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Gte Qwen2 7B Instruct GGUF
アリババNLPチームによって開発された大規模言語モデル、Qwen2アーキテクチャに基づく7Bパラメータバージョン、命令インタラクションをサポート
ダウンロード数 1,502
リリース時間 : 11/11/2024
モデル概要
これは7Bパラメータの命令ファインチューニング大規模言語モデルで、自然言語理解と生成タスクに適しており、llama.cpp推論フレームワークと互換性があります
モデル特徴
マルチ量子化バージョン選択
Q2_KからQ8_0までの12種類の量子化バージョンを提供し、異なるハードウェア条件での推論ニーズを満たします
命令最適化
命令インタラクションシナリオに特化して最適化されており、ユーザーの命令をより良く理解し実行できます
llama.cpp互換
モデル量子化後はllama.cpp推論フレームワークと完全互換で、展開が容易です
モデル能力
テキスト生成
命令理解
対話インタラクション
テキスト要約
質問応答システム
使用事例
インテリジェントアシスタント
バーチャルカスタマーサービス
ECプラットフォームの自動カスタマーサービスシステムに使用
ユーザーの質問を理解し正確な回答を提供できます
コンテンツ生成
記事作成
コンテンツクリエイターが初稿を生成するのを支援
一貫性があり論理的なテキストコンテンツを生成可能
tags:
- mteb
- sentence-transformers
- transformers
- Qwen2
- sentence-similarity
- TensorBlock
- GGUF license: apache-2.0 base_model: Alibaba-NLP/gte-Qwen2-7B-instruct model-index:
- name: gte-qwen2-7B-instruct
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: mteb/amazon_counterfactual
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:
name: MTEB AmazonPolarityClassification
type: mteb/amazon_polarity
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:
name: MTEB AmazonReviewsClassification (en)
type: mteb/amazon_reviews_multi
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy value: 62.564
- type: f1 value: 60.975777935041066
- task:
type: Retrieval
dataset:
name: MTEB ArguAna
type: 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:
name: MTEB ArxivClusteringP2P
type: mteb/arxiv-clustering-p2p
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure value: 56.461169803700564
- task:
type: Clustering
dataset:
name: MTEB ArxivClusteringS2S
type: mteb/arxiv-clustering-s2s
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure value: 51.73600434466286
- task:
type: Reranking
dataset:
name: MTEB AskUbuntuDupQuestions
type: mteb/askubuntudupquestions-reranking
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map value: 67.57827065898053
- type: mrr value: 79.08136569493911
- task:
type: STS
dataset:
name: MTEB BIOSSES
type: mteb/biosses-sts
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:
name: MTEB Banking77Classification
type: mteb/banking77
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy value: 87.56818181818181
- type: f1 value: 87.25826722019875
- task:
type: Clustering
dataset:
name: MTEB BiorxivClusteringP2P
type: mteb/biorxiv-clustering-p2p
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure value: 50.09239610327673
- task:
type: Clustering
dataset:
name: MTEB BiorxivClusteringS2S
type: mteb/biorxiv-clustering-s2s
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure value: 46.64733054606282
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackAndroidRetrieval
type: BeIR/cqadupstack
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:
name: MTEB CQADupstackEnglishRetrieval
type: BeIR/cqadupstack
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:
name: MTEB CQADupstackGamingRetrieval
type: BeIR/cqadupstack
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:
name: MTEB CQADupstackGisRetrieval
type: BeIR/cqadupstack
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:
name: MTEB CQADupstackMathematicaRetrieval
type: BeIR/cqadupstack
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:
name: MTEB CQADupstackPhysicsRetrieval
type: BeIR/cqadupstack
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:
name: MTEB CQADupstackProgrammersRetrieval
type: BeIR/cqadupstack
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:
name: MTEB CQADupstackRetrieval
type: BeIR/cqadupstack
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
- 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:
name: MTEB CQADupstackStatsRetrieval
type: BeIR/cqadupstack
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:
name: MTEB CQADupstackTexRetrieval
type: BeIR/cqadupstack
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:
name: MTEB CQADupstackUnixRetrieval
type: BeIR/cqadupstack
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:
name: MTEB CQADupstackWebmastersRetrieval
type: BeIR/cqadupstack
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:
name: MTEB ClimateFEVER
type: mteb/climate-fever
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:
name: MTEB DBPedia
type: 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:
name: MTEB EmotionClassification
type: mteb/emotion
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy value: 79.455
- type: f1 value: 74.16798697647569
- task:
type: Retrieval
dataset:
name: MTEB FEVER
type: 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:
name: MTEB FiQA2018
type: mteb/fiqa
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:
name: MTEB HotpotQA
type: 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:
name: MTEB ImdbClassification
type: mteb/imdb
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:
name: MTEB MSMARCO
type: 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:
name: MTEB MTOPDomainClassification (en)
type: mteb/mtop_domain
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy value: 99.03784769721841
- type: f1 value: 98.97791641821495
- task:
type: Classification
dataset:
name: MTEB MTOPIntentClassification (en)
type: mteb/mtop_intent
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy value: 91.88326493388054
- type: f1 value: 73.74809928034335
- task:
type: Classification
dataset:
name: MTEB MassiveIntentClassification (en)
type: mteb/amazon_massive_intent
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 85.41358439811701
- type: f1 value: 83.503679460639
- task:
type: Classification
dataset:
name: MTEB MassiveScenarioClassification (en)
type: mteb/amazon_massive_scenario
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy value: 89.77135171486215
- type: f1 value: 88.89843747468366
- task:
type: Clustering
dataset:
name: MTEB MedrxivClusteringP2P
type: mteb/medrxiv-clustering-p2p
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure value: 46.22695362087359
- task:
type: Clustering
dataset:
name: MTEB MedrxivClusteringS2S
type: mteb/medrxiv-clustering-s2s
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure value: 44.132372165849425
- task:
type: Reranking
dataset:
name: MTEB MindSmallReranking
type: mteb/mind_small
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map value: 33.35680810650402
- type: mrr value: 34.72625715637218
- task:
type: Retrieval
dataset:
name: MTEB NFCorpus
type: 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:
name: MTEB NQ
type: 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:
name: MTEB QuoraRetrieval
type: mteb/quora
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:
