Instructions to use Erin/mist-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Erin/mist-zh with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Erin/mist-zh")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Erin/mist-zh") model = AutoModel.from_pretrained("Erin/mist-zh") - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - mteb | |
| model-index: | |
| - name: mist-zh | |
| results: | |
| - task: | |
| type: STS | |
| dataset: | |
| type: C-MTEB/AFQMC | |
| name: MTEB AFQMC | |
| config: default | |
| split: validation | |
| revision: None | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 44.80910972039708 | |
| - type: cos_sim_spearman | |
| value: 46.97947004057185 | |
| - type: euclidean_pearson | |
| value: 45.36774158404125 | |
| - type: euclidean_spearman | |
| value: 46.97947004232487 | |
| - type: manhattan_pearson | |
| value: 45.23486628014998 | |
| - type: manhattan_spearman | |
| value: 46.87721960765866 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: C-MTEB/ATEC | |
| name: MTEB ATEC | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 49.5294624928126 | |
| - type: cos_sim_spearman | |
| value: 51.34771777448503 | |
| - type: euclidean_pearson | |
| value: 53.56859824288157 | |
| - type: euclidean_spearman | |
| value: 51.34771439634126 | |
| - type: manhattan_pearson | |
| value: 53.581640877132685 | |
| - type: manhattan_spearman | |
| value: 51.349656519071274 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_reviews_multi | |
| name: MTEB AmazonReviewsClassification (zh) | |
| config: zh | |
| split: test | |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d | |
| metrics: | |
| - type: accuracy | |
| value: 39.318 | |
| - type: f1 | |
| value: 37.37720144558489 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: C-MTEB/BQ | |
| name: MTEB BQ | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 62.12016334764962 | |
| - type: cos_sim_spearman | |
| value: 65.08208654969742 | |
| - type: euclidean_pearson | |
| value: 63.53078822303454 | |
| - type: euclidean_spearman | |
| value: 65.0820865487212 | |
| - type: manhattan_pearson | |
| value: 63.510532363654725 | |
| - type: manhattan_spearman | |
| value: 65.06622789125241 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: C-MTEB/CLSClusteringP2P | |
| name: MTEB CLSClusteringP2P | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: v_measure | |
| value: 39.5071157612481 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: C-MTEB/CLSClusteringS2S | |
| name: MTEB CLSClusteringS2S | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: v_measure | |
| value: 37.99964332311132 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: C-MTEB/CMedQAv1-reranking | |
| name: MTEB CMedQAv1 | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map | |
| value: 84.67010533089491 | |
| - type: mrr | |
| value: 86.99488095238095 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: C-MTEB/CMedQAv2-reranking | |
| name: MTEB CMedQAv2 | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map | |
| value: 85.27288868896477 | |
| - type: mrr | |
| value: 87.5929761904762 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/CmedqaRetrieval | |
| name: MTEB CmedqaRetrieval | |
| config: default | |
| split: dev | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 23.949 | |
| - type: map_at_10 | |
| value: 35.394 | |
| - type: map_at_100 | |
| value: 37.235 | |
| - type: map_at_1000 | |
| value: 37.364999999999995 | |
| - type: map_at_3 | |
