| --- |
| library_name: transformers |
| license: apache-2.0 |
| datasets: |
| - BeastyZ/E5-R |
| language: |
| - en |
| model-index: |
| - name: e5-R-mistral-7b |
| results: |
| - dataset: |
| config: default |
| name: MTEB ArguAna |
| revision: None |
| split: test |
| type: mteb/arguana |
| metrics: |
| - type: map_at_1 |
| value: 33.57 |
| - type: map_at_10 |
| value: 49.952000000000005 |
| - type: map_at_100 |
| value: 50.673 |
| - type: map_at_1000 |
| value: 50.674 |
| - type: map_at_3 |
| value: 44.915 |
| - type: map_at_5 |
| value: 47.876999999999995 |
| - type: mrr_at_1 |
| value: 34.211000000000006 |
| - type: mrr_at_10 |
| value: 50.19 |
| - type: mrr_at_100 |
| value: 50.905 |
| - type: mrr_at_1000 |
| value: 50.906 |
| - type: mrr_at_3 |
| value: 45.128 |
| - type: mrr_at_5 |
| value: 48.097 |
| - type: ndcg_at_1 |
| value: 33.57 |
| - type: ndcg_at_10 |
| value: 58.994 |
| - type: ndcg_at_100 |
| value: 61.806000000000004 |
| - type: ndcg_at_1000 |
| value: 61.824999999999996 |
| - type: ndcg_at_3 |
| value: 48.681000000000004 |
| - type: ndcg_at_5 |
| value: 54.001 |
| - type: precision_at_1 |
| value: 33.57 |
| - type: precision_at_10 |
| value: 8.784 |
| - type: precision_at_100 |
| value: 0.9950000000000001 |
| - type: precision_at_1000 |
| value: 0.1 |
| - type: precision_at_3 |
| value: 19.867 |
| - type: precision_at_5 |
| value: 14.495 |
| - type: recall_at_1 |
| value: 33.57 |
| - type: recall_at_10 |
| value: 87.83800000000001 |
| - type: recall_at_100 |
| value: 99.502 |
| - type: recall_at_1000 |
| value: 99.644 |
| - type: recall_at_3 |
| value: 59.602 |
| - type: recall_at_5 |
| value: 72.475 |
| - type: main_score |
| value: 58.994 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB CQADupstackRetrieval |
| revision: None |
| split: test |
| type: mteb/cqadupstack |
| metrics: |
| - type: map_at_1 |
| value: 24.75 |
| - type: map_at_10 |
| value: 34.025 |
| - type: map_at_100 |
| value: 35.126000000000005 |
| - type: map_at_1000 |
| value: 35.219 |
| - type: map_at_3 |
| value: 31.607000000000003 |
| - type: map_at_5 |
| value: 32.962 |
| - type: mrr_at_1 |
| value: 27.357 |
| - type: mrr_at_10 |
| value: 36.370999999999995 |
| - type: mrr_at_100 |
| value: 37.364000000000004 |
| - type: mrr_at_1000 |
| value: 37.423 |
| - type: mrr_at_3 |
| value: 34.288000000000004 |
| - type: mrr_at_5 |
| value: 35.434 |
| - type: ndcg_at_1 |
| value: 27.357 |
| - type: ndcg_at_10 |
| value: 46.593999999999997 |
| - type: ndcg_at_100 |
| value: 44.317 |
| - type: ndcg_at_1000 |
| value: 46.475 |
| - type: ndcg_at_3 |
| value: 34.473 |
| - type: ndcg_at_5 |
| value: 36.561 |
| - type: precision_at_1 |
| value: 27.357 |
| - type: precision_at_10 |
| value: 6.081 |
| - type: precision_at_100 |
| value: 0.9299999999999999 |
| - type: precision_at_1000 |
| value: 0.124 |
| - type: precision_at_3 |
| value: 14.911 |
| - type: precision_at_5 |
| value: 10.24 |
