Sentence Similarity
sentence-transformers
PyTorch
Transformers
English
t5
text-embedding
embeddings
information-retrieval
beir
text-classification
language-model
text-clustering
text-semantic-similarity
text-evaluation
prompt-retrieval
text-reranking
feature-extraction
English
Sentence Similarity
natural_questions
ms_marco
fever
hotpot_qa
mteb
Eval Results
| pipeline_tag: sentence-similarity | |
| tags: | |
| - text-embedding | |
| - embeddings | |
| - information-retrieval | |
| - beir | |
| - text-classification | |
| - language-model | |
| - text-clustering | |
| - text-semantic-similarity | |
| - text-evaluation | |
| - prompt-retrieval | |
| - text-reranking | |
| - sentence-transformers | |
| - feature-extraction | |
| - sentence-similarity | |
| - transformers | |
| - t5 | |
| - English | |
| - Sentence Similarity | |
| - natural_questions | |
| - ms_marco | |
| - fever | |
| - hotpot_qa | |
| - mteb | |
| language: en | |
| inference: false | |
| license: apache-2.0 | |
| model-index: | |
| - name: final_base_results | |
| results: | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_counterfactual | |
| name: MTEB AmazonCounterfactualClassification (en) | |
| config: en | |
| split: test | |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 | |
| metrics: | |
| - type: accuracy | |
| value: 86.2089552238806 | |
| - type: ap | |
| value: 55.76273850794966 | |
| - type: f1 | |
| value: 81.26104211414781 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_polarity | |
| name: MTEB AmazonPolarityClassification | |
| config: default | |
| split: test | |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 | |
| metrics: | |
| - type: accuracy | |
| value: 88.35995000000001 | |
| - type: ap | |
| value: 84.18839957309655 | |
| - type: f1 | |
| value: 88.317619250081 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_reviews_multi | |
| name: MTEB AmazonReviewsClassification (en) | |
| config: en | |
| split: test | |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d | |
| metrics: | |
| - type: accuracy | |
| value: 44.64 | |
| - type: f1 | |
| value: 42.48663956478136 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: arguana | |
| name: MTEB ArguAna | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 27.383000000000003 | |
| - type: map_at_10 | |
| value: 43.024 | |
| - type: map_at_100 | |
| value: 44.023 | |
| - type: map_at_1000 | |
| value: 44.025999999999996 | |
| - type: map_at_3 | |
| value: 37.684 | |
| - type: map_at_5 | |
| value: 40.884 | |
| - type: mrr_at_1 | |
| value: 28.094 | |
| - type: mrr_at_10 | |
| value: 43.315 | |
| - type: mrr_at_100 | |
| value: 44.313 | |
| - type: mrr_at_1000 | |
| value: 44.317 | |
| - type: mrr_at_3 | |
| value: 37.862 | |
| - type: mrr_at_5 | |
| value: 41.155 | |
| - type: ndcg_at_1 | |
| value: 27.383000000000003 | |
| - type: ndcg_at_10 | |
| value: 52.032000000000004 | |
| - type: ndcg_at_100 | |
| value: 56.19499999999999 | |
| - type: ndcg_at_1000 | |
| value: 56.272 | |
| - type: ndcg_at_3 | |
| value: 41.166000000000004 | |
| - type: ndcg_at_5 | |
| value: 46.92 | |
| - type: precision_at_1 | |
| value: 27.383000000000003 | |
| - type: precision_at_10 | |
| value: 8.087 | |
| - type: precision_at_100 | |
| value: 0.989 | |
| - type: precision_at_1000 | |
| value: 0.099 | |
| - type: precision_at_3 | |
| value: 17.093 | |
| - type: precision_at_5 | |
| value: 13.044 | |
| - type: recall_at_1 | |
| value: 27.383000000000003 | |
| - type: recall_at_10 | |
| value: 80.868 | |
| - type: recall_at_100 | |
| value: 98.86200000000001 | |
| - type: recall_at_1000 | |
| value: 99.431 | |
| - type: recall_at_3 | |
| value: 51.28 | |
| - type: recall_at_5 | |
| value: 65.22 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/arxiv-clustering-p2p | |
| name: MTEB ArxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d | |
| metrics: | |
| - type: v_measure | |
| value: 39.68441054431849 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/arxiv-clustering-s2s | |
| name: MTEB ArxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 | |
| metrics: | |
| - type: v_measure | |
| value: 29.188539728343844 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/askubuntudupquestions-reranking | |
| name: MTEB AskUbuntuDupQuestions | |
| config: default | |
| split: test | |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 | |
| metrics: | |
| - type: map | |
| value: 63.173362687519784 | |
| - type: mrr | |
| value: 76.18860748362133 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/biosses-sts | |
| name: MTEB BIOSSES | |
| config: default | |
| split: test | |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 82.30789953771232 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/banking77 | |
| name: MTEB Banking77Classification | |
| config: default | |
| split: test | |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 | |
| metrics: | |
| - type: accuracy | |
| value: 77.03571428571428 | |
| - type: f1 | |
| value: 75.87384305045917 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/biorxiv-clustering-p2p | |
| name: MTEB BiorxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 | |
| metrics: | |
| - type: v_measure | |
| value: 32.98041170516364 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/biorxiv-clustering-s2s | |
| name: MTEB BiorxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 | |
| metrics: | |
| - type: v_measure | |
| value: 25.71652988451154 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackAndroidRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 33.739999999999995 | |
| - type: map_at_10 | |
| value: 46.197 | |
| - type: map_at_100 | |
| value: 47.814 | |
| - type: map_at_1000 | |
| value: 47.934 | |
| - type: map_at_3 | |
| value: 43.091 | |
| - type: map_at_5 | |
| value: 44.81 | |
| - type: mrr_at_1 | |
| value: 41.059 | |
| - type: mrr_at_10 | |
| value: 52.292 | |
| - type: mrr_at_100 | |
| value: 52.978 | |
| - type: mrr_at_1000 | |
| value: 53.015 | |
| - type: mrr_at_3 | |
| value: 49.976 | |
| - type: mrr_at_5 | |
| value: 51.449999999999996 | |
| - type: ndcg_at_1 | |
| value: 41.059 | |
| - type: ndcg_at_10 | |
| value: 52.608 | |
| - type: ndcg_at_100 | |
| value: 57.965 | |
| - type: ndcg_at_1000 | |
| value: 59.775999999999996 | |
| - type: ndcg_at_3 | |
| value: 48.473 | |
| - type: ndcg_at_5 | |
| value: 50.407999999999994 | |
| - type: precision_at_1 | |
| value: 41.059 | |
| - type: precision_at_10 | |
| value: 9.943 | |
| - type: precision_at_100 | |
| value: 1.6070000000000002 | |
| - type: precision_at_1000 | |
| value: 0.20500000000000002 | |
| - type: precision_at_3 | |
| value: 23.413999999999998 | |
| - type: precision_at_5 | |
| value: 16.481 | |
| - type: recall_at_1 | |
| value: 33.739999999999995 | |
| - type: recall_at_10 | |
| value: 63.888999999999996 | |
| - type: recall_at_100 | |
| value: 85.832 | |
| - type: recall_at_1000 | |
| value: 97.475 | |
| - type: recall_at_3 | |
| value: 51.953 | |
| - type: recall_at_5 | |
| value: 57.498000000000005 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackEnglishRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 31.169999999999998 | |
| - type: map_at_10 | |
| value: 41.455 | |
| - type: map_at_100 | |
| value: 42.716 | |
| - type: map_at_1000 | |
| value: 42.847 | |
| - type: map_at_3 | |
| value: 38.568999999999996 | |
| - type: map_at_5 | |
| value: 40.099000000000004 | |
| - type: mrr_at_1 | |
| value: 39.427 | |
| - type: mrr_at_10 | |
| value: 47.818 | |
| - type: mrr_at_100 | |
| value: 48.519 | |
| - type: mrr_at_1000 | |
| value: 48.558 | |
| - type: mrr_at_3 | |
| value: 45.86 | |
| - type: mrr_at_5 | |
| value: 46.936 | |
| - type: ndcg_at_1 | |
| value: 39.427 | |
| - type: ndcg_at_10 | |
| value: 47.181 | |
| - type: ndcg_at_100 | |
| value: 51.737 | |
| - type: ndcg_at_1000 | |
| value: 53.74 | |
| - type: ndcg_at_3 | |
| value: 43.261 | |
| - type: ndcg_at_5 | |
| value: 44.891 | |
| - type: precision_at_1 | |
| value: 39.427 | |
| - type: precision_at_10 | |
| value: 8.847 | |
| - type: precision_at_100 | |
| value: 1.425 | |
| - type: precision_at_1000 | |