| value: 31.433 | |
| - type: map_at_5 | |
| value: 33.668 | |
| - type: mrr_at_1 | |
| value: 36.834 | |
| - type: mrr_at_10 | |
| value: 44.451 | |
| - type: mrr_at_100 | |
| value: 45.445 | |
| - type: mrr_at_1000 | |
| value: 45.501000000000005 | |
| - type: mrr_at_3 | |
| value: 42.010999999999996 | |
| - type: mrr_at_5 | |
| value: 43.34 | |
| - type: ndcg_at_1 | |
| value: 36.834 | |
| - type: ndcg_at_10 | |
| value: 41.803000000000004 | |
| - type: ndcg_at_100 | |
| value: 49.091 | |
| - type: ndcg_at_1000 | |
| value: 51.474 | |
| - type: ndcg_at_3 | |
| value: 36.736000000000004 | |
| - type: ndcg_at_5 | |
| value: 38.868 | |
| - type: precision_at_1 | |
| value: 36.834 | |
| - type: precision_at_10 | |
| value: 9.354999999999999 | |
| - type: precision_at_100 | |
| value: 1.5310000000000001 | |
| - type: precision_at_1000 | |
| value: 0.183 | |
| - type: precision_at_3 | |
| value: 20.78 | |
| - type: precision_at_5 | |
| value: 15.238999999999999 | |
| - type: recall_at_1 | |
| value: 23.949 | |
| - type: recall_at_10 | |
| value: 51.68000000000001 | |
| - type: recall_at_100 | |
| value: 81.938 | |
| - type: recall_at_1000 | |
| value: 98.091 | |
| - type: recall_at_3 | |
| value: 36.408 | |
| - type: recall_at_5 | |
| value: 42.952 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: C-MTEB/CMNLI | |
| name: MTEB Cmnli | |
| config: default | |
| split: validation | |
| revision: None | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 76.24774503908598 | |
| - type: cos_sim_ap | |
| value: 84.76081551540754 | |
| - type: cos_sim_f1 | |
| value: 77.76321537789427 | |
| - type: cos_sim_precision | |
| value: 72.96577167452347 | |
| - type: cos_sim_recall | |
| value: 83.23591302314706 | |
| - type: dot_accuracy | |
| value: 76.24774503908598 | |
| - type: dot_ap | |
| value: 84.75968761251127 | |
| - type: dot_f1 | |
| value: 77.76321537789427 | |
| - type: dot_precision | |
| value: 72.96577167452347 | |
| - type: dot_recall | |
| value: 83.23591302314706 | |
| - type: euclidean_accuracy | |
| value: 76.24774503908598 | |
| - type: euclidean_ap | |
| value: 84.7608250840413 | |
| - type: euclidean_f1 | |
| value: 77.76321537789427 | |
| - type: euclidean_precision | |
| value: 72.96577167452347 | |
| - type: euclidean_recall | |
| value: 83.23591302314706 | |
| - type: manhattan_accuracy | |
| value: 76.19963920625375 | |
| - type: manhattan_ap | |
| value: 84.76313920535411 | |
| - type: manhattan_f1 | |
| value: 77.74253527288636 | |
| - type: manhattan_precision | |
| value: 73.0374023838882 | |
| - type: manhattan_recall | |
| value: 83.09562777647884 | |
| - type: max_accuracy | |
| value: 76.24774503908598 | |
| - type: max_ap | |
| value: 84.76313920535411 | |
| - type: max_f1 | |
| value: 77.76321537789427 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/CovidRetrieval | |
| name: MTEB CovidRetrieval | |
| config: default | |
| split: dev | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 66.149 | |
| - type: map_at_10 | |
| value: 75.22999999999999 | |
| - type: map_at_100 | |
| value: 75.536 | |
| - type: map_at_1000 | |
| value: 75.542 | |
| - type: map_at_3 | |
| value: 73.384 | |
| - type: map_at_5 | |
| value: 74.459 | |
| - type: mrr_at_1 | |
| value: 66.28 | |
| - type: mrr_at_10 | |
| value: 75.232 | |
| - type: mrr_at_100 | |
| value: 75.52799999999999 | |
| - type: mrr_at_1000 | |
| value: 75.534 | |
| - type: mrr_at_3 | |
| value: 73.446 | |
| - type: mrr_at_5 | |
| value: 74.473 | |
| - type: ndcg_at_1 | |
