|
--- |
|
tags: |
|
- mteb |
|
model-index: |
|
- name: l3_wordllama_256 |
|
results: |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
|
split: test |
|
revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 65.97014925373134 |
|
- type: ap |
|
value: 27.33017285839569 |
|
- type: f1 |
|
value: 59.04330619047924 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonPolarityClassification |
|
config: default |
|
split: test |
|
revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 63.248250000000006 |
|
- type: ap |
|
value: 58.695642654646576 |
|
- type: f1 |
|
value: 62.98826255412888 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
|
split: test |
|
revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 31.689999999999998 |
|
- type: f1 |
|
value: 31.106666192619258 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB ArguAna |
|
config: default |
|
split: test |
|
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
|
metrics: |
|
- type: map_at_1 |
|
value: 19.986 |
|
- type: map_at_10 |
|
value: 34.634 |
|
- type: map_at_100 |
|
value: 35.937000000000005 |
|
- type: map_at_1000 |
|
value: 35.954 |
|
- type: map_at_3 |
|
value: 29.742 |
|
- type: map_at_5 |
|
value: 32.444 |
|
- type: mrr_at_1 |
|
value: 20.341 |
|
- type: mrr_at_10 |
|
value: 34.763 |
|
- type: mrr_at_100 |
|
value: 36.065999999999995 |
|
- type: mrr_at_1000 |
|
value: 36.083 |
|
- type: mrr_at_3 |
|
value: 29.872 |
|
- type: mrr_at_5 |
|
value: 32.574999999999996 |
|
- type: ndcg_at_1 |
|
value: 19.986 |
|
- type: ndcg_at_10 |
|
value: 43.074 |
|
- type: ndcg_at_100 |
|
value: 48.819 |
|
- type: ndcg_at_1000 |
|
value: 49.26 |
|
- type: ndcg_at_3 |
|
value: 32.934000000000005 |
|
- type: ndcg_at_5 |
|
value: 37.830999999999996 |
|
- type: precision_at_1 |
|
value: 19.986 |
|
- type: precision_at_10 |
|
value: 7.02 |
|
- type: precision_at_100 |
|
value: 0.958 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 14.059 |
|
- type: precision_at_5 |
|
value: 10.825 |
|
- type: recall_at_1 |
|
value: 19.986 |
|
- type: recall_at_10 |
|
value: 70.199 |
|
- type: recall_at_100 |
|
value: 95.804 |
|
- type: recall_at_1000 |
|
value: 99.21799999999999 |
|
- type: recall_at_3 |
|
value: 42.176 |
|
- type: recall_at_5 |
|
value: 54.125 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 39.64176717184799 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 29.06122250673383 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB AskUbuntuDupQuestions |
|
config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 55.808484614132844 |
|
- type: mrr |
|
value: 71.09121487930351 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 74.96889982129713 |
|
- type: cos_sim_spearman |
|
value: 70.34256665852179 |
|
- type: euclidean_pearson |
|
value: 73.59375229907496 |
|
- type: euclidean_spearman |
|
value: 70.34256665852179 |
|
- type: manhattan_pearson |
|
value: 72.38820178677287 |
|
- type: manhattan_spearman |
|
value: 69.3919425882689 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 73.56818181818181 |
|
- type: f1 |
|
value: 72.78107232170503 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 33.10380086081637 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 25.238238325966222 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
|
revision: f46a197baaae43b4f621051089b82a364682dfeb |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.294999999999998 |
|
- type: map_at_10 |
|
value: 27.535999999999998 |
|
- type: map_at_100 |
|
value: 28.803 |
|
- type: map_at_1000 |
|
value: 28.971000000000004 |
|
- type: map_at_3 |
|
value: 25.029 |
|
- type: map_at_5 |
|
value: 26.526 |
|
- type: mrr_at_1 |
|
value: 24.893 |
|
- type: mrr_at_10 |
|
value: 32.554 |
|
- type: mrr_at_100 |
|
value: 33.504 |
|
- type: mrr_at_1000 |
|
value: 33.583 |
|
- type: mrr_at_3 |
|
value: 30.091 |
|
- type: mrr_at_5 |
|
value: 31.535999999999998 |
|
- type: ndcg_at_1 |
|
value: 24.893 |
|
- type: ndcg_at_10 |
|
value: 32.495000000000005 |
|
- type: ndcg_at_100 |
|
value: 38.288 |
|
- type: ndcg_at_1000 |
|
value: 41.559000000000005 |
|
- type: ndcg_at_3 |
|
value: 28.321 |
|
- type: ndcg_at_5 |
|
value: 30.401 |
|
- type: precision_at_1 |
|
value: 24.893 |
|
- type: precision_at_10 |
|
value: 6.109 |
|
- type: precision_at_100 |
|
value: 1.142 |
|
- type: precision_at_1000 |
|
value: 0.179 |
|
- type: precision_at_3 |
|
value: 13.447999999999999 |
|
- type: precision_at_5 |
|
value: 9.927999999999999 |
|
- type: recall_at_1 |
|
value: 20.294999999999998 |
|
- type: recall_at_10 |
|
value: 42.129 |
|
- type: recall_at_100 |
|
value: 67.709 |
|
- type: recall_at_1000 |
|
value: 89.534 |
|
- type: recall_at_3 |
|
value: 30.148999999999997 |
|
- type: recall_at_5 |
|
