| --- |
| tags: |
| - mteb |
| - sentence-transformers |
| - transformers |
| - Qwen2 |
| - sentence-similarity |
| tasks: |
| - text-embedding |
| license: apache-2.0 |
| name: RedHatAI/gte-Qwen2-7B-instruct |
| description: Text embedding model, recommended for use with Docling. |
| readme: https://huggingface.co/RedHatAI/gte-Qwen2-7B-instruct/blob/main/README.md |
| provider: Alibaba Cloud |
| model-index: |
| - name: gte-qwen2-7B-instruct |
| results: |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_counterfactual |
| name: MTEB AmazonCounterfactualClassification (en) |
| config: en |
| split: test |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
| metrics: |
| - type: accuracy |
| value: 91.31343283582089 |
| - type: ap |
| value: 67.64251402604096 |
| - type: f1 |
| value: 87.53372530755692 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_polarity |
| name: MTEB AmazonPolarityClassification |
| config: default |
| split: test |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
| metrics: |
| - type: accuracy |
| value: 97.497825 |
| - type: ap |
| value: 96.30329547047529 |
| - type: f1 |
| value: 97.49769793778039 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (en) |
| config: en |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 62.564 |
| - type: f1 |
| value: 60.975777935041066 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/arguana |
| name: MTEB ArguAna |
| config: default |
| split: test |
| revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
| metrics: |
| - type: map_at_1 |
| value: 36.486000000000004 |
| - type: map_at_10 |
| value: 54.842 |
| - type: map_at_100 |
| value: 55.206999999999994 |
| - type: map_at_1000 |
| value: 55.206999999999994 |
| - type: map_at_3 |
| value: 49.893 |
| - type: map_at_5 |
| value: 53.105000000000004 |
| - type: mrr_at_1 |
| value: 37.34 |
| - type: mrr_at_10 |
| value: 55.143 |
| - type: mrr_at_100 |
| value: 55.509 |
| - type: mrr_at_1000 |
| value: 55.509 |
| - type: mrr_at_3 |
| value: 50.212999999999994 |
| - type: mrr_at_5 |
| value: 53.432 |
| - type: ndcg_at_1 |
| value: 36.486000000000004 |
| - type: ndcg_at_10 |
| value: 64.273 |
| - type: ndcg_at_100 |
| value: 65.66199999999999 |
| - type: ndcg_at_1000 |
| value: 65.66199999999999 |
| - type: ndcg_at_3 |
| value: 54.352999999999994 |
| - type: ndcg_at_5 |
| value: 60.131 |
| - type: precision_at_1 |
| value: 36.486000000000004 |
| - type: precision_at_10 |
| value: 9.395000000000001 |
| - type: precision_at_100 |
| value: 0.996 |
| - type: precision_at_1000 |
| value: 0.1 |
| - type: precision_at_3 |
| value: 22.428 |
| - type: precision_at_5 |
| value: 16.259 |
| - type: recall_at_1 |
| value: 36.486000000000004 |
| - type: recall_at_10 |
| value: 93.95400000000001 |
| - type: recall_at_100 |
| value: 99.644 |
| - type: recall_at_1000 |
| value: 99.644 |
| - type: recall_at_3 |
| value: 67.283 |
| - type: recall_at_5 |
| value: 81.294 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-p2p |
| name: MTEB ArxivClusteringP2P |
| config: default |
| split: test |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| metrics: |
| - type: v_measure |
| value: 56.461169803700564 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-s2s |
| name: MTEB ArxivClusteringS2S |
| config: default |
| split: test |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
| metrics: |
| - type: v_measure |
| value: 51.73600434466286 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/askubuntudupquestions-reranking |
| name: MTEB AskUbuntuDupQuestions |
| config: default |
| split: test |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
| metrics: |
| - type: map |
| value: 67.57827065898053 |
| - type: mrr |
| value: 79.08136569493911 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/biosses-sts |
| name: MTEB BIOSSES |
| config: default |
| split: test |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
| metrics: |
| - type: cos_sim_pearson |
| value: 83.53324575999243 |
| - type: cos_sim_spearman |
| value: 81.37173362822374 |
| - type: euclidean_pearson |
| value: 82.19243335103444 |
| - type: euclidean_spearman |
| value: 81.33679307304334 |
| - type: manhattan_pearson |
| value: 82.38752665975699 |
| - type: manhattan_spearman |
| value: 81.31510583189689 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/banking77 |
| name: MTEB Banking77Classification |
| config: default |
| split: test |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| metrics: |
| - type: accuracy |
| value: 87.56818181818181 |
| - type: f1 |
| value: 87.25826722019875 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-p2p |
| name: MTEB BiorxivClusteringP2P |
| config: default |
| split: test |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| metrics: |
| - type: v_measure |
| value: 50.09239610327673 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-s2s |
| name: MTEB BiorxivClusteringS2S |
| config: default |
| split: test |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
| metrics: |
| - type: v_measure |
| value: 46.64733054606282 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackAndroidRetrieval |
| config: default |
| split: test |
| revision: f46a197baaae43b4f621051089b82a364682dfeb |
| metrics: |
| - type: map_at_1 |
| value: 33.997 |
| - type: map_at_10 |
| value: 48.176 |
| - type: map_at_100 |
| value: 49.82 |
| - type: map_at_1000 |
| value: 49.924 |
| - type: map_at_3 |
| value: 43.626 |
| - type: map_at_5 |
| value: 46.275 |
| - type: mrr_at_1 |
| value: 42.059999999999995 |
| - type: mrr_at_10 |
| value: 53.726 |
| - type: mrr_at_100 |
| value: 54.398 |
| - type: mrr_at_1000 |
| value: 54.416 |
| - type: mrr_at_3 |
| value: 50.714999999999996 |
| - type: mrr_at_5 |
| value: 52.639 |
| - type: ndcg_at_1 |
| value: 42.059999999999995 |
| - type: ndcg_at_10 |
| value: 55.574999999999996 |
| - type: ndcg_at_100 |
| value: 60.744 |
| - type: ndcg_at_1000 |
| value: 61.85699999999999 |
| - type: ndcg_at_3 |
| value: 49.363 |
| - type: ndcg_at_5 |
| value: 52.44 |
| - type: precision_at_1 |
| value: 42.059999999999995 |
| - type: precision_at_10 |
| value: 11.101999999999999 |
| - type: precision_at_100 |
| value: 1.73 |
| - type: precision_at_1000 |
| value: 0.218 |
| - type: precision_at_3 |
| value: 24.464 |
| - type: precision_at_5 |
| value: 18.026 |
| - type: recall_at_1 |
| value: 33.997 |
| - type: recall_at_10 |
| value: 70.35900000000001 |
| - type: recall_at_100 |
| value: 91.642 |
| - type: recall_at_1000 |
| value: 97.977 |
| - type: recall_at_3 |
| value: 52.76 |
| - type: recall_at_5 |
| value: 61.148 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackEnglishRetrieval |
| config: default |
| split: test |
| revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
| metrics: |
| - type: map_at_1 |
| value: 35.884 |
| - type: map_at_10 |
| value: 48.14 |
| - type: map_at_100 |
| value: 49.5 |
| - type: map_at_1000 |
| value: 49.63 |
| - type: map_at_3 |
| value: 44.646 |
| - type: map_at_5 |
| value: 46.617999999999995 |
| - type: mrr_at_1 |
| value: 44.458999999999996 |
| - type: mrr_at_10 |
| value: 53.751000000000005 |
| - type: mrr_at_100 |
| value: 54.37800000000001 |
| - type: mrr_at_1000 |
| value: 54.415 |
| - type: mrr_at_3 |
| value: 51.815 |
| - type: mrr_at_5 |
| value: 52.882 |
| - type: ndcg_at_1 |
| value: 44.458999999999996 |
| - type: ndcg_at_10 |
| value: 54.157 |
| - type: ndcg_at_100 |
| value: 58.362 |
| - type: ndcg_at_1000 |
| value: 60.178 |
| - type: ndcg_at_3 |
| value: 49.661 |
| - type: ndcg_at_5 |
| value: 51.74999999999999 |
| - type: precision_at_1 |
| value: 44.458999999999996 |
| - type: precision_at_10 |
| value: 10.248 |
| - type: precision_at_100 |
| value: 1.5890000000000002 |
| - type: precision_at_1000 |
| value: 0.207 |
| - type: precision_at_3 |
| value: 23.928 |
| - type: precision_at_5 |
| value: 16.878999999999998 |
| - type: recall_at_1 |
| value: 35.884 |
| - type: recall_at_10 |
| value: 64.798 |
| - type: recall_at_100 |
| value: 82.345 |
| - type: recall_at_1000 |
| value: 93.267 |
| - type: recall_at_3 |
| value: 51.847 |
| - type: recall_at_5 |
| value: 57.601 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackGamingRetrieval |
| config: default |
| split: test |
| revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
| metrics: |
| - type: map_at_1 |
| value: 39.383 |
| - type: map_at_10 |
| value: 53.714 |
| - type: map_at_100 |
| value: 54.838 |
| - type: map_at_1000 |
| value: 54.87800000000001 |
| - type: map_at_3 |
| value: 50.114999999999995 |
| - type: map_at_5 |
| value: 52.153000000000006 |
| - type: mrr_at_1 |
| value: 45.016 |
| - type: mrr_at_10 |
| value: 56.732000000000006 |
| - type: mrr_at_100 |
| value: 57.411 |
| - type: mrr_at_1000 |
| value: 57.431 |
| - type: mrr_at_3 |
| value: 54.044000000000004 |
| - type: mrr_at_5 |
| value: 55.639 |
| - type: ndcg_at_1 |
| value: 45.016 |
| - type: ndcg_at_10 |
| value: 60.228 |
| - type: ndcg_at_100 |
| value: 64.277 |
| - type: ndcg_at_1000 |
| value: 65.07 |
| - type: ndcg_at_3 |
| value: 54.124 |
| - type: ndcg_at_5 |
| value: 57.147000000000006 |
| - type: precision_at_1 |
| value: 45.016 |
| - type: precision_at_10 |
| value: 9.937 |
| - type: precision_at_100 |
| value: 1.288 |
| - type: precision_at_1000 |
| value: 0.13899999999999998 |
| - type: precision_at_3 |
| value: 24.471999999999998 |
| - type: precision_at_5 |
| value: 16.991 |
| - type: recall_at_1 |
| value: 39.383 |
| - type: recall_at_10 |
| value: 76.175 |
| - type: recall_at_100 |
| value: 93.02 |
| - type: recall_at_1000 |
| value: 98.60900000000001 |
| - type: recall_at_3 |
| value: 60.265 |
| - type: recall_at_5 |
| value: 67.46600000000001 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackGisRetrieval |
| config: default |
| split: test |
| revision: 5003b3064772da1887988e05400cf3806fe491f2 |
| metrics: |
| - type: map_at_1 |
| value: 27.426000000000002 |
| - type: map_at_10 |
| value: 37.397000000000006 |
| - type: map_at_100 |
| value: 38.61 |
| - type: map_at_1000 |
| value: 38.678000000000004 |
| - type: map_at_3 |
| value: 34.150999999999996 |
| - type: map_at_5 |
| value: 36.137 |
| - type: mrr_at_1 |
| value: 29.944 |
| - type: mrr_at_10 |
| value: 39.654 |
| - type: mrr_at_100 |
| value: 40.638000000000005 |
| - type: mrr_at_1000 |
| value: 40.691 |
| - type: mrr_at_3 |
| value: 36.817 |
| - type: mrr_at_5 |
| value: 38.524 |
| - type: ndcg_at_1 |
| value: 29.944 |
| - type: ndcg_at_10 |
| value: 43.094 |
| - type: ndcg_at_100 |
| value: 48.789 |
| - type: ndcg_at_1000 |
| value: 50.339999999999996 |
| - type: ndcg_at_3 |
| value: 36.984 |
| - type: ndcg_at_5 |
| value: 40.248 |
| - type: precision_at_1 |
| value: 29.944 |
| - type: precision_at_10 |
| value: 6.78 |
| - type: precision_at_100 |
| value: 1.024 |
| - type: precision_at_1000 |
| value: 0.11800000000000001 |
| - type: precision_at_3 |
| value: 15.895000000000001 |
| - type: precision_at_5 |
| value: 11.39 |
| - type: recall_at_1 |
| value: 27.426000000000002 |
| - type: recall_at_10 |
| value: 58.464000000000006 |
| - type: recall_at_100 |
| value: 84.193 |
| - type: recall_at_1000 |
| value: 95.52000000000001 |
| - type: recall_at_3 |
| value: 42.172 |
| - type: recall_at_5 |
| value: 50.101 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackMathematicaRetrieval |
| config: default |
| split: test |
| revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
| metrics: |
| - type: map_at_1 |
| value: 19.721 |
| - type: map_at_10 |
| value: 31.604 |
| - type: map_at_100 |
| value: 32.972 |
| - type: map_at_1000 |
| value: 33.077 |
| - type: map_at_3 |
| value: 27.218999999999998 |
| - type: map_at_5 |
| value: 29.53 |
| - type: mrr_at_1 |
| value: 25.0 |
| - type: mrr_at_10 |
| value: 35.843 |
| - type: mrr_at_100 |
| value: 36.785000000000004 |
| - type: mrr_at_1000 |
| value: 36.842000000000006 |
| - type: mrr_at_3 |
| value: 32.193 |
| - type: mrr_at_5 |
| value: 34.264 |
| - type: ndcg_at_1 |
| value: 25.0 |
| - type: ndcg_at_10 |
| value: 38.606 |
| - type: ndcg_at_100 |
| value: 44.272 |
| - type: ndcg_at_1000 |
| value: 46.527 |
| - type: ndcg_at_3 |
| value: 30.985000000000003 |
| - type: ndcg_at_5 |
| value: 34.43 |
| - type: precision_at_1 |
| value: 25.0 |
| - type: precision_at_10 |
| value: 7.811 |
| - type: precision_at_100 |
| value: 1.203 |
| - type: precision_at_1000 |
| value: 0.15 |
| - type: precision_at_3 |
| value: 15.423 |
| - type: precision_at_5 |
| value: 11.791 |
| - type: recall_at_1 |
| value: 19.721 |
| - type: recall_at_10 |
| value: 55.625 |
| - type: recall_at_100 |
| value: 79.34400000000001 |
| - type: recall_at_1000 |
| value: 95.208 |
| - type: recall_at_3 |
| value: 35.19 |
| - type: recall_at_5 |
| value: 43.626 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackPhysicsRetrieval |
| config: default |
| split: test |
| revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
| metrics: |
| - type: map_at_1 |
| value: 33.784 |
| - type: map_at_10 |
| value: 47.522 |
| - type: map_at_100 |
| value: 48.949999999999996 |
| - type: map_at_1000 |
| value: 49.038 |
| - type: map_at_3 |
| value: 43.284 |
| - type: map_at_5 |
| value: 45.629 |
| - type: mrr_at_1 |
| value: 41.482 |
| - type: mrr_at_10 |
| value: 52.830999999999996 |
| - type: mrr_at_100 |
| value: 53.559999999999995 |
| - type: mrr_at_1000 |
| value: 53.588 |
| - type: mrr_at_3 |
| value: 50.016000000000005 |
| - type: mrr_at_5 |
| value: 51.614000000000004 |
| - type: ndcg_at_1 |
| value: 41.482 |
| - type: ndcg_at_10 |
| value: 54.569 |
| - type: ndcg_at_100 |
| value: 59.675999999999995 |
| - type: ndcg_at_1000 |
| value: 60.989000000000004 |
| - type: ndcg_at_3 |
| value: 48.187000000000005 |
| - type: ndcg_at_5 |
| value: 51.183 |
| - type: precision_at_1 |
| value: 41.482 |
| - type: precision_at_10 |
| value: 10.221 |
| - type: precision_at_100 |
| value: 1.486 |
| - type: precision_at_1000 |
| value: 0.17500000000000002 |
| - type: precision_at_3 |
| value: 23.548 |
| - type: precision_at_5 |
| value: 16.805 |
| - type: recall_at_1 |
| value: 33.784 |
| - type: recall_at_10 |
| value: 69.798 |
| - type: recall_at_100 |
| value: 90.098 |
| - type: recall_at_1000 |
| value: 98.176 |
| - type: recall_at_3 |
| value: 52.127 |
| - type: recall_at_5 |
| value: 59.861 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackProgrammersRetrieval |
| config: default |
| split: test |
| revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
| metrics: |
| - type: map_at_1 |
| value: 28.038999999999998 |
| - type: map_at_10 |
| value: 41.904 |
| - type: map_at_100 |
| value: 43.36 |
| - type: map_at_1000 |
| value: 43.453 |
| - type: map_at_3 |
| value: 37.785999999999994 |
| - type: map_at_5 |
| value: 40.105000000000004 |
| - type: mrr_at_1 |
| value: 35.046 |
| - type: mrr_at_10 |
| value: 46.926 |
| - type: mrr_at_100 |
| value: 47.815000000000005 |
| - type: mrr_at_1000 |
| value: 47.849000000000004 |
| - type: mrr_at_3 |
| value: 44.273 |
| - type: mrr_at_5 |
| value: 45.774 |
| - type: ndcg_at_1 |
| value: 35.046 |
| - type: ndcg_at_10 |
| value: 48.937000000000005 |
| - type: ndcg_at_100 |
| value: 54.544000000000004 |
| - type: ndcg_at_1000 |
| value: 56.069 |
| - type: ndcg_at_3 |
| value: 42.858000000000004 |
| - type: ndcg_at_5 |
| value: 45.644 |
| - type: precision_at_1 |
| value: 35.046 |
| - type: precision_at_10 |
| value: 9.452 |
| - type: precision_at_100 |
| value: 1.429 |
| - type: precision_at_1000 |
| value: 0.173 |
| - type: precision_at_3 |
| value: 21.346999999999998 |
| - type: precision_at_5 |
| value: 15.342 |
| - type: recall_at_1 |
| value: 28.038999999999998 |
| - type: recall_at_10 |
| value: 64.59700000000001 |
| - type: recall_at_100 |
| value: 87.735 |
| - type: recall_at_1000 |
| value: 97.41300000000001 |
| - type: recall_at_3 |
| value: 47.368 |
| - type: recall_at_5 |
| value: 54.93900000000001 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackRetrieval |
| config: default |
| split: test |
| revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
| metrics: |
| - type: map_at_1 |
| value: 28.17291666666667 |
| - type: map_at_10 |
| value: 40.025749999999995 |
| - type: map_at_100 |
| value: 41.39208333333333 |
| - type: map_at_1000 |
| value: 41.499249999999996 |
| - type: map_at_3 |
| value: 36.347 |
| - type: map_at_5 |
| value: 38.41391666666667 |
| - type: mrr_at_1 |
| value: 33.65925 |
| - type: mrr_at_10 |
| value: 44.085499999999996 |
| - type: mrr_at_100 |
| value: 44.94116666666667 |
| - type: mrr_at_1000 |
| value: 44.9855 |
| - type: mrr_at_3 |
| value: 41.2815 |
| - type: mrr_at_5 |
| value: 42.91491666666666 |
| - type: ndcg_at_1 |
| value: 33.65925 |
| - type: ndcg_at_10 |
| value: 46.430833333333325 |
| - type: ndcg_at_100 |
| value: 51.761 |
| - type: ndcg_at_1000 |
| value: 53.50899999999999 |
| - type: ndcg_at_3 |
| value: 40.45133333333333 |
| - type: ndcg_at_5 |
| value: 43.31483333333334 |
| - type: precision_at_1 |
| value: 33.65925 |
| - type: precision_at_10 |
| value: 8.4995 |
| - type: precision_at_100 |
| value: 1.3210000000000004 |
| - type: precision_at_1000 |
| value: 0.16591666666666666 |
| - type: precision_at_3 |