| value: 66.386 | |
| - type: ndcg_at_10 | |
| value: 79.295 | |
| - type: ndcg_at_100 | |
| value: 80.741 | |
| - type: ndcg_at_1000 | |
| value: 80.891 | |
| - type: ndcg_at_3 | |
| value: 75.613 | |
| - type: ndcg_at_5 | |
| value: 77.46300000000001 | |
| - type: precision_at_1 | |
| value: 66.386 | |
| - type: precision_at_10 | |
| value: 9.283 | |
| - type: precision_at_100 | |
| value: 0.996 | |
| - type: precision_at_1000 | |
| value: 0.101 | |
| - type: precision_at_3 | |
| value: 27.503 | |
| - type: precision_at_5 | |
| value: 17.408 | |
| - type: recall_at_1 | |
| value: 66.149 | |
| - type: recall_at_10 | |
| value: 91.886 | |
| - type: recall_at_100 | |
| value: 98.52499999999999 | |
| - type: recall_at_1000 | |
| value: 99.684 | |
| - type: recall_at_3 | |
| value: 81.849 | |
| - type: recall_at_5 | |
| value: 86.275 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/DuRetrieval | |
| name: MTEB DuRetrieval | |
| config: default | |
| split: dev | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 25.166 | |
| - type: map_at_10 | |
| value: 78.805 | |
| - type: map_at_100 | |
| value: 81.782 | |
| - type: map_at_1000 | |
| value: 81.818 | |
| - type: map_at_3 | |
| value: 54.226 | |
| - type: map_at_5 | |
| value: 68.783 | |
| - type: mrr_at_1 | |
| value: 88.6 | |
| - type: mrr_at_10 | |
| value: 92.244 | |
| - type: mrr_at_100 | |
| value: 92.31899999999999 | |
| - type: mrr_at_1000 | |
| value: 92.321 | |
| - type: mrr_at_3 | |
| value: 91.867 | |
| - type: mrr_at_5 | |
| value: 92.119 | |
| - type: ndcg_at_1 | |
| value: 88.6 | |
| - type: ndcg_at_10 | |
| value: 86.432 | |
| - type: ndcg_at_100 | |
| value: 89.357 | |
| - type: ndcg_at_1000 | |
| value: 89.688 | |
| - type: ndcg_at_3 | |
| value: 84.90299999999999 | |
| - type: ndcg_at_5 | |
| value: 84.137 | |
| - type: precision_at_1 | |
| value: 88.6 | |
| - type: precision_at_10 | |
| value: 41.685 | |
| - type: precision_at_100 | |
| value: 4.811 | |
| - type: precision_at_1000 | |
| value: 0.48900000000000005 | |
| - type: precision_at_3 | |
| value: 76.44999999999999 | |
| - type: precision_at_5 | |
| value: 64.87 | |
| - type: recall_at_1 | |
| value: 25.166 | |
| - type: recall_at_10 | |
| value: 88.227 | |
| - type: recall_at_100 | |
| value: 97.597 | |
| - type: recall_at_1000 | |
| value: 99.359 | |
| - type: recall_at_3 | |
| value: 56.946 | |
| - type: recall_at_5 | |
| value: 74.261 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/EcomRetrieval | |
| name: MTEB EcomRetrieval | |
| config: default | |
| split: dev | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 48.3 | |
| - type: map_at_10 | |
| value: 57.635999999999996 | |
| - type: map_at_100 | |
| value: 58.306000000000004 | |
| - type: map_at_1000 | |
| value: 58.326 | |
| - type: map_at_3 | |
| value: 54.900000000000006 | |
| - type: map_at_5 | |
| value: 56.620000000000005 | |
| - type: mrr_at_1 | |
| value: 48.3 | |
| - type: mrr_at_10 | |
| value: 57.635999999999996 | |
| - type: mrr_at_100 | |
| value: 58.306000000000004 | |
| - type: mrr_at_1000 | |
| value: 58.326 | |
| - type: mrr_at_3 | |
| value: 54.900000000000006 | |
| - type: mrr_at_5 | |
| value: 56.620000000000005 | |
| - type: ndcg_at_1 | |
| value: 48.3 | |
| - type: ndcg_at_10 | |
| value: 62.638000000000005 | |
| - type: ndcg_at_100 | |
| value: 65.726 | |
| - type: ndcg_at_1000 | |
| value: 66.253 | |
| - type: ndcg_at_3 | |
| value: 57.081 | |
| - type: ndcg_at_5 | |
| value: 60.217 | |
| - type: precision_at_1 | |
| value: 48.3 | |
