| 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-Qwen2-7B-instruct - GGUF | |
| - Model creator: https://huggingface.co/Alibaba-NLP/ | |
| - Original model: https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct/ | |
| | Name | Quant method | Size | | |
| | ---- | ---- | ---- | | |
| | [gte-Qwen2-7B-instruct.Q2_K.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q2_K.gguf) | Q2_K | 2.81GB | | |
| | [gte-Qwen2-7B-instruct.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.IQ3_XS.gguf) | IQ3_XS | 3.11GB | | |
| | [gte-Qwen2-7B-instruct.IQ3_S.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.IQ3_S.gguf) | IQ3_S | 3.26GB | | |
| | [gte-Qwen2-7B-instruct.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q3_K_S.gguf) | Q3_K_S | 3.25GB | | |
| | [gte-Qwen2-7B-instruct.IQ3_M.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.IQ3_M.gguf) | IQ3_M | 3.33GB | | |
| | [gte-Qwen2-7B-instruct.Q3_K.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q3_K.gguf) | Q3_K | 3.55GB | | |
| | [gte-Qwen2-7B-instruct.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q3_K_M.gguf) | Q3_K_M | 3.55GB | | |
| | [gte-Qwen2-7B-instruct.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q3_K_L.gguf) | Q3_K_L | 3.81GB | | |
| | [gte-Qwen2-7B-instruct.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.IQ4_XS.gguf) | IQ4_XS | 3.96GB | | |
| | [gte-Qwen2-7B-instruct.Q4_0.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q4_0.gguf) | Q4_0 | 4.13GB | | |
| | [gte-Qwen2-7B-instruct.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.IQ4_NL.gguf) | IQ4_NL | 4.15GB | | |
| | [gte-Qwen2-7B-instruct.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q4_K_S.gguf) | Q4_K_S | 4.15GB | | |
| | [gte-Qwen2-7B-instruct.Q4_K.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q4_K.gguf) | Q4_K | 4.36GB | | |
| | [gte-Qwen2-7B-instruct.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q4_K_M.gguf) | Q4_K_M | 4.36GB | | |
| | [gte-Qwen2-7B-instruct.Q4_1.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q4_1.gguf) | Q4_1 | 4.54GB | | |
| | [gte-Qwen2-7B-instruct.Q5_0.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q5_0.gguf) | Q5_0 | 4.95GB | | |
| | [gte-Qwen2-7B-instruct.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q5_K_S.gguf) | Q5_K_S | 4.95GB | | |
| | [gte-Qwen2-7B-instruct.Q5_K.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q5_K.gguf) | Q5_K | 5.07GB | | |
| | [gte-Qwen2-7B-instruct.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q5_K_M.gguf) | Q5_K_M | 5.07GB | | |
| | [gte-Qwen2-7B-instruct.Q5_1.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q5_1.gguf) | Q5_1 | 5.36GB | | |
| | [gte-Qwen2-7B-instruct.Q6_K.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q6_K.gguf) | Q6_K | 5.82GB | | |
| | [gte-Qwen2-7B-instruct.Q8_0.gguf](https://huggingface.co/RichardErkhov/Alibaba-NLP_-_gte-Qwen2-7B-instruct-gguf/blob/main/gte-Qwen2-7B-instruct.Q8_0.gguf) | Q8_0 | 7.54GB | | |
| Original model description: | |
| --- | |
| tags: | |
| - mteb | |
| - sentence-transformers | |
| - transformers | |
| - Qwen2 | |
| - sentence-similarity | |
| license: apache-2.0 | |
| model-index: | |
| - name: gte-qwen2-7B-instruct | |
| results: | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_counterfactual | |
| name: MTEB AmazonCounterfactualClassification (en) | |
| config: en | |
| split: test | |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 | |
| metrics: | |
| - type: accuracy | |
| value: 91.31343283582089 | |
| - type: ap | |
| value: 67.64251402604096 | |
| - type: f1 | |
| value: 87.53372530755692 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_polarity | |
| name: MTEB AmazonPolarityClassification | |
| config: default | |
| split: test | |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 | |
| metrics: | |
| - type: accuracy | |
| value: 97.497825 | |
| - type: ap | |
| value: 96.30329547047529 | |
| - type: f1 | |
| value: 97.49769793778039 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_reviews_multi | |
| name: MTEB AmazonReviewsClassification (en) | |
| config: en | |
| split: test | |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d | |
| metrics: | |
| - type: accuracy | |
| value: 62.564 | |
| - type: f1 | |
| value: 60.975777935041066 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/arguana | |
| name: MTEB ArguAna | |
| config: default | |
| split: test | |
| revision: c22ab2a51041ffd869aaddef7af8d8215647e41a | |
| metrics: | |
| - type: map_at_1 | |
| value: 36.486000000000004 | |
| - type: map_at_10 | |
| value: 54.842 | |
| - type: map_at_100 | |
| value: 55.206999999999994 | |
| - type: map_at_1000 | |
| value: 55.206999999999994 | |
| - type: map_at_3 | |
| value: 49.893 | |
| - type: map_at_5 | |
| value: 53.105000000000004 | |
| - type: mrr_at_1 | |
| value: 37.34 | |
| - type: mrr_at_10 | |
| value: 55.143 | |
| - type: mrr_at_100 | |
| value: 55.509 | |
| - type: mrr_at_1000 | |
| value: 55.509 | |
| - type: mrr_at_3 | |
| value: 50.212999999999994 | |
| - type: mrr_at_5 | |
| value: 53.432 | |
| - type: ndcg_at_1 | |
| value: 36.486000000000004 | |
| - type: ndcg_at_10 | |
| value: 64.273 | |
| - type: ndcg_at_100 | |
| value: 65.66199999999999 | |
| - type: ndcg_at_1000 | |
| value: 65.66199999999999 | |
| - type: ndcg_at_3 | |
| value: 54.352999999999994 | |
| - type: ndcg_at_5 | |
| value: 60.131 | |
| - type: precision_at_1 | |
| value: 36.486000000000004 | |
| - type: precision_at_10 | |
| value: 9.395000000000001 | |
| - type: precision_at_100 | |
| value: 0.996 | |
| - type: precision_at_1000 | |
| value: 0.1 | |
| - type: precision_at_3 | |
| value: 22.428 | |
| - type: precision_at_5 | |
| value: 16.259 | |
| - type: recall_at_1 | |
| value: 36.486000000000004 | |
| - type: recall_at_10 | |
| value: 93.95400000000001 | |
| - type: recall_at_100 | |
| value: 99.644 | |
| - type: recall_at_1000 | |
| value: 99.644 | |
| - type: recall_at_3 | |
| value: 67.283 | |
| - type: recall_at_5 | |
| value: 81.294 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/arxiv-clustering-p2p | |
| name: MTEB ArxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d | |
| metrics: | |
| - type: v_measure | |
| value: 56.461169803700564 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/arxiv-clustering-s2s | |
| name: MTEB ArxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 | |
| metrics: | |
| - type: v_measure | |
| value: 51.73600434466286 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/askubuntudupquestions-reranking | |
| name: MTEB AskUbuntuDupQuestions | |
| config: default | |
| split: test | |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 | |
| metrics: | |
| - type: map | |
| value: 67.57827065898053 | |
| - type: mrr | |
| value: 79.08136569493911 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/biosses-sts | |
| name: MTEB BIOSSES | |
| config: default | |
| split: test | |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 83.53324575999243 | |
| - type: cos_sim_spearman | |
| value: 81.37173362822374 | |
| - type: euclidean_pearson | |
| value: 82.19243335103444 | |
| - type: euclidean_spearman | |
| value: 81.33679307304334 | |
| - type: manhattan_pearson | |
| value: 82.38752665975699 | |
| - type: manhattan_spearman | |
| value: 81.31510583189689 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/banking77 | |
| name: MTEB Banking77Classification | |
| config: default | |
| split: test | |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 | |
| metrics: | |
| - type: accuracy | |
| value: 87.56818181818181 | |
| - type: f1 | |
| value: 87.25826722019875 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/biorxiv-clustering-p2p | |
| name: MTEB BiorxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 | |
| metrics: | |
| - type: v_measure | |
| value: 50.09239610327673 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/biorxiv-clustering-s2s | |
| name: MTEB BiorxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 | |
| metrics: | |
| - type: v_measure | |
| value: 46.64733054606282 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackAndroidRetrieval | |
| config: default | |
| split: test | |
| revision: f46a197baaae43b4f621051089b82a364682dfeb | |
| metrics: | |
| - type: map_at_1 | |
| value: 33.997 | |
| - type: map_at_10 | |
| value: 48.176 | |
| - type: map_at_100 | |
| value: 49.82 | |
| - type: map_at_1000 | |
| value: 49.924 | |
| - type: map_at_3 | |
| value: 43.626 | |
| - type: map_at_5 | |
| value: 46.275 | |
| - type: mrr_at_1 | |
| value: 42.059999999999995 | |
| - type: mrr_at_10 | |
| value: 53.726 | |
| - type: mrr_at_100 | |
| value: 54.398 | |
| - type: mrr_at_1000 | |
| value: 54.416 | |
| - type: mrr_at_3 | |
| value: 50.714999999999996 | |
| - type: mrr_at_5 | |
| value: 52.639 | |
| - type: ndcg_at_1 | |
| value: 42.059999999999995 | |
| - type: ndcg_at_10 | |
| value: 55.574999999999996 | |
| - type: ndcg_at_100 | |
| value: 60.744 | |
| - type: ndcg_at_1000 | |
| value: 61.85699999999999 | |
| - type: ndcg_at_3 | |
| value: 49.363 | |
| - type: ndcg_at_5 | |
| value: 52.44 | |
| - type: precision_at_1 | |
| value: 42.059999999999995 | |
| - type: precision_at_10 | |
| value: 11.101999999999999 | |
| - type: precision_at_100 | |
| value: 1.73 | |
| - type: precision_at_1000 | |
| value: 0.218 | |
| - type: precision_at_3 | |
| value: 24.464 | |
| - type: precision_at_5 | |
| value: 18.026 | |
| - type: recall_at_1 | |
| value: 33.997 | |
| - type: recall_at_10 | |
| value: 70.35900000000001 | |
| - type: recall_at_100 | |
| value: 91.642 | |
| - type: recall_at_1000 | |
| value: 97.977 | |
| - type: recall_at_3 | |
| value: 52.76 | |
| - type: recall_at_5 | |
| value: 61.148 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackEnglishRetrieval | |
| config: default | |
| split: test | |
| revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 | |
| metrics: | |
| - type: map_at_1 | |
| value: 35.884 | |
| - type: map_at_10 | |
| value: 48.14 | |
| - type: map_at_100 | |
| value: 49.5 | |
| - type: map_at_1000 | |
| value: 49.63 | |
| - type: map_at_3 | |
| value: 44.646 | |
| - type: map_at_5 | |
| value: 46.617999999999995 | |
| - type: mrr_at_1 | |
| value: 44.458999999999996 | |
| - type: mrr_at_10 | |
| value: 53.751000000000005 | |
| - type: mrr_at_100 | |
| value: 54.37800000000001 | |
| - type: mrr_at_1000 | |
| value: 54.415 | |
| - type: mrr_at_3 | |
| value: 51.815 | |
| - type: mrr_at_5 | |
| value: 52.882 | |
| - type: ndcg_at_1 | |
| value: 44.458999999999996 | |
| - type: ndcg_at_10 | |
| value: 54.157 | |
| - type: ndcg_at_100 | |
| value: 58.362 | |
| - type: ndcg_at_1000 | |
| value: 60.178 | |
| - type: ndcg_at_3 | |
| value: 49.661 | |
| - type: ndcg_at_5 | |
| value: 51.74999999999999 | |
| - type: precision_at_1 | |
| value: 44.458999999999996 | |
| - type: precision_at_10 | |
| value: 10.248 | |
| - type: precision_at_100 | |
| value: 1.5890000000000002 | |
| - type: precision_at_1000 | |
| value: 0.207 | |
| - type: precision_at_3 | |
| value: 23.928 | |
| - type: precision_at_5 | |
| value: 16.878999999999998 | |
| - type: recall_at_1 | |
| value: 35.884 | |
| - type: recall_at_10 | |
| value: 64.798 | |
| - type: recall_at_100 | |
| value: 82.345 | |
| - type: recall_at_1000 | |
| value: 93.267 | |
| - type: recall_at_3 | |
| value: 51.847 | |
| - type: recall_at_5 | |
| value: 57.601 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackGamingRetrieval | |
| config: default | |
| split: test | |
| revision: 4885aa143210c98657558c04aaf3dc47cfb54340 | |
| metrics: | |
| - type: map_at_1 | |
| value: 39.383 | |
| - type: map_at_10 | |
| value: 53.714 | |
| - type: map_at_100 | |
| value: 54.838 | |
| - type: map_at_1000 | |
| value: 54.87800000000001 | |
| - type: map_at_3 | |
| value: 50.114999999999995 | |
| - type: map_at_5 | |
| value: 52.153000000000006 | |
| - type: mrr_at_1 | |
| value: 45.016 | |
| - type: mrr_at_10 | |
| value: 56.732000000000006 | |
| - type: mrr_at_100 | |
| value: 57.411 | |
| - type: mrr_at_1000 | |
| value: 57.431 | |
| - type: mrr_at_3 | |
| value: 54.044000000000004 | |
| - type: mrr_at_5 | |
| value: 55.639 | |
| - type: ndcg_at_1 | |
| value: 45.016 | |
| - type: ndcg_at_10 | |
| value: 60.228 | |
| - type: ndcg_at_100 | |
| value: 64.277 | |
| - type: ndcg_at_1000 | |
| value: 65.07 | |
