| | --- |
| | pipeline_tag: text-generation |
| | inference: true |
| | license: apache-2.0 |
| | datasets: |
| | - GritLM/tulu2 |
| | tags: |
| | - mteb |
| | - TensorBlock |
| | - GGUF |
| | base_model: GritLM/GritLM-7B |
| | model-index: |
| | - name: GritLM-7B |
| | results: |
| | - task: |
| | type: Classification |
| | dataset: |
| | name: MTEB AmazonCounterfactualClassification (en) |
| | type: mteb/amazon_counterfactual |
| | config: en |
| | split: test |
| | revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
| | metrics: |
| | - type: accuracy |
| | value: 81.17910447761194 |
| | - type: ap |
| | value: 46.26260671758199 |
| | - type: f1 |
| | value: 75.44565719934167 |
| | - task: |
| | type: Classification |
| | dataset: |
| | name: MTEB AmazonPolarityClassification |
| | type: mteb/amazon_polarity |
| | config: default |
| | split: test |
| | revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
| | metrics: |
| | - type: accuracy |
| | value: 96.5161 |
| | - type: ap |
| | value: 94.79131981460425 |
| | - type: f1 |
| | value: 96.51506148413065 |
| | - task: |
| | type: Classification |
| | dataset: |
| | name: MTEB AmazonReviewsClassification (en) |
| | type: mteb/amazon_reviews_multi |
| | config: en |
| | split: test |
| | revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| | metrics: |
| | - type: accuracy |
| | value: 57.806000000000004 |
| | - type: f1 |
| | value: 56.78350156257903 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB ArguAna |
| | type: arguana |
| | config: default |
| | split: test |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 38.478 |
| | - type: map_at_10 |
| | value: 54.955 |
| | - type: map_at_100 |
| | value: 54.955 |
| | - type: map_at_1000 |
| | value: 54.955 |
| | - type: map_at_3 |
| | value: 50.888999999999996 |
| | - type: map_at_5 |
| | value: 53.349999999999994 |
| | - type: mrr_at_1 |
| | value: 39.757999999999996 |
| | - type: mrr_at_10 |
| | value: 55.449000000000005 |
| | - type: mrr_at_100 |
| | value: 55.449000000000005 |
| | - type: mrr_at_1000 |
| | value: 55.449000000000005 |
| | - type: mrr_at_3 |
| | value: 51.37500000000001 |
| | - type: mrr_at_5 |
| | value: 53.822 |
| | - type: ndcg_at_1 |
| | value: 38.478 |
| | - type: ndcg_at_10 |
| | value: 63.239999999999995 |
| | - type: ndcg_at_100 |
| | value: 63.239999999999995 |
| | - type: ndcg_at_1000 |
| | value: 63.239999999999995 |
| | - type: ndcg_at_3 |
| | value: 54.935 |
| | - type: ndcg_at_5 |
| | value: 59.379000000000005 |
| | - type: precision_at_1 |
| | value: 38.478 |
| | - type: precision_at_10 |
| | value: 8.933 |
| | - type: precision_at_100 |
| | value: 0.893 |
| | - type: precision_at_1000 |
| | value: 0.089 |
| | - type: precision_at_3 |
| | value: 22.214 |
| | - type: precision_at_5 |
| | value: 15.491 |
| | - type: recall_at_1 |
| | value: 38.478 |
| | - type: recall_at_10 |
| | value: 89.331 |
| | - type: recall_at_100 |
| | value: 89.331 |
| | - type: recall_at_1000 |
| | value: 89.331 |
| | - type: recall_at_3 |
| | value: 66.643 |
| | - type: recall_at_5 |
| | value: 77.45400000000001 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | name: MTEB ArxivClusteringP2P |
| | type: mteb/arxiv-clustering-p2p |
| | config: default |
| | split: test |
| | revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| | metrics: |
| | - type: v_measure |
| | value: 51.67144081472449 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | name: MTEB ArxivClusteringS2S |
| | type: mteb/arxiv-clustering-s2s |
| | config: default |
| | split: test |
| | revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
| | metrics: |
| | - type: v_measure |
| | value: 48.11256154264126 |
| | - task: |
| | type: Reranking |
| | dataset: |
| | name: MTEB AskUbuntuDupQuestions |
| | type: mteb/askubuntudupquestions-reranking |
| | config: default |
| | split: test |
| | revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
| | metrics: |
| | - type: map |
| | value: 67.33801955487878 |
| | - type: mrr |
| | value: 80.71549487754474 |
| | - task: |
| | type: STS |
| | dataset: |
| | name: MTEB BIOSSES |
| | type: mteb/biosses-sts |
| | config: default |
| | split: test |
| | revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 88.1935203751726 |
| | - type: cos_sim_spearman |
| | value: 86.35497970498659 |
| | - type: euclidean_pearson |
| | value: 85.46910708503744 |
| | - type: euclidean_spearman |
| | value: 85.13928935405485 |
| | - type: manhattan_pearson |
| | value: 85.68373836333303 |
| | - type: manhattan_spearman |
| | value: 85.40013867117746 |
| | - task: |
| | type: Classification |
| | dataset: |
| | name: MTEB Banking77Classification |
| | type: mteb/banking77 |
| | config: default |
| | split: test |
| | revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| | metrics: |
| | - type: accuracy |
| | value: 88.46753246753248 |
| | - type: f1 |
| | value: 88.43006344981134 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | name: MTEB BiorxivClusteringP2P |
| | type: mteb/biorxiv-clustering-p2p |
| | config: default |
| | split: test |
| | revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| | metrics: |
| | - type: v_measure |
| | value: 40.86793640310432 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | name: MTEB BiorxivClusteringS2S |
| | type: mteb/biorxiv-clustering-s2s |
| | config: default |
| | split: test |
| | revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
| | metrics: |
| | - type: v_measure |
| | value: 39.80291334130727 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB CQADupstackAndroidRetrieval |
| | type: BeIR/cqadupstack |
| | config: default |
| | split: test |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 38.421 |
| | - type: map_at_10 |
| | value: 52.349000000000004 |
| | - type: map_at_100 |
| | value: 52.349000000000004 |
| | - type: map_at_1000 |
| | value: 52.349000000000004 |
| | - type: map_at_3 |
| | value: 48.17 |
| | - type: map_at_5 |
| | value: 50.432 |
| | - type: mrr_at_1 |
| | value: 47.353 |
| | - type: mrr_at_10 |
| | value: 58.387 |
| | - type: mrr_at_100 |
| | value: 58.387 |
| | - type: mrr_at_1000 |
| | value: 58.387 |
| | - type: mrr_at_3 |
| | value: 56.199 |
| | - type: mrr_at_5 |
| | value: 57.487 |
| | - type: ndcg_at_1 |
| | value: 47.353 |
| | - type: ndcg_at_10 |
| | value: 59.202 |
| | - type: ndcg_at_100 |
| | value: 58.848 |
| | - type: ndcg_at_1000 |
| | value: 58.831999999999994 |
| | - type: ndcg_at_3 |
| | value: 54.112 |
| | - type: ndcg_at_5 |
| | value: 56.312 |
| | - type: precision_at_1 |
| | value: 47.353 |
| | - type: precision_at_10 |
| | value: 11.459 |
| | - type: precision_at_100 |
| | value: 1.146 |
| | - type: precision_at_1000 |
| | value: 0.11499999999999999 |
| | - type: precision_at_3 |
| | value: 26.133 |
| | - type: precision_at_5 |
| | value: 18.627 |
| | - type: recall_at_1 |
| | value: 38.421 |
| | - type: recall_at_10 |
| | value: 71.89 |
| | - type: recall_at_100 |
| | value: 71.89 |
| | - type: recall_at_1000 |
| | value: 71.89 |
| | - type: recall_at_3 |
| | value: 56.58 |
| | - type: recall_at_5 |
| | value: 63.125 |
| | - type: map_at_1 |
| | value: 38.025999999999996 |
| | - type: map_at_10 |
| | value: 50.590999999999994 |
| | - type: map_at_100 |
| | value: 51.99700000000001 |
| | - type: map_at_1000 |
| | value: 52.11599999999999 |
| | - type: map_at_3 |
| | value: 47.435 |
| | - type: map_at_5 |
| | value: 49.236000000000004 |
| | - type: mrr_at_1 |
| | value: 48.28 |
| | - type: mrr_at_10 |
| | value: 56.814 |
| | - type: mrr_at_100 |
| | value: 57.446 |
| | - type: mrr_at_1000 |
| | value: 57.476000000000006 |
| | - type: mrr_at_3 |
| | value: 54.958 |
| | - type: mrr_at_5 |
| | value: 56.084999999999994 |
| | - type: ndcg_at_1 |
| | value: 48.28 |
| | - type: ndcg_at_10 |
| | value: 56.442 |
| | - type: ndcg_at_100 |
| | value: 60.651999999999994 |
| | - type: ndcg_at_1000 |
| | value: 62.187000000000005 |
| | - type: ndcg_at_3 |
| | value: 52.866 |
| | - type: ndcg_at_5 |
| | value: 54.515 |
| | - type: precision_at_1 |
| | value: 48.28 |
| | - type: precision_at_10 |
| | value: 10.586 |
| | - type: precision_at_100 |
| | value: 1.6310000000000002 |
| | - type: precision_at_1000 |
| | value: 0.20600000000000002 |
| | - type: precision_at_3 |
| | value: 25.945 |
| | - type: precision_at_5 |
| | value: 18.076 |
| | - type: recall_at_1 |
| | value: 38.025999999999996 |