| - type: precision_at_10 | |
| value: 7.85 | |
| - type: precision_at_100 | |
| value: 0.9249999999999999 | |
| - type: precision_at_1000 | |
| value: 0.097 | |
| - type: precision_at_3 | |
| value: 21.133 | |
| - type: precision_at_5 | |
| value: 14.219999999999999 | |
| - type: recall_at_1 | |
| value: 48.3 | |
| - type: recall_at_10 | |
| value: 78.5 | |
| - type: recall_at_100 | |
| value: 92.5 | |
| - type: recall_at_1000 | |
| value: 96.6 | |
| - type: recall_at_3 | |
| value: 63.4 | |
| - type: recall_at_5 | |
| value: 71.1 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: C-MTEB/IFlyTek-classification | |
| name: MTEB IFlyTek | |
| config: default | |
| split: validation | |
| revision: None | |
| metrics: | |
| - type: accuracy | |
| value: 47.9646017699115 | |
| - type: f1 | |
| value: 35.03552351349023 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: C-MTEB/JDReview-classification | |
| name: MTEB JDReview | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: accuracy | |
| value: 84.8968105065666 | |
| - type: ap | |
| value: 52.564605306946774 | |
| - type: f1 | |
| value: 79.59880155481291 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: C-MTEB/LCQMC | |
| name: MTEB LCQMC | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 70.03662039861051 | |
| - type: cos_sim_spearman | |
| value: 76.9642260444222 | |
| - type: euclidean_pearson | |
| value: 75.47376966815843 | |
| - type: euclidean_spearman | |
| value: 76.9642282583736 | |
| - type: manhattan_pearson | |
| value: 75.45535385433548 | |
| - type: manhattan_spearman | |
| value: 76.94609742735338 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/MMarcoRetrieval | |
| name: MTEB MMarcoRetrieval | |
| config: default | |
| split: dev | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 65.604 | |
| - type: map_at_10 | |
| value: 74.522 | |
| - type: map_at_100 | |
| value: 74.878 | |
| - type: map_at_1000 | |
| value: 74.889 | |
| - type: map_at_3 | |
| value: 72.61 | |
| - type: map_at_5 | |
| value: 73.882 | |
| - type: mrr_at_1 | |
| value: 67.75099999999999 | |
| - type: mrr_at_10 | |
| value: 75.08399999999999 | |
| - type: mrr_at_100 | |
| value: 75.402 | |
| - type: mrr_at_1000 | |
| value: 75.412 | |
| - type: mrr_at_3 | |
| value: 73.446 | |
| - type: mrr_at_5 | |
| value: 74.531 | |
| - type: ndcg_at_1 | |
| value: 67.75099999999999 | |
| - type: ndcg_at_10 | |
| value: 78.172 | |
| - type: ndcg_at_100 | |
| value: 79.753 | |
| - type: ndcg_at_1000 | |
| value: 80.06400000000001 | |
| - type: ndcg_at_3 | |
| value: 74.607 | |
| - type: ndcg_at_5 | |
| value: 76.728 | |
| - type: precision_at_1 | |
| value: 67.75099999999999 | |
| - type: precision_at_10 | |
| value: 9.443999999999999 | |
| - type: precision_at_100 | |
| value: 1.023 | |
| - type: precision_at_1000 | |
| value: 0.105 | |
| - type: precision_at_3 | |
| value: 28.009 | |
| - type: precision_at_5 | |
| value: 17.934 | |
| - type: recall_at_1 | |
| value: 65.604 | |
| - type: recall_at_10 | |
| value: 88.84100000000001 | |
| - type: recall_at_100 | |
| value: 95.954 | |
| - type: recall_at_1000 | |
| value: 98.425 | |
| - type: recall_at_3 | |
| value: 79.497 | |
| - type: recall_at_5 | |
| value: 84.515 | |
| - 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: 67.64963012777405 | |
| - type: f1 | |
| value: 65.01092085388518 | |
| - 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: 72.9724277067922 | |
| - type: f1 | |
| value: 72.48003852874602 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/MedicalRetrieval | |