name: MTEB RedditClustering
type: mteb/reddit-clustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure value: 73.55219145406065
- task:
type: Clustering
dataset:
name: MTEB RedditClusteringP2P
type: mteb/reddit-clustering-p2p
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure value: 74.13437105242755
- task:
type: Retrieval
dataset:
name: MTEB SCIDOCS
type: 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:
name: MTEB SICK-R
type: mteb/sickr-sts
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:
name: MTEB STS12
type: mteb/sts12-sts
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:
name: MTEB STS13
type: mteb/sts13-sts
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:
name: MTEB STS14
type: mteb/sts14-sts
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:
name: MTEB STS15
type: mteb/sts15-sts
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:
name: MTEB STS16
type: mteb/sts16-sts
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:
name: MTEB STS17 (en-en)
type: mteb/sts17-crosslingual-sts
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:
name: MTEB STS22 (en)
type: mteb/sts22-crosslingual-sts
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:
name: MTEB STSBenchmark
type: mteb/stsbenchmark-sts
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:
name: MTEB SciDocsRR
type: mteb/scidocs-reranking
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map value: 89.09255369305481
- type: mrr value: 97.10323445617563
- task:
type: Retrieval
dataset:
name: MTEB SciFact
type: 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:
name: MTEB SprintDuplicateQuestions
type: mteb/sprintduplicatequestions-pairclassification
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:
name: MTEB StackExchangeClustering
type: mteb/stackexchange-clustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure value: 79.86443362395185
- task:
type: Clustering
dataset:
name: MTEB StackExchangeClusteringP2P
type: mteb/stackexchange-clustering-p2p
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure value: 49.40897096662564
- task:
type: Reranking
dataset:
name: MTEB StackOverflowDupQuestions
type: mteb/stackoverflowdupquestions-reranking
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map value: 55.66040806627947
- type: mrr value: 56.58670475766064
- task:
type: Summarization
dataset:
name: MTEB SummEval
type: 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:
name: MTEB TRECCOVID
type: mteb/trec-covid
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:
name: MTEB Touche2020
type: 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:
name: MTEB ToxicConversationsClassification
type: mteb/toxic_conversations_50k
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:
name: MTEB TweetSentimentExtractionClassification
type: mteb/tweet_sentiment_extraction
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy value: 72.58347481607245
- type: f1 value: 72.74877295564937
- task:
type: Clustering
dataset:
name: MTEB TwentyNewsgroupsClustering
type: mteb/twentynewsgroups-clustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure value: 53.90586138221305
- task:
type: PairClassification
dataset:
name: MTEB TwitterSemEval2015
type: mteb/twittersemeval2015-pairclassification
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:
name: MTEB TwitterURLCorpus
type: mteb/twitterurlcorpus-pairclassification
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:
name: MTEB AFQMC
type: C-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:
name: MTEB ATEC
type: C-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:
name: MTEB AmazonReviewsClassification (zh)
type: mteb/amazon_reviews_multi
config: zh
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy value: 53.98400000000001
- type: f1 value: 51.21447361350723
- task:
type: STS
dataset:
name: MTEB BQ
type: C-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:
name: MTEB CLSClusteringP2P
type: C-MTEB/CLSClusteringP2P
config: default
split: test
revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
metrics:
- type: v_measure value: 47.07270168705156
- task:
type: Clustering
dataset:
name: MTEB CLSClusteringS2S
type: C-MTEB/CLSClusteringS2S
config: default
split: test
revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
metrics:
- type: v_measure value: 45.98511703185043
- task:
type: Reranking
dataset:
name: MTEB CMedQAv1
type: C-MTEB/CMedQAv1-reranking
config: default
split: test
revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
metrics:
- type: map value: 88.19895157194931
- type: mrr value: 90.21424603174603
- task:
type: Reranking
dataset:
name: MTEB CMedQAv2
type: C-MTEB/CMedQAv2-reranking
config: default
split: test
revision: 23d186750531a14a0357ca22cd92d712fd512ea0
metrics:
- type: map value: 88.03317320980119
- type: mrr value: 89.9461507936508
- task:
type: Retrieval
dataset:
name: MTEB CmedqaRetrieval
type: C-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:
name: MTEB Cmnli
type: C-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:
name: MTEB CovidRetrieval
type: C-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:
name: MTEB DuRetrieval
type: C-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:
name: MTEB EcomRetrieval
type: C-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:
name: MTEB IFlyTek
type: C-MTEB/IFlyTek-classification
config: default
split: validation
revision: 421605374b29664c5fc098418fe20ada9bd55f8a
metrics:
- type: accuracy value: 54.52096960369373
- type: f1 value: 40.930845295808695
- task:
type: Classification
dataset:
name: MTEB JDReview
type: C-MTEB/JDReview-classification
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:
name: MTEB LCQMC
type: C-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:
name: MTEB MMarcoReranking
type: C-MTEB/Mmarco-reranking
config: default
split: dev
revision: None
metrics:
- type: map value: 31.648613483640254
- type: mrr value: 30.37420634920635
- task:
type: Retrieval
dataset:
name: MTEB MMarcoRetrieval
type: C-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:
name: MTEB MassiveIntentClassification (zh-CN)
type: mteb/amazon_massive_intent
config: zh-CN
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 81.08607935440484
- type: f1 value: 78.24879986066307
- task:
type: Classification
dataset:
name: MTEB MassiveScenarioClassification (zh-CN)
type: mteb/amazon_massive_scenario
config: zh-CN
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy value: 86.05917955615332
- type: f1 value: 85.05279279434997
- task:
type: Retrieval
dataset:
name: MTEB MedicalRetrieval