| value: 19.165083333333335 |
| - type: precision_at_5 |
| value: 13.81816666666667 |
| - type: recall_at_1 |
| value: 28.17291666666667 |
| - type: recall_at_10 |
| value: 61.12624999999999 |
| - type: recall_at_100 |
| value: 83.97266666666667 |
| - type: recall_at_1000 |
| value: 95.66550000000001 |
| - type: recall_at_3 |
| value: 44.661249999999995 |
| - type: recall_at_5 |
| value: 51.983333333333334 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackStatsRetrieval |
| config: default |
| split: test |
| revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
| metrics: |
| - type: map_at_1 |
| value: 24.681 |
| - type: map_at_10 |
| value: 34.892 |
| - type: map_at_100 |
| value: 35.996 |
| - type: map_at_1000 |
| value: 36.083 |
| - type: map_at_3 |
| value: 31.491999999999997 |
| - type: map_at_5 |
| value: 33.632 |
| - type: mrr_at_1 |
| value: 28.528 |
| - type: mrr_at_10 |
| value: 37.694 |
| - type: mrr_at_100 |
| value: 38.613 |
| - type: mrr_at_1000 |
| value: 38.668 |
| - type: mrr_at_3 |
| value: 34.714 |
| - type: mrr_at_5 |
| value: 36.616 |
| - type: ndcg_at_1 |
| value: 28.528 |
| - type: ndcg_at_10 |
| value: 40.703 |
| - type: ndcg_at_100 |
| value: 45.993 |
| - type: ndcg_at_1000 |
| value: 47.847 |
| - type: ndcg_at_3 |
| value: 34.622 |
| - type: ndcg_at_5 |
| value: 38.035999999999994 |
| - type: precision_at_1 |
| value: 28.528 |
| - type: precision_at_10 |
| value: 6.902 |
| - type: precision_at_100 |
| value: 1.0370000000000001 |
| - type: precision_at_1000 |
| value: 0.126 |
| - type: precision_at_3 |
| value: 15.798000000000002 |
| - type: precision_at_5 |
| value: 11.655999999999999 |
| - type: recall_at_1 |
| value: 24.681 |
| - type: recall_at_10 |
| value: 55.81 |
| - type: recall_at_100 |
| value: 79.785 |
| - type: recall_at_1000 |
| value: 92.959 |
| - type: recall_at_3 |
| value: 39.074 |
| - type: recall_at_5 |
| value: 47.568 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackTexRetrieval |
| config: default |
| split: test |
| revision: 46989137a86843e03a6195de44b09deda022eec7 |
| metrics: |
| - type: map_at_1 |
| value: 18.627 |
| - type: map_at_10 |
| value: 27.872000000000003 |
| - type: map_at_100 |
| value: 29.237999999999996 |
| - type: map_at_1000 |
| value: 29.363 |
| - type: map_at_3 |
| value: 24.751 |
| - type: map_at_5 |
| value: 26.521 |
| - type: mrr_at_1 |
| value: 23.021 |
| - type: mrr_at_10 |
| value: 31.924000000000003 |
| - type: mrr_at_100 |
| value: 32.922000000000004 |
| - type: mrr_at_1000 |
| value: 32.988 |
| - type: mrr_at_3 |
| value: 29.192 |
| - type: mrr_at_5 |
| value: 30.798 |
| - type: ndcg_at_1 |
| value: 23.021 |
| - type: ndcg_at_10 |
| value: 33.535 |
| - type: ndcg_at_100 |
| value: 39.732 |
| - type: ndcg_at_1000 |
| value: 42.201 |
| - type: ndcg_at_3 |
| value: 28.153 |
| - type: ndcg_at_5 |
| value: 30.746000000000002 |
| - type: precision_at_1 |
| value: 23.021 |
| - type: precision_at_10 |
| value: 6.459 |
| - type: precision_at_100 |
| value: 1.1320000000000001 |
| - type: precision_at_1000 |
| value: 0.153 |
| - type: precision_at_3 |
| value: 13.719000000000001 |
| - type: precision_at_5 |
| value: 10.193000000000001 |
| - type: recall_at_1 |
| value: 18.627 |
| - type: recall_at_10 |
| value: 46.463 |
| - type: recall_at_100 |
| value: 74.226 |
| - type: recall_at_1000 |
| value: 91.28500000000001 |
| - type: recall_at_3 |
| value: 31.357000000000003 |
| - type: recall_at_5 |
| value: 38.067 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackUnixRetrieval |
| config: default |
| split: test |
| revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
| metrics: |
| - type: map_at_1 |
| value: 31.457 |
| - type: map_at_10 |
| value: 42.888 |
| - type: map_at_100 |
| value: 44.24 |
| - type: map_at_1000 |
| value: 44.327 |
| - type: map_at_3 |
| value: 39.588 |
| - type: map_at_5 |
| value: 41.423 |
| - type: mrr_at_1 |
| value: 37.126999999999995 |
| - type: mrr_at_10 |
| value: 47.083000000000006 |
| - type: mrr_at_100 |
| value: 47.997 |
| - type: mrr_at_1000 |
| value: 48.044 |
| - type: mrr_at_3 |
| value: 44.574000000000005 |
| - type: mrr_at_5 |
| value: 46.202 |
| - type: ndcg_at_1 |
| value: 37.126999999999995 |
| - type: ndcg_at_10 |
| value: 48.833 |
| - type: ndcg_at_100 |
| value: 54.327000000000005 |
| - type: ndcg_at_1000 |
| value: 56.011 |
| - type: ndcg_at_3 |
| value: 43.541999999999994 |
| - type: ndcg_at_5 |
| value: 46.127 |
| - type: precision_at_1 |
| value: 37.126999999999995 |
| - type: precision_at_10 |
| value: 8.376999999999999 |
| - type: precision_at_100 |
| value: 1.2309999999999999 |
| - type: precision_at_1000 |
| value: 0.146 |
| - type: precision_at_3 |
| value: 20.211000000000002 |
| - type: precision_at_5 |
| value: 14.16 |
| - type: recall_at_1 |
| value: 31.457 |
| - type: recall_at_10 |
| value: 62.369 |
| - type: recall_at_100 |
| value: 85.444 |
| - type: recall_at_1000 |
| value: 96.65599999999999 |
| - type: recall_at_3 |
| value: 47.961 |
| - type: recall_at_5 |
| value: 54.676 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackWebmastersRetrieval |
| config: default |
| split: test |
| revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
| metrics: |
| - type: map_at_1 |
| value: 27.139999999999997 |
| - type: map_at_10 |
| value: 38.801 |
| - type: map_at_100 |
| value: 40.549 |
| - type: map_at_1000 |
| value: 40.802 |
| - type: map_at_3 |
| value: 35.05 |
| - type: map_at_5 |
| value: 36.884 |
| - type: mrr_at_1 |
| value: 33.004 |
| - type: mrr_at_10 |
| value: 43.864 |
| - type: mrr_at_100 |
| value: 44.667 |
| - type: mrr_at_1000 |
| value: 44.717 |
| - type: mrr_at_3 |
| value: 40.777 |
| - type: mrr_at_5 |
| value: 42.319 |
| - type: ndcg_at_1 |
| value: 33.004 |
| - type: ndcg_at_10 |
| value: 46.022 |
| - type: ndcg_at_100 |
| value: 51.542 |
| - type: ndcg_at_1000 |
| value: 53.742000000000004 |
| - type: ndcg_at_3 |
| value: 39.795 |
| - type: ndcg_at_5 |
| value: 42.272 |
| - type: precision_at_1 |
| value: 33.004 |
| - type: precision_at_10 |
| value: 9.012 |
| - type: precision_at_100 |
| value: 1.7770000000000001 |
| - type: precision_at_1000 |
| value: 0.26 |
| - type: precision_at_3 |
| value: 19.038 |
| - type: precision_at_5 |
| value: 13.675999999999998 |
| - type: recall_at_1 |
| value: 27.139999999999997 |
| - type: recall_at_10 |
| value: 60.961 |
| - type: recall_at_100 |
| value: 84.451 |
| - type: recall_at_1000 |
| value: 98.113 |
| - type: recall_at_3 |
| value: 43.001 |
| - type: recall_at_5 |
| value: 49.896 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackWordpressRetrieval |
| config: default |
| split: test |
| revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
| metrics: |
| - type: map_at_1 |
| value: 17.936 |
| - type: map_at_10 |
| value: 27.399 |
| - type: map_at_100 |
| value: 28.632 |
| - type: map_at_1000 |
| value: 28.738000000000003 |
| - type: map_at_3 |
| value: 24.456 |
| - type: map_at_5 |
| value: 26.06 |
| - type: mrr_at_1 |
| value: 19.224 |
| - type: mrr_at_10 |
| value: 28.998 |
| - type: mrr_at_100 |
| value: 30.11 |
| - type: mrr_at_1000 |
| value: 30.177 |
| - type: mrr_at_3 |
| value: 26.247999999999998 |
| - type: mrr_at_5 |
| value: 27.708 |
| - type: ndcg_at_1 |
| value: 19.224 |
| - type: ndcg_at_10 |
| value: 32.911 |
| - type: ndcg_at_100 |
| value: 38.873999999999995 |
| - type: ndcg_at_1000 |
| value: 41.277 |
| - type: ndcg_at_3 |
| value: 27.142 |
| - type: ndcg_at_5 |
| value: 29.755 |
| - type: precision_at_1 |
| value: 19.224 |
| - type: precision_at_10 |
| value: 5.6930000000000005 |
| - type: precision_at_100 |
| value: 0.9259999999999999 |
| - type: precision_at_1000 |
| value: 0.126 |
| - type: precision_at_3 |
| value: 12.138 |
| - type: precision_at_5 |
| value: 8.909 |
| - type: recall_at_1 |
| value: 17.936 |
| - type: recall_at_10 |
| value: 48.096 |
| - type: recall_at_100 |
| value: 75.389 |
| - type: recall_at_1000 |
| value: 92.803 |
| - type: recall_at_3 |
| value: 32.812999999999995 |
| - type: recall_at_5 |
| value: 38.851 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/climate-fever |
| name: MTEB ClimateFEVER |
| config: default |
| split: test |
| revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
| metrics: |
| - type: map_at_1 |
| value: 22.076999999999998 |
| - type: map_at_10 |
| value: 35.44 |
| - type: map_at_100 |
| value: 37.651 |
| - type: map_at_1000 |
| value: 37.824999999999996 |
| - type: map_at_3 |
| value: 30.764999999999997 |
| - type: map_at_5 |
| value: 33.26 |
| - type: mrr_at_1 |
| value: 50.163000000000004 |
| - type: mrr_at_10 |
| value: 61.207 |
| - type: mrr_at_100 |
| value: 61.675000000000004 |
| - type: mrr_at_1000 |
| value: 61.692 |
| - type: mrr_at_3 |
| value: 58.60999999999999 |
| - type: mrr_at_5 |
| value: 60.307 |
| - type: ndcg_at_1 |
| value: 50.163000000000004 |
| - type: ndcg_at_10 |
| value: 45.882 |
| - type: ndcg_at_100 |
| value: 53.239999999999995 |
| - type: ndcg_at_1000 |
| value: 55.852000000000004 |
| - type: ndcg_at_3 |
| value: 40.514 |
| - type: ndcg_at_5 |
| value: 42.038 |
| - type: precision_at_1 |
| value: 50.163000000000004 |
| - type: precision_at_10 |
| value: 13.466000000000001 |
| - type: precision_at_100 |
| value: 2.164 |
| - type: precision_at_1000 |
| value: 0.266 |
| - type: precision_at_3 |
| value: 29.707 |
| - type: precision_at_5 |
| value: 21.694 |
| - type: recall_at_1 |
| value: 22.076999999999998 |
| - type: recall_at_10 |
| value: 50.193 |
| - type: recall_at_100 |
| value: 74.993 |
| - type: recall_at_1000 |
| value: 89.131 |
| - type: recall_at_3 |
| value: 35.472 |
| - type: recall_at_5 |
| value: 41.814 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/dbpedia |
| name: MTEB DBPedia |
| config: default |
| split: test |
| revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
| metrics: |
| - type: map_at_1 |
| value: 9.953 |
| - type: map_at_10 |
| value: 24.515 |
| - type: map_at_100 |
| value: 36.173 |
| - type: map_at_1000 |
| value: 38.351 |
| - type: map_at_3 |
| value: 16.592000000000002 |
| - type: map_at_5 |
| value: 20.036 |
| - type: mrr_at_1 |
| value: 74.25 |
| - type: mrr_at_10 |
| value: 81.813 |
| - type: mrr_at_100 |
| value: 82.006 |
| - type: mrr_at_1000 |
| value: 82.011 |
| - type: mrr_at_3 |
| value: 80.875 |
| - type: mrr_at_5 |
| value: 81.362 |
| - type: ndcg_at_1 |
| value: 62.5 |
| - type: ndcg_at_10 |
| value: 52.42 |
| - type: ndcg_at_100 |
| value: 56.808 |
| - type: ndcg_at_1000 |
| value: 63.532999999999994 |
| - type: ndcg_at_3 |
| value: 56.654 |
| - type: ndcg_at_5 |
| value: 54.18300000000001 |
| - type: precision_at_1 |
| value: 74.25 |
| - type: precision_at_10 |
| value: 42.699999999999996 |
| - type: precision_at_100 |
| value: 13.675 |
| - type: precision_at_1000 |
| value: 2.664 |
| - type: precision_at_3 |
| value: 60.5 |
| - type: precision_at_5 |
| value: 52.800000000000004 |
| - type: recall_at_1 |
| value: 9.953 |
| - type: recall_at_10 |
| value: 30.253999999999998 |
| - type: recall_at_100 |
| value: 62.516000000000005 |
| - type: recall_at_1000 |
| value: 84.163 |
| - type: recall_at_3 |
| value: 18.13 |
| - type: recall_at_5 |
| value: 22.771 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/emotion |
| name: MTEB EmotionClassification |
| config: default |
| split: test |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
| metrics: |
| - type: accuracy |
| value: 79.455 |
| - type: f1 |
| value: 74.16798697647569 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/fever |
| name: MTEB FEVER |
| config: default |
| split: test |
| revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
| metrics: |
| - type: map_at_1 |
| value: 87.531 |
| - type: map_at_10 |
| value: 93.16799999999999 |
| - type: map_at_100 |
| value: 93.341 |
| - type: map_at_1000 |
| value: 93.349 |
| - type: map_at_3 |
| value: 92.444 |
| - type: map_at_5 |
| value: 92.865 |
| - type: mrr_at_1 |
| value: 94.014 |
| - type: mrr_at_10 |
| value: 96.761 |
| - type: mrr_at_100 |
| value: 96.762 |
| - type: mrr_at_1000 |
| value: 96.762 |
| - type: mrr_at_3 |
| value: 96.672 |
| - type: mrr_at_5 |
| value: 96.736 |
| - type: ndcg_at_1 |
| value: 94.014 |
| - type: ndcg_at_10 |
| value: 95.112 |
| - type: ndcg_at_100 |
| value: 95.578 |
| - type: ndcg_at_1000 |
| value: 95.68900000000001 |
| - type: ndcg_at_3 |
| value: 94.392 |
| - type: ndcg_at_5 |
| value: 94.72500000000001 |
| - type: precision_at_1 |
| value: 94.014 |
| - type: precision_at_10 |
| value: 11.065 |
| - type: precision_at_100 |
| value: 1.157 |
| - type: precision_at_1000 |
| value: 0.11800000000000001 |
| - type: precision_at_3 |
| value: 35.259 |
| - type: precision_at_5 |
| value: 21.599 |
| - type: recall_at_1 |
| value: 87.531 |
| - type: recall_at_10 |
| value: 97.356 |
| - type: recall_at_100 |
| value: 98.965 |
| - type: recall_at_1000 |
| value: 99.607 |
| - type: recall_at_3 |
| value: 95.312 |
| - type: recall_at_5 |
| value: 96.295 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/fiqa |
| name: MTEB FiQA2018 |
| config: default |
| split: test |
| revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
| metrics: |
| - type: map_at_1 |
| value: 32.055 |
| - type: map_at_10 |
| value: 53.114 |
| - type: map_at_100 |
| value: 55.235 |
| - type: map_at_1000 |
| value: 55.345 |
| - type: map_at_3 |
| value: 45.854 |
| - type: map_at_5 |
| value: 50.025 |
| - type: mrr_at_1 |
| value: 60.34 |
| - type: mrr_at_10 |
| value: 68.804 |
| - type: mrr_at_100 |
| value: 69.309 |
| - type: mrr_at_1000 |
| value: 69.32199999999999 |
| - type: mrr_at_3 |
| value: 66.40899999999999 |
| - type: mrr_at_5 |
| value: 67.976 |
| - type: ndcg_at_1 |
| value: 60.34 |
| - type: ndcg_at_10 |
| value: 62.031000000000006 |
| - type: ndcg_at_100 |
| value: 68.00500000000001 |
| - type: ndcg_at_1000 |
| value: 69.286 |
| - type: ndcg_at_3 |
| value: 56.355999999999995 |
| - type: ndcg_at_5 |
| value: 58.687 |
| - type: precision_at_1 |
| value: 60.34 |
| - type: precision_at_10 |
| value: 17.176 |
| - type: precision_at_100 |
| value: 2.36 |
| - type: precision_at_1000 |
| value: 0.259 |
| - type: precision_at_3 |
| value: 37.14 |
| - type: precision_at_5 |
| value: 27.809 |
| - type: recall_at_1 |
| value: 32.055 |
| - type: recall_at_10 |
| value: 70.91 |
| - type: recall_at_100 |
| value: 91.83 |
| - type: recall_at_1000 |
| value: 98.871 |
| - type: recall_at_3 |
| value: 51.202999999999996 |
| - type: recall_at_5 |
| value: 60.563 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/hotpotqa |
| name: MTEB HotpotQA |
| config: default |
| split: test |
| revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
| metrics: |
| - type: map_at_1 |
| value: 43.68 |
| - type: map_at_10 |
| value: 64.389 |
| - type: map_at_100 |
| value: 65.24 |
| - type: map_at_1000 |
| value: 65.303 |
| - type: map_at_3 |
| value: 61.309000000000005 |
| - type: map_at_5 |
| value: 63.275999999999996 |
| - type: mrr_at_1 |
| value: 87.36 |
| - type: mrr_at_10 |
| value: 91.12 |
| - type: mrr_at_100 |
| value: 91.227 |
| - type: mrr_at_1000 |
| value: 91.229 |
| - type: mrr_at_3 |
| value: 90.57600000000001 |
| - type: mrr_at_5 |
| value: 90.912 |
| - type: ndcg_at_1 |
| value: 87.36 |
| - type: ndcg_at_10 |
| value: 73.076 |
| - type: ndcg_at_100 |
| value: 75.895 |
| - type: ndcg_at_1000 |
| value: 77.049 |
| - type: ndcg_at_3 |
| value: 68.929 |
| - type: ndcg_at_5 |
| value: 71.28 |
| - type: precision_at_1 |
| value: 87.36 |
| - type: precision_at_10 |
| value: 14.741000000000001 |
| - type: precision_at_100 |
| value: 1.694 |
| - type: precision_at_1000 |
| value: 0.185 |
| - type: precision_at_3 |
| value: 43.043 |
| - type: precision_at_5 |
| value: 27.681 |
| - type: recall_at_1 |
| value: 43.68 |
| - type: recall_at_10 |
| value: 73.707 |
| - type: recall_at_100 |
| value: 84.7 |
| - type: recall_at_1000 |
| value: 92.309 |
| - type: recall_at_3 |
| value: 64.564 |
| - type: recall_at_5 |
| value: 69.203 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/imdb |
| name: MTEB ImdbClassification |
| config: default |
| split: test |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
| metrics: |
| - type: accuracy |
| value: 96.75399999999999 |
| - type: ap |
| value: 95.29389839242187 |
| - type: f1 |
| value: 96.75348377433475 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/msmarco |
| name: MTEB MSMARCO |
| config: default |
| split: dev |
| revision: c5a29a104738b98a9e76336939199e264163d4a0 |
| metrics: |
| - type: map_at_1 |
| value: 25.176 |
| - type: map_at_10 |
| value: 38.598 |
| - type: map_at_100 |
| value: 39.707 |
| - type: map_at_1000 |
| value: 39.744 |
| - type: map_at_3 |
| value: 34.566 |
| - type: map_at_5 |
| value: 36.863 |
| - type: mrr_at_1 |
| value: 25.874000000000002 |
| - type: mrr_at_10 |
| value: 39.214 |
| - type: mrr_at_100 |
| value: 40.251 |
| - type: mrr_at_1000 |
| value: 40.281 |
| - type: mrr_at_3 |
| value: 35.291 |
| - type: mrr_at_5 |
| value: 37.545 |
| - type: ndcg_at_1 |
| value: 25.874000000000002 |
| - type: ndcg_at_10 |
| value: 45.98 |
| - type: ndcg_at_100 |
| value: 51.197 |
| - type: ndcg_at_1000 |
| value: 52.073 |
| - type: ndcg_at_3 |
| value: 37.785999999999994 |