| name: MTEB MedicalRetrieval | |
| config: default | |
| split: dev | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 48.9 | |
| - type: map_at_10 | |
| value: 55.189 | |
| - type: map_at_100 | |
| value: 55.687 | |
| - type: map_at_1000 | |
| value: 55.74400000000001 | |
| - type: map_at_3 | |
| value: 53.75 | |
| - type: map_at_5 | |
| value: 54.555 | |
| - type: mrr_at_1 | |
| value: 49.1 | |
| - type: mrr_at_10 | |
| value: 55.289 | |
| - type: mrr_at_100 | |
| value: 55.788000000000004 | |
| - type: mrr_at_1000 | |
| value: 55.845 | |
| - type: mrr_at_3 | |
| value: 53.849999999999994 | |
| - type: mrr_at_5 | |
| value: 54.655 | |
| - type: ndcg_at_1 | |
| value: 48.9 | |
| - type: ndcg_at_10 | |
| value: 58.275 | |
| - type: ndcg_at_100 | |
| value: 60.980000000000004 | |
| - type: ndcg_at_1000 | |
| value: 62.672000000000004 | |
| - type: ndcg_at_3 | |
| value: 55.282 | |
| - type: ndcg_at_5 | |
| value: 56.749 | |
| - type: precision_at_1 | |
| value: 48.9 | |
| - type: precision_at_10 | |
| value: 6.800000000000001 | |
| - type: precision_at_100 | |
| value: 0.8130000000000001 | |
| - type: precision_at_1000 | |
| value: 0.095 | |
| - type: precision_at_3 | |
| value: 19.900000000000002 | |
| - type: precision_at_5 | |
| value: 12.659999999999998 | |
| - type: recall_at_1 | |
| value: 48.9 | |
| - type: recall_at_10 | |
| value: 68.0 | |
| - type: recall_at_100 | |
| value: 81.3 | |
| - type: recall_at_1000 | |
| value: 95.0 | |
| - type: recall_at_3 | |
| value: 59.699999999999996 | |
| - type: recall_at_5 | |
| value: 63.3 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: C-MTEB/MultilingualSentiment-classification | |
| name: MTEB MultilingualSentiment | |
| config: default | |
| split: validation | |
| revision: None | |
| metrics: | |
| - type: accuracy | |
| value: 71.53666666666668 | |
| - type: f1 | |
| value: 70.74267338218574 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: C-MTEB/OCNLI | |
| name: MTEB Ocnli | |
| config: default | |
| split: validation | |
| revision: None | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 70.43854899837575 | |
| - type: cos_sim_ap | |
| value: 75.25713109733296 | |
| - type: cos_sim_f1 | |
| value: 73.18777292576418 | |
| - type: cos_sim_precision | |
| value: 62.397617274758 | |
| - type: cos_sim_recall | |
| value: 88.48996832101372 | |
| - type: dot_accuracy | |
| value: 70.43854899837575 | |
| - type: dot_ap | |
| value: 75.25713109733296 | |
| - type: dot_f1 | |
| value: 73.18777292576418 | |
| - type: dot_precision | |
| value: 62.397617274758 | |
| - type: dot_recall | |
| value: 88.48996832101372 | |
| - type: euclidean_accuracy | |
| value: 70.43854899837575 | |
| - type: euclidean_ap | |
| value: 75.25713109733296 | |
| - type: euclidean_f1 | |
| value: 73.18777292576418 | |
| - type: euclidean_precision | |
| value: 62.397617274758 | |
| - type: euclidean_recall | |
| value: 88.48996832101372 | |
| - type: manhattan_accuracy | |
| value: 70.60097455332972 | |
| - type: manhattan_ap | |
| value: 75.22177995740668 | |
| - type: manhattan_f1 | |
| value: 73.13750532141337 | |
| - type: manhattan_precision | |
| value: 61.26961483594865 | |
| - type: manhattan_recall | |
| value: 90.70749736008447 | |
| - type: max_accuracy | |
| value: 70.60097455332972 | |
| - type: max_ap | |
| value: 75.25713109733296 | |
| - type: max_f1 | |
| value: 73.18777292576418 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: C-MTEB/OnlineShopping-classification | |
