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--- |
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base_model: BAAI/bge-small-en-v1.5 |
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language: |
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- en |
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license: mit |
|
tags: |
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- sentence-transformers |
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- feature-extraction |
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- sentence-similarity |
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- transformers |
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- mteb |
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- llama-cpp |
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- gguf-my-repo |
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model-index: |
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- name: bge-small-en-v1.5 |
|
results: |
|
- task: |
|
type: Classification |
|
dataset: |
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name: MTEB AmazonCounterfactualClassification (en) |
|
type: mteb/amazon_counterfactual |
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config: en |
|
split: test |
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 73.79104477611939 |
|
- type: ap |
|
value: 37.21923821573361 |
|
- type: f1 |
|
value: 68.0914945617093 |
|
- task: |
|
type: Classification |
|
dataset: |
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name: MTEB AmazonPolarityClassification |
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type: mteb/amazon_polarity |
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config: default |
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split: test |
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revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 92.75377499999999 |
|
- type: ap |
|
value: 89.46766124546022 |
|
- type: f1 |
|
value: 92.73884001331487 |
|
- task: |
|
type: Classification |
|
dataset: |
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name: MTEB AmazonReviewsClassification (en) |
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type: mteb/amazon_reviews_multi |
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config: en |
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split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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metrics: |
|
- type: accuracy |
|
value: 46.986 |
|
- type: f1 |
|
value: 46.55936786727896 |
|
- task: |
|
type: Retrieval |
|
dataset: |
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name: MTEB ArguAna |
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type: arguana |
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config: default |
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split: test |
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revision: None |
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metrics: |
|
- type: map_at_1 |
|
value: 35.846000000000004 |
|
- type: map_at_10 |
|
value: 51.388 |
|
- type: map_at_100 |
|
value: 52.132999999999996 |
|
- type: map_at_1000 |
|
value: 52.141000000000005 |
|
- type: map_at_3 |
|
value: 47.037 |
|
- type: map_at_5 |
|
value: 49.579 |
|
- type: mrr_at_1 |
|
value: 36.558 |
|
- type: mrr_at_10 |
|
value: 51.658 |
|
- type: mrr_at_100 |
|
value: 52.402 |
|
- type: mrr_at_1000 |
|
value: 52.410000000000004 |
|
- type: mrr_at_3 |
|
value: 47.345 |
|
- type: mrr_at_5 |
|
value: 49.797999999999995 |
|
- type: ndcg_at_1 |
|
value: 35.846000000000004 |
|
- type: ndcg_at_10 |
|
value: 59.550000000000004 |
|
- type: ndcg_at_100 |
|
value: 62.596 |
|
- type: ndcg_at_1000 |
|
value: 62.759 |
|
- type: ndcg_at_3 |
|
value: 50.666999999999994 |
|
- type: ndcg_at_5 |
|
value: 55.228 |
|
- type: precision_at_1 |
|
value: 35.846000000000004 |
|
- type: precision_at_10 |
|
value: 8.542 |
|
- type: precision_at_100 |
|
value: 0.984 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 20.389 |
|
- type: precision_at_5 |
|
value: 14.438 |
|
- type: recall_at_1 |
|
value: 35.846000000000004 |
|
- type: recall_at_10 |
|
value: 85.42 |
|
- type: recall_at_100 |
|
value: 98.43499999999999 |
|
- type: recall_at_1000 |
|
value: 99.644 |
|
- type: recall_at_3 |
|
value: 61.166 |
|
- type: recall_at_5 |
|
value: 72.191 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB ArxivClusteringP2P |
|
type: mteb/arxiv-clustering-p2p |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 47.402770198163594 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB ArxivClusteringS2S |
|
type: mteb/arxiv-clustering-s2s |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 40.01545436974177 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB AskUbuntuDupQuestions |
|
type: mteb/askubuntudupquestions-reranking |
|
config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 62.586465273207196 |
|
- type: mrr |
|
value: 74.42169019038825 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB BIOSSES |
|
type: mteb/biosses-sts |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 85.1891186537969 |
|
- type: cos_sim_spearman |
|
value: 83.75492046087288 |
|
- type: euclidean_pearson |
|
value: 84.11766204805357 |
|
- type: euclidean_spearman |
|
value: 84.01456493126516 |
|
- type: manhattan_pearson |
|
value: 84.2132950502772 |
|
- type: manhattan_spearman |
|
value: 83.89227298813377 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB Banking77Classification |
|
type: mteb/banking77 |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 85.74025974025975 |
|
- type: f1 |
|
value: 85.71493566466381 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB BiorxivClusteringP2P |
|
type: mteb/biorxiv-clustering-p2p |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 38.467181385006434 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB BiorxivClusteringS2S |
|
type: mteb/biorxiv-clustering-s2s |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 34.719496037339056 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB CQADupstackAndroidRetrieval |
|
type: BeIR/cqadupstack |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 29.587000000000003 |
|
- type: map_at_10 |
|
value: 41.114 |
|
- type: map_at_100 |
|
value: 42.532 |
|
- type: map_at_1000 |
|
value: 42.661 |
|
- type: map_at_3 |
|
value: 37.483 |
|
- type: map_at_5 |
|
value: 39.652 |
|
- type: mrr_at_1 |
|
value: 36.338 |
|
- type: mrr_at_10 |
|
value: 46.763 |
|
- type: mrr_at_100 |
|
value: 47.393 |
|
- type: mrr_at_1000 |
|
value: 47.445 |
|
- type: mrr_at_3 |
|
value: 43.538 |
|
- type: mrr_at_5 |
|
value: 45.556000000000004 |
|
- type: ndcg_at_1 |
|
value: 36.338 |
|
- type: ndcg_at_10 |
|
value: 47.658 |
|
- type: ndcg_at_100 |
|
value: 52.824000000000005 |
|
- type: ndcg_at_1000 |
|
value: 54.913999999999994 |
|
- type: ndcg_at_3 |
|
value: 41.989 |
|
- type: ndcg_at_5 |
|
value: 44.944 |
|
- type: precision_at_1 |
|
value: 36.338 |
|
- type: precision_at_10 |
|
value: 9.156 |
|
