| Quantization made by Richard Erkhov. | |
| [Github](https://github.com/RichardErkhov) | |
| [Discord](https://discord.gg/pvy7H8DZMG) | |
| [Request more models](https://github.com/RichardErkhov/quant_request) | |
| gte-Qwen2-1.5B-instruct - GGUF | |
| - Model creator: https://huggingface.co/Alibaba-NLP/ | |
| - Original model: https://huggingface.co/Alibaba-NLP/gte-Qwen2-1.5B-instruct/ | |
| | Name | Quant method | Size | | |
| | ---- | ---- | ---- | | |
| | [gte-Qwen2-1.5B-instruct.Q2_K.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q2_K.gguf) | Q2_K | 0.7GB | | |
| | [gte-Qwen2-1.5B-instruct.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.IQ3_XS.gguf) | IQ3_XS | 0.77GB | | |
| | [gte-Qwen2-1.5B-instruct.IQ3_S.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.IQ3_S.gguf) | IQ3_S | 0.8GB | | |
| | [gte-Qwen2-1.5B-instruct.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q3_K_S.gguf) | Q3_K_S | 0.8GB | | |
| | [gte-Qwen2-1.5B-instruct.IQ3_M.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.IQ3_M.gguf) | IQ3_M | 0.82GB | | |
| | [gte-Qwen2-1.5B-instruct.Q3_K.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q3_K.gguf) | Q3_K | 0.86GB | | |
| | [gte-Qwen2-1.5B-instruct.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q3_K_M.gguf) | Q3_K_M | 0.86GB | | |
| | [gte-Qwen2-1.5B-instruct.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q3_K_L.gguf) | Q3_K_L | 0.91GB | | |
| | [gte-Qwen2-1.5B-instruct.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.IQ4_XS.gguf) | IQ4_XS | 0.96GB | | |
| | [gte-Qwen2-1.5B-instruct.Q4_0.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q4_0.gguf) | Q4_0 | 0.99GB | | |
| | [gte-Qwen2-1.5B-instruct.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.IQ4_NL.gguf) | IQ4_NL | 1.0GB | | |
| | [gte-Qwen2-1.5B-instruct.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q4_K_S.gguf) | Q4_K_S | 1.0GB | | |
| | [gte-Qwen2-1.5B-instruct.Q4_K.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q4_K.gguf) | Q4_K | 1.04GB | | |
| | [gte-Qwen2-1.5B-instruct.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q4_K_M.gguf) | Q4_K_M | 1.04GB | | |
| | [gte-Qwen2-1.5B-instruct.Q4_1.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q4_1.gguf) | Q4_1 | 1.08GB | | |
| | [gte-Qwen2-1.5B-instruct.Q5_0.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q5_0.gguf) | Q5_0 | 1.17GB | | |
| | [gte-Qwen2-1.5B-instruct.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q5_K_S.gguf) | Q5_K_S | 1.17GB | | |
| | [gte-Qwen2-1.5B-instruct.Q5_K.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q5_K.gguf) | Q5_K | 1.2GB | | |
| | [gte-Qwen2-1.5B-instruct.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q5_K_M.gguf) | Q5_K_M | 1.2GB | | |
| | [gte-Qwen2-1.5B-instruct.Q5_1.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q5_1.gguf) | Q5_1 | 1.26GB | | |
| | [gte-Qwen2-1.5B-instruct.Q6_K.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q6_K.gguf) | Q6_K | 1.36GB | | |
| | [gte-Qwen2-1.5B-instruct.Q8_0.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-1.5B-instruct-gguf/blob/main/gte-Qwen2-1.5B-instruct.Q8_0.gguf) | Q8_0 | 1.76GB | | |
| Original model description: | |
| --- | |
| tags: | |
| - mteb | |
| - sentence-transformers | |
| - transformers | |
| - Qwen2 | |
| - sentence-similarity | |
| license: apache-2.0 | |
| model-index: | |
| - name: gte-qwen2-7B-instruct | |
| results: | |
| - dataset: | |
| config: en | |
| name: MTEB AmazonCounterfactualClassification (en) | |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 | |
| split: test | |
| type: mteb/amazon_counterfactual | |
| metrics: | |
| - type: accuracy | |
| value: 83.98507462686567 | |
| - type: ap | |
| value: 50.93015252587014 | |
| - type: f1 | |
| value: 78.50416599051215 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB AmazonPolarityClassification | |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 | |
| split: test | |
| type: mteb/amazon_polarity | |
| metrics: | |
| - type: accuracy | |
| value: 96.61065 | |
| - type: ap | |
| value: 94.89174052954196 | |
| - type: f1 | |
| value: 96.60942596940565 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: en | |
| name: MTEB AmazonReviewsClassification (en) | |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d | |
| split: test | |
| type: mteb/amazon_reviews_multi | |
| metrics: | |
| - type: accuracy | |
| value: 55.614000000000004 | |
| - type: f1 | |
| value: 54.90553480294904 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB ArguAna | |
| revision: c22ab2a51041ffd869aaddef7af8d8215647e41a | |
| split: test | |
| type: mteb/arguana | |
| metrics: | |
| - type: map_at_1 | |
| value: 45.164 | |
| - type: map_at_10 | |
| value: 61.519 | |
| - type: map_at_100 | |
| value: 61.769 | |
| - type: map_at_1000 | |
| value: 61.769 | |
| - type: map_at_3 | |
| value: 57.443999999999996 | |
| - type: map_at_5 | |
| value: 60.058 | |
| - type: mrr_at_1 | |
| value: 46.088 | |
| - type: mrr_at_10 | |
| value: 61.861 | |
| - type: mrr_at_100 | |
| value: 62.117999999999995 | |
| - type: mrr_at_1000 | |
| value: 62.117999999999995 | |
| - type: mrr_at_3 | |
| value: 57.729 | |
| - type: mrr_at_5 | |
| value: 60.392 | |
| - type: ndcg_at_1 | |
| value: 45.164 | |
| - type: ndcg_at_10 | |
| value: 69.72 | |
| - type: ndcg_at_100 | |
| value: 70.719 | |
| - type: ndcg_at_1000 | |
| value: 70.719 | |
| - type: ndcg_at_3 | |
| value: 61.517999999999994 | |
| - type: ndcg_at_5 | |
| value: 66.247 | |
| - type: precision_at_1 | |
| value: 45.164 | |
| - type: precision_at_10 | |
| value: 9.545 | |
| - type: precision_at_100 | |
| value: 0.996 | |
| - type: precision_at_1000 | |
| value: 0.1 | |
| - type: precision_at_3 | |
| value: 24.443 | |
| - type: precision_at_5 | |
| value: 16.97 | |
| - type: recall_at_1 | |
| value: 45.164 | |
| - type: recall_at_10 | |
| value: 95.448 | |
| - type: recall_at_100 | |
| value: 99.644 | |
| - type: recall_at_1000 | |
| value: 99.644 | |
| - type: recall_at_3 | |
| value: 73.329 | |
| - type: recall_at_5 | |
| value: 84.851 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB ArxivClusteringP2P | |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d | |
| split: test | |
| type: mteb/arxiv-clustering-p2p | |
| metrics: | |
| - type: v_measure | |
| value: 50.511868162026175 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB ArxivClusteringS2S | |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 | |
| split: test | |
| type: mteb/arxiv-clustering-s2s | |
| metrics: | |
| - type: v_measure | |
| value: 45.007803189284004 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB AskUbuntuDupQuestions | |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 | |
| split: test | |
| type: mteb/askubuntudupquestions-reranking | |
| metrics: | |
| - type: map | |
| value: 64.55292107723382 | |
| - type: mrr | |
| value: 77.66158818097877 | |
| task: | |
| type: Reranking | |
| - dataset: | |
| config: default | |
| name: MTEB BIOSSES | |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a | |
| split: test | |
| type: mteb/biosses-sts | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 85.65459047085452 | |
| - type: cos_sim_spearman | |
| value: 82.10729255710761 | |
| - type: euclidean_pearson | |
| value: 82.78079159312476 | |
| - type: euclidean_spearman | |
| value: 80.50002701880933 | |
| - type: manhattan_pearson | |
| value: 82.41372641383016 | |
| - type: manhattan_spearman | |
| value: 80.57412509272639 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB Banking77Classification | |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 | |
| split: test | |
| type: mteb/banking77 | |
| metrics: | |
| - type: accuracy | |
| value: 87.30844155844156 | |
| - type: f1 | |
| value: 87.25307322443255 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB BiorxivClusteringP2P | |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 | |
| split: test | |
| type: mteb/biorxiv-clustering-p2p | |
| metrics: | |
| - type: v_measure | |
| value: 43.20754608934859 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB BiorxivClusteringS2S | |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 | |
| split: test | |
| type: mteb/biorxiv-clustering-s2s | |
| metrics: | |
| - type: v_measure | |
| value: 38.818037697335505 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB CQADupstackAndroidRetrieval | |
| revision: f46a197baaae43b4f621051089b82a364682dfeb | |
| split: test | |
| type: BeIR/cqadupstack | |
| metrics: | |
| - type: map_at_1 | |
| value: 35.423 | |
| - type: map_at_10 | |
| value: 47.198 | |
| - type: map_at_100 | |
| value: 48.899 | |
| - type: map_at_1000 | |
| value: 49.004 | |
| - type: map_at_3 | |
| value: 43.114999999999995 | |
| - type: map_at_5 | |
| value: 45.491 | |
| - type: mrr_at_1 | |
| value: 42.918 | |
| - type: mrr_at_10 | |
| value: 53.299 | |
| - type: mrr_at_100 | |
| value: 54.032000000000004 | |
| - type: mrr_at_1000 | |
| value: 54.055 | |
| - type: mrr_at_3 | |
| value: 50.453 | |
| - type: mrr_at_5 | |
| value: 52.205999999999996 | |
| - type: ndcg_at_1 | |
| value: 42.918 | |
| - type: ndcg_at_10 | |
| value: 53.98 | |
| - type: ndcg_at_100 | |
| value: 59.57 | |
| - type: ndcg_at_1000 | |
| value: 60.879000000000005 | |
| - type: ndcg_at_3 | |
| value: 48.224000000000004 | |
| - type: ndcg_at_5 | |
| value: 50.998 | |
| - type: precision_at_1 | |
| value: 42.918 | |
| - type: precision_at_10 | |
| value: 10.299999999999999 | |
| - type: precision_at_100 | |
| value: 1.687 | |
| - type: precision_at_1000 | |
| value: 0.211 | |
| - type: precision_at_3 | |
| value: 22.842000000000002 | |
| - type: precision_at_5 | |
| value: 16.681 | |
| - type: recall_at_1 | |
| value: 35.423 | |
| - type: recall_at_10 | |
| value: 66.824 | |
| - type: recall_at_100 | |
| value: 89.564 | |
| - type: recall_at_1000 | |
| value: 97.501 | |
| - type: recall_at_3 | |
| value: 50.365 | |
| - type: recall_at_5 | |
| value: 57.921 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB CQADupstackEnglishRetrieval | |
| revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 | |
| split: test | |
| type: BeIR/cqadupstack | |
| metrics: | |
| - type: map_at_1 | |
| value: 33.205 | |
| - type: map_at_10 | |
| value: 44.859 | |
| - type: map_at_100 | |
| value: 46.135 | |
| - type: map_at_1000 | |
| value: 46.259 | |
| - type: map_at_3 | |
| value: 41.839 | |
| - type: map_at_5 | |
| value: 43.662 | |
| - type: mrr_at_1 | |
| value: 41.146 | |
| - type: mrr_at_10 | |
| value: 50.621 | |
| - type: mrr_at_100 | |
| value: 51.207 | |
| - type: mrr_at_1000 | |
| value: 51.246 | |
| - type: mrr_at_3 | |
| value: 48.535000000000004 | |
| - type: mrr_at_5 | |
| value: 49.818 | |
| - type: ndcg_at_1 | |
| value: 41.146 | |
| - type: ndcg_at_10 | |
| value: 50.683 | |
| - type: ndcg_at_100 | |
| value: 54.82 | |
| - type: ndcg_at_1000 | |
| value: 56.69 | |
| - type: ndcg_at_3 | |
| value: 46.611000000000004 | |
| - type: ndcg_at_5 | |
| value: 48.66 | |
| - type: precision_at_1 | |
| value: 41.146 | |
| - type: precision_at_10 | |
| value: 9.439 | |
| - type: precision_at_100 | |
| value: 1.465 | |
| - type: precision_at_1000 | |
| value: 0.194 | |
| - type: precision_at_3 | |
| value: 22.59 | |
| - type: precision_at_5 | |
| value: 15.86 | |
| - type: recall_at_1 | |
| value: 33.205 | |
| - type: recall_at_10 | |
| value: 61.028999999999996 | |
| - type: recall_at_100 | |
| value: 78.152 | |
| - type: recall_at_1000 | |
| value: 89.59700000000001 | |
| - type: recall_at_3 | |
| value: 49.05 | |
| - type: recall_at_5 | |
| value: 54.836 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB CQADupstackGamingRetrieval | |
| revision: 4885aa143210c98657558c04aaf3dc47cfb54340 | |
| split: test | |
| type: BeIR/cqadupstack | |
| metrics: | |
| - type: map_at_1 | |
| value: 41.637 | |
| - type: map_at_10 | |
| value: 55.162 | |
| - type: map_at_100 | |
| value: 56.142 | |
| - type: map_at_1000 | |
| value: 56.188 | |
| - type: map_at_3 | |
| value: 51.564 | |
| - type: map_at_5 | |
| value: 53.696 | |
| - type: mrr_at_1 | |
| value: 47.524 | |
| - type: mrr_at_10 | |
| value: 58.243 | |
| - type: mrr_at_100 | |
| value: 58.879999999999995 | |
| - type: mrr_at_1000 | |
| value: 58.9 | |
| - type: mrr_at_3 | |
| value: 55.69499999999999 | |
| - type: mrr_at_5 | |
| value: 57.284 | |
| - type: ndcg_at_1 | |
| value: 47.524 | |
| - type: ndcg_at_10 | |
| value: 61.305 | |
| - type: ndcg_at_100 | |
| value: 65.077 | |
| - type: ndcg_at_1000 | |
| value: 65.941 | |
| - type: ndcg_at_3 | |
| value: 55.422000000000004 | |
| - type: ndcg_at_5 | |
| value: 58.516 | |
| - type: precision_at_1 | |
| value: 47.524 | |
| - type: precision_at_10 | |
| value: 9.918000000000001 | |
| - type: precision_at_100 | |
| value: 1.276 | |
| - type: precision_at_1000 | |
| value: 0.13899999999999998 | |
| - type: precision_at_3 | |
| value: 24.765 | |
| - type: precision_at_5 | |
| value: 17.204 | |
| - type: recall_at_1 | |
| value: 41.637 | |
| - type: recall_at_10 | |
| value: 76.185 | |
| - type: recall_at_100 | |
| value: 92.149 | |
| - type: recall_at_1000 | |
| value: 98.199 | |
| - type: recall_at_3 | |
| value: 60.856 | |
| - type: recall_at_5 | |
| value: 68.25099999999999 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB CQADupstackGisRetrieval | |
| revision: 5003b3064772da1887988e05400cf3806fe491f2 | |
| split: test | |
| type: BeIR/cqadupstack | |
| metrics: | |
| - type: map_at_1 | |
| value: 26.27 | |
| - type: map_at_10 | |
| value: 37.463 | |
| - type: map_at_100 | |
| value: 38.434000000000005 | |
| - type: map_at_1000 | |
| value: 38.509 | |
| - type: map_at_3 | |
| value: 34.226 | |
| - type: map_at_5 | |
| value: 36.161 | |
| - type: mrr_at_1 | |
| value: 28.588 | |
| - type: mrr_at_10 | |
| value: 39.383 | |
| - type: mrr_at_100 | |
| value: 40.23 | |
| - type: mrr_at_1000 | |
| value: 40.281 | |
| - type: mrr_at_3 | |
| value: 36.422 | |
| - type: mrr_at_5 | |
| value: 38.252 | |
| - type: ndcg_at_1 | |
| value: 28.588 | |
| - type: ndcg_at_10 | |
| value: 43.511 | |
| - type: ndcg_at_100 | |
| value: 48.274 | |
| - type: ndcg_at_1000 | |
| value: 49.975 | |
| - type: ndcg_at_3 | |
| value: 37.319 | |
| - type: ndcg_at_5 | |
| value: 40.568 | |
| - type: precision_at_1 | |
| value: 28.588 | |
| - type: precision_at_10 | |
| value: 6.893000000000001 | |
| - type: precision_at_100 | |
| value: 0.9900000000000001 | |
| - type: precision_at_1000 | |
| value: 0.117 | |
| - type: precision_at_3 | |
| value: 16.347 | |
| - type: precision_at_5 | |
| value: 11.661000000000001 | |
| - type: recall_at_1 | |
| value: 26.27 | |
| - type: recall_at_10 | |
| value: 60.284000000000006 | |
| - type: recall_at_100 | |
| value: 81.902 | |
| - type: recall_at_1000 | |
| value: 94.43 | |
| - type: recall_at_3 | |
| value: 43.537 | |
| - type: recall_at_5 | |
| value: 51.475 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB CQADupstackMathematicaRetrieval | |
| revision: 90fceea13679c63fe563ded68f3b6f06e50061de | |
| split: test | |
| type: BeIR/cqadupstack | |
| metrics: | |
| - type: map_at_1 | |
| value: 18.168 | |
| - type: map_at_10 | |
| value: 28.410000000000004 | |
| - type: map_at_100 | |
| value: 29.78 | |
| - type: map_at_1000 | |
| value: 29.892999999999997 | |
| - type: map_at_3 | |
| value: 25.238 | |
| - type: map_at_5 | |
| value: 26.96 | |
| - type: mrr_at_1 | |
| value: 23.507 | |
| - type: mrr_at_10 | |
| value: 33.382 | |
| - type: mrr_at_100 | |
| value: 34.404 | |
| - type: mrr_at_1000 | |
| value: 34.467999999999996 | |
| - type: mrr_at_3 | |
| value: 30.637999999999998 | |
| - type: mrr_at_5 | |
| value: 32.199 | |
| - type: ndcg_at_1 | |
| value: 23.507 | |
| - type: ndcg_at_10 | |
| value: 34.571000000000005 | |
| - type: ndcg_at_100 | |
| value: 40.663 | |
| - type: ndcg_at_1000 | |
| value: 43.236000000000004 | |
| - type: ndcg_at_3 | |
| value: 29.053 | |
| - type: ndcg_at_5 | |
| value: 31.563999999999997 | |
| - type: precision_at_1 | |
| value: 23.507 | |
| - type: precision_at_10 | |
| value: 6.654 | |
| - type: precision_at_100 | |
| value: 1.113 | |
| - type: precision_at_1000 | |
| value: 0.146 | |
| - type: precision_at_3 | |
| value: 14.427999999999999 | |
| - type: precision_at_5 | |
| value: 10.498000000000001 | |
| - type: recall_at_1 | |
| value: 18.168 | |
| - type: recall_at_10 | |
| value: 48.443000000000005 | |
| - type: recall_at_100 | |
| value: 74.47 | |
| - type: recall_at_1000 | |
| value: 92.494 | |
| - type: recall_at_3 | |
| value: 33.379999999999995 | |
| - type: recall_at_5 | |
| value: 39.76 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB CQADupstackPhysicsRetrieval | |
| revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 | |
| split: test | |
| type: BeIR/cqadupstack | |
| metrics: | |
| - type: map_at_1 | |
| value: 32.39 | |
| - type: map_at_10 | |
| value: 44.479 | |
| - type: map_at_100 | |
| value: 45.977000000000004 | |
| - type: map_at_1000 | |
| value: 46.087 | |
| - type: map_at_3 | |
| value: 40.976 | |
| - type: map_at_5 | |
| value: 43.038 | |
| - type: mrr_at_1 | |
| value: 40.135 | |
| - type: mrr_at_10 | |
| value: 50.160000000000004 | |
| - type: mrr_at_100 | |
| value: 51.052 | |