| - type: recall_at_1 |
| value: 24.75 |
| - type: recall_at_10 |
| value: 51.856 |
| - type: recall_at_100 |
| value: 76.44300000000001 |
| - type: recall_at_1000 |
| value: 92.078 |
| - type: recall_at_3 |
| value: 39.427 |
| - type: recall_at_5 |
| value: 44.639 |
| - type: main_score |
| value: 46.593999999999997 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB ClimateFEVER |
| revision: None |
| split: test |
| type: mteb/climate-fever |
| metrics: |
| - type: map_at_1 |
| value: 16.436 |
| - type: map_at_10 |
| value: 29.693 |
| - type: map_at_100 |
| value: 32.179 |
| - type: map_at_1000 |
| value: 32.353 |
| - type: map_at_3 |
| value: 24.556 |
| - type: map_at_5 |
| value: 27.105 |
| - type: mrr_at_1 |
| value: 37.524 |
| - type: mrr_at_10 |
| value: 51.475 |
| - type: mrr_at_100 |
| value: 52.107000000000006 |
| - type: mrr_at_1000 |
| value: 52.123 |
| - type: mrr_at_3 |
| value: 48.35 |
| - type: mrr_at_5 |
| value: 50.249 |
| - type: ndcg_at_1 |
| value: 37.524 |
| - type: ndcg_at_10 |
| value: 40.258 |
| - type: ndcg_at_100 |
| value: 48.364000000000004 |
| - type: ndcg_at_1000 |
| value: 51.031000000000006 |
| - type: ndcg_at_3 |
| value: 33.359 |
| - type: ndcg_at_5 |
| value: 35.573 |
| - type: precision_at_1 |
| value: 37.524 |
| - type: precision_at_10 |
| value: 12.886000000000001 |
| - type: precision_at_100 |
| value: 2.169 |
| - type: precision_at_1000 |
| value: 0.268 |
| - type: precision_at_3 |
| value: 25.624000000000002 |
| - type: precision_at_5 |
| value: 19.453 |
| - type: recall_at_1 |
| value: 16.436 |
| - type: recall_at_10 |
| value: 47.77 |
| - type: recall_at_100 |
| value: 74.762 |
| - type: recall_at_1000 |
| value: 89.316 |
| - type: recall_at_3 |
| value: 30.508000000000003 |
| - type: recall_at_5 |
| value: 37.346000000000004 |
| - type: main_score |
| value: 40.258 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB DBPedia |
| revision: None |
| split: test |
| type: mteb/dbpedia |
| metrics: |
| - type: map_at_1 |
| value: 10.147 |
| - type: map_at_10 |
| value: 24.631 |
| - type: map_at_100 |
| value: 35.657 |
| - type: map_at_1000 |
| value: 37.824999999999996 |
| - type: map_at_3 |
| value: 16.423 |
| - type: map_at_5 |
| value: 19.666 |
| - type: mrr_at_1 |
| value: 76.5 |
| - type: mrr_at_10 |
| value: 82.793 |
| - type: mrr_at_100 |
| value: 83.015 |
| - type: mrr_at_1000 |
| value: 83.021 |
| - type: mrr_at_3 |
| value: 81.75 |
| - type: mrr_at_5 |
| value: 82.375 |
| - type: ndcg_at_1 |
| value: 64.75 |
| - type: ndcg_at_10 |
| value: 51.031000000000006 |
| - type: ndcg_at_100 |
| value: 56.005 |
| - type: ndcg_at_1000 |
| value: 63.068000000000005 |
| - type: ndcg_at_3 |
| value: 54.571999999999996 |
| - type: ndcg_at_5 |
| value: 52.66499999999999 |
| - type: precision_at_1 |
| value: 76.5 |
| - type: precision_at_10 |
| value: 42.15 |
| - type: precision_at_100 |
| value: 13.22 |
| - type: precision_at_1000 |
| value: 2.5989999999999998 |