| | - type: recall_at_10 |
| | value: 66.11399999999999 |
| | - type: recall_at_100 |
| | value: 83.339 |
| | - type: recall_at_1000 |
| | value: 92.413 |
| | - type: recall_at_3 |
| | value: 54.493 |
| | - type: recall_at_5 |
| | value: 59.64699999999999 |
| | - type: map_at_1 |
| | value: 47.905 |
| | - type: map_at_10 |
| | value: 61.58 |
| | - type: map_at_100 |
| | value: 62.605 |
| | - type: map_at_1000 |
| | value: 62.637 |
| | - type: map_at_3 |
| | value: 58.074000000000005 |
| | - type: map_at_5 |
| | value: 60.260000000000005 |
| | - type: mrr_at_1 |
| | value: 54.42 |
| | - type: mrr_at_10 |
| | value: 64.847 |
| | - type: mrr_at_100 |
| | value: 65.403 |
| | - type: mrr_at_1000 |
| | value: 65.41900000000001 |
| | - type: mrr_at_3 |
| | value: 62.675000000000004 |
| | - type: mrr_at_5 |
| | value: 64.101 |
| | - type: ndcg_at_1 |
| | value: 54.42 |
| | - type: ndcg_at_10 |
| | value: 67.394 |
| | - type: ndcg_at_100 |
| | value: 70.846 |
| | - type: ndcg_at_1000 |
| | value: 71.403 |
| | - type: ndcg_at_3 |
| | value: 62.025 |
| | - type: ndcg_at_5 |
| | value: 65.032 |
| | - type: precision_at_1 |
| | value: 54.42 |
| | - type: precision_at_10 |
| | value: 10.646 |
| | - type: precision_at_100 |
| | value: 1.325 |
| | - type: precision_at_1000 |
| | value: 0.13999999999999999 |
| | - type: precision_at_3 |
| | value: 27.398 |
| | - type: precision_at_5 |
| | value: 18.796 |
| | - type: recall_at_1 |
| | value: 47.905 |
| | - type: recall_at_10 |
| | value: 80.84599999999999 |
| | - type: recall_at_100 |
| | value: 95.078 |
| | - type: recall_at_1000 |
| | value: 98.878 |
| | - type: recall_at_3 |
| | value: 67.05600000000001 |
| | - type: recall_at_5 |
| | value: 74.261 |
| | - type: map_at_1 |
| | value: 30.745 |
| | - type: map_at_10 |
| | value: 41.021 |
| | - type: map_at_100 |
| | value: 41.021 |
| | - type: map_at_1000 |
| | value: 41.021 |
| | - type: map_at_3 |
| | value: 37.714999999999996 |
| | - type: map_at_5 |
| | value: 39.766 |
| | - type: mrr_at_1 |
| | value: 33.559 |
| | - type: mrr_at_10 |
| | value: 43.537 |
| | - type: mrr_at_100 |
| | value: 43.537 |
| | - type: mrr_at_1000 |
| | value: 43.537 |
| | - type: mrr_at_3 |
| | value: 40.546 |
| | - type: mrr_at_5 |
| | value: 42.439 |
| | - type: ndcg_at_1 |
| | value: 33.559 |
| | - type: ndcg_at_10 |
| | value: 46.781 |
| | - type: ndcg_at_100 |
| | value: 46.781 |
| | - type: ndcg_at_1000 |
| | value: 46.781 |
| | - type: ndcg_at_3 |
| | value: 40.516000000000005 |
| | - type: ndcg_at_5 |
| | value: 43.957 |
| | - type: precision_at_1 |
| | value: 33.559 |
| | - type: precision_at_10 |
| | value: 7.198 |
| | - type: precision_at_100 |
| | value: 0.72 |
| | - type: precision_at_1000 |
| | value: 0.07200000000000001 |
| | - type: precision_at_3 |
| | value: 17.1 |
| | - type: precision_at_5 |
| | value: 12.316 |
| | - type: recall_at_1 |
| | value: 30.745 |
| | - type: recall_at_10 |
| | value: 62.038000000000004 |
| | - type: recall_at_100 |
| | value: 62.038000000000004 |
| | - type: recall_at_1000 |
| | value: 62.038000000000004 |
| | - type: recall_at_3 |
| | value: 45.378 |
| | - type: recall_at_5 |
| | value: 53.580000000000005 |
| | - type: map_at_1 |
| | value: 19.637999999999998 |
| | - type: map_at_10 |
| | value: 31.05 |
| | - type: map_at_100 |
| | value: 31.05 |
| | - type: map_at_1000 |
| | value: 31.05 |
| | - type: map_at_3 |
| | value: 27.628000000000004 |
| | - type: map_at_5 |
| | value: 29.767 |
| | - type: mrr_at_1 |
| | value: 25.0 |
| | - type: mrr_at_10 |
| | value: 36.131 |
| | - type: mrr_at_100 |
| | value: 36.131 |
| | - type: mrr_at_1000 |
| | value: 36.131 |
| | - type: mrr_at_3 |
| | value: 33.333 |
| | - type: mrr_at_5 |
| | value: 35.143 |
| | - type: ndcg_at_1 |
| | value: 25.0 |
| | - type: ndcg_at_10 |
| | value: 37.478 |
| | - type: ndcg_at_100 |
| | value: 37.469 |
| | - type: ndcg_at_1000 |
| | value: 37.469 |
| | - type: ndcg_at_3 |
| | value: 31.757999999999996 |
| | - type: ndcg_at_5 |
| | value: 34.821999999999996 |
| | - type: precision_at_1 |
| | value: 25.0 |
| | - type: precision_at_10 |
| | value: 7.188999999999999 |
| | - type: precision_at_100 |
| | value: 0.719 |
| | - type: precision_at_1000 |
| | value: 0.07200000000000001 |
| | - type: precision_at_3 |
| | value: 15.837000000000002 |
| | - type: precision_at_5 |
| | value: 11.841 |
| | - type: recall_at_1 |
| | value: 19.637999999999998 |
| | - type: recall_at_10 |
| | value: 51.836000000000006 |
| | - type: recall_at_100 |
| | value: 51.836000000000006 |
| | - type: recall_at_1000 |
| | value: 51.836000000000006 |
| | - type: recall_at_3 |
| | value: 36.384 |
| | - type: recall_at_5 |
| | value: 43.964 |
| | - type: map_at_1 |
| | value: 34.884 |
| | - type: map_at_10 |
| | value: 47.88 |
| | - type: map_at_100 |
| | value: 47.88 |
| | - type: map_at_1000 |
| | value: 47.88 |
| | - type: map_at_3 |
| | value: 43.85 |
| | - type: map_at_5 |
| | value: 46.414 |
| | - type: mrr_at_1 |
| | value: 43.022 |
| | - type: mrr_at_10 |
| | value: 53.569 |
| | - type: mrr_at_100 |
| | value: 53.569 |
| | - type: mrr_at_1000 |
| | value: 53.569 |
| | - type: mrr_at_3 |
| | value: 51.075 |
| | - type: mrr_at_5 |
| | value: 52.725 |
| | - type: ndcg_at_1 |
| | value: 43.022 |
| | - type: ndcg_at_10 |
| | value: 54.461000000000006 |
| | - type: ndcg_at_100 |
| | value: 54.388000000000005 |
| | - type: ndcg_at_1000 |
| | value: 54.388000000000005 |
| | - type: ndcg_at_3 |
| | value: 48.864999999999995 |
| | - type: ndcg_at_5 |
| | value: 52.032000000000004 |
| | - type: precision_at_1 |
| | value: 43.022 |
| | - type: precision_at_10 |
| | value: 9.885 |
| | - type: precision_at_100 |
| | value: 0.988 |
| | - type: precision_at_1000 |
| | value: 0.099 |
| | - type: precision_at_3 |
| | value: 23.612 |
| | - type: precision_at_5 |
| | value: 16.997 |
| | - type: recall_at_1 |
| | value: 34.884 |
| | - type: recall_at_10 |
| | value: 68.12899999999999 |
| | - type: recall_at_100 |
| | value: 68.12899999999999 |
| | - type: recall_at_1000 |
| | value: 68.12899999999999 |
| | - type: recall_at_3 |
| | value: 52.428 |
| | - type: recall_at_5 |
| | value: 60.662000000000006 |
| | - type: map_at_1 |
| | value: 31.588 |
| | - type: map_at_10 |
| | value: 43.85 |
| | - type: map_at_100 |
| | value: 45.317 |
| | - type: map_at_1000 |
| | value: 45.408 |
| | - type: map_at_3 |
| | value: 39.73 |
| | - type: map_at_5 |
| | value: 42.122 |
| | - type: mrr_at_1 |
| | value: 38.927 |
| | - type: mrr_at_10 |
| | value: 49.582 |
| | - type: mrr_at_100 |
| | value: 50.39 |
| | - type: mrr_at_1000 |
| | value: 50.426 |
| | - type: mrr_at_3 |
| | value: 46.518 |
| | - type: mrr_at_5 |
| | value: 48.271 |
| | - type: ndcg_at_1 |
| | value: 38.927 |
| | - type: ndcg_at_10 |
| | value: 50.605999999999995 |
| | - type: ndcg_at_100 |
| | value: 56.22200000000001 |
| | - type: ndcg_at_1000 |
| | value: 57.724 |
| | - type: ndcg_at_3 |
| | value: 44.232 |
| | - type: ndcg_at_5 |
| | value: 47.233999999999995 |
| | - type: precision_at_1 |
| | value: 38.927 |
| | - type: precision_at_10 |
| | value: 9.429 |
| | - type: precision_at_100 |
| | value: 1.435 |
| | - type: precision_at_1000 |
| | value: 0.172 |
| | - type: precision_at_3 |
| | value: 21.271 |
| | - type: precision_at_5 |
| | value: 15.434000000000001 |
| | - type: recall_at_1 |
| | value: 31.588 |
| | - type: recall_at_10 |
| | value: 64.836 |
| | - type: recall_at_100 |
| | value: 88.066 |
| | - type: recall_at_1000 |
| | value: 97.748 |
| | - type: recall_at_3 |
| | value: 47.128 |
| | - type: recall_at_5 |
| | value: 54.954 |
| | - type: map_at_1 |
| | value: 31.956083333333336 |
| | - type: map_at_10 |
| | value: 43.33483333333333 |
| | - type: map_at_100 |
| | value: 44.64883333333333 |
| | - type: map_at_1000 |
| | value: 44.75 |
| | - type: map_at_3 |
| | value: 39.87741666666666 |
| | - type: map_at_5 |
| | value: 41.86766666666667 |
| | - type: mrr_at_1 |
| | value: 38.06341666666667 |
| | - type: mrr_at_10 |
| | value: 47.839666666666666 |
| | - type: mrr_at_100 |
| | value: 48.644000000000005 |
| | - type: mrr_at_1000 |
| | value: 48.68566666666667 |
| | - type: mrr_at_3 |
| | value: 45.26358333333334 |
| | - type: mrr_at_5 |
| | value: 46.790000000000006 |
| | - type: ndcg_at_1 |
| | value: 38.06341666666667 |
| | - type: ndcg_at_10 |
| | value: 49.419333333333334 |
| | - type: ndcg_at_100 |
| | value: 54.50166666666667 |
| | - type: ndcg_at_1000 |
