|
--- |
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base_model: baai/bge-base-en-v1.5 |
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language: |
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- en |
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library_name: model2vec |
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license: mit |
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model_name: brown-fairy-base-v0 |
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tags: |
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- embeddings |
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- static-embeddings |
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- sentence-transformers |
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- mteb |
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model-index: |
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- name: bhavnicksm/brown-fairy-base-v0 |
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results: |
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- dataset: |
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config: en |
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name: MTEB AmazonCounterfactualClassification (en) |
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
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split: test |
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type: mteb/amazon_counterfactual |
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metrics: |
|
- type: accuracy |
|
value: 69.52239999999999 |
|
- type: f1 |
|
value: 63.4127 |
|
- type: f1_weighted |
|
value: 72.48599999999999 |
|
- type: ap |
|
value: 31.8446 |
|
- type: ap_weighted |
|
value: 31.8446 |
|
- type: main_score |
|
value: 69.52239999999999 |
|
task: |
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type: Classification |
|
- dataset: |
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config: default |
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name: MTEB AmazonPolarityClassification (default) |
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revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
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split: test |
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type: mteb/amazon_polarity |
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metrics: |
|
- type: accuracy |
|
value: 68.709 |
|
- type: f1 |
|
value: 68.2583 |
|
- type: f1_weighted |
|
value: 68.2583 |
|
- type: ap |
|
value: 63.728899999999996 |
|
- type: ap_weighted |
|
value: 63.728899999999996 |
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- type: main_score |
|
value: 68.709 |
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task: |
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type: Classification |
|
- dataset: |
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config: en |
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name: MTEB AmazonReviewsClassification (en) |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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split: test |
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type: mteb/amazon_reviews_multi |
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metrics: |
|
- type: accuracy |
|
value: 34.014 |
|
- type: f1 |
|
value: 33.4588 |
|
- type: f1_weighted |
|
value: 33.4588 |
|
- type: main_score |
|
value: 34.014 |
|
task: |
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type: Classification |
|
- dataset: |
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config: default |
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name: MTEB ArguAna (default) |
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revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
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split: test |
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type: mteb/arguana |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 20.341 |
|
- type: ndcg_at_3 |
|
value: 30.547 |
|
- type: ndcg_at_5 |
|
value: 34.963 |
|
- type: ndcg_at_10 |
|
value: 39.805 |
|
- type: ndcg_at_20 |
|
value: 42.397 |
|
- type: ndcg_at_100 |
|
value: 45.216 |
|
- type: ndcg_at_1000 |
|
value: 46.339999999999996 |
|
- type: map_at_1 |
|
value: 20.341 |
|
- type: map_at_3 |
|
value: 27.962999999999997 |
|
- type: map_at_5 |
|
value: 30.409999999999997 |
|
- type: map_at_10 |
|
value: 32.4 |
|
- type: map_at_20 |
|
value: 33.113 |
|
- type: map_at_100 |
|
value: 33.512 |
|
- type: map_at_1000 |
|
value: 33.556000000000004 |
|
- type: recall_at_1 |
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value: 20.341 |
|
- type: recall_at_3 |
|
value: 38.051 |
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- type: recall_at_5 |
|
value: 48.791000000000004 |
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- type: recall_at_10 |
|
value: 63.798 |
|
- type: recall_at_20 |
|
value: 74.03999999999999 |
|
- type: recall_at_100 |
|
value: 89.118 |
|
- type: recall_at_1000 |
|
value: 97.866 |
|
- type: precision_at_1 |
|
value: 20.341 |
|
- type: precision_at_3 |
|
value: 12.684000000000001 |
|
- type: precision_at_5 |
|
value: 9.758 |
|
- type: precision_at_10 |
|
value: 6.38 |
|
- type: precision_at_20 |
|
value: 3.702 |
|
- type: precision_at_100 |
|
value: 0.8909999999999999 |
|
- type: precision_at_1000 |
|
value: 0.098 |
|
- type: mrr_at_1 |
|
value: 20.6259 |
|
- type: mrr_at_3 |
|
value: 28.058300000000003 |
|
- type: mrr_at_5 |
|
value: 30.4979 |
|
- type: mrr_at_10 |
|
value: 32.5131 |
|
- type: mrr_at_20 |
|
value: 33.222699999999996 |
|
- type: mrr_at_100 |
|
value: 33.6243 |
|
- type: mrr_at_1000 |
|
value: 33.6687 |
|
- type: nauc_ndcg_at_1_max |
|
value: -6.208 |
|
- type: nauc_ndcg_at_1_std |
|
value: 0.6887 |
|
- type: nauc_ndcg_at_1_diff1 |
|
value: 5.5123 |
|
- type: nauc_ndcg_at_3_max |
|
value: -1.8608 |
|
- type: nauc_ndcg_at_3_std |
|
value: 3.7832999999999997 |
|
- type: nauc_ndcg_at_3_diff1 |
|
value: 7.5778 |
|
- type: nauc_ndcg_at_5_max |
|
value: 0.0929 |
|
- type: nauc_ndcg_at_5_std |
|
value: 5.8453 |
|
- type: nauc_ndcg_at_5_diff1 |
|
value: 9.316 |
|
- type: nauc_ndcg_at_10_max |
|
value: 0.557 |
|
- type: nauc_ndcg_at_10_std |
|
value: 5.8692 |
|
- type: nauc_ndcg_at_10_diff1 |
|
value: 8.3828 |
|
- type: nauc_ndcg_at_20_max |
|
value: 1.567 |
|
- type: nauc_ndcg_at_20_std |
|
value: 8.2355 |
|
- type: nauc_ndcg_at_20_diff1 |
|
value: 9.1907 |
|
- type: nauc_ndcg_at_100_max |
|
value: 1.0833000000000002 |
|
- type: nauc_ndcg_at_100_std |
|
value: 8.6248 |
|
- type: nauc_ndcg_at_100_diff1 |
|
value: 9.0073 |
|
- type: nauc_ndcg_at_1000_max |
|
value: -0.166 |
|
- type: nauc_ndcg_at_1000_std |
|
value: 7.394100000000001 |
|
- type: nauc_ndcg_at_1000_diff1 |
|
value: 8.1955 |
|
- type: nauc_map_at_1_max |
|
value: -6.208 |
|
- type: nauc_map_at_1_std |
|
value: 0.6887 |
|
- type: nauc_map_at_1_diff1 |
|
value: 5.5123 |
|
- type: nauc_map_at_3_max |
|
value: -3.0332999999999997 |
|
- type: nauc_map_at_3_std |
|
value: 2.9010000000000002 |
|
- type: nauc_map_at_3_diff1 |
|
value: 6.8088 |
|
- type: nauc_map_at_5_max |
|
value: -1.9215 |
|
- type: nauc_map_at_5_std |
|
value: 4.023000000000001 |
|
- type: nauc_map_at_5_diff1 |
|
value: 7.8248999999999995 |
|
- type: nauc_map_at_10_max |
|
value: -1.8037 |
|
- type: nauc_map_at_10_std |
|
value: 3.9838 |
|
- type: nauc_map_at_10_diff1 |
|
value: 7.3617 |
|
- type: nauc_map_at_20_max |
|
value: -1.5614 |
|
- type: nauc_map_at_20_std |
|
value: 4.6065000000000005 |
|
- type: nauc_map_at_20_diff1 |
|
value: 7.5846 |
|
- type: nauc_map_at_100_max |
|
value: -1.6330999999999998 |
|
- type: nauc_map_at_100_std |
|
value: 4.693 |
|
- type: nauc_map_at_100_diff1 |
|
value: 7.5309 |
|
- type: nauc_map_at_1000_max |
|
value: -1.6847999999999999 |
|
- type: nauc_map_at_1000_std |
|
value: 4.6508 |
|
- type: nauc_map_at_1000_diff1 |
|
value: 7.5036000000000005 |
|
- type: nauc_recall_at_1_max |
|
value: -6.208 |
|
- type: nauc_recall_at_1_std |
|
value: 0.6887 |
|
- type: nauc_recall_at_1_diff1 |
|
value: 5.5123 |
|
- type: nauc_recall_at_3_max |
|
value: 1.2662 |
|
- type: nauc_recall_at_3_std |
|
value: 6.1506 |
|
- type: nauc_recall_at_3_diff1 |
|
value: 9.6919 |
|
- type: nauc_recall_at_5_max |
|
value: 5.7511 |
|
- type: nauc_recall_at_5_std |
|
value: 11.0652 |
|
- type: nauc_recall_at_5_diff1 |
|
value: 13.5713 |
|
- type: nauc_recall_at_10_max |
|
value: 8.5342 |
|
- type: nauc_recall_at_10_std |
|
value: 12.2161 |
|
- type: nauc_recall_at_10_diff1 |
|
value: 11.6188 |
|
- type: nauc_recall_at_20_max |
|
value: 15.7488 |
|
- type: nauc_recall_at_20_std |
|
value: 25.6755 |
|
- type: nauc_recall_at_20_diff1 |
|
value: 16.3568 |
|
- type: nauc_recall_at_100_max |
|
value: 24.424799999999998 |
|
- type: nauc_recall_at_100_std |
|
value: 47.6945 |
|
- type: nauc_recall_at_100_diff1 |
|
value: 22.4622 |
|
- type: nauc_recall_at_1000_max |
|
value: 3.0951 |
|
- type: nauc_recall_at_1000_std |
|
value: 84.10419999999999 |
|
- type: nauc_recall_at_1000_diff1 |
|
value: -2.6364 |
|
- type: nauc_precision_at_1_max |
|
value: -6.208 |
|
- type: nauc_precision_at_1_std |
|
value: 0.6887 |
|
- type: nauc_precision_at_1_diff1 |
|
value: 5.5123 |
|
- type: nauc_precision_at_3_max |
|
value: 1.2662 |
|
- type: nauc_precision_at_3_std |
|
value: 6.1506 |
|
- type: nauc_precision_at_3_diff1 |
|
value: 9.6919 |
|
- type: nauc_precision_at_5_max |
|
value: 5.7511 |
|
- type: nauc_precision_at_5_std |
|
value: 11.0652 |
|
- type: nauc_precision_at_5_diff1 |
|
value: 13.5713 |
|
- type: nauc_precision_at_10_max |
|
value: 8.5342 |
|
- type: nauc_precision_at_10_std |
|
value: 12.2161 |
|
- type: nauc_precision_at_10_diff1 |
|
value: 11.6188 |
|
- type: nauc_precision_at_20_max |
|
value: 15.7488 |
|
- type: nauc_precision_at_20_std |
|
value: 25.6755 |
|
- type: nauc_precision_at_20_diff1 |
|
value: 16.3568 |
|
- type: nauc_precision_at_100_max |
|
value: 24.424799999999998 |
|
- type: nauc_precision_at_100_std |
|
value: 47.6945 |
|
- type: nauc_precision_at_100_diff1 |
|
value: 22.4622 |
|
- type: nauc_precision_at_1000_max |
|
value: 3.0951 |
|
- type: nauc_precision_at_1000_std |
|
value: 84.10419999999999 |
|
- type: nauc_precision_at_1000_diff1 |
|
value: -2.6364 |
|
- type: nauc_mrr_at_1_max |
|
value: -5.611800000000001 |
|
- type: nauc_mrr_at_1_std |
|
value: 0.2596 |
|
- type: nauc_mrr_at_1_diff1 |
|
value: 4.5101 |
|
- type: nauc_mrr_at_3_max |
|
value: -3.1917 |
|
- type: nauc_mrr_at_3_std |
|
value: 2.7559 |
|
- type: nauc_mrr_at_3_diff1 |
|
value: 5.756 |
|
- type: nauc_mrr_at_5_max |
|
value: -2.1292999999999997 |
|
- type: nauc_mrr_at_5_std |
|
value: 3.7653 |
|
- type: nauc_mrr_at_5_diff1 |
|
value: 6.7995 |
|
- type: nauc_mrr_at_10_max |
|
value: -1.8915000000000002 |
|
- type: nauc_mrr_at_10_std |
|
value: 3.778 |
|
- type: nauc_mrr_at_10_diff1 |
|
value: 6.4253 |
|
- type: nauc_mrr_at_20_max |
|
value: -1.6753 |
|
- type: nauc_mrr_at_20_std |
|
value: 4.389 |
|
- type: nauc_mrr_at_20_diff1 |
|
value: 6.6081 |
|
- type: nauc_mrr_at_100_max |
|
value: -1.7302000000000002 |
|
- type: nauc_mrr_at_100_std |
|
value: 4.4796000000000005 |
|
- type: nauc_mrr_at_100_diff1 |
|
value: 6.563199999999999 |
|
- type: nauc_mrr_at_1000_max |
|
value: -1.7819000000000003 |
|
- type: nauc_mrr_at_1000_std |
|
value: 4.4372 |
|
- type: nauc_mrr_at_1000_diff1 |
|
value: 6.5346 |
|
- type: main_score |
|
value: 39.805 |
|
task: |
|
type: Retrieval |
|
- dataset: |
|
config: default |
|
name: MTEB ArxivClusteringP2P (default) |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
split: test |
|
type: mteb/arxiv-clustering-p2p |
|
metrics: |
|
- type: v_measure |
|
value: 30.9023 |
|
- type: v_measure_std |
|
value: 14.6095 |
|
- type: main_score |
|
value: 30.9023 |
|
task: |
|
type: Clustering |
|
- dataset: |
|
config: default |
|
name: MTEB ArxivClusteringS2S (default) |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