| - type: precision_at_3 |
| value: 58.416999999999994 |
| - type: precision_at_5 |
| value: 52.2 |
| - type: recall_at_1 |
| value: 10.147 |
| - type: recall_at_10 |
| value: 30.786 |
| - type: recall_at_100 |
| value: 62.873000000000005 |
| - type: recall_at_1000 |
| value: 85.358 |
| - type: recall_at_3 |
| value: 17.665 |
| - type: recall_at_5 |
| value: 22.088 |
| - type: main_score |
| value: 51.031000000000006 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB FEVER |
| revision: None |
| split: test |
| type: mteb/fever |
| metrics: |
| - type: map_at_1 |
| value: 78.52900000000001 |
| - type: map_at_10 |
| value: 87.24199999999999 |
| - type: map_at_100 |
| value: 87.446 |
| - type: map_at_1000 |
| value: 87.457 |
| - type: map_at_3 |
| value: 86.193 |
| - type: map_at_5 |
| value: 86.898 |
| - type: mrr_at_1 |
| value: 84.518 |
| - type: mrr_at_10 |
| value: 90.686 |
| - type: mrr_at_100 |
| value: 90.73 |
| - type: mrr_at_1000 |
| value: 90.731 |
| - type: mrr_at_3 |
| value: 90.227 |
| - type: mrr_at_5 |
| value: 90.575 |
| - type: ndcg_at_1 |
| value: 84.518 |
| - type: ndcg_at_10 |
| value: 90.324 |
| - type: ndcg_at_100 |
| value: 90.96300000000001 |
| - type: ndcg_at_1000 |
| value: 91.134 |
| - type: ndcg_at_3 |
| value: 88.937 |
| - type: ndcg_at_5 |
| value: 89.788 |
| - type: precision_at_1 |
| value: 84.518 |
| - type: precision_at_10 |
| value: 10.872 |
| - type: precision_at_100 |
| value: 1.1440000000000001 |
| - type: precision_at_1000 |
| value: 0.117 |
| - type: precision_at_3 |
| value: 34.108 |
| - type: precision_at_5 |
| value: 21.154999999999998 |
| - type: recall_at_1 |
| value: 78.52900000000001 |
| - type: recall_at_10 |
| value: 96.123 |
| - type: recall_at_100 |
| value: 98.503 |
| - type: recall_at_1000 |
| value: 99.518 |
| - type: recall_at_3 |
| value: 92.444 |
| - type: recall_at_5 |
| value: 94.609 |
| - type: main_score |
| value: 90.324 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB FiQA2018 |
| revision: None |
| split: test |
| type: mteb/fiqa |
| metrics: |
| - type: map_at_1 |
| value: 29.38 |
| - type: map_at_10 |
| value: 50.28 |
| - type: map_at_100 |
| value: 52.532999999999994 |
| - type: map_at_1000 |
| value: 52.641000000000005 |
| - type: map_at_3 |
| value: 43.556 |
| - type: map_at_5 |
| value: 47.617 |
| - type: mrr_at_1 |
| value: 56.79 |
| - type: mrr_at_10 |
| value: 65.666 |
| - type: mrr_at_100 |
| value: 66.211 |
| - type: mrr_at_1000 |
| value: 66.226 |
| - type: mrr_at_3 |
| value: 63.452 |
| - type: mrr_at_5 |
| value: 64.895 |
| - type: ndcg_at_1 |
| value: 56.79 |
| - type: ndcg_at_10 |
| value: 58.68 |
| - type: ndcg_at_100 |
| value: 65.22 |
| - type: ndcg_at_1000 |
| value: 66.645 |
| - type: ndcg_at_3 |
| value: 53.981 |
| - type: ndcg_at_5 |
| value: 55.95 |
| - type: precision_at_1 |
| value: 56.79 |
| - type: precision_at_10 |
| value: 16.311999999999998 |
| - type: precision_at_100 |
