--- base_model: Alibaba-NLP/gte-Qwen2-1.5B-instruct license: apache-2.0 tags: - mteb - sentence-transformers - transformers - Qwen2 - sentence-similarity - llama-cpp - gguf-my-repo model-index: - name: gte-qwen2-7B-instruct results: - task: type: Classification dataset: name: MTEB AmazonCounterfactualClassification (en) type: mteb/amazon_counterfactual config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 83.98507462686567 - type: ap value: 50.93015252587014 - type: f1 value: 78.50416599051215 - task: type: Classification dataset: name: MTEB AmazonPolarityClassification type: mteb/amazon_polarity config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 96.61065 - type: ap value: 94.89174052954196 - type: f1 value: 96.60942596940565 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (en) type: mteb/amazon_reviews_multi config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 55.614000000000004 - type: f1 value: 54.90553480294904 - task: type: Retrieval dataset: name: MTEB ArguAna type: mteb/arguana config: default split: test revision: c22ab2a51041ffd869aaddef7af8d8215647e41a metrics: - type: map_at_1 value: 45.164 - type: map_at_10 value: 61.519 - type: map_at_100 value: 61.769 - type: map_at_1000 value: 61.769 - type: map_at_3 value: 57.443999999999996 - type: map_at_5 value: 60.058 - type: mrr_at_1 value: 46.088 - type: mrr_at_10 value: 61.861 - type: mrr_at_100 value: 62.117999999999995 - type: mrr_at_1000 value: 62.117999999999995 - type: mrr_at_3 value: 57.729 - type: mrr_at_5 value: 60.392 - type: ndcg_at_1 value: 45.164 - type: ndcg_at_10 value: 69.72 - type: ndcg_at_100 value: 70.719 - type: ndcg_at_1000 value: 70.719 - type: ndcg_at_3 value: 61.517999999999994 - type: ndcg_at_5 value: 66.247 - type: precision_at_1 value: 45.164 - type: precision_at_10 value: 9.545 - type: precision_at_100 value: 0.996 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 24.443 - type: precision_at_5 value: 16.97 - type: recall_at_1 value: 45.164 - type: recall_at_10 value: 95.448 - type: recall_at_100 value: 99.644 - type: recall_at_1000 value: 99.644 - type: recall_at_3 value: 73.329 - type: recall_at_5 value: 84.851 - task: type: Clustering dataset: name: MTEB ArxivClusteringP2P type: mteb/arxiv-clustering-p2p config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 50.511868162026175 - task: type: Clustering dataset: name: MTEB ArxivClusteringS2S type: mteb/arxiv-clustering-s2s config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 45.007803189284004 - task: type: Reranking dataset: name: MTEB AskUbuntuDupQuestions type: mteb/askubuntudupquestions-reranking config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 64.55292107723382 - type: mrr value: 77.66158818097877 - task: type: STS dataset: name: MTEB BIOSSES type: mteb/biosses-sts config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 85.65459047085452 - type: cos_sim_spearman value: 82.10729255710761 - type: euclidean_pearson value: 82.78079159312476 - type: euclidean_spearman value: 80.50002701880933 - type: manhattan_pearson value: 82.41372641383016 - type: manhattan_spearman value: 80.57412509272639 - task: type: Classification dataset: name: MTEB Banking77Classification type: mteb/banking77 config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 87.30844155844156 - type: f1 value: 87.25307322443255 - task: type: Clustering dataset: name: MTEB BiorxivClusteringP2P type: mteb/biorxiv-clustering-p2p config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 43.20754608934859 - task: type: Clustering dataset: name: MTEB BiorxivClusteringS2S type: mteb/biorxiv-clustering-s2s config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 38.818037697335505 - task: type: Retrieval dataset: name: MTEB CQADupstackAndroidRetrieval type: BeIR/cqadupstack config: default split: test revision: f46a197baaae43b4f621051089b82a364682dfeb metrics: - type: map_at_1 value: 35.423 - type: map_at_10 value: 47.198 - type: map_at_100 value: 48.899 - type: map_at_1000 value: 49.004 - type: map_at_3 value: 43.114999999999995 - type: map_at_5 value: 45.491 - type: mrr_at_1 value: 42.918 - type: mrr_at_10 value: 53.299 - type: mrr_at_100 value: 54.032000000000004 - type: mrr_at_1000 value: 54.055 - type: mrr_at_3 value: 50.453 - type: mrr_at_5 value: 52.205999999999996 - type: ndcg_at_1 value: 42.918 - type: ndcg_at_10 value: 53.98 - type: ndcg_at_100 value: 59.57 - type: ndcg_at_1000 value: 60.879000000000005 - type: ndcg_at_3 value: 48.224000000000004 - type: ndcg_at_5 value: 50.998 - type: precision_at_1 value: 42.918 - type: precision_at_10 value: 10.299999999999999 - type: precision_at_100 value: 1.687 - type: precision_at_1000 value: 0.211 - type: precision_at_3 value: 22.842000000000002 - type: precision_at_5 value: 16.681 - type: recall_at_1 value: 35.423 - type: recall_at_10 value: 66.824 - type: recall_at_100 value: 89.564 - type: recall_at_1000 value: 97.501 - type: recall_at_3 value: 50.365 - type: recall_at_5 value: 57.921 - task: type: Retrieval dataset: name: MTEB CQADupstackEnglishRetrieval type: BeIR/cqadupstack config: default split: test revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 metrics: - type: map_at_1 value: 33.205 - type: map_at_10 value: 44.859 - type: map_at_100 value: 46.135 - type: map_at_1000 value: 46.259 - type: map_at_3 value: 41.839 - type: map_at_5 value: 43.662 - type: mrr_at_1 value: 41.146 - type: mrr_at_10 value: 50.621 - type: mrr_at_100 value: 51.207 - type: mrr_at_1000 value: 51.246 - type: mrr_at_3 value: 48.535000000000004 - type: mrr_at_5 value: 49.818 - type: ndcg_at_1 value: 41.146 - type: ndcg_at_10 value: 50.683 - type: ndcg_at_100 value: 54.82 - type: ndcg_at_1000 value: 56.69 - type: ndcg_at_3 value: 46.611000000000004 - type: ndcg_at_5 value: 48.66 - type: precision_at_1 value: 41.146 - type: precision_at_10 value: 9.439 - type: precision_at_100 value: 1.465 - type: precision_at_1000 value: 0.194 - type: precision_at_3 value: 22.59 - type: precision_at_5 value: 15.86 - type: recall_at_1 value: 33.205 - type: recall_at_10 value: 61.028999999999996 - type: recall_at_100 value: 78.152 - type: recall_at_1000 value: 89.59700000000001 - type: recall_at_3 value: 49.05 - type: recall_at_5 value: 54.836 - task: type: Retrieval dataset: name: MTEB CQADupstackGamingRetrieval type: BeIR/cqadupstack config: default split: test revision: 4885aa143210c98657558c04aaf3dc47cfb54340 metrics: - type: map_at_1 value: 41.637 - type: map_at_10 value: 55.162 - type: map_at_100 value: 56.142 - type: map_at_1000 value: 56.188 - type: map_at_3 value: 51.564 - type: map_at_5 value: 53.696 - type: mrr_at_1 value: 47.524 - type: mrr_at_10 value: 58.243 - type: mrr_at_100 value: 58.879999999999995 - type: mrr_at_1000 value: 58.9 - type: mrr_at_3 value: 55.69499999999999 - type: mrr_at_5 value: 57.284 - type: ndcg_at_1 value: 47.524 - type: ndcg_at_10 value: 61.305 - type: ndcg_at_100 value: 65.077 - type: ndcg_at_1000 value: 65.941 - type: ndcg_at_3 value: 55.422000000000004 - type: ndcg_at_5 value: 58.516 - type: precision_at_1 value: 47.524 - type: precision_at_10 value: 9.918000000000001 - type: precision_at_100 value: 1.276 - type: precision_at_1000 value: 0.13899999999999998 - type: precision_at_3 value: 24.765 - type: precision_at_5 value: 17.204 - type: recall_at_1 value: 41.637 - type: recall_at_10 value: 76.185 - type: recall_at_100 value: 92.149 - type: recall_at_1000 value: 98.199 - type: recall_at_3 value: 60.856 - type: recall_at_5 value: 68.25099999999999 - task: type: Retrieval dataset: name: MTEB CQADupstackGisRetrieval type: BeIR/cqadupstack config: default split: test revision: 5003b3064772da1887988e05400cf3806fe491f2 metrics: - type: map_at_1 value: 26.27 - type: map_at_10 value: 37.463 - type: map_at_100 value: 38.434000000000005 - type: map_at_1000 value: 38.509 - type: map_at_3 value: 34.226 - type: map_at_5 value: 36.161 - type: mrr_at_1 value: 28.588 - type: mrr_at_10 value: 39.383 - type: mrr_at_100 value: 40.23 - type: mrr_at_1000 value: 40.281 - type: mrr_at_3 value: 36.422 - type: mrr_at_5 value: 38.252 - type: ndcg_at_1 value: 28.588 - type: ndcg_at_10 value: 43.511 - type: ndcg_at_100 value: 48.274 - type: ndcg_at_1000 value: 49.975 - type: ndcg_at_3 value: 37.319 - type: ndcg_at_5 value: 40.568 - type: precision_at_1 value: 28.588 - type: precision_at_10 value: 6.893000000000001 - type: precision_at_100 value: 0.9900000000000001 - type: precision_at_1000 value: 0.117 - type: precision_at_3 value: 16.347 - type: precision_at_5 value: 11.661000000000001 - type: recall_at_1 value: 26.27 - type: recall_at_10 value: 60.284000000000006 - type: recall_at_100 value: 81.902 - type: recall_at_1000 value: 94.43 - type: recall_at_3 value: 43.537 - type: recall_at_5 value: 51.475 - task: type: Retrieval dataset: name: MTEB CQADupstackMathematicaRetrieval type: BeIR/cqadupstack config: default split: test revision: 90fceea13679c63fe563ded68f3b6f06e50061de metrics: - type: map_at_1 value: 18.168 - type: map_at_10 value: 28.410000000000004 - type: map_at_100 value: 29.78 - type: map_at_1000 value: 29.892999999999997 - type: map_at_3 value: 25.238 - type: map_at_5 value: 26.96 - type: mrr_at_1 value: 23.507 - type: mrr_at_10 value: 33.382 - type: mrr_at_100 value: 34.404 - type: mrr_at_1000 value: 34.467999999999996 - type: mrr_at_3 value: 30.637999999999998 - type: mrr_at_5 value: 32.199 - type: ndcg_at_1 value: 23.507 - type: ndcg_at_10 value: 34.571000000000005 - type: ndcg_at_100 value: 40.663 - type: ndcg_at_1000 value: 43.236000000000004 - type: ndcg_at_3 value: 29.053 - type: ndcg_at_5 value: 31.563999999999997 - type: precision_at_1 value: 23.507 - type: precision_at_10 value: 6.654 - type: precision_at_100 value: 1.113 - type: precision_at_1000 value: 0.146 - type: precision_at_3 value: 14.427999999999999 - type: precision_at_5 value: 10.498000000000001 - type: recall_at_1 value: 18.168 - type: recall_at_10 value: 48.443000000000005 - type: recall_at_100 value: 74.47 - type: recall_at_1000 value: 92.494 - type: recall_at_3 value: 33.379999999999995 - type: recall_at_5 value: 39.76 - task: type: Retrieval dataset: name: MTEB CQADupstackPhysicsRetrieval type: BeIR/cqadupstack config: default split: test revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 metrics: - type: map_at_1 value: 32.39 - type: map_at_10 value: 44.479 - type: map_at_100 value: 45.977000000000004 - type: map_at_1000 value: 46.087 - type: map_at_3 value: 40.976 - type: map_at_5 value: 