| | value: 56.161166666666674 |
| | - type: ndcg_at_3 |
| | value: 43.982416666666666 |
| | - type: ndcg_at_5 |
| | value: 46.638083333333334 |
| | - type: precision_at_1 |
| | value: 38.06341666666667 |
| | - type: precision_at_10 |
| | value: 8.70858333333333 |
| | - type: precision_at_100 |
| | value: 1.327 |
| | - type: precision_at_1000 |
| | value: 0.165 |
| | - type: precision_at_3 |
| | value: 20.37816666666667 |
| | - type: precision_at_5 |
| | value: 14.516333333333334 |
| | - type: recall_at_1 |
| | value: 31.956083333333336 |
| | - type: recall_at_10 |
| | value: 62.69458333333334 |
| | - type: recall_at_100 |
| | value: 84.46433333333334 |
| | - type: recall_at_1000 |
| | value: 95.58449999999999 |
| | - type: recall_at_3 |
| | value: 47.52016666666666 |
| | - type: recall_at_5 |
| | value: 54.36066666666666 |
| | - type: map_at_1 |
| | value: 28.912 |
| | - type: map_at_10 |
| | value: 38.291 |
| | - type: map_at_100 |
| | value: 39.44 |
| | - type: map_at_1000 |
| | value: 39.528 |
| | - type: map_at_3 |
| | value: 35.638 |
| | - type: map_at_5 |
| | value: 37.218 |
| | - type: mrr_at_1 |
| | value: 32.822 |
| | - type: mrr_at_10 |
| | value: 41.661 |
| | - type: mrr_at_100 |
| | value: 42.546 |
| | - type: mrr_at_1000 |
| | value: 42.603 |
| | - type: mrr_at_3 |
| | value: 39.238 |
| | - type: mrr_at_5 |
| | value: 40.726 |
| | - type: ndcg_at_1 |
| | value: 32.822 |
| | - type: ndcg_at_10 |
| | value: 43.373 |
| | - type: ndcg_at_100 |
| | value: 48.638 |
| | - type: ndcg_at_1000 |
| | value: 50.654999999999994 |
| | - type: ndcg_at_3 |
| | value: 38.643 |
| | - type: ndcg_at_5 |
| | value: 41.126000000000005 |
| | - type: precision_at_1 |
| | value: 32.822 |
| | - type: precision_at_10 |
| | value: 6.8709999999999996 |
| | - type: precision_at_100 |
| | value: 1.032 |
| | - type: precision_at_1000 |
| | value: 0.128 |
| | - type: precision_at_3 |
| | value: 16.82 |
| | - type: precision_at_5 |
| | value: 11.718 |
| | - type: recall_at_1 |
| | value: 28.912 |
| | - type: recall_at_10 |
| | value: 55.376999999999995 |
| | - type: recall_at_100 |
| | value: 79.066 |
| | - type: recall_at_1000 |
| | value: 93.664 |
| | - type: recall_at_3 |
| | value: 42.569 |
| | - type: recall_at_5 |
| | value: 48.719 |
| | - type: map_at_1 |
| | value: 22.181 |
| | - type: map_at_10 |
| | value: 31.462 |
| | - type: map_at_100 |
| | value: 32.73 |
| | - type: map_at_1000 |
| | value: 32.848 |
| | - type: map_at_3 |
| | value: 28.57 |
| | - type: map_at_5 |
| | value: 30.182 |
| | - type: mrr_at_1 |
| | value: 27.185 |
| | - type: mrr_at_10 |
| | value: 35.846000000000004 |
| | - type: mrr_at_100 |
| | value: 36.811 |
| | - type: mrr_at_1000 |
| | value: 36.873 |
| | - type: mrr_at_3 |
| | value: 33.437 |
| | - type: mrr_at_5 |
| | value: 34.813 |
| | - type: ndcg_at_1 |
| | value: 27.185 |
| | - type: ndcg_at_10 |
| | value: 36.858000000000004 |
| | - type: ndcg_at_100 |
| | value: 42.501 |
| | - type: ndcg_at_1000 |
| | value: 44.945 |
| | - type: ndcg_at_3 |
| | value: 32.066 |
| | - type: ndcg_at_5 |
| | value: 34.29 |
| | - type: precision_at_1 |
| | value: 27.185 |
| | - type: precision_at_10 |
| | value: 6.752 |
| | - type: precision_at_100 |
| | value: 1.111 |
| | - type: precision_at_1000 |
| | value: 0.151 |
| | - type: precision_at_3 |
| | value: 15.290000000000001 |
| | - type: precision_at_5 |
| | value: 11.004999999999999 |
| | - type: recall_at_1 |
| | value: 22.181 |
| | - type: recall_at_10 |
| | value: 48.513 |
| | - type: recall_at_100 |
| | value: 73.418 |
| | - type: recall_at_1000 |
| | value: 90.306 |
| | - type: recall_at_3 |
| | value: 35.003 |
| | - type: recall_at_5 |
| | value: 40.876000000000005 |
| | - type: map_at_1 |
| | value: 33.934999999999995 |
| | - type: map_at_10 |
| | value: 44.727 |
| | - type: map_at_100 |
| | value: 44.727 |
| | - type: map_at_1000 |
| | value: 44.727 |
| | - type: map_at_3 |
| | value: 40.918 |
| | - type: map_at_5 |
| | value: 42.961 |
| | - type: mrr_at_1 |
| | value: 39.646 |
| | - type: mrr_at_10 |
| | value: 48.898 |
| | - type: mrr_at_100 |
| | value: 48.898 |
| | - type: mrr_at_1000 |
| | value: 48.898 |
| | - type: mrr_at_3 |
| | value: 45.896 |
| | - type: mrr_at_5 |
| | value: 47.514 |
| | - type: ndcg_at_1 |
| | value: 39.646 |
| | - type: ndcg_at_10 |
| | value: 50.817 |
| | - type: ndcg_at_100 |
| | value: 50.803 |
| | - type: ndcg_at_1000 |
| | value: 50.803 |
| | - type: ndcg_at_3 |
| | value: 44.507999999999996 |
| | - type: ndcg_at_5 |
| | value: 47.259 |
| | - type: precision_at_1 |
| | value: 39.646 |
| | - type: precision_at_10 |
| | value: 8.759 |
| | - type: precision_at_100 |
| | value: 0.876 |
| | - type: precision_at_1000 |
| | value: 0.08800000000000001 |
| | - type: precision_at_3 |
| | value: 20.274 |
| | - type: precision_at_5 |
| | value: 14.366000000000001 |
| | - type: recall_at_1 |
| | value: 33.934999999999995 |
| | - type: recall_at_10 |
| | value: 65.037 |
| | - type: recall_at_100 |
| | value: 65.037 |
| | - type: recall_at_1000 |
| | value: 65.037 |
| | - type: recall_at_3 |
| | value: 47.439 |
| | - type: recall_at_5 |
| | value: 54.567 |
| | - type: map_at_1 |
| | value: 32.058 |
| | - type: map_at_10 |
| | value: 43.137 |
| | - type: map_at_100 |
| | value: 43.137 |
| | - type: map_at_1000 |
| | value: 43.137 |
| | - type: map_at_3 |
| | value: 39.882 |
| | - type: map_at_5 |
| | value: 41.379 |
| | - type: mrr_at_1 |
| | value: 38.933 |
| | - type: mrr_at_10 |
| | value: 48.344 |
| | - type: mrr_at_100 |
| | value: 48.344 |
| | - type: mrr_at_1000 |
| | value: 48.344 |
| | - type: mrr_at_3 |
| | value: 45.652 |
| | - type: mrr_at_5 |
| | value: 46.877 |
| | - type: ndcg_at_1 |
| | value: 38.933 |
| | - type: ndcg_at_10 |
| | value: 49.964 |
| | - type: ndcg_at_100 |
| | value: 49.242000000000004 |
| | - type: ndcg_at_1000 |
| | value: 49.222 |
| | - type: ndcg_at_3 |
| | value: 44.605 |
| | - type: ndcg_at_5 |
| | value: 46.501999999999995 |
| | - type: precision_at_1 |
| | value: 38.933 |
| | - type: precision_at_10 |
| | value: 9.427000000000001 |
| | - type: precision_at_100 |
| | value: 0.943 |
| | - type: precision_at_1000 |
| | value: 0.094 |
| | - type: precision_at_3 |
| | value: 20.685000000000002 |
| | - type: precision_at_5 |
| | value: 14.585 |
| | - type: recall_at_1 |
| | value: 32.058 |
| | - type: recall_at_10 |
| | value: 63.074 |
| | - type: recall_at_100 |
| | value: 63.074 |
| | - type: recall_at_1000 |
| | value: 63.074 |
| | - type: recall_at_3 |
| | value: 47.509 |
| | - type: recall_at_5 |
| | value: 52.455 |
| | - type: map_at_1 |
| | value: 26.029000000000003 |
| | - type: map_at_10 |
| | value: 34.646 |
| | - type: map_at_100 |
| | value: 34.646 |
| | - type: map_at_1000 |
| | value: 34.646 |
| | - type: map_at_3 |
| | value: 31.456 |
| | - type: map_at_5 |
| | value: 33.138 |
| | - type: mrr_at_1 |
| | value: 28.281 |
| | - type: mrr_at_10 |
| | value: 36.905 |
| | - type: mrr_at_100 |
| | value: 36.905 |
| | - type: mrr_at_1000 |
| | value: 36.905 |
| | - type: mrr_at_3 |
| | value: 34.011 |
| | - type: mrr_at_5 |
| | value: 35.638 |
| | - type: ndcg_at_1 |
| | value: 28.281 |
| | - type: ndcg_at_10 |
| | value: 40.159 |
| | - type: ndcg_at_100 |
| | value: 40.159 |
| | - type: ndcg_at_1000 |
| | value: 40.159 |
| | - type: ndcg_at_3 |
| | value: 33.995 |
| | - type: ndcg_at_5 |
| | value: 36.836999999999996 |
| | - type: precision_at_1 |
| | value: 28.281 |
| | - type: precision_at_10 |
| | value: 6.358999999999999 |
| | - type: precision_at_100 |
| | value: 0.636 |
| | - type: precision_at_1000 |
| | value: 0.064 |
| | - type: precision_at_3 |
| | value: 14.233 |
| | - type: precision_at_5 |
| | value: 10.314 |
| | - type: recall_at_1 |
| | value: 26.029000000000003 |
| | - type: recall_at_10 |
| | value: 55.08 |
| | - type: recall_at_100 |
| | value: 55.08 |
| | - type: recall_at_1000 |
| | value: 55.08 |
| | - type: recall_at_3 |
| | value: 38.487 |
| | - type: recall_at_5 |
| | value: 45.308 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB ClimateFEVER |
| | type: climate-fever |
| | config: default |
| | split: test |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 12.842999999999998 |
| | - type: map_at_10 |
| | value: 22.101000000000003 |
| | - type: map_at_100 |
| | value: 24.319 |
| | - type: map_at_1000 |
| | value: 24.51 |
| | - type: map_at_3 |
| | value: 18.372 |
| | - type: map_at_5 |
| | value: 20.323 |