| value: 2.316 |
| - type: precision_at_1000 |
| value: 0.258 |
| - type: precision_at_3 |
| value: 36.214 |
| - type: precision_at_5 |
| value: 27.067999999999998 |
| - type: recall_at_1 |
| value: 29.38 |
| - type: recall_at_10 |
| value: 66.503 |
| - type: recall_at_100 |
| value: 89.885 |
| - type: recall_at_1000 |
| value: 97.954 |
| - type: recall_at_3 |
| value: 48.866 |
| - type: recall_at_5 |
| value: 57.60999999999999 |
| - type: main_score |
| value: 58.68 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB HotpotQA |
| revision: None |
| split: test |
| type: mteb/hotpotqa |
| metrics: |
| - type: map_at_1 |
| value: 42.134 |
| - type: map_at_10 |
| value: 73.412 |
| - type: map_at_100 |
| value: 74.144 |
| - type: map_at_1000 |
| value: 74.181 |
| - type: map_at_3 |
| value: 70.016 |
| - type: map_at_5 |
| value: 72.174 |
| - type: mrr_at_1 |
| value: 84.267 |
| - type: mrr_at_10 |
| value: 89.18599999999999 |
| - type: mrr_at_100 |
| value: 89.29599999999999 |
| - type: mrr_at_1000 |
| value: 89.298 |
| - type: mrr_at_3 |
| value: 88.616 |
| - type: mrr_at_5 |
| value: 88.957 |
| - type: ndcg_at_1 |
| value: 84.267 |
| - type: ndcg_at_10 |
| value: 80.164 |
| - type: ndcg_at_100 |
| value: 82.52199999999999 |
| - type: ndcg_at_1000 |
| value: 83.176 |
| - type: ndcg_at_3 |
| value: 75.616 |
| - type: ndcg_at_5 |
| value: 78.184 |
| - type: precision_at_1 |
| value: 84.267 |
| - type: precision_at_10 |
| value: 16.916 |
| - type: precision_at_100 |
| value: 1.872 |
| - type: precision_at_1000 |
| value: 0.196 |
| - type: precision_at_3 |
| value: 49.71 |
| - type: precision_at_5 |
| value: 31.854 |
| - type: recall_at_1 |
| value: 42.134 |
| - type: recall_at_10 |
| value: 84.578 |
| - type: recall_at_100 |
| value: 93.606 |
| - type: recall_at_1000 |
| value: 97.86 |
| - type: recall_at_3 |
| value: 74.564 |
| - type: recall_at_5 |
| value: 79.635 |
| - type: main_score |
| value: 80.164 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB MSMARCO |
| revision: None |
| split: dev |
| type: mteb/msmarco |
| metrics: |
| - type: map_at_1 |
| value: 22.276 |
| - type: map_at_10 |
| value: 35.493 |
| - type: map_at_100 |
| value: 36.656 |
| - type: map_at_1000 |
| value: 36.699 |
| - type: map_at_3 |
| value: 31.320999999999998 |
| - type: map_at_5 |
| value: 33.772999999999996 |
| - type: mrr_at_1 |
| value: 22.966 |
| - type: mrr_at_10 |
| value: 36.074 |
| - type: mrr_at_100 |
| value: 37.183 |
| - type: mrr_at_1000 |
| value: 37.219 |
| - type: mrr_at_3 |
| value: 31.984 |
| - type: mrr_at_5 |
| value: 34.419 |
| - type: ndcg_at_1 |
| value: 22.966 |
| - type: ndcg_at_10 |
| value: 42.895 |
| - type: ndcg_at_100 |
| value: 48.453 |
| - type: ndcg_at_1000 |
| value: 49.464999999999996 |
| - type: ndcg_at_3 |
| value: 34.410000000000004 |
| - type: ndcg_at_5 |
| value: 38.78 |
| - type: precision_at_1 |
| value: 22.966 |
| - type: precision_at_10 |
| value: 6.88 |