| - type: mrr_at_1000 | |
| value: 51.087 | |
| - type: mrr_at_3 | |
| value: 47.818 | |
| - type: mrr_at_5 | |
| value: 49.171 | |
| - type: ndcg_at_1 | |
| value: 40.135 | |
| - type: ndcg_at_10 | |
| value: 50.731 | |
| - type: ndcg_at_100 | |
| value: 56.452000000000005 | |
| - type: ndcg_at_1000 | |
| value: 58.123000000000005 | |
| - type: ndcg_at_3 | |
| value: 45.507 | |
| - type: ndcg_at_5 | |
| value: 48.11 | |
| - type: precision_at_1 | |
| value: 40.135 | |
| - type: precision_at_10 | |
| value: 9.192 | |
| - type: precision_at_100 | |
| value: 1.397 | |
| - type: precision_at_1000 | |
| value: 0.169 | |
| - type: precision_at_3 | |
| value: 21.816 | |
| - type: precision_at_5 | |
| value: 15.476 | |
| - type: recall_at_1 | |
| value: 32.39 | |
| - type: recall_at_10 | |
| value: 63.597 | |
| - type: recall_at_100 | |
| value: 86.737 | |
| - type: recall_at_1000 | |
| value: 97.039 | |
| - type: recall_at_3 | |
| value: 48.906 | |
| - type: recall_at_5 | |
| value: 55.659000000000006 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB CQADupstackProgrammersRetrieval | |
| revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 | |
| split: test | |
| type: BeIR/cqadupstack | |
| metrics: | |
| - type: map_at_1 | |
| value: 28.397 | |
| - type: map_at_10 | |
| value: 39.871 | |
| - type: map_at_100 | |
| value: 41.309000000000005 | |
| - type: map_at_1000 | |
| value: 41.409 | |
| - type: map_at_3 | |
| value: 36.047000000000004 | |
| - type: map_at_5 | |
| value: 38.104 | |
| - type: mrr_at_1 | |
| value: 34.703 | |
| - type: mrr_at_10 | |
| value: 44.773 | |
| - type: mrr_at_100 | |
| value: 45.64 | |
| - type: mrr_at_1000 | |
| value: 45.678999999999995 | |
| - type: mrr_at_3 | |
| value: 41.705 | |
| - type: mrr_at_5 | |
| value: 43.406 | |
| - type: ndcg_at_1 | |
| value: 34.703 | |
| - type: ndcg_at_10 | |
| value: 46.271 | |
| - type: ndcg_at_100 | |
| value: 52.037 | |
| - type: ndcg_at_1000 | |
| value: 53.81700000000001 | |
| - type: ndcg_at_3 | |
| value: 39.966 | |
| - type: ndcg_at_5 | |
| value: 42.801 | |
| - type: precision_at_1 | |
| value: 34.703 | |
| - type: precision_at_10 | |
| value: 8.744 | |
| - type: precision_at_100 | |
| value: 1.348 | |
| - type: precision_at_1000 | |
| value: 0.167 | |
| - type: precision_at_3 | |
| value: 19.102 | |
| - type: precision_at_5 | |
| value: 13.836 | |
| - type: recall_at_1 | |
| value: 28.397 | |
| - type: recall_at_10 | |
| value: 60.299 | |
| - type: recall_at_100 | |
| value: 84.595 | |
| - type: recall_at_1000 | |
| value: 96.155 | |
| - type: recall_at_3 | |
| value: 43.065 | |
| - type: recall_at_5 | |
| value: 50.371 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB CQADupstackRetrieval | |
| revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 | |
| split: test | |
| type: BeIR/cqadupstack | |
| metrics: | |
| - type: map_at_1 | |
| value: 28.044333333333338 | |
| - type: map_at_10 | |
| value: 38.78691666666666 | |
| - type: map_at_100 | |
| value: 40.113 | |
| - type: map_at_1000 | |
| value: 40.22125 | |
| - type: map_at_3 | |
| value: 35.52966666666667 | |
| - type: map_at_5 | |
| value: 37.372749999999996 | |
| - type: mrr_at_1 | |
| value: 33.159083333333335 | |
| - type: mrr_at_10 | |
| value: 42.913583333333335 | |
| - type: mrr_at_100 | |
| value: 43.7845 | |
| - type: mrr_at_1000 | |
| value: 43.830333333333336 | |
| - type: mrr_at_3 | |
| value: 40.29816666666667 | |
| - type: mrr_at_5 | |
| value: 41.81366666666667 | |
| - type: ndcg_at_1 | |
| value: 33.159083333333335 | |
| - type: ndcg_at_10 | |
| value: 44.75750000000001 | |
| - type: ndcg_at_100 | |
| value: 50.13658333333334 | |
| - type: ndcg_at_1000 | |
| value: 52.037 | |
| - type: ndcg_at_3 | |
| value: 39.34258333333334 | |
| - type: ndcg_at_5 | |
| value: 41.93708333333333 | |
| - type: precision_at_1 | |
| value: 33.159083333333335 | |
| - type: precision_at_10 | |
| value: 7.952416666666667 | |
| - type: precision_at_100 | |
| value: 1.2571666666666668 | |
| - type: precision_at_1000 | |
| value: 0.16099999999999998 | |
| - type: precision_at_3 | |
| value: 18.303833333333337 | |
| - type: precision_at_5 | |
| value: 13.057083333333333 | |
| - type: recall_at_1 | |
| value: 28.044333333333338 | |
| - type: recall_at_10 | |
| value: 58.237249999999996 | |
| - type: recall_at_100 | |
| value: 81.35391666666666 | |
| - type: recall_at_1000 | |
| value: 94.21283333333334 | |
| - type: recall_at_3 | |
| value: 43.32341666666667 | |
| - type: recall_at_5 | |
| value: 49.94908333333333 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB CQADupstackStatsRetrieval | |
| revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a | |
| split: test | |
| type: BeIR/cqadupstack | |
| metrics: | |
| - type: map_at_1 | |
| value: 27.838 | |
| - type: map_at_10 | |
| value: 36.04 | |
| - type: map_at_100 | |
| value: 37.113 | |
| - type: map_at_1000 | |
| value: 37.204 | |
| - type: map_at_3 | |
| value: 33.585 | |
| - type: map_at_5 | |
| value: 34.845 | |
| - type: mrr_at_1 | |
| value: 30.982 | |
| - type: mrr_at_10 | |
| value: 39.105000000000004 | |
| - type: mrr_at_100 | |
| value: 39.98 | |
| - type: mrr_at_1000 | |
| value: 40.042 | |
| - type: mrr_at_3 | |
| value: 36.912 | |
| - type: mrr_at_5 | |
| value: 38.062000000000005 | |
| - type: ndcg_at_1 | |
| value: 30.982 | |
| - type: ndcg_at_10 | |
| value: 40.982 | |
| - type: ndcg_at_100 | |
| value: 46.092 | |
| - type: ndcg_at_1000 | |
| value: 48.25 | |
| - type: ndcg_at_3 | |
| value: 36.41 | |
| - type: ndcg_at_5 | |
| value: 38.379999999999995 | |
| - type: precision_at_1 | |
| value: 30.982 | |
| - type: precision_at_10 | |
| value: 6.534 | |
| - type: precision_at_100 | |
| value: 0.9820000000000001 | |
| - type: precision_at_1000 | |
| value: 0.124 | |
| - type: precision_at_3 | |
| value: 15.745999999999999 | |
| - type: precision_at_5 | |
| value: 10.828 | |
| - type: recall_at_1 | |
| value: 27.838 | |
| - type: recall_at_10 | |
| value: 52.971000000000004 | |
| - type: recall_at_100 | |
| value: 76.357 | |
| - type: recall_at_1000 | |
| value: 91.973 | |
| - type: recall_at_3 | |
| value: 40.157 | |
| - type: recall_at_5 | |
| value: 45.147999999999996 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB CQADupstackTexRetrieval | |
| revision: 46989137a86843e03a6195de44b09deda022eec7 | |
| split: test | |
| type: BeIR/cqadupstack | |
| metrics: | |
| - type: map_at_1 | |
| value: 19.059 | |
| - type: map_at_10 | |
| value: 27.454 | |
| - type: map_at_100 | |
| value: 28.736 | |
| - type: map_at_1000 | |
| value: 28.865000000000002 | |
| - type: map_at_3 | |
| value: 24.773999999999997 | |
| - type: map_at_5 | |
| value: 26.266000000000002 | |
| - type: mrr_at_1 | |
| value: 23.125 | |
| - type: mrr_at_10 | |
| value: 31.267 | |
| - type: mrr_at_100 | |
| value: 32.32 | |
| - type: mrr_at_1000 | |
| value: 32.394 | |
| - type: mrr_at_3 | |
| value: 28.894 | |
| - type: mrr_at_5 | |
| value: 30.281000000000002 | |
| - type: ndcg_at_1 | |
| value: 23.125 | |
| - type: ndcg_at_10 | |
| value: 32.588 | |
| - type: ndcg_at_100 | |
| value: 38.432 | |
| - type: ndcg_at_1000 | |
| value: 41.214 | |
| - type: ndcg_at_3 | |
| value: 27.938000000000002 | |
| - type: ndcg_at_5 | |
| value: 30.127 | |
| - type: precision_at_1 | |
| value: 23.125 | |
| - type: precision_at_10 | |
| value: 5.9639999999999995 | |
| - type: precision_at_100 | |
| value: 1.047 | |
| - type: precision_at_1000 | |
| value: 0.148 | |
| - type: precision_at_3 | |
| value: 13.294 | |
| - type: precision_at_5 | |
| value: 9.628 | |
| - type: recall_at_1 | |
| value: 19.059 | |
| - type: recall_at_10 | |
| value: 44.25 | |
| - type: recall_at_100 | |
| value: 69.948 | |
| - type: recall_at_1000 | |
| value: 89.35300000000001 | |
| - type: recall_at_3 | |
| value: 31.114000000000004 | |
| - type: recall_at_5 | |
| value: 36.846000000000004 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB CQADupstackUnixRetrieval | |
| revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 | |
| split: test | |
| type: BeIR/cqadupstack | |
| metrics: | |
| - type: map_at_1 | |
| value: 28.355999999999998 | |
| - type: map_at_10 | |
| value: 39.055 | |
| - type: map_at_100 | |
| value: 40.486 | |
| - type: map_at_1000 | |
| value: 40.571 | |
| - type: map_at_3 | |
| value: 35.69 | |
| - type: map_at_5 | |
| value: 37.605 | |
| - type: mrr_at_1 | |
| value: 33.302 | |
| - type: mrr_at_10 | |
| value: 42.986000000000004 | |
| - type: mrr_at_100 | |
| value: 43.957 | |
| - type: mrr_at_1000 | |
| value: 43.996 | |
| - type: mrr_at_3 | |
| value: 40.111999999999995 | |
| - type: mrr_at_5 | |
| value: 41.735 | |
| - type: ndcg_at_1 | |
| value: 33.302 | |
| - type: ndcg_at_10 | |
| value: 44.962999999999994 | |
| - type: ndcg_at_100 | |
| value: 50.917 | |
| - type: ndcg_at_1000 | |
| value: 52.622 | |
| - type: ndcg_at_3 | |
| value: 39.182 | |
| - type: ndcg_at_5 | |
| value: 41.939 | |
| - type: precision_at_1 | |
| value: 33.302 | |
| - type: precision_at_10 | |
| value: 7.779999999999999 | |
| - type: precision_at_100 | |
| value: 1.203 | |
| - type: precision_at_1000 | |
| value: 0.145 | |
| - type: precision_at_3 | |
| value: 18.035 | |
| - type: precision_at_5 | |
| value: 12.873000000000001 | |
| - type: recall_at_1 | |
| value: 28.355999999999998 | |
| - type: recall_at_10 | |
| value: 58.782000000000004 | |
| - type: recall_at_100 | |
| value: 84.02199999999999 | |
| - type: recall_at_1000 | |
| value: 95.511 | |
| - type: recall_at_3 | |
| value: 43.126999999999995 | |
| - type: recall_at_5 | |
| value: 50.14999999999999 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB CQADupstackWebmastersRetrieval | |
| revision: 160c094312a0e1facb97e55eeddb698c0abe3571 | |
| split: test | |
| type: BeIR/cqadupstack | |
| metrics: | |
| - type: map_at_1 | |
| value: 27.391 | |
| - type: map_at_10 | |
| value: 37.523 | |
| - type: map_at_100 | |
| value: 39.312000000000005 | |
| - type: map_at_1000 | |
| value: 39.54 | |
| - type: map_at_3 | |
| value: 34.231 | |
| - type: map_at_5 | |
| value: 36.062 | |
| - type: mrr_at_1 | |
| value: 32.016 | |
| - type: mrr_at_10 | |
| value: 41.747 | |
| - type: mrr_at_100 | |
| value: 42.812 | |
| - type: mrr_at_1000 | |
| value: 42.844 | |
| - type: mrr_at_3 | |
| value: 39.129999999999995 | |
| - type: mrr_at_5 | |
| value: 40.524 | |
| - type: ndcg_at_1 | |
| value: 32.016 | |
| - type: ndcg_at_10 | |
| value: 43.826 | |
| - type: ndcg_at_100 | |
| value: 50.373999999999995 | |
| - type: ndcg_at_1000 | |
| value: 52.318 | |
| - type: ndcg_at_3 | |
| value: 38.479 | |
| - type: ndcg_at_5 | |
| value: 40.944 | |
| - type: precision_at_1 | |
| value: 32.016 | |
| - type: precision_at_10 | |
| value: 8.280999999999999 | |
| - type: precision_at_100 | |
| value: 1.6760000000000002 | |
| - type: precision_at_1000 | |
| value: 0.25 | |
| - type: precision_at_3 | |
| value: 18.05 | |
| - type: precision_at_5 | |
| value: 13.083 | |
| - type: recall_at_1 | |
| value: 27.391 | |
| - type: recall_at_10 | |
| value: 56.928999999999995 | |
| - type: recall_at_100 | |
| value: 85.169 | |
| - type: recall_at_1000 | |
| value: 96.665 | |
| - type: recall_at_3 | |
| value: 42.264 | |
| - type: recall_at_5 | |
| value: 48.556 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB CQADupstackWordpressRetrieval | |
| revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 | |
| split: test | |
| type: BeIR/cqadupstack | |
| metrics: | |
| - type: map_at_1 | |
| value: 18.398 | |
| - type: map_at_10 | |
| value: 27.929 | |
| - type: map_at_100 | |
| value: 29.032999999999998 | |
| - type: map_at_1000 | |
| value: 29.126 | |
| - type: map_at_3 | |
| value: 25.070999999999998 | |
| - type: map_at_5 | |
| value: 26.583000000000002 | |
| - type: mrr_at_1 | |
| value: 19.963 | |
| - type: mrr_at_10 | |
| value: 29.997 | |
| - type: mrr_at_100 | |
| value: 30.9 | |
| - type: mrr_at_1000 | |
| value: 30.972 | |
| - type: mrr_at_3 | |
| value: 27.264 | |
| - type: mrr_at_5 | |
| value: 28.826 | |
| - type: ndcg_at_1 | |
| value: 19.963 | |
| - type: ndcg_at_10 | |
| value: 33.678999999999995 | |
| - type: ndcg_at_100 | |
| value: 38.931 | |
| - type: ndcg_at_1000 | |
| value: 41.379 | |
| - type: ndcg_at_3 | |
| value: 28.000000000000004 | |
| - type: ndcg_at_5 | |
| value: 30.637999999999998 | |
| - type: precision_at_1 | |
| value: 19.963 | |
| - type: precision_at_10 | |
| value: 5.7299999999999995 | |
| - type: precision_at_100 | |
| value: 0.902 | |
| - type: precision_at_1000 | |
| value: 0.122 | |
| - type: precision_at_3 | |
| value: 12.631 | |
| - type: precision_at_5 | |
| value: 9.057 | |
| - type: recall_at_1 | |
| value: 18.398 | |
| - type: recall_at_10 | |
| value: 49.254 | |
| - type: recall_at_100 | |
| value: 73.182 | |
| - type: recall_at_1000 | |
| value: 91.637 | |
| - type: recall_at_3 | |
| value: 34.06 | |
| - type: recall_at_5 | |
| value: 40.416000000000004 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB ClimateFEVER | |
| revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 | |
| split: test | |
| type: mteb/climate-fever | |
| metrics: | |
| - type: map_at_1 | |
| value: 19.681 | |
| - type: map_at_10 | |
| value: 32.741 | |
| - type: map_at_100 | |
| value: 34.811 | |
| - type: map_at_1000 | |
| value: 35.003 | |
| - type: map_at_3 | |
| value: 27.697 | |
| - type: map_at_5 | |
| value: 30.372 | |
| - type: mrr_at_1 | |
| value: 44.951 | |
| - type: mrr_at_10 | |
| value: 56.34400000000001 | |
| - type: mrr_at_100 | |
| value: 56.961 | |
| - type: mrr_at_1000 | |
| value: 56.987 | |
| - type: mrr_at_3 | |
| value: 53.681 | |
| - type: mrr_at_5 | |
| value: 55.407 | |
| - type: ndcg_at_1 | |
| value: 44.951 | |
| - type: ndcg_at_10 | |
| value: 42.905 | |
| - type: ndcg_at_100 | |
| value: 49.95 | |
| - type: ndcg_at_1000 | |
| value: 52.917 | |
| - type: ndcg_at_3 | |
| value: 36.815 | |
| - type: ndcg_at_5 | |
| value: 38.817 | |
| - type: precision_at_1 | |
| value: 44.951 | |
| - type: precision_at_10 | |
| value: 12.989999999999998 | |
| - type: precision_at_100 | |
| value: 2.068 | |
| - type: precision_at_1000 | |
| value: 0.263 | |
| - type: precision_at_3 | |
| value: 27.275 | |
| - type: precision_at_5 | |
| value: 20.365 | |
| - type: recall_at_1 | |
| value: 19.681 | |
| - type: recall_at_10 | |
| value: 48.272999999999996 | |
| - type: recall_at_100 | |
| value: 71.87400000000001 | |
| - type: recall_at_1000 | |
| value: 87.929 | |
| - type: recall_at_3 | |
| value: 32.653999999999996 | |
| - type: recall_at_5 | |
| value: 39.364 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB DBPedia | |
| revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 | |
| split: test | |
| type: mteb/dbpedia | |
| metrics: | |
| - type: map_at_1 | |
| value: 10.231 | |
| - type: map_at_10 | |
| value: 22.338 | |
| - type: map_at_100 | |
| value: 31.927 | |
| - type: map_at_1000 | |
| value: 33.87 | |
| - type: map_at_3 | |
| value: 15.559999999999999 | |
| - type: map_at_5 | |
| value: 18.239 | |
| - type: mrr_at_1 | |
| value: 75.0 | |
| - type: mrr_at_10 | |
| value: 81.303 | |
| - type: mrr_at_100 | |
| value: 81.523 | |
| - type: mrr_at_1000 | |
| value: 81.53 | |
| - type: mrr_at_3 | |
| value: 80.083 | |
| - type: mrr_at_5 | |
| value: 80.758 | |
| - type: ndcg_at_1 | |
| value: 64.625 | |
| - type: ndcg_at_10 | |
| value: 48.687000000000005 | |
| - type: ndcg_at_100 | |
| value: 52.791 | |
| - type: ndcg_at_1000 | |
| value: 60.041999999999994 | |
| - type: ndcg_at_3 | |
| value: 53.757999999999996 | |
| - type: ndcg_at_5 | |
| value: 50.76500000000001 | |
| - type: precision_at_1 | |
| value: 75.0 | |
| - type: precision_at_10 | |
| value: 38.3 | |
| - type: precision_at_100 | |
| value: 12.025 | |
| - type: precision_at_1000 | |
| value: 2.3970000000000002 | |
| - type: precision_at_3 | |
| value: 55.417 | |
| - type: precision_at_5 | |
| value: 47.5 | |
| - type: recall_at_1 | |
| value: 10.231 | |
| - type: recall_at_10 | |
| value: 27.697 | |
| - type: recall_at_100 | |
| value: 57.409 | |
| - type: recall_at_1000 | |
| value: 80.547 | |
| - type: recall_at_3 | |
| value: 16.668 | |
| - type: recall_at_5 | |
| value: 20.552 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB EmotionClassification | |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 | |
| split: test | |
| type: mteb/emotion | |
| metrics: | |
| - type: accuracy | |
| value: 61.365 | |
| - type: f1 | |
| value: 56.7540827912991 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB FEVER | |
| revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 | |
| split: test | |
| type: mteb/fever | |
| metrics: | |
| - type: map_at_1 | |
| value: 83.479 | |
| - type: map_at_10 | |
| value: 88.898 | |
| - type: map_at_100 | |
| value: 89.11 | |
| - type: map_at_1000 | |
| value: 89.12400000000001 | |
| - type: map_at_3 | |
| value: 88.103 | |
| - type: map_at_5 | |
| value: 88.629 | |
| - type: mrr_at_1 | |
| value: 89.934 | |
| - type: mrr_at_10 | |
| value: 93.91000000000001 | |
| - type: mrr_at_100 | |
| value: 93.937 | |
| - type: mrr_at_1000 | |
| value: 93.938 | |
| - type: mrr_at_3 | |
| value: 93.62700000000001 | |
| - type: mrr_at_5 | |
| value: 93.84599999999999 | |