| value: 0.189 | |
| - type: precision_at_3 | |
| value: 20.785999999999998 | |
| - type: precision_at_5 | |
| value: 14.560999999999998 | |
| - type: recall_at_1 | |
| value: 31.169999999999998 | |
| - type: recall_at_10 | |
| value: 56.971000000000004 | |
| - type: recall_at_100 | |
| value: 76.31400000000001 | |
| - type: recall_at_1000 | |
| value: 88.93900000000001 | |
| - type: recall_at_3 | |
| value: 45.208 | |
| - type: recall_at_5 | |
| value: 49.923 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackGamingRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 39.682 | |
| - type: map_at_10 | |
| value: 52.766000000000005 | |
| - type: map_at_100 | |
| value: 53.84100000000001 | |
| - type: map_at_1000 | |
| value: 53.898 | |
| - type: map_at_3 | |
| value: 49.291000000000004 | |
| - type: map_at_5 | |
| value: 51.365 | |
| - type: mrr_at_1 | |
| value: 45.266 | |
| - type: mrr_at_10 | |
| value: 56.093 | |
| - type: mrr_at_100 | |
| value: 56.763 | |
| - type: mrr_at_1000 | |
| value: 56.793000000000006 | |
| - type: mrr_at_3 | |
| value: 53.668000000000006 | |
| - type: mrr_at_5 | |
| value: 55.1 | |
| - type: ndcg_at_1 | |
| value: 45.266 | |
| - type: ndcg_at_10 | |
| value: 58.836 | |
| - type: ndcg_at_100 | |
| value: 62.863 | |
| - type: ndcg_at_1000 | |
| value: 63.912 | |
| - type: ndcg_at_3 | |
| value: 53.19199999999999 | |
| - type: ndcg_at_5 | |
| value: 56.125 | |
| - type: precision_at_1 | |
| value: 45.266 | |
| - type: precision_at_10 | |
| value: 9.492 | |
| - type: precision_at_100 | |
| value: 1.236 | |
| - type: precision_at_1000 | |
| value: 0.13699999999999998 | |
| - type: precision_at_3 | |
| value: 23.762 | |
| - type: precision_at_5 | |
| value: 16.414 | |
| - type: recall_at_1 | |
| value: 39.682 | |
| - type: recall_at_10 | |
| value: 73.233 | |
| - type: recall_at_100 | |
| value: 90.335 | |
| - type: recall_at_1000 | |
| value: 97.452 | |
| - type: recall_at_3 | |
| value: 58.562000000000005 | |
| - type: recall_at_5 | |
| value: 65.569 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackGisRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 26.743 | |
| - type: map_at_10 | |
| value: 34.016000000000005 | |
| - type: map_at_100 | |
| value: 35.028999999999996 | |
| - type: map_at_1000 | |
| value: 35.113 | |
| - type: map_at_3 | |
| value: 31.763 | |
| - type: map_at_5 | |
| value: 33.013999999999996 | |
| - type: mrr_at_1 | |
| value: 28.927000000000003 | |
| - type: mrr_at_10 | |
| value: 36.32 | |
| - type: mrr_at_100 | |
| value: 37.221 | |
| - type: mrr_at_1000 | |
| value: 37.281 | |
| - type: mrr_at_3 | |
| value: 34.105000000000004 | |
| - type: mrr_at_5 | |
| value: 35.371 | |
| - type: ndcg_at_1 | |
| value: 28.927000000000003 | |
| - type: ndcg_at_10 | |
| value: 38.474000000000004 | |
| - type: ndcg_at_100 | |
| value: 43.580000000000005 | |
| - type: ndcg_at_1000 | |
| value: 45.64 | |
| - type: ndcg_at_3 | |
| value: 34.035 | |
| - type: ndcg_at_5 | |
| value: 36.186 | |
| - type: precision_at_1 | |
| value: 28.927000000000003 | |
| - type: precision_at_10 | |
| value: 5.74 | |
| - type: precision_at_100 | |
| value: 0.8710000000000001 | |
| - type: precision_at_1000 | |
| value: 0.108 | |
| - type: precision_at_3 | |
| value: 14.124 | |
| - type: precision_at_5 | |
| value: 9.74 | |
| - type: recall_at_1 | |
| value: 26.743 | |
| - type: recall_at_10 | |
| value: 49.955 | |
| - type: recall_at_100 | |
| value: 73.904 | |
| - type: recall_at_1000 | |
| value: 89.133 | |
| - type: recall_at_3 | |
| value: 38.072 | |
| - type: recall_at_5 | |
| value: 43.266 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackMathematicaRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 16.928 | |
| - type: map_at_10 | |
| value: 23.549 | |
| - type: map_at_100 | |
| value: 24.887 | |
| - type: map_at_1000 | |
| value: 25.018 | |
| - type: map_at_3 | |
| value: 21.002000000000002 | |
| - type: map_at_5 | |
| value: 22.256 | |
| - type: mrr_at_1 | |
| value: 21.02 | |
| - type: mrr_at_10 | |
| value: 27.898 | |
| - type: mrr_at_100 | |
| value: 29.018 | |
| - type: mrr_at_1000 | |
| value: 29.099999999999998 | |
| - type: mrr_at_3 | |
| value: 25.456 | |
| - type: mrr_at_5 | |
| value: 26.625 | |
| - type: ndcg_at_1 | |
| value: 21.02 | |
| - type: ndcg_at_10 | |
| value: 28.277 | |
| - type: ndcg_at_100 | |
| value: 34.54 | |
| - type: ndcg_at_1000 | |
| value: 37.719 | |
| - type: ndcg_at_3 | |
| value: 23.707 | |
| - type: ndcg_at_5 | |
| value: 25.482 | |
| - type: precision_at_1 | |
| value: 21.02 | |
| - type: precision_at_10 | |
| value: 5.361 | |
| - type: precision_at_100 | |
| value: 0.9809999999999999 | |
| - type: precision_at_1000 | |
| value: 0.13899999999999998 | |
| - type: precision_at_3 | |
| value: 11.401 | |
| - type: precision_at_5 | |
| value: 8.209 | |
| - type: recall_at_1 | |
| value: 16.928 | |
| - type: recall_at_10 | |
| value: 38.601 | |
| - type: recall_at_100 | |
| value: 65.759 | |
| - type: recall_at_1000 | |
| value: 88.543 | |
| - type: recall_at_3 | |
| value: 25.556 | |
| - type: recall_at_5 | |
| value: 30.447000000000003 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackPhysicsRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 28.549000000000003 | |
| - type: map_at_10 | |
| value: 38.426 | |
| - type: map_at_100 | |
| value: 39.845000000000006 | |
| - type: map_at_1000 | |
| value: 39.956 | |
| - type: map_at_3 | |
| value: 35.372 | |
| - type: map_at_5 | |
| value: 37.204 | |
| - type: mrr_at_1 | |
| value: 35.034 | |
| - type: mrr_at_10 | |
| value: 44.041000000000004 | |
| - type: mrr_at_100 | |
| value: 44.95 | |
| - type: mrr_at_1000 | |
| value: 44.997 | |
| - type: mrr_at_3 | |
| value: 41.498000000000005 | |
| - type: mrr_at_5 | |
| value: 43.077 | |
| - type: ndcg_at_1 | |
| value: 35.034 | |
| - type: ndcg_at_10 | |
| value: 44.218 | |
| - type: ndcg_at_100 | |
| value: 49.958000000000006 | |
| - type: ndcg_at_1000 | |
| value: 52.019000000000005 | |
| - type: ndcg_at_3 | |
| value: 39.34 | |
| - type: ndcg_at_5 | |
| value: 41.892 | |
| - type: precision_at_1 | |
| value: 35.034 | |
| - type: precision_at_10 | |
| value: 7.911 | |
| - type: precision_at_100 | |
| value: 1.26 | |
| - type: precision_at_1000 | |
| value: 0.16 | |
| - type: precision_at_3 | |
| value: 18.511 | |
| - type: precision_at_5 | |
| value: 13.205 | |
| - type: recall_at_1 | |
| value: 28.549000000000003 | |
| - type: recall_at_10 | |
| value: 56.035999999999994 | |
| - type: recall_at_100 | |
| value: 79.701 | |
| - type: recall_at_1000 | |
| value: 93.149 | |
| - type: recall_at_3 | |
| value: 42.275 | |
| - type: recall_at_5 | |
| value: 49.097 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackProgrammersRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 29.391000000000002 | |
| - type: map_at_10 | |
| value: 39.48 | |
| - type: map_at_100 | |
| value: 40.727000000000004 | |
| - type: map_at_1000 | |
| value: 40.835 | |
| - type: map_at_3 | |
| value: 36.234 | |
| - type: map_at_5 | |
| value: 37.877 | |
| - type: mrr_at_1 | |
| value: 35.959 | |
| - type: mrr_at_10 | |
| value: 44.726 | |
| - type: mrr_at_100 | |
| value: 45.531 | |
| - type: mrr_at_1000 | |
| value: 45.582 | |
| - type: mrr_at_3 | |
| value: 42.047000000000004 | |
| - type: mrr_at_5 | |
| value: 43.611 | |
| - type: ndcg_at_1 | |
| value: 35.959 | |
| - type: ndcg_at_10 | |
| value: 45.303 | |
| - type: ndcg_at_100 | |
| value: 50.683 | |
| - type: ndcg_at_1000 | |
| value: 52.818 | |
| - type: ndcg_at_3 | |
| value: 39.987 | |
| - type: ndcg_at_5 | |
| value: 42.243 | |
| - type: precision_at_1 | |
| value: 35.959 | |
| - type: precision_at_10 | |
| value: 8.241999999999999 | |
| - type: precision_at_100 | |
| value: 1.274 | |
| - type: precision_at_1000 | |
| value: 0.163 | |
| - type: precision_at_3 | |
| value: 18.836 | |
| - type: precision_at_5 | |
| value: 13.196 | |
| - type: recall_at_1 | |
| value: 29.391000000000002 | |
| - type: recall_at_10 | |
| value: 57.364000000000004 | |
| - type: recall_at_100 | |
| value: 80.683 | |
| - type: recall_at_1000 | |
| value: 94.918 | |
| - type: recall_at_3 | |