- type: precision_at_100 |
|
value: 1.4789999999999999 |
|
- type: precision_at_1000 |
|
value: 0.196 |
|
- type: precision_at_3 |
|
value: 20.076 |
|
- type: precision_at_5 |
|
value: 14.85 |
|
- type: recall_at_1 |
|
value: 29.587000000000003 |
|
- type: recall_at_10 |
|
value: 60.746 |
|
- type: recall_at_100 |
|
value: 82.157 |
|
- type: recall_at_1000 |
|
value: 95.645 |
|
- type: recall_at_3 |
|
value: 44.821 |
|
- type: recall_at_5 |
|
value: 52.819 |
|
- type: map_at_1 |
|
value: 30.239 |
|
- type: map_at_10 |
|
value: 39.989000000000004 |
|
- type: map_at_100 |
|
value: 41.196 |
|
- type: map_at_1000 |
|
value: 41.325 |
|
- type: map_at_3 |
|
value: 37.261 |
|
- type: map_at_5 |
|
value: 38.833 |
|
- type: mrr_at_1 |
|
value: 37.516 |
|
- type: mrr_at_10 |
|
value: 46.177 |
|
- type: mrr_at_100 |
|
value: 46.806 |
|
- type: mrr_at_1000 |
|
value: 46.849000000000004 |
|
- type: mrr_at_3 |
|
value: 44.002 |
|
- type: mrr_at_5 |
|
value: 45.34 |
|
- type: ndcg_at_1 |
|
value: 37.516 |
|
- type: ndcg_at_10 |
|
value: 45.586 |
|
- type: ndcg_at_100 |
|
value: 49.897000000000006 |
|
- type: ndcg_at_1000 |
|
value: 51.955 |
|
- type: ndcg_at_3 |
|
value: 41.684 |
|
- type: ndcg_at_5 |
|
value: 43.617 |
|
- type: precision_at_1 |
|
value: 37.516 |
|
- type: precision_at_10 |
|
value: 8.522 |
|
- type: precision_at_100 |
|
value: 1.374 |
|
- type: precision_at_1000 |
|
value: 0.184 |
|
- type: precision_at_3 |
|
value: 20.105999999999998 |
|
- type: precision_at_5 |
|
value: 14.152999999999999 |
|
- type: recall_at_1 |
|
value: 30.239 |
|
- type: recall_at_10 |
|
value: 55.03 |
|
- type: recall_at_100 |
|
value: 73.375 |
|
- type: recall_at_1000 |
|
value: 86.29599999999999 |
|
- type: recall_at_3 |
|
value: 43.269000000000005 |
|
- type: recall_at_5 |
|
value: 48.878 |
|
- type: map_at_1 |
|
value: 38.338 |
|
- type: map_at_10 |
|
value: 50.468999999999994 |
|
- type: map_at_100 |
|
value: 51.553000000000004 |
|
- type: map_at_1000 |
|
value: 51.608 |
|
- type: map_at_3 |
|
value: 47.107 |
|
- type: map_at_5 |
|
value: 49.101 |
|
- type: mrr_at_1 |
|
value: 44.201 |
|
- type: mrr_at_10 |
|
value: 54.057 |
|
- type: mrr_at_100 |
|
value: 54.764 |
|
- type: mrr_at_1000 |
|
value: 54.791000000000004 |
|
- type: mrr_at_3 |
|
value: 51.56699999999999 |
|
- type: mrr_at_5 |
|
value: 53.05 |
|
- type: ndcg_at_1 |
|
value: 44.201 |
|
- type: ndcg_at_10 |
|
value: 56.379000000000005 |
|
- type: ndcg_at_100 |
|
value: 60.645 |
|
- type: ndcg_at_1000 |
|
value: 61.73499999999999 |
|
- type: ndcg_at_3 |
|
value: 50.726000000000006 |
|
- type: ndcg_at_5 |
|
value: 53.58500000000001 |
|
- type: precision_at_1 |
|
value: 44.201 |
|
- type: precision_at_10 |
|
value: 9.141 |
|
- type: precision_at_100 |
|
value: 1.216 |
|
- type: precision_at_1000 |
|
value: 0.135 |
|
- type: precision_at_3 |
|
value: 22.654 |
|
- type: precision_at_5 |
|
value: 15.723999999999998 |
|
- type: recall_at_1 |
|
value: 38.338 |
|
- type: recall_at_10 |
|
value: 70.30499999999999 |
|
- type: recall_at_100 |
|
value: 88.77199999999999 |
|
- type: recall_at_1000 |
|
value: 96.49799999999999 |
|
- type: recall_at_3 |
|
value: 55.218 |
|
- type: recall_at_5 |
|
value: 62.104000000000006 |
|
- type: map_at_1 |
|
value: 25.682 |
|
- type: map_at_10 |
|
value: 33.498 |
|
- type: map_at_100 |
|
value: 34.461000000000006 |
|
- type: map_at_1000 |
|
value: 34.544000000000004 |
|
- type: map_at_3 |
|
value: 30.503999999999998 |
|
- type: map_at_5 |
|
value: 32.216 |
|
- type: mrr_at_1 |
|
value: 27.683999999999997 |
|
- type: mrr_at_10 |
|
value: 35.467999999999996 |
|
- type: mrr_at_100 |
|
value: 36.32 |
|
- type: mrr_at_1000 |
|
value: 36.386 |
|
- type: mrr_at_3 |
|
value: 32.618 |
|
- type: mrr_at_5 |
|
value: 34.262 |
|
- type: ndcg_at_1 |
|
value: 27.683999999999997 |
|
- type: ndcg_at_10 |
|
value: 38.378 |
|
- type: ndcg_at_100 |
|
value: 43.288 |
|
- type: ndcg_at_1000 |
|
value: 45.413 |
|
- type: ndcg_at_3 |
|
value: 32.586 |
|
- type: ndcg_at_5 |
|
value: 35.499 |
|
- type: precision_at_1 |
|
value: 27.683999999999997 |
|
- type: precision_at_10 |
|
value: 5.864 |
|
- type: precision_at_100 |
|
value: 0.882 |
|
- type: precision_at_1000 |
|
value: 0.11 |
|
- type: precision_at_3 |
|
value: 13.446 |
|
- type: precision_at_5 |
|
value: 9.718 |
|
- type: recall_at_1 |
|
value: 25.682 |
|
- type: recall_at_10 |
|
value: 51.712 |
|
- type: recall_at_100 |
|
value: 74.446 |
|
- type: recall_at_1000 |
|
value: 90.472 |
|
- type: recall_at_3 |
|
value: 36.236000000000004 |
|
- type: recall_at_5 |
|
value: 43.234 |
|
- type: map_at_1 |
|
value: 16.073999999999998 |
|
- type: map_at_10 |
|
value: 24.352999999999998 |
|
- type: map_at_100 |
|
value: 25.438 |
|
- type: map_at_1000 |
|
value: 25.545 |
|
- type: map_at_3 |
|
value: 21.614 |
|
- type: map_at_5 |
|
value: 23.104 |
|
- type: mrr_at_1 |
|
value: 19.776 |
|
- type: mrr_at_10 |
|
value: 28.837000000000003 |
|
- type: mrr_at_100 |
|
value: 29.755 |
|
- type: mrr_at_1000 |
|
value: 29.817 |
|
- type: mrr_at_3 |
|
value: 26.201999999999998 |
|
- type: mrr_at_5 |
|
value: 27.714 |
|
- type: ndcg_at_1 |
|
value: 19.776 |
|
- type: ndcg_at_10 |
|
value: 29.701 |
|
- type: ndcg_at_100 |
|
value: 35.307 |
|
- type: ndcg_at_1000 |
|
value: 37.942 |
|
- type: ndcg_at_3 |
|
value: 24.764 |
|
- type: ndcg_at_5 |
|
value: 27.025 |
|
- type: precision_at_1 |
|
value: 19.776 |
|
- type: precision_at_10 |
|
value: 5.659 |
|
- type: precision_at_100 |
|
value: 0.971 |
|
- type: precision_at_1000 |
|
value: 0.133 |
|
- type: precision_at_3 |
|
value: 12.065 |
|
- type: precision_at_5 |
|
value: 8.905000000000001 |
|
- type: recall_at_1 |
|
value: 16.073999999999998 |
|
- type: recall_at_10 |
|
value: 41.647 |
|
- type: recall_at_100 |
|
value: 66.884 |
|
- type: recall_at_1000 |
|
value: 85.91499999999999 |
|
- type: recall_at_3 |
|
value: 27.916 |
|
- type: recall_at_5 |
|
value: 33.729 |
|
- type: map_at_1 |
|
value: 28.444999999999997 |
|
- type: map_at_10 |
|
value: 38.218999999999994 |
|
- type: map_at_100 |
|
value: 39.595 |
|
- type: map_at_1000 |
|
value: 39.709 |
|
- type: map_at_3 |
|
value: 35.586 |
|
- type: map_at_5 |
|
value: 36.895 |
|
- type: mrr_at_1 |
|
value: 34.841 |
|
- type: mrr_at_10 |
|
value: 44.106 |
|
- type: mrr_at_100 |
|
value: 44.98 |
|
- type: mrr_at_1000 |
|
value: 45.03 |
|
- type: mrr_at_3 |
|
value: 41.979 |
|
- type: mrr_at_5 |
|
value: 43.047999999999995 |
|
- type: ndcg_at_1 |
|
value: 34.841 |
|
- type: ndcg_at_10 |
|
value: 43.922 |
|
- type: ndcg_at_100 |
|
value: 49.504999999999995 |
|
- type: ndcg_at_1000 |
|
value: 51.675000000000004 |
|
- type: ndcg_at_3 |
|
value: 39.858 |
|
- type: ndcg_at_5 |
|
value: 41.408 |
|
- type: precision_at_1 |
|
value: 34.841 |
|
- type: precision_at_10 |
|
value: 7.872999999999999 |
|
- type: precision_at_100 |
|
value: 1.2449999999999999 |
|
- type: precision_at_1000 |
|
value: 0.161 |
|
- type: precision_at_3 |
|
value: 18.993 |
|
- type: precision_at_5 |
|
value: 13.032 |
|
- type: recall_at_1 |
|
value: 28.444999999999997 |
|
- type: recall_at_10 |
|
value: 54.984 |
|
- type: recall_at_100 |
|