value: 35.804 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 16.426 |
|
- type: map_at_10 |
|
value: 22.461000000000002 |
|
- type: map_at_100 |
|
value: 23.424 |
|
- type: map_at_1000 |
|
value: 23.559 |
|
- type: map_at_3 |
|
value: 20.643 |
|
- type: map_at_5 |
|
value: 21.602 |
|
- type: mrr_at_1 |
|
value: 20.701 |
|
- type: mrr_at_10 |
|
value: 26.734 |
|
- type: mrr_at_100 |
|
value: 27.516000000000002 |
|
- type: mrr_at_1000 |
|
value: 27.594 |
|
- type: mrr_at_3 |
|
value: 24.936 |
|
- type: mrr_at_5 |
|
value: 25.901000000000003 |
|
- type: ndcg_at_1 |
|
value: 20.701 |
|
- type: ndcg_at_10 |
|
value: 26.381 |
|
- type: ndcg_at_100 |
|
value: 30.731 |
|
- type: ndcg_at_1000 |
|
value: 33.603 |
|
- type: ndcg_at_3 |
|
value: 23.336000000000002 |
|
- type: ndcg_at_5 |
|
value: 24.644 |
|
- type: precision_at_1 |
|
value: 20.701 |
|
- type: precision_at_10 |
|
value: 5.006 |
|
- type: precision_at_100 |
|
value: 0.9339999999999999 |
|
- type: precision_at_1000 |
|
value: 0.14200000000000002 |
|
- type: precision_at_3 |
|
value: 11.315999999999999 |
|
- type: precision_at_5 |
|
value: 8.14 |
|
- type: recall_at_1 |
|
value: 16.426 |
|
- type: recall_at_10 |
|
value: 33.593 |
|
- type: recall_at_100 |
|
value: 52.746 |
|
- type: recall_at_1000 |
|
value: 72.15899999999999 |
|
- type: recall_at_3 |
|
value: 24.712 |
|
- type: recall_at_5 |
|
value: 28.233000000000004 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.46 |
|
- type: map_at_10 |
|
value: 33.292 |
|
- type: map_at_100 |
|
value: 34.437 |
|
- type: map_at_1000 |
|
value: 34.534 |
|
- type: map_at_3 |
|
value: 30.567 |
|
- type: map_at_5 |
|
value: 32.202 |
|
- type: mrr_at_1 |
|
value: 28.276 |
|
- type: mrr_at_10 |
|
value: 36.235 |
|
- type: mrr_at_100 |
|
value: 37.173 |
|
- type: mrr_at_1000 |
|
value: 37.234 |
|
- type: mrr_at_3 |
|
value: 33.783 |
|
- type: mrr_at_5 |
|
value: 35.237 |
|
- type: ndcg_at_1 |
|
value: 28.276 |
|
- type: ndcg_at_10 |
|
value: 38.202000000000005 |
|
- type: ndcg_at_100 |
|
value: 43.634 |
|
- type: ndcg_at_1000 |
|
value: 45.894 |
|
- type: ndcg_at_3 |
|
value: 33.19 |
|
- type: ndcg_at_5 |
|
value: 35.798 |
|
- type: precision_at_1 |
|
value: 28.276 |
|
- type: precision_at_10 |
|
value: 6.332 |
|
- type: precision_at_100 |
|
value: 1.008 |
|
- type: precision_at_1000 |
|
value: 0.127 |
|
- type: precision_at_3 |
|
value: 14.671000000000001 |
|
- type: precision_at_5 |
|
value: 10.571 |
|
- type: recall_at_1 |
|
value: 24.46 |
|
- type: recall_at_10 |
|
value: 50.156 |
|
- type: recall_at_100 |
|
value: 74.648 |
|
- type: recall_at_1000 |
|
value: 91.269 |
|
- type: recall_at_3 |
|
value: 36.937999999999995 |
|
- type: recall_at_5 |
|
value: 43.15 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: 5003b3064772da1887988e05400cf3806fe491f2 |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.052999999999999 |
|
- type: map_at_10 |
|
value: 18.287 |
|
- type: map_at_100 |
|
value: 19.137 |
|
- type: map_at_1000 |
|
value: 19.258 |
|
- type: map_at_3 |
|
value: 16.79 |
|
- type: map_at_5 |
|
value: 17.618000000000002 |
|
- type: mrr_at_1 |
|
value: 15.254000000000001 |
|
- type: mrr_at_10 |
|
value: 19.88 |
|
- type: mrr_at_100 |
|
value: 20.71 |
|
- type: mrr_at_1000 |
|
value: 20.812 |
|
- type: mrr_at_3 |
|
value: 18.23 |
|
- type: mrr_at_5 |
|
value: 19.185 |
|
- type: ndcg_at_1 |
|
value: 15.254000000000001 |
|
- type: ndcg_at_10 |
|
value: 21.183 |
|
- type: ndcg_at_100 |
|
value: 25.972 |
|
- type: ndcg_at_1000 |
|
value: 29.271 |
|
- type: ndcg_at_3 |
|
value: 18.046 |
|
- type: ndcg_at_5 |
|
value: 19.570999999999998 |
|
- type: precision_at_1 |
|
value: 15.254000000000001 |
|
- type: precision_at_10 |
|
value: 3.288 |
|
- type: precision_at_100 |
|
value: 0.614 |
|
- type: precision_at_1000 |
|
value: 0.094 |
|
- type: precision_at_3 |
|
value: 7.5329999999999995 |
|
- type: precision_at_5 |
|
value: 5.379 |
|
- type: recall_at_1 |
|
value: 14.052999999999999 |
|
- type: recall_at_10 |
|
value: 28.599999999999998 |
|
- type: recall_at_100 |
|
value: 51.815 |
|
- type: recall_at_1000 |
|
value: 77.04299999999999 |
|
- type: recall_at_3 |
|
value: 20.238999999999997 |
|
- type: recall_at_5 |
|
value: 23.837 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.475000000000001 |
|
- type: map_at_10 |
|
value: 12.898000000000001 |
|
- type: map_at_100 |
|
value: 13.950000000000001 |
|
- type: map_at_1000 |
|
value: 14.063999999999998 |
|
- type: map_at_3 |
|
value: 10.965 |
|
- type: map_at_5 |
|
value: 11.905000000000001 |
|
- type: mrr_at_1 |
|
value: 10.323 |
|
- type: mrr_at_10 |
|
value: 15.431000000000001 |
|
- type: mrr_at_100 |
|
value: 16.442 |
|
- type: mrr_at_1000 |
|
value: 16.526 |
|
- type: mrr_at_3 |
|
value: 13.288 |
|
- type: mrr_at_5 |