| - type: ndcg_at_5 |
| value: 41.870000000000005 |
| - type: precision_at_1 |
| value: 25.874000000000002 |
| - type: precision_at_10 |
| value: 7.181 |
| - type: precision_at_100 |
| value: 0.979 |
| - type: precision_at_1000 |
| value: 0.106 |
| - type: precision_at_3 |
| value: 16.051000000000002 |
| - type: precision_at_5 |
| value: 11.713 |
| - type: recall_at_1 |
| value: 25.176 |
| - type: recall_at_10 |
| value: 68.67699999999999 |
| - type: recall_at_100 |
| value: 92.55 |
| - type: recall_at_1000 |
| value: 99.164 |
| - type: recall_at_3 |
| value: 46.372 |
| - type: recall_at_5 |
| value: 56.16 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_domain |
| name: MTEB MTOPDomainClassification (en) |
| config: en |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 99.03784769721841 |
| - type: f1 |
| value: 98.97791641821495 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_intent |
| name: MTEB MTOPIntentClassification (en) |
| config: en |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
| - type: accuracy |
| value: 91.88326493388054 |
| - type: f1 |
| value: 73.74809928034335 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (en) |
| config: en |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
| - type: accuracy |
| value: 85.41358439811701 |
| - type: f1 |
| value: 83.503679460639 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (en) |
| config: en |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 89.77135171486215 |
| - type: f1 |
| value: 88.89843747468366 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-p2p |
| name: MTEB MedrxivClusteringP2P |
| config: default |
| split: test |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
| metrics: |
| - type: v_measure |
| value: 46.22695362087359 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-s2s |
| name: MTEB MedrxivClusteringS2S |
| config: default |
| split: test |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
| metrics: |
| - type: v_measure |
| value: 44.132372165849425 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/mind_small |
| name: MTEB MindSmallReranking |
| config: default |
| split: test |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
| metrics: |
| - type: map |
| value: 33.35680810650402 |
| - type: mrr |
| value: 34.72625715637218 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/nfcorpus |
| name: MTEB NFCorpus |
| config: default |
| split: test |
| revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
| metrics: |
| - type: map_at_1 |
| value: 7.165000000000001 |
| - type: map_at_10 |
| value: 15.424 |
| - type: map_at_100 |
| value: 20.28 |
| - type: map_at_1000 |
| value: 22.065 |
| - type: map_at_3 |
| value: 11.236 |
| - type: map_at_5 |
| value: 13.025999999999998 |
| - type: mrr_at_1 |
| value: 51.702999999999996 |
| - type: mrr_at_10 |
| value: 59.965 |
| - type: mrr_at_100 |
| value: 60.667 |
| - type: mrr_at_1000 |
| value: 60.702999999999996 |
| - type: mrr_at_3 |
| value: 58.772000000000006 |
| - type: mrr_at_5 |
| value: 59.267 |
| - type: ndcg_at_1 |
| value: 49.536 |
| - type: ndcg_at_10 |
| value: 40.6 |
| - type: ndcg_at_100 |
| value: 37.848 |
| - type: ndcg_at_1000 |
| value: 46.657 |
| - type: ndcg_at_3 |
| value: 46.117999999999995 |
| - type: ndcg_at_5 |
| value: 43.619 |
| - type: precision_at_1 |
| value: 51.393 |
| - type: precision_at_10 |
| value: 30.31 |
| - type: precision_at_100 |
| value: 9.972 |
| - type: precision_at_1000 |
| value: 2.329 |
| - type: precision_at_3 |
| value: 43.137 |
| - type: precision_at_5 |
| value: 37.585 |
| - type: recall_at_1 |
| value: 7.165000000000001 |
| - type: recall_at_10 |
| value: 19.689999999999998 |
| - type: recall_at_100 |
| value: 39.237 |
| - type: recall_at_1000 |
| value: 71.417 |
| - type: recall_at_3 |
| value: 12.247 |
| - type: recall_at_5 |
| value: 14.902999999999999 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/nq |
| name: MTEB NQ |
| config: default |
| split: test |
| revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
| metrics: |
| - type: map_at_1 |
| value: 42.653999999999996 |
| - type: map_at_10 |
| value: 59.611999999999995 |
| - type: map_at_100 |
| value: 60.32300000000001 |
| - type: map_at_1000 |
| value: 60.336 |
| - type: map_at_3 |
| value: 55.584999999999994 |
| - type: map_at_5 |
| value: 58.19 |
| - type: mrr_at_1 |
| value: 47.683 |
| - type: mrr_at_10 |
| value: 62.06700000000001 |
| - type: mrr_at_100 |
| value: 62.537 |
| - type: mrr_at_1000 |
| value: 62.544999999999995 |
| - type: mrr_at_3 |
| value: 59.178 |
| - type: mrr_at_5 |
| value: 61.034 |
| - type: ndcg_at_1 |
| value: 47.654 |
| - type: ndcg_at_10 |
| value: 67.001 |
| - type: ndcg_at_100 |
| value: 69.73899999999999 |
| - type: ndcg_at_1000 |
| value: 69.986 |
| - type: ndcg_at_3 |
| value: 59.95700000000001 |
| - type: ndcg_at_5 |
| value: 64.025 |
| - type: precision_at_1 |
| value: 47.654 |
| - type: precision_at_10 |
| value: 10.367999999999999 |
| - type: precision_at_100 |
| value: 1.192 |
| - type: precision_at_1000 |
| value: 0.121 |
| - type: precision_at_3 |
| value: 26.651000000000003 |
| - type: precision_at_5 |
| value: 18.459 |
| - type: recall_at_1 |
| value: 42.653999999999996 |
| - type: recall_at_10 |
| value: 86.619 |
| - type: recall_at_100 |
| value: 98.04899999999999 |
| - type: recall_at_1000 |
| value: 99.812 |
| - type: recall_at_3 |
| value: 68.987 |
| - type: recall_at_5 |
| value: 78.158 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/quora |
| name: MTEB QuoraRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 72.538 |
| - type: map_at_10 |
| value: 86.702 |
| - type: map_at_100 |
| value: 87.31 |
| - type: map_at_1000 |
| value: 87.323 |
| - type: map_at_3 |
| value: 83.87 |
| - type: map_at_5 |
| value: 85.682 |
| - type: mrr_at_1 |
| value: 83.31 |
| - type: mrr_at_10 |
| value: 89.225 |
| - type: mrr_at_100 |
| value: 89.30399999999999 |
| - type: mrr_at_1000 |
| value: 89.30399999999999 |
| - type: mrr_at_3 |
| value: 88.44300000000001 |
| - type: mrr_at_5 |
| value: 89.005 |
| - type: ndcg_at_1 |
| value: 83.32000000000001 |
| - type: ndcg_at_10 |
| value: 90.095 |
| - type: ndcg_at_100 |
| value: 91.12 |
| - type: ndcg_at_1000 |
| value: 91.179 |
| - type: ndcg_at_3 |
| value: 87.606 |
| - type: ndcg_at_5 |
| value: 89.031 |
| - type: precision_at_1 |
| value: 83.32000000000001 |
| - type: precision_at_10 |
| value: 13.641 |
| - type: precision_at_100 |
| value: 1.541 |
| - type: precision_at_1000 |
| value: 0.157 |
| - type: precision_at_3 |
| value: 38.377 |
| - type: precision_at_5 |
| value: 25.162000000000003 |
| - type: recall_at_1 |
| value: 72.538 |
| - type: recall_at_10 |
| value: 96.47200000000001 |
| - type: recall_at_100 |
| value: 99.785 |
| - type: recall_at_1000 |
| value: 99.99900000000001 |
| - type: recall_at_3 |
| value: 89.278 |
| - type: recall_at_5 |
| value: 93.367 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering |
| name: MTEB RedditClustering |
| config: default |
| split: test |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| metrics: |
| - type: v_measure |
| value: 73.55219145406065 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering-p2p |
| name: MTEB RedditClusteringP2P |
| config: default |
| split: test |
| revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
| metrics: |
| - type: v_measure |
| value: 74.13437105242755 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/scidocs |
| name: MTEB SCIDOCS |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 6.873 |
| - type: map_at_10 |
| value: 17.944 |
| - type: map_at_100 |
| value: 21.171 |
| - type: map_at_1000 |
| value: 21.528 |
| - type: map_at_3 |
| value: 12.415 |
| - type: map_at_5 |
| value: 15.187999999999999 |
| - type: mrr_at_1 |
| value: 33.800000000000004 |
| - type: mrr_at_10 |
| value: 46.455 |
| - type: mrr_at_100 |
| value: 47.378 |
| - type: mrr_at_1000 |
| value: 47.394999999999996 |
| - type: mrr_at_3 |
| value: 42.367 |
| - type: mrr_at_5 |
| value: 44.972 |
| - type: ndcg_at_1 |
| value: 33.800000000000004 |
| - type: ndcg_at_10 |
| value: 28.907 |
| - type: ndcg_at_100 |
| value: 39.695 |
| - type: ndcg_at_1000 |
| value: 44.582 |
| - type: ndcg_at_3 |
| value: 26.949 |
| - type: ndcg_at_5 |
| value: 23.988 |
| - type: precision_at_1 |
| value: 33.800000000000004 |
| - type: precision_at_10 |
| value: 15.079999999999998 |
| - type: precision_at_100 |
| value: 3.056 |
| - type: precision_at_1000 |
| value: 0.42100000000000004 |
| - type: precision_at_3 |
| value: 25.167 |
| - type: precision_at_5 |
| value: 21.26 |
| - type: recall_at_1 |
| value: 6.873 |
| - type: recall_at_10 |
| value: 30.568 |
| - type: recall_at_100 |
| value: 62.062 |
| - type: recall_at_1000 |
| value: 85.37700000000001 |
| - type: recall_at_3 |
| value: 15.312999999999999 |
| - type: recall_at_5 |
| value: 21.575 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sickr-sts |
| name: MTEB SICK-R |
| config: default |
| split: test |
| revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
| metrics: |
| - type: cos_sim_pearson |
| value: 82.37009118256057 |
| - type: cos_sim_spearman |
| value: 79.27986395671529 |
| - type: euclidean_pearson |
| value: 79.18037715442115 |
| - type: euclidean_spearman |
| value: 79.28004791561621 |
| - type: manhattan_pearson |
| value: 79.34062972800541 |
| - type: manhattan_spearman |
| value: 79.43106695543402 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts12-sts |
| name: MTEB STS12 |
| config: default |
| split: test |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| metrics: |
| - type: cos_sim_pearson |
| value: 87.48474767383833 |
| - type: cos_sim_spearman |
| value: 79.54505388752513 |
| - type: euclidean_pearson |
| value: 83.43282704179565 |
| - type: euclidean_spearman |
| value: 79.54579919925405 |
| - type: manhattan_pearson |
| value: 83.77564492427952 |
| - type: manhattan_spearman |
| value: 79.84558396989286 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts13-sts |
| name: MTEB STS13 |
| config: default |
| split: test |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| metrics: |
| - type: cos_sim_pearson |
| value: 88.803698035802 |
| - type: cos_sim_spearman |
| value: 88.83451367754881 |
| - type: euclidean_pearson |
| value: 88.28939285711628 |
| - type: euclidean_spearman |
| value: 88.83528996073112 |
| - type: manhattan_pearson |
| value: 88.28017412671795 |
| - type: manhattan_spearman |
| value: 88.9228828016344 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts14-sts |
| name: MTEB STS14 |
| config: default |
| split: test |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.27469288153428 |
| - type: cos_sim_spearman |
| value: 83.87477064876288 |
| - type: euclidean_pearson |
| value: 84.2601737035379 |
| - type: euclidean_spearman |
| value: 83.87431082479074 |
| - type: manhattan_pearson |
| value: 84.3621547772745 |
| - type: manhattan_spearman |
| value: 84.12094375000423 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts15-sts |
| name: MTEB STS15 |
| config: default |
| split: test |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| metrics: |
| - type: cos_sim_pearson |
| value: 88.12749863201587 |
| - type: cos_sim_spearman |
| value: 88.54287568368565 |
| - type: euclidean_pearson |
| value: 87.90429700607999 |
| - type: euclidean_spearman |
| value: 88.5437689576261 |
| - type: manhattan_pearson |
| value: 88.19276653356833 |
| - type: manhattan_spearman |
| value: 88.99995393814679 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts16-sts |
| name: MTEB STS16 |
| config: default |
| split: test |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.68398747560902 |
| - type: cos_sim_spearman |
| value: 86.48815303460574 |
| - type: euclidean_pearson |
| value: 85.52356631237954 |
| - type: euclidean_spearman |
| value: 86.486391949551 |
| - type: manhattan_pearson |
| value: 85.67267981761788 |
| - type: manhattan_spearman |
| value: 86.7073696332485 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts17-crosslingual-sts |
| name: MTEB STS17 (en-en) |
| config: en-en |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 88.9057107443124 |
| - type: cos_sim_spearman |
| value: 88.7312168757697 |
| - type: euclidean_pearson |
| value: 88.72810439714794 |
| - type: euclidean_spearman |
| value: 88.71976185854771 |
| - type: manhattan_pearson |
| value: 88.50433745949111 |
| - type: manhattan_spearman |
| value: 88.51726175544195 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (en) |
| config: en |
| split: test |
| revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| metrics: |
| - type: cos_sim_pearson |
| value: 67.59391795109886 |
| - type: cos_sim_spearman |
| value: 66.87613008631367 |
| - type: euclidean_pearson |
| value: 69.23198488262217 |
| - type: euclidean_spearman |
| value: 66.85427723013692 |
| - type: manhattan_pearson |
| value: 69.50730124841084 |
| - type: manhattan_spearman |
| value: 67.10404669820792 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/stsbenchmark-sts |
| name: MTEB STSBenchmark |
| config: default |
| split: test |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
| metrics: |
| - type: cos_sim_pearson |
| value: 87.0820605344619 |
| - type: cos_sim_spearman |
| value: 86.8518089863434 |
| - type: euclidean_pearson |
| value: 86.31087134689284 |
| - type: euclidean_spearman |
| value: 86.8518520517941 |
| - type: manhattan_pearson |
| value: 86.47203796160612 |
| - type: manhattan_spearman |
| value: 87.1080149734421 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/scidocs-reranking |
| name: MTEB SciDocsRR |
| config: default |
| split: test |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| metrics: |
| - type: map |
| value: 89.09255369305481 |
| - type: mrr |
| value: 97.10323445617563 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/scifact |
| name: MTEB SciFact |
| config: default |
| split: test |
| revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
| metrics: |
| - type: map_at_1 |
| value: 61.260999999999996 |
| - type: map_at_10 |
| value: 74.043 |
| - type: map_at_100 |
| value: 74.37700000000001 |
| - type: map_at_1000 |
| value: 74.384 |
| - type: map_at_3 |
| value: 71.222 |
| - type: map_at_5 |
| value: 72.875 |
| - type: mrr_at_1 |
| value: 64.333 |
| - type: mrr_at_10 |
| value: 74.984 |
| - type: mrr_at_100 |
| value: 75.247 |
| - type: mrr_at_1000 |
| value: 75.25500000000001 |
| - type: mrr_at_3 |
| value: 73.167 |
| - type: mrr_at_5 |
| value: 74.35000000000001 |
| - type: ndcg_at_1 |
| value: 64.333 |
| - type: ndcg_at_10 |
| value: 79.06 |
| - type: ndcg_at_100 |
| value: 80.416 |
| - type: ndcg_at_1000 |
| value: 80.55600000000001 |
| - type: ndcg_at_3 |
| value: 74.753 |
| - type: ndcg_at_5 |
| value: 76.97500000000001 |
| - type: precision_at_1 |
| value: 64.333 |
| - type: precision_at_10 |
| value: 10.567 |
| - type: precision_at_100 |
| value: 1.1199999999999999 |
| - type: precision_at_1000 |
| value: 0.11299999999999999 |
| - type: precision_at_3 |
| value: 29.889 |
| - type: precision_at_5 |
| value: 19.533 |
| - type: recall_at_1 |
| value: 61.260999999999996 |
| - type: recall_at_10 |
| value: 93.167 |
| - type: recall_at_100 |
| value: 99.0 |
| - type: recall_at_1000 |
| value: 100.0 |
| - type: recall_at_3 |
| value: 81.667 |
| - type: recall_at_5 |
| value: 87.394 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/sprintduplicatequestions-pairclassification |
| name: MTEB SprintDuplicateQuestions |
| config: default |
| split: test |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 99.71980198019801 |
| - type: cos_sim_ap |
| value: 92.81616007802704 |
| - type: cos_sim_f1 |
| value: 85.17548454688318 |
| - type: cos_sim_precision |
| value: 89.43894389438944 |
| - type: cos_sim_recall |
| value: 81.3 |
| - type: dot_accuracy |
| value: 99.71980198019801 |
| - type: dot_ap |
| value: 92.81398760591358 |
| - type: dot_f1 |
| value: 85.17548454688318 |
| - type: dot_precision |
| value: 89.43894389438944 |
| - type: dot_recall |
| value: 81.3 |
| - type: euclidean_accuracy |
| value: 99.71980198019801 |
| - type: euclidean_ap |
| value: 92.81560637245072 |
| - type: euclidean_f1 |
| value: 85.17548454688318 |
| - type: euclidean_precision |
| value: 89.43894389438944 |
| - type: euclidean_recall |
| value: 81.3 |
| - type: manhattan_accuracy |
| value: 99.73069306930694 |
| - type: manhattan_ap |
| value: 93.14005487480794 |
| - type: manhattan_f1 |
| value: 85.56263269639068 |
| - type: manhattan_precision |
| value: 91.17647058823529 |
| - type: manhattan_recall |
| value: 80.60000000000001 |
| - type: max_accuracy |
| value: 99.73069306930694 |
| - type: max_ap |
| value: 93.14005487480794 |
| - type: max_f1 |
| value: 85.56263269639068 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering |
| name: MTEB StackExchangeClustering |
| config: default |
| split: test |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
| metrics: |
| - type: v_measure |
| value: 79.86443362395185 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering-p2p |
| name: MTEB StackExchangeClusteringP2P |
| config: default |