type: C-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:
name: MTEB MultilingualSentiment
type: C-MTEB/MultilingualSentiment-classification
config: default
split: validation
revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
metrics:
- type: accuracy value: 76.87666666666667
- type: f1 value: 76.7317686219665
- task:
type: PairClassification
dataset:
name: MTEB Ocnli
type: C-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:
name: MTEB OnlineShopping
type: C-MTEB/OnlineShopping-classification
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:
name: MTEB PAWSX
type: C-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:
name: MTEB QBQTC
type: C-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:
name: MTEB STS22 (zh)
type: mteb/sts22-crosslingual-sts
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:
name: MTEB STSB
type: C-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:
name: MTEB T2Reranking
type: C-MTEB/T2Reranking
config: default
split: dev
revision: 76631901a18387f85eaa53e5450019b87ad58ef9
metrics:
- type: map value: 67.80129586475687
- type: mrr value: 77.77402311635554
- task:
type: Retrieval
dataset:
name: MTEB T2Retrieval
type: C-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:
name: MTEB TNews
type: C-MTEB/TNews-classification
config: default
split: validation
revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
metrics:
- type: accuracy value: 52.971999999999994
- type: f1 value: 50.2898280984929
- task:
type: Clustering
dataset:
name: MTEB ThuNewsClusteringP2P
type: C-MTEB/ThuNewsClusteringP2P
config: default
split: test
revision: 5798586b105c0434e4f0fe5e767abe619442cf93
metrics:
- type: v_measure value: 86.0797948663824
- task:
type: Clustering
dataset:
name: MTEB ThuNewsClusteringS2S
type: C-MTEB/ThuNewsClusteringS2S
config: default
split: test
revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
metrics:
- type: v_measure value: 85.10759092255017
- task:
type: Retrieval
dataset:
name: MTEB VideoRetrieval
type: C-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:
name: MTEB Waimai
type: C-MTEB/waimai-classification
config: default
split: test
revision: 339287def212450dcaa9df8c22bf93e9980c7023
metrics:
- type: accuracy value: 89.47
- type: ap value: 75.59561751845389
- type: f1 value: 87.95207751382563
- task:
type: Clustering
dataset:
name: MTEB AlloProfClusteringP2P
type: lyon-nlp/alloprof
config: default
split: test
revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
metrics:
- type: v_measure value: 76.05592323841036
- type: v_measure value: 64.51718058866508
- task:
type: Reranking
dataset:
name: MTEB AlloprofReranking
type: lyon-nlp/mteb-fr-reranking-alloprof-s2p
config: default
split: test
revision: 666fdacebe0291776e86f29345663dfaf80a0db9
metrics:
- type: map value: 73.08278490943373
- type: mrr value: 74.66561454570449
- task:
type: Retrieval
dataset:
name: MTEB AlloprofRetrieval
type: lyon-nlp/alloprof
config: default
split: test
revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
metrics:
- type: map_at_1 value: 38.912
- type: map_at_10 value: 52.437999999999995
- type: map_at_100 value: 53.38
- type: map_at_1000 value: 53.427
- type: map_at_3 value: 48.879
- type: map_at_5 value: 50.934000000000005
- type: mrr_at_1 value: 44.085
- type: mrr_at_10 value: 55.337
- type: mrr_at_100 value: 56.016999999999996
- type: mrr_at_1000 value: 56.043
- type: mrr_at_3 value: 52.55499999999999
- type: mrr_at_5 value: 54.20399999999999
- type: ndcg_at_1 value: 44.085
- type: ndcg_at_10 value: 58.876
- type: ndcg_at_100 value: 62.714000000000006
- type: ndcg_at_1000 value: 63.721000000000004
- type: ndcg_at_3 value: 52.444
- type: ndcg_at_5 value: 55.692
- type: precision_at_1 value: 44.085
- type: precision_at_10 value: 9.21
- type: precision_at_100 value: 1.164
- type: precision_at_1000 value: 0.128
- type: precision_at_3 value: 23.043
- type: precision_at_5 value: 15.898000000000001
- type: recall_at_1 value: 38.912
- type: recall_at_10 value: 75.577
- type: recall_at_100 value: 92.038
- type: recall_at_1000 value: 99.325
- type: recall_at_3 value: 58.592
- type: recall_at_5 value: 66.235
- task:
type: Classification
dataset:
name: MTEB AmazonReviewsClassification (fr)
type: mteb/amazon_reviews_multi
config: fr
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy value: 55.532000000000004
- type: f1 value: 52.5783943471605
- task:
type: Retrieval
dataset:
name: MTEB BSARDRetrieval
type: maastrichtlawtech/bsard
config: default
split: test
revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59
metrics:
- type: map_at_1 value: 8.108
- type: map_at_10 value: 14.710999999999999
- type: map_at_100 value: 15.891
- type: map_at_1000 value: 15.983
- type: map_at_3 value: 12.237
- type: map_at_5 value: 13.679
- type: mrr_at_1 value: 8.108
- type: mrr_at_10 value: 14.710999999999999
- type: mrr_at_100 value: 15.891
- type: mrr_at_1000 value: 15.983
- type: mrr_at_3 value: 12.237
- type: mrr_at_5 value: 13.679
- type: ndcg_at_1 value: 8.108
- type: ndcg_at_10 value: 18.796
- type: ndcg_at_100 value: 25.098
- type: ndcg_at_1000 value: 27.951999999999998
- type: ndcg_at_3 value: 13.712
- type: ndcg_at_5 value: 16.309
- type: precision_at_1 value: 8.108
- type: precision_at_10 value: 3.198
- type: precision_at_100 value: 0.626
- type: precision_at_1000 value: 0.086
- type: precision_at_3 value: 6.006
- type: precision_at_5 value: 4.865
- type: recall_at_1 value: 8.108
- type: recall_at_10 value: 31.982
- type: recall_at_100 value: 62.613
- type: recall_at_1000 value: 86.036
- type: recall_at_3 value: 18.018
- type: recall_at_5 value: 24.324
- task:
type: Clustering
dataset:
name: MTEB HALClusteringS2S
type: lyon-nlp/clustering-hal-s2s
config: default
split: test
revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915
metrics:
- type: v_measure value: 30.833269778867116
- task:
type: Clustering
dataset:
name: MTEB MLSUMClusteringP2P
type: mlsum
config: default
split: test
revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
metrics:
- type: v_measure value: 50.0281928004713
- type: v_measure value: 43.699961510636534
- task:
type: Classification
dataset:
name: MTEB MTOPDomainClassification (fr)
type: mteb/mtop_domain
config: fr
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy value: 96.68963357344191
- type: f1 value: 96.45175170820961
- task:
type: Classification
dataset:
name: MTEB MTOPIntentClassification (fr)
type: mteb/mtop_intent
config: fr
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy value: 87.46946445349202
- type: f1 value: 65.79860440988624
- task:
type: Classification
dataset:
name: MTEB MasakhaNEWSClassification (fra)