value: 78.342 |
|
- type: recall_at_1000 |
|
value: 92.77 |
|
- type: recall_at_3 |
|
value: 42.842999999999996 |
|
- type: recall_at_5 |
|
value: 47.247 |
|
- type: map_at_1 |
|
value: 23.072 |
|
- type: map_at_10 |
|
value: 32.354 |
|
- type: map_at_100 |
|
value: 33.800000000000004 |
|
- type: map_at_1000 |
|
value: 33.908 |
|
- type: map_at_3 |
|
value: 29.232000000000003 |
|
- type: map_at_5 |
|
value: 31.049 |
|
- type: mrr_at_1 |
|
value: 29.110000000000003 |
|
- type: mrr_at_10 |
|
value: 38.03 |
|
- type: mrr_at_100 |
|
value: 39.032 |
|
- type: mrr_at_1000 |
|
value: 39.086999999999996 |
|
- type: mrr_at_3 |
|
value: 35.407 |
|
- type: mrr_at_5 |
|
value: 36.76 |
|
- type: ndcg_at_1 |
|
value: 29.110000000000003 |
|
- type: ndcg_at_10 |
|
value: 38.231 |
|
- type: ndcg_at_100 |
|
value: 44.425 |
|
- type: ndcg_at_1000 |
|
value: 46.771 |
|
- type: ndcg_at_3 |
|
value: 33.095 |
|
- type: ndcg_at_5 |
|
value: 35.459 |
|
- type: precision_at_1 |
|
value: 29.110000000000003 |
|
- type: precision_at_10 |
|
value: 7.215000000000001 |
|
- type: precision_at_100 |
|
value: 1.2109999999999999 |
|
- type: precision_at_1000 |
|
value: 0.157 |
|
- type: precision_at_3 |
|
value: 16.058 |
|
- type: precision_at_5 |
|
value: 11.644 |
|
- type: recall_at_1 |
|
value: 23.072 |
|
- type: recall_at_10 |
|
value: 50.285999999999994 |
|
- type: recall_at_100 |
|
value: 76.596 |
|
- type: recall_at_1000 |
|
value: 92.861 |
|
- type: recall_at_3 |
|
value: 35.702 |
|
- type: recall_at_5 |
|
value: 42.152 |
|
- type: map_at_1 |
|
value: 24.937916666666666 |
|
- type: map_at_10 |
|
value: 33.755250000000004 |
|
- type: map_at_100 |
|
value: 34.955999999999996 |
|
- type: map_at_1000 |
|
value: 35.070499999999996 |
|
- type: map_at_3 |
|
value: 30.98708333333333 |
|
- type: map_at_5 |
|
value: 32.51491666666666 |
|
- type: mrr_at_1 |
|
value: 29.48708333333333 |
|
- type: mrr_at_10 |
|
value: 37.92183333333334 |
|
- type: mrr_at_100 |
|
value: 38.76583333333333 |
|
- type: mrr_at_1000 |
|
value: 38.82466666666667 |
|
- type: mrr_at_3 |
|
value: 35.45125 |
|
- type: mrr_at_5 |
|
value: 36.827000000000005 |
|
- type: ndcg_at_1 |
|
value: 29.48708333333333 |
|
- type: ndcg_at_10 |
|
value: 39.05225 |
|
- type: ndcg_at_100 |
|
value: 44.25983333333334 |
|
- type: ndcg_at_1000 |
|
value: 46.568333333333335 |
|
- type: ndcg_at_3 |
|
value: 34.271583333333325 |
|
- type: ndcg_at_5 |
|
value: 36.483916666666666 |
|
- type: precision_at_1 |
|
value: 29.48708333333333 |
|
- type: precision_at_10 |
|
value: 6.865749999999999 |
|
- type: precision_at_100 |
|
value: 1.1195833333333332 |
|
- type: precision_at_1000 |
|
value: 0.15058333333333335 |
|
- type: precision_at_3 |
|
value: 15.742083333333333 |
|
- type: precision_at_5 |
|
value: 11.221916666666667 |
|
- type: recall_at_1 |
|
value: 24.937916666666666 |
|
- type: recall_at_10 |
|
value: 50.650416666666665 |
|
- type: recall_at_100 |
|
value: 73.55383333333334 |
|
- type: recall_at_1000 |
|
value: 89.61691666666667 |
|
- type: recall_at_3 |
|
value: 37.27808333333334 |
|
- type: recall_at_5 |
|
value: 42.99475 |
|
- type: map_at_1 |
|
value: 23.947 |
|
- type: map_at_10 |
|
value: 30.575000000000003 |
|
- type: map_at_100 |
|
value: 31.465 |
|
- type: map_at_1000 |
|
value: 31.558000000000003 |
|
- type: map_at_3 |
|
value: 28.814 |
|
- type: map_at_5 |
|
value: 29.738999999999997 |
|
- type: mrr_at_1 |
|
value: 26.994 |
|
- type: mrr_at_10 |
|
value: 33.415 |
|
- type: mrr_at_100 |
|
value: 34.18 |
|
- type: mrr_at_1000 |
|
value: 34.245 |
|
- type: mrr_at_3 |
|
value: 31.621 |
|
- type: mrr_at_5 |
|
value: 32.549 |
|
- type: ndcg_at_1 |
|
value: 26.994 |
|
- type: ndcg_at_10 |
|
value: 34.482 |
|
- type: ndcg_at_100 |
|
value: 38.915 |
|
- type: ndcg_at_1000 |
|
value: 41.355 |
|
- type: ndcg_at_3 |
|
value: 31.139 |
|
- type: ndcg_at_5 |
|
value: 32.589 |
|
- type: precision_at_1 |
|
value: 26.994 |
|
- type: precision_at_10 |
|
value: 5.322 |
|
- type: precision_at_100 |
|
value: 0.8160000000000001 |
|
- type: precision_at_1000 |
|
value: 0.11100000000000002 |
|
- type: precision_at_3 |
|
value: 13.344000000000001 |
|
- type: precision_at_5 |
|
value: 8.988 |
|
- type: recall_at_1 |
|
value: 23.947 |
|
- type: recall_at_10 |
|
value: 43.647999999999996 |
|
- type: recall_at_100 |
|
value: 63.851 |
|
- type: recall_at_1000 |
|
value: 82.0 |
|
- type: recall_at_3 |
|
value: 34.288000000000004 |
|
- type: recall_at_5 |
|
value: 38.117000000000004 |
|
- type: map_at_1 |
|
value: 16.197 |
|
- type: map_at_10 |
|
value: 22.968 |
|
- type: map_at_100 |
|
value: 24.095 |
|
- type: map_at_1000 |
|
value: 24.217 |
|
- type: map_at_3 |
|
value: 20.771 |
|
- type: map_at_5 |
|
value: 21.995 |
|
- type: mrr_at_1 |
|
value: 19.511 |
|
- type: mrr_at_10 |
|
value: 26.55 |
|
- type: mrr_at_100 |
|
value: 27.500999999999998 |
|
- type: mrr_at_1000 |
|
value: 27.578999999999997 |
|
- type: mrr_at_3 |
|
value: 24.421 |
|
- type: mrr_at_5 |
|
value: 25.604 |
|
- type: ndcg_at_1 |
|
value: 19.511 |
|
- type: ndcg_at_10 |
|
value: 27.386 |
|
- type: ndcg_at_100 |
|
value: 32.828 |
|
- type: ndcg_at_1000 |
|
value: 35.739 |
|
- type: ndcg_at_3 |
|
value: 23.405 |
|
- type: ndcg_at_5 |
|
value: 25.255 |
|
- type: precision_at_1 |
|
value: 19.511 |
|
- type: precision_at_10 |
|
value: 5.017 |
|
- type: precision_at_100 |
|
value: 0.91 |
|
- type: precision_at_1000 |
|
value: 0.133 |
|
- type: precision_at_3 |
|
value: 11.023 |
|
- type: precision_at_5 |
|
value: 8.025 |
|
- type: recall_at_1 |
|
value: 16.197 |
|
- type: recall_at_10 |
|
value: 37.09 |
|
- type: recall_at_100 |
|
value: 61.778 |
|
- type: recall_at_1000 |
|
value: 82.56599999999999 |
|
- type: recall_at_3 |
|
value: 26.034000000000002 |
|
- type: recall_at_5 |
|
value: 30.762 |
|
- type: map_at_1 |
|
value: 25.41 |
|
- type: map_at_10 |
|
value: 33.655 |
|
- type: map_at_100 |
|
value: 34.892 |
|
- type: map_at_1000 |
|
value: 34.995 |
|
- type: map_at_3 |
|
value: 30.94 |
|
- type: map_at_5 |
|
value: 32.303 |
|
- type: mrr_at_1 |
|
value: 29.477999999999998 |
|
- type: mrr_at_10 |
|
value: 37.443 |
|
- type: mrr_at_100 |
|
value: 38.383 |
|
- type: mrr_at_1000 |
|
value: 38.440000000000005 |
|
- type: mrr_at_3 |
|
value: 34.949999999999996 |
|
- type: mrr_at_5 |
|
value: 36.228 |
|
- type: ndcg_at_1 |
|
value: 29.477999999999998 |
|
- type: ndcg_at_10 |
|
value: 38.769 |
|
- type: ndcg_at_100 |
|
value: 44.245000000000005 |
|
- type: ndcg_at_1000 |
|
value: 46.593 |
|
- type: ndcg_at_3 |
|
value: 33.623 |
|
- type: ndcg_at_5 |
|
value: 35.766 |
|
- type: precision_at_1 |
|
value: 29.477999999999998 |
|
- type: precision_at_10 |
|
value: 6.455 |
|
- type: precision_at_100 |
|
value: 1.032 |
|
- type: precision_at_1000 |
|
value: 0.135 |
|
- type: precision_at_3 |
|
value: 14.893999999999998 |
|
- type: precision_at_5 |
|
value: 10.485 |
|
- type: recall_at_1 |
|
value: 25.41 |
|
- type: recall_at_10 |
|
value: 50.669 |
|
- type: recall_at_100 |
|
value: 74.084 |
|
- type: recall_at_1000 |
|
value: 90.435 |
|
- type: recall_at_3 |
|
value: 36.679 |
|
- type: recall_at_5 |
|
value: 41.94 |