| name: MTEB OnlineShopping | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: accuracy | |
| value: 91.3 | |
| - type: ap | |
| value: 89.03601366589187 | |
| - type: f1 | |
| value: 91.28612226957141 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: C-MTEB/PAWSX | |
| name: MTEB PAWSX | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 24.254041798082984 | |
| - type: cos_sim_spearman | |
| value: 30.029755057178846 | |
| - type: euclidean_pearson | |
| value: 30.394005237465905 | |
| - type: euclidean_spearman | |
| value: 30.029751825186153 | |
| - type: manhattan_pearson | |
| value: 30.400683181995863 | |
| - type: manhattan_spearman | |
| value: 29.981240616043326 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: C-MTEB/QBQTC | |
| name: MTEB QBQTC | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 35.09911024323138 | |
| - type: cos_sim_spearman | |
| value: 37.49790006053554 | |
| - type: euclidean_pearson | |
| value: 35.65689785105493 | |
| - type: euclidean_spearman | |
| value: 37.498032509597344 | |
| - type: manhattan_pearson | |
| value: 35.68350134483341 | |
| - type: manhattan_spearman | |
| value: 37.54046578100128 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts22-crosslingual-sts | |
| name: MTEB STS22 (zh) | |
| config: zh | |
| split: test | |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 68.26707578158273 | |
| - type: cos_sim_spearman | |
| value: 69.19741429899995 | |
| - type: euclidean_pearson | |
| value: 68.53026048034656 | |
| - type: euclidean_spearman | |
| value: 69.1974135636389 | |
| - type: manhattan_pearson | |
| value: 70.02306646353263 | |
| - type: manhattan_spearman | |
| value: 70.46158498712836 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: C-MTEB/STSB | |
| name: MTEB STSB | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 78.88749955421177 | |
| - type: cos_sim_spearman | |
| value: 79.56695106617856 | |
| - type: euclidean_pearson | |
| value: 79.13787024514338 | |
| - type: euclidean_spearman | |
| value: 79.56690827015423 | |
| - type: manhattan_pearson | |
| value: 79.08154812411563 | |
| - type: manhattan_spearman | |
| value: 79.52391077945943 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: C-MTEB/T2Reranking | |
| name: MTEB T2Reranking | |
| config: default | |
| split: dev | |
| revision: None | |
| metrics: | |
| - type: map | |
| value: 65.78663254562939 | |
| - type: mrr | |
| value: 74.9786877626248 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/T2Retrieval | |
| name: MTEB T2Retrieval | |
| config: default | |
| split: dev | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 26.169999999999998 | |
| - type: map_at_10 | |
| value: 74.009 | |
| - type: map_at_100 | |
| value: 77.788 | |
| - type: map_at_1000 | |
| value: 77.866 | |
| - type: map_at_3 | |
| value: 51.861000000000004 | |
| - type: map_at_5 | |
| value: 63.775000000000006 | |
| - type: mrr_at_1 | |
| value: 87.748 | |
| - type: mrr_at_10 | |
| value: 90.737 | |
| - type: mrr_at_100 | |
| value: 90.84400000000001 | |
| - type: mrr_at_1000 | |
| value: 90.849 | |
| - type: mrr_at_3 | |
| value: 90.257 | |
| - type: mrr_at_5 | |
| value: 90.54299999999999 | |
| - type: ndcg_at_1 | |
| value: 87.748 | |
| - type: ndcg_at_10 | |
| value: 82.114 | |
| - type: ndcg_at_100 | |
| value: 86.148 | |
| - type: ndcg_at_1000 | |
| value: 86.913 | |
| - type: ndcg_at_3 | |
| value: 83.54599999999999 | |
| - type: ndcg_at_5 | |
| value: 81.987 | |