| split: test |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
| metrics: |
| - type: v_measure |
| value: 49.40897096662564 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/stackoverflowdupquestions-reranking |
| name: MTEB StackOverflowDupQuestions |
| config: default |
| split: test |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
| metrics: |
| - type: map |
| value: 55.66040806627947 |
| - type: mrr |
| value: 56.58670475766064 |
| - task: |
| type: Summarization |
| dataset: |
| type: mteb/summeval |
| name: MTEB SummEval |
| config: default |
| split: test |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
| metrics: |
| - type: cos_sim_pearson |
| value: 31.51015090598575 |
| - type: cos_sim_spearman |
| value: 31.35016454939226 |
| - type: dot_pearson |
| value: 31.5150068731 |
| - type: dot_spearman |
| value: 31.34790869023487 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/trec-covid |
| name: MTEB TRECCOVID |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 0.254 |
| - type: map_at_10 |
| value: 2.064 |
| - type: map_at_100 |
| value: 12.909 |
| - type: map_at_1000 |
| value: 31.761 |
| - type: map_at_3 |
| value: 0.738 |
| - type: map_at_5 |
| value: 1.155 |
| - type: mrr_at_1 |
| value: 96.0 |
| - type: mrr_at_10 |
| value: 98.0 |
| - type: mrr_at_100 |
| value: 98.0 |
| - type: mrr_at_1000 |
| value: 98.0 |
| - type: mrr_at_3 |
| value: 98.0 |
| - type: mrr_at_5 |
| value: 98.0 |
| - type: ndcg_at_1 |
| value: 93.0 |
| - type: ndcg_at_10 |
| value: 82.258 |
| - type: ndcg_at_100 |
| value: 64.34 |
| - type: ndcg_at_1000 |
| value: 57.912 |
| - type: ndcg_at_3 |
| value: 90.827 |
| - type: ndcg_at_5 |
| value: 86.79 |
| - type: precision_at_1 |
| value: 96.0 |
| - type: precision_at_10 |
| value: 84.8 |
| - type: precision_at_100 |
| value: 66.0 |
| - type: precision_at_1000 |
| value: 25.356 |
| - type: precision_at_3 |
| value: 94.667 |
| - type: precision_at_5 |
| value: 90.4 |
| - type: recall_at_1 |
| value: 0.254 |
| - type: recall_at_10 |
| value: 2.1950000000000003 |
| - type: recall_at_100 |
| value: 16.088 |
| - type: recall_at_1000 |
| value: 54.559000000000005 |
| - type: recall_at_3 |
| value: 0.75 |
| - type: recall_at_5 |
| value: 1.191 |
| - task: |
| type: Retrieval |
| dataset: |
| type: mteb/touche2020 |
| name: MTEB Touche2020 |
| config: default |
| split: test |
| revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
| metrics: |
| - type: map_at_1 |
| value: 2.976 |
| - type: map_at_10 |
| value: 11.389000000000001 |
| - type: map_at_100 |
| value: 18.429000000000002 |
| - type: map_at_1000 |
| value: 20.113 |
| - type: map_at_3 |
| value: 6.483 |
| - type: map_at_5 |
| value: 8.770999999999999 |
| - type: mrr_at_1 |
| value: 40.816 |
| - type: mrr_at_10 |
| value: 58.118 |
| - type: mrr_at_100 |
| value: 58.489999999999995 |
| - type: mrr_at_1000 |
| value: 58.489999999999995 |
| - type: mrr_at_3 |
| value: 53.061 |
| - type: mrr_at_5 |
| value: 57.041 |
| - type: ndcg_at_1 |
| value: 40.816 |
| - type: ndcg_at_10 |
| value: 30.567 |
| - type: ndcg_at_100 |
| value: 42.44 |
| - type: ndcg_at_1000 |
| value: 53.480000000000004 |
| - type: ndcg_at_3 |
| value: 36.016 |
| - type: ndcg_at_5 |
| value: 34.257 |
| - type: precision_at_1 |
| value: 42.857 |
| - type: precision_at_10 |
| value: 25.714 |
| - type: precision_at_100 |
| value: 8.429 |
| - type: precision_at_1000 |
| value: 1.5939999999999999 |
| - type: precision_at_3 |
| value: 36.735 |
| - type: precision_at_5 |
| value: 33.878 |
| - type: recall_at_1 |
| value: 2.976 |
| - type: recall_at_10 |
| value: 17.854999999999997 |
| - type: recall_at_100 |
| value: 51.833 |
| - type: recall_at_1000 |
| value: 86.223 |
| - type: recall_at_3 |
| value: 7.887 |
| - type: recall_at_5 |
| value: 12.026 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/toxic_conversations_50k |
| name: MTEB ToxicConversationsClassification |
| config: default |
| split: test |
| revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
| metrics: |
| - type: accuracy |
| value: 85.1174 |
| - type: ap |
| value: 30.169441069345748 |
| - type: f1 |
| value: 69.79254701873245 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/tweet_sentiment_extraction |
| name: MTEB TweetSentimentExtractionClassification |
| config: default |
| split: test |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| metrics: |
| - type: accuracy |
| value: 72.58347481607245 |
| - type: f1 |
| value: 72.74877295564937 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/twentynewsgroups-clustering |
| name: MTEB TwentyNewsgroupsClustering |
| config: default |
| split: test |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| metrics: |
| - type: v_measure |
| value: 53.90586138221305 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twittersemeval2015-pairclassification |
| name: MTEB TwitterSemEval2015 |
| config: default |
| split: test |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 87.35769207844072 |
| - type: cos_sim_ap |
| value: 77.9645072410354 |
| - type: cos_sim_f1 |
| value: 71.32352941176471 |
| - type: cos_sim_precision |
| value: 66.5903890160183 |
| - type: cos_sim_recall |
| value: 76.78100263852242 |
| - type: dot_accuracy |
| value: 87.37557370209214 |
| - type: dot_ap |
| value: 77.96250046429908 |
| - type: dot_f1 |
| value: 71.28932757557064 |
| - type: dot_precision |
| value: 66.95249130938586 |
| - type: dot_recall |
| value: 76.22691292875989 |
| - type: euclidean_accuracy |
| value: 87.35173153722357 |
| - type: euclidean_ap |
| value: 77.96520460741593 |
| - type: euclidean_f1 |
| value: 71.32470733210104 |
| - type: euclidean_precision |
| value: 66.91329479768785 |
| - type: euclidean_recall |
| value: 76.35883905013192 |
| - type: manhattan_accuracy |
| value: 87.25636287774931 |
| - type: manhattan_ap |
| value: 77.77752485611796 |
| - type: manhattan_f1 |
| value: 71.18148599269183 |
| - type: manhattan_precision |
| value: 66.10859728506787 |
| - type: manhattan_recall |
| value: 77.0976253298153 |
| - type: max_accuracy |
| value: 87.37557370209214 |
| - type: max_ap |
| value: 77.96520460741593 |
| - type: max_f1 |
| value: 71.32470733210104 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twitterurlcorpus-pairclassification |
| name: MTEB TwitterURLCorpus |
| config: default |
| split: test |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
| metrics: |
| - type: cos_sim_accuracy |
| value: 89.38176737687739 |
| - type: cos_sim_ap |
| value: 86.58811861657401 |
| - type: cos_sim_f1 |
| value: 79.09430644097604 |
| - type: cos_sim_precision |
| value: 75.45085977911366 |
| - type: cos_sim_recall |
| value: 83.10748383122882 |
| - type: dot_accuracy |
| value: 89.38370784336554 |
| - type: dot_ap |
| value: 86.58840606004333 |
| - type: dot_f1 |
| value: 79.10179860068133 |
| - type: dot_precision |
| value: 75.44546153308643 |
| - type: dot_recall |
| value: 83.13058207576223 |
| - type: euclidean_accuracy |
| value: 89.38564830985369 |
| - type: euclidean_ap |
| value: 86.58820721061164 |
| - type: euclidean_f1 |
| value: 79.09070942235888 |
| - type: euclidean_precision |
| value: 75.38729937194697 |
| - type: euclidean_recall |
| value: 83.17677856482906 |
| - type: manhattan_accuracy |
| value: 89.40699344122326 |
| - type: manhattan_ap |
| value: 86.60631843011362 |
| - type: manhattan_f1 |
| value: 79.14949970570925 |
| - type: manhattan_precision |
| value: 75.78191039729502 |
| - type: manhattan_recall |
| value: 82.83030489682784 |
| - type: max_accuracy |
| value: 89.40699344122326 |
| - type: max_ap |
| value: 86.60631843011362 |
| - type: max_f1 |
| value: 79.14949970570925 |
| - task: |
| type: STS |
| dataset: |
| type: C-MTEB/AFQMC |
| name: MTEB AFQMC |
| config: default |
| split: validation |
| revision: b44c3b011063adb25877c13823db83bb193913c4 |
| metrics: |
| - type: cos_sim_pearson |
| value: 65.58442135663871 |
| - type: cos_sim_spearman |
| value: 72.2538631361313 |
| - type: euclidean_pearson |
| value: 70.97255486607429 |
| - type: euclidean_spearman |
| value: 72.25374250228647 |
| - type: manhattan_pearson |
| value: 70.83250199989911 |
| - type: manhattan_spearman |
| value: 72.14819496536272 |
| - task: |
| type: STS |
| dataset: |
| type: C-MTEB/ATEC |
| name: MTEB ATEC |
| config: default |
| split: test |
| revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865 |
| metrics: |
| - type: cos_sim_pearson |
| value: 59.99478404929932 |
| - type: cos_sim_spearman |
| value: 62.61836216999812 |
| - type: euclidean_pearson |
| value: 66.86429811933593 |
| - type: euclidean_spearman |
| value: 62.6183520374191 |
| - type: manhattan_pearson |
| value: 66.8063778911633 |
| - type: manhattan_spearman |
| value: 62.569607573241115 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (zh) |
| config: zh |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 53.98400000000001 |
| - type: f1 |
| value: 51.21447361350723 |
| - task: |
| type: STS |
| dataset: |
| type: C-MTEB/BQ |
| name: MTEB BQ |
| config: default |
| split: test |
| revision: e3dda5e115e487b39ec7e618c0c6a29137052a55 |
| metrics: |
| - type: cos_sim_pearson |
| value: 79.11941660686553 |
| - type: cos_sim_spearman |
| value: 81.25029594540435 |
| - type: euclidean_pearson |
| value: 82.06973504238826 |
| - type: euclidean_spearman |
| value: 81.2501989488524 |
| - type: manhattan_pearson |
| value: 82.10094630392753 |
| - type: manhattan_spearman |
| value: 81.27987244392389 |
| - task: |
| type: Clustering |
| dataset: |
| type: C-MTEB/CLSClusteringP2P |
| name: MTEB CLSClusteringP2P |
| config: default |
| split: test |
| revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476 |
| metrics: |
| - type: v_measure |
| value: 47.07270168705156 |
| - task: |
| type: Clustering |
| dataset: |
| type: C-MTEB/CLSClusteringS2S |
| name: MTEB CLSClusteringS2S |
| config: default |
| split: test |
| revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f |
| metrics: |
| - type: v_measure |
| value: 45.98511703185043 |
| - task: |
| type: Reranking |
| dataset: |
| type: C-MTEB/CMedQAv1-reranking |
| name: MTEB CMedQAv1 |
| config: default |
| split: test |
| revision: 8d7f1e942507dac42dc58017c1a001c3717da7df |
| metrics: |
| - type: map |
| value: 88.19895157194931 |
| - type: mrr |
| value: 90.21424603174603 |
| - task: |
| type: Reranking |
| dataset: |
| type: C-MTEB/CMedQAv2-reranking |
| name: MTEB CMedQAv2 |
| config: default |
| split: test |
| revision: 23d186750531a14a0357ca22cd92d712fd512ea0 |
| metrics: |
| - type: map |
| value: 88.03317320980119 |
| - type: mrr |
| value: 89.9461507936508 |
| - task: |
| type: Retrieval |
| dataset: |
| type: C-MTEB/CmedqaRetrieval |
| name: MTEB CmedqaRetrieval |
| config: default |
| split: dev |
| revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301 |
| metrics: |
| - type: map_at_1 |
| value: 29.037000000000003 |
| - type: map_at_10 |
| value: 42.001 |
| - type: map_at_100 |
| value: 43.773 |
| - type: map_at_1000 |
| value: 43.878 |
| - type: map_at_3 |
| value: 37.637 |
| - type: map_at_5 |
| value: 40.034 |
| - type: mrr_at_1 |
| value: 43.136 |
| - type: mrr_at_10 |
| value: 51.158 |
| - type: mrr_at_100 |
| value: 52.083 |
| - type: mrr_at_1000 |
| value: 52.12 |
| - type: mrr_at_3 |
| value: 48.733 |
| - type: mrr_at_5 |
| value: 50.025 |
| - type: ndcg_at_1 |
| value: 43.136 |
| - type: ndcg_at_10 |
| value: 48.685 |
| - type: ndcg_at_100 |
| value: 55.513 |
| - type: ndcg_at_1000 |
| value: 57.242000000000004 |
| - type: ndcg_at_3 |
| value: 43.329 |
| - type: ndcg_at_5 |
| value: 45.438 |
| - type: precision_at_1 |
| value: 43.136 |
| - type: precision_at_10 |
| value: 10.56 |
| - type: precision_at_100 |
| value: 1.6129999999999998 |
| - type: precision_at_1000 |
| value: 0.184 |
| - type: precision_at_3 |
| value: 24.064 |
| - type: precision_at_5 |
| value: 17.269000000000002 |
| - type: recall_at_1 |
| value: 29.037000000000003 |
| - type: recall_at_10 |
| value: 59.245000000000005 |
| - type: recall_at_100 |
| value: 87.355 |
| - type: recall_at_1000 |
| value: 98.74000000000001 |
| - type: recall_at_3 |
| value: 42.99 |
| - type: recall_at_5 |
| value: 49.681999999999995 |
| - task: |
| type: PairClassification |
| dataset: |
| type: C-MTEB/CMNLI |
| name: MTEB Cmnli |
| config: default |
| split: validation |
| revision: 41bc36f332156f7adc9e38f53777c959b2ae9766 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 82.68190018039687 |
| - type: cos_sim_ap |
| value: 90.18017125327886 |
| - type: cos_sim_f1 |
| value: 83.64080906868193 |
| - type: cos_sim_precision |
| value: 79.7076890489303 |
| - type: cos_sim_recall |
| value: 87.98223053542202 |
| - type: dot_accuracy |
| value: 82.68190018039687 |
| - type: dot_ap |
| value: 90.18782350103646 |
| - type: dot_f1 |
| value: 83.64242087729039 |
| - type: dot_precision |
| value: 79.65313028764805 |
| - type: dot_recall |
| value: 88.05237315875614 |
| - type: euclidean_accuracy |
| value: 82.68190018039687 |
| - type: euclidean_ap |
| value: 90.1801957900632 |
| - type: euclidean_f1 |
| value: 83.63636363636364 |
| - type: euclidean_precision |
| value: 79.52772506852203 |
| - type: euclidean_recall |
| value: 88.19265840542437 |
| - type: manhattan_accuracy |
| value: 82.14070956103427 |
| - type: manhattan_ap |
| value: 89.96178420101427 |
| - type: manhattan_f1 |
| value: 83.21087838578791 |
| - type: manhattan_precision |
| value: 78.35605121850475 |
| - type: manhattan_recall |
| value: 88.70703764320785 |
| - type: max_accuracy |
| value: 82.68190018039687 |
| - type: max_ap |
| value: 90.18782350103646 |
| - type: max_f1 |
| value: 83.64242087729039 |
| - task: |
| type: Retrieval |
| dataset: |
| type: C-MTEB/CovidRetrieval |
| name: MTEB CovidRetrieval |
| config: default |
| split: dev |
| revision: 1271c7809071a13532e05f25fb53511ffce77117 |
| metrics: |
| - type: map_at_1 |
| value: 72.234 |
| - type: map_at_10 |
| value: 80.10000000000001 |
| - type: map_at_100 |
| value: 80.36 |
| - type: map_at_1000 |
| value: 80.363 |
| - type: map_at_3 |
| value: 78.315 |
| - type: map_at_5 |
| value: 79.607 |
| - type: mrr_at_1 |
| value: 72.392 |
| - type: mrr_at_10 |
| value: 80.117 |
| - type: mrr_at_100 |
| value: 80.36999999999999 |
| - type: mrr_at_1000 |
| value: 80.373 |
| - type: mrr_at_3 |
| value: 78.469 |
| - type: mrr_at_5 |
| value: 79.633 |
| - type: ndcg_at_1 |
| value: 72.392 |
| - type: ndcg_at_10 |
| value: 83.651 |
| - type: ndcg_at_100 |
| value: 84.749 |
| - type: ndcg_at_1000 |
| value: 84.83000000000001 |
| - type: ndcg_at_3 |
| value: 80.253 |
| - type: ndcg_at_5 |
| value: 82.485 |
| - type: precision_at_1 |
| value: 72.392 |
| - type: precision_at_10 |
| value: 9.557 |
| - type: precision_at_100 |
| value: 1.004 |
| - type: precision_at_1000 |
| value: 0.101 |
| - type: precision_at_3 |
| value: 28.732000000000003 |
| - type: precision_at_5 |
| value: 18.377 |
| - type: recall_at_1 |
| value: 72.234 |
| - type: recall_at_10 |
| value: 94.573 |
| - type: recall_at_100 |
| value: 99.368 |
| - type: recall_at_1000 |
| value: 100.0 |
| - type: recall_at_3 |
| value: 85.669 |
| - type: recall_at_5 |
| value: 91.01700000000001 |
| - task: |
| type: Retrieval |
| dataset: |
| type: C-MTEB/DuRetrieval |
| name: MTEB DuRetrieval |
| config: default |
| split: dev |
| revision: a1a333e290fe30b10f3f56498e3a0d911a693ced |
| metrics: |
| - type: map_at_1 |
| value: 26.173999999999996 |
| - type: map_at_10 |
| value: 80.04 |
| - type: map_at_100 |
| value: 82.94500000000001 |
| - type: map_at_1000 |
| value: 82.98100000000001 |
| - type: map_at_3 |
| value: 55.562999999999995 |
| - type: map_at_5 |
| value: 69.89800000000001 |
| - type: mrr_at_1 |
| value: 89.5 |
| - type: mrr_at_10 |
| value: 92.996 |
| - type: mrr_at_100 |
| value: 93.06400000000001 |
| - type: mrr_at_1000 |
| value: 93.065 |
| - type: mrr_at_3 |
| value: 92.658 |
| - type: mrr_at_5 |
| value: 92.84599999999999 |
| - type: ndcg_at_1 |
| value: 89.5 |
| - type: ndcg_at_10 |
| value: 87.443 |
| - type: ndcg_at_100 |
| value: 90.253 |
| - type: ndcg_at_1000 |
| value: 90.549 |
| - type: ndcg_at_3 |
| value: 85.874 |
| - type: ndcg_at_5 |
| value: 84.842 |
| - type: precision_at_1 |
| value: 89.5 |
| - type: precision_at_10 |
| value: 41.805 |
| - type: precision_at_100 |
| value: 4.827 |
| - type: precision_at_1000 |
| value: 0.49 |
| - type: precision_at_3 |
| value: 76.85 |
| - type: precision_at_5 |
| value: 64.8 |
| - type: recall_at_1 |
| value: 26.173999999999996 |
| - type: recall_at_10 |
| value: 89.101 |
| - type: recall_at_100 |
| value: 98.08099999999999 |
| - type: recall_at_1000 |
| value: 99.529 |
| - type: recall_at_3 |
| value: 57.902 |
| - type: recall_at_5 |
| value: 74.602 |
| - task: |
| type: Retrieval |
| dataset: |
| type: C-MTEB/EcomRetrieval |
| name: MTEB EcomRetrieval |
| config: default |
| split: dev |
| revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9 |
| metrics: |
| - type: map_at_1 |
| value: 56.10000000000001 |
| - type: map_at_10 |
| value: 66.15299999999999 |
| - type: map_at_100 |
| value: 66.625 |
| - type: map_at_1000 |
| value: 66.636 |
| - type: map_at_3 |
| value: 63.632999999999996 |
| - type: map_at_5 |