|
- type: map_at_1 |
|
value: 23.339 |
|
- type: map_at_10 |
|
value: 31.852000000000004 |
|
- type: map_at_100 |
|
value: 33.411 |
|
- type: map_at_1000 |
|
value: 33.62 |
|
- type: map_at_3 |
|
value: 28.929 |
|
- type: map_at_5 |
|
value: 30.542 |
|
- type: mrr_at_1 |
|
value: 28.063 |
|
- type: mrr_at_10 |
|
value: 36.301 |
|
- type: mrr_at_100 |
|
value: 37.288 |
|
- type: mrr_at_1000 |
|
value: 37.349 |
|
- type: mrr_at_3 |
|
value: 33.663 |
|
- type: mrr_at_5 |
|
value: 35.165 |
|
- type: ndcg_at_1 |
|
value: 28.063 |
|
- type: ndcg_at_10 |
|
value: 37.462 |
|
- type: ndcg_at_100 |
|
value: 43.620999999999995 |
|
- type: ndcg_at_1000 |
|
value: 46.211 |
|
- type: ndcg_at_3 |
|
value: 32.68 |
|
- type: ndcg_at_5 |
|
value: 34.981 |
|
- type: precision_at_1 |
|
value: 28.063 |
|
- type: precision_at_10 |
|
value: 7.1739999999999995 |
|
- type: precision_at_100 |
|
value: 1.486 |
|
- type: precision_at_1000 |
|
value: 0.23500000000000001 |
|
- type: precision_at_3 |
|
value: 15.217 |
|
- type: precision_at_5 |
|
value: 11.265 |
|
- type: recall_at_1 |
|
value: 23.339 |
|
- type: recall_at_10 |
|
value: 48.376999999999995 |
|
- type: recall_at_100 |
|
value: 76.053 |
|
- type: recall_at_1000 |
|
value: 92.455 |
|
- type: recall_at_3 |
|
value: 34.735 |
|
- type: recall_at_5 |
|
value: 40.71 |
|
- type: map_at_1 |
|
value: 18.925 |
|
- type: map_at_10 |
|
value: 26.017000000000003 |
|
- type: map_at_100 |
|
value: 27.034000000000002 |
|
- type: map_at_1000 |
|
value: 27.156000000000002 |
|
- type: map_at_3 |
|
value: 23.604 |
|
- type: map_at_5 |
|
value: 24.75 |
|
- type: mrr_at_1 |
|
value: 20.333000000000002 |
|
- type: mrr_at_10 |
|
value: 27.915 |
|
- type: mrr_at_100 |
|
value: 28.788000000000004 |
|
- type: mrr_at_1000 |
|
value: 28.877999999999997 |
|
- type: mrr_at_3 |
|
value: 25.446999999999996 |
|
- type: mrr_at_5 |
|
value: 26.648 |
|
- type: ndcg_at_1 |
|
value: 20.333000000000002 |
|
- type: ndcg_at_10 |
|
value: 30.673000000000002 |
|
- type: ndcg_at_100 |
|
value: 35.618 |
|
- type: ndcg_at_1000 |
|
value: 38.517 |
|
- type: ndcg_at_3 |
|
value: 25.71 |
|
- type: ndcg_at_5 |
|
value: 27.679 |
|
- type: precision_at_1 |
|
value: 20.333000000000002 |
|
- type: precision_at_10 |
|
value: 4.9910000000000005 |
|
- type: precision_at_100 |
|
value: 0.8130000000000001 |
|
- type: precision_at_1000 |
|
value: 0.117 |
|
- type: precision_at_3 |
|
value: 11.029 |
|
- type: precision_at_5 |
|
value: 7.8740000000000006 |
|
- type: recall_at_1 |
|
value: 18.925 |
|
- type: recall_at_10 |
|
value: 43.311 |
|
- type: recall_at_100 |
|
value: 66.308 |
|
- type: recall_at_1000 |
|
value: 87.49 |
|
- type: recall_at_3 |
|
value: 29.596 |
|
- type: recall_at_5 |
|
value: 34.245 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB ClimateFEVER |
|
type: climate-fever |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.714 |
|
- type: map_at_10 |
|
value: 23.194 |
|
- type: map_at_100 |
|
value: 24.976000000000003 |
|
- type: map_at_1000 |
|
value: 25.166 |
|
- type: map_at_3 |
|
value: 19.709 |
|
- type: map_at_5 |
|
value: 21.523999999999997 |
|
- type: mrr_at_1 |
|
value: 30.619000000000003 |
|
- type: mrr_at_10 |
|
value: 42.563 |
|
- type: mrr_at_100 |
|
value: 43.386 |
|
- type: mrr_at_1000 |
|
value: 43.423 |
|
- type: mrr_at_3 |
|
value: 39.555 |
|
- type: mrr_at_5 |
|
value: 41.268 |
|
- type: ndcg_at_1 |
|
value: 30.619000000000003 |
|
- type: ndcg_at_10 |
|
value: 31.836 |
|
- type: ndcg_at_100 |
|
value: 38.652 |
|
- type: ndcg_at_1000 |
|
value: 42.088 |
|
- type: ndcg_at_3 |
|
value: 26.733 |
|
- type: ndcg_at_5 |
|
value: 28.435 |
|
- type: precision_at_1 |
|
value: 30.619000000000003 |
|
- type: precision_at_10 |
|
value: 9.751999999999999 |
|
- type: precision_at_100 |
|
value: 1.71 |
|
- type: precision_at_1000 |
|
value: 0.23500000000000001 |
|
- type: precision_at_3 |
|
value: 19.935 |
|
- type: precision_at_5 |
|
value: 14.984 |
|
- type: recall_at_1 |
|
value: 13.714 |
|
- type: recall_at_10 |
|
value: 37.26 |
|
- type: recall_at_100 |
|
value: 60.546 |
|
- type: recall_at_1000 |
|
value: 79.899 |
|
- type: recall_at_3 |
|
value: 24.325 |
|
- type: recall_at_5 |
|
value: 29.725 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB DBPedia |
|
type: dbpedia-entity |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.462 |
|
- type: map_at_10 |
|
value: 18.637 |
|
- type: map_at_100 |
|
value: 26.131999999999998 |
|
- type: map_at_1000 |
|
value: 27.607 |
|
- type: map_at_3 |
|
value: 13.333 |
|
- type: map_at_5 |
|
value: 15.654000000000002 |
|
- type: mrr_at_1 |
|
value: 66.25 |
|
- type: mrr_at_10 |
|
value: 74.32600000000001 |
|
- type: mrr_at_100 |
|
value: 74.60900000000001 |
|
- type: mrr_at_1000 |
|
value: 74.62 |
|
- type: mrr_at_3 |
|
value: 72.667 |
|
- type: mrr_at_5 |
|
value: 73.817 |
|
- type: ndcg_at_1 |
|
value: 53.87499999999999 |
|
- type: ndcg_at_10 |
|
value: 40.028999999999996 |
|
- type: ndcg_at_100 |
|
value: 44.199 |
|
- type: ndcg_at_1000 |
|
value: 51.629999999999995 |
|
- type: ndcg_at_3 |
|
value: 44.113 |
|
- type: ndcg_at_5 |
|
value: 41.731 |
|
- type: precision_at_1 |
|
value: 66.25 |
|
- type: precision_at_10 |
|
value: 31.900000000000002 |
|
- type: precision_at_100 |
|
value: 10.043000000000001 |
|
- type: precision_at_1000 |
|
value: 1.926 |
|
- type: precision_at_3 |
|
value: 47.417 |
|
- type: precision_at_5 |
|
value: 40.65 |
|
- type: recall_at_1 |
|
value: 8.462 |
|
- type: recall_at_10 |
|
value: 24.293 |
|
- type: recall_at_100 |
|
value: 50.146 |
|
- type: recall_at_1000 |
|
value: 74.034 |
|
- type: recall_at_3 |
|
value: 14.967 |
|
- type: recall_at_5 |
|
value: 18.682000000000002 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB EmotionClassification |
|
type: mteb/emotion |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 47.84499999999999 |
|
- type: f1 |
|
value: 42.48106691979349 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB FEVER |
|
type: fever |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 74.034 |
|
- type: map_at_10 |
|
value: 82.76 |
|
- type: map_at_100 |
|
value: 82.968 |
|
- type: map_at_1000 |
|
value: 82.98299999999999 |
|
- type: map_at_3 |
|
value: 81.768 |
|
- type: map_at_5 |
|
value: 82.418 |
|
- type: mrr_at_1 |
|
value: 80.048 |
|
- type: mrr_at_10 |
|
value: 87.64999999999999 |
|
- type: mrr_at_100 |
|
value: 87.712 |
|
- type: mrr_at_1000 |
|
value: 87.713 |
|
- type: mrr_at_3 |
|
value: 87.01100000000001 |
|
- type: mrr_at_5 |
|
value: 87.466 |
|
- type: ndcg_at_1 |
|
value: 80.048 |
|
- type: ndcg_at_10 |
|
value: 86.643 |
|
- type: ndcg_at_100 |
|
value: 87.361 |
|
- type: ndcg_at_1000 |
|
value: 87.606 |
|
- type: ndcg_at_3 |
|
value: 85.137 |
|
- type: ndcg_at_5 |
|
value: 86.016 |
|
- type: precision_at_1 |
|
value: 80.048 |
|
- type: precision_at_10 |
|
value: 10.372 |
|
- type: precision_at_100 |
|
value: 1.093 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 32.638 |
|
- type: precision_at_5 |
|
value: 20.177 |
|
- type: recall_at_1 |
|
value: 74.034 |
|
- type: recall_at_10 |
|
value: 93.769 |
|
- type: recall_at_100 |
|