| - type: precision_at_100 |
| value: 0.966 |
| - type: precision_at_1000 |
| value: 0.105 |
| - type: precision_at_3 |
| value: 14.785 |
| - type: precision_at_5 |
| value: 11.074 |
| - type: recall_at_1 |
| value: 22.276 |
| - type: recall_at_10 |
| value: 65.756 |
| - type: recall_at_100 |
| value: 91.34100000000001 |
| - type: recall_at_1000 |
| value: 98.957 |
| - type: recall_at_3 |
| value: 42.67 |
| - type: recall_at_5 |
| value: 53.161 |
| - type: main_score |
| value: 42.895 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB NFCorpus |
| revision: None |
| split: test |
| type: mteb/nfcorpus |
| metrics: |
| - type: map_at_1 |
| value: 7.188999999999999 |
| - type: map_at_10 |
| value: 16.176 |
| - type: map_at_100 |
| value: 20.504 |
| - type: map_at_1000 |
| value: 22.203999999999997 |
| - type: map_at_3 |
| value: 11.766 |
| - type: map_at_5 |
| value: 13.655999999999999 |
| - type: mrr_at_1 |
| value: 55.418 |
| - type: mrr_at_10 |
| value: 62.791 |
| - type: mrr_at_100 |
| value: 63.339 |
| - type: mrr_at_1000 |
| value: 63.369 |
| - type: mrr_at_3 |
| value: 60.99099999999999 |
| - type: mrr_at_5 |
| value: 62.059 |
| - type: ndcg_at_1 |
| value: 53.715 |
| - type: ndcg_at_10 |
| value: 41.377 |
| - type: ndcg_at_100 |
| value: 37.999 |
| - type: ndcg_at_1000 |
| value: 46.726 |
| - type: ndcg_at_3 |
| value: 47.262 |
| - type: ndcg_at_5 |
| value: 44.708999999999996 |
| - type: precision_at_1 |
| value: 55.108000000000004 |
| - type: precision_at_10 |
| value: 30.154999999999998 |
| - type: precision_at_100 |
| value: 9.582 |
| - type: precision_at_1000 |
| value: 2.2720000000000002 |
| - type: precision_at_3 |
| value: 43.55 |
| - type: precision_at_5 |
| value: 38.204 |
| - type: recall_at_1 |
| value: 7.188999999999999 |
| - type: recall_at_10 |
| value: 20.655 |
| - type: recall_at_100 |
| value: 38.068000000000005 |
| - type: recall_at_1000 |
| value: 70.208 |
| - type: recall_at_3 |
| value: 12.601 |
| - type: recall_at_5 |
| value: 15.573999999999998 |
| - type: main_score |
| value: 41.377 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB NQ |
| revision: None |
| split: test |
| type: mteb/nq |
| metrics: |
| - type: map_at_1 |
| value: 46.017 |
| - type: map_at_10 |
| value: 62.910999999999994 |
| - type: map_at_100 |
| value: 63.526 |
| - type: map_at_1000 |
| value: 63.536 |
| - type: map_at_3 |
| value: 59.077999999999996 |
| - type: map_at_5 |
| value: 61.521 |
| - type: mrr_at_1 |
| value: 51.68000000000001 |
| - type: mrr_at_10 |
| value: 65.149 |
| - type: mrr_at_100 |
| value: 65.542 |
| - type: mrr_at_1000 |
| value: 65.55 |
| - type: mrr_at_3 |
| value: 62.49 |
| - type: mrr_at_5 |
| value: 64.178 |
| - type: ndcg_at_1 |
| value: 51.651 |
| - type: ndcg_at_10 |
| value: 69.83500000000001 |
| - type: ndcg_at_100 |
| value: 72.18 |
| - type: ndcg_at_1000 |
| value: 72.393 |
| - type: ndcg_at_3 |
| value: 63.168 |
| - type: ndcg_at_5 |
| value: 66.958 |