| - type: ndcg_at_1 | |
| value: 89.934 | |
| - type: ndcg_at_10 | |
| value: 91.574 | |
| - type: ndcg_at_100 | |
| value: 92.238 | |
| - type: ndcg_at_1000 | |
| value: 92.45 | |
| - type: ndcg_at_3 | |
| value: 90.586 | |
| - type: ndcg_at_5 | |
| value: 91.16300000000001 | |
| - type: precision_at_1 | |
| value: 89.934 | |
| - type: precision_at_10 | |
| value: 10.555 | |
| - type: precision_at_100 | |
| value: 1.1159999999999999 | |
| - type: precision_at_1000 | |
| value: 0.11499999999999999 | |
| - type: precision_at_3 | |
| value: 33.588 | |
| - type: precision_at_5 | |
| value: 20.642 | |
| - type: recall_at_1 | |
| value: 83.479 | |
| - type: recall_at_10 | |
| value: 94.971 | |
| - type: recall_at_100 | |
| value: 97.397 | |
| - type: recall_at_1000 | |
| value: 98.666 | |
| - type: recall_at_3 | |
| value: 92.24799999999999 | |
| - type: recall_at_5 | |
| value: 93.797 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB FiQA2018 | |
| revision: 27a168819829fe9bcd655c2df245fb19452e8e06 | |
| split: test | |
| type: mteb/fiqa | |
| metrics: | |
| - type: map_at_1 | |
| value: 27.16 | |
| - type: map_at_10 | |
| value: 45.593 | |
| - type: map_at_100 | |
| value: 47.762 | |
| - type: map_at_1000 | |
| value: 47.899 | |
| - type: map_at_3 | |
| value: 39.237 | |
| - type: map_at_5 | |
| value: 42.970000000000006 | |
| - type: mrr_at_1 | |
| value: 52.623 | |
| - type: mrr_at_10 | |
| value: 62.637 | |
| - type: mrr_at_100 | |
| value: 63.169 | |
| - type: mrr_at_1000 | |
| value: 63.185 | |
| - type: mrr_at_3 | |
| value: 59.928000000000004 | |
| - type: mrr_at_5 | |
| value: 61.702999999999996 | |
| - type: ndcg_at_1 | |
| value: 52.623 | |
| - type: ndcg_at_10 | |
| value: 54.701 | |
| - type: ndcg_at_100 | |
| value: 61.263 | |
| - type: ndcg_at_1000 | |
| value: 63.134 | |
| - type: ndcg_at_3 | |
| value: 49.265 | |
| - type: ndcg_at_5 | |
| value: 51.665000000000006 | |
| - type: precision_at_1 | |
| value: 52.623 | |
| - type: precision_at_10 | |
| value: 15.185 | |
| - type: precision_at_100 | |
| value: 2.202 | |
| - type: precision_at_1000 | |
| value: 0.254 | |
| - type: precision_at_3 | |
| value: 32.767 | |
| - type: precision_at_5 | |
| value: 24.722 | |
| - type: recall_at_1 | |
| value: 27.16 | |
| - type: recall_at_10 | |
| value: 63.309000000000005 | |
| - type: recall_at_100 | |
| value: 86.722 | |
| - type: recall_at_1000 | |
| value: 97.505 | |
| - type: recall_at_3 | |
| value: 45.045 | |
| - type: recall_at_5 | |
| value: 54.02400000000001 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB HotpotQA | |
| revision: ab518f4d6fcca38d87c25209f94beba119d02014 | |
| split: test | |
| type: mteb/hotpotqa | |
| metrics: | |
| - type: map_at_1 | |
| value: 42.573 | |
| - type: map_at_10 | |
| value: 59.373 | |
| - type: map_at_100 | |
| value: 60.292 | |
| - type: map_at_1000 | |
| value: 60.358999999999995 | |
| - type: map_at_3 | |
| value: 56.159000000000006 | |
| - type: map_at_5 | |
| value: 58.123999999999995 | |
| - type: mrr_at_1 | |
| value: 85.14500000000001 | |
| - type: mrr_at_10 | |
| value: 89.25999999999999 | |
| - type: mrr_at_100 | |
| value: 89.373 | |
| - type: mrr_at_1000 | |
| value: 89.377 | |
| - type: mrr_at_3 | |
| value: 88.618 | |
| - type: mrr_at_5 | |
| value: 89.036 | |
| - type: ndcg_at_1 | |
| value: 85.14500000000001 | |
| - type: ndcg_at_10 | |
| value: 68.95 | |
| - type: ndcg_at_100 | |
| value: 71.95 | |
| - type: ndcg_at_1000 | |
| value: 73.232 | |
| - type: ndcg_at_3 | |
| value: 64.546 | |
| - type: ndcg_at_5 | |
| value: 66.945 | |
| - type: precision_at_1 | |
| value: 85.14500000000001 | |
| - type: precision_at_10 | |
| value: 13.865 | |
| - type: precision_at_100 | |
| value: 1.619 | |
| - type: precision_at_1000 | |
| value: 0.179 | |
| - type: precision_at_3 | |
| value: 39.703 | |
| - type: precision_at_5 | |
| value: 25.718000000000004 | |
| - type: recall_at_1 | |
| value: 42.573 | |
| - type: recall_at_10 | |
| value: 69.325 | |
| - type: recall_at_100 | |
| value: 80.932 | |
| - type: recall_at_1000 | |
| value: 89.446 | |
| - type: recall_at_3 | |
| value: 59.553999999999995 | |
| - type: recall_at_5 | |
| value: 64.294 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB ImdbClassification | |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 | |
| split: test | |
| type: mteb/imdb | |
| metrics: | |
| - type: accuracy | |
| value: 95.8336 | |
| - type: ap | |
| value: 93.78862962194073 | |
| - type: f1 | |
| value: 95.83192650728371 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB MSMARCO | |
| revision: c5a29a104738b98a9e76336939199e264163d4a0 | |
| split: dev | |
| type: mteb/msmarco | |
| metrics: | |
| - type: map_at_1 | |
| value: 23.075000000000003 | |
| - type: map_at_10 | |
| value: 36.102000000000004 | |
| - type: map_at_100 | |
| value: 37.257 | |
| - type: map_at_1000 | |
| value: 37.3 | |
| - type: map_at_3 | |
| value: 32.144 | |
| - type: map_at_5 | |
| value: 34.359 | |
| - type: mrr_at_1 | |
| value: 23.711 | |
| - type: mrr_at_10 | |
| value: 36.671 | |
| - type: mrr_at_100 | |
| value: 37.763999999999996 | |
| - type: mrr_at_1000 | |
| value: 37.801 | |
| - type: mrr_at_3 | |
| value: 32.775 | |
| - type: mrr_at_5 | |
| value: 34.977000000000004 | |
| - type: ndcg_at_1 | |
| value: 23.711 | |
| - type: ndcg_at_10 | |
| value: 43.361 | |
| - type: ndcg_at_100 | |
| value: 48.839 | |
| - type: ndcg_at_1000 | |
| value: 49.88 | |
| - type: ndcg_at_3 | |
| value: 35.269 | |
| - type: ndcg_at_5 | |
| value: 39.224 | |
| - type: precision_at_1 | |
| value: 23.711 | |
| - type: precision_at_10 | |
| value: 6.866999999999999 | |
| - type: precision_at_100 | |
| value: 0.96 | |
| - type: precision_at_1000 | |
| value: 0.105 | |
| - type: precision_at_3 | |
| value: 15.096000000000002 | |
| - type: precision_at_5 | |
| value: 11.083 | |
| - type: recall_at_1 | |
| value: 23.075000000000003 | |
| - type: recall_at_10 | |
| value: 65.756 | |
| - type: recall_at_100 | |
| value: 90.88199999999999 | |
| - type: recall_at_1000 | |
| value: 98.739 | |
| - type: recall_at_3 | |
| value: 43.691 | |
| - type: recall_at_5 | |
| value: 53.15800000000001 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: en | |
| name: MTEB MTOPDomainClassification (en) | |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf | |
| split: test | |
| type: mteb/mtop_domain | |
| metrics: | |
| - type: accuracy | |
| value: 97.69493844049248 | |
| - type: f1 | |
| value: 97.55048089616261 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: en | |
| name: MTEB MTOPIntentClassification (en) | |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba | |
| split: test | |
| type: mteb/mtop_intent | |
| metrics: | |
| - type: accuracy | |
| value: 88.75968992248062 | |
| - type: f1 | |
| value: 72.26321223399123 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: en | |
| name: MTEB MassiveIntentClassification (en) | |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 | |
| split: test | |
| type: mteb/amazon_massive_intent | |
| metrics: | |
| - type: accuracy | |
| value: 82.40080699394754 | |
| - type: f1 | |
| value: 79.62590029057968 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: en | |
| name: MTEB MassiveScenarioClassification (en) | |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 | |
| split: test | |
| type: mteb/amazon_massive_scenario | |
| metrics: | |
| - type: accuracy | |
| value: 84.49562878278414 | |
| - type: f1 | |
| value: 84.0040193313333 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB MedrxivClusteringP2P | |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 | |
| split: test | |
| type: mteb/medrxiv-clustering-p2p | |
| metrics: | |
| - type: v_measure | |
| value: 39.386760057101945 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB MedrxivClusteringS2S | |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 | |
| split: test | |
| type: mteb/medrxiv-clustering-s2s | |
| metrics: | |
| - type: v_measure | |
| value: 37.89687154075537 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB MindSmallReranking | |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 | |
| split: test | |
| type: mteb/mind_small | |
| metrics: | |
| - type: map | |
| value: 33.94151656057482 | |
| - type: mrr | |
| value: 35.32684700746953 | |
| task: | |
| type: Reranking | |
| - dataset: | |
| config: default | |
| name: MTEB NFCorpus | |
| revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 | |
| split: test | |
| type: mteb/nfcorpus | |
| metrics: | |
| - type: map_at_1 | |
| value: 6.239999999999999 | |
| - type: map_at_10 | |
| value: 14.862 | |
| - type: map_at_100 | |
| value: 18.955 | |
| - type: map_at_1000 | |
| value: 20.694000000000003 | |
| - type: map_at_3 | |
| value: 10.683 | |
| - type: map_at_5 | |
| value: 12.674 | |
| - type: mrr_at_1 | |
| value: 50.15500000000001 | |
| - type: mrr_at_10 | |
| value: 59.697 | |
| - type: mrr_at_100 | |
| value: 60.095 | |
| - type: mrr_at_1000 | |
| value: 60.129999999999995 | |
| - type: mrr_at_3 | |
| value: 58.35900000000001 | |
| - type: mrr_at_5 | |
| value: 58.839 | |
| - type: ndcg_at_1 | |
| value: 48.452 | |
| - type: ndcg_at_10 | |
| value: 39.341 | |
| - type: ndcg_at_100 | |
| value: 35.866 | |
| - type: ndcg_at_1000 | |
| value: 45.111000000000004 | |
| - type: ndcg_at_3 | |
| value: 44.527 | |
| - type: ndcg_at_5 | |
| value: 42.946 | |
| - type: precision_at_1 | |
| value: 50.15500000000001 | |
| - type: precision_at_10 | |
| value: 29.536 | |
| - type: precision_at_100 | |
| value: 9.142 | |
| - type: precision_at_1000 | |
| value: 2.2849999999999997 | |
| - type: precision_at_3 | |
| value: 41.899 | |
| - type: precision_at_5 | |
| value: 37.647000000000006 | |
| - type: recall_at_1 | |
| value: 6.239999999999999 | |
| - type: recall_at_10 | |
| value: 19.278000000000002 | |
| - type: recall_at_100 | |
| value: 36.074 | |
| - type: recall_at_1000 | |
| value: 70.017 | |
| - type: recall_at_3 | |
| value: 12.066 | |
| - type: recall_at_5 | |
| value: 15.254000000000001 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB NQ | |
| revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 | |
| split: test | |
| type: mteb/nq | |
| metrics: | |
| - type: map_at_1 | |
| value: 39.75 | |
| - type: map_at_10 | |
| value: 56.443 | |
| - type: map_at_100 | |
| value: 57.233999999999995 | |
| - type: map_at_1000 | |
| value: 57.249 | |
| - type: map_at_3 | |
| value: 52.032999999999994 | |
| - type: map_at_5 | |
| value: 54.937999999999995 | |
| - type: mrr_at_1 | |
| value: 44.728 | |
| - type: mrr_at_10 | |
| value: 58.939 | |
| - type: mrr_at_100 | |
| value: 59.489000000000004 | |
| - type: mrr_at_1000 | |
| value: 59.499 | |
| - type: mrr_at_3 | |
| value: 55.711999999999996 | |
| - type: mrr_at_5 | |
| value: 57.89 | |
| - type: ndcg_at_1 | |
| value: 44.728 | |
| - type: ndcg_at_10 | |
| value: 63.998999999999995 | |
| - type: ndcg_at_100 | |
| value: 67.077 | |
| - type: ndcg_at_1000 | |
| value: 67.40899999999999 | |
| - type: ndcg_at_3 | |
| value: 56.266000000000005 | |
| - type: ndcg_at_5 | |
| value: 60.88 | |
| - type: precision_at_1 | |
| value: 44.728 | |
| - type: precision_at_10 | |
| value: 10.09 | |
| - type: precision_at_100 | |
| value: 1.1809999999999998 | |
| - type: precision_at_1000 | |
| value: 0.121 | |
| - type: precision_at_3 | |
| value: 25.145 | |
| - type: precision_at_5 | |
| value: 17.822 | |
| - type: recall_at_1 | |
| value: 39.75 | |
| - type: recall_at_10 | |
| value: 84.234 | |
| - type: recall_at_100 | |
| value: 97.055 | |
| - type: recall_at_1000 | |
| value: 99.517 | |
| - type: recall_at_3 | |
| value: 64.851 | |
| - type: recall_at_5 | |
| value: 75.343 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB QuoraRetrieval | |
| revision: None | |
| split: test | |
| type: mteb/quora | |
| metrics: | |
| - type: map_at_1 | |
| value: 72.085 | |
| - type: map_at_10 | |
| value: 86.107 | |
| - type: map_at_100 | |
| value: 86.727 | |
| - type: map_at_1000 | |
| value: 86.74 | |
| - type: map_at_3 | |
| value: 83.21 | |
| - type: map_at_5 | |
| value: 85.06 | |
| - type: mrr_at_1 | |
| value: 82.94 | |
| - type: mrr_at_10 | |
| value: 88.845 | |
| - type: mrr_at_100 | |
| value: 88.926 | |
| - type: mrr_at_1000 | |
| value: 88.927 | |
| - type: mrr_at_3 | |
| value: 87.993 | |
| - type: mrr_at_5 | |
| value: 88.62299999999999 | |
| - type: ndcg_at_1 | |
| value: 82.97 | |
| - type: ndcg_at_10 | |
| value: 89.645 | |
| - type: ndcg_at_100 | |
| value: 90.717 | |
| - type: ndcg_at_1000 | |
| value: 90.78 | |
| - type: ndcg_at_3 | |
| value: 86.99900000000001 | |
| - type: ndcg_at_5 | |
| value: 88.52600000000001 | |
| - type: precision_at_1 | |
| value: 82.97 | |
| - type: precision_at_10 | |
| value: 13.569 | |
| - type: precision_at_100 | |
| value: 1.539 | |
| - type: precision_at_1000 | |
| value: 0.157 | |
| - type: precision_at_3 | |
| value: 38.043 | |
| - type: precision_at_5 | |
| value: 24.992 | |
| - type: recall_at_1 | |
| value: 72.085 | |
| - type: recall_at_10 | |
| value: 96.262 | |
| - type: recall_at_100 | |
| value: 99.77000000000001 | |
| - type: recall_at_1000 | |
| value: 99.997 | |
| - type: recall_at_3 | |
| value: 88.652 | |
| - type: recall_at_5 | |
| value: 93.01899999999999 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB RedditClustering | |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb | |
| split: test | |
| type: mteb/reddit-clustering | |
| metrics: | |
| - type: v_measure | |
| value: 55.82153952668092 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB RedditClusteringP2P | |
| revision: 282350215ef01743dc01b456c7f5241fa8937f16 | |
| split: test | |
| type: mteb/reddit-clustering-p2p | |
| metrics: | |
| - type: v_measure | |
| value: 62.094465801879295 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB SCIDOCS | |
| revision: None | |
| split: test | |
| type: mteb/scidocs | |
| metrics: | |
| - type: map_at_1 | |
| value: 5.688 | |
| - type: map_at_10 | |
| value: 15.201999999999998 | |
| - type: map_at_100 | |
| value: 18.096 | |
| - type: map_at_1000 | |
| value: 18.481 | |
| - type: map_at_3 | |
| value: 10.734 | |
| - type: map_at_5 | |
| value: 12.94 | |
| - type: mrr_at_1 | |
| value: 28.000000000000004 | |
| - type: mrr_at_10 | |
| value: 41.101 | |
| - type: mrr_at_100 | |
| value: 42.202 | |
| - type: mrr_at_1000 | |
| value: 42.228 | |
| - type: mrr_at_3 | |
| value: 37.683 | |
| - type: mrr_at_5 | |
| value: 39.708 | |
| - type: ndcg_at_1 | |
| value: 28.000000000000004 | |
| - type: ndcg_at_10 | |
| value: 24.976000000000003 | |
| - type: ndcg_at_100 | |
| value: 35.129 | |
| - type: ndcg_at_1000 | |
| value: 40.77 | |
| - type: ndcg_at_3 | |
| value: 23.787 | |
| - type: ndcg_at_5 | |
| value: 20.816000000000003 | |
| - type: precision_at_1 | |
| value: 28.000000000000004 | |
| - type: precision_at_10 | |
| value: 13.04 | |
| - type: precision_at_100 | |
| value: 2.761 | |
| - type: precision_at_1000 | |
| value: 0.41000000000000003 | |
| - type: precision_at_3 | |
| value: 22.6 | |
| - type: precision_at_5 | |
| value: 18.52 | |
| - type: recall_at_1 | |
| value: 5.688 | |
| - type: recall_at_10 | |
| value: 26.43 | |
| - type: recall_at_100 | |
| value: 56.02 | |
| - type: recall_at_1000 | |
| value: 83.21 | |
| - type: recall_at_3 | |
| value: 13.752 | |
| - type: recall_at_5 | |
| value: 18.777 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB SICK-R | |
| revision: a6ea5a8cab320b040a23452cc28066d9beae2cee | |
| split: test | |
| type: mteb/sickr-sts | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 85.15084859283178 | |
| - type: cos_sim_spearman | |
| value: 80.49030614009419 | |
| - type: euclidean_pearson | |
| value: 81.84574978672468 | |
| - type: euclidean_spearman | |
| value: 79.89787150656818 | |
| - type: manhattan_pearson | |
| value: 81.63076538567131 | |
| - type: manhattan_spearman | |
| value: 79.69867352121841 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB STS12 | |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 | |
| split: test | |
| type: mteb/sts12-sts | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 84.64097921490992 | |
| - type: cos_sim_spearman | |
| value: 77.25370084896514 | |
| - type: euclidean_pearson | |
| value: 82.71210826468788 | |
| - type: euclidean_spearman | |
| value: 78.50445584994826 | |
| - type: manhattan_pearson | |
| value: 82.92580164330298 | |
| - type: manhattan_spearman | |
| value: 78.69686891301019 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB STS13 | |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca | |
| split: test | |
| type: mteb/sts13-sts | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 87.24596417308994 | |
| - type: cos_sim_spearman | |
| value: 87.79454220555091 | |
| - type: euclidean_pearson | |
| value: 87.40242561671164 | |
| - type: euclidean_spearman | |
| value: 88.25955597373556 | |
| - type: manhattan_pearson | |
| value: 87.25160240485849 | |
| - type: manhattan_spearman | |
| value: 88.155794979818 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB STS14 | |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 | |
| split: test | |