| value: 42.263 | |
| - type: recall_at_5 | |
| value: 48.634 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 26.791749999999997 | |
| - type: map_at_10 | |
| value: 35.75541666666667 | |
| - type: map_at_100 | |
| value: 37.00791666666667 | |
| - type: map_at_1000 | |
| value: 37.12408333333333 | |
| - type: map_at_3 | |
| value: 33.02966666666667 | |
| - type: map_at_5 | |
| value: 34.56866666666667 | |
| - type: mrr_at_1 | |
| value: 31.744333333333337 | |
| - type: mrr_at_10 | |
| value: 39.9925 | |
| - type: mrr_at_100 | |
| value: 40.86458333333333 | |
| - type: mrr_at_1000 | |
| value: 40.92175000000001 | |
| - type: mrr_at_3 | |
| value: 37.68183333333334 | |
| - type: mrr_at_5 | |
| value: 39.028499999999994 | |
| - type: ndcg_at_1 | |
| value: 31.744333333333337 | |
| - type: ndcg_at_10 | |
| value: 40.95008333333334 | |
| - type: ndcg_at_100 | |
| value: 46.25966666666667 | |
| - type: ndcg_at_1000 | |
| value: 48.535333333333334 | |
| - type: ndcg_at_3 | |
| value: 36.43333333333333 | |
| - type: ndcg_at_5 | |
| value: 38.602333333333334 | |
| - type: precision_at_1 | |
| value: 31.744333333333337 | |
| - type: precision_at_10 | |
| value: 7.135166666666666 | |
| - type: precision_at_100 | |
| value: 1.1535833333333334 | |
| - type: precision_at_1000 | |
| value: 0.15391666666666665 | |
| - type: precision_at_3 | |
| value: 16.713 | |
| - type: precision_at_5 | |
| value: 11.828416666666666 | |
| - type: recall_at_1 | |
| value: 26.791749999999997 | |
| - type: recall_at_10 | |
| value: 51.98625 | |
| - type: recall_at_100 | |
| value: 75.30358333333334 | |
| - type: recall_at_1000 | |
| value: 91.05433333333333 | |
| - type: recall_at_3 | |
| value: 39.39583333333333 | |
| - type: recall_at_5 | |
| value: 45.05925 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackStatsRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 22.219 | |
| - type: map_at_10 | |
| value: 29.162 | |
| - type: map_at_100 | |
| value: 30.049999999999997 | |
| - type: map_at_1000 | |
| value: 30.144 | |
| - type: map_at_3 | |
| value: 27.204 | |
| - type: map_at_5 | |
| value: 28.351 | |
| - type: mrr_at_1 | |
| value: 25.153 | |
| - type: mrr_at_10 | |
| value: 31.814999999999998 | |
| - type: mrr_at_100 | |
| value: 32.573 | |
| - type: mrr_at_1000 | |
| value: 32.645 | |
| - type: mrr_at_3 | |
| value: 29.934 | |
| - type: mrr_at_5 | |
| value: 30.946 | |
| - type: ndcg_at_1 | |
| value: 25.153 | |
| - type: ndcg_at_10 | |
| value: 33.099000000000004 | |
| - type: ndcg_at_100 | |
| value: 37.768 | |
| - type: ndcg_at_1000 | |
| value: 40.331 | |
| - type: ndcg_at_3 | |
| value: 29.473 | |
| - type: ndcg_at_5 | |
| value: 31.206 | |
| - type: precision_at_1 | |
| value: 25.153 | |
| - type: precision_at_10 | |
| value: 5.183999999999999 | |
| - type: precision_at_100 | |
| value: 0.8170000000000001 | |
| - type: precision_at_1000 | |
| value: 0.11100000000000002 | |
| - type: precision_at_3 | |
| value: 12.831999999999999 | |
| - type: precision_at_5 | |
| value: 8.895999999999999 | |
| - type: recall_at_1 | |
| value: 22.219 | |
| - type: recall_at_10 | |
| value: 42.637 | |
| - type: recall_at_100 | |
| value: 64.704 | |
| - type: recall_at_1000 | |
| value: 83.963 | |
| - type: recall_at_3 | |
| value: 32.444 | |
| - type: recall_at_5 | |
| value: 36.802 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackTexRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 17.427999999999997 | |
| - type: map_at_10 | |
| value: 24.029 | |
| - type: map_at_100 | |
| value: 25.119999999999997 | |
| - type: map_at_1000 | |
| value: 25.257 | |
| - type: map_at_3 | |
| value: 22.016 | |
| - type: map_at_5 | |
| value: 23.143 | |
| - type: mrr_at_1 | |
| value: 21.129 | |
| - type: mrr_at_10 | |
| value: 27.750000000000004 | |
| - type: mrr_at_100 | |
| value: 28.666999999999998 | |
| - type: mrr_at_1000 | |
| value: 28.754999999999995 | |
| - type: mrr_at_3 | |
| value: 25.849 | |
| - type: mrr_at_5 | |
| value: 26.939999999999998 | |
| - type: ndcg_at_1 | |
| value: 21.129 | |
| - type: ndcg_at_10 | |
| value: 28.203 | |
| - type: ndcg_at_100 | |
| value: 33.44 | |
| - type: ndcg_at_1000 | |
| value: 36.61 | |
| - type: ndcg_at_3 | |
| value: 24.648999999999997 | |
| - type: ndcg_at_5 | |
| value: 26.316 | |
| - type: precision_at_1 | |
| value: 21.129 | |
| - type: precision_at_10 | |
| value: 5.055 | |
| - type: precision_at_100 | |
| value: 0.909 | |
| - type: precision_at_1000 | |
| value: 0.13699999999999998 | |
| - type: precision_at_3 | |
| value: 11.666 | |
| - type: precision_at_5 | |
| value: 8.3 | |
| - type: recall_at_1 | |
| value: 17.427999999999997 | |
| - type: recall_at_10 | |
| value: 36.923 | |
| - type: recall_at_100 | |
| value: 60.606 | |
| - type: recall_at_1000 | |
| value: 83.19 | |
| - type: recall_at_3 | |
| value: 26.845000000000002 | |
| - type: recall_at_5 | |
| value: 31.247000000000003 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackUnixRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 26.457000000000004 | |
| - type: map_at_10 | |
| value: 35.228 | |
| - type: map_at_100 | |
| value: 36.475 | |
| - type: map_at_1000 | |
| value: 36.585 | |
| - type: map_at_3 | |
| value: 32.444 | |
| - type: map_at_5 | |
| value: 34.046 | |
| - type: mrr_at_1 | |
| value: 30.784 | |
| - type: mrr_at_10 | |
| value: 39.133 | |
| - type: mrr_at_100 | |
| value: 40.11 | |
| - type: mrr_at_1000 | |
| value: 40.169 | |
| - type: mrr_at_3 | |
| value: 36.692 | |
| - type: mrr_at_5 | |
| value: 38.17 | |
| - type: ndcg_at_1 | |
| value: 30.784 | |
| - type: ndcg_at_10 | |
| value: 40.358 | |
| - type: ndcg_at_100 | |
| value: 46.119 | |
| - type: ndcg_at_1000 | |
| value: 48.428 | |
| - type: ndcg_at_3 | |
| value: 35.504000000000005 | |
| - type: ndcg_at_5 | |
| value: 37.864 | |
| - type: precision_at_1 | |
| value: 30.784 | |
| - type: precision_at_10 | |
| value: 6.800000000000001 | |
| - type: precision_at_100 | |
| value: 1.083 | |
| - type: precision_at_1000 | |
| value: 0.13899999999999998 | |
| - type: precision_at_3 | |
| value: 15.920000000000002 | |
| - type: precision_at_5 | |
| value: 11.437 | |
| - type: recall_at_1 | |
| value: 26.457000000000004 | |
| - type: recall_at_10 | |
| value: 51.845 | |
| - type: recall_at_100 | |
| value: 77.046 | |
| - type: recall_at_1000 | |
| value: 92.892 | |
| - type: recall_at_3 | |
| value: 38.89 | |
| - type: recall_at_5 | |
| value: 44.688 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackWebmastersRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 29.378999999999998 | |
| - type: map_at_10 | |
| value: 37.373 | |
| - type: map_at_100 | |
| value: 39.107 | |
| - type: map_at_1000 | |
| value: 39.317 | |
| - type: map_at_3 | |
| value: 34.563 | |
| - type: map_at_5 | |
| value: 36.173 | |
| - type: mrr_at_1 | |
| value: 35.178 | |
| - type: mrr_at_10 | |
| value: 42.44 | |
| - type: mrr_at_100 | |
| value: 43.434 | |
| - type: mrr_at_1000 | |
| value: 43.482 | |
| - type: mrr_at_3 | |
| value: 39.987 | |
| - type: mrr_at_5 | |
| value: 41.370000000000005 | |
| - type: ndcg_at_1 | |
| value: 35.178 | |
| - type: ndcg_at_10 | |
| value: 42.82 | |
| - type: ndcg_at_100 | |
| value: 48.935 | |
| - type: ndcg_at_1000 | |
| value: 51.28 | |
| - type: ndcg_at_3 | |
| value: 38.562999999999995 | |
| - type: ndcg_at_5 | |
| value: 40.687 | |
| - type: precision_at_1 | |
| value: 35.178 | |
| - type: precision_at_10 | |
| value: 7.945 | |
| - type: precision_at_100 | |
| value: 1.524 | |
| - type: precision_at_1000 | |
| value: 0.242 | |
| - type: precision_at_3 | |
| value: 17.721 | |
| - type: precision_at_5 | |
| value: 12.925 | |
| - type: recall_at_1 | |
| value: 29.378999999999998 | |
| - type: recall_at_10 | |
| value: 52.141999999999996 | |
| - type: recall_at_100 | |
| value: 79.49000000000001 | |
| - type: recall_at_1000 | |
| value: 93.782 | |
| - type: recall_at_3 | |
| value: 39.579 | |
| - type: recall_at_5 | |
| value: 45.462 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackWordpressRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 19.814999999999998 | |
| - type: map_at_10 | |