| | - type: mrr_at_1 |
| | value: 27.948 |
| | - type: mrr_at_10 |
| | value: 40.321 |
| | - type: mrr_at_100 |
| | value: 41.262 |
| | - type: mrr_at_1000 |
| | value: 41.297 |
| | - type: mrr_at_3 |
| | value: 36.558 |
| | - type: mrr_at_5 |
| | value: 38.824999999999996 |
| | - type: ndcg_at_1 |
| | value: 27.948 |
| | - type: ndcg_at_10 |
| | value: 30.906 |
| | - type: ndcg_at_100 |
| | value: 38.986 |
| | - type: ndcg_at_1000 |
| | value: 42.136 |
| | - type: ndcg_at_3 |
| | value: 24.911 |
| | - type: ndcg_at_5 |
| | value: 27.168999999999997 |
| | - type: precision_at_1 |
| | value: 27.948 |
| | - type: precision_at_10 |
| | value: 9.798 |
| | - type: precision_at_100 |
| | value: 1.8399999999999999 |
| | - type: precision_at_1000 |
| | value: 0.243 |
| | - type: precision_at_3 |
| | value: 18.328 |
| | - type: precision_at_5 |
| | value: 14.502 |
| | - type: recall_at_1 |
| | value: 12.842999999999998 |
| | - type: recall_at_10 |
| | value: 37.245 |
| | - type: recall_at_100 |
| | value: 64.769 |
| | - type: recall_at_1000 |
| | value: 82.055 |
| | - type: recall_at_3 |
| | value: 23.159 |
| | - type: recall_at_5 |
| | value: 29.113 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB DBPedia |
| | type: dbpedia-entity |
| | config: default |
| | split: test |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 8.934000000000001 |
| | - type: map_at_10 |
| | value: 21.915000000000003 |
| | - type: map_at_100 |
| | value: 21.915000000000003 |
| | - type: map_at_1000 |
| | value: 21.915000000000003 |
| | - type: map_at_3 |
| | value: 14.623 |
| | - type: map_at_5 |
| | value: 17.841 |
| | - type: mrr_at_1 |
| | value: 71.25 |
| | - type: mrr_at_10 |
| | value: 78.994 |
| | - type: mrr_at_100 |
| | value: 78.994 |
| | - type: mrr_at_1000 |
| | value: 78.994 |
| | - type: mrr_at_3 |
| | value: 77.208 |
| | - type: mrr_at_5 |
| | value: 78.55799999999999 |
| | - type: ndcg_at_1 |
| | value: 60.62499999999999 |
| | - type: ndcg_at_10 |
| | value: 46.604 |
| | - type: ndcg_at_100 |
| | value: 35.653 |
| | - type: ndcg_at_1000 |
| | value: 35.531 |
| | - type: ndcg_at_3 |
| | value: 50.605 |
| | - type: ndcg_at_5 |
| | value: 48.730000000000004 |
| | - type: precision_at_1 |
| | value: 71.25 |
| | - type: precision_at_10 |
| | value: 37.75 |
| | - type: precision_at_100 |
| | value: 3.775 |
| | - type: precision_at_1000 |
| | value: 0.377 |
| | - type: precision_at_3 |
| | value: 54.417 |
| | - type: precision_at_5 |
| | value: 48.15 |
| | - type: recall_at_1 |
| | value: 8.934000000000001 |
| | - type: recall_at_10 |
| | value: 28.471000000000004 |
| | - type: recall_at_100 |
| | value: 28.471000000000004 |
| | - type: recall_at_1000 |
| | value: 28.471000000000004 |
| | - type: recall_at_3 |
| | value: 16.019 |
| | - type: recall_at_5 |
| | value: 21.410999999999998 |
| | - task: |
| | type: Classification |
| | dataset: |
| | name: MTEB EmotionClassification |
| | type: mteb/emotion |
| | config: default |
| | split: test |
| | revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
| | metrics: |
| | - type: accuracy |
| | value: 52.81 |
| | - type: f1 |
| | value: 47.987573380720114 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB FEVER |
| | type: fever |
| | config: default |
| | split: test |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 66.81899999999999 |
| | - type: map_at_10 |
| | value: 78.034 |
| | - type: map_at_100 |
| | value: 78.034 |
| | - type: map_at_1000 |
| | value: 78.034 |
| | - type: map_at_3 |
| | value: 76.43100000000001 |
| | - type: map_at_5 |
| | value: 77.515 |
| | - type: mrr_at_1 |
| | value: 71.542 |
| | - type: mrr_at_10 |
| | value: 81.638 |
| | - type: mrr_at_100 |
| | value: 81.638 |
| | - type: mrr_at_1000 |
| | value: 81.638 |
| | - type: mrr_at_3 |
| | value: 80.403 |
| | - type: mrr_at_5 |
| | value: 81.256 |
| | - type: ndcg_at_1 |
| | value: 71.542 |
| | - type: ndcg_at_10 |
| | value: 82.742 |
| | - type: ndcg_at_100 |
| | value: 82.741 |
| | - type: ndcg_at_1000 |
| | value: 82.741 |
| | - type: ndcg_at_3 |
| | value: 80.039 |
| | - type: ndcg_at_5 |
| | value: 81.695 |
| | - type: precision_at_1 |
| | value: 71.542 |
| | - type: precision_at_10 |
| | value: 10.387 |
| | - type: precision_at_100 |
| | value: 1.039 |
| | - type: precision_at_1000 |
| | value: 0.104 |
| | - type: precision_at_3 |
| | value: 31.447999999999997 |
| | - type: precision_at_5 |
| | value: 19.91 |
| | - type: recall_at_1 |
| | value: 66.81899999999999 |
| | - type: recall_at_10 |
| | value: 93.372 |
| | - type: recall_at_100 |
| | value: 93.372 |
| | - type: recall_at_1000 |
| | value: 93.372 |
| | - type: recall_at_3 |
| | value: 86.33 |
| | - type: recall_at_5 |
| | value: 90.347 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB FiQA2018 |
| | type: fiqa |
| | config: default |
| | split: test |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 31.158 |
| | - type: map_at_10 |
| | value: 52.017 |
| | - type: map_at_100 |
| | value: 54.259 |
| | - type: map_at_1000 |
| | value: 54.367 |
| | - type: map_at_3 |
| | value: 45.738 |
| | - type: map_at_5 |
| | value: 49.283 |
| | - type: mrr_at_1 |
| | value: 57.87 |
| | - type: mrr_at_10 |
| | value: 66.215 |
| | - type: mrr_at_100 |
| | value: 66.735 |
| | - type: mrr_at_1000 |
| | value: 66.75 |
| | - type: mrr_at_3 |
| | value: 64.043 |
| | - type: mrr_at_5 |
| | value: 65.116 |
| | - type: ndcg_at_1 |
| | value: 57.87 |
| | - type: ndcg_at_10 |
| | value: 59.946999999999996 |
| | - type: ndcg_at_100 |
| | value: 66.31099999999999 |
| | - type: ndcg_at_1000 |
| | value: 67.75999999999999 |
| | - type: ndcg_at_3 |
| | value: 55.483000000000004 |
| | - type: ndcg_at_5 |
| | value: 56.891000000000005 |
| | - type: precision_at_1 |
| | value: 57.87 |
| | - type: precision_at_10 |
| | value: 16.497 |
| | - type: precision_at_100 |
| | value: 2.321 |
| | - type: precision_at_1000 |
| | value: 0.258 |
| | - type: precision_at_3 |
| | value: 37.14 |
| | - type: precision_at_5 |
| | value: 27.067999999999998 |
| | - type: recall_at_1 |
| | value: 31.158 |
| | - type: recall_at_10 |
| | value: 67.381 |
| | - type: recall_at_100 |
| | value: 89.464 |
| | - type: recall_at_1000 |
| | value: 97.989 |
| | - type: recall_at_3 |
| | value: 50.553000000000004 |
| | - type: recall_at_5 |
| | value: 57.824 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB HotpotQA |
| | type: hotpotqa |
| | config: default |
| | split: test |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 42.073 |
| | - type: map_at_10 |
| | value: 72.418 |
| | - type: map_at_100 |
| | value: 73.175 |
| | - type: map_at_1000 |
| | value: 73.215 |
| | - type: map_at_3 |
| | value: 68.791 |
| | - type: map_at_5 |
| | value: 71.19 |
| | - type: mrr_at_1 |
| | value: 84.146 |
| | - type: mrr_at_10 |
| | value: 88.994 |
| | - type: mrr_at_100 |
| | value: 89.116 |
| | - type: mrr_at_1000 |
| | value: 89.12 |
| | - type: mrr_at_3 |
| | value: 88.373 |
| | - type: mrr_at_5 |
| | value: 88.82 |
| | - type: ndcg_at_1 |
| | value: 84.146 |
| | - type: ndcg_at_10 |
| | value: 79.404 |
| | - type: ndcg_at_100 |
| | value: 81.83200000000001 |
| | - type: ndcg_at_1000 |
| | value: 82.524 |
| | - type: ndcg_at_3 |
| | value: 74.595 |
| | - type: ndcg_at_5 |
| | value: 77.474 |
| | - type: precision_at_1 |
| | value: 84.146 |
| | - type: precision_at_10 |
| | value: 16.753999999999998 |
| | - type: precision_at_100 |
| | value: 1.8599999999999999 |
| | - type: precision_at_1000 |
| | value: 0.19499999999999998 |
| | - type: precision_at_3 |
| | value: 48.854 |
| | - type: precision_at_5 |
| | value: 31.579 |
| | - type: recall_at_1 |
| | value: 42.073 |
| | - type: recall_at_10 |
| | value: 83.768 |
| | - type: recall_at_100 |
| | value: 93.018 |
| | - type: recall_at_1000 |
| | value: 97.481 |
| | - type: recall_at_3 |
| | value: 73.282 |
| | - type: recall_at_5 |
| | value: 78.947 |
| | - task: |
| | type: Classification |
| | dataset: |
| | name: MTEB ImdbClassification |
| | type: mteb/imdb |
| | config: default |
| | split: test |
| | revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
| | metrics: |
| | - type: accuracy |
| | value: 94.9968 |
| | - type: ap |
| | value: 92.93892195862824 |
| | - type: f1 |
| | value: 94.99327998213761 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB MSMARCO |
| | type: msmarco |
| | config: default |
| | split: dev |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 21.698 |