type: masakhane/masakhanews
config: fra
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: accuracy value: 82.60663507109005
- type: f1 value: 77.20462646604777
- task:
type: Clustering
dataset:
name: MTEB MasakhaNEWSClusteringP2P (fra)
type: masakhane/masakhanews
config: fra
split: test
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
metrics:
- type: v_measure value: 60.19311264967803
- type: v_measure value: 63.6235764409785
- task:
type: Classification
dataset:
name: MTEB MassiveIntentClassification (fr)
type: mteb/amazon_massive_intent
config: fr
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 81.65097511768661
- type: f1 value: 78.77796091490924
- task:
type: Classification
dataset:
name: MTEB MassiveScenarioClassification (fr)
type: mteb/amazon_massive_scenario
config: fr
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy value: 86.64425016812373
- type: f1 value: 85.4912728670017
- task:
type: Retrieval
dataset:
name: MTEB MintakaRetrieval (fr)
type: jinaai/mintakaqa
config: fr
split: test
revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e
metrics:
- type: map_at_1 value: 35.913000000000004
- type: map_at_10 value: 48.147
- type: map_at_100 value: 48.91
- type: map_at_1000 value: 48.949
- type: map_at_3 value: 45.269999999999996
- type: map_at_5 value: 47.115
- type: mrr_at_1 value: 35.913000000000004
- type: mrr_at_10 value: 48.147
- type: mrr_at_100 value: 48.91
- type: mrr_at_1000 value: 48.949
- type: mrr_at_3 value: 45.269999999999996
- type: mrr_at_5 value: 47.115
- type: ndcg_at_1 value: 35.913000000000004
- type: ndcg_at_10 value: 54.03
- type: ndcg_at_100 value: 57.839
- type: ndcg_at_1000 value: 58.925000000000004
- type: ndcg_at_3 value: 48.217999999999996
- type: ndcg_at_5 value: 51.56699999999999
- type: precision_at_1 value: 35.913000000000004
- type: precision_at_10 value: 7.244000000000001
- type: precision_at_100 value: 0.9039999999999999
- type: precision_at_1000 value: 0.099
- type: precision_at_3 value: 18.905
- type: precision_at_5 value: 12.981000000000002
- type: recall_at_1 value: 35.913000000000004
- type: recall_at_10 value: 72.441
- type: recall_at_100 value: 90.41799999999999
- type: recall_at_1000 value: 99.099
- type: recall_at_3 value: 56.716
- type: recall_at_5 value: 64.90599999999999
- task:
type: PairClassification
dataset:
name: MTEB OpusparcusPC (fr)
type: GEM/opusparcus
config: fr
split: test
revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
metrics:
- type: cos_sim_accuracy value: 99.90069513406156
- type: cos_sim_ap value: 100.0
- type: cos_sim_f1 value: 99.95032290114257
- type: cos_sim_precision value: 100.0
- type: cos_sim_recall value: 99.90069513406156
- type: dot_accuracy value: 99.90069513406156
- type: dot_ap value: 100.0
- type: dot_f1 value: 99.95032290114257
- type: dot_precision value: 100.0
- type: dot_recall value: 99.90069513406156
- type: euclidean_accuracy value: 99.90069513406156
- type: euclidean_ap value: 100.0
- type: euclidean_f1 value: 99.95032290114257
- type: euclidean_precision value: 100.0
- type: euclidean_recall value: 99.90069513406156
- type: manhattan_accuracy value: 99.90069513406156
- type: manhattan_ap value: 100.0
- type: manhattan_f1 value: 99.95032290114257
- type: manhattan_precision value: 100.0
- type: manhattan_recall value: 99.90069513406156
- type: max_accuracy value: 99.90069513406156
- type: max_ap value: 100.0
- type: max_f1 value: 99.95032290114257
- task:
type: PairClassification
dataset:
name: MTEB PawsX (fr)
type: paws-x
config: fr
split: test
revision: 8a04d940a42cd40658986fdd8e3da561533a3646
metrics:
- type: cos_sim_accuracy value: 75.25
- type: cos_sim_ap value: 80.86376001270014
- type: cos_sim_f1 value: 73.65945437441204
- type: cos_sim_precision value: 64.02289452166802
- type: cos_sim_recall value: 86.71096345514951
- type: dot_accuracy value: 75.25
- type: dot_ap value: 80.93686107633002
- type: dot_f1 value: 73.65945437441204
- type: dot_precision value: 64.02289452166802
- type: dot_recall value: 86.71096345514951
- type: euclidean_accuracy value: 75.25
- type: euclidean_ap value: 80.86379136218862
- type: euclidean_f1 value: 73.65945437441204
- type: euclidean_precision value: 64.02289452166802
- type: euclidean_recall value: 86.71096345514951
- type: manhattan_accuracy value: 75.3
- type: manhattan_ap value: 80.87826606097734
- type: manhattan_f1 value: 73.68421052631581
- type: manhattan_precision value: 64.0
- type: manhattan_recall value: 86.82170542635659
- type: max_accuracy value: 75.3
- type: max_ap value: 80.93686107633002
- type: max_f1 value: 73.68421052631581
- task:
type: STS
dataset:
name: MTEB SICKFr
type: Lajavaness/SICK-fr
config: default
split: test
revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a
metrics:
- type: cos_sim_pearson value: 81.42349425981143
- type: cos_sim_spearman value: 78.90454327031226
- type: euclidean_pearson value: 78.39086497435166
- type: euclidean_spearman value: 78.9046133980509
- type: manhattan_pearson value: 78.63743094286502
- type: manhattan_spearman value: 79.12136348449269
- task:
type: STS
dataset:
name: MTEB STS22 (fr)
type: mteb/sts22-crosslingual-sts
config: fr
split: test
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
metrics:
- type: cos_sim_pearson value: 81.452697919749
- type: cos_sim_spearman value: 82.58116836039301
- type: euclidean_pearson value: 81.04038478932786
- type: euclidean_spearman value: 82.58116836039301
- type: manhattan_pearson value: 81.37075396187771
- type: manhattan_spearman value: 82.73678231355368
- task:
type: STS
dataset:
name: MTEB STSBenchmarkMultilingualSTS (fr)
type: stsb_multi_mt
config: fr
split: test
revision: 93d57ef91790589e3ce9c365164337a8a78b7632
metrics:
- type: cos_sim_pearson value: 85.7419764013806
- type: cos_sim_spearman value: 85.46085808849622
- type: euclidean_pearson value: 83.70449639870063
- type: euclidean_spearman value: 85.46159013076233
- type: manhattan_pearson value: 83.95259510313929
- type: manhattan_spearman value: 85.8029724659458
- task:
type: Summarization
dataset:
name: MTEB SummEvalFr
type: lyon-nlp/summarization-summeval-fr-p2p
config: default
split: test
revision: b385812de6a9577b6f4d0f88c6a6e35395a94054
metrics:
- type: cos_sim_pearson value: 32.61063271753325
- type: cos_sim_spearman value: 31.454589417353603
- type: dot_pearson value: 32.6106288643431
- type: dot_spearman value: 31.454589417353603
- task:
type: Reranking
dataset:
name: MTEB SyntecReranking
type: lyon-nlp/mteb-fr-reranking-syntec-s2p
config: default
split: test
revision: b205c5084a0934ce8af14338bf03feb19499c84d
metrics:
- type: map value: 84.31666666666666