| value: 27.383999999999997 | |
| - type: map_at_100 | |
| value: 28.483999999999998 | |
| - type: map_at_1000 | |
| value: 28.585 | |
| - type: map_at_3 | |
| value: 24.807000000000002 | |
| - type: map_at_5 | |
| value: 26.485999999999997 | |
| - type: mrr_at_1 | |
| value: 21.996 | |
| - type: mrr_at_10 | |
| value: 29.584 | |
| - type: mrr_at_100 | |
| value: 30.611 | |
| - type: mrr_at_1000 | |
| value: 30.684 | |
| - type: mrr_at_3 | |
| value: 27.11 | |
| - type: mrr_at_5 | |
| value: 28.746 | |
| - type: ndcg_at_1 | |
| value: 21.996 | |
| - type: ndcg_at_10 | |
| value: 32.024 | |
| - type: ndcg_at_100 | |
| value: 37.528 | |
| - type: ndcg_at_1000 | |
| value: 40.150999999999996 | |
| - type: ndcg_at_3 | |
| value: 27.016000000000002 | |
| - type: ndcg_at_5 | |
| value: 29.927999999999997 | |
| - type: precision_at_1 | |
| value: 21.996 | |
| - type: precision_at_10 | |
| value: 5.102 | |
| - type: precision_at_100 | |
| value: 0.856 | |
| - type: precision_at_1000 | |
| value: 0.117 | |
| - type: precision_at_3 | |
| value: 11.583 | |
| - type: precision_at_5 | |
| value: 8.577 | |
| - type: recall_at_1 | |
| value: 19.814999999999998 | |
| - type: recall_at_10 | |
| value: 44.239 | |
| - type: recall_at_100 | |
| value: 69.269 | |
| - type: recall_at_1000 | |
| value: 89.216 | |
| - type: recall_at_3 | |
| value: 31.102999999999998 | |
| - type: recall_at_5 | |
| value: 38.078 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: climate-fever | |
| name: MTEB ClimateFEVER | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 11.349 | |
| - type: map_at_10 | |
| value: 19.436 | |
| - type: map_at_100 | |
| value: 21.282999999999998 | |
| - type: map_at_1000 | |
| value: 21.479 | |
| - type: map_at_3 | |
| value: 15.841 | |
| - type: map_at_5 | |
| value: 17.558 | |
| - type: mrr_at_1 | |
| value: 25.863000000000003 | |
| - type: mrr_at_10 | |
| value: 37.218 | |
| - type: mrr_at_100 | |
| value: 38.198 | |
| - type: mrr_at_1000 | |
| value: 38.236 | |
| - type: mrr_at_3 | |
| value: 33.409 | |
| - type: mrr_at_5 | |
| value: 35.602000000000004 | |
| - type: ndcg_at_1 | |
| value: 25.863000000000003 | |
| - type: ndcg_at_10 | |
| value: 27.953 | |
| - type: ndcg_at_100 | |
| value: 35.327 | |
| - type: ndcg_at_1000 | |
| value: 38.708999999999996 | |
| - type: ndcg_at_3 | |
| value: 21.985 | |
| - type: ndcg_at_5 | |
| value: 23.957 | |
| - type: precision_at_1 | |
| value: 25.863000000000003 | |
| - type: precision_at_10 | |
| value: 8.99 | |
| - type: precision_at_100 | |
| value: 1.6889999999999998 | |
| - type: precision_at_1000 | |
| value: 0.232 | |
| - type: precision_at_3 | |
| value: 16.308 | |
| - type: precision_at_5 | |
| value: 12.912 | |
| - type: recall_at_1 | |
| value: 11.349 | |
| - type: recall_at_10 | |
| value: 34.581 | |
| - type: recall_at_100 | |
| value: 60.178 | |
| - type: recall_at_1000 | |
| value: 78.88199999999999 | |
| - type: recall_at_3 | |
| value: 20.041999999999998 | |
| - type: recall_at_5 | |
| value: 25.458 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: dbpedia-entity | |
| name: MTEB DBPedia | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 7.893 | |
| - type: map_at_10 | |
| value: 15.457 | |
| - type: map_at_100 | |
| value: 20.905 | |
| - type: map_at_1000 | |
| value: 22.116 | |
| - type: map_at_3 | |
| value: 11.593 | |
| - type: map_at_5 | |
| value: 13.134 | |
| - type: mrr_at_1 | |
| value: 57.49999999999999 | |
| - type: mrr_at_10 | |
| value: 65.467 | |
| - type: mrr_at_100 | |
| value: 66.022 | |
| - type: mrr_at_1000 | |
| value: 66.039 | |
| - type: mrr_at_3 | |
| value: 63.458000000000006 | |
| - type: mrr_at_5 | |
| value: 64.546 | |
| - type: ndcg_at_1 | |
| value: 45.875 | |
| - type: ndcg_at_10 | |
| value: 33.344 | |
| - type: ndcg_at_100 | |
| value: 36.849 | |
| - type: ndcg_at_1000 | |
| value: 44.03 | |
| - type: ndcg_at_3 | |
| value: 37.504 | |
| - type: ndcg_at_5 | |
| value: 34.892 | |
| - type: precision_at_1 | |
| value: 57.49999999999999 | |
| - type: precision_at_10 | |
| value: 25.95 | |
| - type: precision_at_100 | |
| value: 7.89 | |
| - type: precision_at_1000 | |
| value: 1.669 | |
| - type: precision_at_3 | |
| value: 40.333000000000006 | |
| - type: precision_at_5 | |
| value: 33.050000000000004 | |
| - type: recall_at_1 | |
| value: 7.893 | |
| - type: recall_at_10 | |
| value: 20.724999999999998 | |
| - type: recall_at_100 | |
| value: 42.516 | |
| - type: recall_at_1000 | |
| value: 65.822 | |
| - type: recall_at_3 | |
| value: 12.615000000000002 | |
| - type: recall_at_5 | |
| value: 15.482000000000001 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/emotion | |
| name: MTEB EmotionClassification | |
| config: default | |
| split: test | |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 | |
| metrics: | |
| - type: accuracy | |
| value: 51.760000000000005 | |
| - type: f1 | |
| value: 45.51690565701713 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: fever | |
| name: MTEB FEVER | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 53.882 | |
| - type: map_at_10 | |
| value: 65.902 | |
| - type: map_at_100 | |
| value: 66.33 | |
| - type: map_at_1000 | |
| value: 66.348 | |
| - type: map_at_3 | |
| value: 63.75999999999999 | |
| - type: map_at_5 | |
| value: 65.181 | |
| - type: mrr_at_1 | |
| value: 58.041 | |
| - type: mrr_at_10 | |
| value: 70.133 | |
| - type: mrr_at_100 | |
| value: 70.463 | |
| - type: mrr_at_1000 | |
| value: 70.47 | |
| - type: mrr_at_3 | |
| value: 68.164 | |
| - type: mrr_at_5 | |
| value: 69.465 | |
| - type: ndcg_at_1 | |
| value: 58.041 | |
| - type: ndcg_at_10 | |
| value: 71.84700000000001 | |
| - type: ndcg_at_100 | |
| value: 73.699 | |
| - type: ndcg_at_1000 | |
| value: 74.06700000000001 | |
| - type: ndcg_at_3 | |
| value: 67.855 | |
| - type: ndcg_at_5 | |
| value: 70.203 | |
| - type: precision_at_1 | |
| value: 58.041 | |
| - type: precision_at_10 | |
| value: 9.427000000000001 | |
| - type: precision_at_100 | |
| value: 1.049 | |
| - type: precision_at_1000 | |
| value: 0.11 | |
| - type: precision_at_3 | |
| value: 27.278000000000002 | |
| - type: precision_at_5 | |
| value: 17.693 | |
| - type: recall_at_1 | |
| value: 53.882 | |
| - type: recall_at_10 | |
| value: 85.99 | |
| - type: recall_at_100 | |
| value: 94.09100000000001 | |
| - type: recall_at_1000 | |
| value: 96.612 | |
| - type: recall_at_3 | |
| value: 75.25 | |
| - type: recall_at_5 | |
| value: 80.997 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: fiqa | |
| name: MTEB FiQA2018 | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 19.165 | |
| - type: map_at_10 | |
| value: 31.845000000000002 | |
| - type: map_at_100 | |
| value: 33.678999999999995 | |
| - type: map_at_1000 | |
| value: 33.878 | |
| - type: map_at_3 | |
| value: 27.881 | |
| - type: map_at_5 | |
| value: 30.049999999999997 | |
| - type: mrr_at_1 | |
| value: 38.272 | |
| - type: mrr_at_10 | |
| value: 47.04 | |
| - type: mrr_at_100 | |
| value: 47.923 | |
| - type: mrr_at_1000 | |
| value: 47.973 | |
| - type: mrr_at_3 | |
| value: 44.985 | |
| - type: mrr_at_5 | |
| value: 46.150000000000006 | |
| - type: ndcg_at_1 | |
| value: 38.272 | |
| - type: ndcg_at_10 | |
| value: 39.177 | |
| - type: ndcg_at_100 | |
| value: 45.995000000000005 | |
| - type: ndcg_at_1000 | |
| value: 49.312 | |
| - type: ndcg_at_3 | |
| value: 36.135 | |
| - type: ndcg_at_5 | |
| value: 36.936 | |
| - type: precision_at_1 | |
| value: 38.272 | |
| - type: precision_at_10 | |
| value: 10.926 | |
| - type: precision_at_100 | |
| value: 1.809 | |
| - type: precision_at_1000 | |
| value: 0.23700000000000002 | |
| - type: precision_at_3 | |
| value: 24.331 | |
| - type: precision_at_5 | |
| value: 17.747 | |
| - type: recall_at_1 | |
| value: 19.165 | |
| - type: recall_at_10 | |
| value: 45.103 | |
| - type: recall_at_100 | |
| value: 70.295 | |
| - type: recall_at_1000 | |
| value: 90.592 | |
| - type: recall_at_3 | |
| value: 32.832 | |
| - type: recall_at_5 | |
| value: 37.905 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: hotpotqa | |
| name: MTEB HotpotQA | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 32.397 | |