split: test |
|
type: mteb/arxiv-clustering-s2s |
|
metrics: |
|
- type: v_measure |
|
value: 19.1012 |
|
- type: v_measure_std |
|
value: 15.511800000000001 |
|
- type: main_score |
|
value: 19.1012 |
|
task: |
|
type: Clustering |
|
- dataset: |
|
config: default |
|
name: MTEB AskUbuntuDupQuestions (default) |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
split: test |
|
type: mteb/askubuntudupquestions-reranking |
|
metrics: |
|
- type: map |
|
value: 54.0474 |
|
- type: mrr |
|
value: 67.00150000000001 |
|
- type: nAUC_map_max |
|
value: 14.266100000000002 |
|
- type: nAUC_map_std |
|
value: 11.7906 |
|
- type: nAUC_map_diff1 |
|
value: 7.5044 |
|
- type: nAUC_mrr_max |
|
value: 20.1721 |
|
- type: nAUC_mrr_std |
|
value: 13.1225 |
|
- type: nAUC_mrr_diff1 |
|
value: 14.3512 |
|
- type: main_score |
|
value: 54.0474 |
|
task: |
|
type: Reranking |
|
- dataset: |
|
config: default |
|
name: MTEB BIOSSES (default) |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
split: test |
|
type: mteb/biosses-sts |
|
metrics: |
|
- type: pearson |
|
value: 73.3465 |
|
- type: spearman |
|
value: 69.6932 |
|
- type: cosine_pearson |
|
value: 73.3465 |
|
- type: cosine_spearman |
|
value: 69.6932 |
|
- type: manhattan_pearson |
|
value: 54.115899999999996 |
|
- type: manhattan_spearman |
|
value: 54.1759 |
|
- type: euclidean_pearson |
|
value: 54.2153 |
|
- type: euclidean_spearman |
|
value: 54.0488 |
|
- type: main_score |
|
value: 69.6932 |
|
task: |
|
type: STS |
|
- dataset: |
|
config: default |
|
name: MTEB Banking77Classification (default) |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
split: test |
|
type: mteb/banking77 |
|
metrics: |
|
- type: accuracy |
|
value: 74.2987 |
|
- type: f1 |
|
value: 73.85119999999999 |
|
- type: f1_weighted |
|
value: 73.85119999999999 |
|
- type: main_score |
|
value: 74.2987 |
|
task: |
|
type: Classification |
|
- dataset: |
|
config: default |
|
name: MTEB BiorxivClusteringP2P (default) |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
split: test |
|
type: mteb/biorxiv-clustering-p2p |
|
metrics: |
|
- type: v_measure |
|
value: 29.8415 |
|
- type: v_measure_std |
|
value: 0.7605 |
|
- type: main_score |
|
value: 29.8415 |
|
task: |
|
type: Clustering |
|
- dataset: |
|
config: default |
|
name: MTEB BiorxivClusteringS2S (default) |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
split: test |
|
type: mteb/biorxiv-clustering-s2s |
|
metrics: |
|
- type: v_measure |
|
value: 16.4917 |
|
- type: v_measure_std |
|
value: 1.2364 |
|
- type: main_score |
|
value: 16.4917 |
|
task: |
|
type: Clustering |
|
- dataset: |
|
config: default |
|
name: MTEB CQADupstackRetrieval (default) |
|
revision: '1' |
|
split: test |
|
type: CQADupstackRetrieval_is_a_combined_dataset |
|
metrics: |
|
- type: ndcg_at_10 |
|
value: 21.9561 |
|
- type: main_score |
|
value: 21.9561 |
|
task: |
|
type: Retrieval |
|
- dataset: |
|
config: default |
|
name: MTEB ClimateFEVER (default) |
|
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
|
split: test |
|
type: mteb/climate-fever |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 18.826999999999998 |
|
- type: ndcg_at_3 |
|
value: 16.482 |
|
- type: ndcg_at_5 |
|
value: 17.9 |
|
- type: ndcg_at_10 |
|
value: 20.948 |
|
- type: ndcg_at_20 |
|
value: 23.665 |
|
- type: ndcg_at_100 |
|
value: 28.192 |
|
- type: ndcg_at_1000 |
|
value: 31.846999999999998 |
|
- type: map_at_1 |
|
value: 8.221 |
|
- type: map_at_3 |
|
value: 11.72 |
|
- type: map_at_5 |
|
value: 12.844 |
|
- type: map_at_10 |
|
value: 14.17 |
|
- type: map_at_20 |
|
value: 15.043000000000001 |
|
- type: map_at_100 |
|
value: 15.842 |
|
- type: map_at_1000 |
|
value: 16.04 |
|
- type: recall_at_1 |
|
value: 8.221 |
|
- type: recall_at_3 |
|
value: 15.214 |
|
- type: recall_at_5 |
|
value: 19.185 |
|
- type: recall_at_10 |
|
value: 26.14 |
|
- type: recall_at_20 |
|
value: 33.931 |
|
- type: recall_at_100 |
|
value: 51.429 |
|
- type: recall_at_1000 |
|
value: 72.269 |
|
- type: precision_at_1 |
|
value: 18.826999999999998 |
|
- type: precision_at_3 |
|
value: 12.4 |
|
- type: precision_at_5 |
|
value: 9.707 |
|
- type: precision_at_10 |
|
value: 6.84 |
|
- type: precision_at_20 |
|
value: 4.557 |
|
- type: precision_at_100 |
|
value: 1.461 |
|
- type: precision_at_1000 |
|
value: 0.212 |
|
- type: mrr_at_1 |
|
value: 18.8274 |
|
- type: mrr_at_3 |
|
value: 25.2226 |
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task: |
|
type: Retrieval |
|
- dataset: |
|
config: default |
|
name: MTEB DBPedia (default) |
|
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
|
split: test |
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type: mteb/dbpedia |
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|
value: 10.453 |
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- type: main_score |
|
value: 23.246 |
|
task: |
|
type: Retrieval |
|
- dataset: |
|
config: default |
|
name: MTEB EmotionClassification (default) |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
split: test |
|
type: mteb/emotion |
|
metrics: |
|
- type: accuracy |
|
value: 45.68 |
|
- type: f1 |
|
value: 43.1207 |
|
- type: f1_weighted |
|
value: 48.0349 |
|
- type: main_score |
|
value: 45.68 |
|
task: |
|
type: Classification |
|
- dataset: |
|
config: default |
|
name: MTEB FEVER (default) |
|
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
|
split: test |
|
type: mteb/fever |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 16.742 |
|
- type: ndcg_at_3 |
|
value: 23.316 |
|
- type: ndcg_at_5 |
|
value: 25.738 |
|
- type: ndcg_at_10 |
|
value: 28.68 |
|
- type: ndcg_at_20 |
|
value: 30.959999999999997 |
|
- type: ndcg_at_100 |
|
value: 34.037 |
|
- type: ndcg_at_1000 |
|
value: 36.004999999999995 |
|
- type: map_at_1 |
|
value: 15.797 |
|
- type: map_at_3 |
|
value: 21.209 |
|
- type: map_at_5 |
|
value: 22.547 |
|
- type: map_at_10 |
|
value: 23.762 |
|
- type: map_at_20 |
|
value: 24.401 |
|
- type: map_at_100 |
|
value: 24.83 |
|
- type: map_at_1000 |
|
value: 24.901 |
|
- type: recall_at_1 |
|
value: 15.797 |
|
- type: recall_at_3 |
|
value: 28.233000000000004 |
|
- type: recall_at_5 |
|
value: 33.997 |
|
- type: recall_at_10 |
|
value: 42.888 |
|
- type: recall_at_20 |
|
value: 51.635 |
|
- type: recall_at_100 |
|
value: 67.801 |
|
- type: recall_at_1000 |
|
value: 82.998 |
|
- type: precision_at_1 |
|
value: 16.742 |
|
- type: precision_at_3 |
|
value: 10.096 |
|
- type: precision_at_5 |
|
value: 7.335999999999999 |
|
- type: precision_at_10 |
|
value: 4.65 |
|
- type: precision_at_20 |
|
value: 2.817 |
|
- type: precision_at_100 |
|
value: 0.748 |
|
- type: precision_at_1000 |
|
value: 0.093 |
|
- type: mrr_at_1 |
|
value: 16.7417 |
|
- type: mrr_at_3 |
|
value: 22.4122 |
|
- type: mrr_at_5 |
|
value: 23.8374 |
|
- type: mrr_at_10 |
|
value: 25.101000000000003 |
|
- type: mrr_at_20 |
|
value: 25.739800000000002 |
|
- type: mrr_at_100 |
|
value: 26.164199999999997 |
|
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|
value: 26.227800000000002 |
|
- type: nauc_ndcg_at_1_max |
|
value: 13.991500000000002 |
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|
value: -25.4382 |
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value: 21.2751 |
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value: 15.4019 |
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|
value: 15.334900000000001 |
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|
value: 17.1297 |
|
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|
value: -26.709 |
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|
value: 14.072799999999999 |
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- type: nauc_ndcg_at_20_max |
|
value: 18.0756 |
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value: -25.849899999999998 |
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|
value: 13.3475 |
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|
value: 18.5017 |
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value: -25.1975 |
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value: 13.128200000000001 |
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value: 18.570500000000003 |
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value: 17.5 |
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- type: nauc_map_at_5_max |
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value: 15.748599999999998 |
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- type: nauc_map_at_5_std |
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value: -25.928 |
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value: 16.8883 |
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- type: nauc_map_at_10_max |
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value: 16.036 |
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value: -26.2116 |
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|
value: 16.335 |
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value: 16.305500000000002 |
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value: 21.4966 |
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- type: nauc_recall_at_3_max |
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value: 16.1074 |
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value: -25.916099999999997 |
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value: 13.5176 |
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- type: nauc_recall_at_5_max |
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value: 18.0189 |
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- type: nauc_recall_at_5_std |
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value: -25.795299999999997 |
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|
value: 11.3842 |
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- type: nauc_recall_at_10_max |
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value: 19.4035 |
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- type: nauc_recall_at_10_std |
|
value: -27.2015 |
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|
value: 7.9085 |
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- type: nauc_recall_at_20_max |
|
value: 22.5578 |
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- type: nauc_recall_at_20_std |
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value: -24.1674 |
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|
value: 5.0956 |
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- type: nauc_recall_at_100_max |
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value: 25.2855 |
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- type: nauc_recall_at_100_std |
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value: -19.9378 |
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|
value: 1.3199 |
|
- type: nauc_recall_at_1000_max |
|
value: 29.253400000000003 |
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- type: nauc_recall_at_1000_std |
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value: -8.519599999999999 |
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|
value: 0.1057 |
|
- type: nauc_precision_at_1_max |
|
value: 13.991500000000002 |
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- type: nauc_precision_at_1_std |
|
value: -25.4382 |
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|
value: 21.2751 |
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|
value: 15.758700000000001 |
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- type: nauc_precision_at_3_std |
|
value: -26.3494 |
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value: 13.6081 |
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value: 17.851300000000002 |
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- type: nauc_precision_at_5_std |
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value: -26.3818 |
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value: 11.4331 |
