65384615384615 |
|
- type: f1 |
|
value: 27.820512820512818 |
|
- type: precision |
|
value: 26.09432234432234 |
|
- type: recall |
|
value: 33.65384615384615 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (urd-eng) |
|
config: urd-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 74.5 |
|
- type: f1 |
|
value: 70.09686507936507 |
|
- type: precision |
|
value: 68.3117857142857 |
|
- type: recall |
|
value: 74.5 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (ara-eng) |
|
config: ara-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 88.3 |
|
- type: f1 |
|
value: 85.37333333333333 |
|
- type: precision |
|
value: 84.05833333333334 |
|
- type: recall |
|
value: 88.3 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (kor-eng) |
|
config: kor-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 25.0 |
|
- type: f1 |
|
value: 22.393124632031995 |
|
- type: precision |
|
value: 21.58347686592367 |
|
- type: recall |
|
value: 25.0 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (yid-eng) |
|
config: yid-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 0.589622641509434 |
|
- type: f1 |
|
value: 0.15804980033762941 |
|
- type: precision |
|
value: 0.1393275384872965 |
|
- type: recall |
|
value: 0.589622641509434 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (fin-eng) |
|
config: fin-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 4.1000000000000005 |
|
- type: f1 |
|
value: 3.4069011332551775 |
|
- type: precision |
|
value: 3.1784507042253516 |
|
- type: recall |
|
value: 4.1000000000000005 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (tha-eng) |
|
config: tha-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 3.102189781021898 |
|
- type: f1 |
|
value: 2.223851811694751 |
|
- type: precision |
|
value: 2.103465682299194 |
|
- type: recall |
|
value: 3.102189781021898 |
|
- task: |
|
type: BitextMining |
|
dataset: |
|
type: mteb/tatoeba-bitext-mining |
|
name: MTEB Tatoeba (wuu-eng) |
|
config: wuu-eng |
|
split: test |
|
revision: ed9e4a974f867fd9736efcf222fc3a26487387a5 |
|
metrics: |
|
- type: accuracy |
|
value: 83.1 |
|
- type: f1 |
|
value: 79.58255835667599 |
|
- type: precision |
|
value: 78.09708333333333 |
|
- type: recall |
|
value: 83.1 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: webis-touche2020 |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: 527b7d77e16e343303e68cb6af11d6e18b9f7b3b |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.322 |
|
- type: map_at_10 |
|
value: 8.959999999999999 |
|
- type: map_at_100 |
|
value: 15.136 |
|
- type: map_at_1000 |
|
value: 16.694 |
|
- type: map_at_3 |
|
value: 4.837000000000001 |
|
- type: map_at_5 |
|
value: 6.196 |
|
- type: mrr_at_1 |
|
value: 28.571 |
|
- type: mrr_at_10 |
|
value: 47.589999999999996 |
|
- type: mrr_at_100 |
|
value: 48.166 |
|
- type: mrr_at_1000 |
|
value: 48.169000000000004 |
|
- type: mrr_at_3 |
|
value: 43.197 |
|
- type: mrr_at_5 |
|
value: 45.646 |
|
- type: ndcg_at_1 |
|
value: 26.531 |
|
- type: ndcg_at_10 |
|
value: 23.982 |
|
- type: ndcg_at_100 |
|
value: 35.519 |
|
- type: ndcg_at_1000 |
|
value: 46.878 |
|
- type: ndcg_at_3 |
|
value: 26.801000000000002 |
|
- type: ndcg_at_5 |
|
value: 24.879 |
|
- type: precision_at_1 |
|
value: 28.571 |
|
- type: precision_at_10 |
|
value: 22.041 |
|
- type: precision_at_100 |
|
value: 7.4079999999999995 |
|
- type: precision_at_1000 |
|
value: 1.492 |
|
- type: precision_at_3 |
|
value: 28.571 |
|
- type: precision_at_5 |
|
value: 25.306 |
|
- type: recall_at_1 |
|
value: 2.322 |
|
- type: recall_at_10 |
|
value: 15.443999999999999 |
|
- type: recall_at_100 |
|
value: 45.918 |
|
- type: recall_at_1000 |
|
value: 79.952 |
|
- type: recall_at_3 |
|
value: 6.143 |
|
- type: recall_at_5 |
|
value: 8.737 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/toxic_conversations_50k |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de |
|
metrics: |
|
- type: accuracy |
|
value: 66.5452 |
|
- type: ap |
|
value: 12.99191723223892 |
|
- type: f1 |
|
value: 51.667665096195734 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/tweet_sentiment_extraction |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: 62146448f05be9e52a36b8ee9936447ea787eede |
|
metrics: |
|
- type: accuracy |
|
value: 55.854555744199196 |
|
- type: f1 |
|
value: 56.131766302254185 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/twentynewsgroups-clustering |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 091a54f9a36281ce7d6590ec8c75dd485e7e01d4 |
|