| - type: map_at_10 | |
| value: 44.83 | |
| - type: map_at_100 | |
| value: 45.716 | |
| - type: map_at_1000 | |
| value: 45.797 | |
| - type: map_at_3 | |
| value: 41.955999999999996 | |
| - type: map_at_5 | |
| value: 43.736999999999995 | |
| - type: mrr_at_1 | |
| value: 64.794 | |
| - type: mrr_at_10 | |
| value: 71.866 | |
| - type: mrr_at_100 | |
| value: 72.22 | |
| - type: mrr_at_1000 | |
| value: 72.238 | |
| - type: mrr_at_3 | |
| value: 70.416 | |
| - type: mrr_at_5 | |
| value: 71.304 | |
| - type: ndcg_at_1 | |
| value: 64.794 | |
| - type: ndcg_at_10 | |
| value: 54.186 | |
| - type: ndcg_at_100 | |
| value: 57.623000000000005 | |
| - type: ndcg_at_1000 | |
| value: 59.302 | |
| - type: ndcg_at_3 | |
| value: 49.703 | |
| - type: ndcg_at_5 | |
| value: 52.154999999999994 | |
| - type: precision_at_1 | |
| value: 64.794 | |
| - type: precision_at_10 | |
| value: 11.219 | |
| - type: precision_at_100 | |
| value: 1.394 | |
| - type: precision_at_1000 | |
| value: 0.16199999999999998 | |
| - type: precision_at_3 | |
| value: 30.767 | |
| - type: precision_at_5 | |
| value: 20.397000000000002 | |
| - type: recall_at_1 | |
| value: 32.397 | |
| - type: recall_at_10 | |
| value: 56.096999999999994 | |
| - type: recall_at_100 | |
| value: 69.696 | |
| - type: recall_at_1000 | |
| value: 80.88499999999999 | |
| - type: recall_at_3 | |
| value: 46.150999999999996 | |
| - type: recall_at_5 | |
| value: 50.993 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/imdb | |
| name: MTEB ImdbClassification | |
| config: default | |
| split: test | |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 | |
| metrics: | |
| - type: accuracy | |
| value: 81.1744 | |
| - type: ap | |
| value: 75.44973697032414 | |
| - type: f1 | |
| value: 81.09901117955782 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: msmarco | |
| name: MTEB MSMARCO | |
| config: default | |
| split: dev | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 19.519000000000002 | |
| - type: map_at_10 | |
| value: 31.025000000000002 | |
| - type: map_at_100 | |
| value: 32.275999999999996 | |
| - type: map_at_1000 | |
| value: 32.329 | |
| - type: map_at_3 | |
| value: 27.132 | |
| - type: map_at_5 | |
| value: 29.415999999999997 | |
| - type: mrr_at_1 | |
| value: 20.115 | |
| - type: mrr_at_10 | |
| value: 31.569000000000003 | |
| - type: mrr_at_100 | |
| value: 32.768 | |
| - type: mrr_at_1000 | |
| value: 32.816 | |
| - type: mrr_at_3 | |
| value: 27.748 | |
| - type: mrr_at_5 | |
| value: 29.956 | |
| - type: ndcg_at_1 | |
| value: 20.115 | |
| - type: ndcg_at_10 | |
| value: 37.756 | |
| - type: ndcg_at_100 | |
| value: 43.858000000000004 | |
| - type: ndcg_at_1000 | |
| value: 45.199 | |
| - type: ndcg_at_3 | |
| value: 29.818 | |
| - type: ndcg_at_5 | |
| value: 33.875 | |
| - type: precision_at_1 | |
| value: 20.115 | |
| - type: precision_at_10 | |
| value: 6.122 | |
| - type: precision_at_100 | |
| value: 0.919 | |
| - type: precision_at_1000 | |
| value: 0.10300000000000001 | |
| - type: precision_at_3 | |
| value: 12.794 | |
| - type: precision_at_5 | |
| value: 9.731 | |
| - type: recall_at_1 | |
| value: 19.519000000000002 | |
| - type: recall_at_10 | |
| value: 58.62500000000001 | |
| - type: recall_at_100 | |
| value: 86.99 | |
| - type: recall_at_1000 | |
| value: 97.268 | |
| - type: recall_at_3 | |
| value: 37.002 | |
| - type: recall_at_5 | |
| value: 46.778 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/mtop_domain | |
| name: MTEB MTOPDomainClassification (en) | |
| config: en | |
| split: test | |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf | |
| metrics: | |
| - type: accuracy | |
| value: 93.71865025079799 | |
| - type: f1 | |
| value: 93.38906173610519 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/mtop_intent | |
| name: MTEB MTOPIntentClassification (en) | |
| config: en | |
| split: test | |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba | |
| metrics: | |
| - type: accuracy | |
| value: 70.2576379388965 | |
| - type: f1 | |
| value: 49.20405830249464 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_massive_intent | |
| name: MTEB MassiveIntentClassification (en) | |
| config: en | |
| split: test | |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 | |
| metrics: | |
| - type: accuracy | |
| value: 67.48486886348351 | |
| - type: f1 | |
| value: 64.92199176095157 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_massive_scenario | |
| name: MTEB MassiveScenarioClassification (en) | |
| config: en | |
| split: test | |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 | |
| metrics: | |
| - type: accuracy | |
| value: 72.59246805648958 | |
| - type: f1 | |
| value: 72.1222026389164 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/medrxiv-clustering-p2p | |
| name: MTEB MedrxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 | |
| metrics: | |
| - type: v_measure | |
| value: 30.887642595096825 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/medrxiv-clustering-s2s | |
| name: MTEB MedrxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 | |
| metrics: | |
| - type: v_measure | |
| value: 28.3764418784054 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/mind_small | |
| name: MTEB MindSmallReranking | |
| config: default | |
| split: test | |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 | |
| metrics: | |
| - type: map | |
| value: 31.81544126336991 | |
| - type: mrr | |
| value: 32.82666576268031 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: nfcorpus | |
| name: MTEB NFCorpus | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 5.185 | |
| - type: map_at_10 | |
| value: 11.158 | |
| - type: map_at_100 | |
| value: 14.041 | |
| - type: map_at_1000 | |
| value: 15.360999999999999 | |
| - type: map_at_3 | |
| value: 8.417 | |
| - type: map_at_5 | |
| value: 9.378 | |
| - type: mrr_at_1 | |
| value: 44.582 | |
| - type: mrr_at_10 | |
| value: 53.083999999999996 | |
| - type: mrr_at_100 | |
| value: 53.787 | |
| - type: mrr_at_1000 | |
| value: 53.824000000000005 | |
| - type: mrr_at_3 | |
| value: 51.187000000000005 | |
| - type: mrr_at_5 | |
| value: 52.379 | |
| - type: ndcg_at_1 | |
| value: 42.57 | |
| - type: ndcg_at_10 | |
| value: 31.593 | |
| - type: ndcg_at_100 | |
| value: 29.093999999999998 | |
| - type: ndcg_at_1000 | |
| value: 37.909 | |
| - type: ndcg_at_3 | |
| value: 37.083 | |
| - type: ndcg_at_5 | |
| value: 34.397 | |
| - type: precision_at_1 | |
| value: 43.963 | |
| - type: precision_at_10 | |
| value: 23.498 | |
| - type: precision_at_100 | |
| value: 7.6160000000000005 | |
| - type: precision_at_1000 | |
| value: 2.032 | |
| - type: precision_at_3 | |
| value: 34.572 | |
| - type: precision_at_5 | |
| value: 29.412 | |
| - type: recall_at_1 | |
| value: 5.185 | |
| - type: recall_at_10 | |
| value: 15.234 | |
| - type: recall_at_100 | |
| value: 29.49 | |
| - type: recall_at_1000 | |
| value: 62.273999999999994 | |
| - type: recall_at_3 | |
| value: 9.55 | |
| - type: recall_at_5 | |
| value: 11.103 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: nq | |
| name: MTEB NQ | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 23.803 | |
| - type: map_at_10 | |
| value: 38.183 | |
| - type: map_at_100 | |
| value: 39.421 | |
| - type: map_at_1000 | |
| value: 39.464 | |
| - type: map_at_3 | |
| value: 33.835 | |
| - type: map_at_5 | |
| value: 36.327 | |
| - type: mrr_at_1 | |
| value: 26.68 | |
| - type: mrr_at_10 | |
| value: 40.439 | |
| - type: mrr_at_100 | |
| value: 41.415 | |
| - type: mrr_at_1000 | |
| value: 41.443999999999996 | |
| - type: mrr_at_3 | |
| value: 36.612 | |
| - type: mrr_at_5 | |
| value: 38.877 | |
| - type: ndcg_at_1 | |
| value: 26.68 | |
| - type: ndcg_at_10 | |
| value: 45.882 | |
| - type: ndcg_at_100 | |
| value: 51.227999999999994 | |
| - type: ndcg_at_1000 | |
| value: 52.207 | |
| - type: ndcg_at_3 | |
| value: 37.511 | |
| - type: ndcg_at_5 | |
| value: 41.749 | |
| - type: precision_at_1 | |
| value: 26.68 | |
| - type: precision_at_10 | |
| value: 7.9750000000000005 | |