| - type: ndcg_at_3 | |
| value: 54.124 | |
| - type: ndcg_at_5 | |
| value: 57.147000000000006 | |
| - type: precision_at_1 | |
| value: 45.016 | |
| - type: precision_at_10 | |
| value: 9.937 | |
| - type: precision_at_100 | |
| value: 1.288 | |
| - type: precision_at_1000 | |
| value: 0.13899999999999998 | |
| - type: precision_at_3 | |
| value: 24.471999999999998 | |
| - type: precision_at_5 | |
| value: 16.991 | |
| - type: recall_at_1 | |
| value: 39.383 | |
| - type: recall_at_10 | |
| value: 76.175 | |
| - type: recall_at_100 | |
| value: 93.02 | |
| - type: recall_at_1000 | |
| value: 98.60900000000001 | |
| - type: recall_at_3 | |
| value: 60.265 | |
| - type: recall_at_5 | |
| value: 67.46600000000001 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackGisRetrieval | |
| config: default | |
| split: test | |
| revision: 5003b3064772da1887988e05400cf3806fe491f2 | |
| metrics: | |
| - type: map_at_1 | |
| value: 27.426000000000002 | |
| - type: map_at_10 | |
| value: 37.397000000000006 | |
| - type: map_at_100 | |
| value: 38.61 | |
| - type: map_at_1000 | |
| value: 38.678000000000004 | |
| - type: map_at_3 | |
| value: 34.150999999999996 | |
| - type: map_at_5 | |
| value: 36.137 | |
| - type: mrr_at_1 | |
| value: 29.944 | |
| - type: mrr_at_10 | |
| value: 39.654 | |
| - type: mrr_at_100 | |
| value: 40.638000000000005 | |
| - type: mrr_at_1000 | |
| value: 40.691 | |
| - type: mrr_at_3 | |
| value: 36.817 | |
| - type: mrr_at_5 | |
| value: 38.524 | |
| - type: ndcg_at_1 | |
| value: 29.944 | |
| - type: ndcg_at_10 | |
| value: 43.094 | |
| - type: ndcg_at_100 | |
| value: 48.789 | |
| - type: ndcg_at_1000 | |
| value: 50.339999999999996 | |
| - type: ndcg_at_3 | |
| value: 36.984 | |
| - type: ndcg_at_5 | |
| value: 40.248 | |
| - type: precision_at_1 | |
| value: 29.944 | |
| - type: precision_at_10 | |
| value: 6.78 | |
| - type: precision_at_100 | |
| value: 1.024 | |
| - type: precision_at_1000 | |
| value: 0.11800000000000001 | |
| - type: precision_at_3 | |
| value: 15.895000000000001 | |
| - type: precision_at_5 | |
| value: 11.39 | |
| - type: recall_at_1 | |
| value: 27.426000000000002 | |
| - type: recall_at_10 | |
| value: 58.464000000000006 | |
| - type: recall_at_100 | |
| value: 84.193 | |
| - type: recall_at_1000 | |
| value: 95.52000000000001 | |
| - type: recall_at_3 | |
| value: 42.172 | |
| - type: recall_at_5 | |
| value: 50.101 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackMathematicaRetrieval | |
| config: default | |
| split: test | |
| revision: 90fceea13679c63fe563ded68f3b6f06e50061de | |
| metrics: | |
| - type: map_at_1 | |
| value: 19.721 | |
| - type: map_at_10 | |
| value: 31.604 | |
| - type: map_at_100 | |
| value: 32.972 | |
| - type: map_at_1000 | |
| value: 33.077 | |
| - type: map_at_3 | |
| value: 27.218999999999998 | |
| - type: map_at_5 | |
| value: 29.53 | |
| - type: mrr_at_1 | |
| value: 25.0 | |
| - type: mrr_at_10 | |
| value: 35.843 | |
| - type: mrr_at_100 | |
| value: 36.785000000000004 | |
| - type: mrr_at_1000 | |
| value: 36.842000000000006 | |
| - type: mrr_at_3 | |
| value: 32.193 | |
| - type: mrr_at_5 | |
| value: 34.264 | |
| - type: ndcg_at_1 | |
| value: 25.0 | |
| - type: ndcg_at_10 | |
| value: 38.606 | |
| - type: ndcg_at_100 | |
| value: 44.272 | |
| - type: ndcg_at_1000 | |
| value: 46.527 | |
| - type: ndcg_at_3 | |
| value: 30.985000000000003 | |
| - type: ndcg_at_5 | |
| value: 34.43 | |
| - type: precision_at_1 | |
| value: 25.0 | |
| - type: precision_at_10 | |
| value: 7.811 | |
| - type: precision_at_100 | |
| value: 1.203 | |
| - type: precision_at_1000 | |
| value: 0.15 | |
| - type: precision_at_3 | |
| value: 15.423 | |
| - type: precision_at_5 | |
| value: 11.791 | |
| - type: recall_at_1 | |
| value: 19.721 | |
| - type: recall_at_10 | |
| value: 55.625 | |
| - type: recall_at_100 | |
| value: 79.34400000000001 | |
| - type: recall_at_1000 | |
| value: 95.208 | |
| - type: recall_at_3 | |
| value: 35.19 | |
| - type: recall_at_5 | |
| value: 43.626 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackPhysicsRetrieval | |
| config: default | |
| split: test | |
| revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 | |
| metrics: | |
| - type: map_at_1 | |
| value: 33.784 | |
| - type: map_at_10 | |
| value: 47.522 | |
| - type: map_at_100 | |
| value: 48.949999999999996 | |
| - type: map_at_1000 | |
| value: 49.038 | |
| - type: map_at_3 | |
| value: 43.284 | |
| - type: map_at_5 | |
| value: 45.629 | |
| - type: mrr_at_1 | |
| value: 41.482 | |
| - type: mrr_at_10 | |
| value: 52.830999999999996 | |
| - type: mrr_at_100 | |
| value: 53.559999999999995 | |
| - type: mrr_at_1000 | |
| value: 53.588 | |
| - type: mrr_at_3 | |
| value: 50.016000000000005 | |
| - type: mrr_at_5 | |
| value: 51.614000000000004 | |
| - type: ndcg_at_1 | |
| value: 41.482 | |
| - type: ndcg_at_10 | |
| value: 54.569 | |
| - type: ndcg_at_100 | |
| value: 59.675999999999995 | |
| - type: ndcg_at_1000 | |
| value: 60.989000000000004 | |
| - type: ndcg_at_3 | |
| value: 48.187000000000005 | |
| - type: ndcg_at_5 | |
| value: 51.183 | |
| - type: precision_at_1 | |
| value: 41.482 | |
| - type: precision_at_10 | |
| value: 10.221 | |
| - type: precision_at_100 | |
| value: 1.486 | |
| - type: precision_at_1000 | |
| value: 0.17500000000000002 | |
| - type: precision_at_3 | |
| value: 23.548 | |
| - type: precision_at_5 | |
| value: 16.805 | |
| - type: recall_at_1 | |
| value: 33.784 | |
| - type: recall_at_10 | |
| value: 69.798 | |
| - type: recall_at_100 | |
| value: 90.098 | |
| - type: recall_at_1000 | |
| value: 98.176 | |
| - type: recall_at_3 | |
| value: 52.127 | |
| - type: recall_at_5 | |
| value: 59.861 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackProgrammersRetrieval | |
| config: default | |
| split: test | |
| revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 | |
| metrics: | |
| - type: map_at_1 | |
| value: 28.038999999999998 | |
| - type: map_at_10 | |
| value: 41.904 | |
| - type: map_at_100 | |
| value: 43.36 | |
| - type: map_at_1000 | |
| value: 43.453 | |
| - type: map_at_3 | |
| value: 37.785999999999994 | |
| - type: map_at_5 | |
| value: 40.105000000000004 | |
| - type: mrr_at_1 | |
| value: 35.046 | |
| - type: mrr_at_10 | |
| value: 46.926 | |
| - type: mrr_at_100 | |
| value: 47.815000000000005 | |
| - type: mrr_at_1000 | |
| value: 47.849000000000004 | |
| - type: mrr_at_3 | |
| value: 44.273 | |
| - type: mrr_at_5 | |
| value: 45.774 | |
| - type: ndcg_at_1 | |
| value: 35.046 | |
| - type: ndcg_at_10 | |
| value: 48.937000000000005 | |
| - type: ndcg_at_100 | |
| value: 54.544000000000004 | |
| - type: ndcg_at_1000 | |
| value: 56.069 | |
| - type: ndcg_at_3 | |
| value: 42.858000000000004 | |
| - type: ndcg_at_5 | |
| value: 45.644 | |
| - type: precision_at_1 | |
| value: 35.046 | |
| - type: precision_at_10 | |
| value: 9.452 | |
| - type: precision_at_100 | |
| value: 1.429 | |
| - type: precision_at_1000 | |
| value: 0.173 | |
| - type: precision_at_3 | |
| value: 21.346999999999998 | |
| - type: precision_at_5 | |
| value: 15.342 | |
| - type: recall_at_1 | |
| value: 28.038999999999998 | |
| - type: recall_at_10 | |
| value: 64.59700000000001 | |
| - type: recall_at_100 | |
| value: 87.735 | |
| - type: recall_at_1000 | |
| value: 97.41300000000001 | |
| - type: recall_at_3 | |
| value: 47.368 | |
| - type: recall_at_5 | |
| value: 54.93900000000001 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackRetrieval | |
| config: default | |
| split: test | |
| revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 | |
| metrics: | |
| - type: map_at_1 | |
| value: 28.17291666666667 | |
| - type: map_at_10 | |
| value: 40.025749999999995 | |
| - type: map_at_100 | |
| value: 41.39208333333333 | |
| - type: map_at_1000 | |
| value: 41.499249999999996 | |
| - type: map_at_3 | |
| value: 36.347 | |
| - type: map_at_5 | |
| value: 38.41391666666667 | |
| - type: mrr_at_1 | |
| value: 33.65925 | |
| - type: mrr_at_10 | |
| value: 44.085499999999996 | |
| - type: mrr_at_100 | |
| value: 44.94116666666667 | |
| - type: mrr_at_1000 | |
| value: 44.9855 | |
| - type: mrr_at_3 | |
| value: 41.2815 | |
| - type: mrr_at_5 | |
| value: 42.91491666666666 | |
| - type: ndcg_at_1 | |
| value: 33.65925 | |
| - type: ndcg_at_10 | |
| value: 46.430833333333325 | |
| - type: ndcg_at_100 | |
| value: 51.761 | |
| - type: ndcg_at_1000 | |
| value: 53.50899999999999 | |
| - type: ndcg_at_3 | |
| value: 40.45133333333333 | |
| - type: ndcg_at_5 | |
| value: 43.31483333333334 | |
| - type: precision_at_1 | |
| value: 33.65925 | |
| - type: precision_at_10 | |
| value: 8.4995 | |
| - type: precision_at_100 | |
| value: 1.3210000000000004 | |
| - type: precision_at_1000 | |
| value: 0.16591666666666666 | |
| - type: precision_at_3 | |
| value: 19.165083333333335 | |
| - type: precision_at_5 | |
| value: 13.81816666666667 | |
| - type: recall_at_1 | |
| value: 28.17291666666667 | |
| - type: recall_at_10 | |
| value: 61.12624999999999 | |
| - type: recall_at_100 | |
| value: 83.97266666666667 | |
| - type: recall_at_1000 | |
| value: 95.66550000000001 | |
| - type: recall_at_3 | |
| value: 44.661249999999995 | |
| - type: recall_at_5 | |
| value: 51.983333333333334 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackStatsRetrieval | |
| config: default | |
| split: test | |
| revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a | |
| metrics: | |
| - type: map_at_1 | |
| value: 24.681 | |
| - type: map_at_10 | |
| value: 34.892 | |
| - type: map_at_100 | |
| value: 35.996 | |
| - type: map_at_1000 | |
| value: 36.083 | |
| - type: map_at_3 | |
| value: 31.491999999999997 | |
| - type: map_at_5 | |
| value: 33.632 | |
| - type: mrr_at_1 | |
| value: 28.528 | |
| - type: mrr_at_10 | |
| value: 37.694 | |
| - type: mrr_at_100 | |
| value: 38.613 | |
| - type: mrr_at_1000 | |
| value: 38.668 | |
| - type: mrr_at_3 | |
| value: 34.714 | |
| - type: mrr_at_5 | |
| value: 36.616 | |
| - type: ndcg_at_1 | |
| value: 28.528 | |
| - type: ndcg_at_10 | |
| value: 40.703 | |
| - type: ndcg_at_100 | |
| value: 45.993 | |
| - type: ndcg_at_1000 | |
| value: 47.847 | |
| - type: ndcg_at_3 | |
| value: 34.622 | |
| - type: ndcg_at_5 | |
| value: 38.035999999999994 | |
| - type: precision_at_1 | |
| value: 28.528 | |
| - type: precision_at_10 | |
| value: 6.902 | |
| - type: precision_at_100 | |
| value: 1.0370000000000001 | |
| - type: precision_at_1000 | |
| value: 0.126 | |
| - type: precision_at_3 | |
| value: 15.798000000000002 | |
| - type: precision_at_5 | |
| value: 11.655999999999999 | |
| - type: recall_at_1 | |
| value: 24.681 | |
| - type: recall_at_10 | |
| value: 55.81 | |
| - type: recall_at_100 | |
| value: 79.785 | |
| - type: recall_at_1000 | |
| value: 92.959 | |
| - type: recall_at_3 | |
| value: 39.074 | |
| - type: recall_at_5 | |
| value: 47.568 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackTexRetrieval | |
| config: default | |
| split: test | |
| revision: 46989137a86843e03a6195de44b09deda022eec7 | |
| metrics: | |
| - type: map_at_1 | |
| value: 18.627 | |
| - type: map_at_10 | |
| value: 27.872000000000003 | |
| - type: map_at_100 | |
| value: 29.237999999999996 | |
| - type: map_at_1000 | |
| value: 29.363 | |
| - type: map_at_3 | |
| value: 24.751 | |
| - type: map_at_5 | |
| value: 26.521 | |
| - type: mrr_at_1 | |
| value: 23.021 | |
| - type: mrr_at_10 | |
| value: 31.924000000000003 | |
| - type: mrr_at_100 | |
| value: 32.922000000000004 | |
| - type: mrr_at_1000 | |
| value: 32.988 | |
| - type: mrr_at_3 | |
| value: 29.192 | |
| - type: mrr_at_5 | |
| value: 30.798 | |
| - type: ndcg_at_1 | |
| value: 23.021 | |
| - type: ndcg_at_10 | |
| value: 33.535 | |
| - type: ndcg_at_100 | |
| value: 39.732 | |
| - type: ndcg_at_1000 | |
| value: 42.201 | |
| - type: ndcg_at_3 | |
| value: 28.153 | |
| - type: ndcg_at_5 | |
| value: 30.746000000000002 | |
| - type: precision_at_1 | |
| value: 23.021 | |
| - type: precision_at_10 | |
| value: 6.459 | |
| - type: precision_at_100 | |
| value: 1.1320000000000001 | |
| - type: precision_at_1000 | |
| value: 0.153 | |
| - type: precision_at_3 | |
| value: 13.719000000000001 | |
| - type: precision_at_5 | |
| value: 10.193000000000001 | |
| - type: recall_at_1 | |
| value: 18.627 | |
| - type: recall_at_10 | |
| value: 46.463 | |