|
value: 14.382 |
|
- type: ndcg_at_1 |
|
value: 10.323 |
|
- type: ndcg_at_10 |
|
value: 16.325 |
|
- type: ndcg_at_100 |
|
value: 21.831999999999997 |
|
- type: ndcg_at_1000 |
|
value: 25.079 |
|
- type: ndcg_at_3 |
|
value: 12.372 |
|
- type: ndcg_at_5 |
|
value: 14.011999999999999 |
|
- type: precision_at_1 |
|
value: 10.323 |
|
- type: precision_at_10 |
|
value: 3.197 |
|
- type: precision_at_100 |
|
value: 0.6930000000000001 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 5.970000000000001 |
|
- type: precision_at_5 |
|
value: 4.627 |
|
- type: recall_at_1 |
|
value: 8.475000000000001 |
|
- type: recall_at_10 |
|
value: 24.651999999999997 |
|
- type: recall_at_100 |
|
value: 49.63 |
|
- type: recall_at_1000 |
|
value: 73.35000000000001 |
|
- type: recall_at_3 |
|
value: 13.852 |
|
- type: recall_at_5 |
|
value: 17.813000000000002 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.278 |
|
- type: map_at_10 |
|
value: 24.852 |
|
- type: map_at_100 |
|
value: 26.308999999999997 |
|
- type: map_at_1000 |
|
value: 26.450000000000003 |
|
- type: map_at_3 |
|
value: 22.183 |
|
- type: map_at_5 |
|
value: 23.493 |
|
- type: mrr_at_1 |
|
value: 22.522000000000002 |
|
- type: mrr_at_10 |
|
value: 29.554000000000002 |
|
- type: mrr_at_100 |
|
value: 30.705 |
|
- type: mrr_at_1000 |
|
value: 30.774 |
|
- type: mrr_at_3 |
|
value: 26.821 |
|
- type: mrr_at_5 |
|
value: 28.288000000000004 |
|
- type: ndcg_at_1 |
|
value: 22.522000000000002 |
|
- type: ndcg_at_10 |
|
value: 29.79 |
|
- type: ndcg_at_100 |
|
value: 36.473 |
|
- type: ndcg_at_1000 |
|
value: 39.440999999999995 |
|
- type: ndcg_at_3 |
|
value: 24.915000000000003 |
|
- type: ndcg_at_5 |
|
value: 26.941 |
|
- type: precision_at_1 |
|
value: 22.522000000000002 |
|
- type: precision_at_10 |
|
value: 5.707 |
|
- type: precision_at_100 |
|
value: 1.076 |
|
- type: precision_at_1000 |
|
value: 0.153 |
|
- type: precision_at_3 |
|
value: 11.645999999999999 |
|
- type: precision_at_5 |
|
value: 8.584999999999999 |
|
- type: recall_at_1 |
|
value: 18.278 |
|
- type: recall_at_10 |
|
value: 40.150999999999996 |
|
- type: recall_at_100 |
|
value: 68.978 |
|
- type: recall_at_1000 |
|
value: 89.295 |
|
- type: recall_at_3 |
|
value: 26.548 |
|
- type: recall_at_5 |
|
value: 31.772 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.634 |
|
- type: map_at_10 |
|
value: 21.377 |
|
- type: map_at_100 |
|
value: 22.522000000000002 |
|
- type: map_at_1000 |
|
value: 22.657 |
|
- type: map_at_3 |
|
value: 19.292 |
|
- type: map_at_5 |
|
value: 20.278 |
|
- type: mrr_at_1 |
|
value: 18.151 |
|
- type: mrr_at_10 |
|
value: 25.263999999999996 |
|
- type: mrr_at_100 |
|
value: 26.156000000000002 |
|
- type: mrr_at_1000 |
|
value: 26.247 |
|
- type: mrr_at_3 |
|
value: 23.154 |
|
- type: mrr_at_5 |
|
value: 24.188000000000002 |
|
- type: ndcg_at_1 |
|
value: 18.151 |
|
- type: ndcg_at_10 |
|
value: 25.773000000000003 |
|
- type: ndcg_at_100 |
|
value: 31.130999999999997 |
|
- type: ndcg_at_1000 |
|
value: 34.452 |
|
- type: ndcg_at_3 |
|
value: 21.975 |
|
- type: ndcg_at_5 |
|
value: 23.36 |
|
- type: precision_at_1 |
|
value: 18.151 |
|
- type: precision_at_10 |
|
value: 4.829 |
|
- type: precision_at_100 |
|
value: 0.894 |
|
- type: precision_at_1000 |
|
value: 0.136 |
|
- type: precision_at_3 |
|
value: 10.693 |
|
- type: precision_at_5 |
|
value: 7.648000000000001 |
|
- type: recall_at_1 |
|
value: 14.634 |
|
- type: recall_at_10 |
|
value: 35.433 |
|
- type: recall_at_100 |
|
value: 58.617 |
|
- type: recall_at_1000 |
|
value: 82.364 |
|
- type: recall_at_3 |
|
value: 24.59 |
|
- type: recall_at_5 |
|
value: 28.217 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.736583333333334 |
|
- type: map_at_10 |
|
value: 20.393 |
|
- type: map_at_100 |
|
value: 21.42775 |
|
- type: map_at_1000 |
|
value: 21.560666666666666 |
|
- type: map_at_3 |
|
value: 18.52958333333333 |
|
- type: map_at_5 |
|
value: 19.509249999999998 |
|
- type: mrr_at_1 |
|
value: 17.61366666666667 |
|
- type: mrr_at_10 |
|
value: 23.522250000000003 |
|
- type: mrr_at_100 |
|
value: 24.424166666666668 |
|
- type: mrr_at_1000 |
|
value: 24.512166666666666 |
|
- type: mrr_at_3 |
|
value: 21.64875 |
|
- type: mrr_at_5 |
|
value: 22.648916666666665 |
|
- type: ndcg_at_1 |
|
value: 17.61366666666667 |
|
- type: ndcg_at_10 |
|
value: 24.16458333333333 |
|
- type: ndcg_at_100 |
|
value: 29.305916666666672 |
|
- type: ndcg_at_1000 |
|
value: 32.52291666666667 |
|
- type: ndcg_at_3 |
|
value: 20.732 |
|
- type: ndcg_at_5 |
|
value: 22.223333333333333 |
|
- type: precision_at_1 |
|
value: 17.61366666666667 |
|
- type: precision_at_10 |
|
value: 4.33925 |
|
- type: precision_at_100 |
|
value: 0.8296666666666666 |
|
- type: precision_at_1000 |
|