| - type: precision_at_1 |
| value: 51.651 |
| - type: precision_at_10 |
| value: 10.626 |
| - type: precision_at_100 |
| value: 1.195 |
| - type: precision_at_1000 |
| value: 0.121 |
| - type: precision_at_3 |
| value: 28.012999999999998 |
| - type: precision_at_5 |
| value: 19.09 |
| - type: recall_at_1 |
| value: 46.017 |
| - type: recall_at_10 |
| value: 88.345 |
| - type: recall_at_100 |
| value: 98.129 |
| - type: recall_at_1000 |
| value: 99.696 |
| - type: recall_at_3 |
| value: 71.531 |
| - type: recall_at_5 |
| value: 80.108 |
| - type: main_score |
| value: 69.83500000000001 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB QuoraRetrieval |
| revision: None |
| split: test |
| type: mteb/quora |
| metrics: |
| - type: map_at_1 |
| value: 72.473 |
| - type: map_at_10 |
| value: 86.72800000000001 |
| - type: map_at_100 |
| value: 87.323 |
| - type: map_at_1000 |
| value: 87.332 |
| - type: map_at_3 |
| value: 83.753 |
| - type: map_at_5 |
| value: 85.627 |
| - type: mrr_at_1 |
| value: 83.39 |
| - type: mrr_at_10 |
| value: 89.149 |
| - type: mrr_at_100 |
| value: 89.228 |
| - type: mrr_at_1000 |
| value: 89.229 |
| - type: mrr_at_3 |
| value: 88.335 |
| - type: mrr_at_5 |
| value: 88.895 |
| - type: ndcg_at_1 |
| value: 83.39 |
| - type: ndcg_at_10 |
| value: 90.109 |
| - type: ndcg_at_100 |
| value: 91.09 |
| - type: ndcg_at_1000 |
| value: 91.13900000000001 |
| - type: ndcg_at_3 |
| value: 87.483 |
| - type: ndcg_at_5 |
| value: 88.942 |
| - type: precision_at_1 |
| value: 83.39 |
| - type: precision_at_10 |
| value: 13.711 |
| - type: precision_at_100 |
| value: 1.549 |
| - type: precision_at_1000 |
| value: 0.157 |
| - type: precision_at_3 |
| value: 38.342999999999996 |
| - type: precision_at_5 |
| value: 25.188 |
| - type: recall_at_1 |
| value: 72.473 |
| - type: recall_at_10 |
| value: 96.57 |
| - type: recall_at_100 |
| value: 99.792 |
| - type: recall_at_1000 |
| value: 99.99900000000001 |
| - type: recall_at_3 |
| value: 88.979 |
| - type: recall_at_5 |
| value: 93.163 |
| - type: main_score |
| value: 90.109 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB SCIDOCS |
| revision: None |
| split: test |
| type: mteb/scidocs |
| metrics: |
| - type: map_at_1 |
| value: 4.598 |
| - type: map_at_10 |
| value: 11.405999999999999 |
| - type: map_at_100 |
| value: 13.447999999999999 |
| - type: map_at_1000 |
| value: 13.758999999999999 |
| - type: map_at_3 |
| value: 8.332 |
| - type: map_at_5 |
| value: 9.709 |
| - type: mrr_at_1 |
| value: 22.6 |
| - type: mrr_at_10 |
| value: 32.978 |
| - type: mrr_at_100 |
| value: 34.149 |
| - type: mrr_at_1000 |
| value: 34.213 |
| - type: mrr_at_3 |
| value: 29.7 |
| - type: mrr_at_5 |
| value: 31.485000000000003 |
| - type: ndcg_at_1 |
| value: 22.6 |
| - type: ndcg_at_10 |
| value: 19.259999999999998 |
| - type: ndcg_at_100 |
| value: 27.21 |
| - type: ndcg_at_1000 |
| value: 32.7 |
| - type: ndcg_at_3 |