value: 96.569 |
|
- type: recall_at_1000 |
|
value: 98.039 |
|
- type: recall_at_3 |
|
value: 89.581 |
|
- type: recall_at_5 |
|
value: 91.906 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB FiQA2018 |
|
type: fiqa |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.5 |
|
- type: map_at_10 |
|
value: 32.857 |
|
- type: map_at_100 |
|
value: 34.589 |
|
- type: map_at_1000 |
|
value: 34.778 |
|
- type: map_at_3 |
|
value: 29.160999999999998 |
|
- type: map_at_5 |
|
value: 31.033 |
|
- type: mrr_at_1 |
|
value: 40.123 |
|
- type: mrr_at_10 |
|
value: 48.776 |
|
- type: mrr_at_100 |
|
value: 49.495 |
|
- type: mrr_at_1000 |
|
value: 49.539 |
|
- type: mrr_at_3 |
|
value: 46.605000000000004 |
|
- type: mrr_at_5 |
|
value: 47.654 |
|
- type: ndcg_at_1 |
|
value: 40.123 |
|
- type: ndcg_at_10 |
|
value: 40.343 |
|
- type: ndcg_at_100 |
|
value: 46.56 |
|
- type: ndcg_at_1000 |
|
value: 49.777 |
|
- type: ndcg_at_3 |
|
value: 37.322 |
|
- type: ndcg_at_5 |
|
value: 37.791000000000004 |
|
- type: precision_at_1 |
|
value: 40.123 |
|
- type: precision_at_10 |
|
value: 11.08 |
|
- type: precision_at_100 |
|
value: 1.752 |
|
- type: precision_at_1000 |
|
value: 0.232 |
|
- type: precision_at_3 |
|
value: 24.897 |
|
- type: precision_at_5 |
|
value: 17.809 |
|
- type: recall_at_1 |
|
value: 20.5 |
|
- type: recall_at_10 |
|
value: 46.388 |
|
- type: recall_at_100 |
|
value: 69.552 |
|
- type: recall_at_1000 |
|
value: 89.011 |
|
- type: recall_at_3 |
|
value: 33.617999999999995 |
|
- type: recall_at_5 |
|
value: 38.211 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB HotpotQA |
|
type: hotpotqa |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 39.135999999999996 |
|
- type: map_at_10 |
|
value: 61.673 |
|
- type: map_at_100 |
|
value: 62.562 |
|
- type: map_at_1000 |
|
value: 62.62 |
|
- type: map_at_3 |
|
value: 58.467999999999996 |
|
- type: map_at_5 |
|
value: 60.463 |
|
- type: mrr_at_1 |
|
value: 78.271 |
|
- type: mrr_at_10 |
|
value: 84.119 |
|
- type: mrr_at_100 |
|
value: 84.29299999999999 |
|
- type: mrr_at_1000 |
|
value: 84.299 |
|
- type: mrr_at_3 |
|
value: 83.18900000000001 |
|
- type: mrr_at_5 |
|
value: 83.786 |
|
- type: ndcg_at_1 |
|
value: 78.271 |
|
- type: ndcg_at_10 |
|
value: 69.935 |
|
- type: ndcg_at_100 |
|
value: 73.01299999999999 |
|
- type: ndcg_at_1000 |
|
value: 74.126 |
|
- type: ndcg_at_3 |
|
value: 65.388 |
|
- type: ndcg_at_5 |
|
value: 67.906 |
|
- type: precision_at_1 |
|
value: 78.271 |
|
- type: precision_at_10 |
|
value: 14.562 |
|
- type: precision_at_100 |
|
value: 1.6969999999999998 |
|
- type: precision_at_1000 |
|
value: 0.184 |
|
- type: precision_at_3 |
|
value: 41.841 |
|
- type: precision_at_5 |
|
value: 27.087 |
|
- type: recall_at_1 |
|
value: 39.135999999999996 |
|
- type: recall_at_10 |
|
value: 72.809 |
|
- type: recall_at_100 |
|
value: 84.86200000000001 |
|
- type: recall_at_1000 |
|
value: 92.208 |
|
- type: recall_at_3 |
|
value: 62.76199999999999 |
|
- type: recall_at_5 |
|
value: 67.718 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB ImdbClassification |
|
type: mteb/imdb |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 90.60600000000001 |
|
- type: ap |
|
value: 86.6579587804335 |
|
- type: f1 |
|
value: 90.5938853929307 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB MSMARCO |
|
type: msmarco |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.852 |
|
- type: map_at_10 |
|
value: 33.982 |
|
- type: map_at_100 |
|
value: 35.116 |
|
- type: map_at_1000 |
|
value: 35.167 |
|
- type: map_at_3 |
|
value: 30.134 |
|
- type: map_at_5 |
|
value: 32.340999999999994 |
|
- type: mrr_at_1 |
|
value: 22.479 |
|
- type: mrr_at_10 |
|
value: 34.594 |
|
- type: mrr_at_100 |
|
value: 35.672 |
|
- type: mrr_at_1000 |
|
value: 35.716 |
|
- type: mrr_at_3 |
|
value: 30.84 |
|
- type: mrr_at_5 |
|
value: 32.998 |
|
- type: ndcg_at_1 |
|
value: 22.493 |
|
- type: ndcg_at_10 |
|
value: 40.833000000000006 |
|
- type: ndcg_at_100 |
|
value: 46.357 |
|
- type: ndcg_at_1000 |
|
value: 47.637 |
|
- type: ndcg_at_3 |
|
value: 32.995999999999995 |
|
- type: ndcg_at_5 |
|
value: 36.919000000000004 |
|
- type: precision_at_1 |
|
value: 22.493 |
|
- type: precision_at_10 |
|
value: 6.465999999999999 |
|
- type: precision_at_100 |
|
value: 0.9249999999999999 |
|
- type: precision_at_1000 |
|
value: 0.104 |
|
- type: precision_at_3 |
|
value: 14.030999999999999 |
|
- type: precision_at_5 |
|
value: 10.413 |
|
- type: recall_at_1 |
|
value: 21.852 |
|
- type: recall_at_10 |
|
value: 61.934999999999995 |
|
- type: recall_at_100 |
|
value: 87.611 |
|
- type: recall_at_1000 |
|
value: 97.441 |
|
- type: recall_at_3 |
|
value: 40.583999999999996 |
|
- type: recall_at_5 |
|
value: 49.992999999999995 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPDomainClassification (en) |
|
type: mteb/mtop_domain |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 93.36069311445507 |
|
- type: f1 |
|
value: 93.16456330371453 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MTOPIntentClassification (en) |
|
type: mteb/mtop_intent |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 74.74692202462381 |
|
- type: f1 |
|
value: 58.17903579421599 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (en) |
|
type: mteb/amazon_massive_intent |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 74.80833893745796 |
|
- type: f1 |
|
value: 72.70786592684664 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveScenarioClassification (en) |
|
type: mteb/amazon_massive_scenario |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 78.69872225958305 |
|
- type: f1 |
|
value: 78.61626934504731 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB MedrxivClusteringP2P |
|
type: mteb/medrxiv-clustering-p2p |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 33.058658628717694 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB MedrxivClusteringS2S |
|
type: mteb/medrxiv-clustering-s2s |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 30.85561739360599 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB MindSmallReranking |
|
type: mteb/mind_small |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 31.290259910144385 |
|
- type: mrr |
|
value: 32.44223046102856 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB NFCorpus |
|
type: nfcorpus |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.288 |
|
- type: map_at_10 |
|
value: 12.267999999999999 |
|
- type: map_at_100 |
|
value: 15.557000000000002 |
|
- type: map_at_1000 |
|
value: 16.98 |
|
- type: map_at_3 |
|
value: 8.866 |
|
- type: map_at_5 |
|
value: 10.418 |
|
- type: mrr_at_1 |
|
value: 43.653 |
|
- type: mrr_at_10 |
|
value: 52.681 |
|
- type: mrr_at_100 |
|
value: 53.315999999999995 |
|
- type: mrr_at_1000 |
|
value: 53.357 |
|
- type: mrr_at_3 |
|
value: 51.393 |
|
- type: mrr_at_5 |
|
value: 51.903999999999996 |
|
- type: ndcg_at_1 |
|
value: 42.415000000000006 |
|
- type: ndcg_at_10 |
|
value: 34.305 |
|
- type: ndcg_at_100 |
|
value: 30.825999999999997 |
|
- type: ndcg_at_1000 |
|
value: 39.393 |
|
- type: ndcg_at_3 |
|
value: 39.931 |