| | - type: map_at_10 |
| | value: 34.585 |
| | - type: map_at_100 |
| | value: 35.782000000000004 |
| | - type: map_at_1000 |
| | value: 35.825 |
| | - type: map_at_3 |
| | value: 30.397999999999996 |
| | - type: map_at_5 |
| | value: 32.72 |
| | - type: mrr_at_1 |
| | value: 22.192 |
| | - type: mrr_at_10 |
| | value: 35.085 |
| | - type: mrr_at_100 |
| | value: 36.218 |
| | - type: mrr_at_1000 |
| | value: 36.256 |
| | - type: mrr_at_3 |
| | value: 30.986000000000004 |
| | - type: mrr_at_5 |
| | value: 33.268 |
| | - type: ndcg_at_1 |
| | value: 22.192 |
| | - type: ndcg_at_10 |
| | value: 41.957 |
| | - type: ndcg_at_100 |
| | value: 47.658 |
| | - type: ndcg_at_1000 |
| | value: 48.697 |
| | - type: ndcg_at_3 |
| | value: 33.433 |
| | - type: ndcg_at_5 |
| | value: 37.551 |
| | - type: precision_at_1 |
| | value: 22.192 |
| | - type: precision_at_10 |
| | value: 6.781 |
| | - type: precision_at_100 |
| | value: 0.963 |
| | - type: precision_at_1000 |
| | value: 0.105 |
| | - type: precision_at_3 |
| | value: 14.365 |
| | - type: precision_at_5 |
| | value: 10.713000000000001 |
| | - type: recall_at_1 |
| | value: 21.698 |
| | - type: recall_at_10 |
| | value: 64.79 |
| | - type: recall_at_100 |
| | value: 91.071 |
| | - type: recall_at_1000 |
| | value: 98.883 |
| | - type: recall_at_3 |
| | value: 41.611 |
| | - type: recall_at_5 |
| | value: 51.459999999999994 |
| | - task: |
| | type: Classification |
| | dataset: |
| | name: MTEB MTOPDomainClassification (en) |
| | type: mteb/mtop_domain |
| | config: en |
| | split: test |
| | revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| | metrics: |
| | - type: accuracy |
| | value: 96.15823073415413 |
| | - type: f1 |
| | value: 96.00362034963248 |
| | - task: |
| | type: Classification |
| | dataset: |
| | name: MTEB MTOPIntentClassification (en) |
| | type: mteb/mtop_intent |
| | config: en |
| | split: test |
| | revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| | metrics: |
| | - type: accuracy |
| | value: 87.12722298221614 |
| | - type: f1 |
| | value: 70.46888967516227 |
| | - task: |
| | type: Classification |
| | dataset: |
| | name: MTEB MassiveIntentClassification (en) |
| | type: mteb/amazon_massive_intent |
| | config: en |
| | split: test |
| | revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| | metrics: |
| | - type: accuracy |
| | value: 80.77673167451245 |
| | - type: f1 |
| | value: 77.60202561132175 |
| | - task: |
| | type: Classification |
| | dataset: |
| | name: MTEB MassiveScenarioClassification (en) |
| | type: mteb/amazon_massive_scenario |
| | config: en |
| | split: test |
| | revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| | metrics: |
| | - type: accuracy |
| | value: 82.09145931405514 |
| | - type: f1 |
| | value: 81.7701921473406 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | name: MTEB MedrxivClusteringP2P |
| | type: mteb/medrxiv-clustering-p2p |
| | config: default |
| | split: test |
| | revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
| | metrics: |
| | - type: v_measure |
| | value: 36.52153488185864 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | name: MTEB MedrxivClusteringS2S |
| | type: mteb/medrxiv-clustering-s2s |
| | config: default |
| | split: test |
| | revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
| | metrics: |
| | - type: v_measure |
| | value: 36.80090398444147 |
| | - task: |
| | type: Reranking |
| | dataset: |
| | name: MTEB MindSmallReranking |
| | type: mteb/mind_small |
| | config: default |
| | split: test |
| | revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
| | metrics: |
| | - type: map |
| | value: 31.807141746058605 |
| | - type: mrr |
| | value: 32.85025611455029 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB NFCorpus |
| | type: nfcorpus |
| | config: default |
| | split: test |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 6.920999999999999 |
| | - type: map_at_10 |
| | value: 16.049 |
| | - type: map_at_100 |
| | value: 16.049 |
| | - type: map_at_1000 |
| | value: 16.049 |
| | - type: map_at_3 |
| | value: 11.865 |
| | - type: map_at_5 |
| | value: 13.657 |
| | - type: mrr_at_1 |
| | value: 53.87 |
| | - type: mrr_at_10 |
| | value: 62.291 |
| | - type: mrr_at_100 |
| | value: 62.291 |
| | - type: mrr_at_1000 |
| | value: 62.291 |
| | - type: mrr_at_3 |
| | value: 60.681 |
| | - type: mrr_at_5 |
| | value: 61.61 |
| | - type: ndcg_at_1 |
| | value: 51.23799999999999 |
| | - type: ndcg_at_10 |
| | value: 40.892 |
| | - type: ndcg_at_100 |
| | value: 26.951999999999998 |
| | - type: ndcg_at_1000 |
| | value: 26.474999999999998 |
| | - type: ndcg_at_3 |
| | value: 46.821 |
| | - type: ndcg_at_5 |
| | value: 44.333 |
| | - type: precision_at_1 |
| | value: 53.251000000000005 |
| | - type: precision_at_10 |
| | value: 30.124000000000002 |
| | - type: precision_at_100 |
| | value: 3.012 |
| | - type: precision_at_1000 |
| | value: 0.301 |
| | - type: precision_at_3 |
| | value: 43.55 |
| | - type: precision_at_5 |
| | value: 38.266 |
| | - type: recall_at_1 |
| | value: 6.920999999999999 |
| | - type: recall_at_10 |
| | value: 20.852 |
| | - type: recall_at_100 |
| | value: 20.852 |
| | - type: recall_at_1000 |
| | value: 20.852 |
| | - type: recall_at_3 |
| | value: 13.628000000000002 |
| | - type: recall_at_5 |
| | value: 16.273 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB NQ |
| | type: nq |
| | config: default |
| | split: test |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 46.827999999999996 |
| | - type: map_at_10 |
| | value: 63.434000000000005 |
| | - type: map_at_100 |
| | value: 63.434000000000005 |
| | - type: map_at_1000 |
| | value: 63.434000000000005 |
| | - type: map_at_3 |
| | value: 59.794000000000004 |
| | - type: map_at_5 |
| | value: 62.08 |
| | - type: mrr_at_1 |
| | value: 52.288999999999994 |
| | - type: mrr_at_10 |
| | value: 65.95 |
| | - type: mrr_at_100 |
| | value: 65.95 |
| | - type: mrr_at_1000 |
| | value: 65.95 |
| | - type: mrr_at_3 |
| | value: 63.413 |
| | - type: mrr_at_5 |
| | value: 65.08 |
| | - type: ndcg_at_1 |
| | value: 52.288999999999994 |
| | - type: ndcg_at_10 |
| | value: 70.301 |
| | - type: ndcg_at_100 |
| | value: 70.301 |
| | - type: ndcg_at_1000 |
| | value: 70.301 |
| | - type: ndcg_at_3 |
| | value: 63.979 |
| | - type: ndcg_at_5 |
| | value: 67.582 |
| | - type: precision_at_1 |
| | value: 52.288999999999994 |
| | - type: precision_at_10 |
| | value: 10.576 |
| | - type: precision_at_100 |
| | value: 1.058 |
| | - type: precision_at_1000 |
| | value: 0.106 |
| | - type: precision_at_3 |
| | value: 28.177000000000003 |
| | - type: precision_at_5 |
| | value: 19.073 |
| | - type: recall_at_1 |
| | value: 46.827999999999996 |
| | - type: recall_at_10 |
| | value: 88.236 |
| | - type: recall_at_100 |
| | value: 88.236 |
| | - type: recall_at_1000 |
| | value: 88.236 |
| | - type: recall_at_3 |
| | value: 72.371 |
| | - type: recall_at_5 |
| | value: 80.56 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB QuoraRetrieval |
| | type: quora |
| | config: default |
| | split: test |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 71.652 |
| | - type: map_at_10 |
| | value: 85.953 |
| | - type: map_at_100 |
| | value: 85.953 |
| | - type: map_at_1000 |
| | value: 85.953 |
| | - type: map_at_3 |
| | value: 83.05399999999999 |
| | - type: map_at_5 |
| | value: 84.89 |
| | - type: mrr_at_1 |
| | value: 82.42 |
| | - type: mrr_at_10 |
| | value: 88.473 |
| | - type: mrr_at_100 |
| | value: 88.473 |
| | - type: mrr_at_1000 |
| | value: 88.473 |
| | - type: mrr_at_3 |
| | value: 87.592 |
| | - type: mrr_at_5 |
| | value: 88.211 |
| | - type: ndcg_at_1 |
| | value: 82.44 |
| | - type: ndcg_at_10 |
| | value: 89.467 |
| | - type: ndcg_at_100 |
| | value: 89.33 |
| | - type: ndcg_at_1000 |
| | value: 89.33 |
| | - type: ndcg_at_3 |
| | value: 86.822 |
| | - type: ndcg_at_5 |
| | value: 88.307 |
| | - type: precision_at_1 |
| | value: 82.44 |
| | - type: precision_at_10 |
| | value: 13.616 |
| | - type: precision_at_100 |
| | value: 1.362 |
| | - type: precision_at_1000 |
| | value: 0.136 |
| | - type: precision_at_3 |
| | value: 38.117000000000004 |
| | - type: precision_at_5 |
| | value: 25.05 |
| | - type: recall_at_1 |
| | value: 71.652 |
| | - type: recall_at_10 |
| | value: 96.224 |
| | - type: recall_at_100 |
| | value: 96.224 |
| | - type: recall_at_1000 |