| value: 65.293 |
| - type: mrr_at_1 |
| value: 56.10000000000001 |
| - type: mrr_at_10 |
| value: 66.15299999999999 |
| - type: mrr_at_100 |
| value: 66.625 |
| - type: mrr_at_1000 |
| value: 66.636 |
| - type: mrr_at_3 |
| value: 63.632999999999996 |
| - type: mrr_at_5 |
| value: 65.293 |
| - type: ndcg_at_1 |
| value: 56.10000000000001 |
| - type: ndcg_at_10 |
| value: 71.146 |
| - type: ndcg_at_100 |
| value: 73.27799999999999 |
| - type: ndcg_at_1000 |
| value: 73.529 |
| - type: ndcg_at_3 |
| value: 66.09 |
| - type: ndcg_at_5 |
| value: 69.08999999999999 |
| - type: precision_at_1 |
| value: 56.10000000000001 |
| - type: precision_at_10 |
| value: 8.68 |
| - type: precision_at_100 |
| value: 0.964 |
| - type: precision_at_1000 |
| value: 0.098 |
| - type: precision_at_3 |
| value: 24.4 |
| - type: precision_at_5 |
| value: 16.1 |
| - type: recall_at_1 |
| value: 56.10000000000001 |
| - type: recall_at_10 |
| value: 86.8 |
| - type: recall_at_100 |
| value: 96.39999999999999 |
| - type: recall_at_1000 |
| value: 98.3 |
| - type: recall_at_3 |
| value: 73.2 |
| - type: recall_at_5 |
| value: 80.5 |
| - task: |
| type: Classification |
| dataset: |
| type: C-MTEB/IFlyTek-classification |
| name: MTEB IFlyTek |
| config: default |
| split: validation |
| revision: 421605374b29664c5fc098418fe20ada9bd55f8a |
| metrics: |
| - type: accuracy |
| value: 54.52096960369373 |
| - type: f1 |
| value: 40.930845295808695 |
| - task: |
| type: Classification |
| dataset: |
| type: C-MTEB/JDReview-classification |
| name: MTEB JDReview |
| config: default |
| split: test |
| revision: b7c64bd89eb87f8ded463478346f76731f07bf8b |
| metrics: |
| - type: accuracy |
| value: 86.51031894934334 |
| - type: ap |
| value: 55.9516014323483 |
| - type: f1 |
| value: 81.54813679326381 |
| - task: |
| type: STS |
| dataset: |
| type: C-MTEB/LCQMC |
| name: MTEB LCQMC |
| config: default |
| split: test |
| revision: 17f9b096f80380fce5ed12a9be8be7784b337daf |
| metrics: |
| - type: cos_sim_pearson |
| value: 69.67437838574276 |
| - type: cos_sim_spearman |
| value: 73.81314174653045 |
| - type: euclidean_pearson |
| value: 72.63430276680275 |
| - type: euclidean_spearman |
| value: 73.81358736777001 |
| - type: manhattan_pearson |
| value: 72.58743833842829 |
| - type: manhattan_spearman |
| value: 73.7590419009179 |
| - task: |
| type: Reranking |
| dataset: |
| type: C-MTEB/Mmarco-reranking |
| name: MTEB MMarcoReranking |
| config: default |
| split: dev |
| revision: None |
| metrics: |
| - type: map |
| value: 31.648613483640254 |
| - type: mrr |
| value: 30.37420634920635 |
| - task: |
| type: Retrieval |
| dataset: |
| type: C-MTEB/MMarcoRetrieval |
| name: MTEB MMarcoRetrieval |
| config: default |
| split: dev |
| revision: 539bbde593d947e2a124ba72651aafc09eb33fc2 |
| metrics: |
| - type: map_at_1 |
| value: 73.28099999999999 |
| - type: map_at_10 |
| value: 81.977 |
| - type: map_at_100 |
| value: 82.222 |
| - type: map_at_1000 |
| value: 82.22699999999999 |
| - type: map_at_3 |
| value: 80.441 |
| - type: map_at_5 |
| value: 81.46600000000001 |
| - type: mrr_at_1 |
| value: 75.673 |
| - type: mrr_at_10 |
| value: 82.41000000000001 |
| - type: mrr_at_100 |
| value: 82.616 |
| - type: mrr_at_1000 |
| value: 82.621 |
| - type: mrr_at_3 |
| value: 81.094 |
| - type: mrr_at_5 |
| value: 81.962 |
| - type: ndcg_at_1 |
| value: 75.673 |
| - type: ndcg_at_10 |
| value: 85.15599999999999 |
| - type: ndcg_at_100 |
| value: 86.151 |
| - type: ndcg_at_1000 |
| value: 86.26899999999999 |
| - type: ndcg_at_3 |
| value: 82.304 |
| - type: ndcg_at_5 |
| value: 84.009 |
| - type: precision_at_1 |
| value: 75.673 |
| - type: precision_at_10 |
| value: 10.042 |
| - type: precision_at_100 |
| value: 1.052 |
| - type: precision_at_1000 |
| value: 0.106 |
| - type: precision_at_3 |
| value: 30.673000000000002 |
| - type: precision_at_5 |
| value: 19.326999999999998 |
| - type: recall_at_1 |
| value: 73.28099999999999 |
| - type: recall_at_10 |
| value: 94.446 |
| - type: recall_at_100 |
| value: 98.737 |
| - type: recall_at_1000 |
| value: 99.649 |
| - type: recall_at_3 |
| value: 86.984 |
| - type: recall_at_5 |
| value: 91.024 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (zh-CN) |
| config: zh-CN |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
| - type: accuracy |
| value: 81.08607935440484 |
| - type: f1 |
| value: 78.24879986066307 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (zh-CN) |
| config: zh-CN |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 86.05917955615332 |
| - type: f1 |
| value: 85.05279279434997 |
| - task: |
| type: Retrieval |
| dataset: |
| type: C-MTEB/MedicalRetrieval |
| name: MTEB MedicalRetrieval |
| config: default |
| split: dev |
| revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6 |
| metrics: |
| - type: map_at_1 |
| value: 56.2 |
| - type: map_at_10 |
| value: 62.57899999999999 |
| - type: map_at_100 |
| value: 63.154999999999994 |
| - type: map_at_1000 |
| value: 63.193 |
| - type: map_at_3 |
| value: 61.217 |
| - type: map_at_5 |
| value: 62.012 |
| - type: mrr_at_1 |
| value: 56.3 |
| - type: mrr_at_10 |
| value: 62.629000000000005 |
| - type: mrr_at_100 |
| value: 63.205999999999996 |
| - type: mrr_at_1000 |
| value: 63.244 |
| - type: mrr_at_3 |
| value: 61.267 |
| - type: mrr_at_5 |
| value: 62.062 |
| - type: ndcg_at_1 |
| value: 56.2 |
| - type: ndcg_at_10 |
| value: 65.592 |
| - type: ndcg_at_100 |
| value: 68.657 |
| - type: ndcg_at_1000 |
| value: 69.671 |
| - type: ndcg_at_3 |
| value: 62.808 |
| - type: ndcg_at_5 |
| value: 64.24499999999999 |
| - type: precision_at_1 |
| value: 56.2 |
| - type: precision_at_10 |
| value: 7.5 |
| - type: precision_at_100 |
| value: 0.899 |
| - type: precision_at_1000 |
| value: 0.098 |
| - type: precision_at_3 |
| value: 22.467000000000002 |
| - type: precision_at_5 |
| value: 14.180000000000001 |
| - type: recall_at_1 |
| value: 56.2 |
| - type: recall_at_10 |
| value: 75.0 |
| - type: recall_at_100 |
| value: 89.9 |
| - type: recall_at_1000 |
| value: 97.89999999999999 |
| - type: recall_at_3 |
| value: 67.4 |
| - type: recall_at_5 |
| value: 70.89999999999999 |
| - task: |
| type: Classification |
| dataset: |
| type: C-MTEB/MultilingualSentiment-classification |
| name: MTEB MultilingualSentiment |
| config: default |
| split: validation |
| revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a |
| metrics: |
| - type: accuracy |
| value: 76.87666666666667 |
| - type: f1 |
| value: 76.7317686219665 |
| - task: |
| type: PairClassification |
| dataset: |
| type: C-MTEB/OCNLI |
| name: MTEB Ocnli |
| config: default |
| split: validation |
| revision: 66e76a618a34d6d565d5538088562851e6daa7ec |
| metrics: |
| - type: cos_sim_accuracy |
| value: 79.64266377910124 |
| - type: cos_sim_ap |
| value: 84.78274442344829 |
| - type: cos_sim_f1 |
| value: 81.16947472745292 |
| - type: cos_sim_precision |
| value: 76.47058823529412 |
| - type: cos_sim_recall |
| value: 86.48363252375924 |
| - type: dot_accuracy |
| value: 79.64266377910124 |
| - type: dot_ap |
| value: 84.7851404063692 |
| - type: dot_f1 |
| value: 81.16947472745292 |
| - type: dot_precision |
| value: 76.47058823529412 |
| - type: dot_recall |
| value: 86.48363252375924 |
| - type: euclidean_accuracy |
| value: 79.64266377910124 |
| - type: euclidean_ap |
| value: 84.78068373762378 |
| - type: euclidean_f1 |
| value: 81.14794656110837 |
| - type: euclidean_precision |
| value: 76.35009310986965 |
| - type: euclidean_recall |
| value: 86.58922914466737 |
| - type: manhattan_accuracy |
| value: 79.48023822414727 |
| - type: manhattan_ap |
| value: 84.72928897427576 |
| - type: manhattan_f1 |
| value: 81.32084770823064 |
| - type: manhattan_precision |
| value: 76.24768946395564 |
| - type: manhattan_recall |
| value: 87.11721224920802 |
| - type: max_accuracy |
| value: 79.64266377910124 |
| - type: max_ap |
| value: 84.7851404063692 |
| - type: max_f1 |
| value: 81.32084770823064 |
| - task: |
| type: Classification |
| dataset: |
| type: C-MTEB/OnlineShopping-classification |
| name: MTEB OnlineShopping |
| config: default |
| split: test |
| revision: e610f2ebd179a8fda30ae534c3878750a96db120 |
| metrics: |
| - type: accuracy |
| value: 94.3 |
| - type: ap |
| value: 92.8664032274438 |
| - type: f1 |
| value: 94.29311102997727 |
| - task: |
| type: STS |
| dataset: |
| type: C-MTEB/PAWSX |
| name: MTEB PAWSX |
| config: default |
| split: test |
| revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1 |
| metrics: |
| - type: cos_sim_pearson |
| value: 48.51392279882909 |
| - type: cos_sim_spearman |
| value: 54.06338895994974 |
| - type: euclidean_pearson |
| value: 52.58480559573412 |
| - type: euclidean_spearman |
| value: 54.06417276612201 |
| - type: manhattan_pearson |
| value: 52.69525121721343 |
| - type: manhattan_spearman |
| value: 54.048147455389675 |
| - task: |
| type: STS |
| dataset: |
| type: C-MTEB/QBQTC |
| name: MTEB QBQTC |
| config: default |
| split: test |
| revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7 |
| metrics: |
| - type: cos_sim_pearson |
| value: 29.728387290757325 |
| - type: cos_sim_spearman |
| value: 31.366121633635284 |
| - type: euclidean_pearson |
| value: 29.14588368552961 |
| - type: euclidean_spearman |
| value: 31.36764411112844 |
| - type: manhattan_pearson |
| value: 29.63517350523121 |
| - type: manhattan_spearman |
| value: 31.94157020583762 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (zh) |
| config: zh |
| split: test |
| revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| metrics: |
| - type: cos_sim_pearson |
| value: 63.64868296271406 |
| - type: cos_sim_spearman |
| value: 66.12800618164744 |
| - type: euclidean_pearson |
| value: 63.21405767340238 |
| - type: euclidean_spearman |
| value: 66.12786567790748 |
| - type: manhattan_pearson |
| value: 64.04300276525848 |
| - type: manhattan_spearman |
| value: 66.5066857145652 |
| - task: |
| type: STS |
| dataset: |
| type: C-MTEB/STSB |
| name: MTEB STSB |
| config: default |
| split: test |
| revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0 |
| metrics: |
| - type: cos_sim_pearson |
| value: 81.2302623912794 |
| - type: cos_sim_spearman |
| value: 81.16833673266562 |
| - type: euclidean_pearson |
| value: 79.47647843876024 |
| - type: euclidean_spearman |
| value: 81.16944349524972 |
| - type: manhattan_pearson |
| value: 79.84947238492208 |
| - type: manhattan_spearman |
| value: 81.64626599410026 |
| - task: |
| type: Reranking |
| dataset: |
| type: C-MTEB/T2Reranking |
| name: MTEB T2Reranking |
| config: default |
| split: dev |
| revision: 76631901a18387f85eaa53e5450019b87ad58ef9 |
| metrics: |
| - type: map |
| value: 67.80129586475687 |
| - type: mrr |
| value: 77.77402311635554 |
| - task: |
| type: Retrieval |
| dataset: |
| type: C-MTEB/T2Retrieval |
| name: MTEB T2Retrieval |
| config: default |
| split: dev |
| revision: 8731a845f1bf500a4f111cf1070785c793d10e64 |
| metrics: |
| - type: map_at_1 |
| value: 28.666999999999998 |
| - type: map_at_10 |
| value: 81.063 |
| - type: map_at_100 |
| value: 84.504 |
| - type: map_at_1000 |
| value: 84.552 |
| - type: map_at_3 |
| value: 56.897 |
| - type: map_at_5 |
| value: 70.073 |
| - type: mrr_at_1 |
| value: 92.087 |
| - type: mrr_at_10 |
| value: 94.132 |
| - type: mrr_at_100 |
| value: 94.19800000000001 |
| - type: mrr_at_1000 |
| value: 94.19999999999999 |
| - type: mrr_at_3 |
| value: 93.78999999999999 |
| - type: mrr_at_5 |
| value: 94.002 |
| - type: ndcg_at_1 |
| value: 92.087 |
| - type: ndcg_at_10 |
| value: 87.734 |
| - type: ndcg_at_100 |
| value: 90.736 |
| - type: ndcg_at_1000 |
| value: 91.184 |
| - type: ndcg_at_3 |
| value: 88.78 |
| - type: ndcg_at_5 |
| value: 87.676 |
| - type: precision_at_1 |
| value: 92.087 |
| - type: precision_at_10 |
| value: 43.46 |
| - type: precision_at_100 |
| value: 5.07 |
| - type: precision_at_1000 |
| value: 0.518 |
| - type: precision_at_3 |
| value: 77.49000000000001 |
| - type: precision_at_5 |
| value: 65.194 |
| - type: recall_at_1 |
| value: 28.666999999999998 |
| - type: recall_at_10 |
| value: 86.632 |
| - type: recall_at_100 |
| value: 96.646 |
| - type: recall_at_1000 |
| value: 98.917 |
| - type: recall_at_3 |
| value: 58.333999999999996 |
| - type: recall_at_5 |
| value: 72.974 |
| - task: |
| type: Classification |
| dataset: |
| type: C-MTEB/TNews-classification |
| name: MTEB TNews |
| config: default |
| split: validation |
| revision: 317f262bf1e6126357bbe89e875451e4b0938fe4 |
| metrics: |
| - type: accuracy |
| value: 52.971999999999994 |
| - type: f1 |
| value: 50.2898280984929 |
| - task: |
| type: Clustering |
| dataset: |
| type: C-MTEB/ThuNewsClusteringP2P |
| name: MTEB ThuNewsClusteringP2P |
| config: default |
| split: test |
| revision: 5798586b105c0434e4f0fe5e767abe619442cf93 |
| metrics: |
| - type: v_measure |
| value: 86.0797948663824 |
| - task: |
| type: Clustering |
| dataset: |
| type: C-MTEB/ThuNewsClusteringS2S |
| name: MTEB ThuNewsClusteringS2S |
| config: default |
| split: test |
| revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d |
| metrics: |
| - type: v_measure |
| value: 85.10759092255017 |
| - task: |
| type: Retrieval |
| dataset: |
| type: C-MTEB/VideoRetrieval |
| name: MTEB VideoRetrieval |
| config: default |
| split: dev |
| revision: 58c2597a5943a2ba48f4668c3b90d796283c5639 |
| metrics: |
| - type: map_at_1 |
| value: 65.60000000000001 |
| - type: map_at_10 |
| value: 74.773 |
| - type: map_at_100 |
| value: 75.128 |
| - type: map_at_1000 |
| value: 75.136 |
| - type: map_at_3 |
| value: 73.05 |
| - type: map_at_5 |
| value: 74.13499999999999 |
| - type: mrr_at_1 |
| value: 65.60000000000001 |
| - type: mrr_at_10 |
| value: 74.773 |
| - type: mrr_at_100 |
| value: 75.128 |
| - type: mrr_at_1000 |
| value: 75.136 |
| - type: mrr_at_3 |
| value: 73.05 |
| - type: mrr_at_5 |
| value: 74.13499999999999 |
| - type: ndcg_at_1 |
| value: 65.60000000000001 |
| - type: ndcg_at_10 |
| value: 78.84299999999999 |
| - type: ndcg_at_100 |
| value: 80.40899999999999 |
| - type: ndcg_at_1000 |
| value: 80.57 |
| - type: ndcg_at_3 |
| value: 75.40599999999999 |
| - type: ndcg_at_5 |
| value: 77.351 |
| - type: precision_at_1 |
| value: 65.60000000000001 |
| - type: precision_at_10 |
| value: 9.139999999999999 |
| - type: precision_at_100 |
| value: 0.984 |
| - type: precision_at_1000 |
| value: 0.1 |
| - type: precision_at_3 |
| value: 27.400000000000002 |
| - type: precision_at_5 |
| value: 17.380000000000003 |
| - type: recall_at_1 |
| value: 65.60000000000001 |
| - type: recall_at_10 |
| value: 91.4 |
| - type: recall_at_100 |
| value: 98.4 |
| - type: recall_at_1000 |
| value: 99.6 |
| - type: recall_at_3 |
| value: 82.19999999999999 |
| - type: recall_at_5 |
| value: 86.9 |
| - task: |
| type: Classification |
| dataset: |
| type: C-MTEB/waimai-classification |
| name: MTEB Waimai |
| config: default |
| split: test |
| revision: 339287def212450dcaa9df8c22bf93e9980c7023 |
| metrics: |
| - type: accuracy |
| value: 89.47 |
| - type: ap |
| value: 75.59561751845389 |
| - type: f1 |
| value: 87.95207751382563 |
| - dataset: |
| config: default |
| name: MTEB AlloProfClusteringP2P |
| revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b |
| split: test |
| type: lyon-nlp/alloprof |
| metrics: |
| - type: v_measure |
| value: 76.05592323841036 |
| task: |
| type: Clustering |
| - dataset: |
| config: default |
| name: MTEB AlloProfClusteringS2S |
| revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b |
| split: test |
| type: lyon-nlp/alloprof |
| metrics: |
| - type: v_measure |
| value: 64.51718058866508 |
| task: |
| type: Clustering |
| - dataset: |
| config: default |
| name: MTEB AlloprofReranking |
| revision: 666fdacebe0291776e86f29345663dfaf80a0db9 |
| split: test |
| type: lyon-nlp/mteb-fr-reranking-alloprof-s2p |
| metrics: |
| - type: map |
| value: 73.08278490943373 |
| - type: mrr |
| value: 74.66561454570449 |
| task: |
| type: Reranking |
| - dataset: |
| config: default |
| name: MTEB AlloprofRetrieval |
| revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b |
| split: test |
| type: lyon-nlp/alloprof |
| metrics: |
| - type: map_at_1 |
| value: 38.912 |
| - type: map_at_10 |
| value: 52.437999999999995 |
| - type: map_at_100 |
| value: 53.38 |
| - type: map_at_1000 |
| value: 53.427 |
| - type: map_at_3 |
| value: 48.879 |
| - type: map_at_5 |
| value: 50.934000000000005 |
| - type: mrr_at_1 |
| value: 44.085 |
| - type: mrr_at_10 |
| value: 55.337 |
| - type: mrr_at_100 |
| value: 56.016999999999996 |
| - type: mrr_at_1000 |
| value: 56.043 |
| - type: mrr_at_3 |
| value: 52.55499999999999 |
| - type: mrr_at_5 |
| value: 54.20399999999999 |
| - type: ndcg_at_1 |
| value: 44.085 |
| - type: ndcg_at_10 |
| value: 58.876 |
| - type: ndcg_at_100 |
| value: 62.714000000000006 |
| - type: ndcg_at_1000 |
| value: 63.721000000000004 |
| - type: ndcg_at_3 |
| value: 52.444 |
| - type: ndcg_at_5 |
| value: 55.692 |
| - type: precision_at_1 |
| value: 44.085 |
| - type: precision_at_10 |
| value: 9.21 |
| - type: precision_at_100 |
| value: 1.164 |
| - type: precision_at_1000 |
| value: 0.128 |