| value: 18.445 |
| - type: ndcg_at_5 |
| value: 15.812000000000001 |
| - type: precision_at_1 |
| value: 22.6 |
| - type: precision_at_10 |
| value: 9.959999999999999 |
| - type: precision_at_100 |
| value: 2.139 |
| - type: precision_at_1000 |
| value: 0.345 |
| - type: precision_at_3 |
| value: 17.299999999999997 |
| - type: precision_at_5 |
| value: 13.719999999999999 |
| - type: recall_at_1 |
| value: 4.598 |
| - type: recall_at_10 |
| value: 20.186999999999998 |
| - type: recall_at_100 |
| value: 43.362 |
| - type: recall_at_1000 |
| value: 70.11800000000001 |
| - type: recall_at_3 |
| value: 10.543 |
| - type: recall_at_5 |
| value: 13.923 |
| - type: main_score |
| value: 19.259999999999998 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB SciFact |
| revision: None |
| split: test |
| type: mteb/scifact |
| metrics: |
| - type: map_at_1 |
| value: 65.467 |
| - type: map_at_10 |
| value: 74.935 |
| - type: map_at_100 |
| value: 75.395 |
| - type: map_at_1000 |
| value: 75.412 |
| - type: map_at_3 |
| value: 72.436 |
| - type: map_at_5 |
| value: 73.978 |
| - type: mrr_at_1 |
| value: 68.667 |
| - type: mrr_at_10 |
| value: 76.236 |
| - type: mrr_at_100 |
| value: 76.537 |
| - type: mrr_at_1000 |
| value: 76.55499999999999 |
| - type: mrr_at_3 |
| value: 74.722 |
| - type: mrr_at_5 |
| value: 75.639 |
| - type: ndcg_at_1 |
| value: 68.667 |
| - type: ndcg_at_10 |
| value: 78.92099999999999 |
| - type: ndcg_at_100 |
| value: 80.645 |
| - type: ndcg_at_1000 |
| value: 81.045 |
| - type: ndcg_at_3 |
| value: 75.19500000000001 |
| - type: ndcg_at_5 |
| value: 77.114 |
| - type: precision_at_1 |
| value: 68.667 |
| - type: precision_at_10 |
| value: 10.133000000000001 |
| - type: precision_at_100 |
| value: 1.0999999999999999 |
| - type: precision_at_1000 |
| value: 0.11299999999999999 |
| - type: precision_at_3 |
| value: 28.889 |
| - type: precision_at_5 |
| value: 18.8 |
| - type: recall_at_1 |
| value: 65.467 |
| - type: recall_at_10 |
| value: 89.517 |
| - type: recall_at_100 |
| value: 97 |
| - type: recall_at_1000 |
| value: 100 |
| - type: recall_at_3 |
| value: 79.72200000000001 |
| - type: recall_at_5 |
| value: 84.511 |
| - type: main_score |
| value: 78.92099999999999 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB TRECCOVID |
| revision: None |
| split: test |
| type: mteb/trec-covid |
| metrics: |
| - type: map_at_1 |
| value: 0.244 |
| - type: map_at_10 |
| value: 2.183 |
| - type: map_at_100 |
| value: 13.712 |
| - type: map_at_1000 |
| value: 33.147 |
| - type: map_at_3 |
| value: 0.7270000000000001 |
| - type: map_at_5 |
| value: 1.199 |
| - type: mrr_at_1 |
| value: 94 |
| - type: mrr_at_10 |
| value: 97 |
| - type: mrr_at_100 |
| value: 97 |
| - type: mrr_at_1000 |
| value: 97 |
| - type: mrr_at_3 |
| value: 97 |
| - type: mrr_at_5 |
| value: 97 |
| - type: ndcg_at_1 |
| value: 92 |
| - type: ndcg_at_10 |
| value: 84.399 |
| - type: ndcg_at_100 |
| value: 66.771 |
