diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -5,7 +5,814 @@ tags: - sentence-transformers - feature-extraction - sentence-similarity - +- mteb +model-index: +- name: sentence_croissant_v8 + results: + - task: + type: Clustering + dataset: + type: lyon-nlp/alloprof + name: MTEB AlloProfClusteringP2P + config: default + split: test + revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b + metrics: + - type: v_measure + value: 57.428864270265436 + - type: v_measures + value: [0.5614002072589602, 0.5263956507044442, 0.5705983621877876, 0.644706670078619, 0.5546629587554343, 0.5285267431772123, 0.6358898293581395, 0.5652559860439862, 0.5110004766882107, 0.6444495427737497, 0.5614002072589602, 0.5263956507044442, 0.5705983621877876, 0.644706670078619, 0.5546629587554343, 0.5285267431772123, 0.6358898293581395, 0.5652559860439862, 0.5110004766882107, 0.6444495427737497, 0.5614002072589602, 0.5263956507044442, 0.5705983621877876, 0.644706670078619, 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name: MTEB MassiveScenarioClassification (fr) + config: fr + split: test + revision: 7d571f92784cd94a019292a1f45445077d0ef634 + metrics: + - type: accuracy + value: 71.61398789509079 + - type: f1 + value: 71.87797304491475 + - task: + type: Retrieval + dataset: + type: jinaai/mintakaqa + name: MTEB MintakaRetrieval (fr) + config: fr + split: test + revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e + metrics: + - type: map_at_1 + value: 16.339000000000002 + - type: map_at_10 + value: 25.808999999999997 + - type: map_at_100 + value: 27.023999999999997 + - type: map_at_1000 + value: 27.1 + - type: map_at_20 + value: 26.484999999999996 + - type: map_at_3 + value: 22.891000000000002 + - type: map_at_5 + value: 24.568 + - type: mrr_at_1 + value: 16.339000000000002 + - type: mrr_at_10 + value: 25.808999999999997 + - type: mrr_at_100 + value: 27.023999999999997 + - type: mrr_at_1000 + value: 27.1 + - type: mrr_at_20 + value: 26.484999999999996 + - type: mrr_at_3 + value: 22.891000000000002 + 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dataset: + type: paws-x + name: MTEB PawsX (fr) + config: fr + split: test + revision: 8a04d940a42cd40658986fdd8e3da561533a3646 + metrics: + - type: cos_sim_accuracy + value: 65.4 + - type: cos_sim_ap + value: 66.91762455306835 + - type: cos_sim_f1 + value: 64.69093988145639 + - type: cos_sim_precision + value: 52.36463331048663 + - type: cos_sim_recall + value: 84.60686600221484 + - type: dot_accuracy + value: 56.39999999999999 + - type: dot_ap + value: 50.65829702535556 + - type: dot_f1 + value: 62.491349480968864 + - type: dot_precision + value: 45.44539506794162 + - type: dot_recall + value: 100.0 + - type: euclidean_accuracy + value: 65.05 + - type: euclidean_ap + value: 67.15324108025274 + - type: euclidean_f1 + value: 64.36681222707423 + - type: euclidean_precision + value: 53.13626532083634 + - type: euclidean_recall + value: 81.61683277962348 + - type: manhattan_accuracy + value: 65.0 + - type: manhattan_ap + value: 67.15521762543842 + - type: manhattan_f1 + value: 64.35773783428323 + - type: manhattan_precision + value: 53.26560232220609 + - type: manhattan_recall + value: 81.28460686600222 + - type: max_accuracy + value: 65.4 + - type: max_ap + value: 67.15521762543842 + - type: max_f1 + value: 64.69093988145639 + - task: + type: STS + dataset: + type: Lajavaness/SICK-fr + name: MTEB SICKFr + config: default + split: test + revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a + metrics: + - type: cos_sim_pearson + value: 80.13453477364664 + - type: cos_sim_spearman + value: 71.59592251091182 + - type: euclidean_pearson + value: 74.6813217331865 + - type: euclidean_spearman + value: 69.83675848670511 + - type: manhattan_pearson + value: 74.80033516228748 + - type: manhattan_spearman + value: 69.91910080397358 + - task: + type: STS + dataset: + type: mteb/sts22-crosslingual-sts + name: MTEB STS22 (fr) + config: fr + split: test + revision: eea2b4fe26a775864c896887d910b76a8098ad3f + metrics: + - type: cos_sim_pearson + value: 80.66905713032178 + - type: cos_sim_spearman + value: 82.3452553922562 + - type: euclidean_pearson + value: 74.6277040883804 + - type: euclidean_spearman + value: 77.78371755530127 + - type: manhattan_pearson + value: 74.81879938632161 + - type: manhattan_spearman + value: 77.58712341518728 + - task: + type: STS + dataset: + type: PhilipMay/stsb_multi_mt + name: MTEB STSBenchmarkMultilingualSTS (fr) + config: fr + split: test + revision: 93d57ef91790589e3ce9c365164337a8a78b7632 + metrics: + - type: cos_sim_pearson + value: 80.4059890704687 + - type: cos_sim_spearman + value: 79.21950962470463 + - type: euclidean_pearson + value: 77.07401988705624 + - type: euclidean_spearman + value: 77.77234330224117 + - type: manhattan_pearson + value: 77.08866405845029 + - type: manhattan_spearman + value: 77.8144806404841 + - task: + type: Summarization + dataset: + type: lyon-nlp/summarization-summeval-fr-p2p + name: MTEB SummEvalFr + config: default + split: test + revision: b385812de6a9577b6f4d0f88c6a6e35395a94054 + metrics: + - type: cos_sim_pearson + value: 30.36666619115537 + - type: cos_sim_spearman + value: 30.22116851214898 + - type: dot_pearson + value: 28.017505248518955 + - type: dot_spearman + value: 29.11540877445319 + - task: + type: Reranking + dataset: + type: lyon-nlp/mteb-fr-reranking-syntec-s2p + name: MTEB SyntecReranking + config: default + split: test + revision: b205c5084a0934ce8af14338bf03feb19499c84d + metrics: + - type: map + value: 84.06666666666666 + - type: mrr + value: 84.06666666666666 + - task: + type: Retrieval + dataset: + type: lyon-nlp/mteb-fr-retrieval-syntec-s2p + name: MTEB SyntecRetrieval + config: default + split: test + revision: 19661ccdca4dfc2d15122d776b61685f48c68ca9 + metrics: + - type: map_at_1 + value: 56.99999999999999 + - type: map_at_10 + value: 71.035 + - type: map_at_100 + value: 71.257 + - type: map_at_1000 + value: 71.257 + - type: map_at_20 + value: 71.125 + - type: map_at_3 + value: 68.667 + - type: map_at_5 + value: 70.267 + - type: mrr_at_1 + value: 56.99999999999999 + - type: mrr_at_10 + value: 71.035 + - type: mrr_at_100 + value: 71.257 + - type: mrr_at_1000 + value: 71.257 + - type: mrr_at_20 + value: 71.125 + - type: mrr_at_3 + value: 68.667 + - type: mrr_at_5 + value: 70.267 + - type: ndcg_at_1 + value: 56.99999999999999 + - type: ndcg_at_10 + value: 76.957 + - type: ndcg_at_100 + value: 78.037 + - type: ndcg_at_1000 + value: 78.037 + - type: ndcg_at_20 + value: 77.236 + - type: ndcg_at_3 + value: 72.357 + - type: ndcg_at_5 + value: 75.24 + - type: precision_at_1 + value: 56.99999999999999 + - type: precision_at_10 + value: 9.5 + - type: precision_at_100 + value: 1.0 + - type: precision_at_1000 + value: 0.1 + - type: precision_at_20 + value: 4.8 + - type: precision_at_3 + value: 27.667 + - type: precision_at_5 + value: 18.0 + - type: recall_at_1 + value: 56.99999999999999 + - type: recall_at_10 + value: 95.0 + - type: recall_at_100 + value: 100.0 + - type: recall_at_1000 + value: 100.0 + - type: recall_at_20 + value: 96.0 + - type: recall_at_3 + value: 83.0 + - type: recall_at_5 + value: 90.0 + - task: + type: Retrieval + dataset: + type: jinaai/xpqa + name: MTEB XPQARetrieval (fr) + config: fr + split: test + revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f + metrics: + - type: map_at_1 + value: 38.68 + - type: map_at_10 + value: 58.388 + - type: map_at_100 + value: 59.99100000000001 + - type: map_at_1000 + value: 60.045 + - type: map_at_20 + value: 59.439 + - type: map_at_3 + value: 52.467 + - type: map_at_5 + value: 55.832 + - type: mrr_at_1 + value: 61.282000000000004 + - type: mrr_at_10 + value: 68.00500000000001 + - type: mrr_at_100 + value: 68.659 + - type: mrr_at_1000 + value: 68.675 + - type: mrr_at_20 + value: 68.459 + - type: mrr_at_3 + value: 66.444 + - type: mrr_at_5 + value: 67.192 + - type: ndcg_at_1 + value: 61.282000000000004 + - type: ndcg_at_10 + value: 64.802 + - type: ndcg_at_100 + value: 70.104 + - type: ndcg_at_1000 + value: 71.006 + - type: ndcg_at_20 + value: 67.41 + - type: ndcg_at_3 + value: 59.75 + - type: ndcg_at_5 + value: 60.842 + - type: precision_at_1 + value: 61.282000000000004 + - type: precision_at_10 + value: 14.940000000000001 + - type: precision_at_100 + value: 1.936 + - type: precision_at_1000 + value: 0.20600000000000002 + - type: precision_at_20 + value: 8.405 + - type: precision_at_3 + value: 35.870000000000005 + - type: precision_at_5 + value: 25.207 + - type: recall_at_1 + value: 38.68 + - type: recall_at_10 + value: 73.485 + - type: recall_at_100 + value: 93.669 + - type: recall_at_1000 + value: 99.506 + - type: recall_at_20 + value: 81.733 + - type: recall_at_3 + value: 57.352000000000004 + - type: recall_at_5 + value: 63.912 --- # {MODEL_NAME}