| - type: recall_at_100 | |
| value: 74.226 | |
| - type: recall_at_1000 | |
| value: 91.28500000000001 | |
| - type: recall_at_3 | |
| value: 31.357000000000003 | |
| - type: recall_at_5 | |
| value: 38.067 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackUnixRetrieval | |
| config: default | |
| split: test | |
| revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 | |
| metrics: | |
| - type: map_at_1 | |
| value: 31.457 | |
| - type: map_at_10 | |
| value: 42.888 | |
| - type: map_at_100 | |
| value: 44.24 | |
| - type: map_at_1000 | |
| value: 44.327 | |
| - type: map_at_3 | |
| value: 39.588 | |
| - type: map_at_5 | |
| value: 41.423 | |
| - type: mrr_at_1 | |
| value: 37.126999999999995 | |
| - type: mrr_at_10 | |
| value: 47.083000000000006 | |
| - type: mrr_at_100 | |
| value: 47.997 | |
| - type: mrr_at_1000 | |
| value: 48.044 | |
| - type: mrr_at_3 | |
| value: 44.574000000000005 | |
| - type: mrr_at_5 | |
| value: 46.202 | |
| - type: ndcg_at_1 | |
| value: 37.126999999999995 | |
| - type: ndcg_at_10 | |
| value: 48.833 | |
| - type: ndcg_at_100 | |
| value: 54.327000000000005 | |
| - type: ndcg_at_1000 | |
| value: 56.011 | |
| - type: ndcg_at_3 | |
| value: 43.541999999999994 | |
| - type: ndcg_at_5 | |
| value: 46.127 | |
| - type: precision_at_1 | |
| value: 37.126999999999995 | |
| - type: precision_at_10 | |
| value: 8.376999999999999 | |
| - type: precision_at_100 | |
| value: 1.2309999999999999 | |
| - type: precision_at_1000 | |
| value: 0.146 | |
| - type: precision_at_3 | |
| value: 20.211000000000002 | |
| - type: precision_at_5 | |
| value: 14.16 | |
| - type: recall_at_1 | |
| value: 31.457 | |
| - type: recall_at_10 | |
| value: 62.369 | |
| - type: recall_at_100 | |
| value: 85.444 | |
| - type: recall_at_1000 | |
| value: 96.65599999999999 | |
| - type: recall_at_3 | |
| value: 47.961 | |
| - type: recall_at_5 | |
| value: 54.676 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackWebmastersRetrieval | |
| config: default | |
| split: test | |
| revision: 160c094312a0e1facb97e55eeddb698c0abe3571 | |
| metrics: | |
| - type: map_at_1 | |
| value: 27.139999999999997 | |
| - type: map_at_10 | |
| value: 38.801 | |
| - type: map_at_100 | |
| value: 40.549 | |
| - type: map_at_1000 | |
| value: 40.802 | |
| - type: map_at_3 | |
| value: 35.05 | |
| - type: map_at_5 | |
| value: 36.884 | |
| - type: mrr_at_1 | |
| value: 33.004 | |
| - type: mrr_at_10 | |
| value: 43.864 | |
| - type: mrr_at_100 | |
| value: 44.667 | |
| - type: mrr_at_1000 | |
| value: 44.717 | |
| - type: mrr_at_3 | |
| value: 40.777 | |
| - type: mrr_at_5 | |
| value: 42.319 | |
| - type: ndcg_at_1 | |
| value: 33.004 | |
| - type: ndcg_at_10 | |
| value: 46.022 | |
| - type: ndcg_at_100 | |
| value: 51.542 | |
| - type: ndcg_at_1000 | |
| value: 53.742000000000004 | |
| - type: ndcg_at_3 | |
| value: 39.795 | |
| - type: ndcg_at_5 | |
| value: 42.272 | |
| - type: precision_at_1 | |
| value: 33.004 | |
| - type: precision_at_10 | |
| value: 9.012 | |
| - type: precision_at_100 | |
| value: 1.7770000000000001 | |
| - type: precision_at_1000 | |
| value: 0.26 | |
| - type: precision_at_3 | |
| value: 19.038 | |
| - type: precision_at_5 | |
| value: 13.675999999999998 | |
| - type: recall_at_1 | |
| value: 27.139999999999997 | |
| - type: recall_at_10 | |
| value: 60.961 | |
| - type: recall_at_100 | |
| value: 84.451 | |
| - type: recall_at_1000 | |
| value: 98.113 | |
| - type: recall_at_3 | |
| value: 43.001 | |
| - type: recall_at_5 | |
| value: 49.896 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackWordpressRetrieval | |
| config: default | |
| split: test | |
| revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 | |
| metrics: | |
| - type: map_at_1 | |
| value: 17.936 | |
| - type: map_at_10 | |
| value: 27.399 | |
| - type: map_at_100 | |
| value: 28.632 | |
| - type: map_at_1000 | |
| value: 28.738000000000003 | |
| - type: map_at_3 | |
| value: 24.456 | |
| - type: map_at_5 | |
| value: 26.06 | |
| - type: mrr_at_1 | |
| value: 19.224 | |
| - type: mrr_at_10 | |
| value: 28.998 | |
| - type: mrr_at_100 | |
| value: 30.11 | |
| - type: mrr_at_1000 | |
| value: 30.177 | |
| - type: mrr_at_3 | |
| value: 26.247999999999998 | |
| - type: mrr_at_5 | |
| value: 27.708 | |
| - type: ndcg_at_1 | |
| value: 19.224 | |
| - type: ndcg_at_10 | |
| value: 32.911 | |
| - type: ndcg_at_100 | |
| value: 38.873999999999995 | |
| - type: ndcg_at_1000 | |
| value: 41.277 | |
| - type: ndcg_at_3 | |
| value: 27.142 | |
| - type: ndcg_at_5 | |
| value: 29.755 | |
| - type: precision_at_1 | |
| value: 19.224 | |
| - type: precision_at_10 | |
| value: 5.6930000000000005 | |
| - type: precision_at_100 | |
| value: 0.9259999999999999 | |
| - type: precision_at_1000 | |
| value: 0.126 | |
| - type: precision_at_3 | |
| value: 12.138 | |
| - type: precision_at_5 | |
| value: 8.909 | |
| - type: recall_at_1 | |
| value: 17.936 | |
| - type: recall_at_10 | |
| value: 48.096 | |
| - type: recall_at_100 | |
| value: 75.389 | |
| - type: recall_at_1000 | |
| value: 92.803 | |
| - type: recall_at_3 | |
| value: 32.812999999999995 | |
| - type: recall_at_5 | |
| value: 38.851 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/climate-fever | |
| name: MTEB ClimateFEVER | |
| config: default | |
| split: test | |
| revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 | |
| metrics: | |
| - type: map_at_1 | |
| value: 22.076999999999998 | |
| - type: map_at_10 | |
| value: 35.44 | |
| - type: map_at_100 | |
| value: 37.651 | |
| - type: map_at_1000 | |
| value: 37.824999999999996 | |
| - type: map_at_3 | |
| value: 30.764999999999997 | |
| - type: map_at_5 | |
| value: 33.26 | |
| - type: mrr_at_1 | |
| value: 50.163000000000004 | |
| - type: mrr_at_10 | |
| value: 61.207 | |
| - type: mrr_at_100 | |
| value: 61.675000000000004 | |
| - type: mrr_at_1000 | |
| value: 61.692 | |
| - type: mrr_at_3 | |
| value: 58.60999999999999 | |
| - type: mrr_at_5 | |
| value: 60.307 | |
| - type: ndcg_at_1 | |
| value: 50.163000000000004 | |
| - type: ndcg_at_10 | |
| value: 45.882 | |
| - type: ndcg_at_100 | |
| value: 53.239999999999995 | |
| - type: ndcg_at_1000 | |
| value: 55.852000000000004 | |
| - type: ndcg_at_3 | |
| value: 40.514 | |
| - type: ndcg_at_5 | |
| value: 42.038 | |
| - type: precision_at_1 | |
| value: 50.163000000000004 | |
| - type: precision_at_10 | |
| value: 13.466000000000001 | |
| - type: precision_at_100 | |
| value: 2.164 | |
| - type: precision_at_1000 | |
| value: 0.266 | |
| - type: precision_at_3 | |
| value: 29.707 | |
| - type: precision_at_5 | |
| value: 21.694 | |
| - type: recall_at_1 | |
| value: 22.076999999999998 | |
| - type: recall_at_10 | |
| value: 50.193 | |
| - type: recall_at_100 | |
| value: 74.993 | |
| - type: recall_at_1000 | |
| value: 89.131 | |
| - type: recall_at_3 | |
| value: 35.472 | |
| - type: recall_at_5 | |
| value: 41.814 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/dbpedia | |
| name: MTEB DBPedia | |
| config: default | |
| split: test | |
| revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 | |
| metrics: | |
| - type: map_at_1 | |
| value: 9.953 | |
| - type: map_at_10 | |
| value: 24.515 | |
| - type: map_at_100 | |
| value: 36.173 | |
| - type: map_at_1000 | |
| value: 38.351 | |
| - type: map_at_3 | |
| value: 16.592000000000002 | |
| - type: map_at_5 | |
| value: 20.036 | |
| - type: mrr_at_1 | |
| value: 74.25 | |
| - type: mrr_at_10 | |
| value: 81.813 | |
| - type: mrr_at_100 | |
| value: 82.006 | |
| - type: mrr_at_1000 | |
| value: 82.011 | |
| - type: mrr_at_3 | |
| value: 80.875 | |
| - type: mrr_at_5 | |
| value: 81.362 | |
| - type: ndcg_at_1 | |
| value: 62.5 | |
| - type: ndcg_at_10 | |
| value: 52.42 | |
| - type: ndcg_at_100 | |
| value: 56.808 | |
| - type: ndcg_at_1000 | |
| value: 63.532999999999994 | |
| - type: ndcg_at_3 | |
| value: 56.654 | |
| - type: ndcg_at_5 | |
| value: 54.18300000000001 | |
| - type: precision_at_1 | |
| value: 74.25 | |
| - type: precision_at_10 | |
| value: 42.699999999999996 | |
| - type: precision_at_100 | |
| value: 13.675 | |
| - type: precision_at_1000 | |
| value: 2.664 | |
| - type: precision_at_3 | |
| value: 60.5 | |
| - type: precision_at_5 | |
| value: 52.800000000000004 | |
| - type: recall_at_1 | |
| value: 9.953 | |
| - type: recall_at_10 | |
| value: 30.253999999999998 | |
| - type: recall_at_100 | |
| value: 62.516000000000005 | |
| - type: recall_at_1000 | |
| value: 84.163 | |
| - type: recall_at_3 | |
| value: 18.13 | |
| - type: recall_at_5 | |
| value: 22.771 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/emotion | |
| name: MTEB EmotionClassification | |
| config: default | |
| split: test | |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 | |
| metrics: | |
| - type: accuracy | |
| value: 79.455 | |
| - type: f1 | |
| value: 74.16798697647569 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/fever | |
| name: MTEB FEVER | |
| config: default | |
| split: test | |
| revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 | |
| metrics: | |
| - type: map_at_1 | |
| value: 87.531 | |
| - type: map_at_10 | |
| value: 93.16799999999999 | |
| - type: map_at_100 | |
| value: 93.341 | |
| - type: map_at_1000 | |
| value: 93.349 | |
| - type: map_at_3 | |
| value: 92.444 | |
| - type: map_at_5 | |
| value: 92.865 | |
| - type: mrr_at_1 | |
| value: 94.014 | |
| - type: mrr_at_10 | |
| value: 96.761 | |
| - type: mrr_at_100 | |
| value: 96.762 | |
| - type: mrr_at_1000 | |
| value: 96.762 | |
| - type: mrr_at_3 | |
| value: 96.672 | |
| - type: mrr_at_5 | |
| value: 96.736 | |
| - type: ndcg_at_1 | |
| value: 94.014 | |
| - type: ndcg_at_10 | |
| value: 95.112 | |
| - type: ndcg_at_100 | |
| value: 95.578 | |
| - type: ndcg_at_1000 | |
| value: 95.68900000000001 | |
| - type: ndcg_at_3 | |
| value: 94.392 | |
| - type: ndcg_at_5 | |
| value: 94.72500000000001 | |
| - type: precision_at_1 | |
| value: 94.014 | |
| - type: precision_at_10 | |
| value: 11.065 | |
| - type: precision_at_100 | |
| value: 1.157 | |
| - type: precision_at_1000 | |
| value: 0.11800000000000001 | |
| - type: precision_at_3 | |
| value: 35.259 | |
| - type: precision_at_5 | |
| value: 21.599 | |
| - type: recall_at_1 | |
| value: 87.531 | |
| - type: recall_at_10 | |
| value: 97.356 | |
| - type: recall_at_100 | |
| value: 98.965 | |
| - type: recall_at_1000 | |
| value: 99.607 | |
| - type: recall_at_3 | |
| value: 95.312 | |
| - type: recall_at_5 | |
| value: 96.295 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/fiqa | |
| name: MTEB FiQA2018 | |
| config: default | |
| split: test | |
| revision: 27a168819829fe9bcd655c2df245fb19452e8e06 | |
| metrics: | |
| - type: map_at_1 | |
| value: 32.055 | |
| - type: map_at_10 | |
| value: 53.114 | |
| - type: map_at_100 | |
| value: 55.235 | |
| - type: map_at_1000 | |
| value: 55.345 | |
| - type: map_at_3 | |
| value: 45.854 | |
| - type: map_at_5 | |
| value: 50.025 | |
| - type: mrr_at_1 | |
| value: 60.34 | |
| - type: mrr_at_10 | |
| value: 68.804 | |
| - type: mrr_at_100 | |
| value: 69.309 | |
| - type: mrr_at_1000 | |
| value: 69.32199999999999 | |
| - type: mrr_at_3 | |
| value: 66.40899999999999 | |
| - type: mrr_at_5 | |
| value: 67.976 | |
| - type: ndcg_at_1 | |
| value: 60.34 | |
| - type: ndcg_at_10 | |
| value: 62.031000000000006 | |
| - type: ndcg_at_100 | |
| value: 68.00500000000001 | |
| - type: ndcg_at_1000 | |
| value: 69.286 | |
| - type: ndcg_at_3 | |
| value: 56.355999999999995 | |
| - type: ndcg_at_5 | |
| value: 58.687 | |
| - type: precision_at_1 | |
| value: 60.34 | |
| - type: precision_at_10 | |
| value: 17.176 | |
| - type: precision_at_100 | |
| value: 2.36 | |
| - type: precision_at_1000 | |
| value: 0.259 | |
| - type: precision_at_3 | |
| value: 37.14 | |
| - type: precision_at_5 | |
| value: 27.809 | |
| - type: recall_at_1 | |
| value: 32.055 | |
| - type: recall_at_10 | |
| value: 70.91 | |
| - type: recall_at_100 | |
| value: 91.83 | |
| - type: recall_at_1000 | |
| value: 98.871 | |
| - type: recall_at_3 | |
| value: 51.202999999999996 | |
| - type: recall_at_5 | |
| value: 60.563 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/hotpotqa | |
| name: MTEB HotpotQA | |
| config: default | |
| split: test | |
| revision: ab518f4d6fcca38d87c25209f94beba119d02014 | |
| metrics: | |