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value: 19.5748 |
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value: 22.453799999999998 |
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value: -23.707800000000002 |
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value: 5.2 |
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value: 24.1067 |
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value: -16.6068 |
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value: 1.1200999999999999 |
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value: 22.516 |
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value: -0.621 |
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value: -0.26749999999999996 |
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value: 21.2751 |
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value: 14.95 |
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value: -25.885 |
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value: 17.3215 |
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value: 15.5568 |
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value: -25.963 |
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|
value: 16.699 |
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value: 15.901299999999999 |
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value: -26.2471 |
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value: 16.189899999999998 |
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value: 16.1798 |
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value: -25.989600000000003 |
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value: 15.984499999999999 |
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value: 16.2602 |
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value: -25.9187 |
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value: 16.0136 |
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value: 16.2577 |
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value: -25.9039 |
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|
value: 16.0318 |
|
- type: main_score |
|
value: 28.68 |
|
task: |
|
type: Retrieval |
|
- dataset: |
|
config: default |
|
name: MTEB FiQA2018 (default) |
|
revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
|
split: test |
|
type: mteb/fiqa |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 14.198 |
|
- type: ndcg_at_3 |
|
value: 14.018 |
|
- type: ndcg_at_5 |
|
value: 14.857000000000001 |
|
- type: ndcg_at_10 |
|
value: 16.509999999999998 |
|
- type: ndcg_at_20 |
|
value: 18.499 |
|
- type: ndcg_at_100 |
|
value: 22.658 |
|
- type: ndcg_at_1000 |
|
value: 26.894000000000002 |
|
- type: map_at_1 |
|
value: 7.061000000000001 |
|
- type: map_at_3 |
|
value: 10.151 |
|
- type: map_at_5 |
|
value: 11.0 |
|
- type: map_at_10 |
|
value: 11.883000000000001 |
|
- type: map_at_20 |
|
value: 12.5 |
|
- type: map_at_100 |
|
value: 13.154 |
|
- type: map_at_1000 |
|
value: 13.343 |
|
- type: recall_at_1 |
|
value: 7.061000000000001 |
|
- type: recall_at_3 |
|
value: 13.339 |
|
- type: recall_at_5 |
|
value: 16.689999999999998 |
|
- type: recall_at_10 |
|
value: 21.435000000000002 |
|
- type: recall_at_20 |
|
value: 27.779999999999998 |
|
- type: recall_at_100 |
|
value: 45.381 |
|
- type: recall_at_1000 |
|
value: 71.61699999999999 |
|
- type: precision_at_1 |
|
value: 14.198 |
|
- type: precision_at_3 |
|
value: 9.568 |
|
- type: precision_at_5 |
|
value: 7.099 |
|
- type: precision_at_10 |
|
value: 4.7379999999999995 |
|
- type: precision_at_20 |
|
value: 3.1329999999999996 |
|
- type: precision_at_100 |
|
value: 1.083 |
|
- type: precision_at_1000 |
|
value: 0.181 |
|
- type: mrr_at_1 |
|
value: 14.1975 |
|
- type: mrr_at_3 |
|
value: 18.5185 |
|
- type: mrr_at_5 |
|
value: 19.8302 |
|
- type: mrr_at_10 |
|
value: 20.6685 |
|
- type: mrr_at_20 |
|
value: 21.273 |
|
- type: mrr_at_100 |
|
value: 21.8076 |
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|
value: 21.9063 |
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|
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|
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value: 21.5451 |
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- type: main_score |
|
value: 16.509999999999998 |
|
task: |
|
type: Retrieval |
|
- dataset: |
|
config: default |
|
name: MTEB HotpotQA (default) |
|
revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
|
split: test |
|
type: mteb/hotpotqa |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 40.297 |
|
- type: ndcg_at_3 |
|
value: 31.719 |
|
- type: ndcg_at_5 |
|
value: 33.744 |
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value: 35.72 |
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|
value: 37.266 |
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|
value: 39.778000000000006 |
|
- type: ndcg_at_1000 |
|
value: 42.056 |
|
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|
value: 20.149 |
|
- type: map_at_3 |
|
value: 25.899 |
|
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|
value: 27.157999999999998 |
|
- type: map_at_10 |
|
value: 28.105000000000004 |
|
- type: map_at_20 |
|
value: 28.586 |
|
- type: map_at_100 |
|
value: 29.000999999999998 |
|
- type: map_at_1000 |
|
value: 29.098000000000003 |
|
- type: recall_at_1 |
|
value: 20.149 |
|
- type: recall_at_3 |
|
value: 29.932 |
|
- type: recall_at_5 |
|
value: 33.93 |
|
- type: recall_at_10 |
|
value: 38.92 |
|
- type: recall_at_20 |
|
value: 43.903 |
|
- type: recall_at_100 |
|
value: 55.057 |
|
- type: recall_at_1000 |
|
value: 70.27 |
|
- type: precision_at_1 |
|
value: 40.297 |
|
- type: precision_at_3 |
|
value: 19.955000000000002 |
|
- type: precision_at_5 |
|
value: 13.572000000000001 |
|
- type: precision_at_10 |
|
value: 7.784000000000001 |
|
- type: precision_at_20 |
|
value: 4.390000000000001 |
|
- type: precision_at_100 |
|
value: 1.101 |
|
- type: precision_at_1000 |
|
value: 0.14100000000000001 |
|
- type: mrr_at_1 |
|
value: 40.2971 |
|
- type: mrr_at_3 |
|
value: 46.041 |
|
- type: mrr_at_5 |
|
value: 47.199600000000004 |
|
- type: mrr_at_10 |
|
value: 47.9631 |
|
- type: mrr_at_20 |
|
value: 48.3871 |
|
- type: mrr_at_100 |
|
value: 48.661500000000004 |
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|
value: 48.707 |
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|
value: 27.8706 |
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value: -8.272300000000001 |
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value: 57.8385 |
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value: 27.852500000000003 |
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value: 48.365 |
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value: 27.509099999999997 |
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value: 46.5015 |
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|
value: 27.002 |
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value: -4.5545 |
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value: 45.7081 |
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value: 26.984799999999996 |
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value: 44.9584 |
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value: 27.283600000000003 |
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value: 57.8385 |
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value: 47.2019 |
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value: 27.242 |
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value: 45.831 |
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value: 26.9723 |
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value: -4.7007 |
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value: 45.3311 |
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value: 42.3825 |
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value: 37.0532 |
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value: 23.5746 |
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value: -0.5226 |
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value: 34.071200000000005 |
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|
value: 22.1536 |
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value: 2.3993 |
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value: 29.439 |
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value: 20.7576 |
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value: 8.468499999999999 |
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|
value: 21.221799999999998 |
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|
value: 18.7522 |
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- type: nauc_recall_at_1000_std |
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value: 18.916800000000002 |
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|
value: 13.558200000000001 |
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- type: nauc_precision_at_1_max |
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value: 27.8706 |
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- type: nauc_precision_at_1_std |
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value: -8.272300000000001 |
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value: 57.8385 |
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value: 27.3795 |
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value: -5.1751 |
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value: 42.3825 |
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value: 25.634800000000002 |
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value: -3.3379 |
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value: 37.0532 |
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value: 23.5746 |
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value: 34.071200000000005 |
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value: 22.1536 |
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value: 2.3993 |
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|
value: 29.439 |
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value: 20.7576 |
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value: 8.468499999999999 |
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value: 21.221799999999998 |
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value: 18.7522 |
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value: 27.8706 |
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value: 57.8385 |
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value: 54.5601 |
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value: 28.2928 |
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value: -7.8317 |
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|
value: 54.046499999999995 |
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value: 28.151500000000002 |
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value: -7.6431 |
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|
value: 53.9751 |
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|
value: 28.215 |
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- type: nauc_mrr_at_20_std |
|
value: -7.5285 |
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|
value: 53.9177 |
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|
value: 28.215600000000002 |
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- type: nauc_mrr_at_100_std |
|
value: -7.524699999999999 |
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|
value: 53.9393 |
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|
value: 28.2194 |
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value: -7.5150999999999994 |
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|
value: 53.95290000000001 |
|
- type: main_score |
|
value: 35.72 |
|
task: |
|
type: Retrieval |
|
- dataset: |
|
config: default |
|
name: MTEB ImdbClassification (default) |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