| - type: precision_at_3 |
| value: 23.043 |
| - type: precision_at_5 |
| value: 15.898000000000001 |
| - type: recall_at_1 |
| value: 38.912 |
| - type: recall_at_10 |
| value: 75.577 |
| - type: recall_at_100 |
| value: 92.038 |
| - type: recall_at_1000 |
| value: 99.325 |
| - type: recall_at_3 |
| value: 58.592 |
| - type: recall_at_5 |
| value: 66.235 |
| task: |
| type: Retrieval |
| - dataset: |
| config: fr |
| name: MTEB AmazonReviewsClassification (fr) |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| split: test |
| type: mteb/amazon_reviews_multi |
| metrics: |
| - type: accuracy |
| value: 55.532000000000004 |
| - type: f1 |
| value: 52.5783943471605 |
| task: |
| type: Classification |
| - dataset: |
| config: default |
| name: MTEB BSARDRetrieval |
| revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59 |
| split: test |
| type: maastrichtlawtech/bsard |
| metrics: |
| - type: map_at_1 |
| value: 8.108 |
| - type: map_at_10 |
| value: 14.710999999999999 |
| - type: map_at_100 |
| value: 15.891 |
| - type: map_at_1000 |
| value: 15.983 |
| - type: map_at_3 |
| value: 12.237 |
| - type: map_at_5 |
| value: 13.679 |
| - type: mrr_at_1 |
| value: 8.108 |
| - type: mrr_at_10 |
| value: 14.710999999999999 |
| - type: mrr_at_100 |
| value: 15.891 |
| - type: mrr_at_1000 |
| value: 15.983 |
| - type: mrr_at_3 |
| value: 12.237 |
| - type: mrr_at_5 |
| value: 13.679 |
| - type: ndcg_at_1 |
| value: 8.108 |
| - type: ndcg_at_10 |
| value: 18.796 |
| - type: ndcg_at_100 |
| value: 25.098 |
| - type: ndcg_at_1000 |
| value: 27.951999999999998 |
| - type: ndcg_at_3 |
| value: 13.712 |
| - type: ndcg_at_5 |
| value: 16.309 |
| - type: precision_at_1 |
| value: 8.108 |
| - type: precision_at_10 |
| value: 3.198 |
| - type: precision_at_100 |
| value: 0.626 |
| - type: precision_at_1000 |
| value: 0.086 |
| - type: precision_at_3 |
| value: 6.006 |
| - type: precision_at_5 |
| value: 4.865 |
| - type: recall_at_1 |
| value: 8.108 |
| - type: recall_at_10 |
| value: 31.982 |
| - type: recall_at_100 |
| value: 62.613 |
| - type: recall_at_1000 |
| value: 86.036 |
| - type: recall_at_3 |
| value: 18.018 |
| - type: recall_at_5 |
| value: 24.324 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB HALClusteringS2S |
| revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915 |
| split: test |
| type: lyon-nlp/clustering-hal-s2s |
| metrics: |
| - type: v_measure |
| value: 30.833269778867116 |
| task: |
| type: Clustering |
| - dataset: |
| config: default |
| name: MTEB MLSUMClusteringP2P |
| revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 |
| split: test |
| type: mlsum |
| metrics: |
| - type: v_measure |
| value: 50.0281928004713 |
| task: |
| type: Clustering |
| - dataset: |
| config: default |
| name: MTEB MLSUMClusteringS2S |
| revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 |
| split: test |
| type: mlsum |
| metrics: |
| - type: v_measure |
| value: 43.699961510636534 |
| task: |
| type: Clustering |
| - dataset: |
| config: fr |
| name: MTEB MTOPDomainClassification (fr) |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| split: test |
| type: mteb/mtop_domain |
| metrics: |
| - type: accuracy |
| value: 96.68963357344191 |
| - type: f1 |
| value: 96.45175170820961 |
| task: |
| type: Classification |
| - dataset: |
| config: fr |
| name: MTEB MTOPIntentClassification (fr) |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| split: test |
| type: mteb/mtop_intent |
| metrics: |
| - type: accuracy |
| value: 87.46946445349202 |
| - type: f1 |
| value: 65.79860440988624 |
| task: |
| type: Classification |
| - dataset: |
| config: fra |
| name: MTEB MasakhaNEWSClassification (fra) |
| revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 |
| split: test |
| type: masakhane/masakhanews |
| metrics: |
| - type: accuracy |
| value: 82.60663507109005 |
| - type: f1 |
| value: 77.20462646604777 |
| task: |
| type: Classification |
| - dataset: |
| config: fra |
| name: MTEB MasakhaNEWSClusteringP2P (fra) |
| revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 |
| split: test |
| type: masakhane/masakhanews |
| metrics: |
| - type: v_measure |
| value: 60.19311264967803 |
| task: |
| type: Clustering |
| - dataset: |
| config: fra |
| name: MTEB MasakhaNEWSClusteringS2S (fra) |
| revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 |
| split: test |
| type: masakhane/masakhanews |
| metrics: |
| - type: v_measure |
| value: 63.6235764409785 |
| task: |
| type: Clustering |
| - dataset: |
| config: fr |
| name: MTEB MassiveIntentClassification (fr) |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| split: test |
| type: mteb/amazon_massive_intent |
| metrics: |
| - type: accuracy |
| value: 81.65097511768661 |
| - type: f1 |
| value: 78.77796091490924 |
| task: |
| type: Classification |
| - dataset: |
| config: fr |
| name: MTEB MassiveScenarioClassification (fr) |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| split: test |
| type: mteb/amazon_massive_scenario |
| metrics: |
| - type: accuracy |
| value: 86.64425016812373 |
| - type: f1 |
| value: 85.4912728670017 |
| task: |
| type: Classification |
| - dataset: |
| config: fr |
| name: MTEB MintakaRetrieval (fr) |
| revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e |
| split: test |
| type: jinaai/mintakaqa |
| metrics: |
| - type: map_at_1 |
| value: 35.913000000000004 |
| - type: map_at_10 |
| value: 48.147 |
| - type: map_at_100 |
| value: 48.91 |
| - type: map_at_1000 |
| value: 48.949 |
| - type: map_at_3 |
| value: 45.269999999999996 |
| - type: map_at_5 |
| value: 47.115 |
| - type: mrr_at_1 |
| value: 35.913000000000004 |
| - type: mrr_at_10 |
| value: 48.147 |
| - type: mrr_at_100 |
| value: 48.91 |
| - type: mrr_at_1000 |
| value: 48.949 |
| - type: mrr_at_3 |
| value: 45.269999999999996 |
| - type: mrr_at_5 |
| value: 47.115 |
| - type: ndcg_at_1 |
| value: 35.913000000000004 |
| - type: ndcg_at_10 |
| value: 54.03 |
| - type: ndcg_at_100 |
| value: 57.839 |
| - type: ndcg_at_1000 |
| value: 58.925000000000004 |
| - type: ndcg_at_3 |
| value: 48.217999999999996 |
| - type: ndcg_at_5 |
| value: 51.56699999999999 |
| - type: precision_at_1 |
| value: 35.913000000000004 |
| - type: precision_at_10 |
| value: 7.244000000000001 |
| - type: precision_at_100 |
| value: 0.9039999999999999 |
| - type: precision_at_1000 |
| value: 0.099 |
| - type: precision_at_3 |
| value: 18.905 |
| - type: precision_at_5 |
| value: 12.981000000000002 |
| - type: recall_at_1 |
| value: 35.913000000000004 |
| - type: recall_at_10 |
| value: 72.441 |
| - type: recall_at_100 |
| value: 90.41799999999999 |
| - type: recall_at_1000 |
| value: 99.099 |
| - type: recall_at_3 |
| value: 56.716 |
| - type: recall_at_5 |
| value: 64.90599999999999 |
| task: |
| type: Retrieval |
| - dataset: |
| config: fr |
| name: MTEB OpusparcusPC (fr) |
| revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a |
| split: test |
| type: GEM/opusparcus |
| 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: |
| config: fr |
| name: MTEB PawsX (fr) |
| revision: 8a04d940a42cd40658986fdd8e3da561533a3646 |
| split: test |
| type: paws-x |
| metrics: |
| - type: cos_sim_accuracy |
| value: 75.25 |
| - type: cos_sim_ap |
| value: 80.86376001270014 |
| - type: cos_sim_f1 |
| value: 73.65945437441204 |
| - type: cos_sim_precision |
| value: 64.02289452166802 |
| - type: cos_sim_recall |
| value: 86.71096345514951 |
| - type: dot_accuracy |
| value: 75.25 |
| - type: dot_ap |
| value: 80.93686107633002 |
| - type: dot_f1 |
| value: 73.65945437441204 |
| - type: dot_precision |
| value: 64.02289452166802 |
| - type: dot_recall |
| value: 86.71096345514951 |
| - type: euclidean_accuracy |
| value: 75.25 |
| - type: euclidean_ap |
| value: 80.86379136218862 |
| - type: euclidean_f1 |
| value: 73.65945437441204 |
| - type: euclidean_precision |
| value: 64.02289452166802 |
| - type: euclidean_recall |
| value: 86.71096345514951 |
| - type: manhattan_accuracy |
| value: 75.3 |
| - type: manhattan_ap |
| value: 80.87826606097734 |
| - type: manhattan_f1 |
| value: 73.68421052631581 |
| - type: manhattan_precision |
| value: 64.0 |
| - type: manhattan_recall |
| value: 86.82170542635659 |
| - type: max_accuracy |
| value: 75.3 |
| - type: max_ap |
| value: 80.93686107633002 |
| - type: max_f1 |
| value: 73.68421052631581 |
| task: |
| type: PairClassification |
| - dataset: |
| config: default |
| name: MTEB SICKFr |
| revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a |
| split: test |
| type: Lajavaness/SICK-fr |
| metrics: |
| - type: cos_sim_pearson |
| value: 81.42349425981143 |
| - type: cos_sim_spearman |
| value: 78.90454327031226 |
| - type: euclidean_pearson |
| value: 78.39086497435166 |
| - type: euclidean_spearman |
| value: 78.9046133980509 |
| - type: manhattan_pearson |
| value: 78.63743094286502 |
| - type: manhattan_spearman |
| value: 79.12136348449269 |
| task: |
| type: STS |
| - dataset: |
| config: fr |
| name: MTEB STS22 (fr) |
| revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| split: test |
| type: mteb/sts22-crosslingual-sts |
| metrics: |
| - type: cos_sim_pearson |
| value: 81.452697919749 |
| - type: cos_sim_spearman |
| value: 82.58116836039301 |
| - type: euclidean_pearson |
| value: 81.04038478932786 |
| - type: euclidean_spearman |
| value: 82.58116836039301 |
| - type: manhattan_pearson |
| value: 81.37075396187771 |
| - type: manhattan_spearman |
| value: 82.73678231355368 |
| task: |
| type: STS |
| - dataset: |
| config: fr |
| name: MTEB STSBenchmarkMultilingualSTS (fr) |
| revision: 93d57ef91790589e3ce9c365164337a8a78b7632 |
| split: test |
| type: stsb_multi_mt |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.7419764013806 |
| - type: cos_sim_spearman |
| value: 85.46085808849622 |
| - type: euclidean_pearson |
| value: 83.70449639870063 |
| - type: euclidean_spearman |
| value: 85.46159013076233 |
| - type: manhattan_pearson |
| value: 83.95259510313929 |
| - type: manhattan_spearman |
| value: 85.8029724659458 |
| task: |
| type: STS |
| - dataset: |
| config: default |
| name: MTEB SummEvalFr |
| revision: b385812de6a9577b6f4d0f88c6a6e35395a94054 |
| split: test |
| type: lyon-nlp/summarization-summeval-fr-p2p |
| metrics: |
| - type: cos_sim_pearson |
| value: 32.61063271753325 |
| - type: cos_sim_spearman |
| value: 31.454589417353603 |
| - type: dot_pearson |
| value: 32.6106288643431 |
| - type: dot_spearman |
| value: 31.454589417353603 |
| task: |
| type: Summarization |
| - dataset: |
| config: default |
| name: MTEB SyntecReranking |
| revision: b205c5084a0934ce8af14338bf03feb19499c84d |
| split: test |
| type: lyon-nlp/mteb-fr-reranking-syntec-s2p |
| metrics: |
| - type: map |
| value: 84.31666666666666 |
| - type: mrr |
| value: 84.31666666666666 |
| task: |
| type: Reranking |
| - dataset: |
| config: default |
| name: MTEB SyntecRetrieval |
| revision: 77f7e271bf4a92b24fce5119f3486b583ca016ff |
| split: test |
| type: lyon-nlp/mteb-fr-retrieval-syntec-s2p |
| metrics: |
| - type: map_at_1 |
| value: 63.0 |
| - type: map_at_10 |
| value: 73.471 |
| - type: map_at_100 |
| value: 73.87 |
| - type: map_at_1000 |
| value: 73.87 |
| - type: map_at_3 |
| value: 70.5 |
| - type: map_at_5 |
| value: 73.05 |
| - type: mrr_at_1 |
| value: 63.0 |
| - type: mrr_at_10 |
| value: 73.471 |
| - type: mrr_at_100 |
| value: 73.87 |
| - type: mrr_at_1000 |
| value: 73.87 |
| - type: mrr_at_3 |
| value: 70.5 |
| - type: mrr_at_5 |
| value: 73.05 |
| - type: ndcg_at_1 |
| value: 63.0 |
| - type: ndcg_at_10 |
| value: 78.255 |
| - type: ndcg_at_100 |
| value: 79.88 |
| - type: ndcg_at_1000 |
| value: 79.88 |
| - type: ndcg_at_3 |
| value: 72.702 |
| - type: ndcg_at_5 |
| value: 77.264 |
| - type: precision_at_1 |
| value: 63.0 |
| - type: precision_at_10 |
| value: 9.3 |
| - type: precision_at_100 |
| value: 1.0 |
| - type: precision_at_1000 |
| value: 0.1 |
| - type: precision_at_3 |
| value: 26.333000000000002 |
| - type: precision_at_5 |
| value: 18.0 |
| - type: recall_at_1 |
| value: 63.0 |
| - type: recall_at_10 |
| value: 93.0 |
| - type: recall_at_100 |
| value: 100.0 |
| - type: recall_at_1000 |
| value: 100.0 |
| - type: recall_at_3 |
| value: 79.0 |
| - type: recall_at_5 |
| value: 90.0 |
| task: |
| type: Retrieval |
| - dataset: |
| config: fr |
| name: MTEB XPQARetrieval (fr) |
| revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f |
| split: test |
| type: jinaai/xpqa |
| metrics: |
| - type: map_at_1 |
| value: 40.338 |
| - type: map_at_10 |
| value: 61.927 |
| - type: map_at_100 |
| value: 63.361999999999995 |
| - type: map_at_1000 |
| value: 63.405 |
| - type: map_at_3 |
| value: 55.479 |
| - type: map_at_5 |
| value: 59.732 |
| - type: mrr_at_1 |
| value: 63.551 |
| - type: mrr_at_10 |
| value: 71.006 |
| - type: mrr_at_100 |
| value: 71.501 |
| - type: mrr_at_1000 |
| value: 71.509 |
| - type: mrr_at_3 |
| value: 69.07 |
| - type: mrr_at_5 |
| value: 70.165 |
| - type: ndcg_at_1 |
| value: 63.551 |
| - type: ndcg_at_10 |
| value: 68.297 |
| - type: ndcg_at_100 |
| value: 73.13199999999999 |
| - type: ndcg_at_1000 |
| value: 73.751 |
| - type: ndcg_at_3 |
| value: 62.999 |
| - type: ndcg_at_5 |
| value: 64.89 |
| - type: precision_at_1 |
| value: 63.551 |
| - type: precision_at_10 |
| value: 15.661 |
| - type: precision_at_100 |
| value: 1.9789999999999999 |
| - type: precision_at_1000 |
| value: 0.207 |
| - type: precision_at_3 |
| value: 38.273 |
| - type: precision_at_5 |
| value: 27.61 |
| - type: recall_at_1 |
| value: 40.338 |
| - type: recall_at_10 |
| value: 77.267 |
| - type: recall_at_100 |
| value: 95.892 |
| - type: recall_at_1000 |
| value: 99.75500000000001 |
| - type: recall_at_3 |
| value: 60.36 |
| - type: recall_at_5 |
| value: 68.825 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB 8TagsClustering |
| revision: None |
| split: test |
| type: PL-MTEB/8tags-clustering |
| metrics: |
| - type: v_measure |
| value: 51.36126303874126 |
| task: |
| type: Clustering |
| - dataset: |
| config: default |
| name: MTEB AllegroReviews |
| revision: None |
| split: test |
| type: PL-MTEB/allegro-reviews |
| metrics: |
| - type: accuracy |
| value: 67.13717693836979 |
| - type: f1 |
| value: 57.27609848003782 |
| task: |
| type: Classification |
| - dataset: |
| config: default |
| name: MTEB ArguAna-PL |
| revision: 63fc86750af76253e8c760fc9e534bbf24d260a2 |
| split: test |
| type: clarin-knext/arguana-pl |
| metrics: |
| - type: map_at_1 |
| value: 35.276999999999994 |
| - type: map_at_10 |
| value: 51.086 |
| - type: map_at_100 |
| value: 51.788000000000004 |
| - type: map_at_1000 |
| value: 51.791 |
| - type: map_at_3 |
| value: 46.147 |
| - type: map_at_5 |
| value: 49.078 |
| - type: mrr_at_1 |
| value: 35.917 |
| - type: mrr_at_10 |
| value: 51.315999999999995 |
| - type: mrr_at_100 |
| value: 52.018 |
| - type: mrr_at_1000 |
| value: 52.022 |
| - type: mrr_at_3 |
| value: 46.349000000000004 |
| - type: mrr_at_5 |
| value: 49.297000000000004 |
| - type: ndcg_at_1 |
| value: 35.276999999999994 |
| - type: ndcg_at_10 |
| value: 59.870999999999995 |
| - type: ndcg_at_100 |
| value: 62.590999999999994 |
| - type: ndcg_at_1000 |
| value: 62.661 |
| - type: ndcg_at_3 |
| value: 49.745 |
| - type: ndcg_at_5 |
| value: 55.067 |
| - type: precision_at_1 |
| value: 35.276999999999994 |
| - type: precision_at_10 |
| value: 8.791 |
| - type: precision_at_100 |
| value: 0.991 |
| - type: precision_at_1000 |
| value: 0.1 |
| - type: precision_at_3 |
| value: 20.057 |
| - type: precision_at_5 |
| value: 14.637 |
| - type: recall_at_1 |
| value: 35.276999999999994 |
| - type: recall_at_10 |
| value: 87.909 |
| - type: recall_at_100 |
| value: 99.14699999999999 |
| - type: recall_at_1000 |
| value: 99.644 |
| - type: recall_at_3 |
| value: 60.171 |
| - type: recall_at_5 |
| value: 73.18599999999999 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB CBD |
| revision: None |
| split: test |
| type: PL-MTEB/cbd |
| metrics: |
| - type: accuracy |
| value: 78.03000000000002 |
| - type: ap |
| value: 29.12548553897622 |
| - type: f1 |
| value: 66.54857118886073 |
| task: |
| type: Classification |
| - dataset: |
| config: default |
| name: MTEB CDSC-E |
| revision: None |
| split: test |
| type: PL-MTEB/cdsce-pairclassification |
| metrics: |
| - type: cos_sim_accuracy |
| value: 89.0 |
| - type: cos_sim_ap |
| value: 76.75437826834582 |
| - type: cos_sim_f1 |
| value: 66.4850136239782 |
| - type: cos_sim_precision |
| value: 68.92655367231639 |
| - type: cos_sim_recall |
| value: 64.21052631578948 |
| - type: dot_accuracy |
| value: 89.0 |
| - type: dot_ap |
| value: 76.75437826834582 |
| - type: dot_f1 |
| value: 66.4850136239782 |
| - type: dot_precision |
| value: 68.92655367231639 |
| - type: dot_recall |
| value: 64.21052631578948 |
| - type: euclidean_accuracy |
| value: 89.0 |
| - type: euclidean_ap |
| value: 76.75437826834582 |
| - type: euclidean_f1 |
| value: 66.4850136239782 |
| - type: euclidean_precision |
| value: 68.92655367231639 |
| - type: euclidean_recall |
| value: 64.21052631578948 |
| - type: manhattan_accuracy |
| value: 89.0 |
| - type: manhattan_ap |
| value: 76.66074220647083 |