| - type: map_at_1 | |
| value: 43.68 | |
| - type: map_at_10 | |
| value: 64.389 | |
| - type: map_at_100 | |
| value: 65.24 | |
| - type: map_at_1000 | |
| value: 65.303 | |
| - type: map_at_3 | |
| value: 61.309000000000005 | |
| - type: map_at_5 | |
| value: 63.275999999999996 | |
| - type: mrr_at_1 | |
| value: 87.36 | |
| - type: mrr_at_10 | |
| value: 91.12 | |
| - type: mrr_at_100 | |
| value: 91.227 | |
| - type: mrr_at_1000 | |
| value: 91.229 | |
| - type: mrr_at_3 | |
| value: 90.57600000000001 | |
| - type: mrr_at_5 | |
| value: 90.912 | |
| - type: ndcg_at_1 | |
| value: 87.36 | |
| - type: ndcg_at_10 | |
| value: 73.076 | |
| - type: ndcg_at_100 | |
| value: 75.895 | |
| - type: ndcg_at_1000 | |
| value: 77.049 | |
| - type: ndcg_at_3 | |
| value: 68.929 | |
| - type: ndcg_at_5 | |
| value: 71.28 | |
| - type: precision_at_1 | |
| value: 87.36 | |
| - type: precision_at_10 | |
| value: 14.741000000000001 | |
| - type: precision_at_100 | |
| value: 1.694 | |
| - type: precision_at_1000 | |
| value: 0.185 | |
| - type: precision_at_3 | |
| value: 43.043 | |
| - type: precision_at_5 | |
| value: 27.681 | |
| - type: recall_at_1 | |
| value: 43.68 | |
| - type: recall_at_10 | |
| value: 73.707 | |
| - type: recall_at_100 | |
| value: 84.7 | |
| - type: recall_at_1000 | |
| value: 92.309 | |
| - type: recall_at_3 | |
| value: 64.564 | |
| - type: recall_at_5 | |
| value: 69.203 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/imdb | |
| name: MTEB ImdbClassification | |
| config: default | |
| split: test | |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 | |
| metrics: | |
| - type: accuracy | |
| value: 96.75399999999999 | |
| - type: ap | |
| value: 95.29389839242187 | |
| - type: f1 | |
| value: 96.75348377433475 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/msmarco | |
| name: MTEB MSMARCO | |
| config: default | |
| split: dev | |
| revision: c5a29a104738b98a9e76336939199e264163d4a0 | |
| metrics: | |
| - type: map_at_1 | |
| value: 25.176 | |
| - type: map_at_10 | |
| value: 38.598 | |
| - type: map_at_100 | |
| value: 39.707 | |
| - type: map_at_1000 | |
| value: 39.744 | |
| - type: map_at_3 | |
| value: 34.566 | |
| - type: map_at_5 | |
| value: 36.863 | |
| - type: mrr_at_1 | |
| value: 25.874000000000002 | |
| - type: mrr_at_10 | |
| value: 39.214 | |
| - type: mrr_at_100 | |
| value: 40.251 | |
| - type: mrr_at_1000 | |
| value: 40.281 | |
| - type: mrr_at_3 | |
| value: 35.291 | |
| - type: mrr_at_5 | |
| value: 37.545 | |
| - type: ndcg_at_1 | |
| value: 25.874000000000002 | |
| - type: ndcg_at_10 | |
| value: 45.98 | |
| - type: ndcg_at_100 | |
| value: 51.197 | |
| - type: ndcg_at_1000 | |
| value: 52.073 | |
| - type: ndcg_at_3 | |
| value: 37.785999999999994 | |
| - type: ndcg_at_5 | |
| value: 41.870000000000005 | |
| - type: precision_at_1 | |
| value: 25.874000000000002 | |
| - type: precision_at_10 | |
| value: 7.181 | |
| - type: precision_at_100 | |
| value: 0.979 | |
| - type: precision_at_1000 | |
| value: 0.106 | |
| - type: precision_at_3 | |
| value: 16.051000000000002 | |
| - type: precision_at_5 | |
| value: 11.713 | |
| - type: recall_at_1 | |
| value: 25.176 | |
| - type: recall_at_10 | |
| value: 68.67699999999999 | |
| - type: recall_at_100 | |
| value: 92.55 | |
| - type: recall_at_1000 | |
| value: 99.164 | |
| - type: recall_at_3 | |
| value: 46.372 | |
| - type: recall_at_5 | |
| value: 56.16 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/mtop_domain | |
| name: MTEB MTOPDomainClassification (en) | |
| config: en | |
| split: test | |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf | |
| metrics: | |
| - type: accuracy | |
| value: 99.03784769721841 | |
| - type: f1 | |
| value: 98.97791641821495 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/mtop_intent | |
| name: MTEB MTOPIntentClassification (en) | |
| config: en | |
| split: test | |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba | |
| metrics: | |
| - type: accuracy | |
| value: 91.88326493388054 | |
| - type: f1 | |
| value: 73.74809928034335 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_massive_intent | |
| name: MTEB MassiveIntentClassification (en) | |
| config: en | |
| split: test | |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 | |
| metrics: | |
| - type: accuracy | |
| value: 85.41358439811701 | |
| - type: f1 | |
| value: 83.503679460639 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_massive_scenario | |
| name: MTEB MassiveScenarioClassification (en) | |
| config: en | |
| split: test | |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 | |
| metrics: | |
| - type: accuracy | |
| value: 89.77135171486215 | |
| - type: f1 | |
| value: 88.89843747468366 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/medrxiv-clustering-p2p | |
| name: MTEB MedrxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 | |
| metrics: | |
| - type: v_measure | |
| value: 46.22695362087359 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/medrxiv-clustering-s2s | |
| name: MTEB MedrxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 | |
| metrics: | |
| - type: v_measure | |
| value: 44.132372165849425 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/mind_small | |
| name: MTEB MindSmallReranking | |
| config: default | |
| split: test | |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 | |
| metrics: | |
| - type: map | |
| value: 33.35680810650402 | |
| - type: mrr | |
| value: 34.72625715637218 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/nfcorpus | |
| name: MTEB NFCorpus | |
| config: default | |
| split: test | |
| revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 | |
| metrics: | |
| - type: map_at_1 | |
| value: 7.165000000000001 | |
| - type: map_at_10 | |
| value: 15.424 | |
| - type: map_at_100 | |
| value: 20.28 | |
| - type: map_at_1000 | |
| value: 22.065 | |
| - type: map_at_3 | |
| value: 11.236 | |
| - type: map_at_5 | |
| value: 13.025999999999998 | |
| - type: mrr_at_1 | |
| value: 51.702999999999996 | |
| - type: mrr_at_10 | |
| value: 59.965 | |
| - type: mrr_at_100 | |
| value: 60.667 | |
| - type: mrr_at_1000 | |
| value: 60.702999999999996 | |
| - type: mrr_at_3 | |
| value: 58.772000000000006 | |
| - type: mrr_at_5 | |
| value: 59.267 | |
| - type: ndcg_at_1 | |
| value: 49.536 | |
| - type: ndcg_at_10 | |
| value: 40.6 | |
| - type: ndcg_at_100 | |
| value: 37.848 | |
| - type: ndcg_at_1000 | |
| value: 46.657 | |
| - type: ndcg_at_3 | |
| value: 46.117999999999995 | |
| - type: ndcg_at_5 | |
| value: 43.619 | |
| - type: precision_at_1 | |
| value: 51.393 | |
| - type: precision_at_10 | |
| value: 30.31 | |
| - type: precision_at_100 | |
| value: 9.972 | |
| - type: precision_at_1000 | |
| value: 2.329 | |
| - type: precision_at_3 | |
| value: 43.137 | |
| - type: precision_at_5 | |
| value: 37.585 | |
| - type: recall_at_1 | |
| value: 7.165000000000001 | |
| - type: recall_at_10 | |
| value: 19.689999999999998 | |
| - type: recall_at_100 | |
| value: 39.237 | |
| - type: recall_at_1000 | |
| value: 71.417 | |
| - type: recall_at_3 | |
| value: 12.247 | |
| - type: recall_at_5 | |
| value: 14.902999999999999 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/nq | |
| name: MTEB NQ | |
| config: default | |
| split: test | |
| revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 | |
| metrics: | |
| - type: map_at_1 | |
| value: 42.653999999999996 | |
| - type: map_at_10 | |
| value: 59.611999999999995 | |
| - type: map_at_100 | |
| value: 60.32300000000001 | |
| - type: map_at_1000 | |
| value: 60.336 | |
| - type: map_at_3 | |
| value: 55.584999999999994 | |
| - type: map_at_5 | |
| value: 58.19 | |
| - type: mrr_at_1 | |
| value: 47.683 | |
| - type: mrr_at_10 | |
| value: 62.06700000000001 | |
| - type: mrr_at_100 | |
| value: 62.537 | |
| - type: mrr_at_1000 | |
| value: 62.544999999999995 | |
| - type: mrr_at_3 | |
| value: 59.178 | |
| - type: mrr_at_5 | |
| value: 61.034 | |
| - type: ndcg_at_1 | |
| value: 47.654 | |
| - type: ndcg_at_10 | |
| value: 67.001 | |
| - type: ndcg_at_100 | |
| value: 69.73899999999999 | |
| - type: ndcg_at_1000 | |
| value: 69.986 | |
| - type: ndcg_at_3 | |
| value: 59.95700000000001 | |
| - type: ndcg_at_5 | |
| value: 64.025 | |
| - type: precision_at_1 | |
| value: 47.654 | |
| - type: precision_at_10 | |
| value: 10.367999999999999 | |
| - type: precision_at_100 | |
| value: 1.192 | |
| - type: precision_at_1000 | |
| value: 0.121 | |
| - type: precision_at_3 | |
| value: 26.651000000000003 | |
| - type: precision_at_5 | |
| value: 18.459 | |
| - type: recall_at_1 | |
| value: 42.653999999999996 | |
| - type: recall_at_10 | |
| value: 86.619 | |
| - type: recall_at_100 | |
| value: 98.04899999999999 | |
| - type: recall_at_1000 | |
| value: 99.812 | |
| - type: recall_at_3 | |
| value: 68.987 | |
| - type: recall_at_5 | |
| value: 78.158 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/quora | |
| name: MTEB QuoraRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 72.538 | |
| - type: map_at_10 | |
| value: 86.702 | |
| - type: map_at_100 | |
| value: 87.31 | |
| - type: map_at_1000 | |
| value: 87.323 | |
| - type: map_at_3 | |
| value: 83.87 | |
| - type: map_at_5 | |
| value: 85.682 | |
| - type: mrr_at_1 | |
| value: 83.31 | |
| - type: mrr_at_10 | |
| value: 89.225 | |
| - type: mrr_at_100 | |
| value: 89.30399999999999 | |
| - type: mrr_at_1000 | |
| value: 89.30399999999999 | |
| - type: mrr_at_3 | |
| value: 88.44300000000001 | |
| - type: mrr_at_5 | |
| value: 89.005 | |
| - type: ndcg_at_1 | |
| value: 83.32000000000001 | |
| - type: ndcg_at_10 | |
| value: 90.095 | |
| - type: ndcg_at_100 | |
| value: 91.12 | |
| - type: ndcg_at_1000 | |
| value: 91.179 | |
| - type: ndcg_at_3 | |
| value: 87.606 | |
| - type: ndcg_at_5 | |
| value: 89.031 | |
| - type: precision_at_1 | |
| value: 83.32000000000001 | |
| - type: precision_at_10 | |
| value: 13.641 | |
| - type: precision_at_100 | |
| value: 1.541 | |
| - type: precision_at_1000 | |
| value: 0.157 | |
| - type: precision_at_3 | |
| value: 38.377 | |
| - type: precision_at_5 | |
| value: 25.162000000000003 | |
| - type: recall_at_1 | |
| value: 72.538 | |
| - type: recall_at_10 | |
| value: 96.47200000000001 | |
| - type: recall_at_100 | |
| value: 99.785 | |
| - type: recall_at_1000 | |
| value: 99.99900000000001 | |
| - type: recall_at_3 | |
| value: 89.278 | |
| - type: recall_at_5 | |
| value: 93.367 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/reddit-clustering | |
| name: MTEB RedditClustering | |
| config: default | |
| split: test | |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb | |
| metrics: | |
| - type: v_measure | |
| value: 73.55219145406065 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/reddit-clustering-p2p | |
| name: MTEB RedditClusteringP2P | |
| config: default | |
| split: test | |
| revision: 282350215ef01743dc01b456c7f5241fa8937f16 | |
| metrics: | |
| - type: v_measure | |
| value: 74.13437105242755 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/scidocs | |
| name: MTEB SCIDOCS | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 6.873 | |
| - type: map_at_10 | |
| value: 17.944 | |
| - type: map_at_100 | |
| value: 21.171 | |
| - type: map_at_1000 | |
| value: 21.528 | |
| - type: map_at_3 | |
| value: 12.415 | |
| - type: map_at_5 | |
| value: 15.187999999999999 | |
| - type: mrr_at_1 | |
| value: 33.800000000000004 | |
| - type: mrr_at_10 | |
| value: 46.455 | |
| - type: mrr_at_100 | |
| value: 47.378 | |
| - type: mrr_at_1000 | |
| value: 47.394999999999996 | |
| - type: mrr_at_3 | |
| value: 42.367 | |
| - type: mrr_at_5 | |
| value: 44.972 | |
| - type: ndcg_at_1 | |
| value: 33.800000000000004 | |
| - type: ndcg_at_10 | |
| value: 28.907 | |
| - type: ndcg_at_100 | |
| value: 39.695 | |
| - type: ndcg_at_1000 | |
| value: 44.582 | |
| - type: ndcg_at_3 | |
| value: 26.949 | |
| - type: ndcg_at_5 | |
| value: 23.988 | |
| - type: precision_at_1 | |
| value: 33.800000000000004 | |
| - type: precision_at_10 | |
| value: 15.079999999999998 | |
| - type: precision_at_100 | |
| value: 3.056 | |
| - type: precision_at_1000 | |
| value: 0.42100000000000004 | |
| - type: precision_at_3 | |
| value: 25.167 | |
| - type: precision_at_5 | |
| value: 21.26 | |
| - type: recall_at_1 | |
| value: 6.873 | |