split: test |
|
type: mteb/imdb |
|
metrics: |
|
- type: accuracy |
|
value: 65.8656 |
|
- type: f1 |
|
value: 65.385 |
|
- type: f1_weighted |
|
value: 65.385 |
|
- type: ap |
|
value: 60.506899999999995 |
|
- type: ap_weighted |
|
value: 60.506899999999995 |
|
- type: main_score |
|
value: 65.8656 |
|
task: |
|
type: Classification |
|
- dataset: |
|
config: default |
|
name: MTEB MSMARCO (default) |
|
revision: c5a29a104738b98a9e76336939199e264163d4a0 |
|
split: dev |
|
type: mteb/msmarco |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 6.877 |
|
- type: ndcg_at_3 |
|
value: 10.963000000000001 |
|
- type: ndcg_at_5 |
|
value: 12.845 |
|
- type: ndcg_at_10 |
|
value: 14.918000000000001 |
|
- type: ndcg_at_20 |
|
value: 16.721 |
|
- type: ndcg_at_100 |
|
value: 20.041 |
|
- type: ndcg_at_1000 |
|
value: 23.296 |
|
- type: map_at_1 |
|
value: 6.717 |
|
- type: map_at_3 |
|
value: 9.846 |
|
- type: map_at_5 |
|
value: 10.886999999999999 |
|
- type: map_at_10 |
|
value: 11.74 |
|
- type: map_at_20 |
|
value: 12.237 |
|
- type: map_at_100 |
|
value: 12.683 |
|
- type: map_at_1000 |
|
value: 12.792 |
|
- type: recall_at_1 |
|
value: 6.717 |
|
- type: recall_at_3 |
|
value: 13.963999999999999 |
|
- type: recall_at_5 |
|
value: 18.498 |
|
- type: recall_at_10 |
|
value: 24.869 |
|
- type: recall_at_20 |
|
value: 31.901000000000003 |
|
- type: recall_at_100 |
|
value: 49.786 |
|
- type: recall_at_1000 |
|
value: 75.913 |
|
- type: precision_at_1 |
|
value: 6.877 |
|
- type: precision_at_3 |
|
value: 4.809 |
|
- type: precision_at_5 |
|
value: 3.8280000000000003 |
|
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|
value: 2.5829999999999997 |
|
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|
value: 1.6650000000000003 |
|
- type: precision_at_100 |
|
value: 0.523 |
|
- type: precision_at_1000 |
|
value: 0.08 |
|
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|
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|
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|
value: 10.093100000000002 |
|
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|
value: 11.1526 |
|
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|
value: 12.0074 |
|
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|
value: 12.5083 |
|
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|
value: 12.9529 |
|
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|
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|
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|
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|
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|
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|
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|
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value: 19.3717 |
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|
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|
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|
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value: 17.3142 |
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value: 14.5015 |
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- type: nauc_recall_at_1000_std |
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value: 10.9827 |
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|
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|
value: -15.893699999999999 |
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|
value: 22.4454 |
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|
value: 22.0264 |
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|
value: 6.7813 |
|
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|
value: -15.2942 |
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|
value: 21.8857 |
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|
value: 7.0158 |
|
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|
value: -14.894599999999999 |
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|
value: 21.757299999999997 |
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- type: nauc_mrr_at_1000_max |
|
value: 7.0534 |
|
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|
value: -14.8351 |
|
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|
value: 21.7544 |
|
- type: main_score |
|
value: 14.918000000000001 |
|
task: |
|
type: Retrieval |
|
- dataset: |
|
config: en |
|
name: MTEB MTOPDomainClassification (en) |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
split: test |
|
type: mteb/mtop_domain |
|
metrics: |
|
- type: accuracy |
|
value: 82.4669 |
|
- type: f1 |
|
value: 81.3346 |
|
- type: f1_weighted |
|
value: 82.6885 |
|
- type: main_score |
|
value: 82.4669 |
|
task: |
|
type: Classification |
|
- dataset: |
|
config: en |
|
name: MTEB MTOPIntentClassification (en) |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
split: test |
|
type: mteb/mtop_intent |
|
metrics: |
|
- type: accuracy |
|
value: 58.1145 |
|
- type: f1 |
|
value: 40.7841 |
|
- type: f1_weighted |
|
value: 62.343 |
|
- type: main_score |
|
value: 58.1145 |
|
task: |
|
type: Classification |
|
- dataset: |
|
config: en |
|
name: MTEB MassiveIntentClassification (en) |
|
revision: 4672e20407010da34463acc759c162ca9734bca6 |
|
split: test |
|
type: mteb/amazon_massive_intent |
|
metrics: |
|
- type: accuracy |
|
value: 60.24549999999999 |
|
- type: f1 |
|
value: 59.534 |
|
- type: f1_weighted |
|
value: 60.47670000000001 |
|
- type: main_score |
|
value: 60.24549999999999 |
|
task: |
|
type: Classification |
|
- dataset: |
|
config: en |
|
name: MTEB MassiveScenarioClassification (en) |
|
revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8 |
|
split: test |
|
type: mteb/amazon_massive_scenario |
|
metrics: |
|
- type: accuracy |
|
value: 66.32820000000001 |
|
- type: f1 |
|
value: 65.2929 |
|
- type: f1_weighted |
|
value: 66.51979999999999 |
|
- type: main_score |
|
value: 66.32820000000001 |
|
task: |
|
type: Classification |
|
- dataset: |
|
config: default |
|
name: MTEB MedrxivClusteringP2P (default) |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
split: test |
|
type: mteb/medrxiv-clustering-p2p |
|
metrics: |
|
- type: v_measure |
|
value: 25.8495 |
|
- type: v_measure_std |
|
value: 1.6320000000000001 |
|
- type: main_score |
|
value: 25.8495 |
|
task: |
|
type: Clustering |
|
- dataset: |
|
config: default |
|
name: MTEB MedrxivClusteringS2S (default) |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
split: test |
|
type: mteb/medrxiv-clustering-s2s |
|
metrics: |
|
- type: v_measure |
|
value: 20.0754 |
|
- type: v_measure_std |
|
value: 1.3306 |
|
- type: main_score |
|
value: 20.0754 |
|
task: |
|
type: Clustering |
|
- dataset: |
|
config: default |
|
name: MTEB MindSmallReranking (default) |
|
revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7 |
|
split: test |
|
type: mteb/mind_small |
|
metrics: |
|
- type: map |
|
value: 28.5611 |
|
- type: mrr |
|
value: 29.4014 |
|
- type: nAUC_map_max |
|
value: -20.8019 |
|
- type: nAUC_map_std |
|
value: -5.307300000000001 |
|
- type: nAUC_map_diff1 |
|
value: 20.6483 |
|
- type: nAUC_mrr_max |
|
value: -14.9738 |
|
- type: nAUC_mrr_std |
|
value: -2.9508 |
|
- type: nAUC_mrr_diff1 |
|
value: 18.6743 |
|
- type: main_score |
|
value: 28.5611 |
|
task: |
|
type: Reranking |
|
- dataset: |
|
config: default |
|
name: MTEB NFCorpus (default) |
|
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
|
split: test |
|
type: mteb/nfcorpus |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 32.972 |
|
- type: ndcg_at_3 |
|
value: 29.965000000000003 |
|
- type: ndcg_at_5 |
|
value: 28.773 |
|
- type: ndcg_at_10 |
|
value: 26.434 |
|
- type: ndcg_at_20 |
|
value: 24.922 |
|
- type: ndcg_at_100 |
|
value: 24.852 |
|
- type: ndcg_at_1000 |
|
value: 33.388 |
|
- type: map_at_1 |
|
value: 3.737 |
|
- type: map_at_3 |
|
value: 6.387 |
|
- type: map_at_5 |
|
value: 7.420999999999999 |
|
- type: map_at_10 |
|
value: 8.652 |
|
- type: map_at_20 |
|
value: 9.745 |
|
- type: map_at_100 |
|
value: 11.247 |
|
- type: map_at_1000 |
|
value: 12.494 |
|
- type: recall_at_1 |
|
value: 3.737 |
|
- type: recall_at_3 |
|
value: 7.889 |
|
- type: recall_at_5 |
|
value: 10.026 |
|
- type: recall_at_10 |
|
value: 12.615000000000002 |
|
- type: recall_at_20 |
|
value: 16.184 |
|
- type: recall_at_100 |
|
value: 26.988 |
|
- type: recall_at_1000 |
|
value: 57.594 |
|
- type: precision_at_1 |
|
value: 34.675 |
|
- type: precision_at_3 |
|
value: 28.173 |
|
- type: precision_at_5 |
|
value: 25.201 |
|
- type: precision_at_10 |
|
value: 20.0 |
|
- type: precision_at_20 |
|
value: 15.356 |
|
- type: precision_at_100 |
|
value: 6.898 |
|
- type: precision_at_1000 |
|
value: 1.936 |
|
- type: mrr_at_1 |
|
value: 34.674899999999994 |
|
- type: mrr_at_3 |
|
value: 42.0537 |
|
- type: mrr_at_5 |
|
value: 43.741 |
|
- type: mrr_at_10 |
|
value: 44.277699999999996 |
|
- type: mrr_at_20 |
|
value: 44.819700000000005 |
|
- type: mrr_at_100 |
|
value: 45.1552 |
|
- type: mrr_at_1000 |
|
value: 45.2048 |
|
- type: nauc_ndcg_at_1_max |
|
value: 27.6992 |
|
- type: nauc_ndcg_at_1_std |
|
value: 13.1387 |
|
- type: nauc_ndcg_at_1_diff1 |
|
value: 33.7772 |
|
- type: nauc_ndcg_at_3_max |
|
value: 32.4741 |
|
- type: nauc_ndcg_at_3_std |
|
value: 19.264 |
|
- type: nauc_ndcg_at_3_diff1 |
|
value: 26.1486 |
|
- type: nauc_ndcg_at_5_max |
|
value: 32.6623 |
|
- type: nauc_ndcg_at_5_std |
|
value: 21.435499999999998 |
|
- type: nauc_ndcg_at_5_diff1 |
|
value: 24.0412 |
|
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|
value: 33.217400000000005 |
|
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|
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|
- type: nauc_ndcg_at_10_diff1 |
|
value: 22.3637 |
|
- type: nauc_ndcg_at_20_max |
|
value: 33.3978 |
|
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|
value: 22.520200000000003 |
|
- type: nauc_ndcg_at_20_diff1 |
|
value: 22.0163 |
|
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|
value: 33.0608 |
|
- type: nauc_ndcg_at_100_std |
|
value: 20.4305 |
|
- type: nauc_ndcg_at_100_diff1 |
|
value: 21.1175 |
|
- type: nauc_ndcg_at_1000_max |
|
value: 38.198100000000004 |
|
- type: nauc_ndcg_at_1000_std |
|
value: 26.8712 |
|
- type: nauc_ndcg_at_1000_diff1 |
|
value: 22.78 |
|
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|
value: 18.898300000000003 |
|
- type: nauc_map_at_1_std |
|
value: -11.0976 |
|
- type: nauc_map_at_1_diff1 |
|
value: 55.1605 |
|
- type: nauc_map_at_3_max |
|
value: 20.451800000000002 |
|
- type: nauc_map_at_3_std |
|
value: -12.0342 |
|
- type: nauc_map_at_3_diff1 |
|
value: 45.2096 |
|
- type: nauc_map_at_5_max |
|
value: 21.199 |
|
- type: nauc_map_at_5_std |
|
value: -9.8514 |
|
- type: nauc_map_at_5_diff1 |
|
value: 42.0142 |
|
- type: nauc_map_at_10_max |
|
value: 23.1645 |
|
- type: nauc_map_at_10_std |
|
value: -5.8333 |
|
- type: nauc_map_at_10_diff1 |
|
value: 38.048 |
|
- type: nauc_map_at_20_max |
|
value: 24.9482 |
|
- type: nauc_map_at_20_std |
|
value: -1.5368 |
|
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|
value: 36.241299999999995 |
|
- type: nauc_map_at_100_max |
|
value: 27.1413 |
|
- type: nauc_map_at_100_std |
|
value: 5.6268 |
|
- type: nauc_map_at_100_diff1 |
|
value: 33.3298 |
|
- type: nauc_map_at_1000_max |
|
value: 28.7674 |
|
- type: nauc_map_at_1000_std |
|
value: 10.9326 |
|
- type: nauc_map_at_1000_diff1 |
|
value: 31.700899999999997 |
|
- type: nauc_recall_at_1_max |
|
value: 18.898300000000003 |
|
- type: nauc_recall_at_1_std |
|
value: -11.0976 |
|
- type: nauc_recall_at_1_diff1 |
|
value: 55.1605 |
|
- type: nauc_recall_at_3_max |
|
value: 19.4721 |
|
- type: nauc_recall_at_3_std |
|
value: -13.496 |
|
- type: nauc_recall_at_3_diff1 |
|
value: 35.0178 |
|
- type: nauc_recall_at_5_max |
|
value: 19.5024 |
|
- type: nauc_recall_at_5_std |
|
value: -12.3428 |
|
- type: nauc_recall_at_5_diff1 |
|
value: 29.517 |
|
- type: nauc_recall_at_10_max |
|
value: 21.215500000000002 |