| | value: 96.224 |
| | - type: recall_at_3 |
| | value: 88.571 |
| | - type: recall_at_5 |
| | value: 92.812 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | name: MTEB RedditClustering |
| | type: mteb/reddit-clustering |
| | config: default |
| | split: test |
| | revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| | metrics: |
| | - type: v_measure |
| | value: 61.295010338050474 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | name: MTEB RedditClusteringP2P |
| | type: mteb/reddit-clustering-p2p |
| | config: default |
| | split: test |
| | revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
| | metrics: |
| | - type: v_measure |
| | value: 67.26380819328142 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB SCIDOCS |
| | type: scidocs |
| | config: default |
| | split: test |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 5.683 |
| | - type: map_at_10 |
| | value: 14.924999999999999 |
| | - type: map_at_100 |
| | value: 17.532 |
| | - type: map_at_1000 |
| | value: 17.875 |
| | - type: map_at_3 |
| | value: 10.392 |
| | - type: map_at_5 |
| | value: 12.592 |
| | - type: mrr_at_1 |
| | value: 28.000000000000004 |
| | - type: mrr_at_10 |
| | value: 39.951 |
| | - type: mrr_at_100 |
| | value: 41.025 |
| | - type: mrr_at_1000 |
| | value: 41.056 |
| | - type: mrr_at_3 |
| | value: 36.317 |
| | - type: mrr_at_5 |
| | value: 38.412 |
| | - type: ndcg_at_1 |
| | value: 28.000000000000004 |
| | - type: ndcg_at_10 |
| | value: 24.410999999999998 |
| | - type: ndcg_at_100 |
| | value: 33.79 |
| | - type: ndcg_at_1000 |
| | value: 39.035 |
| | - type: ndcg_at_3 |
| | value: 22.845 |
| | - type: ndcg_at_5 |
| | value: 20.080000000000002 |
| | - type: precision_at_1 |
| | value: 28.000000000000004 |
| | - type: precision_at_10 |
| | value: 12.790000000000001 |
| | - type: precision_at_100 |
| | value: 2.633 |
| | - type: precision_at_1000 |
| | value: 0.388 |
| | - type: precision_at_3 |
| | value: 21.367 |
| | - type: precision_at_5 |
| | value: 17.7 |
| | - type: recall_at_1 |
| | value: 5.683 |
| | - type: recall_at_10 |
| | value: 25.91 |
| | - type: recall_at_100 |
| | value: 53.443 |
| | - type: recall_at_1000 |
| | value: 78.73 |
| | - type: recall_at_3 |
| | value: 13.003 |
| | - type: recall_at_5 |
| | value: 17.932000000000002 |
| | - task: |
| | type: STS |
| | dataset: |
| | name: MTEB SICK-R |
| | type: mteb/sickr-sts |
| | config: default |
| | split: test |
| | revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 84.677978681023 |
| | - type: cos_sim_spearman |
| | value: 83.13093441058189 |
| | - type: euclidean_pearson |
| | value: 83.35535759341572 |
| | - type: euclidean_spearman |
| | value: 83.42583744219611 |
| | - type: manhattan_pearson |
| | value: 83.2243124045889 |
| | - type: manhattan_spearman |
| | value: 83.39801618652632 |
| | - task: |
| | type: STS |
| | dataset: |
| | name: MTEB STS12 |
| | type: mteb/sts12-sts |
| | config: default |
| | split: test |
| | revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 81.68960206569666 |
| | - type: cos_sim_spearman |
| | value: 77.3368966488535 |
| | - type: euclidean_pearson |
| | value: 77.62828980560303 |
| | - type: euclidean_spearman |
| | value: 76.77951481444651 |
| | - type: manhattan_pearson |
| | value: 77.88637240839041 |
| | - type: manhattan_spearman |
| | value: 77.22157841466188 |
| | - task: |
| | type: STS |
| | dataset: |
| | name: MTEB STS13 |
| | type: mteb/sts13-sts |
| | config: default |
| | split: test |
| | revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 84.18745821650724 |
| | - type: cos_sim_spearman |
| | value: 85.04423285574542 |
| | - type: euclidean_pearson |
| | value: 85.46604816931023 |
| | - type: euclidean_spearman |
| | value: 85.5230593932974 |
| | - type: manhattan_pearson |
| | value: 85.57912805986261 |
| | - type: manhattan_spearman |
| | value: 85.65955905111873 |
| | - task: |
| | type: STS |
| | dataset: |
| | name: MTEB STS14 |
| | type: mteb/sts14-sts |
| | config: default |
| | split: test |
| | revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 83.6715333300355 |
| | - type: cos_sim_spearman |
| | value: 82.9058522514908 |
| | - type: euclidean_pearson |
| | value: 83.9640357424214 |
| | - type: euclidean_spearman |
| | value: 83.60415457472637 |
| | - type: manhattan_pearson |
| | value: 84.05621005853469 |
| | - type: manhattan_spearman |
| | value: 83.87077724707746 |
| | - task: |
| | type: STS |
| | dataset: |
| | name: MTEB STS15 |
| | type: mteb/sts15-sts |
| | config: default |
| | split: test |
| | revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 87.82422928098886 |
| | - type: cos_sim_spearman |
| | value: 88.12660311894628 |
| | - type: euclidean_pearson |
| | value: 87.50974805056555 |
| | - type: euclidean_spearman |
| | value: 87.91957275596677 |
| | - type: manhattan_pearson |
| | value: 87.74119404878883 |
| | - type: manhattan_spearman |
| | value: 88.2808922165719 |
| | - task: |
| | type: STS |
| | dataset: |
| | name: MTEB STS16 |
| | type: mteb/sts16-sts |
| | config: default |
| | split: test |
| | revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 84.80605838552093 |
| | - type: cos_sim_spearman |
| | value: 86.24123388765678 |
| | - type: euclidean_pearson |
| | value: 85.32648347339814 |
| | - type: euclidean_spearman |
| | value: 85.60046671950158 |
| | - type: manhattan_pearson |
| | value: 85.53800168487811 |
| | - type: manhattan_spearman |
| | value: 85.89542420480763 |
| | - task: |
| | type: STS |
| | dataset: |
| | name: MTEB STS17 (en-en) |
| | type: mteb/sts17-crosslingual-sts |
| | config: en-en |
| | split: test |
| | revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 89.87540978988132 |
| | - type: cos_sim_spearman |
| | value: 90.12715295099461 |
| | - type: euclidean_pearson |
| | value: 91.61085993525275 |
| | - type: euclidean_spearman |
| | value: 91.31835942311758 |
| | - type: manhattan_pearson |
| | value: 91.57500202032934 |
| | - type: manhattan_spearman |
| | value: 91.1790925526635 |
| | - task: |
| | type: STS |
| | dataset: |
| | name: MTEB STS22 (en) |
| | type: mteb/sts22-crosslingual-sts |
| | config: en |
| | split: test |
| | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 69.87136205329556 |
| | - type: cos_sim_spearman |
| | value: 68.6253154635078 |
| | - type: euclidean_pearson |
| | value: 68.91536015034222 |
| | - type: euclidean_spearman |
| | value: 67.63744649352542 |
| | - type: manhattan_pearson |
| | value: 69.2000713045275 |
| | - type: manhattan_spearman |
| | value: 68.16002901587316 |
| | - task: |
| | type: STS |
| | dataset: |
| | name: MTEB STSBenchmark |
| | type: mteb/stsbenchmark-sts |
| | config: default |
| | split: test |
| | revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 85.21849551039082 |
| | - type: cos_sim_spearman |
| | value: 85.6392959372461 |
| | - type: euclidean_pearson |
| | value: 85.92050852609488 |
| | - type: euclidean_spearman |
| | value: 85.97205649009734 |
| | - type: manhattan_pearson |
| | value: 86.1031154802254 |
| | - type: manhattan_spearman |
| | value: 86.26791155517466 |
| | - task: |
| | type: Reranking |
| | dataset: |
| | name: MTEB SciDocsRR |
| | type: mteb/scidocs-reranking |
| | config: default |
| | split: test |
| | revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| | metrics: |
| | - type: map |
| | value: 86.83953958636627 |
| | - type: mrr |
| | value: 96.71167612344082 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB SciFact |
| | type: scifact |
| | config: default |
| | split: test |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 64.994 |
| | - type: map_at_10 |
| | value: 74.763 |
| | - type: map_at_100 |
| | value: 75.127 |
| | - type: map_at_1000 |
| | value: 75.143 |
| | - type: map_at_3 |
| | value: 71.824 |
| | - type: map_at_5 |
| | value: 73.71 |
| | - type: mrr_at_1 |
| | value: 68.333 |
| | - type: mrr_at_10 |
| | value: 75.749 |
| | - type: mrr_at_100 |
| | value: 75.922 |
| | - type: mrr_at_1000 |
| | value: 75.938 |
| | - type: mrr_at_3 |
| | value: 73.556 |
| | - type: mrr_at_5 |
| | value: 74.739 |
| | - type: ndcg_at_1 |
| | value: 68.333 |
| | - type: ndcg_at_10 |
| | value: 79.174 |
| | - type: ndcg_at_100 |
| | value: 80.41 |
| | - type: ndcg_at_1000 |
| | value: 80.804 |
| | - type: ndcg_at_3 |
| | value: 74.361 |
| | - type: ndcg_at_5 |
| | value: 76.861 |
| | - type: precision_at_1 |