|
- type: ndcg_at_5 |
|
value: 37.519999999999996 |
|
- type: precision_at_1 |
|
value: 43.653 |
|
- type: precision_at_10 |
|
value: 25.728 |
|
- type: precision_at_100 |
|
value: 7.932 |
|
- type: precision_at_1000 |
|
value: 2.07 |
|
- type: precision_at_3 |
|
value: 38.184000000000005 |
|
- type: precision_at_5 |
|
value: 32.879000000000005 |
|
- type: recall_at_1 |
|
value: 5.288 |
|
- type: recall_at_10 |
|
value: 16.195 |
|
- type: recall_at_100 |
|
value: 31.135 |
|
- type: recall_at_1000 |
|
value: 61.531000000000006 |
|
- type: recall_at_3 |
|
value: 10.313 |
|
- type: recall_at_5 |
|
value: 12.754999999999999 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB NQ |
|
type: nq |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 28.216 |
|
- type: map_at_10 |
|
value: 42.588 |
|
- type: map_at_100 |
|
value: 43.702999999999996 |
|
- type: map_at_1000 |
|
value: 43.739 |
|
- type: map_at_3 |
|
value: 38.177 |
|
- type: map_at_5 |
|
value: 40.754000000000005 |
|
- type: mrr_at_1 |
|
value: 31.866 |
|
- type: mrr_at_10 |
|
value: 45.189 |
|
- type: mrr_at_100 |
|
value: 46.056000000000004 |
|
- type: mrr_at_1000 |
|
value: 46.081 |
|
- type: mrr_at_3 |
|
value: 41.526999999999994 |
|
- type: mrr_at_5 |
|
value: 43.704 |
|
- type: ndcg_at_1 |
|
value: 31.837 |
|
- type: ndcg_at_10 |
|
value: 50.178 |
|
- type: ndcg_at_100 |
|
value: 54.98800000000001 |
|
- type: ndcg_at_1000 |
|
value: 55.812 |
|
- type: ndcg_at_3 |
|
value: 41.853 |
|
- type: ndcg_at_5 |
|
value: 46.153 |
|
- type: precision_at_1 |
|
value: 31.837 |
|
- type: precision_at_10 |
|
value: 8.43 |
|
- type: precision_at_100 |
|
value: 1.1119999999999999 |
|
- type: precision_at_1000 |
|
value: 0.11900000000000001 |
|
- type: precision_at_3 |
|
value: 19.023 |
|
- type: precision_at_5 |
|
value: 13.911000000000001 |
|
- type: recall_at_1 |
|
value: 28.216 |
|
- type: recall_at_10 |
|
value: 70.8 |
|
- type: recall_at_100 |
|
value: 91.857 |
|
- type: recall_at_1000 |
|
value: 97.941 |
|
- type: recall_at_3 |
|
value: 49.196 |
|
- type: recall_at_5 |
|
value: 59.072 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB QuoraRetrieval |
|
type: quora |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 71.22800000000001 |
|
- type: map_at_10 |
|
value: 85.115 |
|
- type: map_at_100 |
|
value: 85.72 |
|
- type: map_at_1000 |
|
value: 85.737 |
|
- type: map_at_3 |
|
value: 82.149 |
|
- type: map_at_5 |
|
value: 84.029 |
|
- type: mrr_at_1 |
|
value: 81.96 |
|
- type: mrr_at_10 |
|
value: 88.00200000000001 |
|
- type: mrr_at_100 |
|
value: 88.088 |
|
- type: mrr_at_1000 |
|
value: 88.089 |
|
- type: mrr_at_3 |
|
value: 87.055 |
|
- type: mrr_at_5 |
|
value: 87.715 |
|
- type: ndcg_at_1 |
|
value: 82.01 |
|
- type: ndcg_at_10 |
|
value: 88.78 |
|
- type: ndcg_at_100 |
|
value: 89.91 |
|
- type: ndcg_at_1000 |
|
value: 90.013 |
|
- type: ndcg_at_3 |
|
value: 85.957 |
|
- type: ndcg_at_5 |
|
value: 87.56 |
|
- type: precision_at_1 |
|
value: 82.01 |
|
- type: precision_at_10 |
|
value: 13.462 |
|
- type: precision_at_100 |
|
value: 1.528 |
|
- type: precision_at_1000 |
|
value: 0.157 |
|
- type: precision_at_3 |
|
value: 37.553 |
|
- type: precision_at_5 |
|
value: 24.732000000000003 |
|
- type: recall_at_1 |
|
value: 71.22800000000001 |
|
- type: recall_at_10 |
|
value: 95.69 |
|
- type: recall_at_100 |
|
value: 99.531 |
|
- type: recall_at_1000 |
|
value: 99.98 |
|
- type: recall_at_3 |
|
value: 87.632 |
|
- type: recall_at_5 |
|
value: 92.117 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB RedditClustering |
|
type: mteb/reddit-clustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 52.31768034366916 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB RedditClusteringP2P |
|
type: mteb/reddit-clustering-p2p |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 60.640266772723606 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB SCIDOCS |
|
type: scidocs |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.7780000000000005 |
|
- type: map_at_10 |
|
value: 12.299 |
|
- type: map_at_100 |
|
value: 14.363000000000001 |
|
- type: map_at_1000 |
|
value: 14.71 |
|
- type: map_at_3 |
|
value: 8.738999999999999 |
|
- type: map_at_5 |
|
value: 10.397 |
|
- type: mrr_at_1 |
|
value: 23.599999999999998 |
|
- type: mrr_at_10 |
|
value: 34.845 |
|
- type: mrr_at_100 |
|
value: 35.916 |
|
- type: mrr_at_1000 |
|
value: 35.973 |
|
- type: mrr_at_3 |
|
value: 31.7 |
|
- type: mrr_at_5 |
|
value: 33.535 |
|
- type: ndcg_at_1 |
|
value: 23.599999999999998 |
|
- type: ndcg_at_10 |
|
value: 20.522000000000002 |
|
- type: ndcg_at_100 |
|
value: 28.737000000000002 |
|
- type: ndcg_at_1000 |
|
value: 34.596 |
|
- type: ndcg_at_3 |
|
value: 19.542 |
|
- type: ndcg_at_5 |
|
value: 16.958000000000002 |
|
- type: precision_at_1 |
|
value: 23.599999999999998 |
|
- type: precision_at_10 |
|
value: 10.67 |
|
- type: precision_at_100 |
|
value: 2.259 |
|
- type: precision_at_1000 |
|
value: 0.367 |
|
- type: precision_at_3 |
|
value: 18.333 |
|
- type: precision_at_5 |
|
value: 14.879999999999999 |
|
- type: recall_at_1 |
|
value: 4.7780000000000005 |
|
- type: recall_at_10 |
|
value: 21.617 |
|
- type: recall_at_100 |
|
value: 45.905 |
|
- type: recall_at_1000 |
|
value: 74.42 |
|
- type: recall_at_3 |
|
value: 11.148 |
|
- type: recall_at_5 |
|
value: 15.082999999999998 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB SICK-R |
|
type: mteb/sickr-sts |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.22372750297885 |
|
- type: cos_sim_spearman |
|
value: 79.40972617119405 |
|
- type: euclidean_pearson |
|
value: 80.6101072020434 |
|
- type: euclidean_spearman |
|
value: 79.53844217225202 |
|
- type: manhattan_pearson |
|
value: 80.57265975286111 |
|
- type: manhattan_spearman |
|
value: 79.46335611792958 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS12 |
|
type: mteb/sts12-sts |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 85.43713315520749 |
|
- type: cos_sim_spearman |
|
value: 77.44128693329532 |
|
- type: euclidean_pearson |
|
value: 81.63869928101123 |
|
- type: euclidean_spearman |
|
value: 77.29512977961515 |
|
- type: manhattan_pearson |
|
value: 81.63704185566183 |
|
- type: manhattan_spearman |
|
value: 77.29909412738657 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS13 |
|
type: mteb/sts13-sts |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 81.59451537860527 |
|
- type: cos_sim_spearman |
|
value: 82.97994638856723 |
|
- type: euclidean_pearson |
|
value: 82.89478688288412 |
|
- type: euclidean_spearman |
|
value: 83.58740751053104 |
|
- type: manhattan_pearson |
|
value: 82.69140840941608 |
|
- type: manhattan_spearman |
|
value: 83.33665956040555 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS14 |
|
type: mteb/sts14-sts |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.00756527711764 |
|
- type: cos_sim_spearman |
|
value: 81.83560996841379 |
|
- type: euclidean_pearson |
|
value: 82.07684151976518 |
|
- type: euclidean_spearman |
|
value: 82.00913052060511 |
|
- type: manhattan_pearson |
|
value: 82.05690778488794 |
|