| - type: precision_at_100 | |
| value: 1.0959999999999999 | |
| - type: precision_at_1000 | |
| value: 0.11900000000000001 | |
| - type: precision_at_3 | |
| value: 17.449 | |
| - type: precision_at_5 | |
| value: 12.897 | |
| - type: recall_at_1 | |
| value: 23.803 | |
| - type: recall_at_10 | |
| value: 67.152 | |
| - type: recall_at_100 | |
| value: 90.522 | |
| - type: recall_at_1000 | |
| value: 97.743 | |
| - type: recall_at_3 | |
| value: 45.338 | |
| - type: recall_at_5 | |
| value: 55.106 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: quora | |
| name: MTEB QuoraRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 70.473 | |
| - type: map_at_10 | |
| value: 84.452 | |
| - type: map_at_100 | |
| value: 85.101 | |
| - type: map_at_1000 | |
| value: 85.115 | |
| - type: map_at_3 | |
| value: 81.435 | |
| - type: map_at_5 | |
| value: 83.338 | |
| - type: mrr_at_1 | |
| value: 81.19 | |
| - type: mrr_at_10 | |
| value: 87.324 | |
| - type: mrr_at_100 | |
| value: 87.434 | |
| - type: mrr_at_1000 | |
| value: 87.435 | |
| - type: mrr_at_3 | |
| value: 86.31 | |
| - type: mrr_at_5 | |
| value: 87.002 | |
| - type: ndcg_at_1 | |
| value: 81.21000000000001 | |
| - type: ndcg_at_10 | |
| value: 88.19 | |
| - type: ndcg_at_100 | |
| value: 89.44 | |
| - type: ndcg_at_1000 | |
| value: 89.526 | |
| - type: ndcg_at_3 | |
| value: 85.237 | |
| - type: ndcg_at_5 | |
| value: 86.892 | |
| - type: precision_at_1 | |
| value: 81.21000000000001 | |
| - type: precision_at_10 | |
| value: 13.417000000000002 | |
| - type: precision_at_100 | |
| value: 1.537 | |
| - type: precision_at_1000 | |
| value: 0.157 | |
| - type: precision_at_3 | |
| value: 37.31 | |
| - type: precision_at_5 | |
| value: 24.59 | |
| - type: recall_at_1 | |
| value: 70.473 | |
| - type: recall_at_10 | |
| value: 95.367 | |
| - type: recall_at_100 | |
| value: 99.616 | |
| - type: recall_at_1000 | |
| value: 99.996 | |
| - type: recall_at_3 | |
| value: 86.936 | |
| - type: recall_at_5 | |
| value: 91.557 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/reddit-clustering | |
| name: MTEB RedditClustering | |
| config: default | |
| split: test | |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb | |
| metrics: | |
| - type: v_measure | |
| value: 59.25776525253911 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/reddit-clustering-p2p | |
| name: MTEB RedditClusteringP2P | |
| config: default | |
| split: test | |
| revision: 282350215ef01743dc01b456c7f5241fa8937f16 | |
| metrics: | |
| - type: v_measure | |
| value: 63.22135271663078 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: scidocs | |
| name: MTEB SCIDOCS | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 4.003 | |
| - type: map_at_10 | |
| value: 10.062999999999999 | |
| - type: map_at_100 | |
| value: 11.854000000000001 | |
| - type: map_at_1000 | |
| value: 12.145999999999999 | |
| - type: map_at_3 | |
| value: 7.242 | |
| - type: map_at_5 | |
| value: 8.652999999999999 | |
| - type: mrr_at_1 | |
| value: 19.7 | |
| - type: mrr_at_10 | |
| value: 29.721999999999998 | |
| - type: mrr_at_100 | |
| value: 30.867 | |
| - type: mrr_at_1000 | |
| value: 30.944 | |
| - type: mrr_at_3 | |
| value: 26.683 | |
| - type: mrr_at_5 | |
| value: 28.498 | |
| - type: ndcg_at_1 | |
| value: 19.7 | |
| - type: ndcg_at_10 | |
| value: 17.095 | |
| - type: ndcg_at_100 | |
| value: 24.375 | |
| - type: ndcg_at_1000 | |
| value: 29.831000000000003 | |
| - type: ndcg_at_3 | |
| value: 16.305 | |
| - type: ndcg_at_5 | |
| value: 14.291 | |
| - type: precision_at_1 | |
| value: 19.7 | |
| - type: precision_at_10 | |
| value: 8.799999999999999 | |
| - type: precision_at_100 | |
| value: 1.9349999999999998 | |
| - type: precision_at_1000 | |
| value: 0.32399999999999995 | |
| - type: precision_at_3 | |
| value: 15.2 | |
| - type: precision_at_5 | |
| value: 12.540000000000001 | |
| - type: recall_at_1 | |
| value: 4.003 | |
| - type: recall_at_10 | |
| value: 17.877000000000002 | |
| - type: recall_at_100 | |
| value: 39.217 | |
| - type: recall_at_1000 | |
| value: 65.862 | |
| - type: recall_at_3 | |
| value: 9.242 | |
| - type: recall_at_5 | |
| value: 12.715000000000002 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sickr-sts | |
| name: MTEB SICK-R | |
| config: default | |
| split: test | |
| revision: a6ea5a8cab320b040a23452cc28066d9beae2cee | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 80.25888668589654 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts12-sts | |
| name: MTEB STS12 | |
| config: default | |
| split: test | |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 77.02037527837669 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts13-sts | |
| name: MTEB STS13 | |
| config: default | |
| split: test | |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 86.58432681008449 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts14-sts | |
| name: MTEB STS14 | |
| config: default | |
| split: test | |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 81.31697756099051 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts15-sts | |
| name: MTEB STS15 | |
| config: default | |
| split: test | |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 88.18867599667057 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts16-sts | |
| name: MTEB STS16 | |
| config: default | |
| split: test | |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 84.87853941747623 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts17-crosslingual-sts | |
| name: MTEB STS17 (en-en) | |
| config: en-en | |
| split: test | |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 89.46479925383916 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts22-crosslingual-sts | |
| name: MTEB STS22 (en) | |
| config: en | |
| split: test | |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 66.45272113649146 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/stsbenchmark-sts | |
| name: MTEB STSBenchmark | |
| config: default | |
| split: test | |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 86.43357313527851 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/scidocs-reranking | |
| name: MTEB SciDocsRR | |
| config: default | |
| split: test | |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab | |
| metrics: | |
| - type: map | |
| value: 78.82761687254882 | |
| - type: mrr | |
| value: 93.46223674655047 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: scifact | |
| name: MTEB SciFact | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 44.583 | |
| - type: map_at_10 | |
| value: 52.978 | |
| - type: map_at_100 | |
| value: 53.803 | |
| - type: map_at_1000 | |
| value: 53.839999999999996 | |
| - type: map_at_3 | |
| value: 50.03300000000001 | |
| - type: map_at_5 | |
| value: 51.939 | |
| - type: mrr_at_1 | |
| value: 47.0 | |
| - type: mrr_at_10 | |
| value: 54.730000000000004 | |
| - type: mrr_at_100 | |
| value: 55.31399999999999 | |
| - type: mrr_at_1000 | |
| value: 55.346 | |
| - type: mrr_at_3 | |
| value: 52.0 | |
| - type: mrr_at_5 | |
| value: 53.783 | |
| - type: ndcg_at_1 | |
| value: 47.0 | |
| - type: ndcg_at_10 | |
| value: 57.82899999999999 | |
| - type: ndcg_at_100 | |
| value: 61.49400000000001 | |
| - type: ndcg_at_1000 | |
| value: 62.676 | |
| - type: ndcg_at_3 | |
| value: 52.373000000000005 | |
| - type: ndcg_at_5 | |
| value: 55.481 | |
| - type: precision_at_1 | |
| value: 47.0 | |
| - type: precision_at_10 | |
| value: 7.867 | |
| - type: precision_at_100 | |
| value: 0.997 | |
| - type: precision_at_1000 | |
| value: 0.11 | |
| - type: precision_at_3 | |
| value: 20.556 | |
| - type: precision_at_5 | |
| value: 14.066999999999998 | |
| - type: recall_at_1 | |
| value: 44.583 | |
| - type: recall_at_10 | |
| value: 71.172 | |
| - type: recall_at_100 | |
| value: 87.7 | |
| - type: recall_at_1000 | |
| value: 97.333 | |
| - type: recall_at_3 | |
| value: 56.511 | |
| - type: recall_at_5 | |
| value: 64.206 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/sprintduplicatequestions-pairclassification | |
| name: MTEB SprintDuplicateQuestions | |
| config: default | |