- type: mrr value: 84.31666666666666
- task:
type: Retrieval
dataset:
name: MTEB SyntecRetrieval
type: lyon-nlp/mteb-fr-retrieval-syntec-s2p
config: default
split: test
revision: 77f7e271bf4a92b24fce5119f3486b583ca016ff
metrics:
- type: map_at_1 value: 63.0
- type: map_at_10 value: 73.471
- type: map_at_100 value: 73.87
- type: map_at_1000 value: 73.87
- type: map_at_3 value: 70.5
- type: map_at_5 value: 73.05
- type: mrr_at_1 value: 63.0
- type: mrr_at_10 value: 73.471
- type: mrr_at_100 value: 73.87
- type: mrr_at_1000 value: 73.87
- type: mrr_at_3 value: 70.5
- type: mrr_at_5 value: 73.05
- type: ndcg_at_1 value: 63.0
- type: ndcg_at_10 value: 78.255
- type: ndcg_at_100 value: 79.88
- type: ndcg_at_1000 value: 79.88
- type: ndcg_at_3 value: 72.702
- type: ndcg_at_5 value: 77.264
- type: precision_at_1 value: 63.0
- type: precision_at_10 value: 9.3
- type: precision_at_100 value: 1.0
- type: precision_at_1000 value: 0.1
- type: precision_at_3 value: 26.333000000000002
- type: precision_at_5 value: 18.0
- type: recall_at_1 value: 63.0
- type: recall_at_10 value: 93.0
- type: recall_at_100 value: 100.0
- type: recall_at_1000 value: 100.0
- type: recall_at_3 value: 79.0
- type: recall_at_5 value: 90.0
- task:
type: Retrieval
dataset:
name: MTEB XPQARetrieval (fr)
type: jinaai/xpqa
config: fr
split: test
revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f
metrics:
- type: map_at_1 value: 40.338
- type: map_at_10 value: 61.927
- type: map_at_100 value: 63.361999999999995
- type: map_at_1000 value: 63.405
- type: map_at_3 value: 55.479
- type: map_at_5 value: 59.732
- type: mrr_at_1 value: 63.551
- type: mrr_at_10 value: 71.006
- type: mrr_at_100 value: 71.501
- type: mrr_at_1000 value: 71.509
- type: mrr_at_3 value: 69.07
- type: mrr_at_5 value: 70.165
- type: ndcg_at_1 value: 63.551
- type: ndcg_at_10 value: 68.297
- type: ndcg_at_100 value: 73.13199999999999
- type: ndcg_at_1000 value: 73.751
- type: ndcg_at_3 value: 62.999
- type: ndcg_at_5 value: 64.89
- type: precision_at_1 value: 63.551
- type: precision_at_10 value: 15.661
- type: precision_at_100 value: 1.9789999999999999
- type: precision_at_1000 value: 0.207
- type: precision_at_3 value: 38.273
- type: precision_at_5 value: 27.61
- type: recall_at_1 value: 40.338
- type: recall_at_10 value: 77.267
- type: recall_at_100 value: 95.892
- type: recall_at_1000 value: 99.75500000000001
- type: recall_at_3 value: 60.36
- type: recall_at_5 value: 68.825
- task:
type: Clustering
dataset:
name: MTEB 8TagsClustering
type: PL-MTEB/8tags-clustering
config: default
split: test
revision: None
metrics:
- type: v_measure value: 51.36126303874126
- task:
type: Classification
dataset:
name: MTEB AllegroReviews
type: PL-MTEB/allegro-reviews
config: default
split: test
revision: None
metrics:
- type: accuracy value: 67.13717693836979
- type: f1 value: 57.27609848003782
- task:
type: Retrieval
dataset:
name: MTEB ArguAna-PL
type: clarin-knext/arguana-pl
config: default
split: test
revision: 63fc86750af76253e8c760fc9e534bbf24d260a2
metrics:
- type: map_at_1 value: 35.276999999999994
- type: map_at_10 value: 51.086
- type: map_at_100 value: 51.788000000000004
- type: map_at_1000 value: 51.791
- type: map_at_3 value: 46.147
- type: map_at_5 value: 49.078
- type: mrr_at_1 value: 35.917
- type: mrr_at_10 value: 51.315999999999995
- type: mrr_at_100 value: 52.018
- type: mrr_at_1000 value: 52.022
- type: mrr_at_3 value: 46.349000000000004
- type: mrr_at_5 value: 49.297000000000004
- type: ndcg_at_1 value: 35.276999999999994
- type: ndcg_at_10 value: 59.870999999999995
- type: ndcg_at_100 value: 62.590999999999994
- type: ndcg_at_1000 value: 62.661
- type: ndcg_at_3 value: 49.745
- type: ndcg_at_5 value: 55.067
- type: precision_at_1 value: 35.276999999999994
- type: precision_at_10 value: 8.791
- type: precision_at_100 value: 0.991
- type: precision_at_1000 value: 0.1
- type: precision_at_3 value: 20.057
- type: precision_at_5 value: 14.637
- type: recall_at_1 value: 35.276999999999994
- type: recall_at_10 value: 87.909
- type: recall_at_100 value: 99.14699999999999
- type: recall_at_1000 value: 99.644
- type: recall_at_3 value: 60.171
- type: recall_at_5 value: 73.18599999999999
- task:
type: Classification
dataset:
name: MTEB CBD
type: PL-MTEB/cbd
config: default
split: test
revision: None
metrics:
- type: accuracy value: 78.03000000000002
- type: ap value: 29.12548553897622
- type: f1 value: 66.54857118886073
- task:
type: PairClassification
dataset:
name: MTEB CDSC-E
type: PL-MTEB/cdsce-pairclassification
config: default
split: test
revision: None
metrics:
- type: cos_sim_accuracy value: 89.0
- type: cos_sim_ap value: 76.75437826834582
- type: cos_sim_f1 value: 66.4850136239782
- type: cos_sim_precision value: 68.92655367231639
- type: cos_sim_recall value: 64.21052631578948
- type: dot_accuracy value: 89.0
- type: dot_ap value: 76.75437826834582
- type: dot_f1 value: 66.4850136239782
- type: dot_precision value: 68.92655367231639
- type: dot_recall value: 64.21052631578948
- type: euclidean_accuracy value: 89.0
- type: euclidean_ap value: 76.75437826834582
- type: euclidean_f1 value: 66.4850136239782
- type: euclidean_precision value: 68.92655367231639
- type: euclidean_recall value: 64.21052631578948
- type: manhattan_accuracy value: 89.0
- type: manhattan_ap value: 76.66074220647083
- type: manhattan_f1 value: 66.47058823529412
- type: manhattan_precision value: 75.33333333333333
- type: manhattan_recall value: 59.473684210526315
- type: max_accuracy value: 89.0
- type: max_ap value: 76.75437826834582
- type: max_f1 value: 66.4850136239782
- task:
type: STS
dataset:
name: MTEB CDSC-R
type: PL-MTEB/cdscr-sts
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson value: 93.12903172428328
- type: cos_sim_spearman value: 92.66381487060741
- type: euclidean_pearson value: 90.37278396708922
- type: euclidean_spearman value: 92.66381487060741
- type: manhattan_pearson value: 90.32503296540962
- type: manhattan_spearman value: 92.6902938354313
- task:
type: Retrieval
dataset:
name: MTEB DBPedia-PL
type: clarin-knext/dbpedia-pl
config: default
split: test
revision: 76afe41d9af165cc40999fcaa92312b8b012064a
metrics:
- type: map_at_1 value: 8.83
- type: map_at_10 value: 18.326
- type: map_at_100 value: 26.496
- type: map_at_1000 value: 28.455000000000002
- type: map_at_3 value: 12.933
- type: map_at_5 value: 15.168000000000001
- type: mrr_at_1 value: 66.0
- type: mrr_at_10 value: 72.76700000000001
- type: mrr_at_100 value: 73.203
- type: mrr_at_1000 value: 73.219
- type: mrr_at_3 value: 71.458
- type: mrr_at_5 value: 72.246
- type: ndcg_at_1 value: 55.375
- type: ndcg_at_10 value: 41.3