43.038 - type: mrr_at_1 value: 40.135 - type: mrr_at_10 value: 50.160000000000004 - type: mrr_at_100 value: 51.052 - type: mrr_at_1000 value: 51.087 - type: mrr_at_3 value: 47.818 - type: mrr_at_5 value: 49.171 - type: ndcg_at_1 value: 40.135 - type: ndcg_at_10 value: 50.731 - type: ndcg_at_100 value: 56.452000000000005 - type: ndcg_at_1000 value: 58.123000000000005 - type: ndcg_at_3 value: 45.507 - type: ndcg_at_5 value: 48.11 - type: precision_at_1 value: 40.135 - type: precision_at_10 value: 9.192 - type: precision_at_100 value: 1.397 - type: precision_at_1000 value: 0.169 - type: precision_at_3 value: 21.816 - type: precision_at_5 value: 15.476 - type: recall_at_1 value: 32.39 - type: recall_at_10 value: 63.597 - type: recall_at_100 value: 86.737 - type: recall_at_1000 value: 97.039 - type: recall_at_3 value: 48.906 - type: recall_at_5 value: 55.659000000000006 - task: type: Retrieval dataset: name: MTEB CQADupstackProgrammersRetrieval type: BeIR/cqadupstack config: default split: test revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 metrics: - type: map_at_1 value: 28.397 - type: map_at_10 value: 39.871 - type: map_at_100 value: 41.309000000000005 - type: map_at_1000 value: 41.409 - type: map_at_3 value: 36.047000000000004 - type: map_at_5 value: 38.104 - type: mrr_at_1 value: 34.703 - type: mrr_at_10 value: 44.773 - type: mrr_at_100 value: 45.64 - type: mrr_at_1000 value: 45.678999999999995 - type: mrr_at_3 value: 41.705 - type: mrr_at_5 value: 43.406 - type: ndcg_at_1 value: 34.703 - type: ndcg_at_10 value: 46.271 - type: ndcg_at_100 value: 52.037 - type: ndcg_at_1000 value: 53.81700000000001 - type: ndcg_at_3 value: 39.966 - type: ndcg_at_5 value: 42.801 - type: precision_at_1 value: 34.703 - type: precision_at_10 value: 8.744 - type: precision_at_100 value: 1.348 - type: precision_at_1000 value: 0.167 - type: precision_at_3 value: 19.102 - type: precision_at_5 value: 13.836 - type: recall_at_1 value: 28.397 - type: recall_at_10 value: 60.299 - type: recall_at_100 value: 84.595 - type: recall_at_1000 value: 96.155 - type: recall_at_3 value: 43.065 - type: recall_at_5 value: 50.371 - task: type: Retrieval dataset: name: MTEB CQADupstackRetrieval type: BeIR/cqadupstack config: default split: test revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 metrics: - type: map_at_1 value: 28.044333333333338 - type: map_at_10 value: 38.78691666666666 - type: map_at_100 value: 40.113 - type: map_at_1000 value: 40.22125 - type: map_at_3 value: 35.52966666666667 - type: map_at_5 value: 37.372749999999996 - type: mrr_at_1 value: 33.159083333333335 - type: mrr_at_10 value: 42.913583333333335 - type: mrr_at_100 value: 43.7845 - type: mrr_at_1000 value: 43.830333333333336 - type: mrr_at_3 value: 40.29816666666667 - type: mrr_at_5 value: 41.81366666666667 - type: ndcg_at_1 value: 33.159083333333335 - type: ndcg_at_10 value: 44.75750000000001 - type: ndcg_at_100 value: 50.13658333333334 - type: ndcg_at_1000 value: 52.037 - type: ndcg_at_3 value: 39.34258333333334 - type: ndcg_at_5 value: 41.93708333333333 - type: precision_at_1 value: 33.159083333333335 - type: precision_at_10 value: 7.952416666666667 - type: precision_at_100 value: 1.2571666666666668 - type: precision_at_1000 value: 0.16099999999999998 - type: precision_at_3 value: 18.303833333333337 - type: precision_at_5 value: 13.057083333333333 - type: recall_at_1 value: 28.044333333333338 - type: recall_at_10 value: 58.237249999999996 - type: recall_at_100 value: 81.35391666666666 - type: recall_at_1000 value: 94.21283333333334 - type: recall_at_3 value: 43.32341666666667 - type: recall_at_5 value: 49.94908333333333 - type: map_at_1 value: 18.398 - type: map_at_10 value: 27.929 - type: map_at_100 value: 29.032999999999998 - type: map_at_1000 value: 29.126 - type: map_at_3 value: 25.070999999999998 - type: map_at_5 value: 26.583000000000002 - type: mrr_at_1 value: 19.963 - type: mrr_at_10 value: 29.997 - type: mrr_at_100 value: 30.9 - type: mrr_at_1000 value: 30.972 - type: mrr_at_3 value: 27.264 - type: mrr_at_5 value: 28.826 - type: ndcg_at_1 value: 19.963 - type: ndcg_at_10 value: 33.678999999999995 - type: ndcg_at_100 value: 38.931 - type: ndcg_at_1000 value: 41.379 - type: ndcg_at_3 value: 28.000000000000004 - type: ndcg_at_5 value: 30.637999999999998 - type: precision_at_1 value: 19.963 - type: precision_at_10 value: 5.7299999999999995 - type: precision_at_100 value: 0.902 - type: precision_at_1000 value: 0.122 - type: precision_at_3 value: 12.631 - type: precision_at_5 value: 9.057 - type: recall_at_1 value: 18.398 - type: recall_at_10 value: 49.254 - type: recall_at_100 value: 73.182 - type: recall_at_1000 value: 91.637 - type: recall_at_3 value: 34.06 - type: recall_at_5 value: 40.416000000000004 - task: type: Retrieval dataset: name: MTEB CQADupstackStatsRetrieval type: BeIR/cqadupstack config: default split: test revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a metrics: - type: map_at_1 value: 27.838 - type: map_at_10 value: 36.04 - type: map_at_100 value: 37.113 - type: map_at_1000 value: 37.204 - type: map_at_3 value: 33.585 - type: map_at_5 value: 34.845 - type: mrr_at_1 value: 30.982 - type: mrr_at_10 value: 39.105000000000004 - type: mrr_at_100 value: 39.98 - type: mrr_at_1000 value: 40.042 - type: mrr_at_3 value: 36.912 - type: mrr_at_5 value: 38.062000000000005 - type: ndcg_at_1 value: 30.982 - type: ndcg_at_10 value: 40.982 - type: ndcg_at_100 value: 46.092 - type: ndcg_at_1000 value: 48.25 - type: ndcg_at_3 value: 36.41 - type: ndcg_at_5 value: 38.379999999999995 - type: precision_at_1 value: 30.982 - type: precision_at_10 value: 6.534 - type: precision_at_100 value: 0.9820000000000001 - type: precision_at_1000 value: 0.124 - type: precision_at_3 value: 15.745999999999999 - type: precision_at_5 value: 10.828 - type: recall_at_1 value: 27.838 - type: recall_at_10 value: 52.971000000000004 - type: recall_at_100 value: 76.357 - type: recall_at_1000 value: 91.973 - type: recall_at_3 value: 40.157 - type: recall_at_5 value: 45.147999999999996 - task: type: Retrieval dataset: name: MTEB CQADupstackTexRetrieval type: BeIR/cqadupstack config: default split: test revision: 46989137a86843e03a6195de44b09deda022eec7 metrics: - type: map_at_1 value: 19.059 - type: map_at_10 value: 27.454 - type: map_at_100 value: 28.736 - type: map_at_1000 value: 28.865000000000002 - type: map_at_3 value: 24.773999999999997 - type: map_at_5 value: 26.266000000000002 - type: mrr_at_1 value: 23.125 - type: mrr_at_10 value: 31.267 - type: mrr_at_100 value: 32.32 - type: mrr_at_1000 value: 32.394 - type: mrr_at_3 value: 28.894 - type: mrr_at_5 value: 30.281000000000002 - type: ndcg_at_1 value: 23.125 - type: ndcg_at_10 value: 32.588 - type: ndcg_at_100 value: 38.432 - type: ndcg_at_1000 value: 41.214 - type: ndcg_at_3 value: 27.938000000000002 - type: ndcg_at_5 value: 30.127 - type: precision_at_1 value: 23.125 - type: precision_at_10 value: 5.9639999999999995 - type: precision_at_100 value: 1.047 - type: precision_at_1000 value: 0.148 - type: precision_at_3 value: 13.294 - type: precision_at_5 value: 9.628 - type: recall_at_1 value: 19.059 - type: recall_at_10 value: 44.25 - type: recall_at_100 value: 69.948 - type: recall_at_1000 value: 89.35300000000001 - type: recall_at_3 value: 31.114000000000004 - type: recall_at_5 value: 36.846000000000004 - task: type: Retrieval dataset: name: MTEB CQADupstackUnixRetrieval type: BeIR/cqadupstack config: default split: test revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 metrics: - type: map_at_1 value: 28.355999999999998 - type: map_at_10 value: 39.055 - type: map_at_100 value: 40.486 - type: map_at_1000 value: 40.571 - type: map_at_3 value: 35.69 - type: map_at_5 value: 37.605 - type: mrr_at_1 value: 33.302 - type: mrr_at_10 value: 42.986000000000004 - type: mrr_at_100 value: 43.957 - type: mrr_at_1000 value: 43.996 - type: mrr_at_3 value: 40.111999999999995 - type: mrr_at_5 value: 41.735 - type: ndcg_at_1 value: 33.302 - type: ndcg_at_10 value: 44.962999999999994 - type: ndcg_at_100 value: 50.917 - type: ndcg_at_1000 value: 52.622 - type: ndcg_at_3 value: 39.182 - type: ndcg_at_5 value: 41.939 - type: precision_at_1 value: 33.302 - type: precision_at_10 value: 7.779999999999999 - type: precision_at_100 value: 1.203 - type: precision_at_1000 value: 0.145 - type: precision_at_3 value: 18.035 - type: precision_at_5 value: 12.873000000000001 - type: recall_at_1 value: 28.355999999999998 - type: recall_at_10 value: 58.782000000000004 - type: recall_at_100 value: 84.02199999999999 - type: recall_at_1000 value: 95.511 - type: recall_at_3 value: 43.126999999999995 - type: recall_at_5 value: 50.14999999999999 - task: type: Retrieval dataset: name: MTEB CQADupstackWebmastersRetrieval type: BeIR/cqadupstack config: default split: test revision: 160c094312a0e1facb97e55eeddb698c0abe3571 metrics: - type: map_at_1 value: 27.391 - type: map_at_10 value: 37.523 - type: map_at_100 value: 39.312000000000005 - type: map_at_1000 value: 39.54 - type: map_at_3 value: 34.231 - type: map_at_5 value: 36.062 - type: mrr_at_1 value: 32.016 - type: mrr_at_10 value: 41.747 - type: mrr_at_100 value: 42.812 - type: mrr_at_1000 value: 42.844 - type: mrr_at_3 value: 39.129999999999995 - type: mrr_at_5 value: 40.524 - type: ndcg_at_1 value: 32.016 - type: ndcg_at_10 value: 43.826 - type: ndcg_at_100 value: 50.373999999999995 - type: ndcg_at_1000 value: 52.318 - type: ndcg_at_3 value: 38.479 - type: ndcg_at_5 value: 40.944 - type: precision_at_1 value: 32.016 - type: precision_at_10 value: 8.280999999999999 - type: precision_at_100 value: 1.6760000000000002 - type: precision_at_1000 value: 0.25 - type: precision_at_3 value: 18.05 - type: precision_at_5 value: 13.083 - type: recall_at_1 value: 27.391 - type: recall_at_10 value: 56.928999999999995 - type: recall_at_100 value: 85.169 - type: recall_at_1000 value: 96.665 - type: recall_at_3 value: 42.264 - type: recall_at_5 value: 48.556 - task: type: Retrieval dataset: name: MTEB ClimateFEVER type: mteb/climate-fever config: default split: test revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 metrics: - type: map_at_1 value: 19.681 - type: map_at_10 value: 32.741 - type: map_at_100 value: 34.811 - type: map_at_1000 value: 35.003 - type: map_at_3 value: 27.697 - type: map_at_5 value: 30.372 - type: mrr_at_1 value: 44.951 - type: mrr_at_10 value: 56.34400000000001 - type: mrr_at_100 value: 56.961 - type: mrr_at_1000 value: 56.987 - type: mrr_at_3 