|
--- |
|
tags: |
|
- mteb |
|
model-index: |
|
- name: gte_WORDLLAMA_MODEL2VEC_result |
|
results: |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
|
split: test |
|
revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 73.13432835820896 |
|
- type: ap |
|
value: 35.167459200441506 |
|
- type: f1 |
|
value: 66.74544259725131 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonPolarityClassification |
|
config: default |
|
split: test |
|
revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 71.5158 |
|
- type: ap |
|
value: 65.87290139797425 |
|
- type: f1 |
|
value: 71.31117308043078 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
|
split: test |
|
revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 37.032 |
|
- type: f1 |
|
value: 36.34554421029957 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB ArguAna |
|
config: default |
|
split: test |
|
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.541999999999998 |
|
- type: map_at_10 |
|
value: 38.172 |
|
- type: map_at_100 |
|
value: 39.339 |
|
- type: map_at_1000 |
|
value: 39.353 |
|
- type: map_at_3 |
|
value: 33.286 |
|
- type: map_at_5 |
|
value: 35.942 |
|
- type: mrr_at_1 |
|
value: 24.253 |
|
- type: mrr_at_10 |
|
value: 38.423 |
|
- type: mrr_at_100 |
|
value: 39.589 |
|
- type: mrr_at_1000 |
|
value: 39.604 |
|
- type: mrr_at_3 |
|
value: 33.559 |
|
- type: mrr_at_5 |
|
value: 36.169000000000004 |
|
- type: ndcg_at_1 |
|
value: 23.541999999999998 |
|
- type: ndcg_at_10 |
|
value: 46.660000000000004 |
|
- type: ndcg_at_100 |
|
value: 51.800999999999995 |
|
- type: ndcg_at_1000 |
|
value: 52.147 |
|
- type: ndcg_at_3 |
|
value: 36.498000000000005 |
|
- type: ndcg_at_5 |
|
value: 41.309000000000005 |
|
- type: precision_at_1 |
|
value: 23.541999999999998 |
|
- type: precision_at_10 |
|
value: 7.396999999999999 |
|
- type: precision_at_100 |
|
value: 0.9690000000000001 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 15.268 |
|
- type: precision_at_5 |
|
value: 11.508000000000001 |
|
- type: recall_at_1 |
|
value: 23.541999999999998 |
|
- type: recall_at_10 |
|
value: 73.969 |
|
- type: recall_at_100 |
|
value: 96.871 |
|
- type: recall_at_1000 |
|
value: 99.502 |
|
- type: recall_at_3 |
|
value: 45.804 |
|
- type: recall_at_5 |
|
value: 57.538999999999994 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 39.8392617925804 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 29.39147233524174 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB AskUbuntuDupQuestions |
|
config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 55.43457632808065 |
|
- type: mrr |
|
value: 69.7011168271556 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.40924171268267 |
|
- type: cos_sim_spearman |
|
value: 76.48728498335026 |
|
- type: euclidean_pearson |
|
value: 78.11322656013188 |
|
- type: euclidean_spearman |
|
value: 76.48728498335026 |
|
- type: manhattan_pearson |
|
value: 78.39882365124392 |
|
- type: manhattan_spearman |
|
value: 76.55837094044142 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 75.63311688311688 |
|
- type: f1 |
|
value: 74.89031278068427 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 34.47759744268641 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 26.72176842867392 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
|
revision: f46a197baaae43b4f621051089b82a364682dfeb |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.918000000000003 |
|
- type: map_at_10 |
|
value: 29.912 |
|
- type: map_at_100 |
|
value: 31.205 |
|
- type: map_at_1000 |
|
value: 31.357000000000003 |
|
- type: map_at_3 |
|
value: 27.206000000000003 |
|
- type: map_at_5 |
|
value: 28.613 |
|
- type: mrr_at_1 |
|
value: 27.897 |
|
- type: mrr_at_10 |
|
value: 35.921 |
|
- type: mrr_at_100 |
|
value: 36.825 |
|
- type: mrr_at_1000 |
|
value: 36.894 |
|
- type: mrr_at_3 |
|
value: 33.858 |
|
- type: mrr_at_5 |
|
value: 34.881 |
|
- type: ndcg_at_1 |
|
value: 27.897 |
|
- type: ndcg_at_10 |
|
value: 35.306 |
|
- type: ndcg_at_100 |
|
value: 40.955999999999996 |
|
- type: ndcg_at_1000 |
|
value: 43.909 |
|
- type: ndcg_at_3 |
|
value: 31.422 |
|
- type: ndcg_at_5 |
|
value: 32.89 |
|
- type: precision_at_1 |
|
value: 27.897 |
|
- type: precision_at_10 |
|
value: 6.9239999999999995 |
|
- type: precision_at_100 |
|
value: 1.233 |
|
- type: precision_at_1000 |
|
value: 0.18 |
|
- type: precision_at_3 |
|
value: 15.451 |
|
- type: precision_at_5 |
|
value: 11.044 |
|
- type: recall_at_1 |
|
value: 21.918000000000003 |
|
- type: recall_at_10 |
|
value: 45.171 |
|
- type: recall_at_100 |
|
value: 70.226 |
|
- type: recall_at_1000 |
|
value: 90.279 |
|
- type: recall_at_3 |
|
value: 32.657000000000004 |
|
- type: recall_at_5 |
|
value: 37.372 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.456 |
|
- type: map_at_10 |
|
value: 26.596999999999998 |
|
- type: map_at_100 |
|
value: 27.639999999999997 |
|
- type: map_at_1000 |
|
value: 27.766000000000002 |
|
- type: map_at_3 |
|
value: 24.487000000000002 |
|
- type: map_at_5 |
|
value: 25.683 |
|
- type: mrr_at_1 |
|
value: 25.605 |
|
- type: mrr_at_10 |
|
value: 31.326999999999998 |
|
- type: mrr_at_100 |
|
value: 32.133 |
|
- type: mrr_at_1000 |
|
value: 32.198 |
|
- type: mrr_at_3 |
|
value: 29.310000000000002 |
|
- type: mrr_at_5 |
|
value: 30.431 |
|
- type: ndcg_at_1 |
|
value: 25.605 |
|
- type: ndcg_at_10 |
|
value: 30.728 |
|
- type: ndcg_at_100 |
|
value: 35.318 |
|
- type: ndcg_at_1000 |
|
value: 38.082 |
|
- type: ndcg_at_3 |
|
value: 27.226 |
|
- type: ndcg_at_5 |
|
value: 28.828 |
|
- type: precision_at_1 |
|
value: 25.605 |
|
- type: precision_at_10 |
|
value: 5.561 |
|
- type: precision_at_100 |
|
value: 1.001 |
|
- type: precision_at_1000 |
|
value: 0.15 |
|
- type: precision_at_3 |
|
value: 12.717999999999998 |
|
- type: precision_at_5 |
|
value: 9.134 |
|
- type: recall_at_1 |
|
value: 20.456 |
|
- type: recall_at_10 |
|
value: 38.476 |
|
- type: recall_at_100 |
|
value: 58.120000000000005 |
|
- type: recall_at_1000 |
|
value: 76.793 |
|
- type: recall_at_3 |
|
value: 28.232000000000003 |
|
- type: recall_at_5 |