| | value: 68.333 |
| | - type: precision_at_10 |
| | value: 10.333 |
| | - type: precision_at_100 |
| | value: 1.0999999999999999 |
| | - type: precision_at_1000 |
| | value: 0.11299999999999999 |
| | - type: precision_at_3 |
| | value: 28.778 |
| | - type: precision_at_5 |
| | value: 19.067 |
| | - type: recall_at_1 |
| | value: 64.994 |
| | - type: recall_at_10 |
| | value: 91.822 |
| | - type: recall_at_100 |
| | value: 97.0 |
| | - type: recall_at_1000 |
| | value: 100.0 |
| | - type: recall_at_3 |
| | value: 78.878 |
| | - type: recall_at_5 |
| | value: 85.172 |
| | - task: |
| | type: PairClassification |
| | dataset: |
| | name: MTEB SprintDuplicateQuestions |
| | type: mteb/sprintduplicatequestions-pairclassification |
| | config: default |
| | split: test |
| | revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
| | metrics: |
| | - type: cos_sim_accuracy |
| | value: 99.72079207920792 |
| | - type: cos_sim_ap |
| | value: 93.00265215525152 |
| | - type: cos_sim_f1 |
| | value: 85.06596306068602 |
| | - type: cos_sim_precision |
| | value: 90.05586592178771 |
| | - type: cos_sim_recall |
| | value: 80.60000000000001 |
| | - type: dot_accuracy |
| | value: 99.66039603960397 |
| | - type: dot_ap |
| | value: 91.22371407479089 |
| | - type: dot_f1 |
| | value: 82.34693877551021 |
| | - type: dot_precision |
| | value: 84.0625 |
| | - type: dot_recall |
| | value: 80.7 |
| | - type: euclidean_accuracy |
| | value: 99.71881188118812 |
| | - type: euclidean_ap |
| | value: 92.88449963304728 |
| | - type: euclidean_f1 |
| | value: 85.19480519480518 |
| | - type: euclidean_precision |
| | value: 88.64864864864866 |
| | - type: euclidean_recall |
| | value: 82.0 |
| | - type: manhattan_accuracy |
| | value: 99.73267326732673 |
| | - type: manhattan_ap |
| | value: 93.23055393056883 |
| | - type: manhattan_f1 |
| | value: 85.88957055214725 |
| | - type: manhattan_precision |
| | value: 87.86610878661088 |
| | - type: manhattan_recall |
| | value: 84.0 |
| | - type: max_accuracy |
| | value: 99.73267326732673 |
| | - type: max_ap |
| | value: 93.23055393056883 |
| | - type: max_f1 |
| | value: 85.88957055214725 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | name: MTEB StackExchangeClustering |
| | type: mteb/stackexchange-clustering |
| | config: default |
| | split: test |
| | revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
| | metrics: |
| | - type: v_measure |
| | value: 77.3305735900358 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | name: MTEB StackExchangeClusteringP2P |
| | type: mteb/stackexchange-clustering-p2p |
| | config: default |
| | split: test |
| | revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
| | metrics: |
| | - type: v_measure |
| | value: 41.32967136540674 |
| | - task: |
| | type: Reranking |
| | dataset: |
| | name: MTEB StackOverflowDupQuestions |
| | type: mteb/stackoverflowdupquestions-reranking |
| | config: default |
| | split: test |
| | revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
| | metrics: |
| | - type: map |
| | value: 55.95514866379359 |
| | - type: mrr |
| | value: 56.95423245055598 |
| | - task: |
| | type: Summarization |
| | dataset: |
| | name: MTEB SummEval |
| | type: mteb/summeval |
| | config: default |
| | split: test |
| | revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 30.783007208997144 |
| | - type: cos_sim_spearman |
| | value: 30.373444721540533 |
| | - type: dot_pearson |
| | value: 29.210604111143905 |
| | - type: dot_spearman |
| | value: 29.98809758085659 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB TRECCOVID |
| | type: trec-covid |
| | config: default |
| | split: test |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 0.234 |
| | - type: map_at_10 |
| | value: 1.894 |
| | - type: map_at_100 |
| | value: 1.894 |
| | - type: map_at_1000 |
| | value: 1.894 |
| | - type: map_at_3 |
| | value: 0.636 |
| | - type: map_at_5 |
| | value: 1.0 |
| | - type: mrr_at_1 |
| | value: 88.0 |
| | - type: mrr_at_10 |
| | value: 93.667 |
| | - type: mrr_at_100 |
| | value: 93.667 |
| | - type: mrr_at_1000 |
| | value: 93.667 |
| | - type: mrr_at_3 |
| | value: 93.667 |
| | - type: mrr_at_5 |
| | value: 93.667 |
| | - type: ndcg_at_1 |
| | value: 85.0 |
| | - type: ndcg_at_10 |
| | value: 74.798 |
| | - type: ndcg_at_100 |
| | value: 16.462 |
| | - type: ndcg_at_1000 |
| | value: 7.0889999999999995 |
| | - type: ndcg_at_3 |
| | value: 80.754 |
| | - type: ndcg_at_5 |
| | value: 77.319 |
| | - type: precision_at_1 |
| | value: 88.0 |
| | - type: precision_at_10 |
| | value: 78.0 |
| | - type: precision_at_100 |
| | value: 7.8 |
| | - type: precision_at_1000 |
| | value: 0.7799999999999999 |
| | - type: precision_at_3 |
| | value: 83.333 |
| | - type: precision_at_5 |
| | value: 80.80000000000001 |
| | - type: recall_at_1 |
| | value: 0.234 |
| | - type: recall_at_10 |
| | value: 2.093 |
| | - type: recall_at_100 |
| | value: 2.093 |
| | - type: recall_at_1000 |
| | value: 2.093 |
| | - type: recall_at_3 |
| | value: 0.662 |
| | - type: recall_at_5 |
| | value: 1.0739999999999998 |
| | - task: |
| | type: Retrieval |
| | dataset: |
| | name: MTEB Touche2020 |
| | type: webis-touche2020 |
| | config: default |
| | split: test |
| | revision: None |
| | metrics: |
| | - type: map_at_1 |
| | value: 2.703 |
| | - type: map_at_10 |
| | value: 10.866000000000001 |
| | - type: map_at_100 |
| | value: 10.866000000000001 |
| | - type: map_at_1000 |
| | value: 10.866000000000001 |
| | - type: map_at_3 |
| | value: 5.909 |
| | - type: map_at_5 |
| | value: 7.35 |
| | - type: mrr_at_1 |
| | value: 36.735 |
| | - type: mrr_at_10 |
| | value: 53.583000000000006 |
| | - type: mrr_at_100 |
| | value: 53.583000000000006 |
| | - type: mrr_at_1000 |
| | value: 53.583000000000006 |
| | - type: mrr_at_3 |
| | value: 49.32 |
| | - type: mrr_at_5 |
| | value: 51.769 |
| | - type: ndcg_at_1 |
| | value: 34.694 |
| | - type: ndcg_at_10 |
| | value: 27.926000000000002 |
| | - type: ndcg_at_100 |
| | value: 22.701 |
| | - type: ndcg_at_1000 |
| | value: 22.701 |
| | - type: ndcg_at_3 |
| | value: 32.073 |
| | - type: ndcg_at_5 |
| | value: 28.327999999999996 |
| | - type: precision_at_1 |
| | value: 36.735 |
| | - type: precision_at_10 |
| | value: 24.694 |
| | - type: precision_at_100 |
| | value: 2.469 |
| | - type: precision_at_1000 |
| | value: 0.247 |
| | - type: precision_at_3 |
| | value: 31.973000000000003 |
| | - type: precision_at_5 |
| | value: 26.939 |
| | - type: recall_at_1 |
| | value: 2.703 |
| | - type: recall_at_10 |
| | value: 17.702 |
| | - type: recall_at_100 |
| | value: 17.702 |
| | - type: recall_at_1000 |
| | value: 17.702 |
| | - type: recall_at_3 |
| | value: 7.208 |
| | - type: recall_at_5 |
| | value: 9.748999999999999 |
| | - task: |
| | type: Classification |
| | dataset: |
| | name: MTEB ToxicConversationsClassification |
| | type: mteb/toxic_conversations_50k |
| | config: default |
| | split: test |
| | revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
| | metrics: |
| | - type: accuracy |
| | value: 70.79960000000001 |
| | - type: ap |
| | value: 15.467565415565815 |
| | - type: f1 |
| | value: 55.28639823443618 |
| | - task: |
| | type: Classification |
| | dataset: |
| | name: MTEB TweetSentimentExtractionClassification |
| | type: mteb/tweet_sentiment_extraction |
| | config: default |
| | split: test |
| | revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| | metrics: |
| | - type: accuracy |
| | value: 64.7792869269949 |
| | - type: f1 |
| | value: 65.08597154774318 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | name: MTEB TwentyNewsgroupsClustering |
| | type: mteb/twentynewsgroups-clustering |
| | config: default |
| | split: test |
| | revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| | metrics: |
| | - type: v_measure |
| | value: 55.70352297774293 |
| | - task: |
| | type: PairClassification |
| | dataset: |
| | name: MTEB TwitterSemEval2015 |
| | type: mteb/twittersemeval2015-pairclassification |
| | config: default |
| | split: test |
| | revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
| | metrics: |
| | - type: cos_sim_accuracy |
| | value: 88.27561542588067 |
| | - type: cos_sim_ap |
| | value: 81.08262141256193 |
| | - type: cos_sim_f1 |
| | value: 73.82341501361338 |
| | - type: cos_sim_precision |
| | value: 72.5720112159062 |
| | - type: cos_sim_recall |
| | value: 75.11873350923483 |