- type: ndcg_at_100 value: 45.891
- type: ndcg_at_1000 value: 52.905
- type: ndcg_at_3 value: 46.472
- type: ndcg_at_5 value: 43.734
- type: precision_at_1 value: 66.0
- type: precision_at_10 value: 33.074999999999996
- type: precision_at_100 value: 11.094999999999999
- type: precision_at_1000 value: 2.374
- type: precision_at_3 value: 48.583
- type: precision_at_5 value: 42.0
- type: recall_at_1 value: 8.83
- type: recall_at_10 value: 22.587
- type: recall_at_100 value: 50.61600000000001
- type: recall_at_1000 value: 73.559
- type: recall_at_3 value: 13.688
- type: recall_at_5 value: 16.855
- task:
type: Retrieval
dataset:
name: MTEB FiQA-PL
type: clarin-knext/fiqa-pl
config: default
split: test
revision: 2e535829717f8bf9dc829b7f911cc5bbd4e6608e
metrics:
- type: map_at_1 value: 20.587
- type: map_at_10 value: 33.095
- type: map_at_100 value: 35.24
- type: map_at_1000 value: 35.429
- type: map_at_3 value: 28.626
- type: map_at_5 value: 31.136999999999997
- type: mrr_at_1 value: 40.586
- type: mrr_at_10 value: 49.033
- type: mrr_at_100 value: 49.952999999999996
- type: mrr_at_1000 value: 49.992
- type: mrr_at_3 value: 46.553
- type: mrr_at_5 value: 48.035
- type: ndcg_at_1 value: 40.586
- type: ndcg_at_10 value: 41.046
- type: ndcg_at_100 value: 48.586
- type: ndcg_at_1000 value: 51.634
- type: ndcg_at_3 value: 36.773
- type: ndcg_at_5 value: 38.389
- type: precision_at_1 value: 40.586
- type: precision_at_10 value: 11.466
- type: precision_at_100 value: 1.909
- type: precision_at_1000 value: 0.245
- type: precision_at_3 value: 24.434
- type: precision_at_5 value: 18.426000000000002
- type: recall_at_1 value: 20.587
- type: recall_at_10 value: 47.986000000000004
- type: recall_at_100 value: 75.761
- type: recall_at_1000 value: 94.065
- type: recall_at_3 value: 33.339
- type: recall_at_5 value: 39.765
- task:
type: Retrieval
dataset:
name: MTEB HotpotQA-PL
type: clarin-knext/hotpotqa-pl
config: default
split: test
revision: a0bd479ac97b4ccb5bd6ce320c415d0bb4beb907
metrics:
- type: map_at_1 value: 40.878
- type: map_at_10 value: 58.775999999999996
- type: map_at_100 value: 59.632
- type: map_at_1000 value: 59.707
- type: map_at_3 value: 56.074
- type: map_at_5 value: 57.629
- type: mrr_at_1 value: 81.756
- type: mrr_at_10 value: 86.117
- type: mrr_at_100 value: 86.299
- type: mrr_at_1000 value: 86.30600000000001
- type: mrr_at_3 value: 85.345
- type: mrr_at_5 value: 85.832
- type: ndcg_at_1 value: 81.756
- type: ndcg_at_10 value: 67.608
- type: ndcg_at_100 value: 70.575
- type: ndcg_at_1000 value: 71.99600000000001
- type: ndcg_at_3 value: 63.723
- type: ndcg_at_5 value: 65.70700000000001
- type: precision_at_1 value: 81.756
- type: precision_at_10 value: 13.619
- type: precision_at_100 value: 1.5939999999999999
- type: precision_at_1000 value: 0.178
- type: precision_at_3 value: 39.604
- type: precision_at_5 value: 25.332
- type: recall_at_1 value: 40.878
- type: recall_at_10 value: 68.096
- type: recall_at_100 value: 79.696
- type: recall_at_1000 value: 89.082
- type: recall_at_3 value: 59.406000000000006
- type: recall_at_5 value: 63.329
- task:
type: Retrieval
dataset:
name: MTEB MSMARCO-PL
type: clarin-knext/msmarco-pl
config: default
split: test
revision: 8634c07806d5cce3a6138e260e59b81760a0a640
metrics:
- type: map_at_1 value: 2.1839999999999997
- type: map_at_10 value: 11.346
- type: map_at_100 value: 30.325000000000003
- type: map_at_1000 value: 37.806
- type: map_at_3 value: 4.842
- type: map_at_5 value: 6.891
- type: mrr_at_1 value: 86.047
- type: mrr_at_10 value: 89.14699999999999
- type: mrr_at_100 value: 89.46600000000001
- type: mrr_at_1000 value: 89.46600000000001
- type: mrr_at_3 value: 89.14699999999999
- type: mrr_at_5 value: 89.14699999999999
- type: ndcg_at_1 value: 67.829
- type: ndcg_at_10 value: 62.222
- type: ndcg_at_100 value: 55.337
- type: ndcg_at_1000 value: 64.076
- type: ndcg_at_3 value: 68.12700000000001
- type: ndcg_at_5 value: 64.987
- type: precision_at_1 value: 86.047
- type: precision_at_10 value: 69.535
- type: precision_at_100 value: 32.93
- type: precision_at_1000 value: 6.6049999999999995
- type: precision_at_3 value: 79.845
- type: precision_at_5 value: 75.349
- type: recall_at_1 value: 2.1839999999999997
- type: recall_at_10 value: 12.866
- type: recall_at_100 value: 43.505
- type: recall_at_1000 value: 72.366
- type: recall_at_3 value: 4.947
- type: recall_at_5 value: 7.192
- task:
type: Classification
dataset:
name: MTEB MassiveIntentClassification (pl)
type: mteb/amazon_massive_intent
config: pl
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 80.75319435104238
- type: f1 value: 77.58961444860606
- task:
type: Classification
dataset:
name: MTEB MassiveScenarioClassification (pl)
type: mteb/amazon_massive_scenario
config: pl
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy value: 85.54472091459313
- type: f1 value: 84.29498563572106
- task:
type: Retrieval
dataset:
name: MTEB NFCorpus-PL
type: clarin-knext/nfcorpus-pl
config: default
split: test
revision: 9a6f9567fda928260afed2de480d79c98bf0bec0
metrics:
- type: map_at_1 value: 4.367
- type: map_at_10 value: 10.38
- type: map_at_100 value: 13.516
- type: map_at_1000 value: 14.982000000000001
- type: map_at_3 value: 7.367
- type: map_at_5 value: 8.59
- type: mrr_at_1 value: 41.486000000000004
- type: mrr_at_10 value: 48.886
- type: mrr_at_100 value: 49.657000000000004
- type: mrr_at_1000 value: 49.713
- type: mrr_at_3 value: 46.904
- type: mrr_at_5 value: 48.065000000000005
- type: ndcg_at_1 value: 40.402
- type: ndcg_at_10 value: 30.885
- type: ndcg_at_100 value: 28.393
- type: ndcg_at_1000 value: 37.428
- type: ndcg_at_3 value: 35.394999999999996
- type: ndcg_at_5 value: 33.391999999999996
- type: precision_at_1 value: 41.486000000000004
- type: precision_at_10 value: 23.437
- type: precision_at_100 value: 7.638
- type: precision_at_1000 value: 2.0389999999999997
- type: precision_at_3 value: 32.817
- type: precision_at_5 value: 28.915999999999997
- type: recall_at_1 value: 4.367
- type: recall_at_10 value: 14.655000000000001
- type: recall_at_100 value: 29.665999999999997
- type: recall_at_1000 value: 62.073
- type: recall_at_3 value: 8.51
- type: recall_at_5 value: 10.689
- task:
type: Retrieval
dataset:
name: MTEB NQ-PL
type: clarin-knext/nq-pl
config: default
split: test
revision: f171245712cf85dd4700b06bef18001578d0ca8d
metrics:
- type: map_at_1 value: 28.616000000000003
- type: map_at_10 value: 41.626000000000005
- type: map_at_100 value: 42.689
- type: map_at_1000 value: 42.733
- type: map_at_3 value: 37.729
- type: map_at_5 value: 39.879999999999995
- type: mrr_at_1 value: 32.068000000000005