|
value: 32.53 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
metrics: |
|
- type: map_at_1 |
|
value: 28.088 |
|
- type: map_at_10 |
|
value: 37.584 |
|
- type: map_at_100 |
|
value: 38.75 |
|
- type: map_at_1000 |
|
value: 38.842999999999996 |
|
- type: map_at_3 |
|
value: 34.839999999999996 |
|
- type: map_at_5 |
|
value: 36.352000000000004 |
|
- type: mrr_at_1 |
|
value: 32.476 |
|
- type: mrr_at_10 |
|
value: 40.892 |
|
- type: mrr_at_100 |
|
value: 41.792 |
|
- type: mrr_at_1000 |
|
value: 41.845 |
|
- type: mrr_at_3 |
|
value: 38.474000000000004 |
|
- type: mrr_at_5 |
|
value: 39.818999999999996 |
|
- type: ndcg_at_1 |
|
value: 32.476 |
|
- type: ndcg_at_10 |
|
value: 42.811 |
|
- type: ndcg_at_100 |
|
value: 48.045 |
|
- type: ndcg_at_1000 |
|
value: 50.09400000000001 |
|
- type: ndcg_at_3 |
|
value: 37.830000000000005 |
|
- type: ndcg_at_5 |
|
value: 40.168 |
|
- type: precision_at_1 |
|
value: 32.476 |
|
- type: precision_at_10 |
|
value: 7.034 |
|
- type: precision_at_100 |
|
value: 1.061 |
|
- type: precision_at_1000 |
|
value: 0.131 |
|
- type: precision_at_3 |
|
value: 16.949 |
|
- type: precision_at_5 |
|
value: 11.799 |
|
- type: recall_at_1 |
|
value: 28.088 |
|
- type: recall_at_10 |
|
value: 55.318 |
|
- type: recall_at_100 |
|
value: 78.66499999999999 |
|
- type: recall_at_1000 |
|
value: 93.415 |
|
- type: recall_at_3 |
|
value: 41.865 |
|
- type: recall_at_5 |
|
value: 47.675 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: 5003b3064772da1887988e05400cf3806fe491f2 |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.13 |
|
- type: map_at_10 |
|
value: 18.506 |
|
- type: map_at_100 |
|
value: 19.405 |
|
- type: map_at_1000 |
|
value: 19.516 |
|
- type: map_at_3 |
|
value: 16.821 |
|
- type: map_at_5 |
|
value: 17.782 |
|
- type: mrr_at_1 |
|
value: 14.124 |
|
- type: mrr_at_10 |
|
value: 19.767000000000003 |
|
- type: mrr_at_100 |
|
value: 20.66 |
|
- type: mrr_at_1000 |
|
value: 20.755000000000003 |
|
- type: mrr_at_3 |
|
value: 18.023 |
|
- type: mrr_at_5 |
|
value: 19.0 |
|
- type: ndcg_at_1 |
|
value: 14.124 |
|
- type: ndcg_at_10 |
|
value: 21.728 |
|
- type: ndcg_at_100 |
|
value: 26.422 |
|
- type: ndcg_at_1000 |
|
value: 29.73 |
|
- type: ndcg_at_3 |
|
value: 18.312 |
|
- type: ndcg_at_5 |
|
value: 19.993 |
|
- type: precision_at_1 |
|
value: 14.124 |
|
- type: precision_at_10 |
|
value: 3.4459999999999997 |
|
- type: precision_at_100 |
|
value: 0.617 |
|
- type: precision_at_1000 |
|
value: 0.095 |
|
- type: precision_at_3 |
|
value: 7.91 |
|
- type: precision_at_5 |
|
value: 5.695 |
|
- type: recall_at_1 |
|
value: 13.13 |
|
- type: recall_at_10 |
|
value: 30.470000000000002 |
|
- type: recall_at_100 |
|
value: 52.449 |
|
- type: recall_at_1000 |
|
value: 78.25 |
|
- type: recall_at_3 |
|
value: 21.209 |
|
- type: recall_at_5 |
|
value: 25.281 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.7 |
|
- type: map_at_10 |
|
value: 12.333 |
|
- type: map_at_100 |
|
value: 13.367999999999999 |
|
- type: map_at_1000 |
|
value: 13.492 |
|
- type: map_at_3 |
|
value: 10.747 |
|
- type: map_at_5 |
|
value: 11.645999999999999 |
|
- type: mrr_at_1 |
|
value: 9.826 |
|
- type: mrr_at_10 |
|
value: 14.81 |
|
- type: mrr_at_100 |
|
value: 15.854 |
|
- type: mrr_at_1000 |
|
value: 15.953000000000001 |
|
- type: mrr_at_3 |
|
value: 13.039000000000001 |
|
- type: mrr_at_5 |
|
value: 14.046 |
|
- type: ndcg_at_1 |
|
value: 9.826 |
|
- type: ndcg_at_10 |
|
value: 15.437000000000001 |
|
- type: ndcg_at_100 |
|
value: 21.009 |
|
- type: ndcg_at_1000 |
|
value: 24.515 |
|
- type: ndcg_at_3 |
|
value: 12.349 |
|
- type: ndcg_at_5 |
|
value: 13.850000000000001 |
|
- type: precision_at_1 |
|
value: 9.826 |
|
- type: precision_at_10 |
|
value: 3.01 |
|
- type: precision_at_100 |
|
value: 0.692 |
|
- type: precision_at_1000 |
|
value: 0.11199999999999999 |
|
- type: precision_at_3 |
|
value: 6.053 |
|
- type: precision_at_5 |
|
value: 4.577 |
|
- type: recall_at_1 |
|
value: 7.7 |
|
- type: recall_at_10 |
|
value: 22.546 |
|
- type: recall_at_100 |
|
value: 47.648 |
|
- type: recall_at_1000 |
|
value: 73.655 |
|
- type: recall_at_3 |
|
value: 14.289 |
|
- type: recall_at_5 |
|
value: 17.994 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 19.886 |
|
- type: map_at_10 |
|
value: 26.63 |
|
- type: map_at_100 |
|
value: 27.944999999999997 |
|
- type: map_at_1000 |
|
value: 28.097 |
|
- type: map_at_3 |
|
value: 24.077 |
|
- type: map_at_5 |
|
value: 25.378 |
|
- type: mrr_at_1 |
|
value: 24.254 |
|
- type: mrr_at_10 |
|
value: 31.416 |
|
- type: mrr_at_100 |
|
value: 32.425 |
|
- type: mrr_at_1000 |
|
value: 32.501999999999995 |
|
- type: mrr_at_3 |
|
value: 28.793999999999997 |
|
- type: mrr_at_5 |
|
value: 30.237000000000002 |
|
- type: ndcg_at_1 |
|
value: 24.254 |
|
- type: ndcg_at_10 |
|
value: 31.524 |
|
- type: ndcg_at_100 |
|
value: 37.658 |
|
- type: ndcg_at_1000 |
|
value: 40.722 |
|
- type: ndcg_at_3 |
|
value: 26.953 |
|
- type: ndcg_at_5 |
|
value: 28.919 |
|
- type: precision_at_1 |
|
value: 24.254 |
|
- type: precision_at_10 |
|
value: 5.881 |
|
- type: precision_at_100 |
|
value: 1.072 |
|
- type: precision_at_1000 |
|
value: 0.155 |
|
- type: precision_at_3 |
|
value: 12.479999999999999 |
|
- type: precision_at_5 |
|
value: 9.105 |
|
- type: recall_at_1 |
|
value: 19.886 |
|
- type: recall_at_10 |
|
value: 41.593 |
|
- type: recall_at_100 |
|
value: 68.43599999999999 |
|
- type: recall_at_1000 |
|
value: 89.041 |
|
- type: recall_at_3 |
|
value: 28.723 |
|
- type: recall_at_5 |
|
value: 33.804 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
|
metrics: |
|
- type: map_at_1 |
|
value: 15.821 |
|
- type: map_at_10 |
|
value: 21.898999999999997 |
|
- type: map_at_100 |
|
value: 23.189 |
|
- type: map_at_1000 |
|
value: 23.323 |
|
- type: map_at_3 |
|
value: 19.634999999999998 |
|
- type: map_at_5 |
|
value: 20.848 |
|
- type: mrr_at_1 |
|
value: 19.064 |
|
- type: mrr_at_10 |
|
value: 25.784000000000002 |
|
- type: mrr_at_100 |
|
value: 26.828999999999997 |
|
- type: mrr_at_1000 |
|
value: 26.904 |
|
- type: mrr_at_3 |
|