value: 0.12933333333333333 |
|
- type: precision_at_3 |
|
value: 9.6265 |
|
- type: precision_at_5 |
|
value: 6.921666666666666 |
|
- type: recall_at_1 |
|
value: 14.736583333333334 |
|
- type: recall_at_10 |
|
value: 32.46958333333333 |
|
- type: recall_at_100 |
|
value: 55.94050000000001 |
|
- type: recall_at_1000 |
|
value: 79.17466666666667 |
|
- type: recall_at_3 |
|
value: 22.765749999999997 |
|
- type: recall_at_5 |
|
value: 26.614583333333336 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.152 |
|
- type: map_at_10 |
|
value: 16.052 |
|
- type: map_at_100 |
|
value: 16.892 |
|
- type: map_at_1000 |
|
value: 17.0 |
|
- type: map_at_3 |
|
value: 14.677999999999999 |
|
- type: map_at_5 |
|
value: 15.424 |
|
- type: mrr_at_1 |
|
value: 12.883 |
|
- type: mrr_at_10 |
|
value: 17.871000000000002 |
|
- type: mrr_at_100 |
|
value: 18.694 |
|
- type: mrr_at_1000 |
|
value: 18.793000000000003 |
|
- type: mrr_at_3 |
|
value: 16.641000000000002 |
|
- type: mrr_at_5 |
|
value: 17.262 |
|
- type: ndcg_at_1 |
|
value: 12.883 |
|
- type: ndcg_at_10 |
|
value: 18.981 |
|
- type: ndcg_at_100 |
|
value: 23.704 |
|
- type: ndcg_at_1000 |
|
value: 26.810000000000002 |
|
- type: ndcg_at_3 |
|
value: 16.361 |
|
- type: ndcg_at_5 |
|
value: 17.507 |
|
- type: precision_at_1 |
|
value: 12.883 |
|
- type: precision_at_10 |
|
value: 3.221 |
|
- type: precision_at_100 |
|
value: 0.612 |
|
- type: precision_at_1000 |
|
value: 0.095 |
|
- type: precision_at_3 |
|
value: 7.4639999999999995 |
|
- type: precision_at_5 |
|
value: 5.244999999999999 |
|
- type: recall_at_1 |
|
value: 11.152 |
|
- type: recall_at_10 |
|
value: 26.22 |
|
- type: recall_at_100 |
|
value: 48.870000000000005 |
|
- type: recall_at_1000 |
|
value: 72.328 |
|
- type: recall_at_3 |
|
value: 18.838 |
|
- type: recall_at_5 |
|
value: 21.693 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: 46989137a86843e03a6195de44b09deda022eec7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.338 |
|
- type: map_at_10 |
|
value: 12.315 |
|
- type: map_at_100 |
|
value: 13.086 |
|
- type: map_at_1000 |
|
value: 13.214 |
|
- type: map_at_3 |
|
value: 11.032 |
|
- type: map_at_5 |
|
value: 11.691 |
|
- type: mrr_at_1 |
|
value: 10.255 |
|
- type: mrr_at_10 |
|
value: 14.723 |
|
- type: mrr_at_100 |
|
value: 15.528 |
|
- type: mrr_at_1000 |
|
value: 15.626000000000001 |
|
- type: mrr_at_3 |
|
value: 13.289000000000001 |
|
- type: mrr_at_5 |
|
value: 14.047 |
|
- type: ndcg_at_1 |
|
value: 10.255 |
|
- type: ndcg_at_10 |
|
value: 15.058 |
|
- type: ndcg_at_100 |
|
value: 19.326 |
|
- type: ndcg_at_1000 |
|
value: 22.972 |
|
- type: ndcg_at_3 |
|
value: 12.565999999999999 |
|
- type: ndcg_at_5 |
|
value: 13.603000000000002 |
|
- type: precision_at_1 |
|
value: 10.255 |
|
- type: precision_at_10 |
|
value: 2.815 |
|
- type: precision_at_100 |
|
value: 0.597 |
|
- type: precision_at_1000 |
|
value: 0.109 |
|
- type: precision_at_3 |
|
value: 6.045 |
|
- type: precision_at_5 |
|
value: 4.405 |
|
- type: recall_at_1 |
|
value: 8.338 |
|
- type: recall_at_10 |
|
value: 21.125 |
|
- type: recall_at_100 |
|
value: 40.936 |
|
- type: recall_at_1000 |
|
value: 67.984 |
|
- type: recall_at_3 |
|
value: 14.018 |
|
- type: recall_at_5 |
|
value: 16.725 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.575000000000001 |
|
- type: map_at_10 |
|
value: 18.967 |
|
- type: map_at_100 |
|
value: 19.924 |
|
- type: map_at_1000 |
|
value: 20.06 |
|
- type: map_at_3 |
|
value: 17.101 |
|
- type: map_at_5 |
|
value: 18.142 |
|
- type: mrr_at_1 |
|
value: 16.418 |
|
- type: mrr_at_10 |
|
value: 22.131 |
|
- type: mrr_at_100 |
|
value: 22.993 |
|
- type: mrr_at_1000 |
|
value: 23.101 |
|
- type: mrr_at_3 |
|
value: 20.288999999999998 |
|
- type: mrr_at_5 |
|
value: 21.282999999999998 |
|
- type: ndcg_at_1 |
|
value: 16.418 |
|
- type: ndcg_at_10 |
|
value: 22.625 |
|
- type: ndcg_at_100 |
|
value: 27.676000000000002 |
|
- type: ndcg_at_1000 |
|
value: 31.41 |
|
- type: ndcg_at_3 |
|
value: 19.136 |
|
- type: ndcg_at_5 |
|
value: 20.748 |
|
- type: precision_at_1 |
|
value: 16.418 |
|
- type: precision_at_10 |
|
value: 3.9739999999999998 |
|
- type: precision_at_100 |
|
value: 0.743 |
|
- type: precision_at_1000 |
|
value: 0.11800000000000001 |
|
- type: precision_at_3 |
|
value: 8.924 |
|
- type: precision_at_5 |
|
value: 6.381 |
|
- type: recall_at_1 |
|
value: 13.575000000000001 |
|
- type: recall_at_10 |
|
value: 30.794 |
|
- type: recall_at_100 |
|
value: 54.02400000000001 |
|
- type: recall_at_1000 |
|
value: 81.634 |
|
- type: recall_at_3 |
|
value: 21.095 |
|
- type: recall_at_5 |
|
value: 25.25 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.915999999999999 |
|
- type: map_at_10 |
|
value: 20.976 |
|
- type: map_at_100 |
|