| - type: recall_at_10 | |
| value: 30.568 | |
| - type: recall_at_100 | |
| value: 62.062 | |
| - type: recall_at_1000 | |
| value: 85.37700000000001 | |
| - type: recall_at_3 | |
| value: 15.312999999999999 | |
| - type: recall_at_5 | |
| value: 21.575 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sickr-sts | |
| name: MTEB SICK-R | |
| config: default | |
| split: test | |
| revision: a6ea5a8cab320b040a23452cc28066d9beae2cee | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 82.37009118256057 | |
| - type: cos_sim_spearman | |
| value: 79.27986395671529 | |
| - type: euclidean_pearson | |
| value: 79.18037715442115 | |
| - type: euclidean_spearman | |
| value: 79.28004791561621 | |
| - type: manhattan_pearson | |
| value: 79.34062972800541 | |
| - type: manhattan_spearman | |
| value: 79.43106695543402 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts12-sts | |
| name: MTEB STS12 | |
| config: default | |
| split: test | |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 87.48474767383833 | |
| - type: cos_sim_spearman | |
| value: 79.54505388752513 | |
| - type: euclidean_pearson | |
| value: 83.43282704179565 | |
| - type: euclidean_spearman | |
| value: 79.54579919925405 | |
| - type: manhattan_pearson | |
| value: 83.77564492427952 | |
| - type: manhattan_spearman | |
| value: 79.84558396989286 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts13-sts | |
| name: MTEB STS13 | |
| config: default | |
| split: test | |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 88.803698035802 | |
| - type: cos_sim_spearman | |
| value: 88.83451367754881 | |
| - type: euclidean_pearson | |
| value: 88.28939285711628 | |
| - type: euclidean_spearman | |
| value: 88.83528996073112 | |
| - type: manhattan_pearson | |
| value: 88.28017412671795 | |
| - type: manhattan_spearman | |
| value: 88.9228828016344 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts14-sts | |
| name: MTEB STS14 | |
| config: default | |
| split: test | |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 85.27469288153428 | |
| - type: cos_sim_spearman | |
| value: 83.87477064876288 | |
| - type: euclidean_pearson | |
| value: 84.2601737035379 | |
| - type: euclidean_spearman | |
| value: 83.87431082479074 | |
| - type: manhattan_pearson | |
| value: 84.3621547772745 | |
| - type: manhattan_spearman | |
| value: 84.12094375000423 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts15-sts | |
| name: MTEB STS15 | |
| config: default | |
| split: test | |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 88.12749863201587 | |
| - type: cos_sim_spearman | |
| value: 88.54287568368565 | |
| - type: euclidean_pearson | |
| value: 87.90429700607999 | |
| - type: euclidean_spearman | |
| value: 88.5437689576261 | |
| - type: manhattan_pearson | |
| value: 88.19276653356833 | |
| - type: manhattan_spearman | |
| value: 88.99995393814679 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts16-sts | |
| name: MTEB STS16 | |
| config: default | |
| split: test | |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 85.68398747560902 | |
| - type: cos_sim_spearman | |
| value: 86.48815303460574 | |
| - type: euclidean_pearson | |
| value: 85.52356631237954 | |
| - type: euclidean_spearman | |
| value: 86.486391949551 | |
| - type: manhattan_pearson | |
| value: 85.67267981761788 | |
| - type: manhattan_spearman | |
| value: 86.7073696332485 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts17-crosslingual-sts | |
| name: MTEB STS17 (en-en) | |
| config: en-en | |
| split: test | |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 88.9057107443124 | |
| - type: cos_sim_spearman | |
| value: 88.7312168757697 | |
| - type: euclidean_pearson | |
| value: 88.72810439714794 | |
| - type: euclidean_spearman | |
| value: 88.71976185854771 | |
| - type: manhattan_pearson | |
| value: 88.50433745949111 | |
| - type: manhattan_spearman | |
| value: 88.51726175544195 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts22-crosslingual-sts | |
| name: MTEB STS22 (en) | |
| config: en | |
| split: test | |
| revision: eea2b4fe26a775864c896887d910b76a8098ad3f | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 67.59391795109886 | |
| - type: cos_sim_spearman | |
| value: 66.87613008631367 | |
| - type: euclidean_pearson | |
| value: 69.23198488262217 | |
| - type: euclidean_spearman | |
| value: 66.85427723013692 | |
| - type: manhattan_pearson | |
| value: 69.50730124841084 | |
| - type: manhattan_spearman | |
| value: 67.10404669820792 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/stsbenchmark-sts | |
| name: MTEB STSBenchmark | |
| config: default | |
| split: test | |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 87.0820605344619 | |
| - type: cos_sim_spearman | |
| value: 86.8518089863434 | |
| - type: euclidean_pearson | |
| value: 86.31087134689284 | |
| - type: euclidean_spearman | |
| value: 86.8518520517941 | |
| - type: manhattan_pearson | |
| value: 86.47203796160612 | |
| - type: manhattan_spearman | |
| value: 87.1080149734421 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/scidocs-reranking | |
| name: MTEB SciDocsRR | |
| config: default | |
| split: test | |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab | |
| metrics: | |
| - type: map | |
| value: 89.09255369305481 | |
| - type: mrr | |
| value: 97.10323445617563 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/scifact | |
| name: MTEB SciFact | |
| config: default | |
| split: test | |
| revision: 0228b52cf27578f30900b9e5271d331663a030d7 | |
| metrics: | |
| - type: map_at_1 | |
| value: 61.260999999999996 | |
| - type: map_at_10 | |
| value: 74.043 | |
| - type: map_at_100 | |
| value: 74.37700000000001 | |
| - type: map_at_1000 | |
| value: 74.384 | |
| - type: map_at_3 | |
| value: 71.222 | |
| - type: map_at_5 | |
| value: 72.875 | |
| - type: mrr_at_1 | |
| value: 64.333 | |
| - type: mrr_at_10 | |
| value: 74.984 | |
| - type: mrr_at_100 | |
| value: 75.247 | |
| - type: mrr_at_1000 | |
| value: 75.25500000000001 | |
| - type: mrr_at_3 | |
| value: 73.167 | |
| - type: mrr_at_5 | |
| value: 74.35000000000001 | |
| - type: ndcg_at_1 | |
| value: 64.333 | |
| - type: ndcg_at_10 | |
| value: 79.06 | |
| - type: ndcg_at_100 | |
| value: 80.416 | |
| - type: ndcg_at_1000 | |
| value: 80.55600000000001 | |
| - type: ndcg_at_3 | |
| value: 74.753 | |
| - type: ndcg_at_5 | |
| value: 76.97500000000001 | |
| - type: precision_at_1 | |
| value: 64.333 | |
| - type: precision_at_10 | |
| value: 10.567 | |
| - type: precision_at_100 | |
| value: 1.1199999999999999 | |
| - type: precision_at_1000 | |
| value: 0.11299999999999999 | |
| - type: precision_at_3 | |
| value: 29.889 | |
| - type: precision_at_5 | |
| value: 19.533 | |
| - type: recall_at_1 | |
| value: 61.260999999999996 | |
| - type: recall_at_10 | |
| value: 93.167 | |
| - type: recall_at_100 | |
| value: 99.0 | |
| - type: recall_at_1000 | |
| value: 100.0 | |
| - type: recall_at_3 | |
| value: 81.667 | |
| - type: recall_at_5 | |
| value: 87.394 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/sprintduplicatequestions-pairclassification | |
| name: MTEB SprintDuplicateQuestions | |
| config: default | |
| split: test | |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 99.71980198019801 | |
| - type: cos_sim_ap | |
| value: 92.81616007802704 | |
| - type: cos_sim_f1 | |
| value: 85.17548454688318 | |
| - type: cos_sim_precision | |
| value: 89.43894389438944 | |
| - type: cos_sim_recall | |
| value: 81.3 | |
| - type: dot_accuracy | |
| value: 99.71980198019801 | |
| - type: dot_ap | |
| value: 92.81398760591358 | |
| - type: dot_f1 | |
| value: 85.17548454688318 | |
| - type: dot_precision | |
| value: 89.43894389438944 | |
| - type: dot_recall | |
| value: 81.3 | |
| - type: euclidean_accuracy | |
| value: 99.71980198019801 | |
| - type: euclidean_ap | |
| value: 92.81560637245072 | |
| - type: euclidean_f1 | |
| value: 85.17548454688318 | |
| - type: euclidean_precision | |
| value: 89.43894389438944 | |
| - type: euclidean_recall | |
| value: 81.3 | |
| - type: manhattan_accuracy | |
| value: 99.73069306930694 | |
| - type: manhattan_ap | |
| value: 93.14005487480794 | |
| - type: manhattan_f1 | |
| value: 85.56263269639068 | |
| - type: manhattan_precision | |
| value: 91.17647058823529 | |
| - type: manhattan_recall | |
| value: 80.60000000000001 | |
| - type: max_accuracy | |
| value: 99.73069306930694 | |
| - type: max_ap | |
| value: 93.14005487480794 | |
| - type: max_f1 | |
| value: 85.56263269639068 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/stackexchange-clustering | |
| name: MTEB StackExchangeClustering | |
| config: default | |
| split: test | |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 | |
| metrics: | |
| - type: v_measure | |
| value: 79.86443362395185 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/stackexchange-clustering-p2p | |
| name: MTEB StackExchangeClusteringP2P | |
| config: default | |
| split: test | |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 | |
| metrics: | |
| - type: v_measure | |
| value: 49.40897096662564 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/stackoverflowdupquestions-reranking | |
| name: MTEB StackOverflowDupQuestions | |
| config: default | |
| split: test | |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 | |
| metrics: | |
| - type: map | |
| value: 55.66040806627947 | |
| - type: mrr | |
| value: 56.58670475766064 | |
| - task: | |
| type: Summarization | |
| dataset: | |
| type: mteb/summeval | |
| name: MTEB SummEval | |
| config: default | |
| split: test | |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 31.51015090598575 | |
| - type: cos_sim_spearman | |
| value: 31.35016454939226 | |
| - type: dot_pearson | |
| value: 31.5150068731 | |
| - type: dot_spearman | |
| value: 31.34790869023487 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/trec-covid | |
| name: MTEB TRECCOVID | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 0.254 | |
| - type: map_at_10 | |
| value: 2.064 | |
| - type: map_at_100 | |
| value: 12.909 | |
| - type: map_at_1000 | |
| value: 31.761 | |
| - type: map_at_3 | |
| value: 0.738 | |
| - type: map_at_5 | |
| value: 1.155 | |
| - type: mrr_at_1 | |
| value: 96.0 | |
| - type: mrr_at_10 | |
| value: 98.0 | |
| - type: mrr_at_100 | |
| value: 98.0 | |
| - type: mrr_at_1000 | |
| value: 98.0 | |
| - type: mrr_at_3 | |
| value: 98.0 | |
| - type: mrr_at_5 | |
| value: 98.0 | |
| - type: ndcg_at_1 | |
| value: 93.0 | |
| - type: ndcg_at_10 | |
| value: 82.258 | |
| - type: ndcg_at_100 | |
| value: 64.34 | |
| - type: ndcg_at_1000 | |
| value: 57.912 | |
| - type: ndcg_at_3 | |
| value: 90.827 | |
| - type: ndcg_at_5 | |
| value: 86.79 | |
| - type: precision_at_1 | |
| value: 96.0 | |
| - type: precision_at_10 | |
| value: 84.8 | |
| - type: precision_at_100 | |
| value: 66.0 | |
| - type: precision_at_1000 | |
| value: 25.356 | |
| - type: precision_at_3 | |
| value: 94.667 | |
| - type: precision_at_5 | |
| value: 90.4 | |
| - type: recall_at_1 | |
| value: 0.254 | |
| - type: recall_at_10 | |
| value: 2.1950000000000003 | |
| - type: recall_at_100 | |
| value: 16.088 | |
| - type: recall_at_1000 | |
| value: 54.559000000000005 | |
| - type: recall_at_3 | |
| value: 0.75 | |
| - type: recall_at_5 | |
| value: 1.191 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/touche2020 | |
| name: MTEB Touche2020 | |
| config: default | |
| split: test | |
| revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f | |
| metrics: | |
| - type: map_at_1 | |
| value: 2.976 | |
| - type: map_at_10 | |
| value: 11.389000000000001 | |
| - type: map_at_100 | |
| value: 18.429000000000002 | |
| - type: map_at_1000 | |
| value: 20.113 | |
| - type: map_at_3 | |
| value: 6.483 | |
| - type: map_at_5 | |
| value: 8.770999999999999 | |
| - type: mrr_at_1 | |
| value: 40.816 | |
| - type: mrr_at_10 | |
| value: 58.118 | |
| - type: mrr_at_100 | |
| value: 58.489999999999995 | |
| - type: mrr_at_1000 | |
| value: 58.489999999999995 | |
| - type: mrr_at_3 | |
| value: 53.061 | |
| - type: mrr_at_5 | |
| value: 57.041 | |
| - type: ndcg_at_1 | |
| value: 40.816 | |
| - type: ndcg_at_10 | |
| value: 30.567 | |
| - type: ndcg_at_100 | |
| value: 42.44 | |
| - type: ndcg_at_1000 | |
| value: 53.480000000000004 | |
| - type: ndcg_at_3 | |