| split: test | |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 99.66237623762376 | |
| - type: cos_sim_ap | |
| value: 90.35465126226322 | |
| - type: cos_sim_f1 | |
| value: 82.44575936883628 | |
| - type: cos_sim_precision | |
| value: 81.32295719844358 | |
| - type: cos_sim_recall | |
| value: 83.6 | |
| - type: dot_accuracy | |
| value: 99.66237623762376 | |
| - type: dot_ap | |
| value: 90.35464287920453 | |
| - type: dot_f1 | |
| value: 82.44575936883628 | |
| - type: dot_precision | |
| value: 81.32295719844358 | |
| - type: dot_recall | |
| value: 83.6 | |
| - type: euclidean_accuracy | |
| value: 99.66237623762376 | |
| - type: euclidean_ap | |
| value: 90.3546512622632 | |
| - type: euclidean_f1 | |
| value: 82.44575936883628 | |
| - type: euclidean_precision | |
| value: 81.32295719844358 | |
| - type: euclidean_recall | |
| value: 83.6 | |
| - type: manhattan_accuracy | |
| value: 99.65940594059406 | |
| - type: manhattan_ap | |
| value: 90.29220174849843 | |
| - type: manhattan_f1 | |
| value: 82.4987605354487 | |
| - type: manhattan_precision | |
| value: 81.80924287118977 | |
| - type: manhattan_recall | |
| value: 83.2 | |
| - type: max_accuracy | |
| value: 99.66237623762376 | |
| - type: max_ap | |
| value: 90.35465126226322 | |
| - type: max_f1 | |
| value: 82.4987605354487 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/stackexchange-clustering | |
| name: MTEB StackExchangeClustering | |
| config: default | |
| split: test | |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 | |
| metrics: | |
| - type: v_measure | |
| value: 65.0394225901397 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/stackexchange-clustering-p2p | |
| name: MTEB StackExchangeClusteringP2P | |
| config: default | |
| split: test | |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 | |
| metrics: | |
| - type: v_measure | |
| value: 35.27954189859326 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/stackoverflowdupquestions-reranking | |
| name: MTEB StackOverflowDupQuestions | |
| config: default | |
| split: test | |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 | |
| metrics: | |
| - type: map | |
| value: 50.99055979974896 | |
| - type: mrr | |
| value: 51.82745257193787 | |
| - task: | |
| type: Summarization | |
| dataset: | |
| type: mteb/summeval | |
| name: MTEB SummEval | |
| config: default | |
| split: test | |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 30.21655465344237 | |
| - type: cos_sim_spearman | |
| value: 29.853205339630172 | |
| - type: dot_pearson | |
| value: 30.216540628083564 | |
| - type: dot_spearman | |
| value: 29.868978894753027 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: trec-covid | |
| name: MTEB TRECCOVID | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 0.2 | |
| - type: map_at_10 | |
| value: 1.398 | |
| - type: map_at_100 | |
| value: 7.406 | |
| - type: map_at_1000 | |
| value: 18.401 | |
| - type: map_at_3 | |
| value: 0.479 | |
| - type: map_at_5 | |
| value: 0.772 | |
| - type: mrr_at_1 | |
| value: 70.0 | |
| - type: mrr_at_10 | |
| value: 79.25999999999999 | |
| - type: mrr_at_100 | |
| value: 79.25999999999999 | |
| - type: mrr_at_1000 | |
| value: 79.25999999999999 | |
| - type: mrr_at_3 | |
| value: 77.333 | |
| - type: mrr_at_5 | |
| value: 78.133 | |
| - type: ndcg_at_1 | |
| value: 63.0 | |
| - type: ndcg_at_10 | |
| value: 58.548 | |
| - type: ndcg_at_100 | |
| value: 45.216 | |
| - type: ndcg_at_1000 | |
| value: 41.149 | |
| - type: ndcg_at_3 | |
| value: 60.641999999999996 | |
| - type: ndcg_at_5 | |
| value: 61.135 | |
| - type: precision_at_1 | |
| value: 70.0 | |
| - type: precision_at_10 | |
| value: 64.0 | |
| - type: precision_at_100 | |
| value: 46.92 | |
| - type: precision_at_1000 | |
| value: 18.642 | |
| - type: precision_at_3 | |
| value: 64.667 | |
| - type: precision_at_5 | |
| value: 66.4 | |
| - type: recall_at_1 | |
| value: 0.2 | |
| - type: recall_at_10 | |
| value: 1.6729999999999998 | |
| - type: recall_at_100 | |
| value: 10.856 | |
| - type: recall_at_1000 | |
| value: 38.964999999999996 | |
| - type: recall_at_3 | |
| value: 0.504 | |
| - type: recall_at_5 | |
| value: 0.852 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: webis-touche2020 | |
| name: MTEB Touche2020 | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 1.6629999999999998 | |
| - type: map_at_10 | |
| value: 8.601 | |
| - type: map_at_100 | |
| value: 14.354 | |
| - type: map_at_1000 | |
| value: 15.927 | |
| - type: map_at_3 | |
| value: 4.1930000000000005 | |
| - type: map_at_5 | |
| value: 5.655 | |
| - type: mrr_at_1 | |
| value: 18.367 | |
| - type: mrr_at_10 | |
| value: 34.466 | |
| - type: mrr_at_100 | |
| value: 35.235 | |
| - type: mrr_at_1000 | |
| value: 35.27 | |
| - type: mrr_at_3 | |
| value: 28.571 | |
| - type: mrr_at_5 | |
| value: 31.531 | |
| - type: ndcg_at_1 | |
| value: 14.285999999999998 | |
| - type: ndcg_at_10 | |
| value: 20.374 | |
| - type: ndcg_at_100 | |
| value: 33.532000000000004 | |
| - type: ndcg_at_1000 | |
| value: 45.561 | |
| - type: ndcg_at_3 | |
| value: 18.442 | |
| - type: ndcg_at_5 | |
| value: 18.076 | |
| - type: precision_at_1 | |
| value: 18.367 | |
| - type: precision_at_10 | |
| value: 20.204 | |
| - type: precision_at_100 | |
| value: 7.489999999999999 | |
| - type: precision_at_1000 | |
| value: 1.5630000000000002 | |
| - type: precision_at_3 | |
| value: 21.769 | |
| - type: precision_at_5 | |
| value: 20.408 | |
| - type: recall_at_1 | |
| value: 1.6629999999999998 | |
| - type: recall_at_10 | |
| value: 15.549 | |
| - type: recall_at_100 | |
| value: 47.497 | |
| - type: recall_at_1000 | |
| value: 84.524 | |
| - type: recall_at_3 | |
| value: 5.289 | |
| - type: recall_at_5 | |
| value: 8.035 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/toxic_conversations_50k | |
| name: MTEB ToxicConversationsClassification | |
| config: default | |
| split: test | |
| revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c | |
| metrics: | |
| - type: accuracy | |
| value: 71.8194 | |
| - type: ap | |
| value: 14.447702451658554 | |
| - type: f1 | |
| value: 55.13659412856185 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/tweet_sentiment_extraction | |
| name: MTEB TweetSentimentExtractionClassification | |
| config: default | |
| split: test | |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a | |
| metrics: | |
| - type: accuracy | |
| value: 63.310696095076416 | |
| - type: f1 | |
| value: 63.360434851097814 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/twentynewsgroups-clustering | |
| name: MTEB TwentyNewsgroupsClustering | |
| config: default | |
| split: test | |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 | |
| metrics: | |
| - type: v_measure | |
| value: 51.30677907335145 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/twittersemeval2015-pairclassification | |
| name: MTEB TwitterSemEval2015 | |
| config: default | |
| split: test | |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 86.12386004649221 | |
| - type: cos_sim_ap | |
| value: 73.99096426215495 | |
| - type: cos_sim_f1 | |
| value: 68.18416968442834 | |
| - type: cos_sim_precision | |
| value: 66.86960933536275 | |
| - type: cos_sim_recall | |
| value: 69.55145118733509 | |
| - type: dot_accuracy | |
| value: 86.12386004649221 | |
| - type: dot_ap | |
| value: 73.99096813038672 | |
| - type: dot_f1 | |
| value: 68.18416968442834 | |
| - type: dot_precision | |
| value: 66.86960933536275 | |
| - type: dot_recall | |
| value: 69.55145118733509 | |
| - type: euclidean_accuracy | |
| value: 86.12386004649221 | |
| - type: euclidean_ap | |
| value: 73.99095984980165 | |
| - type: euclidean_f1 | |
| value: 68.18416968442834 | |
| - type: euclidean_precision | |
| value: 66.86960933536275 | |
| - type: euclidean_recall | |
| value: 69.55145118733509 | |
| - type: manhattan_accuracy | |
| value: 86.09405734040651 | |
| - type: manhattan_ap | |
| value: 73.96825745608601 | |
| - type: manhattan_f1 | |
| value: 68.13888179729383 | |
| - type: manhattan_precision | |
| value: 65.99901088031652 | |
| - type: manhattan_recall | |