value: 22.127 |
|
- type: map_at_1000 |
|
value: 22.329 |
|
- type: map_at_3 |
|
value: 19.62 |
|
- type: map_at_5 |
|
value: 20.247999999999998 |
|
- type: mrr_at_1 |
|
value: 18.379 |
|
- type: mrr_at_10 |
|
value: 24.822 |
|
- type: mrr_at_100 |
|
value: 25.765 |
|
- type: mrr_at_1000 |
|
value: 25.852000000000004 |
|
- type: mrr_at_3 |
|
value: 23.551 |
|
- type: mrr_at_5 |
|
value: 24.193 |
|
- type: ndcg_at_1 |
|
value: 18.379 |
|
- type: ndcg_at_10 |
|
value: 24.956999999999997 |
|
- type: ndcg_at_100 |
|
value: 30.224 |
|
- type: ndcg_at_1000 |
|
value: 33.883 |
|
- type: ndcg_at_3 |
|
value: 23.094 |
|
- type: ndcg_at_5 |
|
value: 23.659 |
|
- type: precision_at_1 |
|
value: 18.379 |
|
- type: precision_at_10 |
|
value: 4.802 |
|
- type: precision_at_100 |
|
value: 1.105 |
|
- type: precision_at_1000 |
|
value: 0.2 |
|
- type: precision_at_3 |
|
value: 11.462 |
|
- type: precision_at_5 |
|
value: 7.826 |
|
- type: recall_at_1 |
|
value: 14.915999999999999 |
|
- type: recall_at_10 |
|
value: 31.902 |
|
- type: recall_at_100 |
|
value: 57.296 |
|
- type: recall_at_1000 |
|
value: 82.107 |
|
- type: recall_at_3 |
|
value: 25.013 |
|
- type: recall_at_5 |
|
value: 27.281 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 12.237 |
|
- type: map_at_10 |
|
value: 15.703 |
|
- type: map_at_100 |
|
value: 16.522000000000002 |
|
- type: map_at_1000 |
|
value: 16.631999999999998 |
|
- type: map_at_3 |
|
value: 14.455000000000002 |
|
- type: map_at_5 |
|
value: 14.982000000000001 |
|
- type: mrr_at_1 |
|
value: 13.309000000000001 |
|
- type: mrr_at_10 |
|
value: 17.068 |
|
- type: mrr_at_100 |
|
value: 17.904 |
|
- type: mrr_at_1000 |
|
value: 18.004 |
|
- type: mrr_at_3 |
|
value: 15.712000000000002 |
|
- type: mrr_at_5 |
|
value: 16.285 |
|
- type: ndcg_at_1 |
|
value: 13.309000000000001 |
|
- type: ndcg_at_10 |
|
value: 18.205 |
|
- type: ndcg_at_100 |
|
value: 22.68 |
|
- type: ndcg_at_1000 |
|
value: 25.901000000000003 |
|
- type: ndcg_at_3 |
|
value: 15.472 |
|
- type: ndcg_at_5 |
|
value: 16.436 |
|
- type: precision_at_1 |
|
value: 13.309000000000001 |
|
- type: precision_at_10 |
|
value: 2.791 |
|
- type: precision_at_100 |
|
value: 0.538 |
|
- type: precision_at_1000 |
|
value: 0.086 |
|
- type: precision_at_3 |
|
value: 6.346 |
|
- type: precision_at_5 |
|
value: 4.324999999999999 |
|
- type: recall_at_1 |
|
value: 12.237 |
|
- type: recall_at_10 |
|
value: 24.88 |
|
- type: recall_at_100 |
|
value: 46.017 |
|
- type: recall_at_1000 |
|
value: 71.029 |
|
- type: recall_at_3 |
|
value: 17.197000000000003 |
|
- type: recall_at_5 |
|
value: 19.6 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.732 |
|
- type: map_at_10 |
|
value: 12.674 |
|
- type: map_at_100 |
|
value: 14.257 |
|
- type: map_at_1000 |
|
value: 14.463999999999999 |
|
- type: map_at_3 |
|
value: 10.355 |
|
- type: map_at_5 |
|
value: 11.524 |
|
- type: mrr_at_1 |
|
value: 15.831000000000001 |
|
- type: mrr_at_10 |
|
value: 25.972 |
|
- type: mrr_at_100 |
|
value: 27.107999999999997 |
|
- type: mrr_at_1000 |
|
value: 27.167 |
|
- type: mrr_at_3 |
|
value: 22.637999999999998 |
|
- type: mrr_at_5 |
|
value: 24.319 |
|
- type: ndcg_at_1 |
|
value: 15.831000000000001 |
|
- type: ndcg_at_10 |
|
value: 19.244 |
|
- type: ndcg_at_100 |
|
value: 26.329 |
|
- type: ndcg_at_1000 |
|
value: 30.270999999999997 |
|
- type: ndcg_at_3 |
|
value: 14.966 |
|
- type: ndcg_at_5 |
|
value: 16.377 |
|
- type: precision_at_1 |
|
value: 15.831000000000001 |
|
- type: precision_at_10 |
|
value: 6.404 |
|
- type: precision_at_100 |
|
value: 1.403 |
|
- type: precision_at_1000 |
|
value: 0.212 |
|
- type: precision_at_3 |
|
value: 11.64 |
|
- type: precision_at_5 |
|
value: 9.134 |
|
- type: recall_at_1 |
|
value: 6.732 |
|
- type: recall_at_10 |
|
value: 24.855 |
|
- type: recall_at_100 |
|
value: 49.730000000000004 |
|
- type: recall_at_1000 |
|
value: 72.214 |
|
- type: recall_at_3 |
|
value: 14.299000000000001 |
|
- type: recall_at_5 |
|
value: 18.363 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.529 |
|
- type: map_at_10 |
|
value: 9.075999999999999 |
|
- type: map_at_100 |
|
value: 12.394 |
|
- type: map_at_1000 |
|
value: 13.272999999999998 |
|
- type: map_at_3 |
|
value: 6.688 |
|
- type: map_at_5 |
|
value: 7.803 |
|
- type: mrr_at_1 |
|
value: 36.25 |
|
- type: mrr_at_10 |
|
value: 46.867 |
|
- type: mrr_at_100 |
|
value: 47.654 |
|
- type: mrr_at_1000 |
|
value: 47.679 |
|
- type: mrr_at_3 |
|
value: 43.791999999999994 |
|
- type: mrr_at_5 |
|
value: 45.742 |
|
- type: ndcg_at_1 |
|
value: 26.75 |
|
- type: ndcg_at_10 |
|
value: 21.146 |
|
- type: ndcg_at_100 |
|
value: 25.113999999999997 |
|
- type: ndcg_at_1000 |
|
value: 31.873 |
|
- type: ndcg_at_3 |
|
value: 23.142 |
|
- type: ndcg_at_5 |