value: 23.573 |
|
- type: mrr_at_5 |
|
value: 24.812 |
|
- type: ndcg_at_1 |
|
value: 19.064 |
|
- type: ndcg_at_10 |
|
value: 26.229999999999997 |
|
- type: ndcg_at_100 |
|
value: 32.326 |
|
- type: ndcg_at_1000 |
|
value: 35.435 |
|
- type: ndcg_at_3 |
|
value: 22.070999999999998 |
|
- type: ndcg_at_5 |
|
value: 23.93 |
|
- type: precision_at_1 |
|
value: 19.064 |
|
- type: precision_at_10 |
|
value: 4.966 |
|
- type: precision_at_100 |
|
value: 0.967 |
|
- type: precision_at_1000 |
|
value: 0.14100000000000001 |
|
- type: precision_at_3 |
|
value: 10.54 |
|
- type: precision_at_5 |
|
value: 7.785 |
|
- type: recall_at_1 |
|
value: 15.821 |
|
- type: recall_at_10 |
|
value: 35.516 |
|
- type: recall_at_100 |
|
value: 61.971 |
|
- type: recall_at_1000 |
|
value: 83.848 |
|
- type: recall_at_3 |
|
value: 23.97 |
|
- type: recall_at_5 |
|
value: 28.662 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
|
metrics: |
|
- type: map_at_1 |
|
value: 15.921916666666666 |
|
- type: map_at_10 |
|
value: 21.780166666666666 |
|
- type: map_at_100 |
|
value: 22.84433333333333 |
|
- type: map_at_1000 |
|
value: 22.975916666666667 |
|
- type: map_at_3 |
|
value: 19.735916666666665 |
|
- type: map_at_5 |
|
value: 20.860416666666666 |
|
- type: mrr_at_1 |
|
value: 19.054249999999996 |
|
- type: mrr_at_10 |
|
value: 25.021333333333335 |
|
- type: mrr_at_100 |
|
value: 25.93491666666667 |
|
- type: mrr_at_1000 |
|
value: 26.019166666666667 |
|
- type: mrr_at_3 |
|
value: 23.03583333333333 |
|
- type: mrr_at_5 |
|
value: 24.140000000000004 |
|
- type: ndcg_at_1 |
|
value: 19.054249999999996 |
|
- type: ndcg_at_10 |
|
value: 25.70233333333334 |
|
- type: ndcg_at_100 |
|
value: 30.890500000000003 |
|
- type: ndcg_at_1000 |
|
value: 34.02575 |
|
- type: ndcg_at_3 |
|
value: 22.017666666666663 |
|
- type: ndcg_at_5 |
|
value: 23.718666666666664 |
|
- type: precision_at_1 |
|
value: 19.054249999999996 |
|
- type: precision_at_10 |
|
value: 4.622083333333333 |
|
- type: precision_at_100 |
|
value: 0.86825 |
|
- type: precision_at_1000 |
|
value: 0.13258333333333333 |
|
- type: precision_at_3 |
|
value: 10.176166666666669 |
|
- type: precision_at_5 |
|
value: 7.382749999999999 |
|
- type: recall_at_1 |
|
value: 15.921916666666666 |
|
- type: recall_at_10 |
|
value: 34.314833333333326 |
|
- type: recall_at_100 |
|
value: 57.83341666666667 |
|
- type: recall_at_1000 |
|
value: 80.45625000000001 |
|
- type: recall_at_3 |
|
value: 23.967166666666667 |
|
- type: recall_at_5 |
|
value: 28.36841666666666 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
|
metrics: |
|
- type: map_at_1 |
|
value: 12.857 |
|
- type: map_at_10 |
|
value: 17.826 |
|
- type: map_at_100 |
|
value: 18.677 |
|
- type: map_at_1000 |
|
value: 18.775 |
|
- type: map_at_3 |
|
value: 16.227 |
|
- type: map_at_5 |
|
value: 17.168 |
|
- type: mrr_at_1 |
|
value: 14.877 |
|
- type: mrr_at_10 |
|
value: 19.784 |
|
- type: mrr_at_100 |
|
value: 20.662 |
|
- type: mrr_at_1000 |
|
value: 20.746000000000002 |
|
- type: mrr_at_3 |
|
value: 18.175 |
|
- type: mrr_at_5 |
|
value: 19.08 |
|
- type: ndcg_at_1 |
|
value: 14.877 |
|
- type: ndcg_at_10 |
|
value: 20.987000000000002 |
|
- type: ndcg_at_100 |
|
value: 25.654 |
|
- type: ndcg_at_1000 |
|
value: 28.360000000000003 |
|
- type: ndcg_at_3 |
|
value: 17.919 |
|
- type: ndcg_at_5 |
|
value: 19.404 |
|
- type: precision_at_1 |
|
value: 14.877 |
|
- type: precision_at_10 |
|
value: 3.528 |
|
- type: precision_at_100 |
|
value: 0.641 |
|
- type: precision_at_1000 |
|
value: 0.095 |
|
- type: precision_at_3 |
|
value: 8.129 |
|
- type: precision_at_5 |
|
value: 5.798 |
|
- type: recall_at_1 |
|
value: 12.857 |
|
- type: recall_at_10 |
|
value: 28.864 |
|
- type: recall_at_100 |
|
value: 50.943000000000005 |
|
- type: recall_at_1000 |
|
value: 71.158 |
|
- type: recall_at_3 |
|
value: 20.330000000000002 |
|
- type: recall_at_5 |
|
value: 24.03 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: 46989137a86843e03a6195de44b09deda022eec7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.823 |
|
- type: map_at_10 |
|
value: 12.664 |
|
- type: map_at_100 |
|
value: 13.447000000000001 |
|
- type: map_at_1000 |
|
value: 13.58 |
|
- type: map_at_3 |
|
value: 11.372 |
|
- type: map_at_5 |
|
value: 12.052 |
|
- type: mrr_at_1 |
|
value: 10.84 |
|
- type: mrr_at_10 |
|
value: 15.135000000000002 |
|
- type: mrr_at_100 |
|
value: 15.919 |
|
- type: mrr_at_1000 |
|
value: 16.026 |
|
- type: mrr_at_3 |
|
value: 13.702 |
|
- type: mrr_at_5 |
|
value: 14.496 |
|
- type: ndcg_at_1 |
|
value: 10.84 |
|
- type: ndcg_at_10 |
|
value: 15.375 |
|
- type: ndcg_at_100 |
|
value: 19.612 |
|
- type: ndcg_at_1000 |
|
value: 23.305 |
|
- type: ndcg_at_3 |
|
value: 12.879999999999999 |
|
- type: ndcg_at_5 |
|
value: 13.980999999999998 |
|
- type: precision_at_1 |
|
value: 10.84 |
|
- type: precision_at_10 |
|
value: 2.887 |
|
- type: precision_at_100 |
|
value: 0.599 |
|
- type: precision_at_1000 |
|
value: 0.109 |
|
- type: precision_at_3 |
|
value: 6.171 |
|
- type: precision_at_5 |
|
value: 4.522 |
|
- type: recall_at_1 |
|
value: 8.823 |
|
- type: recall_at_10 |
|
value: 21.19 |
|
- type: recall_at_100 |
|
value: 40.843 |
|
- type: recall_at_1000 |
|
value: 68.118 |
|
- type: recall_at_3 |
|
value: 14.219000000000001 |
|
- type: recall_at_5 |
|
value: 17.061 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.841999999999999 |
|
- type: map_at_10 |
|
value: 19.807 |
|
- type: map_at_100 |
|
value: 20.646 |
|
- type: map_at_1000 |
|
value: 20.782 |
|
- type: map_at_3 |
|
value: 17.881 |
|
- type: map_at_5 |
|
value: 18.94 |
|
- type: mrr_at_1 |
|
value: 17.631 |
|
- type: mrr_at_10 |
|
value: 22.949 |
|
- type: mrr_at_100 |
|
value: 23.727 |
|
- type: mrr_at_1000 |
|
value: 23.829 |
|
- type: mrr_at_3 |
|
value: 20.896 |
|
- type: mrr_at_5 |
|
value: 21.964 |
|
- type: ndcg_at_1 |
|
value: 17.631 |
|
- type: ndcg_at_10 |
|
value: 23.544999999999998 |
|
- type: ndcg_at_100 |
|
value: 28.042 |
|
- type: ndcg_at_1000 |
|
value: 31.66 |
|
- type: ndcg_at_3 |
|
value: 19.697 |
|
- type: ndcg_at_5 |
|
value: 21.467 |