- type: mrr_at_10 value: 44.029
- type: mrr_at_100 value: 44.87
- type: mrr_at_1000 value: 44.901
- type: mrr_at_3 value: 40.687
- type: mrr_at_5 value: 42.625
- type: ndcg_at_1 value: 32.068000000000005
- type: ndcg_at_10 value: 48.449999999999996
- type: ndcg_at_100 value: 53.13
- type: ndcg_at_1000 value: 54.186
- type: ndcg_at_3 value: 40.983999999999995
- type: ndcg_at_5 value: 44.628
- type: precision_at_1 value: 32.068000000000005
- type: precision_at_10 value: 7.9750000000000005
- type: precision_at_100 value: 1.061
- type: precision_at_1000 value: 0.116
- type: precision_at_3 value: 18.404999999999998
- type: precision_at_5 value: 13.111
- type: recall_at_1 value: 28.616000000000003
- type: recall_at_10 value: 66.956
- type: recall_at_100 value: 87.657
- type: recall_at_1000 value: 95.548
- type: recall_at_3 value: 47.453
- type: recall_at_5 value: 55.87800000000001
- task:
type: Classification
dataset:
name: MTEB PAC
type: laugustyniak/abusive-clauses-pl
config: default
split: test
revision: None
metrics:
- type: accuracy value: 69.04141326382856
- type: ap value: 77.47589122111044
- type: f1 value: 66.6332277374775
- task:
type: PairClassification
dataset:
name: MTEB PPC
type: PL-MTEB/ppc-pairclassification
config: default
split: test
revision: None
metrics:
- type: cos_sim_accuracy value: 86.4
- type: cos_sim_ap value: 94.1044939667201
- type: cos_sim_f1 value: 88.78048780487805
- type: cos_sim_precision value: 87.22044728434504
- type: cos_sim_recall value: 90.39735099337747
- type: dot_accuracy value: 86.4
- type: dot_ap value: 94.1044939667201
- type: dot_f1 value: 88.78048780487805
- type: dot_precision value: 87.22044728434504
- type: dot_recall value: 90.39735099337747
- type: euclidean_accuracy value: 86.4
- type: euclidean_ap value: 94.1044939667201
- type: euclidean_f1 value: 88.78048780487805
- type: euclidean_precision value: 87.22044728434504
- type: euclidean_recall value: 90.39735099337747
- type: manhattan_accuracy value: 86.4
- type: manhattan_ap value: 94.11438365697387
- type: manhattan_f1 value: 88.77968877968877
- type: manhattan_precision value: 87.84440842787681
- type: manhattan_recall value: 89.73509933774835
- type: max_accuracy value: 86.4
- type: max_ap value: 94.11438365697387
- type: max_f1 value: 88.78048780487805
- task:
type: PairClassification
dataset:
name: MTEB PSC
type: PL-MTEB/psc-pairclassification
config: default
split: test
revision: None
metrics:
- type: cos_sim_accuracy value: 97.86641929499072
- type: cos_sim_ap value: 99.36904211868182
- type: cos_sim_f1 value: 96.56203288490283
- type: cos_sim_precision value: 94.72140762463343
- type: cos_sim_recall value: 98.47560975609755
- type: dot_accuracy value: 97.86641929499072
- type: dot_ap value: 99.36904211868183
- type: dot_f1 value: 96.56203288490283
- type: dot_precision value: 94.72140762463343
- type: dot_recall value: 98.47560975609755
- type: euclidean_accuracy value: 97.86641929499072
- type: euclidean_ap value: 99.36904211868183
- type: euclidean_f1 value: 96.56203288490283
- type: euclidean_precision value: 94.72140762463343
- type: euclidean_recall value: 98.47560975609755
- type: manhattan_accuracy value: 98.14471243042672
- type: manhattan_ap value: 99.43359540492416
- type: manhattan_f1 value: 96.98795180722892
- type: manhattan_precision value: 95.83333333333334
- type: manhattan_recall value: 98.17073170731707
- type: max_accuracy value: 98.14471243042672
- type: max_ap value: 99.43359540492416
- type: max_f1 value: 96.98795180722892
- task:
type: Classification
dataset:
name: MTEB PolEmo2.0-IN
type: PL-MTEB/polemo2_in
config: default
split: test
revision: None
metrics:
- type: accuracy value: 89.39058171745152
- type: f1 value: 86.8552093529568
- task:
type: Classification
dataset:
name: MTEB PolEmo2.0-OUT
type: PL-MTEB/polemo2_out
config: default
split: test
revision: None
metrics:
- type: accuracy value: 74.97975708502024
- type: f1 value: 58.73081628832407
- task:
type: Retrieval
dataset:
name: MTEB Quora-PL
type: clarin-knext/quora-pl
config: default
split: test
revision: 0be27e93455051e531182b85e85e425aba12e9d4
metrics:
- type: map_at_1 value: 64.917
- type: map_at_10 value: 78.74600000000001
- type: map_at_100 value: 79.501
- type: map_at_1000 value: 79.524
- type: map_at_3 value: 75.549
- type: map_at_5 value: 77.495
- type: mrr_at_1 value: 74.9
- type: mrr_at_10 value: 82.112
- type: mrr_at_100 value: 82.314
- type: mrr_at_1000 value: 82.317
- type: mrr_at_3 value: 80.745
- type: mrr_at_5 value: 81.607
- type: ndcg_at_1 value: 74.83999999999999
- type: ndcg_at_10 value: 83.214
- type: ndcg_at_100 value: 84.997
- type: ndcg_at_1000 value: 85.207
- type: ndcg_at_3 value: 79.547
- type: ndcg_at_5 value: 81.46600000000001
- type: precision_at_1 value: 74.83999999999999
- type: precision_at_10 value: 12.822
- type: precision_at_100 value: 1.506
- type: precision_at_1000 value: 0.156
- type: precision_at_3 value: 34.903
- type: precision_at_5 value: 23.16
- type: recall_at_1 value: 64.917
- type: recall_at_10 value: 92.27199999999999
- type: recall_at_100 value: 98.715
- type: recall_at_1000 value: 99.854
- type: recall_at_3 value: 82.04599999999999
- type: recall_at_5 value: 87.2
- task:
type: Retrieval
dataset:
name: MTEB SCIDOCS-PL
type: clarin-knext/scidocs-pl
config: default
split: test
revision: 45452b03f05560207ef19149545f168e596c9337
metrics:
- type: map_at_1 value: 3.51
- type: map_at_10 value: 9.046999999999999
- type: map_at_100 value: 10.823
- type: map_at_1000 value: 11.144
- type: map_at_3 value: 6.257
- type: map_at_5 value: 7.648000000000001
- type: mrr_at_1 value: 17.299999999999997
- type: mrr_at_10 value: 27.419
- type: mrr_at_100 value: 28.618
- type: mrr_at_1000 value: 28.685
- type: mrr_at_3 value: 23.817
- type: mrr_at_5 value: 25.927
- type: ndcg_at_1 value: 17.299999999999997
- type: ndcg_at_10 value: 16.084
- type: ndcg_at_100 value: 23.729
- type: ndcg_at_1000 value: 29.476999999999997
- type: ndcg_at_3 value: 14.327000000000002
- type: ndcg_at_5 value: 13.017999999999999
- type: precision_at_1 value: 17.299999999999997
- type: precision_at_10 value: 8.63
- type: precision_at_100 value: 1.981
- type: precision_at_1000 value: 0.336
- type: precision_at_3 value: 13.4
- type: precision_at_5 value: 11.700000000000001
- type: recall_at_1 value: 3.51
- type: recall_at_10 value: 17.518
- type: recall_at_100 value: 40.275
- type: recall_at_1000 value: 68.203
- type: recall_at_3 value: 8.155
- type: recall_at_5 value: 11.875
- task:
type: PairClassification
dataset:
name: MTEB SICK-E-PL
type: PL-MTEB/sicke-pl-pairclassification
config: default