|
value: 22.273 |
|
- type: precision_at_1 |
|
value: 36.25 |
|
- type: precision_at_10 |
|
value: 18.25 |
|
- type: precision_at_100 |
|
value: 6.16 |
|
- type: precision_at_1000 |
|
value: 1.34 |
|
- type: precision_at_3 |
|
value: 27.250000000000004 |
|
- type: precision_at_5 |
|
value: 23.75 |
|
- type: recall_at_1 |
|
value: 4.529 |
|
- type: recall_at_10 |
|
value: 13.442000000000002 |
|
- type: recall_at_100 |
|
value: 32.534 |
|
- type: recall_at_1000 |
|
value: 55.346 |
|
- type: recall_at_3 |
|
value: 7.771999999999999 |
|
- type: recall_at_5 |
|
value: 10.061 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 37.89000000000001 |
|
- type: f1 |
|
value: 34.12692942265391 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
|
metrics: |
|
- type: map_at_1 |
|
value: 16.28 |
|
- type: map_at_10 |
|
value: 24.729 |
|
- type: map_at_100 |
|
value: 25.785999999999998 |
|
- type: map_at_1000 |
|
value: 25.855 |
|
- type: map_at_3 |
|
value: 22.083 |
|
- type: map_at_5 |
|
value: 23.534 |
|
- type: mrr_at_1 |
|
value: 17.462 |
|
- type: mrr_at_10 |
|
value: 26.358999999999998 |
|
- type: mrr_at_100 |
|
value: 27.412 |
|
- type: mrr_at_1000 |
|
value: 27.473 |
|
- type: mrr_at_3 |
|
value: 23.615 |
|
- type: mrr_at_5 |
|
value: 25.115 |
|
- type: ndcg_at_1 |
|
value: 17.462 |
|
- type: ndcg_at_10 |
|
value: 29.885 |
|
- type: ndcg_at_100 |
|
value: 35.268 |
|
- type: ndcg_at_1000 |
|
value: 37.203 |
|
- type: ndcg_at_3 |
|
value: 24.397 |
|
- type: ndcg_at_5 |
|
value: 26.995 |
|
- type: precision_at_1 |
|
value: 17.462 |
|
- type: precision_at_10 |
|
value: 4.851 |
|
- type: precision_at_100 |
|
value: 0.77 |
|
- type: precision_at_1000 |
|
value: 0.095 |
|
- type: precision_at_3 |
|
value: 10.666 |
|
- type: precision_at_5 |
|
value: 7.762 |
|
- type: recall_at_1 |
|
value: 16.28 |
|
- type: recall_at_10 |
|
value: 44.554 |
|
- type: recall_at_100 |
|
value: 69.736 |
|
- type: recall_at_1000 |
|
value: 84.654 |
|
- type: recall_at_3 |
|
value: 29.529 |
|
- type: recall_at_5 |
|
value: 35.789 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.406 |
|
- type: map_at_10 |
|
value: 12.162 |
|
- type: map_at_100 |
|
value: 13.501 |
|
- type: map_at_1000 |
|
value: 13.700000000000001 |
|
- type: map_at_3 |
|
value: 10.282 |
|
- type: map_at_5 |
|
value: 11.182 |
|
- type: mrr_at_1 |
|
value: 14.969 |
|
- type: mrr_at_10 |
|
value: 21.453 |
|
- type: mrr_at_100 |
|
value: 22.579 |
|
- type: mrr_at_1000 |
|
value: 22.665 |
|
- type: mrr_at_3 |
|
value: 19.084 |
|
- type: mrr_at_5 |
|
value: 20.233999999999998 |
|
- type: ndcg_at_1 |
|
value: 14.969 |
|
- type: ndcg_at_10 |
|
value: 17.022000000000002 |
|
- type: ndcg_at_100 |
|
value: 23.415 |
|
- type: ndcg_at_1000 |
|
value: 27.811000000000003 |
|
- type: ndcg_at_3 |
|
value: 14.191999999999998 |
|
- type: ndcg_at_5 |
|
value: 15.026 |
|
- type: precision_at_1 |
|
value: 14.969 |
|
- type: precision_at_10 |
|
value: 4.954 |
|
- type: precision_at_100 |
|
value: 1.133 |
|
- type: precision_at_1000 |
|
value: 0.191 |
|
- type: precision_at_3 |
|
value: 9.516 |
|
- type: precision_at_5 |
|
value: 7.191 |
|
- type: recall_at_1 |
|
value: 7.406 |
|
- type: recall_at_10 |
|
value: 22.404 |
|
- type: recall_at_100 |
|
value: 47.351 |
|
- type: recall_at_1000 |
|
value: 74.701 |
|
- type: recall_at_3 |
|
value: 13.108 |
|
- type: recall_at_5 |
|
value: 16.531000000000002 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.662 |
|
- type: map_at_10 |
|
value: 28.956 |
|
- type: map_at_100 |
|
value: 29.942999999999998 |
|
- type: map_at_1000 |
|
value: 30.052 |
|
- type: map_at_3 |
|
value: 26.767999999999997 |
|
- type: map_at_5 |
|
value: 28.011000000000003 |
|
- type: mrr_at_1 |
|
value: 41.323 |
|
- type: mrr_at_10 |
|
value: 49.242999999999995 |
|
- type: mrr_at_100 |
|
value: 49.97 |
|
- type: mrr_at_1000 |
|
value: 50.016000000000005 |
|
- type: mrr_at_3 |
|
value: 47.207 |
|
- type: mrr_at_5 |
|
value: 48.364000000000004 |
|
- type: ndcg_at_1 |
|
value: 41.323 |
|
- type: ndcg_at_10 |
|
value: 36.756 |
|
- type: ndcg_at_100 |
|
value: 41.189 |
|
- type: ndcg_at_1000 |
|
value: 43.667 |
|
- type: ndcg_at_3 |
|
value: 32.690999999999995 |
|
- type: ndcg_at_5 |
|
value: 34.703 |
|
- type: precision_at_1 |
|
value: 41.323 |
|
- type: precision_at_10 |
|
value: 8.015 |
|
- type: precision_at_100 |
|
value: 1.155 |
|
- type: precision_at_1000 |
|
value: 0.148 |
|
- type: precision_at_3 |
|
value: 20.612 |
|
- type: precision_at_5 |
|
value: 13.961000000000002 |
|
- type: recall_at_1 |
|
value: 20.662 |
|
- type: recall_at_10 |
|
value: 40.074 |
|
- type: recall_at_100 |
|
value: 57.745000000000005 |
|
- type: recall_at_1000 |
|
value: 74.24 |
|
- type: recall_at_3 |
|
value: 30.918 |
|
- type: recall_at_5 |