- type: manhattan_spearman |
|
value: 82.02260252019525 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS15 |
|
type: mteb/sts15-sts |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.13710262895447 |
|
- type: cos_sim_spearman |
|
value: 87.26412811156248 |
|
- type: euclidean_pearson |
|
value: 86.94151453230228 |
|
- type: euclidean_spearman |
|
value: 87.5363796699571 |
|
- type: manhattan_pearson |
|
value: 86.86989424083748 |
|
- type: manhattan_spearman |
|
value: 87.47315940781353 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS16 |
|
type: mteb/sts16-sts |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.0230597603627 |
|
- type: cos_sim_spearman |
|
value: 84.93344499318864 |
|
- type: euclidean_pearson |
|
value: 84.23754743431141 |
|
- type: euclidean_spearman |
|
value: 85.09707376597099 |
|
- type: manhattan_pearson |
|
value: 84.04325160987763 |
|
- type: manhattan_spearman |
|
value: 84.89353071339909 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS17 (en-en) |
|
type: mteb/sts17-crosslingual-sts |
|
config: en-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.75620824563921 |
|
- type: cos_sim_spearman |
|
value: 87.15065513706398 |
|
- type: euclidean_pearson |
|
value: 88.26281533633521 |
|
- type: euclidean_spearman |
|
value: 87.51963738643983 |
|
- type: manhattan_pearson |
|
value: 88.25599267618065 |
|
- type: manhattan_spearman |
|
value: 87.58048736047483 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (en) |
|
type: mteb/sts22-crosslingual-sts |
|
config: en |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 64.74645319195137 |
|
- type: cos_sim_spearman |
|
value: 65.29996325037214 |
|
- type: euclidean_pearson |
|
value: 67.04297794086443 |
|
- type: euclidean_spearman |
|
value: 65.43841726694343 |
|
- type: manhattan_pearson |
|
value: 67.39459955690904 |
|
- type: manhattan_spearman |
|
value: 65.92864704413651 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STSBenchmark |
|
type: mteb/stsbenchmark-sts |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.31291020270801 |
|
- type: cos_sim_spearman |
|
value: 85.86473738688068 |
|
- type: euclidean_pearson |
|
value: 85.65537275064152 |
|
- type: euclidean_spearman |
|
value: 86.13087454209642 |
|
- type: manhattan_pearson |
|
value: 85.43946955047609 |
|
- type: manhattan_spearman |
|
value: 85.91568175344916 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB SciDocsRR |
|
type: mteb/scidocs-reranking |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 85.93798118350695 |
|
- type: mrr |
|
value: 95.93536274908824 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB SciFact |
|
type: scifact |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 57.594 |
|
- type: map_at_10 |
|
value: 66.81899999999999 |
|
- type: map_at_100 |
|
value: 67.368 |
|
- type: map_at_1000 |
|
value: 67.4 |
|
- type: map_at_3 |
|
value: 64.061 |
|
- type: map_at_5 |
|
value: 65.47 |
|
- type: mrr_at_1 |
|
value: 60.667 |
|
- type: mrr_at_10 |
|
value: 68.219 |
|
- type: mrr_at_100 |
|
value: 68.655 |
|
- type: mrr_at_1000 |
|
value: 68.684 |
|
- type: mrr_at_3 |
|
value: 66.22200000000001 |
|
- type: mrr_at_5 |
|
value: 67.289 |
|
- type: ndcg_at_1 |
|
value: 60.667 |
|
- type: ndcg_at_10 |
|
value: 71.275 |
|
- type: ndcg_at_100 |
|
value: 73.642 |
|
- type: ndcg_at_1000 |
|
value: 74.373 |
|
- type: ndcg_at_3 |
|
value: 66.521 |
|
- type: ndcg_at_5 |
|
value: 68.581 |
|
- type: precision_at_1 |
|
value: 60.667 |
|
- type: precision_at_10 |
|
value: 9.433 |
|
- type: precision_at_100 |
|
value: 1.0699999999999998 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 25.556 |
|
- type: precision_at_5 |
|
value: 16.8 |
|
- type: recall_at_1 |
|
value: 57.594 |
|
- type: recall_at_10 |
|
value: 83.622 |
|
- type: recall_at_100 |
|
value: 94.167 |
|
- type: recall_at_1000 |
|
value: 99.667 |
|
- type: recall_at_3 |
|
value: 70.64399999999999 |
|
- type: recall_at_5 |
|
value: 75.983 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
name: MTEB SprintDuplicateQuestions |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.85841584158416 |
|
- type: cos_sim_ap |
|
value: 96.66996142314342 |
|
- type: cos_sim_f1 |
|
value: 92.83208020050125 |
|
- type: cos_sim_precision |
|
value: 93.06532663316584 |
|
- type: cos_sim_recall |
|
value: 92.60000000000001 |
|
- type: dot_accuracy |
|
value: 99.85841584158416 |
|
- type: dot_ap |
|
value: 96.6775307676576 |
|
- type: dot_f1 |
|
value: 92.69289729177312 |
|
- type: dot_precision |
|
value: 94.77533960292581 |
|
- type: dot_recall |
|
value: 90.7 |
|
- type: euclidean_accuracy |
|
value: 99.86138613861387 |
|
- type: euclidean_ap |
|
value: 96.6338454403108 |
|
- type: euclidean_f1 |
|
value: 92.92214357937311 |
|
- type: euclidean_precision |
|
value: 93.96728016359918 |
|
- type: euclidean_recall |
|
value: 91.9 |
|
- type: manhattan_accuracy |
|
value: 99.86237623762376 |
|
- type: manhattan_ap |
|
value: 96.60370449645053 |
|
- type: manhattan_f1 |
|
value: 92.91177970423253 |
|
- type: manhattan_precision |
|
value: 94.7970863683663 |
|
- type: manhattan_recall |
|
value: 91.10000000000001 |
|
- type: max_accuracy |
|
value: 99.86237623762376 |
|
- type: max_ap |
|
value: 96.6775307676576 |
|
- type: max_f1 |
|
value: 92.92214357937311 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB StackExchangeClustering |
|
type: mteb/stackexchange-clustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 60.77977058695198 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB StackExchangeClusteringP2P |
|
type: mteb/stackexchange-clustering-p2p |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 35.2725272535638 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB StackOverflowDupQuestions |
|
type: mteb/stackoverflowdupquestions-reranking |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 53.64052466362125 |
|
- type: mrr |
|
value: 54.533067014684654 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
name: MTEB SummEval |
|
type: mteb/summeval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 30.677624219206578 |
|
- type: cos_sim_spearman |
|
value: 30.121368518123447 |
|
- type: dot_pearson |
|
value: 30.69870088041608 |
|
- type: dot_spearman |
|
value: 29.61284927093751 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB TRECCOVID |
|
type: trec-covid |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.22 |
|
- type: map_at_10 |
|
value: 1.855 |
|
- type: map_at_100 |
|
value: 9.885 |
|
- type: map_at_1000 |
|
value: 23.416999999999998 |
|
- type: map_at_3 |
|
value: 0.637 |
|
- type: map_at_5 |
|
value: 1.024 |
|
- type: mrr_at_1 |
|
value: 88.0 |
|
- type: mrr_at_10 |
|
value: 93.067 |
|
- type: mrr_at_100 |
|
value: 93.067 |
|
- type: mrr_at_1000 |
|
value: 93.067 |
|
- type: mrr_at_3 |
|
value: 92.667 |
|
- type: mrr_at_5 |
|
value: 93.067 |
|
- type: ndcg_at_1 |
|
value: 82.0 |
|
- type: ndcg_at_10 |
|
value: 75.899 |
|
- type: ndcg_at_100 |
|
value: 55.115 |
|
- type: ndcg_at_1000 |
|
value: 48.368 |
|
- type: ndcg_at_3 |
|
value: 79.704 |
|
- type: ndcg_at_5 |
|
value: 78.39699999999999 |