| value: 36.016 | |
| - type: ndcg_at_5 | |
| value: 34.257 | |
| - type: precision_at_1 | |
| value: 42.857 | |
| - type: precision_at_10 | |
| value: 25.714 | |
| - type: precision_at_100 | |
| value: 8.429 | |
| - type: precision_at_1000 | |
| value: 1.5939999999999999 | |
| - type: precision_at_3 | |
| value: 36.735 | |
| - type: precision_at_5 | |
| value: 33.878 | |
| - type: recall_at_1 | |
| value: 2.976 | |
| - type: recall_at_10 | |
| value: 17.854999999999997 | |
| - type: recall_at_100 | |
| value: 51.833 | |
| - type: recall_at_1000 | |
| value: 86.223 | |
| - type: recall_at_3 | |
| value: 7.887 | |
| - type: recall_at_5 | |
| value: 12.026 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/toxic_conversations_50k | |
| name: MTEB ToxicConversationsClassification | |
| config: default | |
| split: test | |
| revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c | |
| metrics: | |
| - type: accuracy | |
| value: 85.1174 | |
| - type: ap | |
| value: 30.169441069345748 | |
| - type: f1 | |
| value: 69.79254701873245 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/tweet_sentiment_extraction | |
| name: MTEB TweetSentimentExtractionClassification | |
| config: default | |
| split: test | |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a | |
| metrics: | |
| - type: accuracy | |
| value: 72.58347481607245 | |
| - type: f1 | |
| value: 72.74877295564937 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/twentynewsgroups-clustering | |
| name: MTEB TwentyNewsgroupsClustering | |
| config: default | |
| split: test | |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 | |
| metrics: | |
| - type: v_measure | |
| value: 53.90586138221305 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/twittersemeval2015-pairclassification | |
| name: MTEB TwitterSemEval2015 | |
| config: default | |
| split: test | |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 87.35769207844072 | |
| - type: cos_sim_ap | |
| value: 77.9645072410354 | |
| - type: cos_sim_f1 | |
| value: 71.32352941176471 | |
| - type: cos_sim_precision | |
| value: 66.5903890160183 | |
| - type: cos_sim_recall | |
| value: 76.78100263852242 | |
| - type: dot_accuracy | |
| value: 87.37557370209214 | |
| - type: dot_ap | |
| value: 77.96250046429908 | |
| - type: dot_f1 | |
| value: 71.28932757557064 | |
| - type: dot_precision | |
| value: 66.95249130938586 | |
| - type: dot_recall | |
| value: 76.22691292875989 | |
| - type: euclidean_accuracy | |
| value: 87.35173153722357 | |
| - type: euclidean_ap | |
| value: 77.96520460741593 | |
| - type: euclidean_f1 | |
| value: 71.32470733210104 | |
| - type: euclidean_precision | |
| value: 66.91329479768785 | |
| - type: euclidean_recall | |
| value: 76.35883905013192 | |
| - type: manhattan_accuracy | |
| value: 87.25636287774931 | |
| - type: manhattan_ap | |
| value: 77.77752485611796 | |
| - type: manhattan_f1 | |
| value: 71.18148599269183 | |
| - type: manhattan_precision | |
| value: 66.10859728506787 | |
| - type: manhattan_recall | |
| value: 77.0976253298153 | |
| - type: max_accuracy | |
| value: 87.37557370209214 | |
| - type: max_ap | |
| value: 77.96520460741593 | |
| - type: max_f1 | |
| value: 71.32470733210104 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/twitterurlcorpus-pairclassification | |
| name: MTEB TwitterURLCorpus | |
| config: default | |
| split: test | |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 89.38176737687739 | |
| - type: cos_sim_ap | |
| value: 86.58811861657401 | |
| - type: cos_sim_f1 | |
| value: 79.09430644097604 | |
| - type: cos_sim_precision | |
| value: 75.45085977911366 | |
| - type: cos_sim_recall | |
| value: 83.10748383122882 | |
| - type: dot_accuracy | |
| value: 89.38370784336554 | |
| - type: dot_ap | |
| value: 86.58840606004333 | |
| - type: dot_f1 | |
| value: 79.10179860068133 | |
| - type: dot_precision | |
| value: 75.44546153308643 | |
| - type: dot_recall | |
| value: 83.13058207576223 | |
| - type: euclidean_accuracy | |
| value: 89.38564830985369 | |
| - type: euclidean_ap | |
| value: 86.58820721061164 | |
| - type: euclidean_f1 | |
| value: 79.09070942235888 | |
| - type: euclidean_precision | |
| value: 75.38729937194697 | |
| - type: euclidean_recall | |
| value: 83.17677856482906 | |
| - type: manhattan_accuracy | |
| value: 89.40699344122326 | |
| - type: manhattan_ap | |
| value: 86.60631843011362 | |
| - type: manhattan_f1 | |
| value: 79.14949970570925 | |
| - type: manhattan_precision | |
| value: 75.78191039729502 | |
| - type: manhattan_recall | |
| value: 82.83030489682784 | |
| - type: max_accuracy | |
| value: 89.40699344122326 | |
| - type: max_ap | |
| value: 86.60631843011362 | |
| - type: max_f1 | |
| value: 79.14949970570925 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: C-MTEB/AFQMC | |
| name: MTEB AFQMC | |
| config: default | |
| split: validation | |
| revision: b44c3b011063adb25877c13823db83bb193913c4 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 65.58442135663871 | |
| - type: cos_sim_spearman | |
| value: 72.2538631361313 | |
| - type: euclidean_pearson | |
| value: 70.97255486607429 | |
| - type: euclidean_spearman | |
| value: 72.25374250228647 | |
| - type: manhattan_pearson | |
| value: 70.83250199989911 | |
| - type: manhattan_spearman | |
| value: 72.14819496536272 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: C-MTEB/ATEC | |
| name: MTEB ATEC | |
| config: default | |
| split: test | |
| revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 59.99478404929932 | |
| - type: cos_sim_spearman | |
| value: 62.61836216999812 | |
| - type: euclidean_pearson | |
| value: 66.86429811933593 | |
| - type: euclidean_spearman | |
| value: 62.6183520374191 | |
| - type: manhattan_pearson | |
| value: 66.8063778911633 | |
| - type: manhattan_spearman | |
| value: 62.569607573241115 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_reviews_multi | |
| name: MTEB AmazonReviewsClassification (zh) | |
| config: zh | |
| split: test | |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d | |
| metrics: | |
| - type: accuracy | |
| value: 53.98400000000001 | |
| - type: f1 | |
| value: 51.21447361350723 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: C-MTEB/BQ | |
| name: MTEB BQ | |
| config: default | |
| split: test | |
| revision: e3dda5e115e487b39ec7e618c0c6a29137052a55 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 79.11941660686553 | |
| - type: cos_sim_spearman | |
| value: 81.25029594540435 | |
| - type: euclidean_pearson | |
| value: 82.06973504238826 | |
| - type: euclidean_spearman | |
| value: 81.2501989488524 | |
| - type: manhattan_pearson | |
| value: 82.10094630392753 | |
| - type: manhattan_spearman | |
| value: 81.27987244392389 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: C-MTEB/CLSClusteringP2P | |
| name: MTEB CLSClusteringP2P | |
| config: default | |
| split: test | |
| revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476 | |
| metrics: | |
| - type: v_measure | |
| value: 47.07270168705156 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: C-MTEB/CLSClusteringS2S | |
| name: MTEB CLSClusteringS2S | |
| config: default | |
| split: test | |
| revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f | |
| metrics: | |
| - type: v_measure | |
| value: 45.98511703185043 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: C-MTEB/CMedQAv1-reranking | |
| name: MTEB CMedQAv1 | |
| config: default | |
| split: test | |
| revision: 8d7f1e942507dac42dc58017c1a001c3717da7df | |
| metrics: | |
| - type: map | |
| value: 88.19895157194931 | |
| - type: mrr | |
| value: 90.21424603174603 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: C-MTEB/CMedQAv2-reranking | |
| name: MTEB CMedQAv2 | |
| config: default | |
| split: test | |
| revision: 23d186750531a14a0357ca22cd92d712fd512ea0 | |
| metrics: | |
| - type: map | |
| value: 88.03317320980119 | |
| - type: mrr | |
| value: 89.9461507936508 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/CmedqaRetrieval | |
| name: MTEB CmedqaRetrieval | |
| config: default | |
| split: dev | |
| revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301 | |
| metrics: | |
| - type: map_at_1 | |
| value: 29.037000000000003 | |
| - type: map_at_10 | |
| value: 42.001 | |
| - type: map_at_100 | |
| value: 43.773 | |
| - type: map_at_1000 | |
| value: 43.878 | |
| - type: map_at_3 | |
| value: 37.637 | |
| - type: map_at_5 | |
| value: 40.034 | |
| - type: mrr_at_1 | |
| value: 43.136 | |
| - type: mrr_at_10 | |
| value: 51.158 | |
| - type: mrr_at_100 | |
| value: 52.083 | |
| - type: mrr_at_1000 | |
| value: 52.12 | |
| - type: mrr_at_3 | |
| value: 48.733 | |
| - type: mrr_at_5 | |
| value: 50.025 | |
| - type: ndcg_at_1 | |
| value: 43.136 | |
| - type: ndcg_at_10 | |
| value: 48.685 | |
| - type: ndcg_at_100 | |
| value: 55.513 | |
| - type: ndcg_at_1000 | |
| value: 57.242000000000004 | |
| - type: ndcg_at_3 | |
| value: 43.329 | |
| - type: ndcg_at_5 | |
| value: 45.438 | |
| - type: precision_at_1 | |
| value: 43.136 | |
| - type: precision_at_10 | |
| value: 10.56 | |
| - type: precision_at_100 | |
| value: 1.6129999999999998 | |
| - type: precision_at_1000 | |
| value: 0.184 | |
| - type: precision_at_3 | |
| value: 24.064 | |
| - type: precision_at_5 | |
| value: 17.269000000000002 | |
| - type: recall_at_1 | |
| value: 29.037000000000003 | |
| - type: recall_at_10 | |
| value: 59.245000000000005 | |
| - type: recall_at_100 | |
| value: 87.355 | |
| - type: recall_at_1000 | |
| value: 98.74000000000001 | |
| - type: recall_at_3 | |
| value: 42.99 | |
| - type: recall_at_5 | |
| value: 49.681999999999995 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: C-MTEB/CMNLI | |
| name: MTEB Cmnli | |
| config: default | |
| split: validation | |
| revision: 41bc36f332156f7adc9e38f53777c959b2ae9766 | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 82.68190018039687 | |
| - type: cos_sim_ap | |
| value: 90.18017125327886 | |
| - type: cos_sim_f1 | |
| value: 83.64080906868193 | |
| - type: cos_sim_precision | |
| value: 79.7076890489303 | |
| - type: cos_sim_recall | |
| value: 87.98223053542202 | |
| - type: dot_accuracy | |
| value: 82.68190018039687 | |
| - type: dot_ap | |
| value: 90.18782350103646 | |
| - type: dot_f1 | |
| value: 83.64242087729039 | |
| - type: dot_precision | |
| value: 79.65313028764805 | |
| - type: dot_recall | |
| value: 88.05237315875614 | |
| - type: euclidean_accuracy | |
| value: 82.68190018039687 | |
| - type: euclidean_ap | |
| value: 90.1801957900632 | |
| - type: euclidean_f1 | |
| value: 83.63636363636364 | |
| - type: euclidean_precision | |
| value: 79.52772506852203 | |
| - type: euclidean_recall | |
| value: 88.19265840542437 | |
| - type: manhattan_accuracy | |
| value: 82.14070956103427 | |
| - type: manhattan_ap | |
| value: 89.96178420101427 | |
| - type: manhattan_f1 | |
| value: 83.21087838578791 | |
| - type: manhattan_precision | |
| value: 78.35605121850475 | |
| - type: manhattan_recall | |
| value: 88.70703764320785 | |
| - type: max_accuracy | |
| value: 82.68190018039687 | |
| - type: max_ap | |
| value: 90.18782350103646 | |
| - type: max_f1 | |
| value: 83.64242087729039 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/CovidRetrieval | |
| name: MTEB CovidRetrieval | |
| config: default | |
| split: dev | |
| revision: 1271c7809071a13532e05f25fb53511ffce77117 | |
| metrics: | |
| - type: map_at_1 | |
| value: 72.234 | |
| - type: map_at_10 | |
| value: 80.10000000000001 | |
| - type: map_at_100 | |
| value: 80.36 | |
| - type: map_at_1000 | |
| value: 80.363 | |
| - type: map_at_3 | |
| value: 78.315 | |
| - type: map_at_5 | |
| value: 79.607 | |
| - type: mrr_at_1 | |
| value: 72.392 | |
| - type: mrr_at_10 | |
| value: 80.117 | |
| - type: mrr_at_100 | |
| value: 80.36999999999999 | |
| - type: mrr_at_1000 | |
| value: 80.373 | |
| - type: mrr_at_3 | |
| value: 78.469 | |
| - type: mrr_at_5 | |
| value: 79.633 | |
| - type: ndcg_at_1 | |
| value: 72.392 | |
| - type: ndcg_at_10 | |
| value: 83.651 | |
| - type: ndcg_at_100 | |
| value: 84.749 | |
| - type: ndcg_at_1000 | |
| value: 84.83000000000001 | |
| - type: ndcg_at_3 | |
| value: 80.253 | |
| - type: ndcg_at_5 | |
| value: 82.485 | |
| - type: precision_at_1 | |
| value: 72.392 | |
| - type: precision_at_10 | |