|
value: 34.902 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 64.62239999999998 |
|
- type: ap |
|
value: 59.505106899987936 |
|
- type: f1 |
|
value: 64.39587267286105 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB MSMARCO |
|
config: default |
|
split: dev |
|
revision: c5a29a104738b98a9e76336939199e264163d4a0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.507000000000001 |
|
- type: map_at_10 |
|
value: 11.542 |
|
- type: map_at_100 |
|
value: 12.542 |
|
- type: map_at_1000 |
|
value: 12.658 |
|
- type: map_at_3 |
|
value: 9.67 |
|
- type: map_at_5 |
|
value: 10.631 |
|
- type: mrr_at_1 |
|
value: 6.705 |
|
- type: mrr_at_10 |
|
value: 11.857 |
|
- type: mrr_at_100 |
|
value: 12.863 |
|
- type: mrr_at_1000 |
|
value: 12.974 |
|
- type: mrr_at_3 |
|
value: 9.957 |
|
- type: mrr_at_5 |
|
value: 10.933 |
|
- type: ndcg_at_1 |
|
value: 6.705 |
|
- type: ndcg_at_10 |
|
value: 14.764 |
|
- type: ndcg_at_100 |
|
value: 20.258000000000003 |
|
- type: ndcg_at_1000 |
|
value: 23.685000000000002 |
|
- type: ndcg_at_3 |
|
value: 10.809000000000001 |
|
- type: ndcg_at_5 |
|
value: 12.543000000000001 |
|
- type: precision_at_1 |
|
value: 6.705 |
|
- type: precision_at_10 |
|
value: 2.579 |
|
- type: precision_at_100 |
|
value: 0.543 |
|
- type: precision_at_1000 |
|
value: 0.084 |
|
- type: precision_at_3 |
|
value: 4.771 |
|
- type: precision_at_5 |
|
value: 3.734 |
|
- type: recall_at_1 |
|
value: 6.507000000000001 |
|
- type: recall_at_10 |
|
value: 24.842 |
|
- type: recall_at_100 |
|
value: 51.697 |
|
- type: recall_at_1000 |
|
value: 79.081 |
|
- type: recall_at_3 |
|
value: 13.828 |
|
- type: recall_at_5 |
|
value: 18.009 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 84.40264477884178 |
|
- type: f1 |
|
value: 83.43871348215795 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 54.90196078431372 |
|
- type: f1 |
|
value: 35.66115135754105 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 61.371889710827176 |
|
- type: f1 |
|
value: 58.91304009131599 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 67.52185608607937 |
|
- type: f1 |
|
value: 66.27921261407421 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 30.40912967319626 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 26.77476593032722 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 30.522211560565317 |
|
- type: mrr |
|
value: 31.540554976019745 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.871 |
|
- type: map_at_10 |
|
value: 6.643000000000001 |
|
- type: map_at_100 |
|
value: 8.801 |
|
- type: map_at_1000 |
|
value: 9.961 |
|
- type: map_at_3 |
|
value: 4.862 |
|
- type: map_at_5 |
|
value: 5.704 |
|
- type: mrr_at_1 |
|
value: 29.102 |
|
- type: mrr_at_10 |
|
value: 38.79 |
|
- type: mrr_at_100 |
|
value: 39.616 |
|
- type: mrr_at_1000 |
|
value: 39.659 |
|
- type: mrr_at_3 |
|
value: 35.913000000000004 |
|
- type: mrr_at_5 |
|
value: 37.74 |
|
- type: ndcg_at_1 |
|
value: 27.554000000000002 |
|
- type: ndcg_at_10 |
|
value: 22.215 |
|
- type: ndcg_at_100 |
|
value: 21.386 |
|
- type: ndcg_at_1000 |
|
value: 30.615 |
|
- type: ndcg_at_3 |
|
value: 25.546000000000003 |
|
- type: ndcg_at_5 |
|
value: 24.425 |
|
- type: precision_at_1 |
|
value: 29.102 |
|
- type: precision_at_10 |
|
value: 17.121 |
|
- type: precision_at_100 |
|
value: 6.146 |
|
- type: precision_at_1000 |
|
value: 1.9029999999999998 |
|
- type: precision_at_3 |
|
value: 24.871 |
|
- type: precision_at_5 |
|
value: 22.291 |
|
- type: recall_at_1 |
|
value: 2.871 |
|
- type: recall_at_10 |
|
value: 10.184999999999999 |
|
- type: recall_at_100 |
|
value: 24.057000000000002 |
|
- type: recall_at_1000 |
|
value: 56.788000000000004 |
|
- type: recall_at_3 |
|
value: 5.606 |
|
- type: recall_at_5 |
|
value: 7.353 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.455 |
|
- type: map_at_10 |
|
value: 17.904999999999998 |
|
- type: map_at_100 |
|
value: 19.215 |
|
- type: map_at_1000 |
|
value: 19.314 |
|
- type: map_at_3 |
|
value: 15.133 |
|
- type: map_at_5 |
|
value: 16.624 |
|
- type: mrr_at_1 |
|
value: 11.906 |
|
- type: mrr_at_10 |
|
value: 19.595000000000002 |
|
- type: mrr_at_100 |
|
value: 20.765 |
|
- type: mrr_at_1000 |
|
value: 20.845 |
|
- type: mrr_at_3 |
|
value: 16.7 |
|
- type: mrr_at_5 |
|
value: 18.314 |
|
- type: ndcg_at_1 |
|
value: 11.906 |
|
- type: ndcg_at_10 |
|
value: 22.733999999999998 |
|
- type: ndcg_at_100 |
|
value: 29.179 |
|
- type: ndcg_at_1000 |
|
value: 31.848 |
|
- type: ndcg_at_3 |
|
value: 16.98 |
|
- type: ndcg_at_5 |
|
value: 19.695 |
|
- type: precision_at_1 |
|
value: 11.906 |
|
- type: precision_at_10 |
|
value: 4.234999999999999 |
|
- type: precision_at_100 |
|
value: 0.79 |
|
- type: precision_at_1000 |
|
value: 0.105 |
|