| type: mteb/sts14-sts | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 84.44914233422564 | |
| - type: cos_sim_spearman | |
| value: 82.91015471820322 | |
| - type: euclidean_pearson | |
| value: 84.7206656630327 | |
| - type: euclidean_spearman | |
| value: 83.86408872059216 | |
| - type: manhattan_pearson | |
| value: 84.72816725158454 | |
| - type: manhattan_spearman | |
| value: 84.01603388572788 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB STS15 | |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 | |
| split: test | |
| type: mteb/sts15-sts | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 87.6168026237477 | |
| - type: cos_sim_spearman | |
| value: 88.45414278092397 | |
| - type: euclidean_pearson | |
| value: 88.57023240882022 | |
| - type: euclidean_spearman | |
| value: 89.04102190922094 | |
| - type: manhattan_pearson | |
| value: 88.66695535796354 | |
| - type: manhattan_spearman | |
| value: 89.19898476680969 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB STS16 | |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 | |
| split: test | |
| type: mteb/sts16-sts | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 84.27925826089424 | |
| - type: cos_sim_spearman | |
| value: 85.45291099550461 | |
| - type: euclidean_pearson | |
| value: 83.63853036580834 | |
| - type: euclidean_spearman | |
| value: 84.33468035821484 | |
| - type: manhattan_pearson | |
| value: 83.72778773251596 | |
| - type: manhattan_spearman | |
| value: 84.51583132445376 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: en-en | |
| name: MTEB STS17 (en-en) | |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d | |
| split: test | |
| type: mteb/sts17-crosslingual-sts | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 89.67375185692552 | |
| - type: cos_sim_spearman | |
| value: 90.32542469203855 | |
| - type: euclidean_pearson | |
| value: 89.63513717951847 | |
| - type: euclidean_spearman | |
| value: 89.87760271003745 | |
| - type: manhattan_pearson | |
| value: 89.28381452982924 | |
| - type: manhattan_spearman | |
| value: 89.53568197785721 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: en | |
| name: MTEB STS22 (en) | |
| revision: eea2b4fe26a775864c896887d910b76a8098ad3f | |
| split: test | |
| type: mteb/sts22-crosslingual-sts | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 66.24644693819846 | |
| - type: cos_sim_spearman | |
| value: 66.09889420525377 | |
| - type: euclidean_pearson | |
| value: 63.72551583520747 | |
| - type: euclidean_spearman | |
| value: 63.01385470780679 | |
| - type: manhattan_pearson | |
| value: 64.09258157214097 | |
| - type: manhattan_spearman | |
| value: 63.080517752822594 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB STSBenchmark | |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 | |
| split: test | |
| type: mteb/stsbenchmark-sts | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 86.27321463839989 | |
| - type: cos_sim_spearman | |
| value: 86.37572865993327 | |
| - type: euclidean_pearson | |
| value: 86.36268020198149 | |
| - type: euclidean_spearman | |
| value: 86.31089339478922 | |
| - type: manhattan_pearson | |
| value: 86.4260445761947 | |
| - type: manhattan_spearman | |
| value: 86.45885895320457 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB SciDocsRR | |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab | |
| split: test | |
| type: mteb/scidocs-reranking | |
| metrics: | |
| - type: map | |
| value: 86.52456702387798 | |
| - type: mrr | |
| value: 96.34556529164372 | |
| task: | |
| type: Reranking | |
| - dataset: | |
| config: default | |
| name: MTEB SciFact | |
| revision: 0228b52cf27578f30900b9e5271d331663a030d7 | |
| split: test | |
| type: mteb/scifact | |
| metrics: | |
| - type: map_at_1 | |
| value: 61.99400000000001 | |
| - type: map_at_10 | |
| value: 73.38799999999999 | |
| - type: map_at_100 | |
| value: 73.747 | |
| - type: map_at_1000 | |
| value: 73.75 | |
| - type: map_at_3 | |
| value: 70.04599999999999 | |
| - type: map_at_5 | |
| value: 72.095 | |
| - type: mrr_at_1 | |
| value: 65.0 | |
| - type: mrr_at_10 | |
| value: 74.42800000000001 | |
| - type: mrr_at_100 | |
| value: 74.722 | |
| - type: mrr_at_1000 | |
| value: 74.725 | |
| - type: mrr_at_3 | |
| value: 72.056 | |
| - type: mrr_at_5 | |
| value: 73.60600000000001 | |
| - type: ndcg_at_1 | |
| value: 65.0 | |
| - type: ndcg_at_10 | |
| value: 78.435 | |
| - type: ndcg_at_100 | |
| value: 79.922 | |
| - type: ndcg_at_1000 | |
| value: 80.00500000000001 | |
| - type: ndcg_at_3 | |
| value: 73.05199999999999 | |
| - type: ndcg_at_5 | |
| value: 75.98 | |
| - type: precision_at_1 | |
| value: 65.0 | |
| - type: precision_at_10 | |
| value: 10.5 | |
| - type: precision_at_100 | |
| value: 1.123 | |
| - type: precision_at_1000 | |
| value: 0.11299999999999999 | |
| - type: precision_at_3 | |
| value: 28.555999999999997 | |
| - type: precision_at_5 | |
| value: 19.0 | |
| - type: recall_at_1 | |
| value: 61.99400000000001 | |
| - type: recall_at_10 | |
| value: 92.72200000000001 | |
| - type: recall_at_100 | |
| value: 99.333 | |
| - type: recall_at_1000 | |
| value: 100.0 | |
| - type: recall_at_3 | |
| value: 78.739 | |
| - type: recall_at_5 | |
| value: 85.828 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB SprintDuplicateQuestions | |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 | |
| split: test | |
| type: mteb/sprintduplicatequestions-pairclassification | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 99.79009900990098 | |
| - type: cos_sim_ap | |
| value: 95.3203137438653 | |
| - type: cos_sim_f1 | |
| value: 89.12386706948641 | |
| - type: cos_sim_precision | |
| value: 89.75659229208925 | |
| - type: cos_sim_recall | |
| value: 88.5 | |
| - type: dot_accuracy | |
| value: 99.67821782178218 | |
| - type: dot_ap | |
| value: 89.94069840000675 | |
| - type: dot_f1 | |
| value: 83.45902463549521 | |
| - type: dot_precision | |
| value: 83.9231547017189 | |
| - type: dot_recall | |
| value: 83.0 | |
| - type: euclidean_accuracy | |
| value: 99.78613861386138 | |
| - type: euclidean_ap | |
| value: 95.10648259135526 | |
| - type: euclidean_f1 | |
| value: 88.77338877338877 | |
| - type: euclidean_precision | |
| value: 92.42424242424242 | |
| - type: euclidean_recall | |
| value: 85.39999999999999 | |
| - type: manhattan_accuracy | |
| value: 99.7950495049505 | |
| - type: manhattan_ap | |
| value: 95.29987661320946 | |
| - type: manhattan_f1 | |
| value: 89.21313183949972 | |
| - type: manhattan_precision | |
| value: 93.14472252448314 | |
| - type: manhattan_recall | |
| value: 85.6 | |
| - type: max_accuracy | |
| value: 99.7950495049505 | |
| - type: max_ap | |
| value: 95.3203137438653 | |
| - type: max_f1 | |
| value: 89.21313183949972 | |
| task: | |
| type: PairClassification | |
| - dataset: | |
| config: default | |
| name: MTEB StackExchangeClustering | |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 | |
| split: test | |
| type: mteb/stackexchange-clustering | |
| metrics: | |
| - type: v_measure | |
| value: 67.65446577183913 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB StackExchangeClusteringP2P | |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 | |
| split: test | |
| type: mteb/stackexchange-clustering-p2p | |
| metrics: | |
| - type: v_measure | |
| value: 46.30749237193961 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB StackOverflowDupQuestions | |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 | |
| split: test | |
| type: mteb/stackoverflowdupquestions-reranking | |
| metrics: | |
| - type: map | |
| value: 54.91481849959949 | |
| - type: mrr | |
| value: 55.853506175197346 | |
| task: | |
| type: Reranking | |
| - dataset: | |
| config: default | |
| name: MTEB SummEval | |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c | |
| split: test | |
| type: mteb/summeval | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 30.08196549170419 | |
| - type: cos_sim_spearman | |
| value: 31.16661390597077 | |
| - type: dot_pearson | |
| value: 29.892258410943466 | |
| - type: dot_spearman | |
| value: 30.51328811965085 | |
| task: | |
| type: Summarization | |
| - dataset: | |
| config: default | |
| name: MTEB TRECCOVID | |
| revision: None | |
| split: test | |
| type: mteb/trec-covid | |
| metrics: | |
| - type: map_at_1 | |
| value: 0.23900000000000002 | |
| - type: map_at_10 | |
| value: 2.173 | |
| - type: map_at_100 | |
| value: 14.24 | |
| - type: map_at_1000 | |
| value: 35.309000000000005 | |
| - type: map_at_3 | |
| value: 0.7100000000000001 | |
| - type: map_at_5 | |
| value: 1.163 | |
| - type: mrr_at_1 | |
| value: 92.0 | |
| - type: mrr_at_10 | |
| value: 96.0 | |
| - type: mrr_at_100 | |
| value: 96.0 | |
| - type: mrr_at_1000 | |
| value: 96.0 | |
| - type: mrr_at_3 | |
| value: 96.0 | |
| - type: mrr_at_5 | |
| value: 96.0 | |
| - type: ndcg_at_1 | |
| value: 90.0 | |
| - type: ndcg_at_10 | |
| value: 85.382 | |
| - type: ndcg_at_100 | |
| value: 68.03 | |
| - type: ndcg_at_1000 | |
| value: 61.021 | |
| - type: ndcg_at_3 | |
| value: 89.765 | |
| - type: ndcg_at_5 | |
| value: 88.444 | |
| - type: precision_at_1 | |
| value: 92.0 | |
| - type: precision_at_10 | |
| value: 88.0 | |
| - type: precision_at_100 | |
| value: 70.02000000000001 | |
| - type: precision_at_1000 | |
| value: 26.984 | |
| - type: precision_at_3 | |
| value: 94.0 | |
| - type: precision_at_5 | |
| value: 92.80000000000001 | |
| - type: recall_at_1 | |
| value: 0.23900000000000002 | |
| - type: recall_at_10 | |
| value: 2.313 | |
| - type: recall_at_100 | |
| value: 17.049 | |
| - type: recall_at_1000 | |
| value: 57.489999999999995 | |
| - type: recall_at_3 | |
| value: 0.737 | |
| - type: recall_at_5 | |
| value: 1.221 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB Touche2020 | |
| revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f | |
| split: test | |
| type: mteb/touche2020 | |
| metrics: | |
| - type: map_at_1 | |
| value: 2.75 | |
| - type: map_at_10 | |
| value: 11.29 | |
| - type: map_at_100 | |
| value: 18.032999999999998 | |
| - type: map_at_1000 | |
| value: 19.746 | |
| - type: map_at_3 | |
| value: 6.555 | |
| - type: map_at_5 | |
| value: 8.706999999999999 | |
| - type: mrr_at_1 | |
| value: 34.694 | |
| - type: mrr_at_10 | |
| value: 50.55 | |
| - type: mrr_at_100 | |
| value: 51.659 | |
| - type: mrr_at_1000 | |
| value: 51.659 | |
| - type: mrr_at_3 | |
| value: 47.278999999999996 | |
| - type: mrr_at_5 | |
| value: 49.728 | |
| - type: ndcg_at_1 | |
| value: 32.653 | |
| - type: ndcg_at_10 | |
| value: 27.894000000000002 | |
| - type: ndcg_at_100 | |
| value: 39.769 | |
| - type: ndcg_at_1000 | |
| value: 51.495999999999995 | |
| - type: ndcg_at_3 | |
| value: 32.954 | |
| - type: ndcg_at_5 | |
| value: 31.502999999999997 | |
| - type: precision_at_1 | |
| value: 34.694 | |
| - type: precision_at_10 | |
| value: 23.265 | |
| - type: precision_at_100 | |
| value: 7.898 | |
| - type: precision_at_1000 | |
| value: 1.58 | |
| - type: precision_at_3 | |
| value: 34.694 | |
| - type: precision_at_5 | |
| value: 31.429000000000002 | |
| - type: recall_at_1 | |
| value: 2.75 | |
| - type: recall_at_10 | |
| value: 16.953 | |
| - type: recall_at_100 | |
| value: 48.68 | |
| - type: recall_at_1000 | |
| value: 85.18599999999999 | |
| - type: recall_at_3 | |
| value: 7.710999999999999 | |
| - type: recall_at_5 | |
| value: 11.484 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB ToxicConversationsClassification | |
| revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c | |
| split: test | |
| type: mteb/toxic_conversations_50k | |
| metrics: | |
| - type: accuracy | |
| value: 82.66099999999999 | |
| - type: ap | |
| value: 25.555698090238337 | |
| - type: f1 | |
| value: 66.48402012461622 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB TweetSentimentExtractionClassification | |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a | |
| split: test | |
| type: mteb/tweet_sentiment_extraction | |
| metrics: | |
| - type: accuracy | |
| value: 72.94567062818335 | |
| - type: f1 | |
| value: 73.28139189595674 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB TwentyNewsgroupsClustering | |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 | |
| split: test | |
| type: mteb/twentynewsgroups-clustering | |
| metrics: | |
| - type: v_measure | |
| value: 49.581627240203474 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB TwitterSemEval2015 | |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 | |
| split: test | |
| type: mteb/twittersemeval2015-pairclassification | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 87.78089050485785 | |
| - type: cos_sim_ap | |
| value: 79.64487116574168 | |
| - type: cos_sim_f1 | |
| value: 72.46563021970964 | |
| - type: cos_sim_precision | |
| value: 70.62359128474831 | |
| - type: cos_sim_recall | |
| value: 74.40633245382587 | |
| - type: dot_accuracy | |
| value: 86.2609524944865 | |
| - type: dot_ap | |
| value: 75.513046857613 | |
| - type: dot_f1 | |
| value: 68.58213616489695 | |
| - type: dot_precision | |
| value: 65.12455516014235 | |
| - type: dot_recall | |
| value: 72.42744063324538 | |
| - type: euclidean_accuracy | |
| value: 87.6080348095607 | |
| - type: euclidean_ap | |
| value: 79.00204933649795 | |
| - type: euclidean_f1 | |
| value: 72.14495342605589 | |
| - type: euclidean_precision | |
| value: 69.85421299728193 | |
| - type: euclidean_recall | |
| value: 74.5910290237467 | |
| - type: manhattan_accuracy | |
| value: 87.59611372712642 | |
| - type: manhattan_ap | |
| value: 78.78523756706264 | |
| - type: manhattan_f1 | |
| value: 71.86499137718648 | |
| - type: manhattan_precision | |
| value: 67.39833641404806 | |
| - type: manhattan_recall | |
| value: 76.96569920844327 | |
| - type: max_accuracy | |
| value: 87.78089050485785 | |
| - type: max_ap | |
| value: 79.64487116574168 | |
| - type: max_f1 | |
| value: 72.46563021970964 | |
| task: | |
| type: PairClassification | |
| - dataset: | |
| config: default | |
| name: MTEB TwitterURLCorpus | |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf | |
| split: test | |
| type: mteb/twitterurlcorpus-pairclassification | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 89.98719292117825 | |
| - type: cos_sim_ap | |
| value: 87.58146137353202 | |
| - type: cos_sim_f1 | |
| value: 80.28543232369239 | |
| - type: cos_sim_precision | |
| value: 79.1735289714029 | |
| - type: cos_sim_recall | |
| value: 81.42901139513397 | |
| - type: dot_accuracy | |
| value: 88.9199363526992 | |
| - type: dot_ap | |
| value: 84.98499998630417 | |
| - type: dot_f1 | |
| value: 78.21951400757969 | |
| - type: dot_precision | |
| value: 75.58523624874336 | |
| - type: dot_recall | |
| value: 81.04404065291038 | |
| - type: euclidean_accuracy | |
| value: 89.77374160748244 | |
| - type: euclidean_ap | |
| value: 87.35151562835209 | |
| - type: euclidean_f1 | |
| value: 79.92160922940393 | |
| - type: euclidean_precision | |
| value: 76.88531587933979 | |
| - type: euclidean_recall | |
| value: 83.20757622420696 | |
| - type: manhattan_accuracy | |
| value: 89.72717041176699 | |
| - type: manhattan_ap | |
| value: 87.34065592142515 | |
| - type: manhattan_f1 | |
| value: 79.85603419187943 | |
| - type: manhattan_precision | |
| value: 77.82243332115455 | |
| - type: manhattan_recall | |
| value: 81.99876809362489 | |
| - type: max_accuracy | |
| value: 89.98719292117825 | |
| - type: max_ap | |
| value: 87.58146137353202 | |
| - type: max_f1 | |
| value: 80.28543232369239 | |
| task: | |
| type: PairClassification | |
| - dataset: | |
| config: default | |
| name: MTEB AFQMC | |
| revision: b44c3b011063adb25877c13823db83bb193913c4 | |
| split: validation | |
| type: C-MTEB/AFQMC | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 53.45954203592337 | |
| - type: cos_sim_spearman | |
| value: 58.42154680418638 | |
| - type: euclidean_pearson | |
| value: 56.41543791722753 | |
| - type: euclidean_spearman | |
| value: 58.39328016640146 | |
| - type: manhattan_pearson | |
| value: 56.318510356833876 | |
| - type: manhattan_spearman | |
| value: 58.28423447818184 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB ATEC | |
| revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865 | |
| split: test | |
| type: C-MTEB/ATEC | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 50.78356460675945 | |
| - type: cos_sim_spearman | |
| value: 55.6530411663269 | |
| - type: euclidean_pearson | |
| value: 56.50763660417816 | |
| - type: euclidean_spearman | |
| value: 55.733823335669065 | |
| - type: manhattan_pearson | |
| value: 56.45323093512866 | |
| - type: manhattan_spearman | |
| value: 55.63248619032702 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: zh | |
| name: MTEB AmazonReviewsClassification (zh) | |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d | |
| split: test | |
| type: mteb/amazon_reviews_multi | |
| metrics: | |
| - type: accuracy | |
| value: 47.209999999999994 | |
| - type: f1 | |
| value: 46.08892432018655 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB BQ | |
| revision: e3dda5e115e487b39ec7e618c0c6a29137052a55 | |
| split: test | |