| value: 9.557 | |
| - type: precision_at_100 | |
| value: 1.004 | |
| - type: precision_at_1000 | |
| value: 0.101 | |
| - type: precision_at_3 | |
| value: 28.732000000000003 | |
| - type: precision_at_5 | |
| value: 18.377 | |
| - type: recall_at_1 | |
| value: 72.234 | |
| - type: recall_at_10 | |
| value: 94.573 | |
| - type: recall_at_100 | |
| value: 99.368 | |
| - type: recall_at_1000 | |
| value: 100.0 | |
| - type: recall_at_3 | |
| value: 85.669 | |
| - type: recall_at_5 | |
| value: 91.01700000000001 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/DuRetrieval | |
| name: MTEB DuRetrieval | |
| config: default | |
| split: dev | |
| revision: a1a333e290fe30b10f3f56498e3a0d911a693ced | |
| metrics: | |
| - type: map_at_1 | |
| value: 26.173999999999996 | |
| - type: map_at_10 | |
| value: 80.04 | |
| - type: map_at_100 | |
| value: 82.94500000000001 | |
| - type: map_at_1000 | |
| value: 82.98100000000001 | |
| - type: map_at_3 | |
| value: 55.562999999999995 | |
| - type: map_at_5 | |
| value: 69.89800000000001 | |
| - type: mrr_at_1 | |
| value: 89.5 | |
| - type: mrr_at_10 | |
| value: 92.996 | |
| - type: mrr_at_100 | |
| value: 93.06400000000001 | |
| - type: mrr_at_1000 | |
| value: 93.065 | |
| - type: mrr_at_3 | |
| value: 92.658 | |
| - type: mrr_at_5 | |
| value: 92.84599999999999 | |
| - type: ndcg_at_1 | |
| value: 89.5 | |
| - type: ndcg_at_10 | |
| value: 87.443 | |
| - type: ndcg_at_100 | |
| value: 90.253 | |
| - type: ndcg_at_1000 | |
| value: 90.549 | |
| - type: ndcg_at_3 | |
| value: 85.874 | |
| - type: ndcg_at_5 | |
| value: 84.842 | |
| - type: precision_at_1 | |
| value: 89.5 | |
| - type: precision_at_10 | |
| value: 41.805 | |
| - type: precision_at_100 | |
| value: 4.827 | |
| - type: precision_at_1000 | |
| value: 0.49 | |
| - type: precision_at_3 | |
| value: 76.85 | |
| - type: precision_at_5 | |
| value: 64.8 | |
| - type: recall_at_1 | |
| value: 26.173999999999996 | |
| - type: recall_at_10 | |
| value: 89.101 | |
| - type: recall_at_100 | |
| value: 98.08099999999999 | |
| - type: recall_at_1000 | |
| value: 99.529 | |
| - type: recall_at_3 | |
| value: 57.902 | |
| - type: recall_at_5 | |
| value: 74.602 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/EcomRetrieval | |
| name: MTEB EcomRetrieval | |
| config: default | |
| split: dev | |
| revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9 | |
| metrics: | |
| - type: map_at_1 | |
| value: 56.10000000000001 | |
| - type: map_at_10 | |
| value: 66.15299999999999 | |
| - type: map_at_100 | |
| value: 66.625 | |
| - type: map_at_1000 | |
| value: 66.636 | |
| - type: map_at_3 | |
| value: 63.632999999999996 | |
| - type: map_at_5 | |
| value: 65.293 | |
| - type: mrr_at_1 | |
| value: 56.10000000000001 | |
| - type: mrr_at_10 | |
| value: 66.15299999999999 | |
| - type: mrr_at_100 | |
| value: 66.625 | |
| - type: mrr_at_1000 | |
| value: 66.636 | |
| - type: mrr_at_3 | |
| value: 63.632999999999996 | |
| - type: mrr_at_5 | |
| value: 65.293 | |
| - type: ndcg_at_1 | |
| value: 56.10000000000001 | |
| - type: ndcg_at_10 | |
| value: 71.146 | |
| - type: ndcg_at_100 | |
| value: 73.27799999999999 | |
| - type: ndcg_at_1000 | |
| value: 73.529 | |
| - type: ndcg_at_3 | |
| value: 66.09 | |
| - type: ndcg_at_5 | |
| value: 69.08999999999999 | |
| - type: precision_at_1 | |
| value: 56.10000000000001 | |
| - type: precision_at_10 | |
| value: 8.68 | |
| - type: precision_at_100 | |
| value: 0.964 | |
| - type: precision_at_1000 | |
| value: 0.098 | |
| - type: precision_at_3 | |
| value: 24.4 | |
| - type: precision_at_5 | |
| value: 16.1 | |
| - type: recall_at_1 | |
| value: 56.10000000000001 | |
| - type: recall_at_10 | |
| value: 86.8 | |
| - type: recall_at_100 | |
| value: 96.39999999999999 | |
| - type: recall_at_1000 | |
| value: 98.3 | |
| - type: recall_at_3 | |
| value: 73.2 | |
| - type: recall_at_5 | |
| value: 80.5 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: C-MTEB/IFlyTek-classification | |
| name: MTEB IFlyTek | |
| config: default | |
| split: validation | |
| revision: 421605374b29664c5fc098418fe20ada9bd55f8a | |
| metrics: | |
| - type: accuracy | |
| value: 54.52096960369373 | |
| - type: f1 | |
| value: 40.930845295808695 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: C-MTEB/JDReview-classification | |
| name: MTEB JDReview | |
| config: default | |
| split: test | |
| revision: b7c64bd89eb87f8ded463478346f76731f07bf8b | |
| metrics: | |
| - type: accuracy | |
| value: 86.51031894934334 | |
| - type: ap | |
| value: 55.9516014323483 | |
| - type: f1 | |
| value: 81.54813679326381 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: C-MTEB/LCQMC | |
| name: MTEB LCQMC | |
| config: default | |
| split: test | |
| revision: 17f9b096f80380fce5ed12a9be8be7784b337daf | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 69.67437838574276 | |
| - type: cos_sim_spearman | |
| value: 73.81314174653045 | |
| - type: euclidean_pearson | |
| value: 72.63430276680275 | |
| - type: euclidean_spearman | |
| value: 73.81358736777001 | |
| - type: manhattan_pearson | |
| value: 72.58743833842829 | |
| - type: manhattan_spearman | |
| value: 73.7590419009179 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: C-MTEB/Mmarco-reranking | |
| name: MTEB MMarcoReranking | |
| config: default | |
| split: dev | |
| revision: None | |
| metrics: | |
| - type: map | |
| value: 31.648613483640254 | |
| - type: mrr | |
| value: 30.37420634920635 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/MMarcoRetrieval | |
| name: MTEB MMarcoRetrieval | |
| config: default | |
| split: dev | |
| revision: 539bbde593d947e2a124ba72651aafc09eb33fc2 | |
| metrics: | |
| - type: map_at_1 | |
| value: 73.28099999999999 | |
| - type: map_at_10 | |
| value: 81.977 | |
| - type: map_at_100 | |
| value: 82.222 | |
| - type: map_at_1000 | |
| value: 82.22699999999999 | |
| - type: map_at_3 | |
| value: 80.441 | |
| - type: map_at_5 | |
| value: 81.46600000000001 | |
| - type: mrr_at_1 | |
| value: 75.673 | |
| - type: mrr_at_10 | |
| value: 82.41000000000001 | |
| - type: mrr_at_100 | |
| value: 82.616 | |
| - type: mrr_at_1000 | |
| value: 82.621 | |
| - type: mrr_at_3 | |
| value: 81.094 | |
| - type: mrr_at_5 | |
| value: 81.962 | |
| - type: ndcg_at_1 | |
| value: 75.673 | |
| - type: ndcg_at_10 | |
| value: 85.15599999999999 | |
| - type: ndcg_at_100 | |
| value: 86.151 | |
| - type: ndcg_at_1000 | |
| value: 86.26899999999999 | |
| - type: ndcg_at_3 | |
| value: 82.304 | |
| - type: ndcg_at_5 | |
| value: 84.009 | |
| - type: precision_at_1 | |
| value: 75.673 | |
| - type: precision_at_10 | |
| value: 10.042 | |
| - type: precision_at_100 | |
| value: 1.052 | |
| - type: precision_at_1000 | |
| value: 0.106 | |
| - type: precision_at_3 | |
| value: 30.673000000000002 | |
| - type: precision_at_5 | |
| value: 19.326999999999998 | |
| - type: recall_at_1 | |
| value: 73.28099999999999 | |
| - type: recall_at_10 | |
| value: 94.446 | |
| - type: recall_at_100 | |
| value: 98.737 | |
| - type: recall_at_1000 | |
| value: 99.649 | |
| - type: recall_at_3 | |
| value: 86.984 | |
| - type: recall_at_5 | |
| value: 91.024 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_massive_intent | |
| name: MTEB MassiveIntentClassification (zh-CN) | |
| config: zh-CN | |
| split: test | |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 | |
| metrics: | |
| - type: accuracy | |
| value: 81.08607935440484 | |
| - type: f1 | |
| value: 78.24879986066307 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_massive_scenario | |
| name: MTEB MassiveScenarioClassification (zh-CN) | |
| config: zh-CN | |
| split: test | |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 | |
| metrics: | |
| - type: accuracy | |
| value: 86.05917955615332 | |
| - type: f1 | |
| value: 85.05279279434997 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/MedicalRetrieval | |
| name: MTEB MedicalRetrieval | |
| config: default | |
| split: dev | |
| revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6 | |
| metrics: | |
| - type: map_at_1 | |
| value: 56.2 | |
| - type: map_at_10 | |
| value: 62.57899999999999 | |
| - type: map_at_100 | |
| value: 63.154999999999994 | |
| - type: map_at_1000 | |
| value: 63.193 | |
| - type: map_at_3 | |
| value: 61.217 | |
| - type: map_at_5 | |
| value: 62.012 | |
| - type: mrr_at_1 | |
| value: 56.3 | |
| - type: mrr_at_10 | |
| value: 62.629000000000005 | |
| - type: mrr_at_100 | |
| value: 63.205999999999996 | |
| - type: mrr_at_1000 | |
| value: 63.244 | |
| - type: mrr_at_3 | |
| value: 61.267 | |
| - type: mrr_at_5 | |
| value: 62.062 | |
| - type: ndcg_at_1 | |
| value: 56.2 | |
| - type: ndcg_at_10 | |
| value: 65.592 | |
| - type: ndcg_at_100 | |
| value: 68.657 | |
| - type: ndcg_at_1000 | |
| value: 69.671 | |
| - type: ndcg_at_3 | |
| value: 62.808 | |
| - type: ndcg_at_5 | |
| value: 64.24499999999999 | |
| - type: precision_at_1 | |
| value: 56.2 | |
| - type: precision_at_10 | |
| value: 7.5 | |
| - type: precision_at_100 | |
| value: 0.899 | |
| - type: precision_at_1000 | |
| value: 0.098 | |
| - type: precision_at_3 | |
| value: 22.467000000000002 | |
| - type: precision_at_5 | |
| value: 14.180000000000001 | |
| - type: recall_at_1 | |
| value: 56.2 | |
| - type: recall_at_10 | |
| value: 75.0 | |
| - type: recall_at_100 | |
| value: 89.9 | |
| - type: recall_at_1000 | |
| value: 97.89999999999999 | |
| - type: recall_at_3 | |
| value: 67.4 | |
| - type: recall_at_5 | |
| value: 70.89999999999999 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: C-MTEB/MultilingualSentiment-classification | |
| name: MTEB MultilingualSentiment | |
| config: default | |
| split: validation | |
| revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a | |
| metrics: | |
| - type: accuracy | |
| value: 76.87666666666667 | |
| - type: f1 | |
| value: 76.7317686219665 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: C-MTEB/OCNLI | |
| name: MTEB Ocnli | |
| config: default | |
| split: validation | |
| revision: 66e76a618a34d6d565d5538088562851e6daa7ec | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 79.64266377910124 | |
| - type: cos_sim_ap | |
| value: 84.78274442344829 | |
| - type: cos_sim_f1 | |
| value: 81.16947472745292 | |
| - type: cos_sim_precision | |
| value: 76.47058823529412 | |
| - type: cos_sim_recall | |
| value: 86.48363252375924 | |
| - type: dot_accuracy | |
| value: 79.64266377910124 | |
| - type: dot_ap | |
| value: 84.7851404063692 | |
| - type: dot_f1 | |
| value: 81.16947472745292 | |
| - type: dot_precision | |
| value: 76.47058823529412 | |
| - type: dot_recall | |
| value: 86.48363252375924 | |
| - type: euclidean_accuracy | |
| value: 79.64266377910124 | |
| - type: euclidean_ap | |
| value: 84.78068373762378 | |
| - type: euclidean_f1 | |
| value: 81.14794656110837 | |
| - type: euclidean_precision | |
| value: 76.35009310986965 | |
| - type: euclidean_recall | |
| value: 86.58922914466737 | |
| - type: manhattan_accuracy | |
| value: 79.48023822414727 | |
| - type: manhattan_ap | |
| value: 84.72928897427576 | |
| - type: manhattan_f1 | |
| value: 81.32084770823064 | |
| - type: manhattan_precision | |
| value: 76.24768946395564 | |
| - type: manhattan_recall | |
| value: 87.11721224920802 | |
| - type: max_accuracy | |
| value: 79.64266377910124 | |
| - type: max_ap | |
| value: 84.7851404063692 | |
| - type: max_f1 | |
| value: 81.32084770823064 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: C-MTEB/OnlineShopping-classification | |
| name: MTEB OnlineShopping | |
| config: default | |
| split: test | |
| revision: e610f2ebd179a8fda30ae534c3878750a96db120 | |
| metrics: | |
| - type: accuracy | |
| value: 94.3 | |
| - type: ap | |
| value: 92.8664032274438 | |
| - type: f1 | |
| value: 94.29311102997727 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: C-MTEB/PAWSX | |
| name: MTEB PAWSX | |
| config: default | |
| split: test | |
| revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 48.51392279882909 | |
| - type: cos_sim_spearman | |
| value: 54.06338895994974 | |
| - type: euclidean_pearson | |
| value: 52.58480559573412 | |
| - type: euclidean_spearman | |
| value: 54.06417276612201 | |
| - type: manhattan_pearson | |
| value: 52.69525121721343 | |
| - type: manhattan_spearman | |