|
- type: nauc_recall_at_10_std |
|
value: -8.7165 |
|
- type: nauc_recall_at_10_diff1 |
|
value: 24.282 |
|
- type: nauc_recall_at_20_max |
|
value: 21.735 |
|
- type: nauc_recall_at_20_std |
|
value: -5.0988999999999995 |
|
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|
value: 20.3041 |
|
- type: nauc_recall_at_100_max |
|
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|
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|
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|
- type: nauc_recall_at_100_diff1 |
|
value: 5.9747 |
|
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|
value: 21.7819 |
|
- type: nauc_recall_at_1000_std |
|
value: 13.6785 |
|
- type: nauc_recall_at_1000_diff1 |
|
value: -0.25980000000000003 |
|
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|
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|
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|
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|
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|
value: 33.308 |
|
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|
value: 35.1699 |
|
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|
value: 25.9338 |
|
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|
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|
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|
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|
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|
value: 32.4517 |
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
value: 44.658 |
|
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|
value: 2.2702 |
|
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|
value: 25.163600000000002 |
|
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|
value: 51.7642 |
|
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|
value: -4.8361 |
|
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|
value: 20.2984 |
|
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|
value: 49.0469 |
|
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|
value: -6.662700000000001 |
|
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|
value: 28.624899999999997 |
|
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|
value: 12.709599999999998 |
|
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|
value: 33.308 |
|
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|
value: 32.3306 |
|
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|
value: 18.1604 |
|
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|
value: 31.128600000000002 |
|
- type: nauc_mrr_at_5_max |
|
value: 32.0504 |
|
- type: nauc_mrr_at_5_std |
|
value: 18.3022 |
|
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|
value: 30.1868 |
|
- type: nauc_mrr_at_10_max |
|
value: 32.093500000000006 |
|
- type: nauc_mrr_at_10_std |
|
value: 18.348 |
|
- type: nauc_mrr_at_10_diff1 |
|
value: 30.2307 |
|
- type: nauc_mrr_at_20_max |
|
value: 32.3491 |
|
- type: nauc_mrr_at_20_std |
|
value: 18.309800000000003 |
|
- type: nauc_mrr_at_20_diff1 |
|
value: 30.0848 |
|
- type: nauc_mrr_at_100_max |
|
value: 32.5297 |
|
- type: nauc_mrr_at_100_std |
|
value: 18.4197 |
|
- type: nauc_mrr_at_100_diff1 |
|
value: 30.03 |
|
- type: nauc_mrr_at_1000_max |
|
value: 32.502700000000004 |
|
- type: nauc_mrr_at_1000_std |
|
value: 18.4073 |
|
- type: nauc_mrr_at_1000_diff1 |
|
value: 30.059599999999996 |
|
- type: main_score |
|
value: 26.434 |
|
task: |
|
type: Retrieval |
|
- dataset: |
|
config: default |
|
name: MTEB NQ (default) |
|
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
|
split: test |
|
type: mteb/nq |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 9.067 |
|
- type: ndcg_at_3 |
|
value: 13.33 |
|
- type: ndcg_at_5 |
|
value: 15.773000000000001 |
|
- type: ndcg_at_10 |
|
value: 18.239 |
|
- type: ndcg_at_20 |
|
value: 20.777 |
|
- type: ndcg_at_100 |
|
value: 25.046000000000003 |
|
- type: ndcg_at_1000 |
|
value: 27.814 |
|
- type: map_at_1 |
|
value: 8.007 |
|
- type: map_at_3 |
|
value: 11.732 |
|
- type: map_at_5 |
|
value: 13.095 |
|
- type: map_at_10 |
|
value: 14.127 |
|
- type: map_at_20 |
|
value: 14.860000000000001 |
|
- type: map_at_100 |
|
value: 15.467 |
|
- type: map_at_1000 |
|
value: 15.57 |
|
- type: recall_at_1 |
|
value: 8.007 |
|
- type: recall_at_3 |
|
value: 16.553 |
|
- type: recall_at_5 |
|
value: 22.282 |
|
- type: recall_at_10 |
|
value: 29.592000000000002 |
|
- type: recall_at_20 |
|
value: 39.134 |
|
- type: recall_at_100 |
|
value: 61.307 |
|
- type: recall_at_1000 |
|
value: 82.556 |
|
- type: precision_at_1 |
|
value: 9.067 |
|
- type: precision_at_3 |
|
value: 6.441 |
|
- type: precision_at_5 |
|
value: 5.220000000000001 |
|
- type: precision_at_10 |
|
value: 3.488 |
|
- type: precision_at_20 |
|
value: 2.329 |
|
- type: precision_at_100 |
|
value: 0.734 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: mrr_at_1 |
|
value: 9.0672 |
|
- type: mrr_at_3 |
|
value: 13.1277 |
|
- type: mrr_at_5 |
|
value: 14.544199999999998 |
|
- type: mrr_at_10 |
|
value: 15.589400000000001 |
|
- type: mrr_at_20 |
|
value: 16.2651 |
|
- type: mrr_at_100 |
|
value: 16.8195 |
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|
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value: 17.5657 |
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|
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|
value: 8.82 |
|
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value: 11.3832 |
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value: -4.1221 |
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value: 20.5341 |
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value: 12.951099999999999 |
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- type: nauc_precision_at_3_std |
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value: -3.4715999999999996 |
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value: 14.0988 |
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value: 13.7598 |
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|
value: -2.8705000000000003 |
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|
value: 15.6886 |
|
- type: main_score |
|
value: 18.239 |
|
task: |
|
type: Retrieval |
|
- dataset: |
|
config: default |
|
name: MTEB QuoraRetrieval (default) |
|
revision: e4e08e0b7dbe3c8700f0daef558ff32256715259 |
|
split: test |
|
type: mteb/quora |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 72.39 |
|
- type: ndcg_at_3 |
|
value: 76.303 |
|
- type: ndcg_at_5 |
|
value: 78.164 |
|
- type: ndcg_at_10 |
|
value: 79.946 |
|
- type: ndcg_at_20 |
|
value: 80.963 |
|
- type: ndcg_at_100 |
|
value: 82.086 |
|
- type: ndcg_at_1000 |
|
value: 82.494 |
|
- type: map_at_1 |
|
value: 62.965 |
|
- type: map_at_3 |
|
value: 72.429 |
|
- type: map_at_5 |
|
value: 74.246 |
|
- type: map_at_10 |
|
value: 75.414 |
|
- type: map_at_20 |
|
value: 75.87899999999999 |
|
- type: map_at_100 |
|
value: 76.164 |
|
- type: map_at_1000 |
|
value: 76.198 |
|
- type: recall_at_1 |
|
value: 62.965 |
|
- type: recall_at_3 |
|
value: 78.39 |
|
- type: recall_at_5 |
|
value: 83.506 |
|
- type: recall_at_10 |
|
value: 88.787 |
|
- type: recall_at_20 |
|
value: 92.223 |
|
- type: recall_at_100 |
|
value: 96.98 |
|
- type: recall_at_1000 |
|
value: 99.30099999999999 |
|
- type: precision_at_1 |
|
value: 72.39 |
|
- type: precision_at_3 |
|
value: 33.040000000000006 |
|
- type: precision_at_5 |
|
value: 21.884 |
|
- type: precision_at_10 |
|
value: 12.084999999999999 |
|
- type: precision_at_20 |
|
value: 6.49 |
|
- type: precision_at_100 |
|
value: 1.444 |
|
- type: precision_at_1000 |
|
value: 0.154 |
|
- type: mrr_at_1 |
|
value: 72.39 |
|
- type: mrr_at_3 |
|
value: 77.9883 |
|
- type: mrr_at_5 |
|
value: 78.8933 |
|
- type: mrr_at_10 |
|
value: 79.443 |
|
- type: mrr_at_20 |
|
value: 79.6218 |
|
- type: mrr_at_100 |
|
value: 79.7045 |
|
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|
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|
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value: 20.025100000000002 |
|
- type: nauc_precision_at_1000_diff1 |
|
value: -34.4531 |
|
- type: nauc_mrr_at_1_max |
|
value: 43.2621 |
|
- type: nauc_mrr_at_1_std |
|
value: -15.864 |
|
- type: nauc_mrr_at_1_diff1 |
|
value: 74.5603 |
|
- type: nauc_mrr_at_3_max |
|
value: 43.8197 |
|
- type: nauc_mrr_at_3_std |
|
value: -16.1674 |
|
- type: nauc_mrr_at_3_diff1 |
|
value: 72.9802 |
|
- type: nauc_mrr_at_5_max |
|
value: 43.9843 |
|
- type: nauc_mrr_at_5_std |
|
value: -16.042 |
|
- type: nauc_mrr_at_5_diff1 |
|
value: 72.907 |
|
- type: nauc_mrr_at_10_max |
|
value: 44.0294 |
|
- type: nauc_mrr_at_10_std |
|
value: -15.711500000000001 |
|
- type: nauc_mrr_at_10_diff1 |
|
value: 72.9915 |
|
- type: nauc_mrr_at_20_max |
|
value: 44.044200000000004 |
|
- type: nauc_mrr_at_20_std |
|
value: -15.7842 |
|
- type: nauc_mrr_at_20_diff1 |
|
value: 73.0535 |
|
- type: nauc_mrr_at_100_max |
|
value: 44.0194 |
|
- type: nauc_mrr_at_100_std |
|
value: -15.7612 |
|
- type: nauc_mrr_at_100_diff1 |
|
value: 73.0738 |
|
- type: nauc_mrr_at_1000_max |
|
value: 44.0187 |
|
- type: nauc_mrr_at_1000_std |
|
value: -15.764100000000001 |
|
- type: nauc_mrr_at_1000_diff1 |
|
value: 73.0758 |
|
- type: main_score |
|
value: 79.946 |
|
task: |
|
type: Retrieval |
|
- dataset: |
|
config: default |
|
name: MTEB RedditClustering (default) |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
split: test |
|
type: mteb/reddit-clustering |
|
metrics: |
|
- type: v_measure |
|
value: 20.2171 |
|
- type: v_measure_std |
|
value: 4.4216 |
|
- type: main_score |
|
value: 20.2171 |
|
task: |
|
type: Clustering |
|
- dataset: |
|
config: default |
|
name: MTEB RedditClusteringP2P (default) |
|
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33 |
|
split: test |
|
type: mteb/reddit-clustering-p2p |
|
metrics: |
|
- type: v_measure |
|
value: 38.8882 |
|
- type: v_measure_std |
|
value: 9.315 |
|
- type: main_score |
|
value: 38.8882 |
|
task: |
|
type: Clustering |
|
- dataset: |
|
config: default |
|
name: MTEB SCIDOCS (default) |
|
revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88 |
|
split: test |
|
type: mteb/scidocs |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 15.1 |
|
- type: ndcg_at_3 |
|
value: 12.036 |
|
- type: ndcg_at_5 |
|
value: 11.007 |
|
- type: ndcg_at_10 |
|
value: 13.352 |
|
- type: ndcg_at_20 |
|
value: 15.6 |
|
- type: ndcg_at_100 |
|
value: 19.871 |
|
- type: ndcg_at_1000 |
|
value: 25.255 |
|
- type: map_at_1 |
|
value: 3.058 |
|
- type: map_at_3 |
|
value: 5.268 |
|
- type: map_at_5 |
|
value: 6.406000000000001 |
|
- type: map_at_10 |
|
value: 7.478 |
|
- type: map_at_20 |
|
value: 8.21 |
|
- type: map_at_100 |
|
value: 8.946 |
|
- type: map_at_1000 |
|
value: 9.223 |
|
- type: recall_at_1 |
|
value: 3.058 |
|
- type: recall_at_3 |
|
value: 6.793 |
|
- type: recall_at_5 |
|
value: 10.003 |
|
- type: recall_at_10 |
|
value: 14.288 |
|
- type: recall_at_20 |
|
value: 19.542 |
|
- type: recall_at_100 |
|
value: 33.413 |
|
- type: recall_at_1000 |
|
value: 59.733000000000004 |
|
- type: precision_at_1 |
|
value: 15.1 |
|
- type: precision_at_3 |
|
value: 11.167 |
|
- type: precision_at_5 |
|
value: 9.879999999999999 |
|
- type: precision_at_10 |
|
value: 7.07 |
|
- type: precision_at_20 |
|
value: 4.825 |
|
- type: precision_at_100 |
|
value: 1.649 |
|
- type: precision_at_1000 |
|
value: 0.294 |
|
- type: mrr_at_1 |
|
value: 15.1 |
|
- type: mrr_at_3 |
|
value: 20.2833 |
|
- type: mrr_at_5 |
|
value: 22.4733 |
|
- type: mrr_at_10 |
|
value: 23.6601 |
|
- type: mrr_at_20 |
|
value: 24.3772 |
|
- type: mrr_at_100 |
|
value: 24.9007 |
|
- type: mrr_at_1000 |
|
value: 24.9743 |
|
- type: nauc_ndcg_at_1_max |
|
value: 18.8537 |
|
- type: nauc_ndcg_at_1_std |
|
value: -3.2037000000000004 |
|
- type: nauc_ndcg_at_1_diff1 |
|
value: 20.8288 |
|
- type: nauc_ndcg_at_3_max |
|
value: 15.3817 |
|
- type: nauc_ndcg_at_3_std |
|
value: -3.2159 |