|
- type: precision_at_1 |
|
value: 17.631 |
|
- type: precision_at_10 |
|
value: 4.039000000000001 |
|
- type: precision_at_100 |
|
value: 0.7080000000000001 |
|
- type: precision_at_1000 |
|
value: 0.11399999999999999 |
|
- type: precision_at_3 |
|
value: 8.831 |
|
- type: precision_at_5 |
|
value: 6.381 |
|
- type: recall_at_1 |
|
value: 14.841999999999999 |
|
- type: recall_at_10 |
|
value: 32.144 |
|
- type: recall_at_100 |
|
value: 52.896 |
|
- type: recall_at_1000 |
|
value: 79.3 |
|
- type: recall_at_3 |
|
value: 21.64 |
|
- type: recall_at_5 |
|
value: 26.127 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
|
metrics: |
|
- type: map_at_1 |
|
value: 15.182 |
|
- type: map_at_10 |
|
value: 21.423000000000002 |
|
- type: map_at_100 |
|
value: 22.766000000000002 |
|
- type: map_at_1000 |
|
value: 22.966 |
|
- type: map_at_3 |
|
value: 19.096 |
|
- type: map_at_5 |
|
value: 20.514 |
|
- type: mrr_at_1 |
|
value: 18.379 |
|
- type: mrr_at_10 |
|
value: 24.834999999999997 |
|
- type: mrr_at_100 |
|
value: 25.818 |
|
- type: mrr_at_1000 |
|
value: 25.893 |
|
- type: mrr_at_3 |
|
value: 22.628 |
|
- type: mrr_at_5 |
|
value: 24.032 |
|
- type: ndcg_at_1 |
|
value: 18.379 |
|
- type: ndcg_at_10 |
|
value: 25.766 |
|
- type: ndcg_at_100 |
|
value: 31.677 |
|
- type: ndcg_at_1000 |
|
value: 35.024 |
|
- type: ndcg_at_3 |
|
value: 22.027 |
|
- type: ndcg_at_5 |
|
value: 24.046 |
|
- type: precision_at_1 |
|
value: 18.379 |
|
- type: precision_at_10 |
|
value: 5.158 |
|
- type: precision_at_100 |
|
value: 1.2309999999999999 |
|
- type: precision_at_1000 |
|
value: 0.211 |
|
- type: precision_at_3 |
|
value: 10.474 |
|
- type: precision_at_5 |
|
value: 7.983999999999999 |
|
- type: recall_at_1 |
|
value: 15.182 |
|
- type: recall_at_10 |
|
value: 34.008 |
|
- type: recall_at_100 |
|
value: 61.882000000000005 |
|
- type: recall_at_1000 |
|
value: 84.635 |
|
- type: recall_at_3 |
|
value: 23.3 |
|
- type: recall_at_5 |
|
value: 28.732999999999997 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 12.36 |
|
- type: map_at_10 |
|
value: 16.181 |
|
- type: map_at_100 |
|
value: 17.094 |
|
- type: map_at_1000 |
|
value: 17.214 |
|
- type: map_at_3 |
|
value: 14.442 |
|
- type: map_at_5 |
|
value: 15.348999999999998 |
|
- type: mrr_at_1 |
|
value: 13.678 |
|
- type: mrr_at_10 |
|
value: 17.636 |
|
- type: mrr_at_100 |
|
value: 18.575 |
|
- type: mrr_at_1000 |
|
value: 18.685 |
|
- type: mrr_at_3 |
|
value: 15.958 |
|
- type: mrr_at_5 |
|
value: 16.882 |
|
- type: ndcg_at_1 |
|
value: 13.678 |
|
- type: ndcg_at_10 |
|
value: 18.991 |
|
- type: ndcg_at_100 |
|
value: 23.967 |
|
- type: ndcg_at_1000 |
|
value: 27.473 |
|
- type: ndcg_at_3 |
|
value: 15.526000000000002 |
|
- type: ndcg_at_5 |
|
value: 17.148 |
|
- type: precision_at_1 |
|
value: 13.678 |
|
- type: precision_at_10 |
|
value: 3.031 |
|
- type: precision_at_100 |
|
value: 0.597 |
|
- type: precision_at_1000 |
|
value: 0.098 |
|
- type: precision_at_3 |
|
value: 6.4079999999999995 |
|
- type: precision_at_5 |
|
value: 4.769 |
|
- type: recall_at_1 |
|
value: 12.36 |
|
- type: recall_at_10 |
|
value: 26.482 |
|
- type: recall_at_100 |
|
value: 49.922 |
|
- type: recall_at_1000 |
|
value: 76.983 |
|
- type: recall_at_3 |
|
value: 17.172 |
|
- type: recall_at_5 |
|
value: 21.152 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.464 |
|
- type: map_at_10 |
|
value: 14.78 |
|
- type: map_at_100 |
|
value: 16.436999999999998 |
|
- type: map_at_1000 |
|
value: 16.650000000000002 |
|
- type: map_at_3 |
|
value: 12.027000000000001 |
|
- type: map_at_5 |
|
value: 13.428999999999998 |
|
- type: mrr_at_1 |
|
value: 19.544 |
|
- type: mrr_at_10 |
|
value: 29.537999999999997 |
|
- type: mrr_at_100 |
|
value: 30.653000000000002 |
|
- type: mrr_at_1000 |
|
value: 30.708000000000002 |
|
- type: mrr_at_3 |
|
value: 25.798 |
|
- type: mrr_at_5 |
|
value: 28.072000000000003 |
|
- type: ndcg_at_1 |
|
value: 19.544 |
|
- type: ndcg_at_10 |
|
value: 21.953 |
|
- type: ndcg_at_100 |
|
value: 29.188 |
|
- type: ndcg_at_1000 |
|
value: 33.222 |
|
- type: ndcg_at_3 |
|
value: 16.89 |
|
- type: ndcg_at_5 |
|
value: 18.825 |
|
- type: precision_at_1 |
|
value: 19.544 |
|
- type: precision_at_10 |
|
value: 7.277 |
|
- type: precision_at_100 |
|
value: 1.506 |
|
- type: precision_at_1000 |
|
value: 0.22399999999999998 |
|
- type: precision_at_3 |
|
value: 12.834000000000001 |
|
- type: precision_at_5 |
|
value: 10.488999999999999 |
|
- type: recall_at_1 |
|
value: 8.464 |
|
- type: recall_at_10 |
|
value: 27.762999999999998 |
|
- type: recall_at_100 |
|
value: 53.147999999999996 |
|
- type: recall_at_1000 |
|
value: 76.183 |
|
- type: recall_at_3 |
|
value: 15.642 |
|
- type: recall_at_5 |
|
value: 20.593 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.676 |
|
- type: map_at_10 |
|
value: 11.847000000000001 |
|
- type: map_at_100 |
|
value: 16.875999999999998 |
|
- type: map_at_1000 |
|
value: 18.081 |
|
- type: map_at_3 |
|
value: 8.512 |
|
- type: map_at_5 |
|
value: 9.956 |
|
- type: mrr_at_1 |
|
value: 48.0 |
|
- type: mrr_at_10 |
|
value: 57.928000000000004 |
|
- type: mrr_at_100 |
|
value: 58.52 |
|
- type: mrr_at_1000 |
|
value: 58.544 |
|
- type: mrr_at_3 |
|
value: 55.333 |
|
- type: mrr_at_5 |
|
value: 56.958 |
|
- type: ndcg_at_1 |
|
value: 35.875 |
|
- type: ndcg_at_10 |
|
value: 27.221 |
|
- type: ndcg_at_100 |
|
value: 31.808999999999997 |
|
- type: ndcg_at_1000 |
|
value: 39.199 |
|
- type: ndcg_at_3 |
|
value: 30.274 |
|
- type: ndcg_at_5 |
|
value: 28.785 |
|
- type: precision_at_1 |
|
value: 48.0 |
|
- type: precision_at_10 |
|
value: 23.65 |
|
- type: precision_at_100 |
|
value: 7.818 |
|
- type: precision_at_1000 |
|
value: 1.651 |
|
- type: precision_at_3 |
|
value: 35.833 |
|
- type: precision_at_5 |
|
value: 31.0 |
|
- type: recall_at_1 |
|
value: 5.676 |
|
- type: recall_at_10 |
|
value: 16.619 |
|
- type: recall_at_100 |
|
value: 39.422000000000004 |
|
- type: recall_at_1000 |
|
value: 64.095 |
|
- type: recall_at_3 |
|
value: 9.608 |
|
- type: recall_at_5 |
|
value: 12.277000000000001 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 49.185 |