value: 53.681 - type: mrr_at_5 value: 55.407 - type: ndcg_at_1 value: 44.951 - type: ndcg_at_10 value: 42.905 - type: ndcg_at_100 value: 49.95 - type: ndcg_at_1000 value: 52.917 - type: ndcg_at_3 value: 36.815 - type: ndcg_at_5 value: 38.817 - type: precision_at_1 value: 44.951 - type: precision_at_10 value: 12.989999999999998 - type: precision_at_100 value: 2.068 - type: precision_at_1000 value: 0.263 - type: precision_at_3 value: 27.275 - type: precision_at_5 value: 20.365 - type: recall_at_1 value: 19.681 - type: recall_at_10 value: 48.272999999999996 - type: recall_at_100 value: 71.87400000000001 - type: recall_at_1000 value: 87.929 - type: recall_at_3 value: 32.653999999999996 - type: recall_at_5 value: 39.364 - task: type: Retrieval dataset: name: MTEB DBPedia type: mteb/dbpedia config: default split: test revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 metrics: - type: map_at_1 value: 10.231 - type: map_at_10 value: 22.338 - type: map_at_100 value: 31.927 - type: map_at_1000 value: 33.87 - type: map_at_3 value: 15.559999999999999 - type: map_at_5 value: 18.239 - type: mrr_at_1 value: 75.0 - type: mrr_at_10 value: 81.303 - type: mrr_at_100 value: 81.523 - type: mrr_at_1000 value: 81.53 - type: mrr_at_3 value: 80.083 - type: mrr_at_5 value: 80.758 - type: ndcg_at_1 value: 64.625 - type: ndcg_at_10 value: 48.687000000000005 - type: ndcg_at_100 value: 52.791 - type: ndcg_at_1000 value: 60.041999999999994 - type: ndcg_at_3 value: 53.757999999999996 - type: ndcg_at_5 value: 50.76500000000001 - type: precision_at_1 value: 75.0 - type: precision_at_10 value: 38.3 - type: precision_at_100 value: 12.025 - type: precision_at_1000 value: 2.3970000000000002 - type: precision_at_3 value: 55.417 - type: precision_at_5 value: 47.5 - type: recall_at_1 value: 10.231 - type: recall_at_10 value: 27.697 - type: recall_at_100 value: 57.409 - type: recall_at_1000 value: 80.547 - type: recall_at_3 value: 16.668 - type: recall_at_5 value: 20.552 - task: type: Classification dataset: name: MTEB EmotionClassification type: mteb/emotion config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 61.365 - type: f1 value: 56.7540827912991 - task: type: Retrieval dataset: name: MTEB FEVER type: mteb/fever config: default split: test revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 metrics: - type: map_at_1 value: 83.479 - type: map_at_10 value: 88.898 - type: map_at_100 value: 89.11 - type: map_at_1000 value: 89.12400000000001 - type: map_at_3 value: 88.103 - type: map_at_5 value: 88.629 - type: mrr_at_1 value: 89.934 - type: mrr_at_10 value: 93.91000000000001 - type: mrr_at_100 value: 93.937 - type: mrr_at_1000 value: 93.938 - type: mrr_at_3 value: 93.62700000000001 - type: mrr_at_5 value: 93.84599999999999 - type: ndcg_at_1 value: 89.934 - type: ndcg_at_10 value: 91.574 - type: ndcg_at_100 value: 92.238 - type: ndcg_at_1000 value: 92.45 - type: ndcg_at_3 value: 90.586 - type: ndcg_at_5 value: 91.16300000000001 - type: precision_at_1 value: 89.934 - type: precision_at_10 value: 10.555 - type: precision_at_100 value: 1.1159999999999999 - type: precision_at_1000 value: 0.11499999999999999 - type: precision_at_3 value: 33.588 - type: precision_at_5 value: 20.642 - type: recall_at_1 value: 83.479 - type: recall_at_10 value: 94.971 - type: recall_at_100 value: 97.397 - type: recall_at_1000 value: 98.666 - type: recall_at_3 value: 92.24799999999999 - type: recall_at_5 value: 93.797 - task: type: Retrieval dataset: name: MTEB FiQA2018 type: mteb/fiqa config: default split: test revision: 27a168819829fe9bcd655c2df245fb19452e8e06 metrics: - type: map_at_1 value: 27.16 - type: map_at_10 value: 45.593 - type: map_at_100 value: 47.762 - type: map_at_1000 value: 47.899 - type: map_at_3 value: 39.237 - type: map_at_5 value: 42.970000000000006 - type: mrr_at_1 value: 52.623 - type: mrr_at_10 value: 62.637 - type: mrr_at_100 value: 63.169 - type: mrr_at_1000 value: 63.185 - type: mrr_at_3 value: 59.928000000000004 - type: mrr_at_5 value: 61.702999999999996 - type: ndcg_at_1 value: 52.623 - type: ndcg_at_10 value: 54.701 - type: ndcg_at_100 value: 61.263 - type: ndcg_at_1000 value: 63.134 - type: ndcg_at_3 value: 49.265 - type: ndcg_at_5 value: 51.665000000000006 - type: precision_at_1 value: 52.623 - type: precision_at_10 value: 15.185 - type: precision_at_100 value: 2.202 - type: precision_at_1000 value: 0.254 - type: precision_at_3 value: 32.767 - type: precision_at_5 value: 24.722 - type: recall_at_1 value: 27.16 - type: recall_at_10 value: 63.309000000000005 - type: recall_at_100 value: 86.722 - type: recall_at_1000 value: 97.505 - type: recall_at_3 value: 45.045 - type: recall_at_5 value: 54.02400000000001 - task: type: Retrieval dataset: name: MTEB HotpotQA type: mteb/hotpotqa config: default split: test revision: ab518f4d6fcca38d87c25209f94beba119d02014 metrics: - type: map_at_1 value: 42.573 - type: map_at_10 value: 59.373 - type: map_at_100 value: 60.292 - type: map_at_1000 value: 60.358999999999995 - type: map_at_3 value: 56.159000000000006 - type: map_at_5 value: 58.123999999999995 - type: mrr_at_1 value: 85.14500000000001 - type: mrr_at_10 value: 89.25999999999999 - type: mrr_at_100 value: 89.373 - type: mrr_at_1000 value: 89.377 - type: mrr_at_3 value: 88.618 - type: mrr_at_5 value: 89.036 - type: ndcg_at_1 value: 85.14500000000001 - type: ndcg_at_10 value: 68.95 - type: ndcg_at_100 value: 71.95 - type: ndcg_at_1000 value: 73.232 - type: ndcg_at_3 value: 64.546 - type: ndcg_at_5 value: 66.945 - type: precision_at_1 value: 85.14500000000001 - type: precision_at_10 value: 13.865 - type: precision_at_100 value: 1.619 - type: precision_at_1000 value: 0.179 - type: precision_at_3 value: 39.703 - type: precision_at_5 value: 25.718000000000004 - type: recall_at_1 value: 42.573 - type: recall_at_10 value: 69.325 - type: recall_at_100 value: 80.932 - type: recall_at_1000 value: 89.446 - type: recall_at_3 value: 59.553999999999995 - type: recall_at_5 value: 64.294 - task: type: Classification dataset: name: MTEB ImdbClassification type: mteb/imdb config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 95.8336 - type: ap value: 93.78862962194073 - type: f1 value: 95.83192650728371 - task: type: Retrieval dataset: name: MTEB MSMARCO type: mteb/msmarco config: default split: dev revision: c5a29a104738b98a9e76336939199e264163d4a0 metrics: - type: map_at_1 value: 23.075000000000003 - type: map_at_10 value: 36.102000000000004 - type: map_at_100 value: 37.257 - type: map_at_1000 value: 37.3 - type: map_at_3 value: 32.144 - type: map_at_5 value: 34.359 - type: mrr_at_1 value: 23.711 - type: mrr_at_10 value: 36.671 - type: mrr_at_100 value: 37.763999999999996 - type: mrr_at_1000 value: 37.801 - type: mrr_at_3 value: 32.775 - type: mrr_at_5 value: 34.977000000000004 - type: ndcg_at_1 value: 23.711 - type: ndcg_at_10 value: 43.361 - type: ndcg_at_100 value: 48.839 - type: ndcg_at_1000 value: 49.88 - type: ndcg_at_3 value: 35.269 - type: ndcg_at_5 value: 39.224 - type: precision_at_1 value: 23.711 - type: precision_at_10 value: 6.866999999999999 - type: precision_at_100 value: 0.96 - type: precision_at_1000 value: 0.105 - type: precision_at_3 value: 15.096000000000002 - type: precision_at_5 value: 11.083 - type: recall_at_1 value: 23.075000000000003 - type: recall_at_10 value: 65.756 - type: recall_at_100 value: 90.88199999999999 - type: recall_at_1000 value: 98.739 - type: recall_at_3 value: 43.691 - type: recall_at_5 value: 53.15800000000001 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (en) type: mteb/mtop_domain config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 97.69493844049248 - type: f1 value: 97.55048089616261 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (en) type: mteb/mtop_intent config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 88.75968992248062 - type: f1 value: 72.26321223399123 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (en) type: mteb/amazon_massive_intent config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 82.40080699394754 - type: f1 value: 79.62590029057968 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (en) type: mteb/amazon_massive_scenario config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 84.49562878278414 - type: f1 value: 84.0040193313333 - task: type: Clustering dataset: name: MTEB MedrxivClusteringP2P type: mteb/medrxiv-clustering-p2p config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 39.386760057101945 - task: type: Clustering dataset: name: MTEB MedrxivClusteringS2S type: mteb/medrxiv-clustering-s2s config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 37.89687154075537 - task: type: Reranking dataset: name: MTEB MindSmallReranking type: mteb/mind_small config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 33.94151656057482 - type: mrr value: 35.32684700746953 - task: type: Retrieval dataset: name: MTEB NFCorpus type: mteb/nfcorpus config: default split: test revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 metrics: - type: map_at_1 value: 6.239999999999999 - type: map_at_10 value: 14.862 - type: map_at_100 value: 18.955 - type: map_at_1000 value: 20.694000000000003 - type: map_at_3 value: 10.683 - type: map_at_5 value: 12.674 - type: mrr_at_1 value: 50.15500000000001 - type: mrr_at_10 value: 59.697 - type: mrr_at_100 value: 60.095 - type: mrr_at_1000 value: 60.129999999999995 - type: mrr_at_3 value: 58.35900000000001 - type: mrr_at_5 value: 58.839 - type: ndcg_at_1 value: 48.452 - type: ndcg_at_10 value: 39.341 - type: ndcg_at_100 value: 35.866 - type: ndcg_at_1000 value: 45.111000000000004 - type: ndcg_at_3 value: 44.527 - type: ndcg_at_5 value: 42.946 - type: precision_at_1 value: 50.15500000000001 - type: precision_at_10 value: 29.536 - type: precision_at_100 value: 9.142 - type: precision_at_1000 value: 2.2849999999999997 - type: precision_at_3 value: 41.899 - type: precision_at_5 value: 37.647000000000006 - type: recall_at_1 value: 6.239999999999999 - type: recall_at_10 value: 19.278000000000002 - type: recall_at_100 value: 36.074 - type: recall_at_1000 value: 70.017 - type: recall_at_3 value: 12.066 - type: recall_at_5 value: 15.254000000000001 - task: type: Retrieval dataset: name: MTEB NQ type: mteb/nq config: default split: test revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 metrics: - type: map_at_1 value: 39.75 - type: map_at_10 value: 56.443 - type: map_at_100 value: 57.233999999999995 - type: map_at_1000 value: 57.249 - type: map_at_3 value: 52.032999999999994 - type: map_at_5 value: 54.937999999999995 - type: mrr_at_1 value: 44.728 - type: mrr_at_10 value: 58.939 - type: mrr_at_100 value: 59.489000000000004 - type: mrr_at_1000 value: 59.499 - type: mrr_at_3 value: 55.711999999999996 - type: mrr_at_5 value: 57.89 - type: ndcg_at_1 value: 44.728 - type: ndcg_at_10 value: 63.998999999999995 - type: ndcg_at_100 value: 67.077 - type: ndcg_at_1000 value: 67.40899999999999 - type: ndcg_at_3 value: 56.266000000000005 - type: ndcg_at_5 value: 60.88 - type: precision_at_1 value: 44.728 - type: precision_at_10 value: 10.09 - type: precision_at_100 value: 1.1809999999999998 - type: precision_at_1000 value: 0.121 - type: precision_at_3 value: 25.145 - type: precision_at_5 value: 17.822 - type: recall_at_1 value: 39.75 - type: recall_at_10 value: 84.234 - type: recall_at_100 value: 97.055 - type: recall_at_1000 value: 99.517 - type: recall_at_3 value: 64.851 - type: recall_at_5 value: 75.343 - task: type: Retrieval dataset: name: MTEB QuoraRetrieval type: mteb/quora config: default split: test revision: None metrics: - type: map_at_1 value: 72.085 - type: map_at_10 value: 86.107 - type: map_at_100 value: 86.727 - type: map_at_1000 value: 86.74 - type: map_at_3 value: 83.21 - type: map_at_5 value: 85.06 - type: mrr_at_1 value: 82.94 - type: mrr_at_10 value: 88.845 - type: mrr_at_100 value: 88.926 - type: mrr_at_1000 value: 88.927 - type: mrr_at_3 value: 87.993 - type: mrr_at_5 value: 88.62299999999999 - type: ndcg_at_1 value: 82.97 - type: ndcg_at_10 value: 89.645 - type: ndcg_at_100 value: 90.717 - type: ndcg_at_1000 value: 90.78 - type: ndcg_at_3 value: 86.99900000000001 - type: ndcg_at_5 value: 88.52600000000001 - type: precision_at_1 value: 82.97 - type: precision_at_10 value: 13.569 - type: precision_at_100 value: 1.539 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 38.043 - type: precision_at_5 value: 24.992 - type: recall_at_1 value: 72.085 - type: recall_at_10 value: 96.262 - type: recall_at_100 value: 99.77000000000001 - type: recall_at_1000 value: 99.997 - type: recall_at_3 value: 88.652 - type: recall_at_5 value: 93.01899999999999 - task: type: Clustering dataset: name: MTEB RedditClustering type: mteb/reddit-clustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 55.82153952668092 - task: type: Clustering dataset: name: MTEB RedditClusteringP2P type: mteb/reddit-clustering-p2p config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 62.094465801879295 - task: type: Retrieval dataset: name: MTEB SCIDOCS type: mteb/scidocs config: default split: test revision: None metrics: - type: map_at_1 value: 5.688 - type: map_at_10 value: 15.201999999999998 - type: map_at_100 value: 18.096 - type: map_at_1000 value: 18.481 - type: map_at_3 value: 10.734 - type: map_at_5 value: 12.94 - type: mrr_at_1 value: 28.000000000000004 - type: mrr_at_10 value: 41.101 - type: mrr_at_100 value: 42.202 - type: mrr_at_1000 value: 42.228 - type: mrr_at_3 value: 37.683 - type: mrr_at_5 value: 39.708 - type: ndcg_at_1 value: 28.000000000000004 - type: ndcg_at_10 value: 24.976000000000003 - type: ndcg_at_100 value: 35.129 - type: ndcg_at_1000 value: 40.77 - type: ndcg_at_3 value: 23.787 - type: ndcg_at_5 value: 20.816000000000003 - type: precision_at_1 value: 28.000000000000004 - type: precision_at_10 value: 13.04 - type: precision_at_100 value: 2.761 - type: precision_at_1000 value: 0.41000000000000003 - type: precision_at_3 value: 22.6 - type: precision_at_5 value: 18.52 - type: recall_at_1 value: 5.688 - type: recall_at_10 value: 26.43 - type: recall_at_100 value: 56.02 - type: recall_at_1000 value: 83.21 - type: recall_at_3 value: 13.752 - type: recall_at_5 value: 18.777 - task: type: STS dataset: name: MTEB SICK-R type: mteb/sickr-sts config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 85.15084859283178 - type: cos_sim_spearman value: 80.49030614009419 - type: euclidean_pearson value: 81.84574978672468 - type: euclidean_spearman value: 79.89787150656818 - type: manhattan_pearson value: 81.63076538567131 - type: manhattan_spearman value: 79.69867352121841 - task: type: STS dataset: name: MTEB STS12 type: mteb/sts12-sts config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 84.64097921490992 - type: cos_sim_spearman value: 77.25370084896514 - type: euclidean_pearson value: 82.71210826468788 - 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task: type: Retrieval dataset: name: MTEB EcomRetrieval type: C-MTEB/EcomRetrieval config: default split: dev revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9 metrics: - type: map_at_1 value: 47.699999999999996 - type: map_at_10 value: 57.589999999999996 - type: map_at_100 value: 58.226 - type: map_at_1000 value: 58.251 - type: map_at_3 value: 55.233 - type: map_at_5 value: 56.633 - type: mrr_at_1 value: 47.699999999999996 - type: mrr_at_10 value: 57.589999999999996 - type: mrr_at_100 value: 58.226 - type: mrr_at_1000 value: 58.251 - type: mrr_at_3 value: 55.233 - type: mrr_at_5 value: 56.633 - type: ndcg_at_1 value: 47.699999999999996 - type: ndcg_at_10 value: 62.505 - type: ndcg_at_100 value: 65.517 - type: ndcg_at_1000 value: 66.19800000000001 - type: ndcg_at_3 value: 57.643 - type: ndcg_at_5 value: 60.181 - type: precision_at_1 value: 47.699999999999996 - type: precision_at_10 value: 7.8 - type: precision_at_100 value: 0.919 - type: precision_at_1000 value: 0.097 - type: precision_at_3 value: 21.532999999999998 - type: precision_at_5 value: 14.16 - type: recall_at_1 value: 47.699999999999996 - type: recall_at_10 value: 78.0 - type: recall_at_100 value: 91.9 - type: recall_at_1000 value: 97.3 - type: recall_at_3 value: 64.60000000000001 - type: recall_at_5 value: 70.8 - task: type: Classification dataset: name: MTEB IFlyTek type: C-MTEB/IFlyTek-classification config: default split: validation revision: 421605374b29664c5fc098418fe20ada9bd55f8a metrics: - type: accuracy value: 44.84801846864178 - type: f1 value: 37.47347897956339 - task: type: Classification dataset: name: MTEB JDReview type: C-MTEB/JDReview-classification config: default split: test revision: b7c64bd89eb87f8ded463478346f76731f07bf8b metrics: - type: accuracy value: 85.81613508442777 - type: ap value: 52.68244615477374 - type: f1 value: 80.0445640948843 - task: type: STS dataset: name: MTEB LCQMC type: C-MTEB/LCQMC config: default split: test revision: 17f9b096f80380fce5ed12a9be8be7784b337daf metrics: - type: cos_sim_pearson value: 69.57786502217138 - type: cos_sim_spearman value: 75.39106054489906 - type: euclidean_pearson value: 73.72082954602402 - type: euclidean_spearman value: 75.14421475913619 - type: manhattan_pearson value: 73.62463076633642 - type: manhattan_spearman value: 75.01301565104112 - task: type: Reranking dataset: name: MTEB MMarcoReranking type: C-MTEB/Mmarco-reranking config: default split: dev revision: None metrics: - type: map value: 29.143797057999134 - type: mrr value: 28.08174603174603 - task: type: Retrieval dataset: name: MTEB MMarcoRetrieval type: C-MTEB/MMarcoRetrieval config: default split: dev revision: 539bbde593d947e2a124ba72651aafc09eb33fc2 metrics: - type: map_at_1 value: 70.492 - type: map_at_10 value: 79.501 - type: map_at_100 value: 79.728 - type: map_at_1000 value: 79.735 - type: map_at_3 value: 77.77 - type: map_at_5 value: 78.851 - type: mrr_at_1 value: 72.822 - type: mrr_at_10 value: 80.001 - type: mrr_at_100 value: 80.19 - type: mrr_at_1000 value: 80.197 - type: mrr_at_3 value: 78.484 - type: mrr_at_5 value: 79.42099999999999 - type: ndcg_at_1 value: 72.822 - type: ndcg_at_10 value: 83.013 - type: ndcg_at_100 value: 84.013 - type: ndcg_at_1000 value: 84.20400000000001 - type: ndcg_at_3 value: 79.728 - type: ndcg_at_5 value: 81.542 - type: precision_at_1 value: 72.822 - type: precision_at_10 value: 9.917 - type: precision_at_100 value: 1.042 - type: precision_at_1000 value: 0.106 - type: precision_at_3 value: 29.847 - type: precision_at_5 value: 18.871 - type: recall_at_1 value: 70.492 - type: recall_at_10 value: 93.325 - type: recall_at_100 value: 97.822 - type: recall_at_1000 value: 99.319 - type: recall_at_3 value: 84.636 - type: recall_at_5 value: 88.93100000000001 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (zh-CN) type: mteb/amazon_massive_intent config: zh-CN split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 76.88298587760592 - type: f1 value: 73.89001762017176 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (zh-CN) type: mteb/amazon_massive_scenario config: zh-CN split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 80.76328177538669 - type: f1 value: 80.24718532423358 - task: type: Retrieval dataset: name: MTEB MedicalRetrieval type: C-MTEB/MedicalRetrieval config: default split: dev revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6 metrics: - type: map_at_1 value: 49.6 - type: map_at_10 value: 55.620999999999995 - type: map_at_100 value: 56.204 - type: map_at_1000 value: 56.251 - type: map_at_3 value: 54.132999999999996 - type: map_at_5 value: 54.933 - type: mrr_at_1 value: 49.7 - type: mrr_at_10 value: 55.67100000000001 - type: mrr_at_100 value: 56.254000000000005 - type: mrr_at_1000 value: 56.301 - type: mrr_at_3 value: 54.18300000000001 - type: mrr_at_5 value: 54.983000000000004 - type: ndcg_at_1 value: 49.6 - type: ndcg_at_10 value: 58.645 - type: ndcg_at_100 value: 61.789 - type: ndcg_at_1000 value: 63.219 - type: ndcg_at_3 value: 55.567 - type: ndcg_at_5 value: 57.008 - type: precision_at_1 value: 49.6 - type: precision_at_10 value: 6.819999999999999 - type: precision_at_100 value: 0.836 - type: precision_at_1000 value: 0.095 - type: precision_at_3 value: 19.900000000000002 - type: precision_at_5 value: 12.64 - type: recall_at_1 value: 49.6 - type: recall_at_10 value: 68.2 - type: recall_at_100 value: 83.6 - type: recall_at_1000 value: 95.3 - type: recall_at_3 value: 59.699999999999996 - type: recall_at_5 value: 63.2 - task: type: Classification dataset: name: MTEB MultilingualSentiment type: C-MTEB/MultilingualSentiment-classification config: default split: validation revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a metrics: - type: accuracy value: 74.45666666666666 - type: f1 value: 74.32582402190089 - task: type: PairClassification dataset: name: MTEB Ocnli type: C-MTEB/OCNLI config: default split: validation revision: 66e76a618a34d6d565d5538088562851e6daa7ec metrics: - type: cos_sim_accuracy value: 80.67135896047645 - type: cos_sim_ap value: 87.60421240712051 - type: cos_sim_f1 value: 82.1304131408661 - type: cos_sim_precision value: 77.68361581920904 - type: cos_sim_recall value: 87.11721224920802 - type: dot_accuracy value: 79.04710341093666 - type: dot_ap value: 85.6370059719336 - type: dot_f1 value: 80.763723150358 - type: dot_precision value: 73.69337979094077 - type: dot_recall value: 89.33474128827878 - type: euclidean_accuracy value: 81.05035192203573 - type: euclidean_ap value: 87.7880240053663 - type: euclidean_f1 value: 82.50244379276637 - type: euclidean_precision value: 76.7970882620564 - type: euclidean_recall value: 89.1235480464625 - type: manhattan_accuracy value: 80.61721710882512 - type: manhattan_ap value: 87.43568120591175 - type: manhattan_f1 value: 81.89526184538653 - type: manhattan_precision value: 77.5992438563327 - type: manhattan_recall value: 86.6948257655755 - type: max_accuracy value: 81.05035192203573 - type: max_ap value: 87.7880240053663 - type: max_f1 value: 82.50244379276637 - task: type: Classification dataset: name: MTEB OnlineShopping type: C-MTEB/OnlineShopping-classification config: default split: test revision: e610f2ebd179a8fda30ae534c3878750a96db120 metrics: - type: accuracy value: 93.5 - type: ap value: 91.31357903446782 - type: f1 value: 93.48088994006616 - task: type: STS dataset: name: MTEB PAWSX type: C-MTEB/PAWSX config: default split: test revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1 metrics: - type: cos_sim_pearson value: 36.93293453538077 - type: cos_sim_spearman value: 42.45972506308574 - type: euclidean_pearson value: 42.34945133152159 - type: euclidean_spearman value: 42.331610303674644 - type: manhattan_pearson value: 42.31455070249498 - type: manhattan_spearman value: 42.19887982891834 - task: type: STS dataset: name: MTEB QBQTC type: C-MTEB/QBQTC config: default split: test revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7 metrics: - type: cos_sim_pearson value: 33.683290790043785 - type: cos_sim_spearman value: 35.149171171202994 - type: euclidean_pearson value: 32.33806561267862 - type: euclidean_spearman value: 34.483576387347966 - type: manhattan_pearson value: 32.47629754599608 - type: manhattan_spearman value: 34.66434471867615 - task: type: STS dataset: name: MTEB STS22 (zh) type: mteb/sts22-crosslingual-sts config: zh split: test revision: eea2b4fe26a775864c896887d910b76a8098ad3f metrics: - type: cos_sim_pearson value: 66.46322760516104 - type: cos_sim_spearman value: 67.398478319726 - type: euclidean_pearson value: 64.7223480293625 - type: euclidean_spearman value: 66.83118568812951 - type: manhattan_pearson value: 64.88440039828305 - type: manhattan_spearman value: 66.80429458952257 - task: type: STS dataset: name: MTEB STSB type: C-MTEB/STSB config: default split: test revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0 metrics: - type: cos_sim_pearson value: 79.08991383232105 - type: cos_sim_spearman value: 79.39715677296854 - type: euclidean_pearson value: 78.63201279320496 - type: euclidean_spearman value: 79.40262660785731 - type: manhattan_pearson value: 78.98138363146906 - type: manhattan_spearman value: 79.79968413014194 - task: type: Reranking dataset: name: MTEB T2Reranking type: C-MTEB/T2Reranking config: default split: dev revision: 76631901a18387f85eaa53e5450019b87ad58ef9 metrics: - type: map value: 67.43289278789972 - type: mrr value: 77.53012460908535 - task: type: Retrieval dataset: name: MTEB T2Retrieval type: C-MTEB/T2Retrieval config: default split: dev revision: 8731a845f1bf500a4f111cf1070785c793d10e64 metrics: - type: map_at_1 value: 27.733999999999998 - type: map_at_10 value: 78.24799999999999 - type: map_at_100 value: 81.765 - type: map_at_1000 value: 81.824 - type: map_at_3 value: 54.92 - type: map_at_5 value: 67.61399999999999 - type: mrr_at_1 value: 90.527 - type: mrr_at_10 value: 92.843 - type: mrr_at_100 value: 92.927 - type: mrr_at_1000 value: 92.93 - type: mrr_at_3 value: 92.45100000000001 - type: mrr_at_5 value: 92.693 - type: ndcg_at_1 value: 90.527 - type: ndcg_at_10 value: 85.466 - type: ndcg_at_100 value: 88.846 - type: ndcg_at_1000 value: 89.415 - type: ndcg_at_3 value: 86.768 - type: ndcg_at_5 value: 85.46000000000001 - type: precision_at_1 value: 90.527 - type: precision_at_10 value: 42.488 - type: precision_at_100 value: 5.024 - type: precision_at_1000 value: 0.516 - type: precision_at_3 value: 75.907 - type: precision_at_5 value: 63.727000000000004 - type: recall_at_1 value: 27.733999999999998 - type: recall_at_10 value: 84.346 - type: recall_at_100 value: 95.536 - type: recall_at_1000 value: 98.42999999999999 - type: recall_at_3 value: 56.455 - type: recall_at_5 value: 70.755 - task: type: Classification dataset: name: MTEB TNews type: C-MTEB/TNews-classification config: default split: validation revision: 317f262bf1e6126357bbe89e875451e4b0938fe4 metrics: - type: accuracy value: 49.952000000000005 - type: f1 value: 48.264617195258054 - task: type: Clustering dataset: name: MTEB ThuNewsClusteringP2P type: C-MTEB/ThuNewsClusteringP2P config: default split: test revision: 5798586b105c0434e4f0fe5e767abe619442cf93 metrics: - type: v_measure value: 68.23769904483508 - task: type: Clustering dataset: name: MTEB ThuNewsClusteringS2S type: C-MTEB/ThuNewsClusteringS2S config: default split: test revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d metrics: - type: v_measure value: 62.50294403136556 - task: type: Retrieval dataset: name: MTEB VideoRetrieval type: C-MTEB/VideoRetrieval config: default split: dev revision: 58c2597a5943a2ba48f4668c3b90d796283c5639 metrics: - type: map_at_1 value: 54.0 - type: map_at_10 value: 63.668 - type: map_at_100 value: 64.217 - type: map_at_1000 value: 64.23100000000001 - type: map_at_3 value: 61.7 - type: map_at_5 value: 62.870000000000005 - type: mrr_at_1 value: 54.0 - type: mrr_at_10 value: 63.668 - type: mrr_at_100 value: 64.217 - type: mrr_at_1000 value: 64.23100000000001 - type: mrr_at_3 value: 61.7 - type: mrr_at_5 value: 62.870000000000005 - type: ndcg_at_1 value: 54.0 - type: ndcg_at_10 value: 68.11399999999999 - type: ndcg_at_100 value: 70.723 - type: ndcg_at_1000 value: 71.123 - type: ndcg_at_3 value: 64.074 - type: ndcg_at_5 value: 66.178 - type: precision_at_1 value: 54.0 - type: precision_at_10 value: 8.200000000000001 - type: precision_at_100 value: 0.941 - type: precision_at_1000 value: 0.097 - type: precision_at_3 value: 23.633000000000003 - type: precision_at_5 value: 15.2 - type: recall_at_1 value: 54.0 - type: recall_at_10 value: 82.0 - type: recall_at_100 value: 94.1 - type: recall_at_1000 value: 97.3 - type: recall_at_3 value: 70.89999999999999 - type: recall_at_5 value: 76.0 - task: type: Classification dataset: name: MTEB Waimai type: C-MTEB/waimai-classification config: default split: test revision: 339287def212450dcaa9df8c22bf93e9980c7023 metrics: - type: accuracy value: 86.63000000000001 - type: ap value: 69.99457882599567 - type: f1 value: 85.07735617998541 - task: type: Clustering dataset: name: MTEB 8TagsClustering type: PL-MTEB/8tags-clustering config: default split: test revision: None metrics: - type: v_measure value: 44.594104491193555 - task: type: Classification dataset: name: MTEB AllegroReviews type: PL-MTEB/allegro-reviews config: default split: test revision: None metrics: - type: accuracy value: 63.97614314115309 - type: f1 value: 52.15634261679283 - task: type: Retrieval dataset: name: MTEB ArguAna-PL type: clarin-knext/arguana-pl config: default split: test revision: 63fc86750af76253e8c760fc9e534bbf24d260a2 metrics: - type: map_at_1 value: 32.646 - type: map_at_10 value: 47.963 - type: map_at_100 value: 48.789 - type: map_at_1000 value: 48.797000000000004 - type: map_at_3 value: 43.196 - type: map_at_5 value: 46.016 - type: mrr_at_1 value: 33.073 - type: mrr_at_10 value: 48.126000000000005 - type: mrr_at_100 value: 48.946 - type: mrr_at_1000 value: 48.953 - type: mrr_at_3 value: 43.374 - type: mrr_at_5 value: 46.147 - type: ndcg_at_1 value: 32.646 - type: ndcg_at_10 value: 56.481 - type: ndcg_at_100 value: 59.922 - type: ndcg_at_1000 value: 60.07 - type: ndcg_at_3 value: 46.675 - type: ndcg_at_5 value: 51.76500000000001 - type: precision_at_1 value: 32.646 - type: precision_at_10 value: 8.371 - type: precision_at_100 value: 0.9860000000000001 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 18.919 - type: precision_at_5 value: 13.825999999999999 - type: recall_at_1 value: 32.646 - type: recall_at_10 value: 83.71300000000001 - type: recall_at_100 value: 98.578 - type: recall_at_1000 value: 99.644 - type: recall_at_3 value: 56.757000000000005 - type: recall_at_5 value: 69.132 - task: type: Classification dataset: name: MTEB CBD type: PL-MTEB/cbd config: default split: test revision: None metrics: - type: accuracy value: 68.56 - type: ap value: 23.310493680488513 - type: f1 value: 58.85369533105693 - task: type: PairClassification dataset: name: MTEB CDSC-E type: PL-MTEB/cdsce-pairclassification config: default split: test revision: None metrics: - type: cos_sim_accuracy value: 88.5 - type: cos_sim_ap value: 72.42140924378361 - type: cos_sim_f1 value: 66.0919540229885 - type: cos_sim_precision value: 72.78481012658227 - type: cos_sim_recall value: 60.526315789473685 - type: dot_accuracy value: 88.5 - type: dot_ap value: 72.42140924378361 - type: dot_f1 value: 66.0919540229885 - type: dot_precision value: 72.78481012658227 - type: dot_recall value: 60.526315789473685 - type: euclidean_accuracy value: 88.5 - type: euclidean_ap value: 72.42140924378361 - type: euclidean_f1 value: 66.0919540229885 - type: euclidean_precision value: 72.78481012658227 - type: euclidean_recall value: 60.526315789473685 - type: manhattan_accuracy value: 88.5 - type: manhattan_ap value: 72.49745515311696 - type: manhattan_f1 value: 66.0968660968661 - type: manhattan_precision value: 72.04968944099379 - type: manhattan_recall value: 61.05263157894737 - type: max_accuracy value: 88.5 - type: max_ap value: 72.49745515311696 - type: max_f1 value: 66.0968660968661 - task: type: STS dataset: name: MTEB CDSC-R type: PL-MTEB/cdscr-sts config: default split: test revision: None metrics: - type: cos_sim_pearson value: 90.32269765590145 - type: cos_sim_spearman value: 89.73666311491672 - type: euclidean_pearson value: 88.2933868516544 - type: euclidean_spearman value: 89.73666311491672 - type: manhattan_pearson value: 88.33474590219448 - type: manhattan_spearman value: 89.8548364866583 - task: type: Retrieval dataset: name: MTEB DBPedia-PL type: clarin-knext/dbpedia-pl config: default split: test revision: 76afe41d9af165cc40999fcaa92312b8b012064a metrics: - type: map_at_1 value: 7.632999999999999 - type: map_at_10 value: 16.426 - type: map_at_100 value: 22.651 - type: map_at_1000 value: 24.372 - type: map_at_3 value: 11.706 - type: map_at_5 value: 13.529 - type: mrr_at_1 value: 60.75000000000001 - type: mrr_at_10 value: 68.613 - type: mrr_at_100 value: 69.001 - type: mrr_at_1000 value: 69.021 - type: mrr_at_3 value: 67.0 - type: mrr_at_5 value: 67.925 - type: ndcg_at_1 value: 49.875 - type: ndcg_at_10 value: 36.978 - type: ndcg_at_100 value: 40.031 - type: ndcg_at_1000 value: 47.566 - type: ndcg_at_3 value: 41.148 - type: ndcg_at_5 value: 38.702 - type: precision_at_1 value: 60.75000000000001 - type: precision_at_10 value: 29.7 - type: precision_at_100 value: 9.278 - type: precision_at_1000 value: 2.099 - type: precision_at_3 value: 44.0 - type: precision_at_5 value: 37.6 - type: recall_at_1 value: 7.632999999999999 - type: recall_at_10 value: 22.040000000000003 - type: recall_at_100 value: 44.024 - type: recall_at_1000 value: 67.848 - type: recall_at_3 value: 13.093 - type: recall_at_5 value: 15.973 - task: type: Retrieval dataset: name: MTEB FiQA-PL type: clarin-knext/fiqa-pl config: default split: test revision: 2e535829717f8bf9dc829b7f911cc5bbd4e6608e metrics: - type: map_at_1 value: 15.473 - type: map_at_10 value: 24.579 - type: map_at_100 value: 26.387 - type: map_at_1000 value: 26.57 - type: map_at_3 value: 21.278 - type: map_at_5 value: 23.179 - type: mrr_at_1 value: 30.709999999999997 - type: mrr_at_10 value: 38.994 - type: mrr_at_100 value: 39.993 - type: mrr_at_1000 value: 40.044999999999995 - type: mrr_at_3 value: 36.342999999999996 - type: mrr_at_5 value: 37.846999999999994 - type: ndcg_at_1 value: 30.709999999999997 - type: ndcg_at_10 value: 31.608999999999998 - type: ndcg_at_100 value: 38.807 - type: ndcg_at_1000 value: 42.208 - type: ndcg_at_3 value: 28.086 - type: ndcg_at_5 value: 29.323 - type: precision_at_1 value: 30.709999999999997 - type: precision_at_10 value: 8.688 - type: precision_at_100 value: 1.608 - type: precision_at_1000 value: 0.22100000000000003 - type: precision_at_3 value: 18.724 - type: precision_at_5 value: 13.950999999999999 - type: recall_at_1 value: 15.473 - type: recall_at_10 value: 38.361000000000004 - type: recall_at_100 value: 65.2 - type: recall_at_1000 value: 85.789 - type: recall_at_3 value: 25.401 - type: recall_at_5 value: 30.875999999999998 - task: type: Retrieval dataset: name: MTEB HotpotQA-PL type: clarin-knext/hotpotqa-pl config: default split: test revision: a0bd479ac97b4ccb5bd6ce320c415d0bb4beb907 metrics: - type: map_at_1 value: 38.096000000000004 - type: map_at_10 value: 51.44499999999999 - type: map_at_100 value: 52.325 - type: map_at_1000 value: 52.397000000000006 - type: map_at_3 value: 48.626999999999995 - type: map_at_5 value: 50.342 - type: mrr_at_1 value: 76.19200000000001 - type: mrr_at_10 value: 81.191 - type: mrr_at_100 value: 81.431 - type: mrr_at_1000 value: 81.443 - type: mrr_at_3 value: 80.30199999999999 - type: mrr_at_5 value: 80.85900000000001 - type: ndcg_at_1 value: 76.19200000000001 - type: ndcg_at_10 value: 60.9 - type: ndcg_at_100 value: 64.14699999999999 - type: ndcg_at_1000 value: 65.647 - type: ndcg_at_3 value: 56.818000000000005 - type: ndcg_at_5 value: 59.019999999999996 - type: precision_at_1 value: 76.19200000000001 - type: precision_at_10 value: 12.203 - type: precision_at_100 value: 1.478 - type: precision_at_1000 value: 0.168 - type: precision_at_3 value: 34.616 - type: precision_at_5 value: 22.515 - type: recall_at_1 value: 38.096000000000004 - type: recall_at_10 value: 61.013 - type: recall_at_100 value: 73.90299999999999 - type: recall_at_1000 value: 83.91 - type: recall_at_3 value: 51.92400000000001 - type: recall_at_5 value: 56.286 - task: type: Retrieval dataset: name: MTEB MSMARCO-PL type: clarin-knext/msmarco-pl config: default split: test revision: 8634c07806d5cce3a6138e260e59b81760a0a640 metrics: - type: map_at_1 value: 1.548 - type: map_at_10 value: 11.049000000000001 - type: map_at_100 value: 28.874 - type: map_at_1000 value: 34.931 - type: map_at_3 value: 4.162 - type: map_at_5 value: 6.396 - type: mrr_at_1 value: 90.69800000000001 - type: mrr_at_10 value: 92.093 - type: mrr_at_100 value: 92.345 - type: mrr_at_1000 value: 92.345 - type: mrr_at_3 value: 91.86 - type: mrr_at_5 value: 91.86 - type: ndcg_at_1 value: 74.031 - type: ndcg_at_10 value: 63.978 - type: ndcg_at_100 value: 53.101 - type: ndcg_at_1000 value: 60.675999999999995 - type: ndcg_at_3 value: 71.421 - type: ndcg_at_5 value: 68.098 - type: precision_at_1 value: 90.69800000000001 - type: precision_at_10 value: 71.86 - type: precision_at_100 value: 31.395 - type: precision_at_1000 value: 5.981 - type: precision_at_3 value: 84.49600000000001 - type: precision_at_5 value: 79.07 - type: recall_at_1 value: 1.548 - type: recall_at_10 value: 12.149000000000001 - type: recall_at_100 value: 40.794999999999995 - type: recall_at_1000 value: 67.974 - type: recall_at_3 value: 4.244 - type: recall_at_5 value: 6.608 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (pl) type: mteb/amazon_massive_intent config: pl split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 73.55413584398119 - type: f1 value: 69.65610882318181 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (pl) type: mteb/amazon_massive_scenario config: pl split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 76.37188971082716 - type: f1 value: 75.64847309941361 - task: type: Retrieval dataset: name: MTEB NFCorpus-PL type: clarin-knext/nfcorpus-pl config: default split: test revision: 9a6f9567fda928260afed2de480d79c98bf0bec0 metrics: - type: map_at_1 value: 4.919 - type: map_at_10 value: 10.834000000000001 - type: map_at_100 value: 13.38 - type: map_at_1000 value: 14.581 - type: map_at_3 value: 8.198 - type: map_at_5 value: 9.428 - type: mrr_at_1 value: 41.176 - type: mrr_at_10 value: 50.083 - type: mrr_at_100 value: 50.559 - type: mrr_at_1000 value: 50.604000000000006 - type: mrr_at_3 value: 47.936 - type: mrr_at_5 value: 49.407000000000004 - type: ndcg_at_1 value: 39.628 - type: ndcg_at_10 value: 30.098000000000003 - type: ndcg_at_100 value: 27.061 - type: ndcg_at_1000 value: 35.94 - type: ndcg_at_3 value: 35.135 - type: ndcg_at_5 value: 33.335 - type: precision_at_1 value: 41.176 - type: precision_at_10 value: 22.259999999999998 - type: precision_at_100 value: 6.712 - type: precision_at_1000 value: 1.9060000000000001 - type: precision_at_3 value: 33.23 - type: precision_at_5 value: 29.04 - type: recall_at_1 value: 4.919 - type: recall_at_10 value: 14.196 - type: recall_at_100 value: 26.948 - type: recall_at_1000 value: 59.211000000000006 - type: recall_at_3 value: 9.44 - type: recall_at_5 value: 11.569 - task: type: Retrieval dataset: name: MTEB NQ-PL type: clarin-knext/nq-pl config: default split: test revision: f171245712cf85dd4700b06bef18001578d0ca8d metrics: - type: map_at_1 value: 25.35 - type: map_at_10 value: 37.884 - type: map_at_100 value: 38.955 - type: map_at_1000 value: 39.007999999999996 - type: map_at_3 value: 34.239999999999995 - type: map_at_5 value: 36.398 - type: mrr_at_1 value: 28.737000000000002 - type: mrr_at_10 value: 39.973 - type: mrr_at_100 value: 40.844 - type: mrr_at_1000 value: 40.885 - type: mrr_at_3 value: 36.901 - type: mrr_at_5 value: 38.721 - type: ndcg_at_1 value: 28.708 - type: ndcg_at_10 value: 44.204 - type: ndcg_at_100 value: 48.978 - type: ndcg_at_1000 value: 50.33 - type: ndcg_at_3 value: 37.36 - type: ndcg_at_5 value: 40.912 - type: precision_at_1 value: 28.708 - type: precision_at_10 value: 7.367 - type: precision_at_100 value: 1.0030000000000001 - type: precision_at_1000 value: 0.11299999999999999 - type: precision_at_3 value: 17.034 - type: precision_at_5 value: 12.293999999999999 - type: recall_at_1 value: 25.35 - type: recall_at_10 value: 61.411 - type: recall_at_100 value: 82.599 - type: recall_at_1000 value: 92.903 - type: recall_at_3 value: 43.728 - type: recall_at_5 value: 51.854 - task: type: Classification dataset: name: MTEB PAC type: laugustyniak/abusive-clauses-pl config: default split: test revision: None metrics: - type: accuracy value: 69.04141326382856 - type: ap value: 77.49422763833996 - type: f1 value: 66.73472657783407 - task: type: PairClassification dataset: name: MTEB PPC type: PL-MTEB/ppc-pairclassification config: default split: test revision: None metrics: - type: cos_sim_accuracy value: 81.0 - type: cos_sim_ap value: 91.47194213011349 - type: cos_sim_f1 value: 84.73767885532592 - type: cos_sim_precision value: 81.49847094801224 - type: cos_sim_recall value: 88.24503311258279 - type: dot_accuracy value: 81.0 - type: dot_ap value: 91.47194213011349 - type: dot_f1 value: 84.73767885532592 - type: dot_precision value: 81.49847094801224 - type: dot_recall value: 88.24503311258279 - type: euclidean_accuracy value: 81.0 - type: euclidean_ap value: 91.47194213011349 - type: euclidean_f1 value: 84.73767885532592 - type: euclidean_precision value: 81.49847094801224 - type: euclidean_recall value: 88.24503311258279 - type: manhattan_accuracy value: 81.0 - type: manhattan_ap value: 91.46464475050571 - type: manhattan_f1 value: 84.48687350835321 - type: manhattan_precision value: 81.31699846860643 - type: manhattan_recall value: 87.91390728476821 - type: max_accuracy value: 81.0 - type: max_ap value: 91.47194213011349 - type: max_f1 value: 84.73767885532592 - task: type: PairClassification dataset: name: MTEB PSC type: PL-MTEB/psc-pairclassification config: default split: test revision: None metrics: - type: cos_sim_accuracy value: 97.6808905380334 - type: cos_sim_ap value: 99.27948611836348 - type: cos_sim_f1 value: 96.15975422427034 - type: cos_sim_precision value: 96.90402476780186 - type: cos_sim_recall value: 95.42682926829268 - type: dot_accuracy value: 97.6808905380334 - type: dot_ap value: 99.2794861183635 - type: dot_f1 value: 96.15975422427034 - type: dot_precision value: 96.90402476780186 - type: dot_recall value: 95.42682926829268 - type: euclidean_accuracy value: 97.6808905380334 - type: euclidean_ap value: 99.2794861183635 - type: euclidean_f1 value: 96.15975422427034 - type: euclidean_precision value: 96.90402476780186 - type: euclidean_recall value: 95.42682926829268 - type: manhattan_accuracy value: 97.6808905380334 - type: manhattan_ap value: 99.28715055268721 - type: manhattan_f1 value: 96.14791987673343 - type: manhattan_precision value: 97.19626168224299 - type: manhattan_recall value: 95.1219512195122 - type: max_accuracy value: 97.6808905380334 - type: max_ap value: 99.28715055268721 - type: max_f1 value: 96.15975422427034 - task: type: Classification dataset: name: MTEB PolEmo2.0-IN type: PL-MTEB/polemo2_in config: default split: test revision: None metrics: - type: accuracy value: 86.16343490304708 - type: f1 value: 83.3442579486744 - task: type: Classification dataset: name: MTEB PolEmo2.0-OUT type: PL-MTEB/polemo2_out config: default split: test revision: None metrics: - type: accuracy value: 68.40080971659918 - type: f1 value: 53.13720751142237 - task: type: Retrieval dataset: name: MTEB Quora-PL type: clarin-knext/quora-pl config: default split: test revision: 0be27e93455051e531182b85e85e425aba12e9d4 metrics: - type: map_at_1 value: 63.322 - type: map_at_10 value: 76.847 - type: map_at_100 value: 77.616 - type: map_at_1000 value: 77.644 - type: map_at_3 value: 73.624 - type: map_at_5 value: 75.603 - type: mrr_at_1 value: 72.88 - type: mrr_at_10 value: 80.376 - type: mrr_at_100 value: 80.604 - type: mrr_at_1000 value: 80.61 - type: mrr_at_3 value: 78.92 - type: mrr_at_5 value: 79.869 - type: ndcg_at_1 value: 72.89999999999999 - type: ndcg_at_10 value: 81.43 - type: ndcg_at_100 value: 83.394 - type: ndcg_at_1000 value: 83.685 - type: ndcg_at_3 value: 77.62599999999999 - type: ndcg_at_5 value: 79.656 - type: precision_at_1 value: 72.89999999999999 - type: precision_at_10 value: 12.548 - type: precision_at_100 value: 1.4869999999999999 - type: precision_at_1000 value: 0.155 - type: precision_at_3 value: 34.027 - type: precision_at_5 value: 22.654 - type: recall_at_1 value: 63.322 - type: recall_at_10 value: 90.664 - type: recall_at_100 value: 97.974 - type: recall_at_1000 value: 99.636 - type: recall_at_3 value: 80.067 - type: recall_at_5 value: 85.526 - task: type: Retrieval dataset: name: MTEB SCIDOCS-PL type: clarin-knext/scidocs-pl config: default split: test revision: 45452b03f05560207ef19149545f168e596c9337 metrics: - type: map_at_1 value: 3.95 - type: map_at_10 value: 9.658999999999999 - type: map_at_100 value: 11.384 - type: map_at_1000 value: 11.677 - type: map_at_3 value: 7.055 - type: map_at_5 value: 8.244 - type: mrr_at_1 value: 19.5 - type: mrr_at_10 value: 28.777 - type: mrr_at_100 value: 29.936 - type: mrr_at_1000 value: 30.009999999999998 - type: mrr_at_3 value: 25.55 - type: mrr_at_5 value: 27.284999999999997 - type: ndcg_at_1 value: 19.5 - type: ndcg_at_10 value: 16.589000000000002 - type: ndcg_at_100 value: 23.879 - type: ndcg_at_1000 value: 29.279 - type: ndcg_at_3 value: 15.719 - type: ndcg_at_5 value: 13.572000000000001 - type: precision_at_1 value: 19.5 - type: precision_at_10 value: 8.62 - type: precision_at_100 value: 1.924 - type: precision_at_1000 value: 0.322 - type: precision_at_3 value: 14.6 - type: precision_at_5 value: 11.78 - type: recall_at_1 value: 3.95 - type: recall_at_10 value: 17.477999999999998 - type: recall_at_100 value: 38.99 - type: recall_at_1000 value: 65.417 - type: recall_at_3 value: 8.883000000000001 - type: recall_at_5 value: 11.933 - task: type: PairClassification dataset: name: MTEB SICK-E-PL type: PL-MTEB/sicke-pl-pairclassification config: default split: test revision: None metrics: - type: cos_sim_accuracy value: 83.48960456583775 - type: cos_sim_ap value: 76.31522115825375 - type: cos_sim_f1 value: 70.35573122529645 - type: cos_sim_precision value: 70.9934735315446 - type: cos_sim_recall value: 69.72934472934473 - type: dot_accuracy value: 83.48960456583775 - type: dot_ap value: 76.31522115825373 - type: dot_f1 value: 70.35573122529645 - type: dot_precision value: 70.9934735315446 - type: dot_recall value: 69.72934472934473 - type: euclidean_accuracy value: 83.48960456583775 - type: euclidean_ap value: 76.31522115825373 - type: euclidean_f1 value: 70.35573122529645 - type: euclidean_precision value: 70.9934735315446 - type: euclidean_recall value: 69.72934472934473 - type: manhattan_accuracy value: 83.46922136159804 - type: manhattan_ap value: 76.18474601388084 - type: manhattan_f1 value: 70.34779490856937 - type: manhattan_precision value: 70.83032490974729 - type: manhattan_recall value: 69.87179487179486 - type: max_accuracy value: 83.48960456583775 - type: max_ap value: 76.31522115825375 - type: max_f1 value: 70.35573122529645 - task: type: STS dataset: name: MTEB SICK-R-PL type: PL-MTEB/sickr-pl-sts config: default split: test revision: None metrics: - type: cos_sim_pearson value: 77.95374883876302 - type: cos_sim_spearman value: 73.77630219171942 - type: euclidean_pearson value: 75.81927069594934 - type: euclidean_spearman value: 73.7763211303831 - type: manhattan_pearson value: 76.03126859057528 - type: manhattan_spearman value: 73.96528138013369 - task: type: STS dataset: name: MTEB STS22 (pl) type: mteb/sts22-crosslingual-sts config: pl split: test revision: eea2b4fe26a775864c896887d910b76a8098ad3f metrics: - type: cos_sim_pearson value: 37.388282764841826 - type: cos_sim_spearman value: 40.83477184710897 - type: euclidean_pearson value: 26.754737044177805 - type: euclidean_spearman value: 40.83477184710897 - type: manhattan_pearson value: 26.760453110872458 - type: manhattan_spearman value: 41.034477441383856 - task: type: Retrieval dataset: name: MTEB SciFact-PL type: clarin-knext/scifact-pl config: default split: test revision: 47932a35f045ef8ed01ba82bf9ff67f6e109207e metrics: - type: map_at_1 value: 49.15 - type: map_at_10 value: 61.690999999999995 - type: map_at_100 value: 62.348000000000006 - type: map_at_1000 value: 62.38 - type: map_at_3 value: 58.824 - type: map_at_5 value: 60.662000000000006 - type: mrr_at_1 value: 51.333 - type: mrr_at_10 value: 62.731 - type: mrr_at_100 value: 63.245 - type: mrr_at_1000 value: 63.275000000000006 - type: mrr_at_3 value: 60.667 - type: mrr_at_5 value: 61.93300000000001 - type: ndcg_at_1 value: 51.333 - type: ndcg_at_10 value: 67.168 - type: ndcg_at_100 value: 69.833 - type: ndcg_at_1000 value: 70.56700000000001 - type: ndcg_at_3 value: 62.40599999999999 - type: ndcg_at_5 value: 65.029 - type: precision_at_1 value: 51.333 - type: precision_at_10 value: 9.333 - type: precision_at_100 value: 1.0699999999999998 - type: precision_at_1000 value: 0.11299999999999999 - type: precision_at_3 value: 25.333 - type: precision_at_5 value: 17.067 - type: recall_at_1 value: 49.15 - type: recall_at_10 value: 82.533 - type: recall_at_100 value: 94.167 - type: recall_at_1000 value: 99.667 - type: recall_at_3 value: 69.917 - type: recall_at_5 value: 76.356 - task: type: Retrieval dataset: name: MTEB TRECCOVID-PL type: clarin-knext/trec-covid-pl config: default split: test revision: 81bcb408f33366c2a20ac54adafad1ae7e877fdd metrics: - type: map_at_1 value: 0.261 - type: map_at_10 value: 2.1260000000000003 - type: map_at_100 value: 12.171999999999999 - type: map_at_1000 value: 26.884999999999998 - type: map_at_3 value: 0.695 - type: map_at_5 value: 1.134 - type: mrr_at_1 value: 96.0 - type: mrr_at_10 value: 96.952 - type: mrr_at_100 value: 96.952 - type: mrr_at_1000 value: 96.952 - type: mrr_at_3 value: 96.667 - type: mrr_at_5 value: 96.667 - type: ndcg_at_1 value: 92.0 - type: ndcg_at_10 value: 81.193 - type: ndcg_at_100 value: 61.129 - type: ndcg_at_1000 value: 51.157 - type: ndcg_at_3 value: 85.693 - type: ndcg_at_5 value: 84.129 - type: precision_at_1 value: 96.0 - type: precision_at_10 value: 85.39999999999999 - type: precision_at_100 value: 62.03999999999999 - type: precision_at_1000 value: 22.224 - type: precision_at_3 value: 88.0 - type: precision_at_5 value: 88.0 - type: recall_at_1 value: 0.261 - type: recall_at_10 value: 2.262 - type: recall_at_100 value: 14.981 - type: recall_at_1000 value: 46.837 - type: recall_at_3 value: 0.703 - type: recall_at_5 value: 1.172 - task: type: Clustering dataset: name: MTEB AlloProfClusteringP2P type: lyon-nlp/alloprof config: default split: test revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b metrics: - type: v_measure value: 70.55290063940157 - type: v_measure value: 55.41500719337263 - task: type: Reranking dataset: name: MTEB AlloprofReranking type: lyon-nlp/mteb-fr-reranking-alloprof-s2p config: default split: test revision: 666fdacebe0291776e86f29345663dfaf80a0db9 metrics: - type: map value: 73.48697375332002 - type: mrr value: 75.01836585523822 - task: type: Retrieval dataset: name: MTEB AlloprofRetrieval type: lyon-nlp/alloprof config: default split: test revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b metrics: - type: map_at_1 value: 38.454 - type: map_at_10 value: 51.605000000000004 - type: map_at_100 value: 52.653000000000006 - type: map_at_1000 value: 52.697 - type: map_at_3 value: 48.304 - type: map_at_5 value: 50.073 - type: mrr_at_1 value: 43.307 - type: mrr_at_10 value: 54.400000000000006 - type: mrr_at_100 value: 55.147999999999996 - type: mrr_at_1000 value: 55.174 - type: mrr_at_3 value: 51.77 - type: mrr_at_5 value: 53.166999999999994 - type: ndcg_at_1 value: 43.307 - type: ndcg_at_10 value: 57.891000000000005 - type: ndcg_at_100 value: 62.161 - type: ndcg_at_1000 value: 63.083 - type: ndcg_at_3 value: 51.851 - type: ndcg_at_5 value: 54.605000000000004 - type: precision_at_1 value: 43.307 - type: precision_at_10 value: 9.033 - type: precision_at_100 value: 1.172 - type: precision_at_1000 value: 0.127 - type: precision_at_3 value: 22.798 - type: precision_at_5 value: 15.492 - type: recall_at_1 value: 38.454 - type: recall_at_10 value: 74.166 - type: recall_at_100 value: 92.43599999999999 - type: recall_at_1000 value: 99.071 - type: recall_at_3 value: 58.087 - type: recall_at_5 value: 64.568 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (fr) type: mteb/amazon_reviews_multi config: fr split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - 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type: precision_at_1000 value: 0.059000000000000004 - type: precision_at_3 value: 1.802 - type: precision_at_5 value: 1.712 - type: recall_at_1 value: 2.252 - type: recall_at_10 value: 11.712 - type: recall_at_100 value: 33.333 - type: recall_at_1000 value: 59.458999999999996 - type: recall_at_3 value: 5.405 - type: recall_at_5 value: 8.559 - task: type: Clustering dataset: name: MTEB HALClusteringS2S type: lyon-nlp/clustering-hal-s2s config: default split: test revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915 metrics: - type: v_measure value: 28.301882091023288 - task: type: Clustering dataset: name: MTEB MLSUMClusteringP2P type: mlsum config: default split: test revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 metrics: - type: v_measure value: 45.26992995191701 - type: v_measure value: 42.773174876871145 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (fr) type: mteb/mtop_domain config: fr split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 93.47635452552458 - type: f1 value: 93.19922617577213 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (fr) type: mteb/mtop_intent config: fr split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 80.2317569683683 - type: f1 value: 56.18060418621901 - task: type: Classification dataset: name: MTEB MasakhaNEWSClassification (fra) type: masakhane/masakhanews config: fra split: test revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 metrics: - type: accuracy value: 85.18957345971565 - type: f1 value: 80.829981537394 - task: type: Clustering dataset: name: MTEB MasakhaNEWSClusteringP2P (fra) type: masakhane/masakhanews config: fra split: test revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 metrics: - type: v_measure value: 71.04138999801822 - type: v_measure value: 71.7056263158008 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (fr) type: mteb/amazon_massive_intent config: fr split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 76.65097511768661 - type: f1 value: 73.82441070598712 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (fr) type: mteb/amazon_massive_scenario config: fr split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 79.09885675857431 - type: f1 value: 78.28407777434224 - task: type: Retrieval dataset: name: MTEB MintakaRetrieval (fr) type: jinaai/mintakaqa config: fr split: test revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e metrics: - type: map_at_1 value: 25.307000000000002 - type: map_at_10 value: 36.723 - type: map_at_100 value: 37.713 - type: map_at_1000 value: 37.769000000000005 - type: map_at_3 value: 33.77 - type: map_at_5 value: 35.463 - type: mrr_at_1 value: 25.307000000000002 - type: mrr_at_10 value: 36.723 - type: mrr_at_100 value: 37.713 - type: mrr_at_1000 value: 37.769000000000005 - type: mrr_at_3 value: 33.77 - type: mrr_at_5 value: 35.463 - type: ndcg_at_1 value: 25.307000000000002 - type: ndcg_at_10 value: 42.559999999999995 - type: ndcg_at_100 value: 47.457 - type: ndcg_at_1000 value: 49.162 - type: ndcg_at_3 value: 36.461 - type: ndcg_at_5 value: 39.504 - type: precision_at_1 value: 25.307000000000002 - type: precision_at_10 value: 6.106 - type: precision_at_100 value: 0.8420000000000001 - type: precision_at_1000 value: 0.098 - type: precision_at_3 value: 14.741999999999999 - type: precision_at_5 value: 10.319 - type: recall_at_1 value: 25.307000000000002 - type: recall_at_10 value: 61.056999999999995 - type: recall_at_100 value: 84.152 - type: recall_at_1000 value: 98.03399999999999 - type: recall_at_3 value: 44.226 - type: recall_at_5 value: 51.597 - task: type: PairClassification dataset: name: MTEB OpusparcusPC (fr) type: GEM/opusparcus config: fr split: test revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a metrics: - type: cos_sim_accuracy value: 99.90069513406156 - type: cos_sim_ap value: 100.0 - type: cos_sim_f1 value: 99.95032290114257 - type: cos_sim_precision value: 100.0 - type: cos_sim_recall value: 99.90069513406156 - type: dot_accuracy value: 99.90069513406156 - type: dot_ap value: 100.0 - type: dot_f1 value: 99.95032290114257 - type: dot_precision value: 100.0 - type: dot_recall value: 99.90069513406156 - type: euclidean_accuracy value: 99.90069513406156 - type: euclidean_ap value: 100.0 - type: euclidean_f1 value: 99.95032290114257 - type: euclidean_precision value: 100.0 - type: euclidean_recall value: 99.90069513406156 - type: manhattan_accuracy value: 99.90069513406156 - type: manhattan_ap value: 100.0 - type: manhattan_f1 value: 99.95032290114257 - type: manhattan_precision value: 100.0 - type: manhattan_recall value: 99.90069513406156 - type: max_accuracy value: 99.90069513406156 - type: max_ap value: 100.0 - type: max_f1 value: 99.95032290114257 - task: type: PairClassification dataset: name: MTEB PawsX (fr) type: paws-x config: fr split: test revision: 8a04d940a42cd40658986fdd8e3da561533a3646 metrics: - type: cos_sim_accuracy value: 70.8 - type: cos_sim_ap value: 73.7671529695957 - type: cos_sim_f1 value: 68.80964339527875 - type: cos_sim_precision value: 62.95955882352941 - type: cos_sim_recall value: 75.85825027685493 - type: dot_accuracy value: 70.8 - type: dot_ap value: 73.78345265366947 - type: dot_f1 value: 68.80964339527875 - type: dot_precision value: 62.95955882352941 - type: dot_recall value: 75.85825027685493 - type: euclidean_accuracy value: 70.8 - type: euclidean_ap value: 73.7671529695957 - type: euclidean_f1 value: 68.80964339527875 - type: euclidean_precision value: 62.95955882352941 - type: euclidean_recall value: 75.85825027685493 - type: manhattan_accuracy value: 70.75 - type: manhattan_ap value: 73.78996383615953 - type: manhattan_f1 value: 68.79432624113475 - type: manhattan_precision value: 63.39869281045751 - type: manhattan_recall value: 75.1937984496124 - type: max_accuracy value: 70.8 - type: max_ap value: 73.78996383615953 - type: max_f1 value: 68.80964339527875 - task: type: STS dataset: name: MTEB SICKFr type: Lajavaness/SICK-fr config: default split: test revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a metrics: - type: cos_sim_pearson value: 84.03253762760392 - type: cos_sim_spearman value: 79.68280105762004 - type: euclidean_pearson value: 80.98265050044444 - type: euclidean_spearman value: 79.68233242682867 - type: manhattan_pearson value: 80.9678911810704 - type: manhattan_spearman value: 79.70264097683109 - task: type: STS dataset: name: MTEB STS22 (fr) type: mteb/sts22-crosslingual-sts config: fr split: test revision: eea2b4fe26a775864c896887d910b76a8098ad3f metrics: - type: cos_sim_pearson value: 80.56896987572884 - type: cos_sim_spearman value: 81.84352499523287 - type: euclidean_pearson value: 80.40831759421305 - type: euclidean_spearman value: 81.84352499523287 - type: manhattan_pearson value: 80.74333857561238 - type: manhattan_spearman value: 82.41503246733892 - task: type: STS dataset: name: MTEB STSBenchmarkMultilingualSTS (fr) type: stsb_multi_mt config: fr split: test revision: 93d57ef91790589e3ce9c365164337a8a78b7632 metrics: - type: cos_sim_pearson value: 82.71826762276979 - type: cos_sim_spearman value: 82.25433354916042 - type: euclidean_pearson value: 81.87115571724316 - type: euclidean_spearman value: 82.25322342890107 - type: manhattan_pearson value: 82.11174867527224 - type: manhattan_spearman value: 82.55905365203084 - task: type: Summarization dataset: name: MTEB SummEvalFr type: lyon-nlp/summarization-summeval-fr-p2p config: default split: test revision: b385812de6a9577b6f4d0f88c6a6e35395a94054 metrics: - type: cos_sim_pearson value: 30.659441623392887 - type: cos_sim_spearman value: 30.501134097353315 - type: dot_pearson value: 30.659444768851056 - type: dot_spearman value: 30.501134097353315 - task: type: Reranking dataset: name: MTEB SyntecReranking type: lyon-nlp/mteb-fr-reranking-syntec-s2p config: default split: test revision: b205c5084a0934ce8af14338bf03feb19499c84d metrics: - type: map value: 94.03333333333333 - type: mrr value: 94.03333333333333 - task: type: Retrieval dataset: name: MTEB SyntecRetrieval type: lyon-nlp/mteb-fr-retrieval-syntec-s2p config: default split: test revision: 77f7e271bf4a92b24fce5119f3486b583ca016ff metrics: - type: map_at_1 value: 79.0 - type: map_at_10 value: 87.61 - type: map_at_100 value: 87.655 - type: map_at_1000 value: 87.655 - type: map_at_3 value: 87.167 - type: map_at_5 value: 87.36699999999999 - type: mrr_at_1 value: 79.0 - type: mrr_at_10 value: 87.61 - type: mrr_at_100 value: 87.655 - type: mrr_at_1000 value: 87.655 - type: mrr_at_3 value: 87.167 - type: mrr_at_5 value: 87.36699999999999 - type: ndcg_at_1 value: 79.0 - type: ndcg_at_10 value: 90.473 - type: ndcg_at_100 value: 90.694 - type: ndcg_at_1000 value: 90.694 - type: ndcg_at_3 value: 89.464 - type: ndcg_at_5 value: 89.851 - type: precision_at_1 value: 79.0 - type: precision_at_10 value: 9.9 - type: precision_at_100 value: 1.0 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 32.0 - type: precision_at_5 value: 19.400000000000002 - type: recall_at_1 value: 79.0 - type: recall_at_10 value: 99.0 - type: recall_at_100 value: 100.0 - type: recall_at_1000 value: 100.0 - type: recall_at_3 value: 96.0 - type: recall_at_5 value: 97.0 - task: type: Retrieval dataset: name: MTEB XPQARetrieval (fr) type: jinaai/xpqa config: fr split: test revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f metrics: - type: map_at_1 value: 39.395 - type: map_at_10 value: 59.123999999999995 - type: map_at_100 value: 60.704 - type: map_at_1000 value: 60.760000000000005 - type: map_at_3 value: 53.187 - type: map_at_5 value: 56.863 - type: mrr_at_1 value: 62.083 - type: mrr_at_10 value: 68.87299999999999 - type: mrr_at_100 value: 69.46900000000001 - type: mrr_at_1000 value: 69.48299999999999 - type: mrr_at_3 value: 66.8 - type: mrr_at_5 value: 67.928 - type: ndcg_at_1 value: 62.083 - type: ndcg_at_10 value: 65.583 - type: ndcg_at_100 value: 70.918 - type: ndcg_at_1000 value: 71.72800000000001 - type: ndcg_at_3 value: 60.428000000000004 - type: ndcg_at_5 value: 61.853 - type: precision_at_1 value: 62.083 - type: precision_at_10 value: 15.033 - type: precision_at_100 value: 1.9529999999999998 - type: precision_at_1000 value: 0.207 - type: precision_at_3 value: 36.315 - type: precision_at_5 value: 25.955000000000002 - type: recall_at_1 value: 39.395 - type: recall_at_10 value: 74.332 - type: recall_at_100 value: 94.729 - type: recall_at_1000 value: 99.75500000000001 - type: recall_at_3 value: 57.679 - type: recall_at_5 value: 65.036 --- # agier9/gte-Qwen2-1.5B-instruct-Q4_K_M-GGUF This model was converted to GGUF format from [`Alibaba-NLP/gte-Qwen2-1.5B-instruct`](https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo agier9/gte-Qwen2-1.5B-instruct-Q4_K_M-GGUF --hf-file gte-qwen2-1.5b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo agier9/gte-Qwen2-1.5B-instruct-Q4_K_M-GGUF --hf-file gte-qwen2-1.5b-instruct-q4_k_m.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo agier9/gte-Qwen2-1.5B-instruct-Q4_K_M-GGUF --hf-file gte-qwen2-1.5b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo agier9/gte-Qwen2-1.5B-instruct-Q4_K_M-GGUF --hf-file gte-qwen2-1.5b-instruct-q4_k_m.gguf -c 2048 ```