|
- type: nauc_ndcg_at_3_diff1 |
|
value: 18.13 |
|
- type: nauc_ndcg_at_5_max |
|
value: 17.940900000000003 |
|
- type: nauc_ndcg_at_5_std |
|
value: 0.3294 |
|
- type: nauc_ndcg_at_5_diff1 |
|
value: 16.9378 |
|
- type: nauc_ndcg_at_10_max |
|
value: 21.146 |
|
- type: nauc_ndcg_at_10_std |
|
value: 2.6954 |
|
- type: nauc_ndcg_at_10_diff1 |
|
value: 15.363399999999999 |
|
- type: nauc_ndcg_at_20_max |
|
value: 21.9075 |
|
- type: nauc_ndcg_at_20_std |
|
value: 4.9554 |
|
- type: nauc_ndcg_at_20_diff1 |
|
value: 15.4857 |
|
- type: nauc_ndcg_at_100_max |
|
value: 22.9248 |
|
- type: nauc_ndcg_at_100_std |
|
value: 8.8094 |
|
- type: nauc_ndcg_at_100_diff1 |
|
value: 15.1255 |
|
- type: nauc_ndcg_at_1000_max |
|
value: 24.7883 |
|
- type: nauc_ndcg_at_1000_std |
|
value: 13.3551 |
|
- type: nauc_ndcg_at_1000_diff1 |
|
value: 15.1244 |
|
- type: nauc_map_at_1_max |
|
value: 19.238 |
|
- type: nauc_map_at_1_std |
|
value: -2.9537 |
|
- type: nauc_map_at_1_diff1 |
|
value: 21.3456 |
|
- type: nauc_map_at_3_max |
|
value: 16.0914 |
|
- type: nauc_map_at_3_std |
|
value: -4.2357 |
|
- type: nauc_map_at_3_diff1 |
|
value: 17.1314 |
|
- type: nauc_map_at_5_max |
|
value: 17.9317 |
|
- type: nauc_map_at_5_std |
|
value: -1.2885 |
|
- type: nauc_map_at_5_diff1 |
|
value: 15.5052 |
|
- type: nauc_map_at_10_max |
|
value: 20.1204 |
|
- type: nauc_map_at_10_std |
|
value: 0.29109999999999997 |
|
- type: nauc_map_at_10_diff1 |
|
value: 14.513200000000001 |
|
- type: nauc_map_at_20_max |
|
value: 20.6688 |
|
- type: nauc_map_at_20_std |
|
value: 1.6063 |
|
- type: nauc_map_at_20_diff1 |
|
value: 14.934800000000001 |
|
- type: nauc_map_at_100_max |
|
value: 21.2455 |
|
- type: nauc_map_at_100_std |
|
value: 3.1651 |
|
- type: nauc_map_at_100_diff1 |
|
value: 14.6507 |
|
- type: nauc_map_at_1000_max |
|
value: 21.4903 |
|
- type: nauc_map_at_1000_std |
|
value: 3.7647 |
|
- type: nauc_map_at_1000_diff1 |
|
value: 14.6354 |
|
- type: nauc_recall_at_1_max |
|
value: 19.238 |
|
- type: nauc_recall_at_1_std |
|
value: -2.9537 |
|
- type: nauc_recall_at_1_diff1 |
|
value: 21.3456 |
|
- type: nauc_recall_at_3_max |
|
value: 14.5564 |
|
- type: nauc_recall_at_3_std |
|
value: -3.2211 |
|
- type: nauc_recall_at_3_diff1 |
|
value: 17.0505 |
|
- type: nauc_recall_at_5_max |
|
value: 18.159200000000002 |
|
- type: nauc_recall_at_5_std |
|
value: 2.6766 |
|
- type: nauc_recall_at_5_diff1 |
|
value: 14.7598 |
|
- type: nauc_recall_at_10_max |
|
value: 23.6071 |
|
- type: nauc_recall_at_10_std |
|
value: 6.6582 |
|
- type: nauc_recall_at_10_diff1 |
|
value: 11.7647 |
|
- type: nauc_recall_at_20_max |
|
value: 23.5471 |
|
- type: nauc_recall_at_20_std |
|
value: 10.6906 |
|
- type: nauc_recall_at_20_diff1 |
|
value: 11.5654 |
|
- type: nauc_recall_at_100_max |
|
value: 23.2746 |
|
- type: nauc_recall_at_100_std |
|
value: 18.3139 |
|
- type: nauc_recall_at_100_diff1 |
|
value: 10.2364 |
|
- type: nauc_recall_at_1000_max |
|
value: 27.2333 |
|
- type: nauc_recall_at_1000_std |
|
value: 32.5351 |
|
- type: nauc_recall_at_1000_diff1 |
|
value: 8.7211 |
|
- type: nauc_precision_at_1_max |
|
value: 18.8537 |
|
- type: nauc_precision_at_1_std |
|
value: -3.2037000000000004 |
|
- type: nauc_precision_at_1_diff1 |
|
value: 20.8288 |
|
- type: nauc_precision_at_3_max |
|
value: 14.260200000000001 |
|
- type: nauc_precision_at_3_std |
|
value: -3.1767 |
|
- type: nauc_precision_at_3_diff1 |
|
value: 16.9826 |
|
- type: nauc_precision_at_5_max |
|
value: 17.999399999999998 |
|
- type: nauc_precision_at_5_std |
|
value: 2.7119999999999997 |
|
- type: nauc_precision_at_5_diff1 |
|
value: 14.685300000000002 |
|
- type: nauc_precision_at_10_max |
|
value: 23.5629 |
|
- type: nauc_precision_at_10_std |
|
value: 6.7014000000000005 |
|
- type: nauc_precision_at_10_diff1 |
|
value: 11.6848 |
|
- type: nauc_precision_at_20_max |
|
value: 23.1819 |
|
- type: nauc_precision_at_20_std |
|
value: 10.478 |
|
- type: nauc_precision_at_20_diff1 |
|
value: 11.6263 |
|
- type: nauc_precision_at_100_max |
|
value: 22.7954 |
|
- type: nauc_precision_at_100_std |
|
value: 18.215500000000002 |
|
- type: nauc_precision_at_100_diff1 |
|
value: 10.526299999999999 |
|
- type: nauc_precision_at_1000_max |
|
value: 26.4283 |
|
- type: nauc_precision_at_1000_std |
|
value: 31.9492 |
|
- type: nauc_precision_at_1000_diff1 |
|
value: 9.031799999999999 |
|
- type: nauc_mrr_at_1_max |
|
value: 18.8537 |
|
- type: nauc_mrr_at_1_std |
|
value: -3.2037000000000004 |
|
- type: nauc_mrr_at_1_diff1 |
|
value: 20.8288 |
|
- type: nauc_mrr_at_3_max |
|
value: 16.253500000000003 |
|
- type: nauc_mrr_at_3_std |
|
value: -2.3413 |
|
- type: nauc_mrr_at_3_diff1 |
|
value: 20.333399999999997 |
|
- type: nauc_mrr_at_5_max |
|
value: 17.2285 |
|
- type: nauc_mrr_at_5_std |
|
value: -0.5249 |
|
- type: nauc_mrr_at_5_diff1 |
|
value: 20.119 |
|
- type: nauc_mrr_at_10_max |
|
value: 18.351100000000002 |
|
- type: nauc_mrr_at_10_std |
|
value: 0.0489 |
|
- type: nauc_mrr_at_10_diff1 |
|
value: 19.711000000000002 |
|
- type: nauc_mrr_at_20_max |
|
value: 18.409100000000002 |
|
- type: nauc_mrr_at_20_std |
|
value: 0.41079999999999994 |
|
- type: nauc_mrr_at_20_diff1 |
|
value: 19.5248 |
|
- type: nauc_mrr_at_100_max |
|
value: 18.404799999999998 |
|
- type: nauc_mrr_at_100_std |
|
value: 0.4336 |
|
- type: nauc_mrr_at_100_diff1 |
|
value: 19.5129 |
|
- type: nauc_mrr_at_1000_max |
|
value: 18.3706 |
|
- type: nauc_mrr_at_1000_std |
|
value: 0.41529999999999995 |
|
- type: nauc_mrr_at_1000_diff1 |
|
value: 19.5103 |
|
- type: main_score |
|
value: 13.352 |
|
task: |
|
type: Retrieval |
|
- dataset: |
|
config: default |
|
name: MTEB SICK-R (default) |
|
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d |
|
split: test |
|
type: mteb/sickr-sts |
|
metrics: |
|
- type: pearson |
|
value: 73.39529999999999 |
|
- type: spearman |
|
value: 63.871599999999994 |
|
- type: cosine_pearson |
|
value: 73.39529999999999 |
|
- type: cosine_spearman |
|
value: 63.871500000000005 |
|
- type: manhattan_pearson |
|
value: 62.5861 |
|
- type: manhattan_spearman |
|
value: 56.714600000000004 |
|
- type: euclidean_pearson |
|
value: 62.606899999999996 |
|
- type: euclidean_spearman |
|
value: 56.714200000000005 |
|
- type: main_score |
|
value: 63.871500000000005 |
|
task: |
|
type: STS |
|
- dataset: |
|
config: default |
|
name: MTEB STS12 (default) |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
split: test |
|
type: mteb/sts12-sts |
|
metrics: |
|
- type: pearson |
|
value: 72.35770000000001 |
|
- type: spearman |
|
value: 63.606899999999996 |
|
- type: cosine_pearson |
|
value: 72.35770000000001 |
|
- type: cosine_spearman |
|
value: 63.610299999999995 |
|
- type: manhattan_pearson |
|
value: 59.8404 |
|
- type: manhattan_spearman |
|
value: 56.85059999999999 |
|
- type: euclidean_pearson |
|
value: 59.8116 |
|
- type: euclidean_spearman |
|
value: 56.691 |
|
- type: main_score |
|
value: 63.610299999999995 |
|
task: |
|
type: STS |
|
- dataset: |
|
config: default |
|
name: MTEB STS13 (default) |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
split: test |
|
type: mteb/sts13-sts |
|
metrics: |
|
- type: pearson |
|
value: 76.4727 |
|
- type: spearman |
|
value: 76.983 |
|
- type: cosine_pearson |
|
value: 76.4727 |
|
- type: cosine_spearman |
|
value: 76.983 |
|
- type: manhattan_pearson |
|
value: 49.4803 |
|
- type: manhattan_spearman |
|
value: 51.1301 |
|
- type: euclidean_pearson |
|
value: 49.4542 |
|
- type: euclidean_spearman |
|
value: 51.19669999999999 |
|
- type: main_score |
|
value: 76.983 |
|
task: |
|
type: STS |
|
- dataset: |
|
config: default |
|
name: MTEB STS14 (default) |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
split: test |
|
type: mteb/sts14-sts |
|
metrics: |
|
- type: pearson |
|
value: 75.777 |
|
- type: spearman |
|
value: 71.2099 |
|
- type: cosine_pearson |
|
value: 75.777 |
|
- type: cosine_spearman |
|
value: 71.2099 |
|
- type: manhattan_pearson |
|
value: 52.475899999999996 |
|
- type: manhattan_spearman |
|
value: 53.8072 |
|
- type: euclidean_pearson |
|
value: 52.416799999999995 |
|
- type: euclidean_spearman |
|
value: 53.725500000000004 |
|
- type: main_score |
|
value: 71.2099 |
|
task: |
|
type: STS |
|
- dataset: |
|
config: default |
|
name: MTEB STS15 (default) |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
split: test |
|
type: mteb/sts15-sts |
|
metrics: |
|
- type: pearson |
|
value: 80.1072 |
|
- type: spearman |
|
value: 80.735 |
|
- type: cosine_pearson |
|
value: 80.1072 |
|
- type: cosine_spearman |
|
value: 80.7349 |
|
- type: manhattan_pearson |
|
value: 50.711600000000004 |
|
- type: manhattan_spearman |
|
value: 53.491299999999995 |
|
- type: euclidean_pearson |
|
value: 50.6255 |
|
- type: euclidean_spearman |
|
value: 53.47539999999999 |
|
- type: main_score |
|
value: 80.7349 |
|
task: |
|
type: STS |
|
- dataset: |
|
config: default |
|
name: MTEB STS16 (default) |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
split: test |
|
type: mteb/sts16-sts |
|
metrics: |
|
- type: pearson |
|
value: 73.1658 |
|
- type: spearman |
|
value: 74.2121 |
|
- type: cosine_pearson |
|
value: 73.1658 |
|
- type: cosine_spearman |
|
value: 74.2121 |
|
- type: manhattan_pearson |
|
value: 43.4074 |
|
- type: manhattan_spearman |
|
value: 47.193200000000004 |
|
- type: euclidean_pearson |
|
value: 43.438300000000005 |
|
- type: euclidean_spearman |
|
value: 47.2757 |
|
- type: main_score |
|
value: 74.2121 |
|
task: |
|
type: STS |
|
- dataset: |
|
config: en-en |
|
name: MTEB STS17 (en-en) |
|
revision: faeb762787bd10488a50c8b5be4a3b82e411949c |
|
split: test |
|
type: mteb/sts17-crosslingual-sts |
|
metrics: |
|
- type: pearson |
|
value: 81.8156 |
|
- type: spearman |
|
value: 81.9457 |
|
- type: cosine_pearson |
|
value: 81.8156 |
|
- type: cosine_spearman |
|
value: 81.9457 |
|
- type: manhattan_pearson |
|
value: 59.4332 |
|
- type: manhattan_spearman |
|
value: 60.5687 |
|
- type: euclidean_pearson |
|
value: 59.2942 |
|
- type: euclidean_spearman |
|
value: 60.39679999999999 |
|
- type: main_score |
|
value: 81.9457 |
|
task: |
|
type: STS |
|
- dataset: |
|
config: en |
|
name: MTEB STS22 (en) |
|
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 |
|
split: test |
|
type: mteb/sts22-crosslingual-sts |
|
metrics: |
|
- type: pearson |
|
value: 48.9285 |
|
- type: spearman |
|
value: 55.862500000000004 |
|
- type: cosine_pearson |
|
value: 48.9285 |
|
- type: cosine_spearman |
|
value: 55.862500000000004 |
|
- type: manhattan_pearson |
|
value: 43.082300000000004 |
|
- type: manhattan_spearman |
|
value: 51.1876 |
|
- type: euclidean_pearson |
|
value: 43.2313 |
|
- type: euclidean_spearman |
|
value: 51.094899999999996 |
|
- type: main_score |
|
value: 55.862500000000004 |
|
task: |
|
type: STS |
|
- dataset: |
|
config: default |
|
name: MTEB STSBenchmark (default) |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
split: test |
|
type: mteb/stsbenchmark-sts |
|
metrics: |
|
- type: pearson |
|
value: 73.44380000000001 |
|
- type: spearman |
|
value: 71.9343 |
|
- type: cosine_pearson |
|
value: 73.44380000000001 |
|
- type: cosine_spearman |
|
value: 71.9345 |
|
- type: manhattan_pearson |
|
value: 52.233799999999995 |
|
- type: manhattan_spearman |
|
value: 51.7687 |
|
- type: euclidean_pearson |
|
value: 52.2753 |
|
- type: euclidean_spearman |
|
value: 51.845 |
|
- type: main_score |
|
value: 71.9345 |
|
task: |
|
type: STS |
|
- dataset: |
|
config: default |
|
name: MTEB SciDocsRR (default) |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
split: test |
|
type: mteb/scidocs-reranking |
|
metrics: |
|
- type: map |
|
value: 71.4557 |
|
- type: mrr |
|
value: 90.6219 |
|
- type: nAUC_map_max |
|
value: 54.74830000000001 |
|
- type: nAUC_map_std |
|
value: 65.2558 |
|
- type: nAUC_map_diff1 |
|
value: 10.2936 |
|
- type: nAUC_mrr_max |
|
value: 75.10900000000001 |
|
- type: nAUC_mrr_std |
|
value: 69.6523 |
|
- type: nAUC_mrr_diff1 |
|