split: test
revision: None
metrics:
- type: cos_sim_accuracy value: 86.30248675091724
- type: cos_sim_ap value: 83.6756734006714
- type: cos_sim_f1 value: 74.97367497367497
- type: cos_sim_precision value: 73.91003460207612
- type: cos_sim_recall value: 76.06837606837607
- type: dot_accuracy value: 86.30248675091724
- type: dot_ap value: 83.6756734006714
- type: dot_f1 value: 74.97367497367497
- type: dot_precision value: 73.91003460207612
- type: dot_recall value: 76.06837606837607
- type: euclidean_accuracy value: 86.30248675091724
- type: euclidean_ap value: 83.67566984333091
- type: euclidean_f1 value: 74.97367497367497
- type: euclidean_precision value: 73.91003460207612
- type: euclidean_recall value: 76.06837606837607
- type: manhattan_accuracy value: 86.28210354667753
- type: manhattan_ap value: 83.64216119130171
- type: manhattan_f1 value: 74.92152075340078
- type: manhattan_precision value: 73.4107997265892
- type: manhattan_recall value: 76.49572649572649
- type: max_accuracy value: 86.30248675091724
- type: max_ap value: 83.6756734006714
- type: max_f1 value: 74.97367497367497
- task:
type: STS
dataset:
name: MTEB SICK-R-PL
type: PL-MTEB/sickr-pl-sts
config: default
split: test
revision: None
metrics:
- type: cos_sim_pearson value: 82.23295940859121
- type: cos_sim_spearman value: 78.89329160768719
- type: euclidean_pearson value: 79.56019107076818
- type: euclidean_spearman value: 78.89330209904084
- type: manhattan_pearson value: 79.76098513973719
- type: manhattan_spearman value: 79.05490162570123
- task:
type: STS
dataset:
name: MTEB STS22 (pl)
type: mteb/sts22-crosslingual-sts
config: pl
split: test
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
metrics:
- type: cos_sim_pearson value: 37.732606308062486
- type: cos_sim_spearman value: 41.01645667030284
- type: euclidean_pearson value: 26.61722556367085
- type: euclidean_spearman value: 41.01645667030284
- type: manhattan_pearson value: 26.60917378970807
- type: manhattan_spearman value: 41.51335727617614
- task:
type: Retrieval
dataset:
name: MTEB SciFact-PL
type: clarin-knext/scifact-pl
config: default
split: test
revision: 47932a35f045ef8ed01ba82bf9ff67f6e109207e
metrics:
- type: map_at_1 value: 54.31700000000001
- type: map_at_10 value: 65.564
- type: map_at_100 value: 66.062
- type: map_at_1000 value: 66.08699999999999
- type: map_at_3 value: 62.592999999999996
- type: map_at_5 value: 63.888
- type: mrr_at_1 value: 56.99999999999999
- type: mrr_at_10 value: 66.412
- type: mrr_at_100 value: 66.85900000000001
- type: mrr_at_1000 value: 66.88
- type: mrr_at_3 value: 64.22200000000001
- type: mrr_at_5 value: 65.206
- type: ndcg_at_1 value: 56.99999999999999
- type: ndcg_at_10 value: 70.577
- type: ndcg_at_100 value: 72.879
- type: ndcg_at_1000 value: 73.45
- type: ndcg_at_3 value: 65.5
- type: ndcg_at_5 value: 67.278
- type: precision_at_1 value: 56.99999999999999
- type: precision_at_10 value: 9.667
- type: precision_at_100 value: 1.083
- type: precision_at_1000 value: 0.11299999999999999
- type: precision_at_3 value: 26.0
- type: precision_at_5 value: 16.933
- type: recall_at_1 value: 54.31700000000001
- type: recall_at_10 value: 85.056
- type: recall_at_100 value: 95.667
- type: recall_at_1000 value: 100.0
- type: recall_at_3 value: 71.0
- type: recall_at_5 value: 75.672
- task:
type: Retrieval
dataset:
name: MTEB TRECCOVID-PL
type: clarin-knext/trec-covid-pl
config: default
split: test
revision: 81bcb408f33366c2a20ac54adafad1ae7e877fdd
metrics:
- type: map_at_1 value: 0.245
- type: map_at_10 value: 2.051
- type: map_at_100 value: 12.009
- type: map_at_1000 value: 27.448
- type: map_at_3 value: 0.721
- type: map_at_5 value: 1.13
- type: mrr_at_1 value: 88.0
- type: mrr_at_10 value: 93.0
- type: mrr_at_100 value: 93.0
- type: mrr_at_1000 value: 93.0
- type: mrr_at_3 value: 93.0
- type: mrr_at_5 value: 93.0
- type: ndcg_at_1 value: 85.0
- type: ndcg_at_10 value: 80.303
- type: ndcg_at_100 value: 61.23499999999999
- type: ndcg_at_1000 value: 52.978
- type: ndcg_at_3 value: 84.419
- type: ndcg_at_5 value: 82.976
- type: precision_at_1 value: 88.0
- type: precision_at_10 value: 83.39999999999999
- type: precision_at_100 value: 61.96
- type: precision_at_1000 value: 22.648
- type: precision_at_3 value: 89.333
- type: precision_at_5 value: 87.2
- type: recall_at_1 value: 0.245
- type: recall_at_10 value: 2.193
- type: recall_at_100 value: 14.938
- type: recall_at_1000 value: 48.563
- type: recall_at_3 value: 0.738
- type: recall_at_5 value: 1.173
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: mteb/amazon_counterfactual
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
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Alibaba-NLP/gte-Qwen2-7B-instruct - GGUF
This repo contains GGUF format model files for Alibaba-NLP/gte-Qwen2-7B-instruct.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
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| A comprehensive collection of Model Context Protocol (MCP) servers. | A lightweight, open, and extensible multi-LLM interaction studio. |
| 👀 See what we built 👀 | 👀 See what we built 👀 |
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| gte-Qwen2-7B-instruct-Q2_K.gguf | Q2_K | 2.807 GB | smallest, significant quality loss - not recommended for most purposes |
| gte-Qwen2-7B-instruct-Q3_K_S.gguf | Q3_K_S | 3.251 GB | very small, high quality loss |
| gte-Qwen2-7B-instruct-Q3_K_M.gguf | Q3_K_M | 3.545 GB | very small, high quality loss |
| gte-Qwen2-7B-instruct-Q3_K_L.gguf | Q3_K_L | 3.806 GB | small, substantial quality loss |
| gte-Qwen2-7B-instruct-Q4_0.gguf | Q4_0 | 4.125 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| gte-Qwen2-7B-instruct-Q4_K_S.gguf | Q4_K_S | 4.150 GB | small, greater quality loss |
| gte-Qwen2-7B-instruct-Q4_K_M.gguf | Q4_K_M | 4.360 GB | medium, balanced quality - recommended |
| gte-Qwen2-7B-instruct-Q5_0.gguf | Q5_0 | 4.948 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| gte-Qwen2-7B-instruct-Q5_K_S.gguf | Q5_K_S | 4.948 GB | large, low quality loss - recommended |
| gte-Qwen2-7B-instruct-Q5_K_M.gguf | Q5_K_M | 5.069 GB | large, very low quality loss - recommended |
| gte-Qwen2-7B-instruct-Q6_K.gguf | Q6_K | 5.822 GB | very large, extremely low quality loss |
| gte-Qwen2-7B-instruct-Q8_0.gguf | Q8_0 | 7.539 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/gte-Qwen2-7B-instruct-GGUF --include "gte-Qwen2-7B-instruct-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:
huggingface-cli download tensorblock/gte-Qwen2-7B-instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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