|
- type: f1 |
|
value: 44.87033813298503 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.904 |
|
- type: map_at_10 |
|
value: 28.435 |
|
- type: map_at_100 |
|
value: 29.498 |
|
- type: map_at_1000 |
|
value: 29.567 |
|
- type: map_at_3 |
|
value: 25.319000000000003 |
|
- type: map_at_5 |
|
value: 27.13 |
|
- type: mrr_at_1 |
|
value: 20.116999999999997 |
|
- type: mrr_at_10 |
|
value: 30.112 |
|
- type: mrr_at_100 |
|
value: 31.155 |
|
- type: mrr_at_1000 |
|
value: 31.213 |
|
- type: mrr_at_3 |
|
value: 26.895000000000003 |
|
- type: mrr_at_5 |
|
value: 28.793000000000003 |
|
- type: ndcg_at_1 |
|
value: 20.116999999999997 |
|
- type: ndcg_at_10 |
|
value: 34.244 |
|
- type: ndcg_at_100 |
|
value: 39.409 |
|
- type: ndcg_at_1000 |
|
value: 41.195 |
|
- type: ndcg_at_3 |
|
value: 27.872000000000003 |
|
- type: ndcg_at_5 |
|
value: 31.128 |
|
- type: precision_at_1 |
|
value: 20.116999999999997 |
|
- type: precision_at_10 |
|
value: 5.534 |
|
- type: precision_at_100 |
|
value: 0.828 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 12.076 |
|
- type: precision_at_5 |
|
value: 8.965 |
|
- type: recall_at_1 |
|
value: 18.904 |
|
- type: recall_at_10 |
|
value: 50.858000000000004 |
|
- type: recall_at_100 |
|
value: 74.42 |
|
- type: recall_at_1000 |
|
value: 88.023 |
|
- type: recall_at_3 |
|
value: 33.675 |
|
- type: recall_at_5 |
|
value: 41.449999999999996 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.892 |
|
- type: map_at_10 |
|
value: 14.363000000000001 |
|
- type: map_at_100 |
|
value: 15.75 |
|
- type: map_at_1000 |
|
value: 15.959000000000001 |
|
- type: map_at_3 |
|
value: 12.25 |
|
- type: map_at_5 |
|
value: 13.286999999999999 |
|
- type: mrr_at_1 |
|
value: 16.821 |
|
- type: mrr_at_10 |
|
value: 23.425 |
|
- type: mrr_at_100 |
|
value: 24.556 |
|
- type: mrr_at_1000 |
|
value: 24.637 |
|
- type: mrr_at_3 |
|
value: 20.885 |
|
- type: mrr_at_5 |
|
value: 22.127 |
|
- type: ndcg_at_1 |
|
value: 16.821 |
|
- type: ndcg_at_10 |
|
value: 19.412 |
|
- type: ndcg_at_100 |
|
value: 25.836 |
|
- type: ndcg_at_1000 |
|
value: 30.131000000000004 |
|
- type: ndcg_at_3 |
|
value: 16.198 |
|
- type: ndcg_at_5 |
|
value: 17.185 |
|
- type: precision_at_1 |
|
value: 16.821 |
|
- type: precision_at_10 |
|
value: 5.556 |
|
- type: precision_at_100 |
|
value: 1.1820000000000002 |
|
- type: precision_at_1000 |
|
value: 0.194 |
|
- type: precision_at_3 |
|
value: 10.545 |
|
- type: precision_at_5 |
|
value: 8.056000000000001 |
|
- type: recall_at_1 |
|
value: 8.892 |
|
- type: recall_at_10 |
|
value: 25.249 |
|
- type: recall_at_100 |
|
value: 50.263000000000005 |
|
- type: recall_at_1000 |
|
value: 76.43299999999999 |
|
- type: recall_at_3 |
|
value: 15.094 |
|
- type: recall_at_5 |
|
value: 18.673000000000002 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.831 |
|
- type: map_at_10 |
|
value: 29.959999999999997 |
|
- type: map_at_100 |
|
value: 30.959999999999997 |
|
- type: map_at_1000 |
|
value: 31.069000000000003 |
|
- type: map_at_3 |
|
value: 27.453 |
|
- type: map_at_5 |
|
value: 28.838 |
|
- type: mrr_at_1 |
|
value: 41.661 |
|
- type: mrr_at_10 |
|
value: 49.647999999999996 |
|
- type: mrr_at_100 |
|
value: 50.304 |
|
- type: mrr_at_1000 |
|
value: 50.352 |
|
- type: mrr_at_3 |
|
value: 47.403 |
|
- type: mrr_at_5 |
|
value: 48.657000000000004 |
|
- type: ndcg_at_1 |
|
value: 41.661 |
|
- type: ndcg_at_10 |
|
value: 37.854 |
|
- type: ndcg_at_100 |
|
value: 42.248999999999995 |
|
- type: ndcg_at_1000 |
|
value: 44.756 |
|
- type: ndcg_at_3 |
|
value: 33.243 |
|
- type: ndcg_at_5 |
|
value: 35.467 |
|
- type: precision_at_1 |
|
value: 41.661 |
|
- type: precision_at_10 |
|
value: 8.386000000000001 |
|
- type: precision_at_100 |
|
value: 1.1900000000000002 |
|
- type: precision_at_1000 |
|
value: 0.152 |
|
- type: precision_at_3 |
|
value: 21.022 |
|
- type: precision_at_5 |
|
value: 14.377 |
|
- type: recall_at_1 |
|
value: 20.831 |
|
- type: recall_at_10 |
|
value: 41.931000000000004 |
|
- type: recall_at_100 |
|
value: 59.507 |
|
- type: recall_at_1000 |
|
value: 76.232 |
|
- type: recall_at_3 |
|
value: 31.533 |
|
- type: recall_at_5 |
|
value: 35.942 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 70.2136 |
|
- type: ap |
|
value: 64.38274263735502 |
|
- type: f1 |
|
value: 70.02577813394484 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB MSMARCO |
|
config: default |
|
split: dev |
|
revision: c5a29a104738b98a9e76336939199e264163d4a0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.542999999999999 |
|
- type: map_at_10 |
|
value: 13.229 |
|
- type: map_at_100 |
|
value: 14.283999999999999 |
|
- type: map_at_1000 |
|
value: 14.396 |
|
- type: map_at_3 |
|
value: 11.139000000000001 |
|
- type: map_at_5 |
|
value: 12.259 |
|
- type: mrr_at_1 |
|
value: 7.808 |
|
- type: mrr_at_10 |
|
value: 13.577 |
|
- type: mrr_at_100 |
|
value: 14.625 |
|
- type: mrr_at_1000 |
|
value: 14.732000000000001 |
|
- type: mrr_at_3 |
|
value: 11.464 |
|
- type: mrr_at_5 |
|
value: 12.584999999999999 |
|
- type: ndcg_at_1 |
|
value: 7.779 |
|
- type: ndcg_at_10 |
|
value: 16.793 |
|
- type: ndcg_at_100 |
|
value: 22.564 |
|
- type: ndcg_at_1000 |
|
value: 25.799 |
|
- type: ndcg_at_3 |
|
value: 12.431000000000001 |
|
- type: ndcg_at_5 |
|
value: 14.442 |
|
- type: precision_at_1 |
|
value: 7.779 |
|
- type: precision_at_10 |
|
value: 2.894 |
|
- type: precision_at_100 |
|
value: 0.59 |
|
- type: precision_at_1000 |
|
value: 0.087 |
|
- type: precision_at_3 |
|
value: 5.454 |
|
- type: precision_at_5 |
|
value: 4.278 |
|
- type: recall_at_1 |
|
value: 7.542999999999999 |
|
- type: recall_at_10 |
|
value: 27.907 |
|
- type: recall_at_100 |
|
value: 56.13399999999999 |
|
- type: recall_at_1000 |
|
value: 81.877 |
|
- type: recall_at_3 |
|
value: 15.878999999999998 |
|
- type: recall_at_5 |
|
value: 20.726 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 91.68490652074783 |
|
- type: f1 |
|
value: 90.90009716586837 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 61.33150934792522 |
|
- type: f1 |
|