value: 49.4991 |
|
- type: main_score |
|
value: 71.4557 |
|
task: |
|
type: Reranking |
|
- dataset: |
|
config: default |
|
name: MTEB SciFact (default) |
|
revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
|
split: test |
|
type: mteb/scifact |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 43.667 |
|
- type: ndcg_at_3 |
|
value: 52.102000000000004 |
|
- type: ndcg_at_5 |
|
value: 54.751000000000005 |
|
- type: ndcg_at_10 |
|
value: 57.422 |
|
- type: ndcg_at_20 |
|
value: 59.425 |
|
- type: ndcg_at_100 |
|
value: 61.166 |
|
- type: ndcg_at_1000 |
|
value: 62.244 |
|
- type: map_at_1 |
|
value: 41.888999999999996 |
|
- type: map_at_3 |
|
value: 49.435 |
|
- type: map_at_5 |
|
value: 51.029 |
|
- type: map_at_10 |
|
value: 52.190000000000005 |
|
- type: map_at_20 |
|
value: 52.797000000000004 |
|
- type: map_at_100 |
|
value: 53.03 |
|
- type: map_at_1000 |
|
value: 53.069 |
|
- type: recall_at_1 |
|
value: 41.888999999999996 |
|
- type: recall_at_3 |
|
value: 57.916999999999994 |
|
- type: recall_at_5 |
|
value: 64.372 |
|
- type: recall_at_10 |
|
value: 72.311 |
|
- type: recall_at_20 |
|
value: 79.97800000000001 |
|
- type: recall_at_100 |
|
value: 89.333 |
|
- type: recall_at_1000 |
|
value: 97.867 |
|
- type: precision_at_1 |
|
value: 43.667 |
|
- type: precision_at_3 |
|
value: 20.778 |
|
- type: precision_at_5 |
|
value: 14.066999999999998 |
|
- type: precision_at_10 |
|
value: 8.033 |
|
- type: precision_at_20 |
|
value: 4.45 |
|
- type: precision_at_100 |
|
value: 1.0030000000000001 |
|
- type: precision_at_1000 |
|
value: 0.11 |
|
- type: mrr_at_1 |
|
value: 43.666700000000006 |
|
- type: mrr_at_3 |
|
value: 50.9444 |
|
- type: mrr_at_5 |
|
value: 52.3444 |
|
- type: mrr_at_10 |
|
value: 53.3852 |
|
- type: mrr_at_20 |
|
value: 53.8864 |
|
- type: mrr_at_100 |
|
value: 54.0887 |
|
- type: mrr_at_1000 |
|
value: 54.11749999999999 |
|
- type: nauc_ndcg_at_1_max |
|
value: 36.6444 |
|
- type: nauc_ndcg_at_1_std |
|
value: -7.4722 |
|
- type: nauc_ndcg_at_1_diff1 |
|
value: 63.631099999999996 |
|
- type: nauc_ndcg_at_3_max |
|
value: 37.2859 |
|
- type: nauc_ndcg_at_3_std |
|
value: -11.2775 |
|
- type: nauc_ndcg_at_3_diff1 |
|
value: 56.352999999999994 |
|
- type: nauc_ndcg_at_5_max |
|
value: 36.7832 |
|
- type: nauc_ndcg_at_5_std |
|
value: -12.310699999999999 |
|
- type: nauc_ndcg_at_5_diff1 |
|
value: 55.41740000000001 |
|
- type: nauc_ndcg_at_10_max |
|
value: 37.9586 |
|
- type: nauc_ndcg_at_10_std |
|
value: -9.7483 |
|
- type: nauc_ndcg_at_10_diff1 |
|
value: 56.8082 |
|
- type: nauc_ndcg_at_20_max |
|
value: 38.4072 |
|
- type: nauc_ndcg_at_20_std |
|
value: -7.473299999999999 |
|
- type: nauc_ndcg_at_20_diff1 |
|
value: 56.4974 |
|
- type: nauc_ndcg_at_100_max |
|
value: 38.5583 |
|
- type: nauc_ndcg_at_100_std |
|
value: -5.521100000000001 |
|
- type: nauc_ndcg_at_100_diff1 |
|
value: 56.8808 |
|
- type: nauc_ndcg_at_1000_max |
|
value: 38.580999999999996 |
|
- type: nauc_ndcg_at_1000_std |
|
value: -6.6578 |
|
- type: nauc_ndcg_at_1000_diff1 |
|
value: 57.3412 |
|
- type: nauc_map_at_1_max |
|
value: 35.4069 |
|
- type: nauc_map_at_1_std |
|
value: -11.9598 |
|
- type: nauc_map_at_1_diff1 |
|
value: 62.351299999999995 |
|
- type: nauc_map_at_3_max |
|
value: 36.3612 |
|
- type: nauc_map_at_3_std |
|
value: -12.6999 |
|
- type: nauc_map_at_3_diff1 |
|
value: 57.918099999999995 |
|
- type: nauc_map_at_5_max |
|
value: 36.268299999999996 |
|
- type: nauc_map_at_5_std |
|
value: -12.921199999999999 |
|
- type: nauc_map_at_5_diff1 |
|
value: 57.496 |
|
- type: nauc_map_at_10_max |
|
value: 36.918099999999995 |
|
- type: nauc_map_at_10_std |
|
value: -11.6299 |
|
- type: nauc_map_at_10_diff1 |
|
value: 58.1148 |
|
- type: nauc_map_at_20_max |
|
value: 37.060900000000004 |
|
- type: nauc_map_at_20_std |
|
value: -10.8228 |
|
- type: nauc_map_at_20_diff1 |
|
value: 58.0205 |
|
- type: nauc_map_at_100_max |
|
value: 37.085499999999996 |
|
- type: nauc_map_at_100_std |
|
value: -10.5358 |
|
- type: nauc_map_at_100_diff1 |
|
value: 58.095 |
|
- type: nauc_map_at_1000_max |
|
value: 37.1083 |
|
- type: nauc_map_at_1000_std |
|
value: -10.5578 |
|
- type: nauc_map_at_1000_diff1 |
|
value: 58.1224 |
|
- type: nauc_recall_at_1_max |
|
value: 35.4069 |
|
- type: nauc_recall_at_1_std |
|
value: -11.9598 |
|
- type: nauc_recall_at_1_diff1 |
|
value: 62.351299999999995 |
|
- type: nauc_recall_at_3_max |
|
value: 37.6511 |
|
- type: nauc_recall_at_3_std |
|
value: -13.3993 |
|
- type: nauc_recall_at_3_diff1 |
|
value: 50.4572 |
|
- type: nauc_recall_at_5_max |
|
value: 35.8548 |
|
- type: nauc_recall_at_5_std |
|
value: -16.1098 |
|
- type: nauc_recall_at_5_diff1 |
|
value: 47.2106 |
|
- type: nauc_recall_at_10_max |
|
value: 38.9793 |
|
- type: nauc_recall_at_10_std |
|
value: -8.1869 |
|
- type: nauc_recall_at_10_diff1 |
|
value: 50.5379 |
|
- type: nauc_recall_at_20_max |
|
value: 42.3127 |
|
- type: nauc_recall_at_20_std |
|
value: 4.1918999999999995 |
|
- type: nauc_recall_at_20_diff1 |
|
value: 47.5366 |
|
- type: nauc_recall_at_100_max |
|
value: 48.4392 |
|
- type: nauc_recall_at_100_std |
|
value: 37.5486 |
|
- type: nauc_recall_at_100_diff1 |
|
value: 46.853699999999996 |
|
- type: nauc_recall_at_1000_max |
|
value: 70.1389 |
|
- type: nauc_recall_at_1000_std |
|
value: 81.7519 |
|
- type: nauc_recall_at_1000_diff1 |
|
value: 46.0741 |
|
- type: nauc_precision_at_1_max |
|
value: 36.6444 |
|
- type: nauc_precision_at_1_std |
|
value: -7.4722 |
|
- type: nauc_precision_at_1_diff1 |
|
value: 63.631099999999996 |
|
- type: nauc_precision_at_3_max |
|
value: 37.9141 |
|
- type: nauc_precision_at_3_std |
|
value: -2.6281 |
|
- type: nauc_precision_at_3_diff1 |
|
value: 45.406600000000005 |
|
- type: nauc_precision_at_5_max |
|
value: 35.0402 |
|
- type: nauc_precision_at_5_std |
|
value: 0.7128 |
|
- type: nauc_precision_at_5_diff1 |
|
value: 36.686099999999996 |
|
- type: nauc_precision_at_10_max |
|
value: 37.4825 |
|
- type: nauc_precision_at_10_std |
|
value: 15.613199999999999 |
|
- type: nauc_precision_at_10_diff1 |
|
value: 33.1716 |
|
- type: nauc_precision_at_20_max |
|
value: 36.1575 |
|
- type: nauc_precision_at_20_std |
|
value: 30.4446 |
|
- type: nauc_precision_at_20_diff1 |
|
value: 23.3224 |
|
- type: nauc_precision_at_100_max |
|
value: 29.5019 |
|
- type: nauc_precision_at_100_std |
|
value: 52.942 |
|
- type: nauc_precision_at_100_diff1 |
|
value: 9.0284 |
|
- type: nauc_precision_at_1000_max |
|
value: 20.350099999999998 |
|
- type: nauc_precision_at_1000_std |
|
value: 52.2915 |
|
- type: nauc_precision_at_1000_diff1 |
|
value: -8.6009 |
|
- type: nauc_mrr_at_1_max |
|
value: 36.6444 |
|
- type: nauc_mrr_at_1_std |
|
value: -7.4722 |
|
- type: nauc_mrr_at_1_diff1 |
|
value: 63.631099999999996 |
|
- type: nauc_mrr_at_3_max |
|
value: 38.016299999999994 |
|
- type: nauc_mrr_at_3_std |
|
value: -8.0229 |
|
- type: nauc_mrr_at_3_diff1 |
|
value: 58.757400000000004 |
|
- type: nauc_mrr_at_5_max |
|
value: 37.433899999999994 |
|
- type: nauc_mrr_at_5_std |
|
value: -8.1996 |
|
- type: nauc_mrr_at_5_diff1 |
|
value: 58.235899999999994 |
|
- type: nauc_mrr_at_10_max |
|
value: 37.7997 |
|
- type: nauc_mrr_at_10_std |
|
value: -7.542699999999999 |
|
- type: nauc_mrr_at_10_diff1 |
|
value: 58.8486 |
|
- type: nauc_mrr_at_20_max |
|
value: 37.8879 |
|
- type: nauc_mrr_at_20_std |
|
value: -7.133000000000001 |
|
- type: nauc_mrr_at_20_diff1 |
|
value: 58.834900000000005 |
|
- type: nauc_mrr_at_100_max |
|
value: 37.8627 |
|
- type: nauc_mrr_at_100_std |
|
value: -6.9667 |
|
- type: nauc_mrr_at_100_diff1 |
|
value: 58.880900000000004 |
|
- type: nauc_mrr_at_1000_max |
|
value: 37.8675 |
|
- type: nauc_mrr_at_1000_std |
|
value: -6.9817 |
|
- type: nauc_mrr_at_1000_diff1 |
|
value: 58.904500000000006 |
|
- type: main_score |
|
value: 57.422 |
|
task: |
|
type: Retrieval |
|
- dataset: |
|
config: default |
|
name: MTEB SprintDuplicateQuestions (default) |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
split: test |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
metrics: |
|
- type: similarity_accuracy |
|
value: 99.6703 |
|
- type: similarity_accuracy_threshold |
|
value: 81.69669999999999 |
|
- type: similarity_f1 |
|
value: 82.5479 |
|
- type: similarity_f1_threshold |
|
value: 80.97919999999999 |
|
- type: similarity_precision |
|
value: 85.6069 |
|
- type: similarity_recall |
|
value: 79.7 |
|
- type: similarity_ap |
|
value: 87.6918 |
|
- type: cosine_accuracy |
|
value: 99.6703 |
|
- type: cosine_accuracy_threshold |
|
value: 81.69669999999999 |
|
- type: cosine_f1 |
|
value: 82.5479 |
|
- type: cosine_f1_threshold |
|
value: 80.97919999999999 |
|
- type: cosine_precision |
|
value: 85.6069 |
|
- type: cosine_recall |
|
value: 79.7 |
|
- type: cosine_ap |
|
value: 87.6918 |
|
- type: manhattan_accuracy |
|
value: 99.4327 |
|
- type: manhattan_accuracy_threshold |
|
value: 2292.4838999999997 |
|
- type: manhattan_f1 |
|
value: 66.0851 |
|
- type: manhattan_f1_threshold |
|
value: 2517.333 |
|
- type: manhattan_precision |
|
value: 72.6619 |
|
- type: manhattan_recall |
|
value: 60.6 |
|
- type: manhattan_ap |
|
value: 68.1683 |
|
- type: euclidean_accuracy |
|
value: 99.4327 |
|
- type: euclidean_accuracy_threshold |
|
value: 105.6427 |
|
- type: euclidean_f1 |
|
value: 66.1605 |
|
- type: euclidean_f1_threshold |
|
value: 114.9346 |
|
- type: euclidean_precision |
|
value: 72.2749 |
|
- type: euclidean_recall |
|
value: 61.0 |
|
- type: euclidean_ap |
|
value: 68.2419 |
|
- type: dot_accuracy |
|
value: 99.0168 |
|
- type: dot_accuracy_threshold |
|
value: 1011.5417000000001 |
|
- type: dot_f1 |
|
value: 18.6459 |
|
- type: dot_f1_threshold |
|
value: 554.0581999999999 |
|
- type: dot_precision |
|
value: 20.9476 |
|
- type: dot_recall |
|
value: 16.8 |
|
- type: dot_ap |
|
value: 11.5838 |
|
- type: max_accuracy |
|
value: 99.6703 |
|
- type: max_f1 |
|
value: 82.5479 |
|
- type: max_precision |
|
value: 85.6069 |
|
- type: max_recall |
|
value: 79.7 |
|
- type: max_ap |
|
value: 87.6918 |
|
- type: main_score |
|
value: 87.6918 |
|
task: |
|
type: PairClassification |
|
- dataset: |
|
config: default |
|
name: MTEB StackExchangeClustering (default) |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
split: test |
|
type: mteb/stackexchange-clustering |
|
metrics: |
|
- type: v_measure |
|
value: 27.147700000000004 |
|
- type: v_measure_std |
|
value: 4.3151 |
|
- type: main_score |
|
value: 27.147700000000004 |
|
task: |
|
type: Clustering |
|
- dataset: |
|
config: default |
|
name: MTEB StackExchangeClusteringP2P (default) |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
split: test |
|
type: mteb/stackexchange-clustering-p2p |
|
metrics: |
|
- type: v_measure |
|
value: 28.9253 |
|
- type: v_measure_std |
|
value: 1.6500000000000001 |
|
- type: main_score |
|
value: 28.9253 |
|
task: |
|
type: Clustering |
|
- dataset: |
|
config: default |
|
name: MTEB StackOverflowDupQuestions (default) |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
split: test |
|
type: mteb/stackoverflowdupquestions-reranking |
|
metrics: |
|
- type: map |
|
value: 42.7933 |
|
- type: mrr |
|
value: 43.2531 |
|
- type: nAUC_map_max |
|
value: 15.137400000000001 |
|
- type: nAUC_map_std |
|
value: 4.6048 |
|
- type: nAUC_map_diff1 |
|
value: 31.665100000000002 |
|
- type: nAUC_mrr_max |
|
value: 16.429299999999998 |
|
- type: nAUC_mrr_std |
|
value: 4.943899999999999 |
|
- type: nAUC_mrr_diff1 |
|
value: 30.8849 |
|
- type: main_score |
|
value: 42.7933 |
|
task: |
|
type: Reranking |
|
- dataset: |
|
config: default |
|
name: MTEB SummEval (default) |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
split: test |
|
type: mteb/summeval |
|
metrics: |
|
- type: pearson |
|
value: 31.8891 |
|
- type: spearman |
|
value: 30.635299999999997 |
|
- type: cosine_spearman |
|
value: 30.635299999999997 |
|
- type: cosine_pearson |
|
value: 31.8891 |
|
- type: dot_spearman |
|
value: 23.1495 |
|
- type: dot_pearson |