| - type: manhattan_f1 |
| value: 66.47058823529412 |
| - type: manhattan_precision |
| value: 75.33333333333333 |
| - type: manhattan_recall |
| value: 59.473684210526315 |
| - type: max_accuracy |
| value: 89.0 |
| - type: max_ap |
| value: 76.75437826834582 |
| - type: max_f1 |
| value: 66.4850136239782 |
| task: |
| type: PairClassification |
| - dataset: |
| config: default |
| name: MTEB CDSC-R |
| revision: None |
| split: test |
| type: PL-MTEB/cdscr-sts |
| metrics: |
| - type: cos_sim_pearson |
| value: 93.12903172428328 |
| - type: cos_sim_spearman |
| value: 92.66381487060741 |
| - type: euclidean_pearson |
| value: 90.37278396708922 |
| - type: euclidean_spearman |
| value: 92.66381487060741 |
| - type: manhattan_pearson |
| value: 90.32503296540962 |
| - type: manhattan_spearman |
| value: 92.6902938354313 |
| task: |
| type: STS |
| - dataset: |
| config: default |
| name: MTEB DBPedia-PL |
| revision: 76afe41d9af165cc40999fcaa92312b8b012064a |
| split: test |
| type: clarin-knext/dbpedia-pl |
| metrics: |
| - type: map_at_1 |
| value: 8.83 |
| - type: map_at_10 |
| value: 18.326 |
| - type: map_at_100 |
| value: 26.496 |
| - type: map_at_1000 |
| value: 28.455000000000002 |
| - type: map_at_3 |
| value: 12.933 |
| - type: map_at_5 |
| value: 15.168000000000001 |
| - type: mrr_at_1 |
| value: 66.0 |
| - type: mrr_at_10 |
| value: 72.76700000000001 |
| - type: mrr_at_100 |
| value: 73.203 |
| - type: mrr_at_1000 |
| value: 73.219 |
| - type: mrr_at_3 |
| value: 71.458 |
| - type: mrr_at_5 |
| value: 72.246 |
| - type: ndcg_at_1 |
| value: 55.375 |
| - type: ndcg_at_10 |
| value: 41.3 |
| - type: ndcg_at_100 |
| value: 45.891 |
| - type: ndcg_at_1000 |
| value: 52.905 |
| - type: ndcg_at_3 |
| value: 46.472 |
| - type: ndcg_at_5 |
| value: 43.734 |
| - type: precision_at_1 |
| value: 66.0 |
| - type: precision_at_10 |
| value: 33.074999999999996 |
| - type: precision_at_100 |
| value: 11.094999999999999 |
| - type: precision_at_1000 |
| value: 2.374 |
| - type: precision_at_3 |
| value: 48.583 |
| - type: precision_at_5 |
| value: 42.0 |
| - type: recall_at_1 |
| value: 8.83 |
| - type: recall_at_10 |
| value: 22.587 |
| - type: recall_at_100 |
| value: 50.61600000000001 |
| - type: recall_at_1000 |
| value: 73.559 |
| - type: recall_at_3 |
| value: 13.688 |
| - type: recall_at_5 |
| value: 16.855 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB FiQA-PL |
| revision: 2e535829717f8bf9dc829b7f911cc5bbd4e6608e |
| split: test |
| type: clarin-knext/fiqa-pl |
| metrics: |
| - type: map_at_1 |
| value: 20.587 |
| - type: map_at_10 |
| value: 33.095 |
| - type: map_at_100 |
| value: 35.24 |
| - type: map_at_1000 |
| value: 35.429 |
| - type: map_at_3 |
| value: 28.626 |
| - type: map_at_5 |
| value: 31.136999999999997 |
| - type: mrr_at_1 |
| value: 40.586 |
| - type: mrr_at_10 |
| value: 49.033 |
| - type: mrr_at_100 |
| value: 49.952999999999996 |
| - type: mrr_at_1000 |
| value: 49.992 |
| - type: mrr_at_3 |
| value: 46.553 |
| - type: mrr_at_5 |
| value: 48.035 |
| - type: ndcg_at_1 |
| value: 40.586 |
| - type: ndcg_at_10 |
| value: 41.046 |
| - type: ndcg_at_100 |
| value: 48.586 |
| - type: ndcg_at_1000 |
| value: 51.634 |
| - type: ndcg_at_3 |
| value: 36.773 |
| - type: ndcg_at_5 |
| value: 38.389 |
| - type: precision_at_1 |
| value: 40.586 |
| - type: precision_at_10 |
| value: 11.466 |
| - type: precision_at_100 |
| value: 1.909 |
| - type: precision_at_1000 |
| value: 0.245 |
| - type: precision_at_3 |
| value: 24.434 |
| - type: precision_at_5 |
| value: 18.426000000000002 |
| - type: recall_at_1 |
| value: 20.587 |
| - type: recall_at_10 |
| value: 47.986000000000004 |
| - type: recall_at_100 |
| value: 75.761 |
| - type: recall_at_1000 |
| value: 94.065 |
| - type: recall_at_3 |
| value: 33.339 |
| - type: recall_at_5 |
| value: 39.765 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB HotpotQA-PL |
| revision: a0bd479ac97b4ccb5bd6ce320c415d0bb4beb907 |
| split: test |
| type: clarin-knext/hotpotqa-pl |
| metrics: |
| - type: map_at_1 |
| value: 40.878 |
| - type: map_at_10 |
| value: 58.775999999999996 |
| - type: map_at_100 |
| value: 59.632 |
| - type: map_at_1000 |
| value: 59.707 |
| - type: map_at_3 |
| value: 56.074 |
| - type: map_at_5 |
| value: 57.629 |
| - type: mrr_at_1 |
| value: 81.756 |
| - type: mrr_at_10 |
| value: 86.117 |
| - type: mrr_at_100 |
| value: 86.299 |
| - type: mrr_at_1000 |
| value: 86.30600000000001 |
| - type: mrr_at_3 |
| value: 85.345 |
| - type: mrr_at_5 |
| value: 85.832 |
| - type: ndcg_at_1 |
| value: 81.756 |
| - type: ndcg_at_10 |
| value: 67.608 |
| - type: ndcg_at_100 |
| value: 70.575 |
| - type: ndcg_at_1000 |
| value: 71.99600000000001 |
| - type: ndcg_at_3 |
| value: 63.723 |
| - type: ndcg_at_5 |
| value: 65.70700000000001 |
| - type: precision_at_1 |
| value: 81.756 |
| - type: precision_at_10 |
| value: 13.619 |
| - type: precision_at_100 |
| value: 1.5939999999999999 |
| - type: precision_at_1000 |
| value: 0.178 |
| - type: precision_at_3 |
| value: 39.604 |
| - type: precision_at_5 |
| value: 25.332 |
| - type: recall_at_1 |
| value: 40.878 |
| - type: recall_at_10 |
| value: 68.096 |
| - type: recall_at_100 |
| value: 79.696 |
| - type: recall_at_1000 |
| value: 89.082 |
| - type: recall_at_3 |
| value: 59.406000000000006 |
| - type: recall_at_5 |
| value: 63.329 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB MSMARCO-PL |
| revision: 8634c07806d5cce3a6138e260e59b81760a0a640 |
| split: test |
| type: clarin-knext/msmarco-pl |
| metrics: |
| - type: map_at_1 |
| value: 2.1839999999999997 |
| - type: map_at_10 |
| value: 11.346 |
| - type: map_at_100 |
| value: 30.325000000000003 |
| - type: map_at_1000 |
| value: 37.806 |
| - type: map_at_3 |
| value: 4.842 |
| - type: map_at_5 |
| value: 6.891 |
| - type: mrr_at_1 |
| value: 86.047 |
| - type: mrr_at_10 |
| value: 89.14699999999999 |
| - type: mrr_at_100 |
| value: 89.46600000000001 |
| - type: mrr_at_1000 |
| value: 89.46600000000001 |
| - type: mrr_at_3 |
| value: 89.14699999999999 |
| - type: mrr_at_5 |
| value: 89.14699999999999 |
| - type: ndcg_at_1 |
| value: 67.829 |
| - type: ndcg_at_10 |
| value: 62.222 |
| - type: ndcg_at_100 |
| value: 55.337 |
| - type: ndcg_at_1000 |
| value: 64.076 |
| - type: ndcg_at_3 |
| value: 68.12700000000001 |
| - type: ndcg_at_5 |
| value: 64.987 |
| - type: precision_at_1 |
| value: 86.047 |
| - type: precision_at_10 |
| value: 69.535 |
| - type: precision_at_100 |
| value: 32.93 |
| - type: precision_at_1000 |
| value: 6.6049999999999995 |
| - type: precision_at_3 |
| value: 79.845 |
| - type: precision_at_5 |
| value: 75.349 |
| - type: recall_at_1 |
| value: 2.1839999999999997 |
| - type: recall_at_10 |
| value: 12.866 |
| - type: recall_at_100 |
| value: 43.505 |
| - type: recall_at_1000 |
| value: 72.366 |
| - type: recall_at_3 |
| value: 4.947 |
| - type: recall_at_5 |
| value: 7.192 |
| task: |
| type: Retrieval |
| - dataset: |
| config: pl |
| name: MTEB MassiveIntentClassification (pl) |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| split: test |
| type: mteb/amazon_massive_intent |
| metrics: |
| - type: accuracy |
| value: 80.75319435104238 |
| - type: f1 |
| value: 77.58961444860606 |
| task: |
| type: Classification |
| - dataset: |
| config: pl |
| name: MTEB MassiveScenarioClassification (pl) |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| split: test |
| type: mteb/amazon_massive_scenario |
| metrics: |
| - type: accuracy |
| value: 85.54472091459313 |
| - type: f1 |
| value: 84.29498563572106 |
| task: |
| type: Classification |
| - dataset: |
| config: default |
| name: MTEB NFCorpus-PL |
| revision: 9a6f9567fda928260afed2de480d79c98bf0bec0 |
| split: test |
| type: clarin-knext/nfcorpus-pl |
| metrics: |
| - type: map_at_1 |
| value: 4.367 |
| - type: map_at_10 |
| value: 10.38 |
| - type: map_at_100 |
| value: 13.516 |
| - type: map_at_1000 |
| value: 14.982000000000001 |
| - type: map_at_3 |
| value: 7.367 |
| - type: map_at_5 |
| value: 8.59 |
| - type: mrr_at_1 |
| value: 41.486000000000004 |
| - type: mrr_at_10 |
| value: 48.886 |
| - type: mrr_at_100 |
| value: 49.657000000000004 |
| - type: mrr_at_1000 |
| value: 49.713 |
| - type: mrr_at_3 |
| value: 46.904 |
| - type: mrr_at_5 |
| value: 48.065000000000005 |
| - type: ndcg_at_1 |
| value: 40.402 |
| - type: ndcg_at_10 |
| value: 30.885 |
| - type: ndcg_at_100 |
| value: 28.393 |
| - type: ndcg_at_1000 |
| value: 37.428 |
| - type: ndcg_at_3 |
| value: 35.394999999999996 |
| - type: ndcg_at_5 |
| value: 33.391999999999996 |
| - type: precision_at_1 |
| value: 41.486000000000004 |
| - type: precision_at_10 |
| value: 23.437 |
| - type: precision_at_100 |
| value: 7.638 |
| - type: precision_at_1000 |
| value: 2.0389999999999997 |
| - type: precision_at_3 |
| value: 32.817 |
| - type: precision_at_5 |
| value: 28.915999999999997 |
| - type: recall_at_1 |
| value: 4.367 |
| - type: recall_at_10 |
| value: 14.655000000000001 |
| - type: recall_at_100 |
| value: 29.665999999999997 |
| - type: recall_at_1000 |
| value: 62.073 |
| - type: recall_at_3 |
| value: 8.51 |
| - type: recall_at_5 |
| value: 10.689 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB NQ-PL |
| revision: f171245712cf85dd4700b06bef18001578d0ca8d |
| split: test |
| type: clarin-knext/nq-pl |
| metrics: |
| - type: map_at_1 |
| value: 28.616000000000003 |
| - type: map_at_10 |
| value: 41.626000000000005 |
| - type: map_at_100 |
| value: 42.689 |
| - type: map_at_1000 |
| value: 42.733 |
| - type: map_at_3 |
| value: 37.729 |
| - type: map_at_5 |
| value: 39.879999999999995 |
| - type: mrr_at_1 |
| value: 32.068000000000005 |
| - type: mrr_at_10 |
| value: 44.029 |
| - type: mrr_at_100 |
| value: 44.87 |
| - type: mrr_at_1000 |
| value: 44.901 |
| - type: mrr_at_3 |
| value: 40.687 |
| - type: mrr_at_5 |
| value: 42.625 |
| - type: ndcg_at_1 |
| value: 32.068000000000005 |
| - type: ndcg_at_10 |
| value: 48.449999999999996 |
| - type: ndcg_at_100 |
| value: 53.13 |
| - type: ndcg_at_1000 |
| value: 54.186 |
| - type: ndcg_at_3 |
| value: 40.983999999999995 |
| - type: ndcg_at_5 |
| value: 44.628 |
| - type: precision_at_1 |
| value: 32.068000000000005 |
| - type: precision_at_10 |
| value: 7.9750000000000005 |
| - type: precision_at_100 |
| value: 1.061 |
| - type: precision_at_1000 |
| value: 0.116 |
| - type: precision_at_3 |
| value: 18.404999999999998 |
| - type: precision_at_5 |
| value: 13.111 |
| - type: recall_at_1 |
| value: 28.616000000000003 |
| - type: recall_at_10 |
| value: 66.956 |
| - type: recall_at_100 |
| value: 87.657 |
| - type: recall_at_1000 |
| value: 95.548 |
| - type: recall_at_3 |
| value: 47.453 |
| - type: recall_at_5 |
| value: 55.87800000000001 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB PAC |
| revision: None |
| split: test |
| type: laugustyniak/abusive-clauses-pl |
| metrics: |
| - type: accuracy |
| value: 69.04141326382856 |
| - type: ap |
| value: 77.47589122111044 |
| - type: f1 |
| value: 66.6332277374775 |
| task: |
| type: Classification |
| - dataset: |
| config: default |
| name: MTEB PPC |
| revision: None |
| split: test |
| type: PL-MTEB/ppc-pairclassification |
| metrics: |
| - type: cos_sim_accuracy |
| value: 86.4 |
| - type: cos_sim_ap |
| value: 94.1044939667201 |
| - type: cos_sim_f1 |
| value: 88.78048780487805 |
| - type: cos_sim_precision |
| value: 87.22044728434504 |
| - type: cos_sim_recall |
| value: 90.39735099337747 |
| - type: dot_accuracy |
| value: 86.4 |
| - type: dot_ap |
| value: 94.1044939667201 |
| - type: dot_f1 |
| value: 88.78048780487805 |
| - type: dot_precision |
| value: 87.22044728434504 |
| - type: dot_recall |
| value: 90.39735099337747 |
| - type: euclidean_accuracy |
| value: 86.4 |
| - type: euclidean_ap |
| value: 94.1044939667201 |
| - type: euclidean_f1 |
| value: 88.78048780487805 |
| - type: euclidean_precision |
| value: 87.22044728434504 |
| - type: euclidean_recall |
| value: 90.39735099337747 |
| - type: manhattan_accuracy |
| value: 86.4 |
| - type: manhattan_ap |
| value: 94.11438365697387 |
| - type: manhattan_f1 |
| value: 88.77968877968877 |
| - type: manhattan_precision |
| value: 87.84440842787681 |
| - type: manhattan_recall |
| value: 89.73509933774835 |
| - type: max_accuracy |
| value: 86.4 |
| - type: max_ap |
| value: 94.11438365697387 |
| - type: max_f1 |
| value: 88.78048780487805 |
| task: |
| type: PairClassification |
| - dataset: |
| config: default |
| name: MTEB PSC |
| revision: None |
| split: test |
| type: PL-MTEB/psc-pairclassification |
| metrics: |
| - type: cos_sim_accuracy |
| value: 97.86641929499072 |
| - type: cos_sim_ap |
| value: 99.36904211868182 |
| - type: cos_sim_f1 |
| value: 96.56203288490283 |
| - type: cos_sim_precision |
| value: 94.72140762463343 |
| - type: cos_sim_recall |
| value: 98.47560975609755 |
| - type: dot_accuracy |
| value: 97.86641929499072 |
| - type: dot_ap |
| value: 99.36904211868183 |
| - type: dot_f1 |
| value: 96.56203288490283 |
| - type: dot_precision |
| value: 94.72140762463343 |
| - type: dot_recall |
| value: 98.47560975609755 |
| - type: euclidean_accuracy |
| value: 97.86641929499072 |
| - type: euclidean_ap |
| value: 99.36904211868183 |
| - type: euclidean_f1 |
| value: 96.56203288490283 |
| - type: euclidean_precision |
| value: 94.72140762463343 |
| - type: euclidean_recall |
| value: 98.47560975609755 |
| - type: manhattan_accuracy |
| value: 98.14471243042672 |
| - type: manhattan_ap |
| value: 99.43359540492416 |
| - type: manhattan_f1 |
| value: 96.98795180722892 |
| - type: manhattan_precision |
| value: 95.83333333333334 |
| - type: manhattan_recall |
| value: 98.17073170731707 |
| - type: max_accuracy |
| value: 98.14471243042672 |
| - type: max_ap |
| value: 99.43359540492416 |
| - type: max_f1 |
| value: 96.98795180722892 |
| task: |
| type: PairClassification |
| - dataset: |
| config: default |
| name: MTEB PolEmo2.0-IN |
| revision: None |
| split: test |
| type: PL-MTEB/polemo2_in |
| metrics: |
| - type: accuracy |
| value: 89.39058171745152 |
| - type: f1 |
| value: 86.8552093529568 |
| task: |
| type: Classification |
| - dataset: |
| config: default |
| name: MTEB PolEmo2.0-OUT |
| revision: None |
| split: test |
| type: PL-MTEB/polemo2_out |
| metrics: |
| - type: accuracy |
| value: 74.97975708502024 |
| - type: f1 |
| value: 58.73081628832407 |
| task: |
| type: Classification |
| - dataset: |
| config: default |
| name: MTEB Quora-PL |
| revision: 0be27e93455051e531182b85e85e425aba12e9d4 |
| split: test |
| type: clarin-knext/quora-pl |
| metrics: |
| - type: map_at_1 |
| value: 64.917 |
| - type: map_at_10 |
| value: 78.74600000000001 |
| - type: map_at_100 |
| value: 79.501 |
| - type: map_at_1000 |
| value: 79.524 |
| - type: map_at_3 |
| value: 75.549 |
| - type: map_at_5 |
| value: 77.495 |
| - type: mrr_at_1 |
| value: 74.9 |
| - type: mrr_at_10 |
| value: 82.112 |
| - type: mrr_at_100 |
| value: 82.314 |
| - type: mrr_at_1000 |
| value: 82.317 |
| - type: mrr_at_3 |
| value: 80.745 |
| - type: mrr_at_5 |
| value: 81.607 |
| - type: ndcg_at_1 |
| value: 74.83999999999999 |
| - type: ndcg_at_10 |
| value: 83.214 |
| - type: ndcg_at_100 |
| value: 84.997 |
| - type: ndcg_at_1000 |
| value: 85.207 |
| - type: ndcg_at_3 |
| value: 79.547 |
| - type: ndcg_at_5 |
| value: 81.46600000000001 |
| - type: precision_at_1 |
| value: 74.83999999999999 |
| - type: precision_at_10 |
| value: 12.822 |
| - type: precision_at_100 |
| value: 1.506 |
| - type: precision_at_1000 |
| value: 0.156 |
| - type: precision_at_3 |
| value: 34.903 |
| - type: precision_at_5 |
| value: 23.16 |
| - type: recall_at_1 |
| value: 64.917 |
| - type: recall_at_10 |
| value: 92.27199999999999 |
| - type: recall_at_100 |
| value: 98.715 |
| - type: recall_at_1000 |
| value: 99.854 |
| - type: recall_at_3 |
| value: 82.04599999999999 |
| - type: recall_at_5 |
| value: 87.2 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB SCIDOCS-PL |
| revision: 45452b03f05560207ef19149545f168e596c9337 |
| split: test |
| type: clarin-knext/scidocs-pl |
| metrics: |
| - type: map_at_1 |
| value: 3.51 |
| - type: map_at_10 |
| value: 9.046999999999999 |
| - type: map_at_100 |
| value: 10.823 |
| - type: map_at_1000 |
| value: 11.144 |
| - type: map_at_3 |
| value: 6.257 |
| - type: map_at_5 |
| value: 7.648000000000001 |
| - type: mrr_at_1 |
| value: 17.299999999999997 |
| - type: mrr_at_10 |
| value: 27.419 |
| - type: mrr_at_100 |
| value: 28.618 |
| - type: mrr_at_1000 |
| value: 28.685 |
| - type: mrr_at_3 |
| value: 23.817 |
| - type: mrr_at_5 |
| value: 25.927 |
| - type: ndcg_at_1 |
| value: 17.299999999999997 |
| - type: ndcg_at_10 |
| value: 16.084 |
| - type: ndcg_at_100 |
| value: 23.729 |
| - type: ndcg_at_1000 |
| value: 29.476999999999997 |
| - type: ndcg_at_3 |
| value: 14.327000000000002 |
| - type: ndcg_at_5 |
| value: 13.017999999999999 |
| - type: precision_at_1 |
| value: 17.299999999999997 |
| - type: precision_at_10 |
| value: 8.63 |
| - type: precision_at_100 |
| value: 1.981 |
| - type: precision_at_1000 |
| value: 0.336 |
| - type: precision_at_3 |
| value: 13.4 |
| - type: precision_at_5 |
| value: 11.700000000000001 |