| - type: precision_at_1 | |
| value: 87.748 | |
| - type: precision_at_10 | |
| value: 41.076 | |
| - type: precision_at_100 | |
| value: 4.976 | |
| - type: precision_at_1000 | |
| value: 0.515 | |
| - type: precision_at_3 | |
| value: 73.282 | |
| - type: precision_at_5 | |
| value: 61.351 | |
| - type: recall_at_1 | |
| value: 26.169999999999998 | |
| - type: recall_at_10 | |
| value: 81.292 | |
| - type: recall_at_100 | |
| value: 94.285 | |
| - type: recall_at_1000 | |
| value: 98.221 | |
| - type: recall_at_3 | |
| value: 53.824000000000005 | |
| - type: recall_at_5 | |
| value: 67.547 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: C-MTEB/TNews-classification | |
| name: MTEB TNews | |
| config: default | |
| split: validation | |
| revision: None | |
| metrics: | |
| - type: accuracy | |
| value: 51.564 | |
| - type: f1 | |
| value: 49.711462885083286 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: C-MTEB/ThuNewsClusteringP2P | |
| name: MTEB ThuNewsClusteringP2P | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: v_measure | |
| value: 62.57078038998942 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: C-MTEB/ThuNewsClusteringS2S | |
| name: MTEB ThuNewsClusteringS2S | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: v_measure | |
| value: 57.842602165392144 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/VideoRetrieval | |
| name: MTEB VideoRetrieval | |
| config: default | |
| split: dev | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 52.0 | |
| - type: map_at_10 | |
| value: 62.932 | |
| - type: map_at_100 | |
| value: 63.471999999999994 | |
| - type: map_at_1000 | |
| value: 63.483999999999995 | |
| - type: map_at_3 | |
| value: 60.516999999999996 | |
| - type: map_at_5 | |
| value: 62.097 | |
| - type: mrr_at_1 | |
| value: 52.0 | |
| - type: mrr_at_10 | |
| value: 62.932 | |
| - type: mrr_at_100 | |
| value: 63.471999999999994 | |
| - type: mrr_at_1000 | |
| value: 63.483999999999995 | |
| - type: mrr_at_3 | |
| value: 60.516999999999996 | |
| - type: mrr_at_5 | |
| value: 62.097 | |
| - type: ndcg_at_1 | |
| value: 52.0 | |
| - type: ndcg_at_10 | |
| value: 67.963 | |
| - type: ndcg_at_100 | |
| value: 70.598 | |
| - type: ndcg_at_1000 | |
| value: 70.896 | |
| - type: ndcg_at_3 | |
| value: 63.144 | |
| - type: ndcg_at_5 | |
| value: 65.988 | |
| - type: precision_at_1 | |
| value: 52.0 | |
| - type: precision_at_10 | |
| value: 8.36 | |
| - type: precision_at_100 | |
| value: 0.959 | |
| - type: precision_at_1000 | |
| value: 0.098 | |
| - type: precision_at_3 | |
| value: 23.567 | |
| - type: precision_at_5 | |
| value: 15.52 | |
| - type: recall_at_1 | |
| value: 52.0 | |
| - type: recall_at_10 | |
| value: 83.6 | |
| - type: recall_at_100 | |
| value: 95.89999999999999 | |
| - type: recall_at_1000 | |
| value: 98.2 | |
| - type: recall_at_3 | |
| value: 70.7 | |
| - type: recall_at_5 | |
| value: 77.60000000000001 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: C-MTEB/waimai-classification | |
| name: MTEB Waimai | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: accuracy | |
| value: 86.65999999999998 | |
| - type: ap | |
| value: 69.91988858863054 | |
| - type: f1 | |
| value: 84.92982698422784 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: C-MTEB/Mmarco-reranking | |
| name: MTEB MMarcoReranking | |
| config: default | |
| split: dev | |
| revision: None | |
| metrics: | |
| - type: map | |
| value: 27.838972963193315 | |
| - type: mrr | |
| value: 26.65238095238095 | |