| type: C-MTEB/BQ | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 70.25573992001478 | |
| - type: cos_sim_spearman | |
| value: 73.85247134951433 | |
| - type: euclidean_pearson | |
| value: 72.60033082168442 | |
| - type: euclidean_spearman | |
| value: 73.72445893756499 | |
| - type: manhattan_pearson | |
| value: 72.59932284620231 | |
| - type: manhattan_spearman | |
| value: 73.68002490614583 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB CLSClusteringP2P | |
| revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476 | |
| split: test | |
| type: C-MTEB/CLSClusteringP2P | |
| metrics: | |
| - type: v_measure | |
| value: 45.21317724305628 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB CLSClusteringS2S | |
| revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f | |
| split: test | |
| type: C-MTEB/CLSClusteringS2S | |
| metrics: | |
| - type: v_measure | |
| value: 42.49825170976724 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB CMedQAv1 | |
| revision: 8d7f1e942507dac42dc58017c1a001c3717da7df | |
| split: test | |
| type: C-MTEB/CMedQAv1-reranking | |
| metrics: | |
| - type: map | |
| value: 88.15661686810597 | |
| - type: mrr | |
| value: 90.11222222222223 | |
| task: | |
| type: Reranking | |
| - dataset: | |
| config: default | |
| name: MTEB CMedQAv2 | |
| revision: 23d186750531a14a0357ca22cd92d712fd512ea0 | |
| split: test | |
| type: C-MTEB/CMedQAv2-reranking | |
| metrics: | |
| - type: map | |
| value: 88.1204726064383 | |
| - type: mrr | |
| value: 90.20142857142858 | |
| task: | |
| type: Reranking | |
| - dataset: | |
| config: default | |
| name: MTEB CmedqaRetrieval | |
| revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301 | |
| split: dev | |
| type: C-MTEB/CmedqaRetrieval | |
| metrics: | |
| - type: map_at_1 | |
| value: 27.224999999999998 | |
| - type: map_at_10 | |
| value: 40.169 | |
| - type: map_at_100 | |
| value: 42.0 | |
| - type: map_at_1000 | |
| value: 42.109 | |
| - type: map_at_3 | |
| value: 35.76 | |
| - type: map_at_5 | |
| value: 38.221 | |
| - type: mrr_at_1 | |
| value: 40.56 | |
| - type: mrr_at_10 | |
| value: 49.118 | |
| - type: mrr_at_100 | |
| value: 50.092999999999996 | |
| - type: mrr_at_1000 | |
| value: 50.133 | |
| - type: mrr_at_3 | |
| value: 46.507 | |
| - type: mrr_at_5 | |
| value: 47.973 | |
| - type: ndcg_at_1 | |
| value: 40.56 | |
| - type: ndcg_at_10 | |
| value: 46.972 | |
| - type: ndcg_at_100 | |
| value: 54.04 | |
| - type: ndcg_at_1000 | |
| value: 55.862 | |
| - type: ndcg_at_3 | |
| value: 41.36 | |
| - type: ndcg_at_5 | |
| value: 43.704 | |
| - type: precision_at_1 | |
| value: 40.56 | |
| - type: precision_at_10 | |
| value: 10.302999999999999 | |
| - type: precision_at_100 | |
| value: 1.606 | |
| - type: precision_at_1000 | |
| value: 0.184 | |
| - type: precision_at_3 | |
| value: 23.064 | |
| - type: precision_at_5 | |
| value: 16.764000000000003 | |
| - type: recall_at_1 | |
| value: 27.224999999999998 | |
| - type: recall_at_10 | |
| value: 58.05200000000001 | |
| - type: recall_at_100 | |
| value: 87.092 | |
| - type: recall_at_1000 | |
| value: 99.099 | |
| - type: recall_at_3 | |
| value: 41.373 | |
| - type: recall_at_5 | |
| value: 48.453 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB Cmnli | |
| revision: 41bc36f332156f7adc9e38f53777c959b2ae9766 | |
| split: validation | |
| type: C-MTEB/CMNLI | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 77.40228502705953 | |
| - type: cos_sim_ap | |
| value: 86.22359172956327 | |
| - type: cos_sim_f1 | |
| value: 78.96328293736501 | |
| - type: cos_sim_precision | |
| value: 73.36945615091311 | |
| - type: cos_sim_recall | |
| value: 85.48047696983868 | |
| - type: dot_accuracy | |
| value: 75.53818400481059 | |
| - type: dot_ap | |
| value: 83.70164011305312 | |
| - type: dot_f1 | |
| value: 77.67298719348754 | |
| - type: dot_precision | |
| value: 67.49482401656314 | |
| - type: dot_recall | |
| value: 91.46598082768296 | |
| - type: euclidean_accuracy | |
| value: 77.94347564642213 | |
| - type: euclidean_ap | |
| value: 86.4652108728609 | |
| - type: euclidean_f1 | |
| value: 79.15555555555555 | |
| - type: euclidean_precision | |
| value: 75.41816641964853 | |
| - type: euclidean_recall | |
| value: 83.28267477203647 | |
| - type: manhattan_accuracy | |
| value: 77.45039085989175 | |
| - type: manhattan_ap | |
| value: 86.09986583900665 | |
| - type: manhattan_f1 | |
| value: 78.93669264438988 | |
| - type: manhattan_precision | |
| value: 72.63261296660117 | |
| - type: manhattan_recall | |
| value: 86.43909282207154 | |
| - type: max_accuracy | |
| value: 77.94347564642213 | |
| - type: max_ap | |
| value: 86.4652108728609 | |
| - type: max_f1 | |
| value: 79.15555555555555 | |
| task: | |
| type: PairClassification | |
| - dataset: | |
| config: default | |
| name: MTEB CovidRetrieval | |
| revision: 1271c7809071a13532e05f25fb53511ffce77117 | |
| split: dev | |
| type: C-MTEB/CovidRetrieval | |
| metrics: | |
| - type: map_at_1 | |
| value: 69.336 | |
| - type: map_at_10 | |
| value: 77.16 | |
| - type: map_at_100 | |
| value: 77.47500000000001 | |
| - type: map_at_1000 | |
| value: 77.482 | |
| - type: map_at_3 | |
| value: 75.42999999999999 | |
| - type: map_at_5 | |
| value: 76.468 | |
| - type: mrr_at_1 | |
| value: 69.44200000000001 | |
| - type: mrr_at_10 | |
| value: 77.132 | |
| - type: mrr_at_100 | |
| value: 77.43299999999999 | |
| - type: mrr_at_1000 | |
| value: 77.44 | |
| - type: mrr_at_3 | |
| value: 75.395 | |
| - type: mrr_at_5 | |
| value: 76.459 | |
| - type: ndcg_at_1 | |
| value: 69.547 | |
| - type: ndcg_at_10 | |
| value: 80.794 | |
| - type: ndcg_at_100 | |
| value: 82.245 | |
| - type: ndcg_at_1000 | |
| value: 82.40899999999999 | |
| - type: ndcg_at_3 | |
| value: 77.303 | |
| - type: ndcg_at_5 | |
| value: 79.168 | |
| - type: precision_at_1 | |
| value: 69.547 | |
| - type: precision_at_10 | |
| value: 9.305 | |
| - type: precision_at_100 | |
| value: 0.9979999999999999 | |
| - type: precision_at_1000 | |
| value: 0.101 | |
| - type: precision_at_3 | |
| value: 27.749000000000002 | |
| - type: precision_at_5 | |
| value: 17.576 | |
| - type: recall_at_1 | |
| value: 69.336 | |
| - type: recall_at_10 | |
| value: 92.097 | |
| - type: recall_at_100 | |
| value: 98.736 | |
| - type: recall_at_1000 | |
| value: 100.0 | |
| - type: recall_at_3 | |
| value: 82.64 | |
| - type: recall_at_5 | |
| value: 87.144 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB DuRetrieval | |
| revision: a1a333e290fe30b10f3f56498e3a0d911a693ced | |
| split: dev | |
| type: C-MTEB/DuRetrieval | |
| metrics: | |
| - type: map_at_1 | |
| value: 26.817999999999998 | |
| - type: map_at_10 | |
| value: 82.67 | |
| - type: map_at_100 | |
| value: 85.304 | |
| - type: map_at_1000 | |
| value: 85.334 | |
| - type: map_at_3 | |
| value: 57.336 | |
| - type: map_at_5 | |
| value: 72.474 | |
| - type: mrr_at_1 | |
| value: 91.45 | |
| - type: mrr_at_10 | |
| value: 94.272 | |
| - type: mrr_at_100 | |
| value: 94.318 | |
| - type: mrr_at_1000 | |
| value: 94.32000000000001 | |
| - type: mrr_at_3 | |
| value: 94.0 | |
| - type: mrr_at_5 | |
| value: 94.17699999999999 | |
| - type: ndcg_at_1 | |
| value: 91.45 | |
| - type: ndcg_at_10 | |
| value: 89.404 | |
| - type: ndcg_at_100 | |
| value: 91.724 | |
| - type: ndcg_at_1000 | |
| value: 91.973 | |
| - type: ndcg_at_3 | |
| value: 88.104 | |
| - type: ndcg_at_5 | |
| value: 87.25699999999999 | |
| - type: precision_at_1 | |
| value: 91.45 | |
| - type: precision_at_10 | |
| value: 42.585 | |
| - type: precision_at_100 | |
| value: 4.838 | |
| - type: precision_at_1000 | |
| value: 0.49 | |
| - type: precision_at_3 | |
| value: 78.8 | |
| - type: precision_at_5 | |
| value: 66.66 | |
| - type: recall_at_1 | |
| value: 26.817999999999998 | |
| - type: recall_at_10 | |
| value: 90.67 | |
| - type: recall_at_100 | |
| value: 98.36200000000001 | |
| - type: recall_at_1000 | |
| value: 99.583 | |
| - type: recall_at_3 | |
| value: 59.614999999999995 | |
| - type: recall_at_5 | |
| value: 77.05199999999999 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB EcomRetrieval | |
| revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9 | |
| split: dev | |
| type: C-MTEB/EcomRetrieval | |
| metrics: | |
| - type: map_at_1 | |
| value: 47.699999999999996 | |
| - type: map_at_10 | |
| value: 57.589999999999996 | |
| - type: map_at_100 | |
| value: 58.226 | |
| - type: map_at_1000 | |
| value: 58.251 | |
| - type: map_at_3 | |
| value: 55.233 | |
| - type: map_at_5 | |
| value: 56.633 | |
| - type: mrr_at_1 | |
| value: 47.699999999999996 | |
| - type: mrr_at_10 | |
| value: 57.589999999999996 | |
| - type: mrr_at_100 | |
| value: 58.226 | |
| - type: mrr_at_1000 | |
| value: 58.251 | |
| - type: mrr_at_3 | |
| value: 55.233 | |
| - type: mrr_at_5 | |
| value: 56.633 | |
| - type: ndcg_at_1 | |
| value: 47.699999999999996 | |
| - type: ndcg_at_10 | |
| value: 62.505 | |
| - type: ndcg_at_100 | |
| value: 65.517 | |
| - type: ndcg_at_1000 | |
| value: 66.19800000000001 | |
| - type: ndcg_at_3 | |
| value: 57.643 | |
| - type: ndcg_at_5 | |
| value: 60.181 | |
| - type: precision_at_1 | |
| value: 47.699999999999996 | |
| - type: precision_at_10 | |
| value: 7.8 | |
| - type: precision_at_100 | |
| value: 0.919 | |
| - type: precision_at_1000 | |
| value: 0.097 | |
| - type: precision_at_3 | |
| value: 21.532999999999998 | |
| - type: precision_at_5 | |
| value: 14.16 | |
| - type: recall_at_1 | |
| value: 47.699999999999996 | |
| - type: recall_at_10 | |
| value: 78.0 | |
| - type: recall_at_100 | |
| value: 91.9 | |
| - type: recall_at_1000 | |
| value: 97.3 | |
| - type: recall_at_3 | |
| value: 64.60000000000001 | |
| - type: recall_at_5 | |
| value: 70.8 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB IFlyTek | |
| revision: 421605374b29664c5fc098418fe20ada9bd55f8a | |
| split: validation | |
| type: C-MTEB/IFlyTek-classification | |
| metrics: | |
| - type: accuracy | |
| value: 44.84801846864178 | |
| - type: f1 | |
| value: 37.47347897956339 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB JDReview | |
| revision: b7c64bd89eb87f8ded463478346f76731f07bf8b | |
| split: test | |
| type: C-MTEB/JDReview-classification | |
| metrics: | |
| - type: accuracy | |
| value: 85.81613508442777 | |
| - type: ap | |
| value: 52.68244615477374 | |
| - type: f1 | |
| value: 80.0445640948843 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB LCQMC | |
| revision: 17f9b096f80380fce5ed12a9be8be7784b337daf | |
| split: test | |
| type: C-MTEB/LCQMC | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 69.57786502217138 | |
| - type: cos_sim_spearman | |
| value: 75.39106054489906 | |
| - type: euclidean_pearson | |
| value: 73.72082954602402 | |
| - type: euclidean_spearman | |
| value: 75.14421475913619 | |
| - type: manhattan_pearson | |
| value: 73.62463076633642 | |
| - type: manhattan_spearman | |
| value: 75.01301565104112 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB MMarcoReranking | |
| revision: None | |
| split: dev | |
| type: C-MTEB/Mmarco-reranking | |
| metrics: | |
| - type: map | |
| value: 29.143797057999134 | |
| - type: mrr | |
| value: 28.08174603174603 | |
| task: | |
| type: Reranking | |
| - dataset: | |
| config: default | |
| name: MTEB MMarcoRetrieval | |
| revision: 539bbde593d947e2a124ba72651aafc09eb33fc2 | |
| split: dev | |
| type: C-MTEB/MMarcoRetrieval | |
| metrics: | |
| - type: map_at_1 | |
| value: 70.492 | |
| - type: map_at_10 | |
| value: 79.501 | |
| - type: map_at_100 | |
| value: 79.728 | |
| - type: map_at_1000 | |
| value: 79.735 | |
| - type: map_at_3 | |
| value: 77.77 | |
| - type: map_at_5 | |
| value: 78.851 | |
| - type: mrr_at_1 | |
| value: 72.822 | |
| - type: mrr_at_10 | |
| value: 80.001 | |
| - type: mrr_at_100 | |
| value: 80.19 | |
| - type: mrr_at_1000 | |
| value: 80.197 | |
| - type: mrr_at_3 | |
| value: 78.484 | |
| - type: mrr_at_5 | |
| value: 79.42099999999999 | |
| - type: ndcg_at_1 | |
| value: 72.822 | |
| - type: ndcg_at_10 | |
| value: 83.013 | |
| - type: ndcg_at_100 | |
| value: 84.013 | |
| - type: ndcg_at_1000 | |
| value: 84.20400000000001 | |
| - type: ndcg_at_3 | |
| value: 79.728 | |
| - type: ndcg_at_5 | |
| value: 81.542 | |
| - type: precision_at_1 | |
| value: 72.822 | |
| - type: precision_at_10 | |
| value: 9.917 | |
| - type: precision_at_100 | |
| value: 1.042 | |
| - type: precision_at_1000 | |
| value: 0.106 | |
| - type: precision_at_3 | |
| value: 29.847 | |
| - type: precision_at_5 | |
| value: 18.871 | |
| - type: recall_at_1 | |
| value: 70.492 | |
| - type: recall_at_10 | |
| value: 93.325 | |
| - type: recall_at_100 | |
| value: 97.822 | |
| - type: recall_at_1000 | |
| value: 99.319 | |
| - type: recall_at_3 | |
| value: 84.636 | |
| - type: recall_at_5 | |
| value: 88.93100000000001 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: zh-CN | |
| name: MTEB MassiveIntentClassification (zh-CN) | |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 | |
| split: test | |
| type: mteb/amazon_massive_intent | |
| metrics: | |
| - type: accuracy | |
| value: 76.88298587760592 | |
| - type: f1 | |
| value: 73.89001762017176 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: zh-CN | |
| name: MTEB MassiveScenarioClassification (zh-CN) | |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 | |
| split: test | |
| type: mteb/amazon_massive_scenario | |
| metrics: | |
| - type: accuracy | |
| value: 80.76328177538669 | |
| - type: f1 | |
| value: 80.24718532423358 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB MedicalRetrieval | |
| revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6 | |
| split: dev | |
| type: C-MTEB/MedicalRetrieval | |
| metrics: | |
| - type: map_at_1 | |
| value: 49.6 | |
| - type: map_at_10 | |
| value: 55.620999999999995 | |
| - type: map_at_100 | |
| value: 56.204 | |
| - type: map_at_1000 | |
| value: 56.251 | |
| - type: map_at_3 | |
| value: 54.132999999999996 | |
| - type: map_at_5 | |
| value: 54.933 | |
| - type: mrr_at_1 | |
| value: 49.7 | |
| - type: mrr_at_10 | |
| value: 55.67100000000001 | |
| - type: mrr_at_100 | |
| value: 56.254000000000005 | |
| - type: mrr_at_1000 | |
| value: 56.301 | |
| - type: mrr_at_3 | |
| value: 54.18300000000001 | |
| - type: mrr_at_5 | |
| value: 54.983000000000004 | |
| - type: ndcg_at_1 | |
| value: 49.6 | |
| - type: ndcg_at_10 | |
| value: 58.645 | |
| - type: ndcg_at_100 | |
| value: 61.789 | |
| - type: ndcg_at_1000 | |
| value: 63.219 | |
| - type: ndcg_at_3 | |
| value: 55.567 | |
| - type: ndcg_at_5 | |
| value: 57.008 | |
| - type: precision_at_1 | |
| value: 49.6 | |
| - type: precision_at_10 | |
| value: 6.819999999999999 | |
| - type: precision_at_100 | |
| value: 0.836 | |
| - type: precision_at_1000 | |
| value: 0.095 | |
| - type: precision_at_3 | |
| value: 19.900000000000002 | |
| - type: precision_at_5 | |
| value: 12.64 | |
| - type: recall_at_1 | |
| value: 49.6 | |
| - type: recall_at_10 | |
| value: 68.2 | |
| - type: recall_at_100 | |
| value: 83.6 | |
| - type: recall_at_1000 | |
| value: 95.3 | |
| - type: recall_at_3 | |
| value: 59.699999999999996 | |
| - type: recall_at_5 | |
| value: 63.2 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB MultilingualSentiment | |
| revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a | |
| split: validation | |
| type: C-MTEB/MultilingualSentiment-classification | |
| metrics: | |
| - type: accuracy | |
| value: 74.45666666666666 | |
| - type: f1 | |
| value: 74.32582402190089 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB Ocnli | |
| revision: 66e76a618a34d6d565d5538088562851e6daa7ec | |
| split: validation | |
| type: C-MTEB/OCNLI | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 80.67135896047645 | |
| - type: cos_sim_ap | |
| value: 87.60421240712051 | |
| - type: cos_sim_f1 | |
| value: 82.1304131408661 | |
| - type: cos_sim_precision | |
| value: 77.68361581920904 | |
| - type: cos_sim_recall | |
| value: 87.11721224920802 | |
| - type: dot_accuracy | |
| value: 79.04710341093666 | |
| - type: dot_ap | |
| value: 85.6370059719336 | |
| - type: dot_f1 | |
| value: 80.763723150358 | |
| - type: dot_precision | |
| value: 73.69337979094077 | |
| - type: dot_recall | |
| value: 89.33474128827878 | |
| - type: euclidean_accuracy | |
| value: 81.05035192203573 | |
| - type: euclidean_ap | |
| value: 87.7880240053663 | |
| - type: euclidean_f1 | |
| value: 82.50244379276637 | |
| - type: euclidean_precision | |
| value: 76.7970882620564 | |
| - type: euclidean_recall | |
| value: 89.1235480464625 | |
| - type: manhattan_accuracy | |
| value: 80.61721710882512 | |
| - type: manhattan_ap | |
| value: 87.43568120591175 | |
| - type: manhattan_f1 | |
| value: 81.89526184538653 | |
| - type: manhattan_precision | |
| value: 77.5992438563327 | |
| - type: manhattan_recall | |
| value: 86.6948257655755 | |
| - type: max_accuracy | |
| value: 81.05035192203573 | |
| - type: max_ap | |
| value: 87.7880240053663 | |
| - type: max_f1 | |
| value: 82.50244379276637 | |
| task: | |
| type: PairClassification | |
| - dataset: | |
| config: default | |
| name: MTEB OnlineShopping | |
| revision: e610f2ebd179a8fda30ae534c3878750a96db120 | |