| | - type: dot_accuracy |
| | value: 86.66030875603504 |
| | - type: dot_ap |
| | value: 76.6052349228621 |
| | - type: dot_f1 |
| | value: 70.13897280966768 |
| | - type: dot_precision |
| | value: 64.70457079152732 |
| | - type: dot_recall |
| | value: 76.56992084432717 |
| | - type: euclidean_accuracy |
| | value: 88.37098408535495 |
| | - type: euclidean_ap |
| | value: 81.12515230092113 |
| | - type: euclidean_f1 |
| | value: 74.10338225909379 |
| | - type: euclidean_precision |
| | value: 71.76761433868974 |
| | - type: euclidean_recall |
| | value: 76.59630606860158 |
| | - type: manhattan_accuracy |
| | value: 88.34118137926924 |
| | - type: manhattan_ap |
| | value: 80.95751834536561 |
| | - type: manhattan_f1 |
| | value: 73.9119496855346 |
| | - type: manhattan_precision |
| | value: 70.625 |
| | - type: manhattan_recall |
| | value: 77.5197889182058 |
| | - type: max_accuracy |
| | value: 88.37098408535495 |
| | - type: max_ap |
| | value: 81.12515230092113 |
| | - type: max_f1 |
| | value: 74.10338225909379 |
| | - task: |
| | type: PairClassification |
| | dataset: |
| | name: MTEB TwitterURLCorpus |
| | type: mteb/twitterurlcorpus-pairclassification |
| | config: default |
| | split: test |
| | revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
| | metrics: |
| | - type: cos_sim_accuracy |
| | value: 89.79896767182831 |
| | - type: cos_sim_ap |
| | value: 87.40071784061065 |
| | - type: cos_sim_f1 |
| | value: 79.87753144712087 |
| | - type: cos_sim_precision |
| | value: 76.67304015296367 |
| | - type: cos_sim_recall |
| | value: 83.3615645210964 |
| | - type: dot_accuracy |
| | value: 88.95486474948578 |
| | - type: dot_ap |
| | value: 86.00227979119943 |
| | - type: dot_f1 |
| | value: 78.54601474525914 |
| | - type: dot_precision |
| | value: 75.00525394045535 |
| | - type: dot_recall |
| | value: 82.43763473975977 |
| | - type: euclidean_accuracy |
| | value: 89.7892653393876 |
| | - type: euclidean_ap |
| | value: 87.42174706480819 |
| | - type: euclidean_f1 |
| | value: 80.07283321194465 |
| | - type: euclidean_precision |
| | value: 75.96738529574351 |
| | - type: euclidean_recall |
| | value: 84.6473668001232 |
| | - type: manhattan_accuracy |
| | value: 89.8474793340319 |
| | - type: manhattan_ap |
| | value: 87.47814292587448 |
| | - type: manhattan_f1 |
| | value: 80.15461150280949 |
| | - type: manhattan_precision |
| | value: 74.88798234468 |
| | - type: manhattan_recall |
| | value: 86.21804742839544 |
| | - type: max_accuracy |
| | value: 89.8474793340319 |
| | - type: max_ap |
| | value: 87.47814292587448 |
| | - type: max_f1 |
| | value: 80.15461150280949 |
| | --- |
| | |
| | <div style="width: auto; margin-left: auto; margin-right: auto"> |
| | <img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;"> |
| | </div> |
| |
|
| | [](https://tensorblock.co) |
| | [](https://twitter.com/tensorblock_aoi) |
| | [](https://discord.gg/Ej5NmeHFf2) |
| | [](https://github.com/TensorBlock) |
| | [](https://t.me/TensorBlock) |
| |
|
| |
|
| | ## GritLM/GritLM-7B - GGUF |
| |
|
| | This repo contains GGUF format model files for [GritLM/GritLM-7B](https://huggingface.co/GritLM/GritLM-7B). |
| |
|
| | The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d). |
| |
|
| |
|
| | ## Our projects |
| | <table border="1" cellspacing="0" cellpadding="10"> |
| | <tr> |
| | <th colspan="2" style="font-size: 25px;">Forge</th> |
| | </tr> |
| | <tr> |
| | <th colspan="2"> |
| | <img src="https://imgur.com/faI5UKh.jpeg" alt="Forge Project" width="900"/> |
| | </th> |
| | </tr> |
| | <tr> |
| | <th colspan="2">An OpenAI-compatible multi-provider routing layer.</th> |
| | </tr> |
| | <tr> |
| | <th colspan="2"> |
| | <a href="https://github.com/TensorBlock/forge" target="_blank" style=" |
| | display: inline-block; |
| | padding: 8px 16px; |
| | background-color: #FF7F50; |
| | color: white; |
| | text-decoration: none; |
| | border-radius: 6px; |
| | font-weight: bold; |
| | font-family: sans-serif; |
| | ">🚀 Try it now! 🚀</a> |
| | </th> |
| | </tr> |
| | |
| | <tr> |
| | <th style="font-size: 25px;">Awesome MCP Servers</th> |
| | <th style="font-size: 25px;">TensorBlock Studio</th> |
| | </tr> |
| | <tr> |
| | <th><img src="https://imgur.com/2Xov7B7.jpeg" alt="MCP Servers" width="450"/></th> |
| | <th><img src="https://imgur.com/pJcmF5u.jpeg" alt="Studio" width="450"/></th> |
| | </tr> |
| | <tr> |
| | <th>A comprehensive collection of Model Context Protocol (MCP) servers.</th> |
| | <th>A lightweight, open, and extensible multi-LLM interaction studio.</th> |
| | </tr> |
| | <tr> |
| | <th> |
| | <a href="https://github.com/TensorBlock/awesome-mcp-servers" target="_blank" style=" |
| | display: inline-block; |
| | padding: 8px 16px; |
| | background-color: #FF7F50; |
| | color: white; |
| | text-decoration: none; |
| | border-radius: 6px; |
| | font-weight: bold; |
| | font-family: sans-serif; |
| | ">👀 See what we built 👀</a> |
| | </th> |
| | <th> |
| | <a href="https://github.com/TensorBlock/TensorBlock-Studio" target="_blank" style=" |
| | display: inline-block; |
| | padding: 8px 16px; |
| | background-color: #FF7F50; |
| | color: white; |
| | text-decoration: none; |
| | border-radius: 6px; |
| | font-weight: bold; |
| | font-family: sans-serif; |
| | ">👀 See what we built 👀</a> |
| | </th> |
| | </tr> |
| | </table> |
| | ## Prompt template |
| | |
| |
|
| | ``` |
| | <s><|user|> |
| | {prompt} |
| | <|assistant|> |
| | ``` |
| |
|
| | ## Model file specification |
| |
|
| | | Filename | Quant type | File Size | Description | |
| | | -------- | ---------- | --------- | ----------- | |
| | | [GritLM-7B-Q2_K.gguf](https://huggingface.co/tensorblock/GritLM-7B-GGUF/blob/main/GritLM-7B-Q2_K.gguf) | Q2_K | 2.532 GB | smallest, significant quality loss - not recommended for most purposes | |
| | | [GritLM-7B-Q3_K_S.gguf](https://huggingface.co/tensorblock/GritLM-7B-GGUF/blob/main/GritLM-7B-Q3_K_S.gguf) | Q3_K_S | 2.947 GB | very small, high quality loss | |
| | | [GritLM-7B-Q3_K_M.gguf](https://huggingface.co/tensorblock/GritLM-7B-GGUF/blob/main/GritLM-7B-Q3_K_M.gguf) | Q3_K_M | 3.277 GB | very small, high quality loss | |
| | | [GritLM-7B-Q3_K_L.gguf](https://huggingface.co/tensorblock/GritLM-7B-GGUF/blob/main/GritLM-7B-Q3_K_L.gguf) | Q3_K_L | 3.560 GB | small, substantial quality loss | |
| | | [GritLM-7B-Q4_0.gguf](https://huggingface.co/tensorblock/GritLM-7B-GGUF/blob/main/GritLM-7B-Q4_0.gguf) | Q4_0 | 3.827 GB | legacy; small, very high quality loss - prefer using Q3_K_M | |
| | | [GritLM-7B-Q4_K_S.gguf](https://huggingface.co/tensorblock/GritLM-7B-GGUF/blob/main/GritLM-7B-Q4_K_S.gguf) | Q4_K_S | 3.856 GB | small, greater quality loss | |
| | | [GritLM-7B-Q4_K_M.gguf](https://huggingface.co/tensorblock/GritLM-7B-GGUF/blob/main/GritLM-7B-Q4_K_M.gguf) | Q4_K_M | 4.068 GB | medium, balanced quality - recommended | |
| | | [GritLM-7B-Q5_0.gguf](https://huggingface.co/tensorblock/GritLM-7B-GGUF/blob/main/GritLM-7B-Q5_0.gguf) | Q5_0 | 4.654 GB | legacy; medium, balanced quality - prefer using Q4_K_M | |
| | | [GritLM-7B-Q5_K_S.gguf](https://huggingface.co/tensorblock/GritLM-7B-GGUF/blob/main/GritLM-7B-Q5_K_S.gguf) | Q5_K_S | 4.654 GB | large, low quality loss - recommended | |
| | | [GritLM-7B-Q5_K_M.gguf](https://huggingface.co/tensorblock/GritLM-7B-GGUF/blob/main/GritLM-7B-Q5_K_M.gguf) | Q5_K_M | 4.779 GB | large, very low quality loss - recommended | |
| | | [GritLM-7B-Q6_K.gguf](https://huggingface.co/tensorblock/GritLM-7B-GGUF/blob/main/GritLM-7B-Q6_K.gguf) | Q6_K | 5.534 GB | very large, extremely low quality loss | |
| | | [GritLM-7B-Q8_0.gguf](https://huggingface.co/tensorblock/GritLM-7B-GGUF/blob/main/GritLM-7B-Q8_0.gguf) | Q8_0 | 7.167 GB | very large, extremely low quality loss - not recommended | |
| | |
| | |
| | ## Downloading instruction |
| | |
| | ### Command line |
| | |
| | Firstly, install Huggingface Client |
| | |
| | ```shell |
| | pip install -U "huggingface_hub[cli]" |
| | ``` |
| | |
| | Then, downoad the individual model file the a local directory |
| | |
| | ```shell |
| | huggingface-cli download tensorblock/GritLM-7B-GGUF --include "GritLM-7B-Q2_K.gguf" --local-dir MY_LOCAL_DIR |
| | ``` |
| | |
| | If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try: |
| | |
| | ```shell |
| | huggingface-cli download tensorblock/GritLM-7B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' |
| | ``` |
| | |