value: 42.414995407585955 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 66.29455279085406 |
|
- type: f1 |
|
value: 64.0154454215856 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 73.91055817081372 |
|
- type: f1 |
|
value: 72.79505573377739 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 30.478611587568 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 27.395691978780366 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 30.75504868917307 |
|
- type: mrr |
|
value: 31.723412508217553 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.739 |
|
- type: map_at_10 |
|
value: 9.419 |
|
- type: map_at_100 |
|
value: 12.209 |
|
- type: map_at_1000 |
|
value: 13.653 |
|
- type: map_at_3 |
|
value: 7.292999999999999 |
|
- type: map_at_5 |
|
value: 8.291 |
|
- type: mrr_at_1 |
|
value: 38.7 |
|
- type: mrr_at_10 |
|
value: 47.934 |
|
- type: mrr_at_100 |
|
value: 48.605 |
|
- type: mrr_at_1000 |
|
value: 48.646 |
|
- type: mrr_at_3 |
|
value: 45.717 |
|
- type: mrr_at_5 |
|
value: 47.157 |
|
- type: ndcg_at_1 |
|
value: 36.842000000000006 |
|
- type: ndcg_at_10 |
|
value: 28.077 |
|
- type: ndcg_at_100 |
|
value: 26.83 |
|
- type: ndcg_at_1000 |
|
value: 36.272 |
|
- type: ndcg_at_3 |
|
value: 32.429 |
|
- type: ndcg_at_5 |
|
value: 30.823 |
|
- type: precision_at_1 |
|
value: 38.7 |
|
- type: precision_at_10 |
|
value: 20.774 |
|
- type: precision_at_100 |
|
value: 7.331 |
|
- type: precision_at_1000 |
|
value: 2.085 |
|
- type: precision_at_3 |
|
value: 30.341 |
|
- type: precision_at_5 |
|
value: 26.502 |
|
- type: recall_at_1 |
|
value: 4.739 |
|
- type: recall_at_10 |
|
value: 13.065999999999999 |
|
- type: recall_at_100 |
|
value: 28.875 |
|
- type: recall_at_1000 |
|
value: 62.751000000000005 |
|
- type: recall_at_3 |
|
value: 8.338 |
|
- type: recall_at_5 |
|
value: 10.211 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.764 |
|
- type: map_at_10 |
|
value: 18.582 |
|
- type: map_at_100 |
|
value: 19.953000000000003 |
|
- type: map_at_1000 |
|
value: 20.049 |
|
- type: map_at_3 |
|
value: 15.551 |
|
- type: map_at_5 |
|
value: 17.143 |
|
- type: mrr_at_1 |
|
value: 12.283 |
|
- type: mrr_at_10 |
|
value: 20.507 |
|
- type: mrr_at_100 |
|
value: 21.724 |
|
- type: mrr_at_1000 |
|
value: 21.801000000000002 |
|
- type: mrr_at_3 |
|
value: 17.434 |
|
- type: mrr_at_5 |
|
value: 19.097 |
|
- type: ndcg_at_1 |
|
value: 12.254 |
|
- type: ndcg_at_10 |
|
value: 23.818 |
|
- type: ndcg_at_100 |
|
value: 30.652 |
|
- type: ndcg_at_1000 |
|
value: 33.25 |
|
- type: ndcg_at_3 |
|
value: 17.577 |
|
- type: ndcg_at_5 |
|
value: 20.43 |
|
- type: precision_at_1 |
|
value: 12.254 |
|
- type: precision_at_10 |
|
value: 4.492999999999999 |
|
- type: precision_at_100 |
|
value: 0.8370000000000001 |
|
- type: precision_at_1000 |
|
value: 0.109 |
|
- type: precision_at_3 |
|
value: 8.333 |
|
- type: precision_at_5 |
|
value: 6.593 |
|
- type: recall_at_1 |
|
value: 10.764 |
|
- type: recall_at_10 |
|
value: 38.279999999999994 |
|
- type: recall_at_100 |
|
value: 69.77600000000001 |
|
- type: recall_at_1000 |
|
value: 89.75 |
|
- type: recall_at_3 |
|
value: 21.608 |
|
- type: recall_at_5 |
|
value: 28.247 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 66.238 |
|
- type: map_at_10 |
|
value: 79.61 |
|
- type: map_at_100 |
|
value: 80.339 |
|
- type: map_at_1000 |
|
value: 80.366 |
|
- type: map_at_3 |
|
value: 76.572 |
|
- type: map_at_5 |
|
value: 78.45100000000001 |
|
- type: mrr_at_1 |
|
value: 76.18 |
|
- type: mrr_at_10 |
|
value: 83.319 |
|
- type: mrr_at_100 |
|
value: 83.492 |
|
- type: mrr_at_1000 |
|
value: 83.49499999999999 |
|
- type: mrr_at_3 |
|
value: 82.002 |
|
- type: mrr_at_5 |
|
value: 82.88 |
|
- type: ndcg_at_1 |
|
value: 76.24 |
|
- type: ndcg_at_10 |
|
value: 84.048 |
|
- type: ndcg_at_100 |
|
value: 85.76700000000001 |
|
- type: ndcg_at_1000 |
|
value: 85.989 |
|
- type: ndcg_at_3 |
|
value: 80.608 |
|
- type: ndcg_at_5 |
|
value: 82.45 |
|
- type: precision_at_1 |
|
value: 76.24 |
|
- type: precision_at_10 |
|
value: 12.775 |
|
- type: precision_at_100 |
|
value: 1.498 |
|
- type: precision_at_1000 |
|
value: 0.156 |
|
- type: precision_at_3 |
|
value: 35.107 |
|
- type: precision_at_5 |
|
value: 23.198 |
|
- type: recall_at_1 |
|
value: 66.238 |
|
- type: recall_at_10 |
|
value: 92.655 |
|
- type: recall_at_100 |
|
value: 98.79599999999999 |
|
- type: recall_at_1000 |
|
value: 99.914 |
|
- type: recall_at_3 |
|
value: 82.818 |
|
- type: recall_at_5 |
|
value: 87.985 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 45.96790773164943 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 51.114201492992976 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 3.3029999999999995 |
|
- type: map_at_10 |
|
value: 8.534 |
|
- type: map_at_100 |
|
value: 10.269 |
|
- type: map_at_1000 |
|
value: 10.569 |
|
- type: map_at_3 |
|
value: 6.02 |
|
- type: map_at_5 |
|
value: 7.3 |
|
- type: mrr_at_1 |
|
value: 16.2 |
|
- type: mrr_at_10 |
|
value: 26.048 |
|
- type: mrr_at_100 |
|
value: 27.229 |
|
- type: mrr_at_1000 |
|
value: 27.307 |
|
- type: mrr_at_3 |
|
value: 22.8 |
|
- type: mrr_at_5 |
|
value: 24.555 |
|
- type: ndcg_at_1 |
|
value: 16.2 |
|
- type: ndcg_at_10 |
|
value: 15.152 |
|
- type: ndcg_at_100 |
|
value: 22.692999999999998 |
|
- type: ndcg_at_1000 |
|
value: 28.283 |
|
- type: ndcg_at_3 |
|
value: 13.831 |
|
- type: ndcg_at_5 |
|
value: 12.383 |
|
- type: precision_at_1 |
|
value: 16.2 |
|
- type: precision_at_10 |
|
value: 8.15 |
|
- type: precision_at_100 |
|
value: 1.921 |
|
- type: precision_at_1000 |
|
value: 0.326 |
|
- type: precision_at_3 |
|
value: 13.167000000000002 |
|
- type: precision_at_5 |
|
value: 11.200000000000001 |
|
- type: recall_at_1 |
|
value: 3.3029999999999995 |
|
- type: recall_at_10 |
|
value: 16.463 |
|
- type: recall_at_100 |
|
value: 38.968 |
|
- type: recall_at_1000 |
|
value: 66.208 |
|
- type: recall_at_3 |
|
value: 8.023 |
|
- type: recall_at_5 |
|
value: 11.338 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 78.21858054391086 |
|
- type: cos_sim_spearman |
|
value: 67.3365618536054 |
|