| split: test | |
| type: C-MTEB/OnlineShopping-classification | |
| metrics: | |
| - type: accuracy | |
| value: 93.5 | |
| - type: ap | |
| value: 91.31357903446782 | |
| - type: f1 | |
| value: 93.48088994006616 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB PAWSX | |
| revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1 | |
| split: test | |
| type: C-MTEB/PAWSX | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 36.93293453538077 | |
| - type: cos_sim_spearman | |
| value: 42.45972506308574 | |
| - type: euclidean_pearson | |
| value: 42.34945133152159 | |
| - type: euclidean_spearman | |
| value: 42.331610303674644 | |
| - type: manhattan_pearson | |
| value: 42.31455070249498 | |
| - type: manhattan_spearman | |
| value: 42.19887982891834 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB QBQTC | |
| revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7 | |
| split: test | |
| type: C-MTEB/QBQTC | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 33.683290790043785 | |
| - type: cos_sim_spearman | |
| value: 35.149171171202994 | |
| - type: euclidean_pearson | |
| value: 32.33806561267862 | |
| - type: euclidean_spearman | |
| value: 34.483576387347966 | |
| - type: manhattan_pearson | |
| value: 32.47629754599608 | |
| - type: manhattan_spearman | |
| value: 34.66434471867615 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: zh | |
| name: MTEB STS22 (zh) | |
| revision: eea2b4fe26a775864c896887d910b76a8098ad3f | |
| split: test | |
| type: mteb/sts22-crosslingual-sts | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 66.46322760516104 | |
| - type: cos_sim_spearman | |
| value: 67.398478319726 | |
| - type: euclidean_pearson | |
| value: 64.7223480293625 | |
| - type: euclidean_spearman | |
| value: 66.83118568812951 | |
| - type: manhattan_pearson | |
| value: 64.88440039828305 | |
| - type: manhattan_spearman | |
| value: 66.80429458952257 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB STSB | |
| revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0 | |
| split: test | |
| type: C-MTEB/STSB | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 79.08991383232105 | |
| - type: cos_sim_spearman | |
| value: 79.39715677296854 | |
| - type: euclidean_pearson | |
| value: 78.63201279320496 | |
| - type: euclidean_spearman | |
| value: 79.40262660785731 | |
| - type: manhattan_pearson | |
| value: 78.98138363146906 | |
| - type: manhattan_spearman | |
| value: 79.79968413014194 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB T2Reranking | |
| revision: 76631901a18387f85eaa53e5450019b87ad58ef9 | |
| split: dev | |
| type: C-MTEB/T2Reranking | |
| metrics: | |
| - type: map | |
| value: 67.43289278789972 | |
| - type: mrr | |
| value: 77.53012460908535 | |
| task: | |
| type: Reranking | |
| - dataset: | |
| config: default | |
| name: MTEB T2Retrieval | |
| revision: 8731a845f1bf500a4f111cf1070785c793d10e64 | |
| split: dev | |
| type: C-MTEB/T2Retrieval | |
| metrics: | |
| - type: map_at_1 | |
| value: 27.733999999999998 | |
| - type: map_at_10 | |
| value: 78.24799999999999 | |
| - type: map_at_100 | |
| value: 81.765 | |
| - type: map_at_1000 | |
| value: 81.824 | |
| - type: map_at_3 | |
| value: 54.92 | |
| - type: map_at_5 | |
| value: 67.61399999999999 | |
| - type: mrr_at_1 | |
| value: 90.527 | |
| - type: mrr_at_10 | |
| value: 92.843 | |
| - type: mrr_at_100 | |
| value: 92.927 | |
| - type: mrr_at_1000 | |
| value: 92.93 | |
| - type: mrr_at_3 | |
| value: 92.45100000000001 | |
| - type: mrr_at_5 | |
| value: 92.693 | |
| - type: ndcg_at_1 | |
| value: 90.527 | |
| - type: ndcg_at_10 | |
| value: 85.466 | |
| - type: ndcg_at_100 | |
| value: 88.846 | |
| - type: ndcg_at_1000 | |
| value: 89.415 | |
| - type: ndcg_at_3 | |
| value: 86.768 | |
| - type: ndcg_at_5 | |
| value: 85.46000000000001 | |
| - type: precision_at_1 | |
| value: 90.527 | |
| - type: precision_at_10 | |
| value: 42.488 | |
| - type: precision_at_100 | |
| value: 5.024 | |
| - type: precision_at_1000 | |
| value: 0.516 | |
| - type: precision_at_3 | |
| value: 75.907 | |
| - type: precision_at_5 | |
| value: 63.727000000000004 | |
| - type: recall_at_1 | |
| value: 27.733999999999998 | |
| - type: recall_at_10 | |
| value: 84.346 | |
| - type: recall_at_100 | |
| value: 95.536 | |
| - type: recall_at_1000 | |
| value: 98.42999999999999 | |
| - type: recall_at_3 | |
| value: 56.455 | |
| - type: recall_at_5 | |
| value: 70.755 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB TNews | |
| revision: 317f262bf1e6126357bbe89e875451e4b0938fe4 | |
| split: validation | |
| type: C-MTEB/TNews-classification | |
| metrics: | |
| - type: accuracy | |
| value: 49.952000000000005 | |
| - type: f1 | |
| value: 48.264617195258054 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB ThuNewsClusteringP2P | |
| revision: 5798586b105c0434e4f0fe5e767abe619442cf93 | |
| split: test | |
| type: C-MTEB/ThuNewsClusteringP2P | |
| metrics: | |
| - type: v_measure | |
| value: 68.23769904483508 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB ThuNewsClusteringS2S | |
| revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d | |
| split: test | |
| type: C-MTEB/ThuNewsClusteringS2S | |
| metrics: | |
| - type: v_measure | |
| value: 62.50294403136556 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB VideoRetrieval | |
| revision: 58c2597a5943a2ba48f4668c3b90d796283c5639 | |
| split: dev | |
| type: C-MTEB/VideoRetrieval | |
| metrics: | |
| - type: map_at_1 | |
| value: 54.0 | |
| - type: map_at_10 | |
| value: 63.668 | |
| - type: map_at_100 | |
| value: 64.217 | |
| - type: map_at_1000 | |
| value: 64.23100000000001 | |
| - type: map_at_3 | |
| value: 61.7 | |
| - type: map_at_5 | |
| value: 62.870000000000005 | |
| - type: mrr_at_1 | |
| value: 54.0 | |
| - type: mrr_at_10 | |
| value: 63.668 | |
| - type: mrr_at_100 | |
| value: 64.217 | |
| - type: mrr_at_1000 | |
| value: 64.23100000000001 | |
| - type: mrr_at_3 | |
| value: 61.7 | |
| - type: mrr_at_5 | |
| value: 62.870000000000005 | |
| - type: ndcg_at_1 | |
| value: 54.0 | |
| - type: ndcg_at_10 | |
| value: 68.11399999999999 | |
| - type: ndcg_at_100 | |
| value: 70.723 | |
| - type: ndcg_at_1000 | |
| value: 71.123 | |
| - type: ndcg_at_3 | |
| value: 64.074 | |
| - type: ndcg_at_5 | |
| value: 66.178 | |
| - type: precision_at_1 | |
| value: 54.0 | |
| - type: precision_at_10 | |
| value: 8.200000000000001 | |
| - type: precision_at_100 | |
| value: 0.941 | |
| - type: precision_at_1000 | |
| value: 0.097 | |
| - type: precision_at_3 | |
| value: 23.633000000000003 | |
| - type: precision_at_5 | |
| value: 15.2 | |
| - type: recall_at_1 | |
| value: 54.0 | |
| - type: recall_at_10 | |
| value: 82.0 | |
| - type: recall_at_100 | |
| value: 94.1 | |
| - type: recall_at_1000 | |
| value: 97.3 | |
| - type: recall_at_3 | |
| value: 70.89999999999999 | |
| - type: recall_at_5 | |
| value: 76.0 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB Waimai | |
| revision: 339287def212450dcaa9df8c22bf93e9980c7023 | |
| split: test | |
| type: C-MTEB/waimai-classification | |
| metrics: | |
| - type: accuracy | |
| value: 86.63000000000001 | |
| - type: ap | |
| value: 69.99457882599567 | |
| - type: f1 | |
| value: 85.07735617998541 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB 8TagsClustering | |
| revision: None | |
| split: test | |
| type: PL-MTEB/8tags-clustering | |
| metrics: | |
| - type: v_measure | |
| value: 44.594104491193555 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB AllegroReviews | |
| revision: None | |
| split: test | |
| type: PL-MTEB/allegro-reviews | |
| metrics: | |
| - type: accuracy | |
| value: 63.97614314115309 | |
| - type: f1 | |
| value: 52.15634261679283 | |
| 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: 32.646 | |
| - type: map_at_10 | |
| value: 47.963 | |
| - type: map_at_100 | |
| value: 48.789 | |
| - type: map_at_1000 | |
| value: 48.797000000000004 | |
| - type: map_at_3 | |
| value: 43.196 | |
| - type: map_at_5 | |
| value: 46.016 | |
| - type: mrr_at_1 | |
| value: 33.073 | |
| - type: mrr_at_10 | |
| value: 48.126000000000005 | |
| - type: mrr_at_100 | |
| value: 48.946 | |
| - type: mrr_at_1000 | |
| value: 48.953 | |
| - type: mrr_at_3 | |
| value: 43.374 | |
| - type: mrr_at_5 | |
| value: 46.147 | |
| - type: ndcg_at_1 | |
| value: 32.646 | |
| - type: ndcg_at_10 | |
| value: 56.481 | |
| - type: ndcg_at_100 | |
| value: 59.922 | |
| - type: ndcg_at_1000 | |
| value: 60.07 | |
| - type: ndcg_at_3 | |
| value: 46.675 | |
| - type: ndcg_at_5 | |
| value: 51.76500000000001 | |
| - type: precision_at_1 | |
| value: 32.646 | |
| - type: precision_at_10 | |
| value: 8.371 | |
| - type: precision_at_100 | |
| value: 0.9860000000000001 | |
| - type: precision_at_1000 | |
| value: 0.1 | |
| - type: precision_at_3 | |
| value: 18.919 | |
| - type: precision_at_5 | |
| value: 13.825999999999999 | |
| - type: recall_at_1 | |
| value: 32.646 | |
| - type: recall_at_10 | |
| value: 83.71300000000001 | |
| - type: recall_at_100 | |
| value: 98.578 | |
| - type: recall_at_1000 | |
| value: 99.644 | |
| - type: recall_at_3 | |
| value: 56.757000000000005 | |
| - type: recall_at_5 | |
| value: 69.132 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB CBD | |
| revision: None | |
| split: test | |
| type: PL-MTEB/cbd | |
| metrics: | |
| - type: accuracy | |
| value: 68.56 | |
| - type: ap | |
| value: 23.310493680488513 | |
| - type: f1 | |
| value: 58.85369533105693 | |
| 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: 88.5 | |
| - type: cos_sim_ap | |
| value: 72.42140924378361 | |
| - type: cos_sim_f1 | |
| value: 66.0919540229885 | |
| - type: cos_sim_precision | |
| value: 72.78481012658227 | |
| - type: cos_sim_recall | |
| value: 60.526315789473685 | |
| - type: dot_accuracy | |
| value: 88.5 | |
| - type: dot_ap | |
| value: 72.42140924378361 | |
| - type: dot_f1 | |
| value: 66.0919540229885 | |
| - type: dot_precision | |
| value: 72.78481012658227 | |
| - type: dot_recall | |
| value: 60.526315789473685 | |
| - type: euclidean_accuracy | |
| value: 88.5 | |
| - type: euclidean_ap | |
| value: 72.42140924378361 | |
| - type: euclidean_f1 | |
| value: 66.0919540229885 | |
| - type: euclidean_precision | |
| value: 72.78481012658227 | |
| - type: euclidean_recall | |
| value: 60.526315789473685 | |
| - type: manhattan_accuracy | |
| value: 88.5 | |
| - type: manhattan_ap | |
| value: 72.49745515311696 | |
| - type: manhattan_f1 | |
| value: 66.0968660968661 | |
| - type: manhattan_precision | |
| value: 72.04968944099379 | |
| - type: manhattan_recall | |
| value: 61.05263157894737 | |
| - type: max_accuracy | |
| value: 88.5 | |
| - type: max_ap | |
| value: 72.49745515311696 | |
| - type: max_f1 | |
| value: 66.0968660968661 | |
| task: | |
| type: PairClassification | |
| - dataset: | |
| config: default | |
| name: MTEB CDSC-R | |
| revision: None | |
| split: test | |
| type: PL-MTEB/cdscr-sts | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 90.32269765590145 | |
| - type: cos_sim_spearman | |
| value: 89.73666311491672 | |
| - type: euclidean_pearson | |
| value: 88.2933868516544 | |
| - type: euclidean_spearman | |
| value: 89.73666311491672 | |
| - type: manhattan_pearson | |
| value: 88.33474590219448 | |
| - type: manhattan_spearman | |
| value: 89.8548364866583 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB DBPedia-PL | |
| revision: 76afe41d9af165cc40999fcaa92312b8b012064a | |
| split: test | |
| type: clarin-knext/dbpedia-pl | |
| metrics: | |
| - type: map_at_1 | |
| value: 7.632999999999999 | |
| - type: map_at_10 | |
| value: 16.426 | |
| - type: map_at_100 | |
| value: 22.651 | |
| - type: map_at_1000 | |
| value: 24.372 | |
| - type: map_at_3 | |
| value: 11.706 | |
| - type: map_at_5 | |
| value: 13.529 | |
| - type: mrr_at_1 | |
| value: 60.75000000000001 | |
| - type: mrr_at_10 | |
| value: 68.613 | |
| - type: mrr_at_100 | |
| value: 69.001 | |
| - type: mrr_at_1000 | |
| value: 69.021 | |
| - type: mrr_at_3 | |
| value: 67.0 | |
| - type: mrr_at_5 | |
| value: 67.925 | |
| - type: ndcg_at_1 | |
| value: 49.875 | |
| - type: ndcg_at_10 | |
| value: 36.978 | |
| - type: ndcg_at_100 | |
| value: 40.031 | |
| - type: ndcg_at_1000 | |
| value: 47.566 | |
| - type: ndcg_at_3 | |
| value: 41.148 | |
| - type: ndcg_at_5 | |
| value: 38.702 | |
| - type: precision_at_1 | |
| value: 60.75000000000001 | |
| - type: precision_at_10 | |
| value: 29.7 | |
| - type: precision_at_100 | |
| value: 9.278 | |
| - type: precision_at_1000 | |
| value: 2.099 | |
| - type: precision_at_3 | |
| value: 44.0 | |
| - type: precision_at_5 | |
| value: 37.6 | |
| - type: recall_at_1 | |
| value: 7.632999999999999 | |
| - type: recall_at_10 | |
| value: 22.040000000000003 | |
| - type: recall_at_100 | |
| value: 44.024 | |
| - type: recall_at_1000 | |
| value: 67.848 | |
| - type: recall_at_3 | |
| value: 13.093 | |
| - type: recall_at_5 | |
| value: 15.973 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB FiQA-PL | |
| revision: 2e535829717f8bf9dc829b7f911cc5bbd4e6608e | |
| split: test | |
| type: clarin-knext/fiqa-pl | |
| metrics: | |
| - type: map_at_1 | |
| value: 15.473 | |
| - type: map_at_10 | |
| value: 24.579 | |
| - type: map_at_100 | |
| value: 26.387 | |
| - type: map_at_1000 | |
| value: 26.57 | |
| - type: map_at_3 | |
| value: 21.278 | |
| - type: map_at_5 | |
| value: 23.179 | |
| - type: mrr_at_1 | |
| value: 30.709999999999997 | |
| - type: mrr_at_10 | |
| value: 38.994 | |
| - type: mrr_at_100 | |
| value: 39.993 | |
| - type: mrr_at_1000 | |
| value: 40.044999999999995 | |
| - type: mrr_at_3 | |
| value: 36.342999999999996 | |
| - type: mrr_at_5 | |
| value: 37.846999999999994 | |
| - type: ndcg_at_1 | |
| value: 30.709999999999997 | |
| - type: ndcg_at_10 | |
| value: 31.608999999999998 | |
| - type: ndcg_at_100 | |
| value: 38.807 | |
| - type: ndcg_at_1000 | |
| value: 42.208 | |
| - type: ndcg_at_3 | |
| value: 28.086 | |
| - type: ndcg_at_5 | |
| value: 29.323 | |
| - type: precision_at_1 | |
| value: 30.709999999999997 | |
| - type: precision_at_10 | |
| value: 8.688 | |
| - type: precision_at_100 | |
| value: 1.608 | |
| - type: precision_at_1000 | |
| value: 0.22100000000000003 | |
| - type: precision_at_3 | |
| value: 18.724 | |
| - type: precision_at_5 | |
| value: 13.950999999999999 | |
| - type: recall_at_1 | |
| value: 15.473 | |
| - type: recall_at_10 | |
| value: 38.361000000000004 | |
| - type: recall_at_100 | |
| value: 65.2 | |
| - type: recall_at_1000 | |
| value: 85.789 | |
| - type: recall_at_3 | |
| value: 25.401 | |
| - type: recall_at_5 | |
| value: 30.875999999999998 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB HotpotQA-PL | |
| revision: a0bd479ac97b4ccb5bd6ce320c415d0bb4beb907 | |
| split: test | |
| type: clarin-knext/hotpotqa-pl | |
| metrics: | |
| - type: map_at_1 | |
| value: 38.096000000000004 | |
| - type: map_at_10 | |
| value: 51.44499999999999 | |
| - type: map_at_100 | |
| value: 52.325 | |
| - type: map_at_1000 | |
| value: 52.397000000000006 | |
| - type: map_at_3 | |
| value: 48.626999999999995 | |
| - type: map_at_5 | |
| value: 50.342 | |
| - type: mrr_at_1 | |
| value: 76.19200000000001 | |
| - type: mrr_at_10 | |
| value: 81.191 | |
| - type: mrr_at_100 | |
| value: 81.431 | |
| - type: mrr_at_1000 | |
| value: 81.443 | |
| - type: mrr_at_3 | |
| value: 80.30199999999999 | |
| - type: mrr_at_5 | |
| value: 80.85900000000001 | |
| - type: ndcg_at_1 | |
| value: 76.19200000000001 | |
| - type: ndcg_at_10 | |
| value: 60.9 | |
| - type: ndcg_at_100 | |
| value: 64.14699999999999 | |
| - type: ndcg_at_1000 | |
| value: 65.647 | |
| - type: ndcg_at_3 | |
| value: 56.818000000000005 | |
| - type: ndcg_at_5 | |
| value: 59.019999999999996 | |
| - type: precision_at_1 | |
| value: 76.19200000000001 | |
| - type: precision_at_10 | |
| value: 12.203 | |
| - type: precision_at_100 | |
| value: 1.478 | |
| - type: precision_at_1000 | |
| value: 0.168 | |
| - type: precision_at_3 | |
| value: 34.616 | |
| - type: precision_at_5 | |
| value: 22.515 | |
| - type: recall_at_1 | |
| value: 38.096000000000004 | |
| - type: recall_at_10 | |
| value: 61.013 | |
| - type: recall_at_100 | |
| value: 73.90299999999999 | |
| - type: recall_at_1000 | |
| value: 83.91 | |
| - type: recall_at_3 | |
| value: 51.92400000000001 | |
| - type: recall_at_5 | |
| value: 56.286 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB MSMARCO-PL | |
| revision: 8634c07806d5cce3a6138e260e59b81760a0a640 | |
| split: test | |
| type: clarin-knext/msmarco-pl | |
| metrics: | |
| - type: map_at_1 | |
| value: 1.548 | |
| - type: map_at_10 | |
| value: 11.049000000000001 | |
| - type: map_at_100 | |
| value: 28.874 | |
| - type: map_at_1000 | |
| value: 34.931 | |
| - type: map_at_3 | |
| value: 4.162 | |
| - type: map_at_5 | |
| value: 6.396 | |
| - type: mrr_at_1 | |
| value: 90.69800000000001 | |
| - type: mrr_at_10 | |
| value: 92.093 | |
| - type: mrr_at_100 | |
| value: 92.345 | |
| - type: mrr_at_1000 | |
| value: 92.345 | |
| - type: mrr_at_3 | |
| value: 91.86 | |
| - type: mrr_at_5 | |
| value: 91.86 | |
| - type: ndcg_at_1 | |
| value: 74.031 | |