| value: 54.048147455389675 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: C-MTEB/QBQTC | |
| name: MTEB QBQTC | |
| config: default | |
| split: test | |
| revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 29.728387290757325 | |
| - type: cos_sim_spearman | |
| value: 31.366121633635284 | |
| - type: euclidean_pearson | |
| value: 29.14588368552961 | |
| - type: euclidean_spearman | |
| value: 31.36764411112844 | |
| - type: manhattan_pearson | |
| value: 29.63517350523121 | |
| - type: manhattan_spearman | |
| value: 31.94157020583762 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts22-crosslingual-sts | |
| name: MTEB STS22 (zh) | |
| config: zh | |
| split: test | |
| revision: eea2b4fe26a775864c896887d910b76a8098ad3f | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 63.64868296271406 | |
| - type: cos_sim_spearman | |
| value: 66.12800618164744 | |
| - type: euclidean_pearson | |
| value: 63.21405767340238 | |
| - type: euclidean_spearman | |
| value: 66.12786567790748 | |
| - type: manhattan_pearson | |
| value: 64.04300276525848 | |
| - type: manhattan_spearman | |
| value: 66.5066857145652 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: C-MTEB/STSB | |
| name: MTEB STSB | |
| config: default | |
| split: test | |
| revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 81.2302623912794 | |
| - type: cos_sim_spearman | |
| value: 81.16833673266562 | |
| - type: euclidean_pearson | |
| value: 79.47647843876024 | |
| - type: euclidean_spearman | |
| value: 81.16944349524972 | |
| - type: manhattan_pearson | |
| value: 79.84947238492208 | |
| - type: manhattan_spearman | |
| value: 81.64626599410026 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: C-MTEB/T2Reranking | |
| name: MTEB T2Reranking | |
| config: default | |
| split: dev | |
| revision: 76631901a18387f85eaa53e5450019b87ad58ef9 | |
| metrics: | |
| - type: map | |
| value: 67.80129586475687 | |
| - type: mrr | |
| value: 77.77402311635554 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/T2Retrieval | |
| name: MTEB T2Retrieval | |
| config: default | |
| split: dev | |
| revision: 8731a845f1bf500a4f111cf1070785c793d10e64 | |
| metrics: | |
| - type: map_at_1 | |
| value: 28.666999999999998 | |
| - type: map_at_10 | |
| value: 81.063 | |
| - type: map_at_100 | |
| value: 84.504 | |
| - type: map_at_1000 | |
| value: 84.552 | |
| - type: map_at_3 | |
| value: 56.897 | |
| - type: map_at_5 | |
| value: 70.073 | |
| - type: mrr_at_1 | |
| value: 92.087 | |
| - type: mrr_at_10 | |
| value: 94.132 | |
| - type: mrr_at_100 | |
| value: 94.19800000000001 | |
| - type: mrr_at_1000 | |
| value: 94.19999999999999 | |
| - type: mrr_at_3 | |
| value: 93.78999999999999 | |
| - type: mrr_at_5 | |
| value: 94.002 | |
| - type: ndcg_at_1 | |
| value: 92.087 | |
| - type: ndcg_at_10 | |
| value: 87.734 | |
| - type: ndcg_at_100 | |
| value: 90.736 | |
| - type: ndcg_at_1000 | |
| value: 91.184 | |
| - type: ndcg_at_3 | |
| value: 88.78 | |
| - type: ndcg_at_5 | |
| value: 87.676 | |
| - type: precision_at_1 | |
| value: 92.087 | |
| - type: precision_at_10 | |
| value: 43.46 | |
| - type: precision_at_100 | |
| value: 5.07 | |
| - type: precision_at_1000 | |
| value: 0.518 | |
| - type: precision_at_3 | |
| value: 77.49000000000001 | |
| - type: precision_at_5 | |
| value: 65.194 | |
| - type: recall_at_1 | |
| value: 28.666999999999998 | |
| - type: recall_at_10 | |
| value: 86.632 | |
| - type: recall_at_100 | |
| value: 96.646 | |
| - type: recall_at_1000 | |
| value: 98.917 | |
| - type: recall_at_3 | |
| value: 58.333999999999996 | |
| - type: recall_at_5 | |
| value: 72.974 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: C-MTEB/TNews-classification | |
| name: MTEB TNews | |
| config: default | |
| split: validation | |
| revision: 317f262bf1e6126357bbe89e875451e4b0938fe4 | |
| metrics: | |
| - type: accuracy | |
| value: 52.971999999999994 | |
| - type: f1 | |
| value: 50.2898280984929 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: C-MTEB/ThuNewsClusteringP2P | |
| name: MTEB ThuNewsClusteringP2P | |
| config: default | |
| split: test | |
| revision: 5798586b105c0434e4f0fe5e767abe619442cf93 | |
| metrics: | |
| - type: v_measure | |
| value: 86.0797948663824 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: C-MTEB/ThuNewsClusteringS2S | |
| name: MTEB ThuNewsClusteringS2S | |
| config: default | |
| split: test | |
| revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d | |
| metrics: | |
| - type: v_measure | |
| value: 85.10759092255017 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: C-MTEB/VideoRetrieval | |
| name: MTEB VideoRetrieval | |
| config: default | |
| split: dev | |
| revision: 58c2597a5943a2ba48f4668c3b90d796283c5639 | |
| metrics: | |
| - type: map_at_1 | |
| value: 65.60000000000001 | |
| - type: map_at_10 | |
| value: 74.773 | |
| - type: map_at_100 | |
| value: 75.128 | |
| - type: map_at_1000 | |
| value: 75.136 | |
| - type: map_at_3 | |
| value: 73.05 | |
| - type: map_at_5 | |
| value: 74.13499999999999 | |
| - type: mrr_at_1 | |
| value: 65.60000000000001 | |
| - type: mrr_at_10 | |
| value: 74.773 | |
| - type: mrr_at_100 | |
| value: 75.128 | |
| - type: mrr_at_1000 | |
| value: 75.136 | |
| - type: mrr_at_3 | |
| value: 73.05 | |
| - type: mrr_at_5 | |
| value: 74.13499999999999 | |
| - type: ndcg_at_1 | |
| value: 65.60000000000001 | |
| - type: ndcg_at_10 | |
| value: 78.84299999999999 | |
| - type: ndcg_at_100 | |
| value: 80.40899999999999 | |
| - type: ndcg_at_1000 | |
| value: 80.57 | |
| - type: ndcg_at_3 | |
| value: 75.40599999999999 | |
| - type: ndcg_at_5 | |
| value: 77.351 | |
| - type: precision_at_1 | |
| value: 65.60000000000001 | |
| - type: precision_at_10 | |
| value: 9.139999999999999 | |
| - type: precision_at_100 | |
| value: 0.984 | |
| - type: precision_at_1000 | |
| value: 0.1 | |
| - type: precision_at_3 | |
| value: 27.400000000000002 | |
| - type: precision_at_5 | |
| value: 17.380000000000003 | |
| - type: recall_at_1 | |
| value: 65.60000000000001 | |
| - type: recall_at_10 | |
| value: 91.4 | |
| - type: recall_at_100 | |
| value: 98.4 | |
| - type: recall_at_1000 | |
| value: 99.6 | |
| - type: recall_at_3 | |
| value: 82.19999999999999 | |
| - type: recall_at_5 | |
| value: 86.9 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: C-MTEB/waimai-classification | |
| name: MTEB Waimai | |
| config: default | |
| split: test | |
| revision: 339287def212450dcaa9df8c22bf93e9980c7023 | |
| metrics: | |
| - type: accuracy | |
| value: 89.47 | |
| - type: ap | |
| value: 75.59561751845389 | |
| - type: f1 | |
| value: 87.95207751382563 | |
| --- | |
| ## gte-Qwen2-7B-instruct | |
| **gte-Qwen2-7B-instruct** is the latest model in the gte (General Text Embedding) model family that ranks **No.1** in both English and Chinese evaluations on the Massive Text Embedding Benchmark [MTEB benchmark](https://huggingface.co/spaces/mteb/leaderboard) (as of June 16, 2024). | |
| Recently, the [**Qwen team**](https://huggingface.co/Qwen) released the Qwen2 series models, and we have trained the **gte-Qwen2-7B-instruct** model based on the [Qwen2-7B](https://huggingface.co/Qwen/Qwen2-7B) LLM model. Compared to the [gte-Qwen1.5-7B-instruct](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) model, the **gte-Qwen2-7B-instruct** model uses the same training data and training strategies during the finetuning stage, with the only difference being the upgraded base model to Qwen2-7B. Considering the improvements in the Qwen2 series models compared to the Qwen1.5 series, we can also expect consistent performance enhancements in the embedding models. | |
| The model incorporates several key advancements: | |
| - Integration of bidirectional attention mechanisms, enriching its contextual understanding. | |
| - Instruction tuning, applied solely on the query side for streamlined efficiency | |
| - Comprehensive training across a vast, multilingual text corpus spanning diverse domains and scenarios. This training leverages both weakly supervised and supervised data, ensuring the model's applicability across numerous languages and a wide array of downstream tasks. | |
| ## Model Information | |
| - Model Size: 7B | |
| - Embedding Dimension: 3584 | |
| - Max Input Tokens: 32k | |
| ## Requirements | |
| ``` | |
| transformers>=4.39.2 | |
| flash_attn>=2.5.6 | |
| ``` | |
| ## Usage | |
| ### Sentence Transformers | |
| ```python | |
| from sentence_transformers import SentenceTransformer | |
| model = SentenceTransformer("Alibaba-NLP/gte-Qwen2-7B-instruct", trust_remote_code=True) | |
| # In case you want to reduce the maximum length: | |
| model.max_seq_length = 8192 | |
| queries = [ | |
| "how much protein should a female eat", | |
| "summit define", | |
| ] | |
| documents = [ | |
| "As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.", | |
| "Definition of summit for English Language Learners. : 1 the highest point of a mountain : the top of a mountain. : 2 the highest level. : 3 a meeting or series of meetings between the leaders of two or more governments.", | |
| ] | |
| query_embeddings = model.encode(queries, prompt_name="query") | |
| document_embeddings = model.encode(documents) | |
| scores = (query_embeddings @ document_embeddings.T) * 100 | |
| print(scores.tolist()) | |
| ``` | |
| Observe the [config_sentence_transformers.json](config_sentence_transformers.json) to see all pre-built prompt names. Otherwise, you can use `model.encode(queries, prompt="Instruct: ...\nQuery: "` to use a custom prompt of your choice. | |
| ### Transformers | |
| ```python | |
| import torch | |
| import torch.nn.functional as F | |
| from torch import Tensor | |
| from transformers import AutoTokenizer, AutoModel | |
| def last_token_pool(last_hidden_states: Tensor, | |
| attention_mask: Tensor) -> Tensor: | |
| left_padding = (attention_mask[:, -1].sum() == attention_mask.shape[0]) | |
| if left_padding: | |
| return last_hidden_states[:, -1] | |
| else: | |
| sequence_lengths = attention_mask.sum(dim=1) - 1 | |
| batch_size = last_hidden_states.shape[0] | |
| return last_hidden_states[torch.arange(batch_size, device=last_hidden_states.device), sequence_lengths] | |
| def get_detailed_instruct(task_description: str, query: str) -> str: | |
| return f'Instruct: {task_description}\nQuery: {query}' | |
| # Each query must come with a one-sentence instruction that describes the task | |
| task = 'Given a web search query, retrieve relevant passages that answer the query' | |
| queries = [ | |
| get_detailed_instruct(task, 'how much protein should a female eat'), | |
| get_detailed_instruct(task, 'summit define') | |
| ] | |
| # No need to add instruction for retrieval documents | |
| documents = [ | |
| "As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.", | |
| "Definition of summit for English Language Learners. : 1 the highest point of a mountain : the top of a mountain. : 2 the highest level. : 3 a meeting or series of meetings between the leaders of two or more governments." | |
| ] | |
| input_texts = queries + documents | |
| tokenizer = AutoTokenizer.from_pretrained('Alibaba-NLP/gte-Qwen2-7B-instruct', trust_remote_code=True) | |
| model = AutoModel.from_pretrained('Alibaba-NLP/gte-Qwen2-7B-instruct', trust_remote_code=True) | |
| max_length = 8192 | |
| # Tokenize the input texts | |
| batch_dict = tokenizer(input_texts, max_length=max_length, padding=True, truncation=True, return_tensors='pt') | |
| outputs = model(**batch_dict) | |
| embeddings = last_token_pool(outputs.last_hidden_state, batch_dict['attention_mask']) | |
| # normalize embeddings | |
| embeddings = F.normalize(embeddings, p=2, dim=1) | |
| scores = (embeddings[:2] @ embeddings[2:].T) * 100 | |
| print(scores.tolist()) | |
| ``` | |
| ## Evaluation | |
| ### MTEB & C-MTEB | |
| You can use the [scripts/eval_mteb.py](https://huggingface.co/Alibaba-NLP/gte-Qwen2-7B-instruct/blob/main/scripts/eval_mteb.py) to reproduce the following result of **gte-Qwen2-7B-instruct** on MTEB(English)/C-MTEB(Chinese): | |
| | Model Name | MTEB(56) | C-MTEB(35) | | |
| |:----:|:---------:|:----------:| | |
| | [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** | | |
| ### 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 | | |
| ## 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} | |
| } | |
| ``` | |