- type: euclidean_pearson |
|
value: 72.40963340986721 |
|
- type: euclidean_spearman |
|
value: 67.336666949735 |
|
- type: manhattan_pearson |
|
value: 72.14690674984998 |
|
- type: manhattan_spearman |
|
value: 67.32922820760339 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 76.49003508454533 |
|
- type: cos_sim_spearman |
|
value: 66.84152843358724 |
|
- type: euclidean_pearson |
|
value: 72.00905568823764 |
|
- type: euclidean_spearman |
|
value: 66.8427445518875 |
|
- type: manhattan_pearson |
|
value: 71.33279968302561 |
|
- type: manhattan_spearman |
|
value: 66.63248621937453 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 78.26330596241046 |
|
- type: cos_sim_spearman |
|
value: 78.99008985666835 |
|
- type: euclidean_pearson |
|
value: 78.51141445278363 |
|
- type: euclidean_spearman |
|
value: 78.99010203692151 |
|
- type: manhattan_pearson |
|
value: 78.06877144241578 |
|
- type: manhattan_spearman |
|
value: 78.49232451344044 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.14106714330973 |
|
- type: cos_sim_spearman |
|
value: 74.82820560037015 |
|
- type: euclidean_pearson |
|
value: 77.62758758774916 |
|
- type: euclidean_spearman |
|
value: 74.82819590900333 |
|
- type: manhattan_pearson |
|
value: 77.48877257108047 |
|
- type: manhattan_spearman |
|
value: 74.74789870583966 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.48914773660643 |
|
- type: cos_sim_spearman |
|
value: 83.00065347429336 |
|
- type: euclidean_pearson |
|
value: 82.64658342996727 |
|
- type: euclidean_spearman |
|
value: 83.00065194339217 |
|
- type: manhattan_pearson |
|
value: 82.55463149184536 |
|
- type: manhattan_spearman |
|
value: 82.8911825343332 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.784876359328 |
|
- type: cos_sim_spearman |
|
value: 78.360543979936 |
|
- type: euclidean_pearson |
|
value: 77.73937696752135 |
|
- type: euclidean_spearman |
|
value: 78.36053665222538 |
|
- type: manhattan_pearson |
|
value: 77.56126269274264 |
|
- type: manhattan_spearman |
|
value: 78.18717393504727 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS17 (en-en) |
|
config: en-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.63171981287952 |
|
- type: cos_sim_spearman |
|
value: 87.49687143000429 |
|
- type: euclidean_pearson |
|
value: 86.37853734517222 |
|
- type: euclidean_spearman |
|
value: 87.4977435828658 |
|
- type: manhattan_pearson |
|
value: 86.40342805532555 |
|
- type: manhattan_spearman |
|
value: 87.57812091712806 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS22 (en) |
|
config: en |
|
split: test |
|
revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 60.00736823914696 |
|
- type: cos_sim_spearman |
|
value: 60.59580774316736 |
|
- type: euclidean_pearson |
|
value: 61.893600849213094 |
|
- type: euclidean_spearman |
|
value: 60.59580774316736 |
|
- type: manhattan_pearson |
|
value: 61.43013801720455 |
|
- type: manhattan_spearman |
|
value: 59.92526461879062 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 80.58292387813594 |
|
- type: cos_sim_spearman |
|
value: 78.85975762418589 |
|
- type: euclidean_pearson |
|
value: 80.28122335716425 |
|
- type: euclidean_spearman |
|
value: 78.85977608876506 |
|
- type: manhattan_pearson |
|
value: 80.20419882971093 |
|
- type: manhattan_spearman |
|
value: 78.79811621332709 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 78.54383068715617 |
|
- type: mrr |
|
value: 93.62365031482678 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 39.111000000000004 |
|
- type: map_at_10 |
|
value: 47.686 |
|
- type: map_at_100 |
|
value: 48.722 |
|
- type: map_at_1000 |
|
value: 48.776 |
|
- type: map_at_3 |
|
value: 44.625 |
|
- type: map_at_5 |
|
value: 46.289 |
|
- type: mrr_at_1 |
|
value: 41.667 |
|
- type: mrr_at_10 |
|
value: 49.619 |
|
- type: mrr_at_100 |
|
value: 50.434 |
|
- type: mrr_at_1000 |
|
value: 50.482000000000006 |
|
- type: mrr_at_3 |
|
value: 46.833000000000006 |
|
- type: mrr_at_5 |
|
value: 48.317 |
|
- type: ndcg_at_1 |
|
value: 41.667 |
|
- type: ndcg_at_10 |
|
value: 52.819 |
|
- type: ndcg_at_100 |
|
value: 57.69 |
|
- type: ndcg_at_1000 |
|
value: 58.965 |
|
- type: ndcg_at_3 |
|
value: 46.857 |
|
- type: ndcg_at_5 |
|
value: 49.697 |
|
- type: precision_at_1 |
|
value: 41.667 |
|
- type: precision_at_10 |
|
value: 7.367 |
|
- type: precision_at_100 |
|
value: 1.0070000000000001 |
|
- type: precision_at_1000 |
|
value: 0.11199999999999999 |
|
- type: precision_at_3 |
|
value: 18.333 |
|
- type: precision_at_5 |
|
value: 12.6 |
|
- type: recall_at_1 |
|
value: 39.111000000000004 |
|
- type: recall_at_10 |
|
value: 67.039 |
|
- type: recall_at_100 |
|
value: 89.767 |
|
- type: recall_at_1000 |
|
value: 99.467 |
|
- type: recall_at_3 |
|
value: 51.056000000000004 |
|
- type: recall_at_5 |
|
value: 57.99999999999999 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.72772277227723 |
|
- type: cos_sim_ap |
|
value: 91.98542118937158 |
|
- type: cos_sim_f1 |
|
value: 85.91691995947316 |
|
- type: cos_sim_precision |
|
value: 87.06365503080082 |
|
- type: cos_sim_recall |
|
value: 84.8 |
|
- type: dot_accuracy |
|
value: 99.72772277227723 |
|
- type: dot_ap |
|
value: 91.98542118937158 |
|
- type: dot_f1 |
|
value: 85.91691995947316 |
|
- type: dot_precision |
|
value: 87.06365503080082 |
|
- type: dot_recall |
|
value: 84.8 |
|
- type: euclidean_accuracy |
|
value: 99.72772277227723 |
|
- type: euclidean_ap |
|
value: 91.98542118937158 |
|
- type: euclidean_f1 |
|
value: 85.91691995947316 |
|
- type: euclidean_precision |
|
value: 87.06365503080082 |
|
- type: euclidean_recall |
|
value: 84.8 |
|
- type: manhattan_accuracy |
|
value: 99.72574257425742 |
|
- type: manhattan_ap |
|
value: 91.96773898408213 |
|
- type: manhattan_f1 |
|
value: 85.8601327207759 |
|
- type: manhattan_precision |
|
value: 87.69551616266945 |
|
- type: manhattan_recall |
|
value: 84.1 |
|
- type: max_accuracy |
|
value: 99.72772277227723 |
|
- type: max_ap |
|
value: 91.98542118937158 |
|
- type: max_f1 |
|