| - type: ndcg_at_10 | |
| value: 63.978 | |
| - type: ndcg_at_100 | |
| value: 53.101 | |
| - type: ndcg_at_1000 | |
| value: 60.675999999999995 | |
| - type: ndcg_at_3 | |
| value: 71.421 | |
| - type: ndcg_at_5 | |
| value: 68.098 | |
| - type: precision_at_1 | |
| value: 90.69800000000001 | |
| - type: precision_at_10 | |
| value: 71.86 | |
| - type: precision_at_100 | |
| value: 31.395 | |
| - type: precision_at_1000 | |
| value: 5.981 | |
| - type: precision_at_3 | |
| value: 84.49600000000001 | |
| - type: precision_at_5 | |
| value: 79.07 | |
| - type: recall_at_1 | |
| value: 1.548 | |
| - type: recall_at_10 | |
| value: 12.149000000000001 | |
| - type: recall_at_100 | |
| value: 40.794999999999995 | |
| - type: recall_at_1000 | |
| value: 67.974 | |
| - type: recall_at_3 | |
| value: 4.244 | |
| - type: recall_at_5 | |
| value: 6.608 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: pl | |
| name: MTEB MassiveIntentClassification (pl) | |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 | |
| split: test | |
| type: mteb/amazon_massive_intent | |
| metrics: | |
| - type: accuracy | |
| value: 73.55413584398119 | |
| - type: f1 | |
| value: 69.65610882318181 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: pl | |
| name: MTEB MassiveScenarioClassification (pl) | |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 | |
| split: test | |
| type: mteb/amazon_massive_scenario | |
| metrics: | |
| - type: accuracy | |
| value: 76.37188971082716 | |
| - type: f1 | |
| value: 75.64847309941361 | |
| 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: 4.919 | |
| - type: map_at_10 | |
| value: 10.834000000000001 | |
| - type: map_at_100 | |
| value: 13.38 | |
| - type: map_at_1000 | |
| value: 14.581 | |
| - type: map_at_3 | |
| value: 8.198 | |
| - type: map_at_5 | |
| value: 9.428 | |
| - type: mrr_at_1 | |
| value: 41.176 | |
| - type: mrr_at_10 | |
| value: 50.083 | |
| - type: mrr_at_100 | |
| value: 50.559 | |
| - type: mrr_at_1000 | |
| value: 50.604000000000006 | |
| - type: mrr_at_3 | |
| value: 47.936 | |
| - type: mrr_at_5 | |
| value: 49.407000000000004 | |
| - type: ndcg_at_1 | |
| value: 39.628 | |
| - type: ndcg_at_10 | |
| value: 30.098000000000003 | |
| - type: ndcg_at_100 | |
| value: 27.061 | |
| - type: ndcg_at_1000 | |
| value: 35.94 | |
| - type: ndcg_at_3 | |
| value: 35.135 | |
| - type: ndcg_at_5 | |
| value: 33.335 | |
| - type: precision_at_1 | |
| value: 41.176 | |
| - type: precision_at_10 | |
| value: 22.259999999999998 | |
| - type: precision_at_100 | |
| value: 6.712 | |
| - type: precision_at_1000 | |
| value: 1.9060000000000001 | |
| - type: precision_at_3 | |
| value: 33.23 | |
| - type: precision_at_5 | |
| value: 29.04 | |
| - type: recall_at_1 | |
| value: 4.919 | |
| - type: recall_at_10 | |
| value: 14.196 | |
| - type: recall_at_100 | |
| value: 26.948 | |
| - type: recall_at_1000 | |
| value: 59.211000000000006 | |
| - type: recall_at_3 | |
| value: 9.44 | |
| - type: recall_at_5 | |
| value: 11.569 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB NQ-PL | |
| revision: f171245712cf85dd4700b06bef18001578d0ca8d | |
| split: test | |
| type: clarin-knext/nq-pl | |
| metrics: | |
| - type: map_at_1 | |
| value: 25.35 | |
| - type: map_at_10 | |
| value: 37.884 | |
| - type: map_at_100 | |
| value: 38.955 | |
| - type: map_at_1000 | |
| value: 39.007999999999996 | |
| - type: map_at_3 | |
| value: 34.239999999999995 | |
| - type: map_at_5 | |
| value: 36.398 | |
| - type: mrr_at_1 | |
| value: 28.737000000000002 | |
| - type: mrr_at_10 | |
| value: 39.973 | |
| - type: mrr_at_100 | |
| value: 40.844 | |
| - type: mrr_at_1000 | |
| value: 40.885 | |
| - type: mrr_at_3 | |
| value: 36.901 | |
| - type: mrr_at_5 | |
| value: 38.721 | |
| - type: ndcg_at_1 | |
| value: 28.708 | |
| - type: ndcg_at_10 | |
| value: 44.204 | |
| - type: ndcg_at_100 | |
| value: 48.978 | |
| - type: ndcg_at_1000 | |
| value: 50.33 | |
| - type: ndcg_at_3 | |
| value: 37.36 | |
| - type: ndcg_at_5 | |
| value: 40.912 | |
| - type: precision_at_1 | |
| value: 28.708 | |
| - type: precision_at_10 | |
| value: 7.367 | |
| - type: precision_at_100 | |
| value: 1.0030000000000001 | |
| - type: precision_at_1000 | |
| value: 0.11299999999999999 | |
| - type: precision_at_3 | |
| value: 17.034 | |
| - type: precision_at_5 | |
| value: 12.293999999999999 | |
| - type: recall_at_1 | |
| value: 25.35 | |
| - type: recall_at_10 | |
| value: 61.411 | |
| - type: recall_at_100 | |
| value: 82.599 | |
| - type: recall_at_1000 | |
| value: 92.903 | |
| - type: recall_at_3 | |
| value: 43.728 | |
| - type: recall_at_5 | |
| value: 51.854 | |
| task: | |
| type: 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: 77.49422763833996 | |
| - type: f1 | |
| value: 66.73472657783407 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB PPC | |
| revision: None | |
| split: test | |
| type: PL-MTEB/ppc-pairclassification | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 81.0 | |
| - type: cos_sim_ap | |
| value: 91.47194213011349 | |
| - type: cos_sim_f1 | |
| value: 84.73767885532592 | |
| - type: cos_sim_precision | |
| value: 81.49847094801224 | |
| - type: cos_sim_recall | |
| value: 88.24503311258279 | |
| - type: dot_accuracy | |
| value: 81.0 | |
| - type: dot_ap | |
| value: 91.47194213011349 | |
| - type: dot_f1 | |
| value: 84.73767885532592 | |
| - type: dot_precision | |
| value: 81.49847094801224 | |
| - type: dot_recall | |
| value: 88.24503311258279 | |
| - type: euclidean_accuracy | |
| value: 81.0 | |
| - type: euclidean_ap | |
| value: 91.47194213011349 | |
| - type: euclidean_f1 | |
| value: 84.73767885532592 | |
| - type: euclidean_precision | |
| value: 81.49847094801224 | |
| - type: euclidean_recall | |
| value: 88.24503311258279 | |
| - type: manhattan_accuracy | |
| value: 81.0 | |
| - type: manhattan_ap | |
| value: 91.46464475050571 | |
| - type: manhattan_f1 | |
| value: 84.48687350835321 | |
| - type: manhattan_precision | |
| value: 81.31699846860643 | |
| - type: manhattan_recall | |
| value: 87.91390728476821 | |
| - type: max_accuracy | |
| value: 81.0 | |
| - type: max_ap | |
| value: 91.47194213011349 | |
| - type: max_f1 | |
| value: 84.73767885532592 | |
| task: | |
| type: PairClassification | |
| - dataset: | |
| config: default | |
| name: MTEB PSC | |
| revision: None | |
| split: test | |
| type: PL-MTEB/psc-pairclassification | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 97.6808905380334 | |
| - type: cos_sim_ap | |
| value: 99.27948611836348 | |
| - type: cos_sim_f1 | |
| value: 96.15975422427034 | |
| - type: cos_sim_precision | |
| value: 96.90402476780186 | |
| - type: cos_sim_recall | |
| value: 95.42682926829268 | |
| - type: dot_accuracy | |
| value: 97.6808905380334 | |
| - type: dot_ap | |
| value: 99.2794861183635 | |
| - type: dot_f1 | |
| value: 96.15975422427034 | |
| - type: dot_precision | |
| value: 96.90402476780186 | |
| - type: dot_recall | |
| value: 95.42682926829268 | |
| - type: euclidean_accuracy | |
| value: 97.6808905380334 | |
| - type: euclidean_ap | |
| value: 99.2794861183635 | |
| - type: euclidean_f1 | |
| value: 96.15975422427034 | |
| - type: euclidean_precision | |
| value: 96.90402476780186 | |
| - type: euclidean_recall | |
| value: 95.42682926829268 | |
| - type: manhattan_accuracy | |
| value: 97.6808905380334 | |
| - type: manhattan_ap | |
| value: 99.28715055268721 | |
| - type: manhattan_f1 | |
| value: 96.14791987673343 | |
| - type: manhattan_precision | |
| value: 97.19626168224299 | |
| - type: manhattan_recall | |
| value: 95.1219512195122 | |
| - type: max_accuracy | |
| value: 97.6808905380334 | |
| - type: max_ap | |
| value: 99.28715055268721 | |
| - type: max_f1 | |
| value: 96.15975422427034 | |
| task: | |
| type: PairClassification | |
| - dataset: | |
| config: default | |
| name: MTEB PolEmo2.0-IN | |
| revision: None | |
| split: test | |
| type: PL-MTEB/polemo2_in | |
| metrics: | |
| - type: accuracy | |
| value: 86.16343490304708 | |
| - type: f1 | |
| value: 83.3442579486744 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB PolEmo2.0-OUT | |
| revision: None | |
| split: test | |
| type: PL-MTEB/polemo2_out | |
| metrics: | |
| - type: accuracy | |
| value: 68.40080971659918 | |
| - type: f1 | |
| value: 53.13720751142237 | |
| 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: 63.322 | |
| - type: map_at_10 | |
| value: 76.847 | |
| - type: map_at_100 | |
| value: 77.616 | |
| - type: map_at_1000 | |
| value: 77.644 | |
| - type: map_at_3 | |
| value: 73.624 | |
| - type: map_at_5 | |
| value: 75.603 | |
| - type: mrr_at_1 | |
| value: 72.88 | |
| - type: mrr_at_10 | |
| value: 80.376 | |
| - type: mrr_at_100 | |
| value: 80.604 | |
| - type: mrr_at_1000 | |
| value: 80.61 | |
| - type: mrr_at_3 | |
| value: 78.92 | |
| - type: mrr_at_5 | |
| value: 79.869 | |
| - type: ndcg_at_1 | |
| value: 72.89999999999999 | |
| - type: ndcg_at_10 | |
| value: 81.43 | |
| - type: ndcg_at_100 | |
| value: 83.394 | |
| - type: ndcg_at_1000 | |
| value: 83.685 | |
| - type: ndcg_at_3 | |
| value: 77.62599999999999 | |
| - type: ndcg_at_5 | |
| value: 79.656 | |
| - type: precision_at_1 | |
| value: 72.89999999999999 | |
| - type: precision_at_10 | |
| value: 12.548 | |
| - type: precision_at_100 | |
| value: 1.4869999999999999 | |
| - type: precision_at_1000 | |
| value: 0.155 | |
| - type: precision_at_3 | |
| value: 34.027 | |
| - type: precision_at_5 | |
| value: 22.654 | |
| - type: recall_at_1 | |
| value: 63.322 | |
| - type: recall_at_10 | |
| value: 90.664 | |
| - type: recall_at_100 | |
| value: 97.974 | |
| - type: recall_at_1000 | |
| value: 99.636 | |
| - type: recall_at_3 | |
| value: 80.067 | |
| - type: recall_at_5 | |
| value: 85.526 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB SCIDOCS-PL | |
| revision: 45452b03f05560207ef19149545f168e596c9337 | |
| split: test | |
| type: clarin-knext/scidocs-pl | |
| metrics: | |
| - type: map_at_1 | |
| value: 3.95 | |
| - type: map_at_10 | |
| value: 9.658999999999999 | |
| - type: map_at_100 | |
| value: 11.384 | |
| - type: map_at_1000 | |
| value: 11.677 | |
| - type: map_at_3 | |
| value: 7.055 | |
| - type: map_at_5 | |
| value: 8.244 | |
| - type: mrr_at_1 | |
| value: 19.5 | |
| - type: mrr_at_10 | |
| value: 28.777 | |
| - type: mrr_at_100 | |
| value: 29.936 | |
| - type: mrr_at_1000 | |
| value: 30.009999999999998 | |
| - type: mrr_at_3 | |
| value: 25.55 | |
| - type: mrr_at_5 | |
| value: 27.284999999999997 | |
| - type: ndcg_at_1 | |
| value: 19.5 | |
| - type: ndcg_at_10 | |
| value: 16.589000000000002 | |
| - type: ndcg_at_100 | |
| value: 23.879 | |
| - type: ndcg_at_1000 | |
| value: 29.279 | |
| - type: ndcg_at_3 | |
| value: 15.719 | |
| - type: ndcg_at_5 | |
| value: 13.572000000000001 | |
| - type: precision_at_1 | |
| value: 19.5 | |
| - type: precision_at_10 | |
| value: 8.62 | |
| - type: precision_at_100 | |
| value: 1.924 | |
| - type: precision_at_1000 | |
| value: 0.322 | |
| - type: precision_at_3 | |
| value: 14.6 | |
| - type: precision_at_5 | |
| value: 11.78 | |
| - type: recall_at_1 | |
| value: 3.95 | |
| - type: recall_at_10 | |
| value: 17.477999999999998 | |
| - type: recall_at_100 | |
| value: 38.99 | |
| - type: recall_at_1000 | |
| value: 65.417 | |
| - type: recall_at_3 | |
| value: 8.883000000000001 | |
| - type: recall_at_5 | |
| value: 11.933 | |
| task: | |
| type: 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: 83.48960456583775 | |
| - type: cos_sim_ap | |
| value: 76.31522115825375 | |
| - type: cos_sim_f1 | |
| value: 70.35573122529645 | |
| - type: cos_sim_precision | |
| value: 70.9934735315446 | |
| - type: cos_sim_recall | |
| value: 69.72934472934473 | |
| - type: dot_accuracy | |
| value: 83.48960456583775 | |
| - type: dot_ap | |
| value: 76.31522115825373 | |
| - type: dot_f1 | |
| value: 70.35573122529645 | |
| - type: dot_precision | |
| value: 70.9934735315446 | |
| - type: dot_recall | |
| value: 69.72934472934473 | |
| - type: euclidean_accuracy | |
| value: 83.48960456583775 | |
| - type: euclidean_ap | |
| value: 76.31522115825373 | |
| - type: euclidean_f1 | |
| value: 70.35573122529645 | |
| - type: euclidean_precision | |
| value: 70.9934735315446 | |
| - type: euclidean_recall | |
| value: 69.72934472934473 | |
| - type: manhattan_accuracy | |
| value: 83.46922136159804 | |
| - type: manhattan_ap | |
| value: 76.18474601388084 | |
| - type: manhattan_f1 | |
| value: 70.34779490856937 | |
| - type: manhattan_precision | |
| value: 70.83032490974729 | |
| - type: manhattan_recall | |
| value: 69.87179487179486 | |
| - type: max_accuracy | |
| value: 83.48960456583775 | |
| - type: max_ap | |
| value: 76.31522115825375 | |
| - type: max_f1 | |
| value: 70.35573122529645 | |
| task: | |
| type: 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: 77.95374883876302 | |
| - type: cos_sim_spearman | |
| value: 73.77630219171942 | |
| - type: euclidean_pearson | |
| value: 75.81927069594934 | |
| - type: euclidean_spearman | |
| value: 73.7763211303831 | |
| - type: manhattan_pearson | |
| value: 76.03126859057528 | |
| - type: manhattan_spearman | |
| value: 73.96528138013369 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: pl | |
| name: MTEB STS22 (pl) | |
| revision: eea2b4fe26a775864c896887d910b76a8098ad3f | |
| split: test | |
| type: mteb/sts22-crosslingual-sts | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 37.388282764841826 | |
| - type: cos_sim_spearman | |
| value: 40.83477184710897 | |
| - type: euclidean_pearson | |
| value: 26.754737044177805 | |
| - type: euclidean_spearman | |
| value: 40.83477184710897 | |
| - type: manhattan_pearson | |
| value: 26.760453110872458 | |
| - type: manhattan_spearman | |
| value: 41.034477441383856 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB SciFact-PL | |
| revision: 47932a35f045ef8ed01ba82bf9ff67f6e109207e | |
| split: test | |
| type: clarin-knext/scifact-pl | |
| metrics: | |
| - type: map_at_1 | |
| value: 49.15 | |
| - type: map_at_10 | |
| value: 61.690999999999995 | |
| - type: map_at_100 | |
| value: 62.348000000000006 | |
| - type: map_at_1000 | |
| value: 62.38 | |
| - type: map_at_3 | |
| value: 58.824 | |
| - type: map_at_5 | |
| value: 60.662000000000006 | |
| - type: mrr_at_1 | |
| value: 51.333 | |
| - type: mrr_at_10 | |
| value: 62.731 | |
| - type: mrr_at_100 | |
| value: 63.245 | |
| - type: mrr_at_1000 | |
| value: 63.275000000000006 | |
| - type: mrr_at_3 | |
| value: 60.667 | |
| - type: mrr_at_5 | |
| value: 61.93300000000001 | |
| - type: ndcg_at_1 | |
| value: 51.333 | |
| - type: ndcg_at_10 | |
| value: 67.168 | |
| - type: ndcg_at_100 | |
| value: 69.833 | |
| - type: ndcg_at_1000 | |
| value: 70.56700000000001 | |
| - type: ndcg_at_3 | |
| value: 62.40599999999999 | |
| - type: ndcg_at_5 | |
| value: 65.029 | |
| - type: precision_at_1 | |
| value: 51.333 | |
| - type: precision_at_10 | |
| value: 9.333 | |
| - type: precision_at_100 | |
| value: 1.0699999999999998 | |
| - type: precision_at_1000 | |
| value: 0.11299999999999999 | |
| - type: precision_at_3 | |
| value: 25.333 | |
| - type: precision_at_5 | |
| value: 17.067 | |
| - type: recall_at_1 | |
| value: 49.15 | |
| - type: recall_at_10 | |
| value: 82.533 | |
| - type: recall_at_100 | |
| value: 94.167 | |
| - type: recall_at_1000 | |
| value: 99.667 | |
| - type: recall_at_3 | |
| value: 69.917 | |
| - type: recall_at_5 | |
| value: 76.356 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB TRECCOVID-PL | |
| revision: 81bcb408f33366c2a20ac54adafad1ae7e877fdd | |
| split: test | |
| type: clarin-knext/trec-covid-pl | |
| metrics: | |
| - type: map_at_1 | |
| value: 0.261 | |
| - type: map_at_10 | |
| value: 2.1260000000000003 | |
| - type: map_at_100 | |
| value: 12.171999999999999 | |
| - type: map_at_1000 | |
| value: 26.884999999999998 | |
| - type: map_at_3 | |
| value: 0.695 | |
| - type: map_at_5 | |
| value: 1.134 | |
| - type: mrr_at_1 | |
| value: 96.0 | |
| - type: mrr_at_10 | |
| value: 96.952 | |
| - type: mrr_at_100 | |
| value: 96.952 | |
| - type: mrr_at_1000 | |
| value: 96.952 | |
| - type: mrr_at_3 | |
| value: 96.667 | |
| - type: mrr_at_5 | |
| value: 96.667 | |
| - type: ndcg_at_1 | |
| value: 92.0 | |
| - type: ndcg_at_10 | |
| value: 81.193 | |
| - type: ndcg_at_100 | |
| value: 61.129 | |
| - type: ndcg_at_1000 | |
| value: 51.157 | |
| - type: ndcg_at_3 | |
| value: 85.693 | |
| - type: ndcg_at_5 | |
| value: 84.129 | |
| - type: precision_at_1 | |
| value: 96.0 | |
| - type: precision_at_10 | |
| value: 85.39999999999999 | |
| - type: precision_at_100 | |
| value: 62.03999999999999 | |
| - type: precision_at_1000 | |
| value: 22.224 | |
| - type: precision_at_3 | |
| value: 88.0 | |
| - type: precision_at_5 | |
| value: 88.0 | |
| - type: recall_at_1 | |
| value: 0.261 | |
| - type: recall_at_10 | |
| value: 2.262 | |
| - type: recall_at_100 | |
| value: 14.981 | |
| - type: recall_at_1000 | |
| value: 46.837 | |
| - type: recall_at_3 | |
| value: 0.703 | |
| - type: recall_at_5 | |
| value: 1.172 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB AlloProfClusteringP2P | |
| revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b | |