| - type: ndcg_at_1000 |
| value: 59.092 |
| - type: ndcg_at_3 |
| value: 89.173 |
| - type: ndcg_at_5 |
| value: 88.52600000000001 |
| - type: precision_at_1 |
| value: 94 |
| - type: precision_at_10 |
| value: 86.8 |
| - type: precision_at_100 |
| value: 68.24 |
| - type: precision_at_1000 |
| value: 26.003999999999998 |
| - type: precision_at_3 |
| value: 92.667 |
| - type: precision_at_5 |
| value: 92.4 |
| - type: recall_at_1 |
| value: 0.244 |
| - type: recall_at_10 |
| value: 2.302 |
| - type: recall_at_100 |
| value: 16.622 |
| - type: recall_at_1000 |
| value: 55.175 |
| - type: recall_at_3 |
| value: 0.748 |
| - type: recall_at_5 |
| value: 1.247 |
| - type: main_score |
| value: 84.399 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB Touche2020 |
| revision: None |
| split: test |
| type: mteb/touche2020 |
| metrics: |
| - type: map_at_1 |
| value: 2.707 |
| - type: map_at_10 |
| value: 10.917 |
| - type: map_at_100 |
| value: 16.308 |
| - type: map_at_1000 |
| value: 17.953 |
| - type: map_at_3 |
| value: 5.65 |
| - type: map_at_5 |
| value: 7.379 |
| - type: mrr_at_1 |
| value: 34.694 |
| - type: mrr_at_10 |
| value: 49.745 |
| - type: mrr_at_100 |
| value: 50.309000000000005 |
| - type: mrr_at_1000 |
| value: 50.32 |
| - type: mrr_at_3 |
| value: 44.897999999999996 |
| - type: mrr_at_5 |
| value: 48.061 |
| - type: ndcg_at_1 |
| value: 33.672999999999995 |
| - type: ndcg_at_10 |
| value: 26.894000000000002 |
| - type: ndcg_at_100 |
| value: 37.423 |
| - type: ndcg_at_1000 |
| value: 49.376999999999995 |
| - type: ndcg_at_3 |
| value: 30.456 |
| - type: ndcg_at_5 |
| value: 27.772000000000002 |
| - type: precision_at_1 |
| value: 34.694 |
| - type: precision_at_10 |
| value: 23.878 |
| - type: precision_at_100 |
| value: 7.489999999999999 |
| - type: precision_at_1000 |
| value: 1.555 |
| - type: precision_at_3 |
| value: 31.293 |
| - type: precision_at_5 |
| value: 26.939 |
| - type: recall_at_1 |
| value: 2.707 |
| - type: recall_at_10 |
| value: 18.104 |
| - type: recall_at_100 |
| value: 46.93 |
| - type: recall_at_1000 |
| value: 83.512 |
| - type: recall_at_3 |
| value: 6.622999999999999 |
| - type: recall_at_5 |
| value: 10.051 |
| - type: main_score |
| value: 26.894000000000002 |
| task: |
| type: Retrieval |
| tags: |
| - mteb |
| --- |
| |
| # Model Card for e5-R-mistral-7b |
|
|
| <!-- Provide a quick summary of what the model is/does. --> |
|
|
| ## Model Description |
|
|
| <!-- Provide a longer summary of what this model is. --> |
|
|
| e5-R-mistral-7b is a LLM retriever fine-tuned from [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1). |
|
|
| - **Model type:** CausalLM |
| - **Repository:** Welcome to our [GitHub](https://github.com/LeeSureman/E5-Retrieval-Reproduction) repository to obtain code |
| - **Training dataset:** Dataset used for fine-tuning e5-R-mistral-7b is available [here](https://huggingface.co/datasets/BeastyZ/E5-R). |