value: 85.91691995947316 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 50.974351388709024 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 30.94724711190474 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 43.618618519378074 |
|
- type: mrr |
|
value: 44.19061942959002 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: None |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 29.75942900919329 |
|
- type: cos_sim_spearman |
|
value: 30.265779375382486 |
|
- type: dot_pearson |
|
value: 29.759429009193283 |
|
- type: dot_spearman |
|
value: 30.216316271647514 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.154 |
|
- type: map_at_10 |
|
value: 1.216 |
|
- type: map_at_100 |
|
value: 6.401 |
|
- type: map_at_1000 |
|
value: 16.882 |
|
- type: map_at_3 |
|
value: 0.418 |
|
- type: map_at_5 |
|
value: 0.7040000000000001 |
|
- type: mrr_at_1 |
|
value: 62.0 |
|
- type: mrr_at_10 |
|
value: 75.319 |
|
- type: mrr_at_100 |
|
value: 75.435 |
|
- type: mrr_at_1000 |
|
value: 75.435 |
|
- type: mrr_at_3 |
|
value: 73.333 |
|
- type: mrr_at_5 |
|
value: 75.033 |
|
- type: ndcg_at_1 |
|
value: 56.00000000000001 |
|
- type: ndcg_at_10 |
|
value: 54.176 |
|
- type: ndcg_at_100 |
|
value: 40.741 |
|
- type: ndcg_at_1000 |
|
value: 38.385000000000005 |
|
- type: ndcg_at_3 |
|
value: 57.676 |
|
- type: ndcg_at_5 |
|
value: 57.867000000000004 |
|
- type: precision_at_1 |
|
value: 62.0 |
|
- type: precision_at_10 |
|
value: 57.8 |
|
- type: precision_at_100 |
|
value: 42.68 |
|
- type: precision_at_1000 |
|
value: 18.478 |
|
- type: precision_at_3 |
|
value: 61.333000000000006 |
|
- type: precision_at_5 |
|
value: 63.6 |
|
- type: recall_at_1 |
|
value: 0.154 |
|
- type: recall_at_10 |
|
value: 1.468 |
|
- type: recall_at_100 |
|
value: 9.541 |
|
- type: recall_at_1000 |
|
value: 37.218 |
|
- type: recall_at_3 |
|
value: 0.46299999999999997 |
|
- type: recall_at_5 |
|
value: 0.8340000000000001 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.144 |
|
- type: map_at_10 |
|
value: 8.38 |
|
- type: map_at_100 |
|
value: 14.482000000000001 |
|
- type: map_at_1000 |
|
value: 16.179 |
|
- type: map_at_3 |
|
value: 3.821 |
|
- type: map_at_5 |
|
value: 5.96 |
|
- type: mrr_at_1 |
|
value: 26.531 |
|
- type: mrr_at_10 |
|
value: 41.501 |
|
- type: mrr_at_100 |
|
value: 42.575 |
|
- type: mrr_at_1000 |
|
value: 42.575 |
|
- type: mrr_at_3 |
|
value: 36.054 |
|
- type: mrr_at_5 |
|
value: 40.238 |
|
- type: ndcg_at_1 |
|
value: 21.429000000000002 |
|
- type: ndcg_at_10 |
|
value: 21.644 |
|
- type: ndcg_at_100 |
|
value: 35.427 |
|
- type: ndcg_at_1000 |
|
value: 47.116 |
|
- type: ndcg_at_3 |
|
value: 20.814 |
|
- type: ndcg_at_5 |
|
value: 22.783 |
|
- type: precision_at_1 |
|
value: 26.531 |
|
- type: precision_at_10 |
|
value: 21.224 |
|
- type: precision_at_100 |
|
value: 8.265 |
|
- type: precision_at_1000 |
|
value: 1.5959999999999999 |
|
- type: precision_at_3 |
|
value: 23.810000000000002 |
|
- type: precision_at_5 |
|
value: 26.122 |
|
- type: recall_at_1 |
|
value: 2.144 |
|
- type: recall_at_10 |
|
value: 15.278 |
|
- type: recall_at_100 |
|
value: 50.541000000000004 |
|
- type: recall_at_1000 |
|
value: 86.144 |
|
- type: recall_at_3 |
|
value: 5.056 |
|
- type: recall_at_5 |
|
value: 9.203 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 75.88100000000001 |
|
- type: ap |
|
value: 17.210410808772743 |
|
- type: f1 |
|
value: 58.7851360197636 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 59.68024900962084 |
|
- type: f1 |
|
value: 59.95386992880734 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 41.55446050017461 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 82.32699529117244 |
|
- type: cos_sim_ap |
|
value: 61.49148139881723 |
|
- type: cos_sim_f1 |
|
value: 59.31940298507462 |
|
- type: cos_sim_precision |
|
value: 54.17666303162486 |
|
- type: cos_sim_recall |
|
value: 65.54089709762533 |
|
- type: dot_accuracy |
|
value: 82.32699529117244 |
|
- type: dot_ap |
|
value: 61.49148139881723 |
|
- type: dot_f1 |
|
value: 59.31940298507462 |
|
- type: dot_precision |
|
value: 54.17666303162486 |
|
- type: dot_recall |
|
value: 65.54089709762533 |
|
- type: euclidean_accuracy |
|
value: 82.32699529117244 |
|
- type: euclidean_ap |
|
value: 61.49148139881723 |
|
- type: euclidean_f1 |
|
value: 59.31940298507462 |
|
- type: euclidean_precision |
|
value: 54.17666303162486 |
|
- type: euclidean_recall |
|
value: 65.54089709762533 |
|
- type: manhattan_accuracy |
|
value: 82.44024557429815 |
|
- type: manhattan_ap |
|
value: 61.57050440663527 |
|
- type: manhattan_f1 |
|
value: 59.36456916800594 |
|
- type: manhattan_precision |
|
value: 55.8501977204001 |
|
- type: manhattan_recall |
|
value: 63.35092348284961 |
|
- type: max_accuracy |
|
value: 82.44024557429815 |
|
- type: max_ap |
|
value: 61.57050440663527 |
|
- type: max_f1 |
|
value: 59.36456916800594 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 87.70714479760935 |
|
- type: cos_sim_ap |
|
value: 83.52059059692118 |
|
- type: cos_sim_f1 |
|
value: 75.8043805261034 |
|
- type: cos_sim_precision |
|
value: 72.40171000070083 |
|
- type: cos_sim_recall |
|
value: 79.54265475823837 |
|
- type: dot_accuracy |
|
value: 87.70714479760935 |
|
- type: dot_ap |
|
value: 83.52059016767844 |
|
- type: dot_f1 |
|
value: 75.8043805261034 |
|
- type: dot_precision |
|
value: 72.40171000070083 |
|
- type: dot_recall |
|
value: 79.54265475823837 |
|
- type: euclidean_accuracy |
|
value: 87.70714479760935 |
|
- type: euclidean_ap |
|
value: 83.52059046795347 |
|
- type: euclidean_f1 |
|
value: 75.8043805261034 |
|
- type: euclidean_precision |
|
value: 72.40171000070083 |
|
- type: euclidean_recall |
|
value: 79.54265475823837 |
|
- type: manhattan_accuracy |
|
value: 87.7187875965382 |
|
- type: manhattan_ap |
|
value: 83.5377383098018 |
|
- type: manhattan_f1 |
|
value: 75.87021520062012 |
|
- type: manhattan_precision |
|
value: 72.87102035028008 |
|
- type: manhattan_recall |
|
value: 79.12688635663689 |
|
- type: max_accuracy |
|
value: 87.7187875965382 |
|
- type: max_ap |
|
value: 83.5377383098018 |
|
- type: max_f1 |
|
value: 75.87021520062012 |
|
--- |