metrics: |
|
- type: v_measure |
|
value: 37.27891385518074 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twittersemeval2015-pairclassification |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 83.53102461703523 |
|
- type: cos_sim_ap |
|
value: 65.30753664579191 |
|
- type: cos_sim_f1 |
|
value: 61.739943872778305 |
|
- type: cos_sim_precision |
|
value: 55.438891222175556 |
|
- type: cos_sim_recall |
|
value: 69.65699208443272 |
|
- type: dot_accuracy |
|
value: 80.38981939560112 |
|
- type: dot_ap |
|
value: 53.52081118421347 |
|
- type: dot_f1 |
|
value: 54.232957844617346 |
|
- type: dot_precision |
|
value: 48.43393486828459 |
|
- type: dot_recall |
|
value: 61.60949868073878 |
|
- type: euclidean_accuracy |
|
value: 82.23758717291531 |
|
- type: euclidean_ap |
|
value: 60.361102792772535 |
|
- type: euclidean_f1 |
|
value: 57.50518791791561 |
|
- type: euclidean_precision |
|
value: 51.06470106470107 |
|
- type: euclidean_recall |
|
value: 65.8047493403694 |
|
- type: manhattan_accuracy |
|
value: 82.14221851344102 |
|
- type: manhattan_ap |
|
value: 60.341937223793366 |
|
- type: manhattan_f1 |
|
value: 57.53803596127247 |
|
- type: manhattan_precision |
|
value: 51.08473188702415 |
|
- type: manhattan_recall |
|
value: 65.85751978891821 |
|
- type: max_accuracy |
|
value: 83.53102461703523 |
|
- type: max_ap |
|
value: 65.30753664579191 |
|
- type: max_f1 |
|
value: 61.739943872778305 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twitterurlcorpus-pairclassification |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.75305623471883 |
|
- type: cos_sim_ap |
|
value: 85.46387153880272 |
|
- type: cos_sim_f1 |
|
value: 77.91527673159008 |
|
- type: cos_sim_precision |
|
value: 72.93667315828353 |
|
- type: cos_sim_recall |
|
value: 83.62334462580844 |
|
- type: dot_accuracy |
|
value: 85.08169363915086 |
|
- type: dot_ap |
|
value: 74.96808060965559 |
|
- type: dot_f1 |
|
value: 71.39685033990366 |
|
- type: dot_precision |
|
value: 64.16948111759288 |
|
- type: dot_recall |
|
value: 80.45888512473051 |
|
- type: euclidean_accuracy |
|
value: 85.84235650250321 |
|
- type: euclidean_ap |
|
value: 78.42045145247211 |
|
- type: euclidean_f1 |
|
value: 70.32669630775179 |
|
- type: euclidean_precision |
|
value: 70.6298050788227 |
|
- type: euclidean_recall |
|
value: 70.02617801047121 |
|
- type: manhattan_accuracy |
|
value: 85.86176116738464 |
|
- type: manhattan_ap |
|
value: 78.54012451558276 |
|
- type: manhattan_f1 |
|
value: 70.56508080693389 |
|
- type: manhattan_precision |
|
value: 69.39626293456413 |
|
- type: manhattan_recall |
|
value: 71.77394518016631 |
|
- type: max_accuracy |
|
value: 88.75305623471883 |
|
- type: max_ap |
|
value: 85.46387153880272 |
|
- type: max_f1 |
|
value: 77.91527673159008 |
|
--- |
|
|
|
## Usage |
|
|
|
For usage instructions, refer to: https://github.com/Muennighoff/sgpt#asymmetric-semantic-search-be |
|
|
|
The model was trained with the command |
|
```bash |
|
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 accelerate launch examples/training/ms_marco/train_bi-encoder_mnrl.py --model_name bigscience/bloom-7b1 --train_batch_size 32 --eval_batch_size 16 --freezenonbias --specb --lr 4e-4 --wandb --wandbwatchlog gradients --pooling weightedmean --gradcache --chunksize 8 |
|
``` |
|
|
|
## Evaluation Results |
|
|
|
|
|
`{"ndcgs": {"sgpt-bloom-7b1-msmarco": {"scifact": {"NDCG@10": 0.71824}, "nfcorpus": {"NDCG@10": 0.35748}, "arguana": {"NDCG@10": 0.47281}, "scidocs": {"NDCG@10": 0.18435}, "fiqa": {"NDCG@10": 0.35736}, "cqadupstack": {"NDCG@10": 0.3708525}, "quora": {"NDCG@10": 0.74655}, "trec-covid": {"NDCG@10": 0.82731}, "webis-touche2020": {"NDCG@10": 0.2365}}}` |
|
|
|
See the evaluation folder or [MTEB](https://huggingface.co/spaces/mteb/leaderboard) for more results. |
|
|
|
## Training |
|
The model was trained with the parameters: |
|
|
|
**DataLoader**: |
|
|
|
`torch.utils.data.dataloader.DataLoader` of length 15600 with parameters: |
|
``` |
|
{'batch_size': 32, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'} |
|
``` |
|
|
|
The model uses BitFit, weighted-mean pooling & GradCache, for details see: https://arxiv.org/abs/2202.08904 |
|
|
|
**Loss**: |
|
|
|
`sentence_transformers.losses.MultipleNegativesRankingLoss.MNRLGradCache` |
|
|
|
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": 0.0004 |
|
}, |
|
"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: BloomModel |
|
(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} |
|
} |
|
``` |