| split: test | |
| type: lyon-nlp/alloprof | |
| metrics: | |
| - type: v_measure | |
| value: 70.55290063940157 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB AlloProfClusteringS2S | |
| revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b | |
| split: test | |
| type: lyon-nlp/alloprof | |
| metrics: | |
| - type: v_measure | |
| value: 55.41500719337263 | |
| 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: 73.48697375332002 | |
| - type: mrr | |
| value: 75.01836585523822 | |
| task: | |
| type: Reranking | |
| - dataset: | |
| config: default | |
| name: MTEB AlloprofRetrieval | |
| revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b | |
| split: test | |
| type: lyon-nlp/alloprof | |
| metrics: | |
| - type: map_at_1 | |
| value: 38.454 | |
| - type: map_at_10 | |
| value: 51.605000000000004 | |
| - type: map_at_100 | |
| value: 52.653000000000006 | |
| - type: map_at_1000 | |
| value: 52.697 | |
| - type: map_at_3 | |
| value: 48.304 | |
| - type: map_at_5 | |
| value: 50.073 | |
| - type: mrr_at_1 | |
| value: 43.307 | |
| - type: mrr_at_10 | |
| value: 54.400000000000006 | |
| - type: mrr_at_100 | |
| value: 55.147999999999996 | |
| - type: mrr_at_1000 | |
| value: 55.174 | |
| - type: mrr_at_3 | |
| value: 51.77 | |
| - type: mrr_at_5 | |
| value: 53.166999999999994 | |
| - type: ndcg_at_1 | |
| value: 43.307 | |
| - type: ndcg_at_10 | |
| value: 57.891000000000005 | |
| - type: ndcg_at_100 | |
| value: 62.161 | |
| - type: ndcg_at_1000 | |
| value: 63.083 | |
| - type: ndcg_at_3 | |
| value: 51.851 | |
| - type: ndcg_at_5 | |
| value: 54.605000000000004 | |
| - type: precision_at_1 | |
| value: 43.307 | |
| - type: precision_at_10 | |
| value: 9.033 | |
| - type: precision_at_100 | |
| value: 1.172 | |
| - type: precision_at_1000 | |
| value: 0.127 | |
| - type: precision_at_3 | |
| value: 22.798 | |
| - type: precision_at_5 | |
| value: 15.492 | |
| - type: recall_at_1 | |
| value: 38.454 | |
| - type: recall_at_10 | |
| value: 74.166 | |
| - type: recall_at_100 | |
| value: 92.43599999999999 | |
| - type: recall_at_1000 | |
| value: 99.071 | |
| - type: recall_at_3 | |
| value: 58.087 | |
| - type: recall_at_5 | |
| value: 64.568 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: fr | |
| name: MTEB AmazonReviewsClassification (fr) | |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d | |
| split: test | |
| type: mteb/amazon_reviews_multi | |
| metrics: | |
| - type: accuracy | |
| value: 53.474 | |
| - type: f1 | |
| value: 50.38275392350236 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: default | |
| name: MTEB BSARDRetrieval | |
| revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59 | |
| split: test | |
| type: maastrichtlawtech/bsard | |
| metrics: | |
| - type: map_at_1 | |
| value: 2.252 | |
| - type: map_at_10 | |
| value: 4.661 | |
| - type: map_at_100 | |
| value: 5.271 | |
| - type: map_at_1000 | |
| value: 5.3629999999999995 | |
| - type: map_at_3 | |
| value: 3.604 | |
| - type: map_at_5 | |
| value: 4.3020000000000005 | |
| - type: mrr_at_1 | |
| value: 2.252 | |
| - type: mrr_at_10 | |
| value: 4.661 | |
| - type: mrr_at_100 | |
| value: 5.271 | |
| - type: mrr_at_1000 | |
| value: 5.3629999999999995 | |
| - type: mrr_at_3 | |
| value: 3.604 | |
| - type: mrr_at_5 | |
| value: 4.3020000000000005 | |
| - type: ndcg_at_1 | |
| value: 2.252 | |
| - type: ndcg_at_10 | |
| value: 6.3020000000000005 | |
| - type: ndcg_at_100 | |
| value: 10.342 | |
| - type: ndcg_at_1000 | |
| value: 13.475999999999999 | |
| - type: ndcg_at_3 | |
| value: 4.0649999999999995 | |
| - type: ndcg_at_5 | |
| value: 5.344 | |
| - type: precision_at_1 | |
| value: 2.252 | |
| - type: precision_at_10 | |
| value: 1.171 | |
| - type: precision_at_100 | |
| value: 0.333 | |
| - type: precision_at_1000 | |
| value: 0.059000000000000004 | |
| - type: precision_at_3 | |
| value: 1.802 | |
| - type: precision_at_5 | |
| value: 1.712 | |
| - type: recall_at_1 | |
| value: 2.252 | |
| - type: recall_at_10 | |
| value: 11.712 | |
| - type: recall_at_100 | |
| value: 33.333 | |
| - type: recall_at_1000 | |
| value: 59.458999999999996 | |
| - type: recall_at_3 | |
| value: 5.405 | |
| - type: recall_at_5 | |
| value: 8.559 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: default | |
| name: MTEB HALClusteringS2S | |
| revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915 | |
| split: test | |
| type: lyon-nlp/clustering-hal-s2s | |
| metrics: | |
| - type: v_measure | |
| value: 28.301882091023288 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB MLSUMClusteringP2P | |
| revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 | |
| split: test | |
| type: mlsum | |
| metrics: | |
| - type: v_measure | |
| value: 45.26992995191701 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: default | |
| name: MTEB MLSUMClusteringS2S | |
| revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 | |
| split: test | |
| type: mlsum | |
| metrics: | |
| - type: v_measure | |
| value: 42.773174876871145 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: fr | |
| name: MTEB MTOPDomainClassification (fr) | |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf | |
| split: test | |
| type: mteb/mtop_domain | |
| metrics: | |
| - type: accuracy | |
| value: 93.47635452552458 | |
| - type: f1 | |
| value: 93.19922617577213 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: fr | |
| name: MTEB MTOPIntentClassification (fr) | |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba | |
| split: test | |
| type: mteb/mtop_intent | |
| metrics: | |
| - type: accuracy | |
| value: 80.2317569683683 | |
| - type: f1 | |
| value: 56.18060418621901 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: fra | |
| name: MTEB MasakhaNEWSClassification (fra) | |
| revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 | |
| split: test | |
| type: masakhane/masakhanews | |
| metrics: | |
| - type: accuracy | |
| value: 85.18957345971565 | |
| - type: f1 | |
| value: 80.829981537394 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: fra | |
| name: MTEB MasakhaNEWSClusteringP2P (fra) | |
| revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 | |
| split: test | |
| type: masakhane/masakhanews | |
| metrics: | |
| - type: v_measure | |
| value: 71.04138999801822 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: fra | |
| name: MTEB MasakhaNEWSClusteringS2S (fra) | |
| revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 | |
| split: test | |
| type: masakhane/masakhanews | |
| metrics: | |
| - type: v_measure | |
| value: 71.7056263158008 | |
| task: | |
| type: Clustering | |
| - dataset: | |
| config: fr | |
| name: MTEB MassiveIntentClassification (fr) | |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 | |
| split: test | |
| type: mteb/amazon_massive_intent | |
| metrics: | |
| - type: accuracy | |
| value: 76.65097511768661 | |
| - type: f1 | |
| value: 73.82441070598712 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: fr | |
| name: MTEB MassiveScenarioClassification (fr) | |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 | |
| split: test | |
| type: mteb/amazon_massive_scenario | |
| metrics: | |
| - type: accuracy | |
| value: 79.09885675857431 | |
| - type: f1 | |
| value: 78.28407777434224 | |
| task: | |
| type: Classification | |
| - dataset: | |
| config: fr | |
| name: MTEB MintakaRetrieval (fr) | |
| revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e | |
| split: test | |
| type: jinaai/mintakaqa | |
| metrics: | |
| - type: map_at_1 | |
| value: 25.307000000000002 | |
| - type: map_at_10 | |
| value: 36.723 | |
| - type: map_at_100 | |
| value: 37.713 | |
| - type: map_at_1000 | |
| value: 37.769000000000005 | |
| - type: map_at_3 | |
| value: 33.77 | |
| - type: map_at_5 | |
| value: 35.463 | |
| - type: mrr_at_1 | |
| value: 25.307000000000002 | |
| - type: mrr_at_10 | |
| value: 36.723 | |
| - type: mrr_at_100 | |
| value: 37.713 | |
| - type: mrr_at_1000 | |
| value: 37.769000000000005 | |
| - type: mrr_at_3 | |
| value: 33.77 | |
| - type: mrr_at_5 | |
| value: 35.463 | |
| - type: ndcg_at_1 | |
| value: 25.307000000000002 | |
| - type: ndcg_at_10 | |
| value: 42.559999999999995 | |
| - type: ndcg_at_100 | |
| value: 47.457 | |
| - type: ndcg_at_1000 | |
| value: 49.162 | |
| - type: ndcg_at_3 | |
| value: 36.461 | |
| - type: ndcg_at_5 | |
| value: 39.504 | |
| - type: precision_at_1 | |
| value: 25.307000000000002 | |
| - type: precision_at_10 | |
| value: 6.106 | |
| - type: precision_at_100 | |
| value: 0.8420000000000001 | |
| - type: precision_at_1000 | |
| value: 0.098 | |
| - type: precision_at_3 | |
| value: 14.741999999999999 | |
| - type: precision_at_5 | |
| value: 10.319 | |
| - type: recall_at_1 | |
| value: 25.307000000000002 | |
| - type: recall_at_10 | |
| value: 61.056999999999995 | |
| - type: recall_at_100 | |
| value: 84.152 | |
| - type: recall_at_1000 | |
| value: 98.03399999999999 | |
| - type: recall_at_3 | |
| value: 44.226 | |
| - type: recall_at_5 | |
| value: 51.597 | |
| task: | |
| type: 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: 70.8 | |
| - type: cos_sim_ap | |
| value: 73.7671529695957 | |
| - type: cos_sim_f1 | |
| value: 68.80964339527875 | |
| - type: cos_sim_precision | |
| value: 62.95955882352941 | |
| - type: cos_sim_recall | |
| value: 75.85825027685493 | |
| - type: dot_accuracy | |
| value: 70.8 | |
| - type: dot_ap | |
| value: 73.78345265366947 | |
| - type: dot_f1 | |
| value: 68.80964339527875 | |
| - type: dot_precision | |
| value: 62.95955882352941 | |
| - type: dot_recall | |
| value: 75.85825027685493 | |
| - type: euclidean_accuracy | |
| value: 70.8 | |
| - type: euclidean_ap | |
| value: 73.7671529695957 | |
| - type: euclidean_f1 | |
| value: 68.80964339527875 | |
| - type: euclidean_precision | |
| value: 62.95955882352941 | |
| - type: euclidean_recall | |
| value: 75.85825027685493 | |
| - type: manhattan_accuracy | |
| value: 70.75 | |
| - type: manhattan_ap | |
| value: 73.78996383615953 | |
| - type: manhattan_f1 | |
| value: 68.79432624113475 | |
| - type: manhattan_precision | |
| value: 63.39869281045751 | |
| - type: manhattan_recall | |
| value: 75.1937984496124 | |
| - type: max_accuracy | |
| value: 70.8 | |
| - type: max_ap | |
| value: 73.78996383615953 | |
| - type: max_f1 | |
| value: 68.80964339527875 | |
| task: | |
| type: PairClassification | |
| - dataset: | |
| config: default | |
| name: MTEB SICKFr | |
| revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a | |
| split: test | |
| type: Lajavaness/SICK-fr | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 84.03253762760392 | |
| - type: cos_sim_spearman | |
| value: 79.68280105762004 | |
| - type: euclidean_pearson | |
| value: 80.98265050044444 | |
| - type: euclidean_spearman | |
| value: 79.68233242682867 | |
| - type: manhattan_pearson | |
| value: 80.9678911810704 | |
| - type: manhattan_spearman | |
| value: 79.70264097683109 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: fr | |
| name: MTEB STS22 (fr) | |
| revision: eea2b4fe26a775864c896887d910b76a8098ad3f | |
| split: test | |
| type: mteb/sts22-crosslingual-sts | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 80.56896987572884 | |
| - type: cos_sim_spearman | |
| value: 81.84352499523287 | |
| - type: euclidean_pearson | |
| value: 80.40831759421305 | |
| - type: euclidean_spearman | |
| value: 81.84352499523287 | |
| - type: manhattan_pearson | |
| value: 80.74333857561238 | |
| - type: manhattan_spearman | |
| value: 82.41503246733892 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: fr | |
| name: MTEB STSBenchmarkMultilingualSTS (fr) | |
| revision: 93d57ef91790589e3ce9c365164337a8a78b7632 | |
| split: test | |
| type: stsb_multi_mt | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 82.71826762276979 | |
| - type: cos_sim_spearman | |
| value: 82.25433354916042 | |
| - type: euclidean_pearson | |
| value: 81.87115571724316 | |
| - type: euclidean_spearman | |
| value: 82.25322342890107 | |
| - type: manhattan_pearson | |
| value: 82.11174867527224 | |
| - type: manhattan_spearman | |
| value: 82.55905365203084 | |
| task: | |
| type: STS | |
| - dataset: | |
| config: default | |
| name: MTEB SummEvalFr | |
| revision: b385812de6a9577b6f4d0f88c6a6e35395a94054 | |
| split: test | |
| type: lyon-nlp/summarization-summeval-fr-p2p | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 30.659441623392887 | |
| - type: cos_sim_spearman | |
| value: 30.501134097353315 | |
| - type: dot_pearson | |
| value: 30.659444768851056 | |
| - type: dot_spearman | |
| value: 30.501134097353315 | |
| task: | |
| type: Summarization | |
| - dataset: | |
| config: default | |
| name: MTEB SyntecReranking | |
| revision: b205c5084a0934ce8af14338bf03feb19499c84d | |
| split: test | |
| type: lyon-nlp/mteb-fr-reranking-syntec-s2p | |
| metrics: | |
| - type: map | |
| value: 94.03333333333333 | |
| - type: mrr | |
| value: 94.03333333333333 | |
| 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: 79.0 | |
| - type: map_at_10 | |
| value: 87.61 | |
| - type: map_at_100 | |
| value: 87.655 | |
| - type: map_at_1000 | |
| value: 87.655 | |
| - type: map_at_3 | |
| value: 87.167 | |
| - type: map_at_5 | |
| value: 87.36699999999999 | |
| - type: mrr_at_1 | |
| value: 79.0 | |
| - type: mrr_at_10 | |
| value: 87.61 | |
| - type: mrr_at_100 | |
| value: 87.655 | |
| - type: mrr_at_1000 | |
| value: 87.655 | |
| - type: mrr_at_3 | |
| value: 87.167 | |
| - type: mrr_at_5 | |
| value: 87.36699999999999 | |
| - type: ndcg_at_1 | |
| value: 79.0 | |
| - type: ndcg_at_10 | |
| value: 90.473 | |
| - type: ndcg_at_100 | |
| value: 90.694 | |
| - type: ndcg_at_1000 | |
| value: 90.694 | |
| - type: ndcg_at_3 | |
| value: 89.464 | |
| - type: ndcg_at_5 | |
| value: 89.851 | |
| - type: precision_at_1 | |
| value: 79.0 | |
| - type: precision_at_10 | |
| value: 9.9 | |
| - type: precision_at_100 | |
| value: 1.0 | |
| - type: precision_at_1000 | |
| value: 0.1 | |
| - type: precision_at_3 | |
| value: 32.0 | |
| - type: precision_at_5 | |
| value: 19.400000000000002 | |
| - type: recall_at_1 | |
| value: 79.0 | |
| - type: recall_at_10 | |
| value: 99.0 | |
| - type: recall_at_100 | |
| value: 100.0 | |
| - type: recall_at_1000 | |
| value: 100.0 | |
| - type: recall_at_3 | |
| value: 96.0 | |
| - type: recall_at_5 | |
| value: 97.0 | |
| task: | |
| type: Retrieval | |
| - dataset: | |
| config: fr | |
| name: MTEB XPQARetrieval (fr) | |
| revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f | |
| split: test | |
| type: jinaai/xpqa | |
| metrics: | |
| - type: map_at_1 | |
| value: 39.395 | |
| - type: map_at_10 | |
| value: 59.123999999999995 | |
| - type: map_at_100 | |
| value: 60.704 | |
| - type: map_at_1000 | |
| value: 60.760000000000005 | |
| - type: map_at_3 | |
| value: 53.187 | |
| - type: map_at_5 | |
| value: 56.863 | |
| - type: mrr_at_1 | |
| value: 62.083 | |
| - type: mrr_at_10 | |
| value: 68.87299999999999 | |
| - type: mrr_at_100 | |
| value: 69.46900000000001 | |
| - type: mrr_at_1000 | |
| value: 69.48299999999999 | |
| - type: mrr_at_3 | |
| value: 66.8 | |
| - type: mrr_at_5 | |
| value: 67.928 | |
| - type: ndcg_at_1 | |
| value: 62.083 | |
| - type: ndcg_at_10 | |
| value: 65.583 | |
| - type: ndcg_at_100 | |
| value: 70.918 | |
| - type: ndcg_at_1000 | |
| value: 71.72800000000001 | |
| - type: ndcg_at_3 | |
| value: 60.428000000000004 | |
| - type: ndcg_at_5 | |
| value: 61.853 | |
| - type: precision_at_1 | |
| value: 62.083 | |
| - type: precision_at_10 | |
| value: 15.033 | |
| - type: precision_at_100 | |
| value: 1.9529999999999998 | |
| - type: precision_at_1000 | |
| value: 0.207 | |
| - type: precision_at_3 | |
| value: 36.315 | |
| - type: precision_at_5 | |
| value: 25.955000000000002 | |
| - type: recall_at_1 | |
| value: 39.395 | |
| - type: recall_at_10 | |
| value: 74.332 | |
| - type: recall_at_100 | |
| value: 94.729 | |
| - type: recall_at_1000 | |
| value: 99.75500000000001 | |
| - type: recall_at_3 | |
| value: 57.679 | |
| - type: recall_at_5 | |
| value: 65.036 | |
| task: | |
| type: Retrieval | |
| --- | |
| ## gte-Qwen2-1.5B-instruct | |
| **gte-Qwen2-1.5B-instruct** is the latest model in the gte (General Text Embedding) model family. The model is built on [Qwen2-1.5B](https://huggingface.co/Qwen/Qwen2-1.5B) LLM model and use the same training data and strategies as the [gte-Qwen2-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct) model. | |
| 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: 1.5B | |
| - Embedding Dimension: 1536 | |
| - 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-Qwen2-1.5B-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-Qwen2-1.5B-instruct', trust_remote_code=True) | |
| model = AutoModel.from_pretrained('Alibaba-NLP/gte-Qwen2-1.5B-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()) | |
| ``` | |
| ## 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-Qwen2-1.5B-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-instruct**](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 | | |
| ## 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} | |
| } | |
| ``` | |