|
- type: precision_at_1 |
|
value: 88.0 |
|
- type: precision_at_10 |
|
value: 79.60000000000001 |
|
- type: precision_at_100 |
|
value: 56.06 |
|
- type: precision_at_1000 |
|
value: 21.206 |
|
- type: precision_at_3 |
|
value: 84.667 |
|
- type: precision_at_5 |
|
value: 83.2 |
|
- type: recall_at_1 |
|
value: 0.22 |
|
- type: recall_at_10 |
|
value: 2.078 |
|
- type: recall_at_100 |
|
value: 13.297 |
|
- type: recall_at_1000 |
|
value: 44.979 |
|
- type: recall_at_3 |
|
value: 0.6689999999999999 |
|
- type: recall_at_5 |
|
value: 1.106 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB Touche2020 |
|
type: webis-touche2020 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.258 |
|
- type: map_at_10 |
|
value: 10.439 |
|
- type: map_at_100 |
|
value: 16.89 |
|
- type: map_at_1000 |
|
value: 18.407999999999998 |
|
- type: map_at_3 |
|
value: 5.668 |
|
- type: map_at_5 |
|
value: 7.718 |
|
- type: mrr_at_1 |
|
value: 32.653 |
|
- type: mrr_at_10 |
|
value: 51.159 |
|
- type: mrr_at_100 |
|
value: 51.714000000000006 |
|
- type: mrr_at_1000 |
|
value: 51.714000000000006 |
|
- type: mrr_at_3 |
|
value: 47.959 |
|
- type: mrr_at_5 |
|
value: 50.407999999999994 |
|
- type: ndcg_at_1 |
|
value: 29.592000000000002 |
|
- type: ndcg_at_10 |
|
value: 26.037 |
|
- type: ndcg_at_100 |
|
value: 37.924 |
|
- type: ndcg_at_1000 |
|
value: 49.126999999999995 |
|
- type: ndcg_at_3 |
|
value: 30.631999999999998 |
|
- type: ndcg_at_5 |
|
value: 28.571 |
|
- type: precision_at_1 |
|
value: 32.653 |
|
- type: precision_at_10 |
|
value: 22.857 |
|
- type: precision_at_100 |
|
value: 7.754999999999999 |
|
- type: precision_at_1000 |
|
value: 1.529 |
|
- type: precision_at_3 |
|
value: 34.014 |
|
- type: precision_at_5 |
|
value: 29.796 |
|
- type: recall_at_1 |
|
value: 2.258 |
|
- type: recall_at_10 |
|
value: 16.554 |
|
- type: recall_at_100 |
|
value: 48.439 |
|
- type: recall_at_1000 |
|
value: 82.80499999999999 |
|
- type: recall_at_3 |
|
value: 7.283 |
|
- type: recall_at_5 |
|
value: 10.732 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB ToxicConversationsClassification |
|
type: mteb/toxic_conversations_50k |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 69.8858 |
|
- type: ap |
|
value: 13.835684144362109 |
|
- type: f1 |
|
value: 53.803351693244586 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB TweetSentimentExtractionClassification |
|
type: mteb/tweet_sentiment_extraction |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 60.50650820599886 |
|
- type: f1 |
|
value: 60.84357825979259 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB TwentyNewsgroupsClustering |
|
type: mteb/twentynewsgroups-clustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 48.52131044852134 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
name: MTEB TwitterSemEval2015 |
|
type: mteb/twittersemeval2015-pairclassification |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 85.59337187816654 |
|
- type: cos_sim_ap |
|
value: 73.23925826533437 |
|
- type: cos_sim_f1 |
|
value: 67.34693877551021 |
|
- type: cos_sim_precision |
|
value: 62.40432237730752 |
|
- type: cos_sim_recall |
|
value: 73.13984168865434 |
|
- type: dot_accuracy |
|
value: 85.31322644096085 |
|
- type: dot_ap |
|
value: 72.30723963807422 |
|
- type: dot_f1 |
|
value: 66.47051612112296 |
|
- type: dot_precision |
|
value: 62.0792305930845 |
|
- type: dot_recall |
|
value: 71.53034300791556 |
|
- type: euclidean_accuracy |
|
value: 85.61125350181797 |
|
- type: euclidean_ap |
|
value: 73.32843720487845 |
|
- type: euclidean_f1 |
|
value: 67.36549633745895 |
|
- type: euclidean_precision |
|
value: 64.60755813953489 |
|
- type: euclidean_recall |
|
value: 70.36939313984169 |
|
- type: manhattan_accuracy |
|
value: 85.63509566668654 |
|
- type: manhattan_ap |
|
value: 73.16658488311325 |
|
- type: manhattan_f1 |
|
value: 67.20597386434349 |
|
- type: manhattan_precision |
|
value: 63.60424028268551 |
|
- type: manhattan_recall |
|
value: 71.2401055408971 |
|
- type: max_accuracy |
|
value: 85.63509566668654 |
|
- type: max_ap |
|
value: 73.32843720487845 |
|
- type: max_f1 |
|
value: 67.36549633745895 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
name: MTEB TwitterURLCorpus |
|
type: mteb/twitterurlcorpus-pairclassification |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.33779640625606 |
|
- type: cos_sim_ap |
|
value: 84.83868375898157 |
|
- type: cos_sim_f1 |
|
value: 77.16506154017773 |
|
- type: cos_sim_precision |
|
value: 74.62064005753327 |
|
- type: cos_sim_recall |
|
value: 79.88912842623961 |
|
- type: dot_accuracy |
|
value: 88.02732176815307 |
|
- type: dot_ap |
|
value: 83.95089283763002 |
|
- type: dot_f1 |
|
value: 76.29635101196631 |
|
- type: dot_precision |
|
value: 73.31771720613288 |
|
- type: dot_recall |
|
value: 79.52725592854944 |
|
- type: euclidean_accuracy |
|
value: 88.44452206310397 |
|
- type: euclidean_ap |
|
value: 84.98384576824827 |
|
- type: euclidean_f1 |
|
value: 77.29311047696697 |
|
- type: euclidean_precision |
|
value: 74.51232583065381 |
|
- type: euclidean_recall |
|
value: 80.28949799815214 |
|
- type: manhattan_accuracy |
|
value: 88.47362906042613 |
|
- type: manhattan_ap |
|
value: 84.91421462218432 |
|
- type: manhattan_f1 |
|
value: 77.05107637204792 |
|
- type: manhattan_precision |
|
value: 74.74484256243214 |
|
- type: manhattan_recall |
|
value: 79.50415768401602 |
|
- type: max_accuracy |
|
value: 88.47362906042613 |
|
- type: max_ap |
|
value: 84.98384576824827 |
|
- type: max_f1 |
|
value: 77.29311047696697 |
|
--- |
|
|
|
# HowardC/bge-small-en-v1.5-Q4_K_M-GGUF |
|
This model was converted to GGUF format from [`BAAI/bge-small-en-v1.5`](https://huggingface.co/BAAI/bge-small-en-v1.5) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. |
|
Refer to the [original model card](https://huggingface.co/BAAI/bge-small-en-v1.5) for more details on the model. |
|
|
|
## Use with llama.cpp |
|
Install llama.cpp through brew (works on Mac and Linux) |
|
|
|
```bash |
|
brew install llama.cpp |
|
|
|
``` |
|
Invoke the llama.cpp server or the CLI. |
|
|
|
### CLI: |
|
```bash |
|
llama-cli --hf-repo HowardC/bge-small-en-v1.5-Q4_K_M-GGUF --hf-file bge-small-en-v1.5-q4_k_m.gguf -p "The meaning to life and the universe is" |
|
``` |
|
|
|
### Server: |
|
```bash |
|
llama-server --hf-repo HowardC/bge-small-en-v1.5-Q4_K_M-GGUF --hf-file bge-small-en-v1.5-q4_k_m.gguf -c 2048 |
|
``` |
|
|
|
Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. |
|
|
|
Step 1: Clone llama.cpp from GitHub. |
|
``` |
|
git clone https://github.com/ggerganov/llama.cpp |
|
``` |
|
|
|
Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). |
|
``` |
|
cd llama.cpp && LLAMA_CURL=1 make |
|
``` |
|
|
|
Step 3: Run inference through the main binary. |
|
``` |
|
./llama-cli --hf-repo HowardC/bge-small-en-v1.5-Q4_K_M-GGUF --hf-file bge-small-en-v1.5-q4_k_m.gguf -p "The meaning to life and the universe is" |
|
``` |
|
or |
|
``` |
|
./llama-server --hf-repo HowardC/bge-small-en-v1.5-Q4_K_M-GGUF --hf-file bge-small-en-v1.5-q4_k_m.gguf -c 2048 |
|
``` |
|
|