| - type: recall_at_1 |
| value: 3.51 |
| - type: recall_at_10 |
| value: 17.518 |
| - type: recall_at_100 |
| value: 40.275 |
| - type: recall_at_1000 |
| value: 68.203 |
| - type: recall_at_3 |
| value: 8.155 |
| - type: recall_at_5 |
| value: 11.875 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB SICK-E-PL |
| revision: None |
| split: test |
| type: PL-MTEB/sicke-pl-pairclassification |
| metrics: |
| - type: cos_sim_accuracy |
| value: 86.30248675091724 |
| - type: cos_sim_ap |
| value: 83.6756734006714 |
| - type: cos_sim_f1 |
| value: 74.97367497367497 |
| - type: cos_sim_precision |
| value: 73.91003460207612 |
| - type: cos_sim_recall |
| value: 76.06837606837607 |
| - type: dot_accuracy |
| value: 86.30248675091724 |
| - type: dot_ap |
| value: 83.6756734006714 |
| - type: dot_f1 |
| value: 74.97367497367497 |
| - type: dot_precision |
| value: 73.91003460207612 |
| - type: dot_recall |
| value: 76.06837606837607 |
| - type: euclidean_accuracy |
| value: 86.30248675091724 |
| - type: euclidean_ap |
| value: 83.67566984333091 |
| - type: euclidean_f1 |
| value: 74.97367497367497 |
| - type: euclidean_precision |
| value: 73.91003460207612 |
| - type: euclidean_recall |
| value: 76.06837606837607 |
| - type: manhattan_accuracy |
| value: 86.28210354667753 |
| - type: manhattan_ap |
| value: 83.64216119130171 |
| - type: manhattan_f1 |
| value: 74.92152075340078 |
| - type: manhattan_precision |
| value: 73.4107997265892 |
| - type: manhattan_recall |
| value: 76.49572649572649 |
| - type: max_accuracy |
| value: 86.30248675091724 |
| - type: max_ap |
| value: 83.6756734006714 |
| - type: max_f1 |
| value: 74.97367497367497 |
| task: |
| type: PairClassification |
| - dataset: |
| config: default |
| name: MTEB SICK-R-PL |
| revision: None |
| split: test |
| type: PL-MTEB/sickr-pl-sts |
| metrics: |
| - type: cos_sim_pearson |
| value: 82.23295940859121 |
| - type: cos_sim_spearman |
| value: 78.89329160768719 |
| - type: euclidean_pearson |
| value: 79.56019107076818 |
| - type: euclidean_spearman |
| value: 78.89330209904084 |
| - type: manhattan_pearson |
| value: 79.76098513973719 |
| - type: manhattan_spearman |
| value: 79.05490162570123 |
| task: |
| type: STS |
| - dataset: |
| config: pl |
| name: MTEB STS22 (pl) |
| revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| split: test |
| type: mteb/sts22-crosslingual-sts |
| metrics: |
| - type: cos_sim_pearson |
| value: 37.732606308062486 |
| - type: cos_sim_spearman |
| value: 41.01645667030284 |
| - type: euclidean_pearson |
| value: 26.61722556367085 |
| - type: euclidean_spearman |
| value: 41.01645667030284 |
| - type: manhattan_pearson |
| value: 26.60917378970807 |
| - type: manhattan_spearman |
| value: 41.51335727617614 |
| task: |
| type: STS |
| - dataset: |
| config: default |
| name: MTEB SciFact-PL |
| revision: 47932a35f045ef8ed01ba82bf9ff67f6e109207e |
| split: test |
| type: clarin-knext/scifact-pl |
| metrics: |
| - type: map_at_1 |
| value: 54.31700000000001 |
| - type: map_at_10 |
| value: 65.564 |
| - type: map_at_100 |
| value: 66.062 |
| - type: map_at_1000 |
| value: 66.08699999999999 |
| - type: map_at_3 |
| value: 62.592999999999996 |
| - type: map_at_5 |
| value: 63.888 |
| - type: mrr_at_1 |
| value: 56.99999999999999 |
| - type: mrr_at_10 |
| value: 66.412 |
| - type: mrr_at_100 |
| value: 66.85900000000001 |
| - type: mrr_at_1000 |
| value: 66.88 |
| - type: mrr_at_3 |
| value: 64.22200000000001 |
| - type: mrr_at_5 |
| value: 65.206 |
| - type: ndcg_at_1 |
| value: 56.99999999999999 |
| - type: ndcg_at_10 |
| value: 70.577 |
| - type: ndcg_at_100 |
| value: 72.879 |
| - type: ndcg_at_1000 |
| value: 73.45 |
| - type: ndcg_at_3 |
| value: 65.5 |
| - type: ndcg_at_5 |
| value: 67.278 |
| - type: precision_at_1 |
| value: 56.99999999999999 |
| - type: precision_at_10 |
| value: 9.667 |
| - type: precision_at_100 |
| value: 1.083 |
| - type: precision_at_1000 |
| value: 0.11299999999999999 |
| - type: precision_at_3 |
| value: 26.0 |
| - type: precision_at_5 |
| value: 16.933 |
| - type: recall_at_1 |
| value: 54.31700000000001 |
| - type: recall_at_10 |
| value: 85.056 |
| - type: recall_at_100 |
| value: 95.667 |
| - type: recall_at_1000 |
| value: 100.0 |
| - type: recall_at_3 |
| value: 71.0 |
| - type: recall_at_5 |
| value: 75.672 |
| task: |
| type: Retrieval |
| - dataset: |
| config: default |
| name: MTEB TRECCOVID-PL |
| revision: 81bcb408f33366c2a20ac54adafad1ae7e877fdd |
| split: test |
| type: clarin-knext/trec-covid-pl |
| metrics: |
| - type: map_at_1 |
| value: 0.245 |
| - type: map_at_10 |
| value: 2.051 |
| - type: map_at_100 |
| value: 12.009 |
| - type: map_at_1000 |
| value: 27.448 |
| - type: map_at_3 |
| value: 0.721 |
| - type: map_at_5 |
| value: 1.13 |
| - type: mrr_at_1 |
| value: 88.0 |
| - type: mrr_at_10 |
| value: 93.0 |
| - type: mrr_at_100 |
| value: 93.0 |
| - type: mrr_at_1000 |
| value: 93.0 |
| - type: mrr_at_3 |
| value: 93.0 |
| - type: mrr_at_5 |
| value: 93.0 |
| - type: ndcg_at_1 |
| value: 85.0 |
| - type: ndcg_at_10 |
| value: 80.303 |
| - type: ndcg_at_100 |
| value: 61.23499999999999 |
| - type: ndcg_at_1000 |
| value: 52.978 |
| - type: ndcg_at_3 |
| value: 84.419 |
| - type: ndcg_at_5 |
| value: 82.976 |
| - type: precision_at_1 |
| value: 88.0 |
| - type: precision_at_10 |
| value: 83.39999999999999 |
| - type: precision_at_100 |
| value: 61.96 |
| - type: precision_at_1000 |
| value: 22.648 |
| - type: precision_at_3 |
| value: 89.333 |
| - type: precision_at_5 |
| value: 87.2 |
| - type: recall_at_1 |
| value: 0.245 |
| - type: recall_at_10 |
| value: 2.193 |
| - type: recall_at_100 |
| value: 14.938 |
| - type: recall_at_1000 |
| value: 48.563 |
| - type: recall_at_3 |
| value: 0.738 |
| - type: recall_at_5 |
| value: 1.173 |
| task: |
| type: Retrieval |
| --- |
| |
| ## gte-Qwen2-7B-instruct |
|
|
| **gte-Qwen2-7B-instruct** is the latest model in the gte (General Text Embedding) model family that ranks **No.1** in both English and Chinese evaluations on the Massive Text Embedding Benchmark [MTEB benchmark](https://huggingface.co/spaces/mteb/leaderboard) (as of June 16, 2024). |
|
|
| Recently, the [**Qwen team**](https://huggingface.co/Qwen) released the Qwen2 series models, and we have trained the **gte-Qwen2-7B-instruct** model based on the [Qwen2-7B](https://huggingface.co/Qwen/Qwen2-7B) LLM model. Compared to the [gte-Qwen1.5-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) model, the **gte-Qwen2-7B-instruct** model uses the same training data and training strategies during the finetuning stage, with the only difference being the upgraded base model to Qwen2-7B. Considering the improvements in the Qwen2 series models compared to the Qwen1.5 series, we can also expect consistent performance enhancements in the embedding models. |
|
|
| The model incorporates several key advancements: |
|
|
| - Integration of bidirectional attention mechanisms, enriching its contextual understanding. |
| - Instruction tuning, applied solely on the query side for streamlined efficiency |
| - Comprehensive training across a vast, multilingual text corpus spanning diverse domains and scenarios. This training leverages both weakly supervised and supervised data, ensuring the model's applicability across numerous languages and a wide array of downstream tasks. |
|
|
|
|
| ## Model Information |
| - Model Size: 7B |
| - Embedding Dimension: 3584 |
| - Max Input Tokens: 32k |
|
|
| ## Requirements |
| ``` |
| transformers>=4.39.2 |
| flash_attn>=2.5.6 |
| ``` |
| ## Usage |
|
|
| ### Sentence Transformers |
|
|
| ```python |
| from sentence_transformers import SentenceTransformer |
| |
| model = SentenceTransformer("Alibaba-NLP/gte-Qwen2-7B-instruct", trust_remote_code=True) |
| # In case you want to reduce the maximum length: |
| model.max_seq_length = 8192 |
| |
| queries = [ |
| "how much protein should a female eat", |
| "summit define", |
| ] |
| documents = [ |
| "As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.", |
| "Definition of summit for English Language Learners. : 1 the highest point of a mountain : the top of a mountain. : 2 the highest level. : 3 a meeting or series of meetings between the leaders of two or more governments.", |
| ] |
| |
| query_embeddings = model.encode(queries, prompt_name="query") |
| document_embeddings = model.encode(documents) |
| |
| scores = (query_embeddings @ document_embeddings.T) * 100 |
| print(scores.tolist()) |
| ``` |
|
|
| Observe the [config_sentence_transformers.json](config_sentence_transformers.json) to see all pre-built prompt names. Otherwise, you can use `model.encode(queries, prompt="Instruct: ...\nQuery: "` to use a custom prompt of your choice. |
|
|
| ### Transformers |
|
|
| ```python |
| import torch |
| import torch.nn.functional as F |
| |
| from torch import Tensor |
| from transformers import AutoTokenizer, AutoModel |
| |
| |
| def last_token_pool(last_hidden_states: Tensor, |
| attention_mask: Tensor) -> Tensor: |
| left_padding = (attention_mask[:, -1].sum() == attention_mask.shape[0]) |
| if left_padding: |
| return last_hidden_states[:, -1] |
| else: |
| sequence_lengths = attention_mask.sum(dim=1) - 1 |
| batch_size = last_hidden_states.shape[0] |
| return last_hidden_states[torch.arange(batch_size, device=last_hidden_states.device), sequence_lengths] |
| |
| |
| def get_detailed_instruct(task_description: str, query: str) -> str: |
| return f'Instruct: {task_description}\nQuery: {query}' |
| |
| |
| # Each query must come with a one-sentence instruction that describes the task |
| task = 'Given a web search query, retrieve relevant passages that answer the query' |
| queries = [ |
| get_detailed_instruct(task, 'how much protein should a female eat'), |
| get_detailed_instruct(task, 'summit define') |
| ] |
| # No need to add instruction for retrieval documents |
| documents = [ |
| "As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.", |
| "Definition of summit for English Language Learners. : 1 the highest point of a mountain : the top of a mountain. : 2 the highest level. : 3 a meeting or series of meetings between the leaders of two or more governments." |
| ] |
| input_texts = queries + documents |
| |
| tokenizer = AutoTokenizer.from_pretrained('Alibaba-NLP/gte-Qwen2-7B-instruct', trust_remote_code=True) |
| model = AutoModel.from_pretrained('Alibaba-NLP/gte-Qwen2-7B-instruct', trust_remote_code=True) |
| |
| max_length = 8192 |
| |
| # Tokenize the input texts |
| batch_dict = tokenizer(input_texts, max_length=max_length, padding=True, truncation=True, return_tensors='pt') |
| outputs = model(**batch_dict) |
| embeddings = last_token_pool(outputs.last_hidden_state, batch_dict['attention_mask']) |
| |
| # normalize embeddings |
| embeddings = F.normalize(embeddings, p=2, dim=1) |
| scores = (embeddings[:2] @ embeddings[2:].T) * 100 |
| print(scores.tolist()) |
| ``` |
|
|
| ## Infinity_emb |
| |
| Usage via [infinity](https://github.com/michaelfeil/infinity), a MIT Licensed inference server. |
| |
| ``` |
| # requires ~16-32GB VRAM NVIDIA Compute Capability >= 8.0 |
| docker run \ |
| -v $PWD/data:/app/.cache --gpus "0" -p "7997":"7997" \ |
| michaelf34/infinity:0.0.68-trt-onnx \ |
| v2 --model-id Alibaba-NLP/gte-Qwen2-7B-instruct --revision "refs/pr/38" --dtype bfloat16 --batch-size 8 --device cuda --engine torch --port 7997 --no-bettertransformer |
| ``` |
| |
| ## Evaluation |
| |
| ### MTEB & C-MTEB |
| |
| You can use the [scripts/eval_mteb.py](https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct/blob/main/scripts/eval_mteb.py) to reproduce the following result of **gte-Qwen2-7B-instruct** on MTEB(English)/C-MTEB(Chinese): |
| |
| | Model Name | MTEB(56) | C-MTEB(35) | MTEB-fr(26) | MTEB-pl(26) | |
| |:----:|:---------:|:----------:|:----------:|:----------:| |
| | [bge-base-en-1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) | 64.23 | - | - | - | |
| | [bge-large-en-1.5](https://huggingface.co/BAAI/bge-large-en-v1.5) | 63.55 | - | - | - | |
| | [gte-large-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) | 65.39 | - | - | - | |
| | [gte-base-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) | 64.11 | - | - | - | |
| | [mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) | 64.68 | - | - | - | |
| | [acge_text_embedding](https://huggingface.co/aspire/acge_text_embedding) | - | 69.07 | - | - | |
| | [stella-mrl-large-zh-v3.5-1792d](https://huggingface.co/infgrad/stella-mrl-large-zh-v3.5-1792d) | - | 68.55 | - | - | |
| | [gte-large-zh](https://huggingface.co/thenlper/gte-large-zh) | - | 66.72 | - | - | |
| | [multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) | 59.45 | 56.21 | - | - | |
| | [multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) | 61.50 | 58.81 | - | - | |
| | [e5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct) | 66.63 | 60.81 | - | - | |
| | [gte-Qwen1.5-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) | 67.34 | 69.52 | - | - | |
| | [NV-Embed-v1](https://huggingface.co/nvidia/NV-Embed-v1) | 69.32 | - | - | - | |
| | [**gte-Qwen2-7B-instruct**](https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct) | **70.24** | **72.05** | **68.25** | **67.86** | |
| | gte-Qwen2-1.5B-instruc(https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct) | 67.16 | 67.65 | 66.60 | 64.04 | |
| |
| ### GTE Models |
| |
| The gte series models have consistently released two types of models: encoder-only models (based on the BERT architecture) and decode-only models (based on the LLM architecture). |
| |
| | Models | Language | Max Sequence Length | Dimension | Model Size (Memory Usage, fp32) | |
| |:-------------------------------------------------------------------------------------:|:--------:|:-----: |:---------:|:-------------------------------:| |
| | [GTE-large-zh](https://huggingface.co/thenlper/gte-large-zh) | Chinese | 512 | 1024 | 1.25GB | |
| | [GTE-base-zh](https://huggingface.co/thenlper/gte-base-zh) | Chinese | 512 | 512 | 0.41GB | |
| | [GTE-small-zh](https://huggingface.co/thenlper/gte-small-zh) | Chinese | 512 | 512 | 0.12GB | |
| | [GTE-large](https://huggingface.co/thenlper/gte-large) | English | 512 | 1024 | 1.25GB | |
| | [GTE-base](https://huggingface.co/thenlper/gte-base) | English | 512 | 512 | 0.21GB | |
| | [GTE-small](https://huggingface.co/thenlper/gte-small) | English | 512 | 384 | 0.10GB | |
| | [GTE-large-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) | English | 8192 | 1024 | 1.74GB | |
| | [GTE-base-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-base-en-v1.5) | English | 8192 | 768 | 0.51GB | |
| | [GTE-Qwen1.5-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) | Multilingual | 32000 | 4096 | 26.45GB | |
| | [GTE-Qwen2-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct) | Multilingual | 32000 | 3584 | 26.45GB | |
| | [GTE-Qwen2-1.5B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct) | Multilingual | 32000 | 1536 | 6.62GB | |
| |
| ## Cloud API Services |
| |
| In addition to the open-source [GTE](https://huggingface.co/collections/Alibaba-NLP/gte-models-6680f0b13f885cb431e6d469) series models, GTE series models are also available as commercial API services on Alibaba Cloud. |
| |
| - [Embedding Models](https://help.aliyun.com/zh/model-studio/developer-reference/general-text-embedding/): Three versions of the text embedding models are available: text-embedding-v1/v2/v3, with v3 being the latest API service. |
| - [ReRank Models](https://help.aliyun.com/zh/model-studio/developer-reference/general-text-sorting-model/): The gte-rerank model service is available. |
| |
| Note that the models behind the commercial APIs are not entirely identical to the open-source models. |
| |
| ## Community support |
| |
| ### Fine-tuning |
| |
| GTE models can be fine-tuned with a third party framework SWIFT. |
| |
| ```shell |
| pip install ms-swift -U |
| ``` |
| |
| ```shell |
| # check: https://swift.readthedocs.io/en/latest/BestPractices/Embedding.html |
| nproc_per_node=8 |
| NPROC_PER_NODE=$nproc_per_node \ |
| USE_HF=1 \ |
| swift sft \ |
| --model Alibaba-NLP/gte-Qwen2-7B-instruct \ |
| --train_type lora \ |
| --dataset 'sentence-transformers/stsb' \ |
| --torch_dtype bfloat16 \ |
| --num_train_epochs 10 \ |
| --per_device_train_batch_size 2 \ |
| --per_device_eval_batch_size 1 \ |
| --gradient_accumulation_steps $(expr 64 / $nproc_per_node) \ |
| --eval_steps 100 \ |
| --save_steps 100 \ |
| --eval_strategy steps \ |
| --use_chat_template false \ |
| --save_total_limit 5 \ |
| --logging_steps 5 \ |
| --output_dir output \ |
| --warmup_ratio 0.05 \ |
| --learning_rate 5e-6 \ |
| --deepspeed zero3 \ |
| --dataloader_num_workers 4 \ |
| --task_type embedding \ |
| --loss_type cosine_similarity \ |
| --dataloader_drop_last true |
| ``` |
| |
| ## Citation |
|
|
| If you find our paper or models helpful, please consider cite: |
|
|
| ``` |
| @article{li2023towards, |
| title={Towards general text embeddings with multi-stage contrastive learning}, |
| author={Li, Zehan and Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan}, |
| journal={arXiv preprint arXiv:2308.03281}, |
| year={2023} |
| } |
| ``` |