|
value: 20.2811 |
|
- type: main_score |
|
value: 30.635299999999997 |
|
task: |
|
type: Summarization |
|
- dataset: |
|
config: default |
|
name: MTEB TRECCOVID (default) |
|
revision: bb9466bac8153a0349341eb1b22e06409e78ef4e |
|
split: test |
|
type: mteb/trec-covid |
|
metrics: |
|
- type: ndcg_at_1 |
|
value: 60.0 |
|
- type: ndcg_at_3 |
|
value: 56.592 |
|
- type: ndcg_at_5 |
|
value: 52.15 |
|
- type: ndcg_at_10 |
|
value: 48.264 |
|
- type: ndcg_at_20 |
|
value: 43.568 |
|
- type: ndcg_at_100 |
|
value: 31.196 |
|
- type: ndcg_at_1000 |
|
value: 26.101000000000003 |
|
- type: map_at_1 |
|
value: 0.153 |
|
- type: map_at_3 |
|
value: 0.4 |
|
- type: map_at_5 |
|
value: 0.601 |
|
- type: map_at_10 |
|
value: 1.016 |
|
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task: |
|
type: Retrieval |
|
- dataset: |
|
config: default |
|
name: MTEB Touche2020 (default) |
|
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
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split: test |
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type: mteb/touche2020 |
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- type: nauc_mrr_at_5_std |
|
value: -18.9591 |
|
- type: nauc_mrr_at_5_diff1 |
|
value: -13.2719 |
|
- type: nauc_mrr_at_10_max |
|
value: -41.7821 |
|
- type: nauc_mrr_at_10_std |
|
value: -18.368399999999998 |
|
- type: nauc_mrr_at_10_diff1 |
|
value: -13.4359 |
|
- type: nauc_mrr_at_20_max |
|
value: -42.8581 |
|
- type: nauc_mrr_at_20_std |
|
value: -18.6052 |
|
- type: nauc_mrr_at_20_diff1 |
|
value: -13.6098 |
|
- type: nauc_mrr_at_100_max |
|
value: -42.0696 |
|
- type: nauc_mrr_at_100_std |
|
value: -18.1447 |
|
- type: nauc_mrr_at_100_diff1 |
|
value: -14.102500000000001 |
|
- type: nauc_mrr_at_1000_max |
|
value: -42.0696 |
|
- type: nauc_mrr_at_1000_std |
|
value: -18.1447 |
|
- type: nauc_mrr_at_1000_diff1 |
|
value: -14.102500000000001 |
|
- type: main_score |
|
value: 17.318 |
|
task: |
|
type: Retrieval |
|
- dataset: |
|
config: default |
|
name: MTEB ToxicConversationsClassification (default) |
|
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de |
|
split: test |
|
type: mteb/toxic_conversations_50k |
|
metrics: |
|
- type: accuracy |
|
value: 74.0283 |
|
- type: f1 |
|
value: 54.813100000000006 |
|
- type: f1_weighted |
|
value: 79.4125 |
|
- type: ap |
|
value: 12.750800000000002 |
|
- type: ap_weighted |
|
value: 12.750800000000002 |
|
- type: main_score |
|
value: 74.0283 |
|
task: |
|
type: Classification |
|
- dataset: |
|
config: default |
|
name: MTEB TweetSentimentExtractionClassification (default) |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
split: test |
|
type: mteb/tweet_sentiment_extraction |
|
metrics: |
|
- type: accuracy |
|
value: 52.818299999999994 |
|
- type: f1 |
|
value: 52.8999 |
|
- type: f1_weighted |
|
value: 52.223299999999995 |
|
- type: main_score |
|
value: 52.818299999999994 |
|
task: |
|
type: Classification |
|
- dataset: |
|
config: default |
|
name: MTEB TwentyNewsgroupsClustering (default) |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
split: test |
|
type: mteb/twentynewsgroups-clustering |
|
metrics: |
|
- type: v_measure |
|
value: 14.5905 |
|
- type: v_measure_std |
|
value: 1.0532 |
|
- type: main_score |
|
value: 14.5905 |
|
task: |
|
type: Clustering |
|
- dataset: |
|
config: default |
|
name: MTEB TwitterSemEval2015 (default) |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
split: test |
|
type: mteb/twittersemeval2015-pairclassification |
|
metrics: |
|
- type: similarity_accuracy |
|
value: 80.3481 |
|
- type: similarity_accuracy_threshold |
|
value: 85.3551 |
|
- type: similarity_f1 |
|
value: 51.27850000000001 |
|
- type: similarity_f1_threshold |
|
value: 75.8966 |
|
- type: similarity_precision |
|
value: 45.8247 |
|
- type: similarity_recall |
|
value: 58.205799999999996 |
|
- type: similarity_ap |
|
value: 52.295100000000005 |
|
- type: cosine_accuracy |
|
value: 80.3481 |
|
- type: cosine_accuracy_threshold |
|
value: 85.3551 |
|
- type: cosine_f1 |
|
value: 51.27850000000001 |
|
- type: cosine_f1_threshold |
|
value: 75.8966 |
|
- type: cosine_precision |
|
value: 45.8247 |
|
- type: cosine_recall |
|
value: 58.205799999999996 |
|
- type: cosine_ap |
|
value: 52.295199999999994 |
|
- type: manhattan_accuracy |
|
value: 78.9712 |
|
- type: manhattan_accuracy_threshold |
|
value: 3046.9002 |
|
- type: manhattan_f1 |
|
value: 44.784600000000005 |
|
- type: manhattan_f1_threshold |
|
value: 4624.7635 |
|
- type: manhattan_precision |
|
value: 35.5133 |
|
- type: manhattan_recall |
|
value: 60.606899999999996 |
|
- type: manhattan_ap |
|
value: 44.4155 |
|
- type: euclidean_accuracy |
|
value: 78.9772 |
|
- type: euclidean_accuracy_threshold |
|
value: 141.3014 |
|
- type: euclidean_f1 |
|
value: 44.8638 |
|
- type: euclidean_f1_threshold |
|
value: 210.8781 |
|
- type: euclidean_precision |
|
value: 35.3191 |
|
- type: euclidean_recall |
|
value: 61.477599999999995 |
|
- type: euclidean_ap |
|
value: 44.3973 |
|
- type: dot_accuracy |
|
value: 77.4095 |
|
- type: dot_accuracy_threshold |
|
value: 3833.3893000000003 |
|
- type: dot_f1 |
|
value: 41.7116 |
|
- type: dot_f1_threshold |
|
value: 336.5812 |
|
- type: dot_precision |
|
value: 28.259600000000002 |
|
- type: dot_recall |
|
value: 79.6042 |
|
- type: dot_ap |
|
value: 30.7809 |
|
- type: max_accuracy |
|
value: 80.3481 |
|
- type: max_f1 |
|
value: 51.27850000000001 |
|
- type: max_precision |
|
value: 45.8247 |
|
- type: max_recall |
|
value: 79.6042 |
|
- type: max_ap |
|
value: 52.295199999999994 |
|
- type: main_score |
|
value: 52.295199999999994 |
|
task: |
|
type: PairClassification |
|
- dataset: |
|
config: default |
|
name: MTEB TwitterURLCorpus (default) |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
split: test |
|
type: mteb/twitterurlcorpus-pairclassification |
|
metrics: |
|
- type: similarity_accuracy |
|
value: 85.9025 |
|
- type: similarity_accuracy_threshold |
|
value: 71.6078 |
|
- type: similarity_f1 |
|
value: 70.9832 |
|
- type: similarity_f1_threshold |
|
value: 66.4079 |
|
- type: similarity_precision |
|
value: 68.9871 |
|
- type: similarity_recall |
|
value: 73.0982 |
|
- type: similarity_ap |
|
value: 79.2622 |
|
- type: cosine_accuracy |
|
value: 85.9025 |
|
- type: cosine_accuracy_threshold |
|
value: 71.6078 |
|
- type: cosine_f1 |
|
value: 70.9832 |
|
- type: cosine_f1_threshold |
|
value: 66.4079 |
|
- type: cosine_precision |
|
value: 68.9871 |
|
- type: cosine_recall |
|
value: 73.0982 |
|
- type: cosine_ap |
|
value: 79.2622 |
|
- type: manhattan_accuracy |
|
value: 81.8954 |
|
- type: manhattan_accuracy_threshold |
|
value: 2754.9084000000003 |
|
- type: manhattan_f1 |
|
value: 58.4303 |
|
- type: manhattan_f1_threshold |
|
value: 3301.9608 |
|
- type: manhattan_precision |
|
value: 56.1511 |
|
- type: manhattan_recall |
|
value: 60.9024 |
|
- type: manhattan_ap |
|
value: 66.2046 |
|
- type: euclidean_accuracy |
|
value: 81.8974 |
|
- type: euclidean_accuracy_threshold |
|
value: 122.74810000000001 |
|
- type: euclidean_f1 |
|
value: 58.455 |
|
- type: euclidean_f1_threshold |
|
value: 151.3654 |
|
- type: euclidean_precision |
|
value: 55.0722 |
|
- type: euclidean_recall |
|
value: 62.2806 |
|
- type: euclidean_ap |
|
value: 66.22019999999999 |
|
- type: dot_accuracy |
|
value: 78.7402 |
|
- type: dot_accuracy_threshold |
|
value: 317.0264 |
|
- type: dot_f1 |
|
value: 58.2905 |
|
- type: dot_f1_threshold |
|
value: 187.0591 |
|
- type: dot_precision |
|
value: 48.1454 |
|
- type: dot_recall |
|
value: 73.8528 |
|
- type: dot_ap |
|
value: 58.116 |
|
- type: max_accuracy |
|
value: 85.9025 |
|
- type: max_f1 |
|
value: 70.9832 |
|
- type: max_precision |
|
value: 68.9871 |
|
- type: max_recall |
|
value: 73.8528 |
|
- type: max_ap |
|
value: 79.2622 |
|
- type: main_score |
|
value: 79.2622 |
|
task: |
|
type: PairClassification |
|
|
|
--- |
|
# 🧚🏻♀️ brown-fairy-base-v0 Model Card |
|
|
|
<div align="center"> |
|
<img width="50%" alt="Fairy logo" src="./assets/fairy_logo.png"> |
|
</div> |
|
|
|
> [!TIP] |
|
> Fairies are among the most enchanting and magical beings in folklore and mythology. They appear across countless cultures and stories, from ancient forests to modern gardens. They are celebrated for their ability to bridge the mundane and magical realms, known for their ethereal grace and transformative powers. Fairies are tiny, higher-dimensional beings that can interact with the world in ways that are beyond our understanding. |
|
|
|
The fairy series of models are an attempt to tune the beetle series of models to be more suitable for downstream tasks. These models are meant to fully open experiments at making state-of-the-art static embeddings. |
|
|
|
The brown-fairy-base-v0 model is a distillation of the `baai/bge-base-en-v1.5` model into the `brown-beetle-base-v0` model. There was no PCA or Zipf applied to this model. |
|
|
|
## Installation |
|
|
|
Install model2vec using pip: |
|
|
|
```bash |
|
pip install model2vec |
|
``` |
|
|
|
## Usage |
|
|
|
Load this model using the `from_pretrained` method: |
|
|
|
```python |
|
from model2vec import StaticModel |
|
|
|
# Load a pretrained Model2Vec model |
|
model = StaticModel.from_pretrained("bhavnicksm/brown-fairy-base-v0") |
|
|
|
# Compute text embeddings |
|
embeddings = model.encode(["Example sentence"]) |
|
``` |
|
|
|
Read more about the Model2Vec library [here](https://github.com/MinishLab/model2vec). |
|
|
|
## Reproduce this model |
|
|
|
This model was trained on a subset of the 2 Million texts from the [FineWeb-Edu](https://huggingface.co/datasets/mixedbread-ai/fineweb-edu) dataset, which was labeled by the `baai/bge-base-en-v1.5` model. |
|
|
|
<details> |
|
<summary>Training Code</summary> |
|
|
|
Note: The datasets need to me made seperately and loaded with the `datasets` library. |
|
|
|
```python |
|
static_embedding = StaticEmbedding.from_model2vec("bhavnicksm/brown-beetle-base-v0") |
|
model = SentenceTransformer( |
|
modules=[static_embedding] |
|
) |
|
|
|
loss = MSELoss(model) |
|
|
|
run_name = "brown-fairy-base-v0" |
|
args = SentenceTransformerTrainingArguments( |
|
# Required parameter: |
|
output_dir=f"output/{run_name}", |
|
# Optional training parameters: |
|
num_train_epochs=1, |
|
per_device_train_batch_size=2048, |
|
per_device_eval_batch_size=2048, |
|
learning_rate=1e-1, |
|
warmup_ratio=0.1, |
|
fp16=False, # Set to False if you get an error that your GPU can't run on FP16 |
|
bf16=True, # Set to True if you have a GPU that supports BF16 |
|
batch_sampler=BatchSamplers.NO_DUPLICATES, |
|
# Optional tracking/debugging parameters: |
|
eval_strategy="steps", |
|
eval_steps=50, |
|
save_strategy="steps", |
|
save_steps=50, |
|
save_total_limit=5, |
|
logging_steps=50, |
|
logging_first_step=True, |
|
run_name=run_name, |
|
) |
|
|
|
evaluator = NanoBEIREvaluator() |
|
evaluator(model) |
|
|
|
trainer = SentenceTransformerTrainer( |
|
model=model, |
|
args=args, |
|
train_dataset=train_dataset, |
|
eval_dataset=eval_dataset, |
|
loss=loss, |
|
evaluator=evaluator, |
|
) |
|
trainer.train() |
|
|
|
evaluator(model) |
|
|
|
model.save_pretrained(f"output/{run_name}") |
|
``` |
|
|
|
</details> |
|
|
|
## Comparison with other models |
|
|
|
Coming soon... |
|
|
|
## Acknowledgements |
|
|
|
This model is based on the [Model2Vec](https://github.com/MinishLab/model2vec) library. Credit goes to the [Minish Lab](https://github.com/MinishLab) team for developing this library. |
|
|
|
## Citation |
|
|
|
This model builds on work done by Minish Lab. Please cite the [Model2Vec repository](https://github.com/MinishLab/model2vec) if you use this model in your work. |
|
|
|
```bibtex |
|
@software{minishlab2024model2vec, |
|
authors = {Stephan Tulkens, Thomas van Dongen}, |
|
title = {Model2Vec: Turn any Sentence Transformer into a Small Fast Model}, |
|
year = {2024}, |
|
url = {https://github.com/MinishLab/model2vec}, |
|
} |
|
``` |
|
|