| value: 70.42216358839049 | |
| - type: max_accuracy | |
| value: 86.12386004649221 | |
| - type: max_ap | |
| value: 73.99096813038672 | |
| - type: max_f1 | |
| value: 68.18416968442834 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/twitterurlcorpus-pairclassification | |
| name: MTEB TwitterURLCorpus | |
| config: default | |
| split: test | |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 88.99367407924865 | |
| - type: cos_sim_ap | |
| value: 86.19720829843081 | |
| - type: cos_sim_f1 | |
| value: 78.39889075384951 | |
| - type: cos_sim_precision | |
| value: 74.5110278818144 | |
| - type: cos_sim_recall | |
| value: 82.71481367416075 | |
| - type: dot_accuracy | |
| value: 88.99367407924865 | |
| - type: dot_ap | |
| value: 86.19718471454047 | |
| - type: dot_f1 | |
| value: 78.39889075384951 | |
| - type: dot_precision | |
| value: 74.5110278818144 | |
| - type: dot_recall | |
| value: 82.71481367416075 | |
| - type: euclidean_accuracy | |
| value: 88.99367407924865 | |
| - type: euclidean_ap | |
| value: 86.1972021422436 | |
| - type: euclidean_f1 | |
| value: 78.39889075384951 | |
| - type: euclidean_precision | |
| value: 74.5110278818144 | |
| - type: euclidean_recall | |
| value: 82.71481367416075 | |
| - type: manhattan_accuracy | |
| value: 88.95680521597392 | |
| - type: manhattan_ap | |
| value: 86.16659921351506 | |
| - type: manhattan_f1 | |
| value: 78.39125971550081 | |
| - type: manhattan_precision | |
| value: 74.82502799552073 | |
| - type: manhattan_recall | |
| value: 82.31444410224823 | |
| - type: max_accuracy | |
| value: 88.99367407924865 | |
| - type: max_ap | |
| value: 86.19720829843081 | |
| - type: max_f1 | |
| value: 78.39889075384951 | |
| # hkunlp/instructor-base | |
| We introduce **Instructor**👨🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e.g., classification, retrieval, clustering, text evaluation, etc.) and domains (e.g., science, finance, etc.) ***by simply providing the task instruction, without any finetuning***. Instructor👨 achieves sota on 70 diverse embedding tasks! | |
| The model is easy to use with **our customized** `sentence-transformer` library. For more details, check out [our paper](https://arxiv.org/abs/2212.09741) and [project page](https://instructor-embedding.github.io/)! | |
| **************************** **Updates** **************************** | |
| * 01/21: We released a new [checkpoint](https://huggingface.co/hkunlp/instructor-base) trained with hard negatives, which gives better performance. | |
| * 12/21: We released our [paper](https://arxiv.org/abs/2212.09741), [code](https://github.com/HKUNLP/instructor-embedding), [checkpoint](https://huggingface.co/hkunlp/instructor-base) and [project page](https://instructor-embedding.github.io/)! Check them out! | |
| ## Quick start | |
| <hr /> | |
| ## Installation | |
| ```bash | |
| pip install InstructorEmbedding | |
| ``` | |
| ## Compute your customized embeddings | |
| Then you can use the model like this to calculate domain-specific and task-aware embeddings: | |
| ```python | |
| from InstructorEmbedding import INSTRUCTOR | |
| model = INSTRUCTOR('hkunlp/instructor-base') | |
| sentence = "3D ActionSLAM: wearable person tracking in multi-floor environments" | |
| instruction = "Represent the Science title:" | |
| embeddings = model.encode([[instruction,sentence]]) | |
| print(embeddings) | |
| ``` | |
| ## Use cases | |
| <hr /> | |
| ## Calculate embeddings for your customized texts | |
| If you want to calculate customized embeddings for specific sentences, you may follow the unified template to write instructions: | |
| Represent the `domain` `text_type` for `task_objective`: | |
| * `domain` is optional, and it specifies the domain of the text, e.g., science, finance, medicine, etc. | |
| * `text_type` is required, and it specifies the encoding unit, e.g., sentence, document, paragraph, etc. | |
| * `task_objective` is optional, and it specifies the objective of embedding, e.g., retrieve a document, classify the sentence, etc. | |
| ## Calculate Sentence similarities | |
| You can further use the model to compute similarities between two groups of sentences, with **customized embeddings**. | |
| ```python | |
| from sklearn.metrics.pairwise import cosine_similarity | |
| sentences_a = [['Represent the Science sentence: ','Parton energy loss in QCD matter'], | |
| ['Represent the Financial statement: ','The Federal Reserve on Wednesday raised its benchmark interest rate.']] | |
| sentences_b = [['Represent the Science sentence: ','The Chiral Phase Transition in Dissipative Dynamics'], | |
| ['Represent the Financial statement: ','The funds rose less than 0.5 per cent on Friday']] | |
| embeddings_a = model.encode(sentences_a) | |
| embeddings_b = model.encode(sentences_b) | |
| similarities = cosine_similarity(embeddings_a,embeddings_b) | |
| print(similarities) | |
| ``` | |
| ## Information Retrieval | |
| You can also use **customized embeddings** for information retrieval. | |
| ```python | |
| import numpy as np | |
| from sklearn.metrics.pairwise import cosine_similarity | |
| query = [['Represent the Wikipedia question for retrieving supporting documents: ','where is the food stored in a yam plant']] | |
| corpus = [['Represent the Wikipedia document for retrieval: ','Capitalism has been dominant in the Western world since the end of feudalism, but most feel[who?] that the term "mixed economies" more precisely describes most contemporary economies, due to their containing both private-owned and state-owned enterprises. In capitalism, prices determine the demand-supply scale. For example, higher demand for certain goods and services lead to higher prices and lower demand for certain goods lead to lower prices.'], | |
| ['Represent the Wikipedia document for retrieval: ',"The disparate impact theory is especially controversial under the Fair Housing Act because the Act regulates many activities relating to housing, insurance, and mortgage loans—and some scholars have argued that the theory's use under the Fair Housing Act, combined with extensions of the Community Reinvestment Act, contributed to rise of sub-prime lending and the crash of the U.S. housing market and ensuing global economic recession"], | |
| ['Represent the Wikipedia document for retrieval: ','Disparate impact in United States labor law refers to practices in employment, housing, and other areas that adversely affect one group of people of a protected characteristic more than another, even though rules applied by employers or landlords are formally neutral. Although the protected classes vary by statute, most federal civil rights laws protect based on race, color, religion, national origin, and sex as protected traits, and some laws include disability status and other traits as well.']] | |
| query_embeddings = model.encode(query) | |
| corpus_embeddings = model.encode(corpus) | |
| similarities = cosine_similarity(query_embeddings,corpus_embeddings) | |
| retrieved_doc_id = np.argmax(similarities) | |
| print(retrieved_doc_id) | |
| ``` | |
| ## Clustering | |
| Use **customized embeddings** for clustering texts in groups. | |
| ```python | |
| import sklearn.cluster | |
| sentences = [['Represent the Medicine sentence for clustering: ','Dynamical Scalar Degree of Freedom in Horava-Lifshitz Gravity'], | |
| ['Represent the Medicine sentence for clustering: ','Comparison of Atmospheric Neutrino Flux Calculations at Low Energies'], | |
| ['Represent the Medicine sentence for clustering: ','Fermion Bags in the Massive Gross-Neveu Model'], | |
| ['Represent the Medicine sentence for clustering: ',"QCD corrections to Associated t-tbar-H production at the Tevatron"], | |
| ['Represent the Medicine sentence for clustering: ','A New Analysis of the R Measurements: Resonance Parameters of the Higher, Vector States of Charmonium']] | |
| embeddings = model.encode(sentences) | |
| clustering_model = sklearn.cluster.MiniBatchKMeans(n_clusters=2) | |
| clustering_model.fit(embeddings) | |
| cluster_assignment = clustering_model.labels_ | |
| print(cluster_assignment) | |
| ``` |