- type: precision_at_3 |
|
value: 7.976 |
|
- type: precision_at_5 |
|
value: 6.286 |
|
- type: recall_at_1 |
|
value: 10.455 |
|
- type: recall_at_10 |
|
value: 36.114000000000004 |
|
- type: recall_at_100 |
|
value: 65.742 |
|
- type: recall_at_1000 |
|
value: 86.22800000000001 |
|
- type: recall_at_3 |
|
value: 20.826 |
|
- type: recall_at_5 |
|
value: 27.165 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 63.336000000000006 |
|
- type: map_at_10 |
|
value: 76.859 |
|
- type: map_at_100 |
|
value: 77.679 |
|
- type: map_at_1000 |
|
value: 77.705 |
|
- type: map_at_3 |
|
value: 73.681 |
|
- type: map_at_5 |
|
value: 75.558 |
|
- type: mrr_at_1 |
|
value: 73.13 |
|
- type: mrr_at_10 |
|
value: 80.757 |
|
- type: mrr_at_100 |
|
value: 80.99300000000001 |
|
- type: mrr_at_1000 |
|
value: 80.99499999999999 |
|
- type: mrr_at_3 |
|
value: 79.267 |
|
- type: mrr_at_5 |
|
value: 80.209 |
|
- type: ndcg_at_1 |
|
value: 73.15 |
|
- type: ndcg_at_10 |
|
value: 81.693 |
|
- type: ndcg_at_100 |
|
value: 83.733 |
|
- type: ndcg_at_1000 |
|
value: 83.943 |
|
- type: ndcg_at_3 |
|
value: 77.866 |
|
- type: ndcg_at_5 |
|
value: 79.779 |
|
- type: precision_at_1 |
|
value: 73.15 |
|
- type: precision_at_10 |
|
value: 12.603 |
|
- type: precision_at_100 |
|
value: 1.51 |
|
- type: precision_at_1000 |
|
value: 0.156 |
|
- type: precision_at_3 |
|
value: 34.123 |
|
- type: precision_at_5 |
|
value: 22.636 |
|
- type: recall_at_1 |
|
value: 63.336000000000006 |
|
- type: recall_at_10 |
|
value: 91.36999999999999 |
|
- type: recall_at_100 |
|
value: 98.831 |
|
- type: recall_at_1000 |
|
value: 99.901 |
|
- type: recall_at_3 |
|
value: 80.495 |
|
- type: recall_at_5 |
|
value: 85.799 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 43.4964655583453 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 48.31404856068323 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 3.5479999999999996 |
|
- type: map_at_10 |
|
value: 8.923 |
|
- type: map_at_100 |
|
value: 11.038 |
|
- type: map_at_1000 |
|
value: 11.384 |
|
- type: map_at_3 |
|
value: 6.387 |
|
- type: map_at_5 |
|
value: 7.646999999999999 |
|
- type: mrr_at_1 |
|
value: 17.5 |
|
- type: mrr_at_10 |
|
value: 27.71 |
|
- type: mrr_at_100 |
|
value: 28.898000000000003 |
|
- type: mrr_at_1000 |
|
value: 28.96 |
|
- type: mrr_at_3 |
|
value: 24.282999999999998 |
|
- type: mrr_at_5 |
|
value: 26.123 |
|
- type: ndcg_at_1 |
|
value: 17.5 |
|
- type: ndcg_at_10 |
|
value: 15.831999999999999 |
|
- type: ndcg_at_100 |
|
value: 24.478 |
|
- type: ndcg_at_1000 |
|
value: 30.548 |
|
- type: ndcg_at_3 |
|
value: 14.66 |
|
- type: ndcg_at_5 |
|
value: 12.969 |
|
- type: precision_at_1 |
|
value: 17.5 |
|
- type: precision_at_10 |
|
value: 8.38 |
|
- type: precision_at_100 |
|
value: 2.103 |
|
- type: precision_at_1000 |
|
value: 0.356 |
|
- type: precision_at_3 |
|
value: 13.866999999999999 |
|
- type: precision_at_5 |
|
value: 11.58 |
|
- type: recall_at_1 |
|
value: 3.5479999999999996 |
|
- type: recall_at_10 |
|
value: 16.958000000000002 |
|
- type: recall_at_100 |
|
value: 42.687999999999995 |
|
- type: recall_at_1000 |
|
value: 72.173 |
|
- type: recall_at_3 |
|
value: 8.437999999999999 |
|
- type: recall_at_5 |
|
value: 11.738 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.88215495721286 |
|
- type: cos_sim_spearman |
|
value: 66.95635868609415 |
|
- type: euclidean_pearson |
|
value: 71.95058611790435 |
|
- type: euclidean_spearman |
|
value: 66.95635868609415 |
|
- type: manhattan_pearson |
|
value: 71.73499967722593 |
|
- type: manhattan_spearman |
|
value: 66.76136105777387 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 72.56521014258115 |
|
- type: cos_sim_spearman |
|
value: 64.21841908004934 |
|
- type: euclidean_pearson |
|
value: 68.51846331737438 |
|
- type: euclidean_spearman |
|
value: 64.21841908004934 |
|
- type: manhattan_pearson |
|
value: 68.27567108498233 |
|
- type: manhattan_spearman |
|
value: 64.09725470920785 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 72.71775862893193 |
|
- type: cos_sim_spearman |
|
value: 73.28911820172492 |
|
- type: euclidean_pearson |
|
value: 72.83254599010056 |
|
- type: euclidean_spearman |
|
value: 73.28922176679981 |
|
- type: manhattan_pearson |
|
value: 72.56589783996398 |
|
- type: manhattan_spearman |
|
value: 72.99829341365574 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 73.89757752366668 |
|
- type: cos_sim_spearman |
|
value: 68.93443322328304 |
|
- type: euclidean_pearson |
|
value: 71.74950262447223 |
|
- type: euclidean_spearman |
|
value: 68.93447340804855 |
|
- type: manhattan_pearson |
|
value: 71.53131355539159 |
|
- type: manhattan_spearman |
|
value: 68.75571712820332 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 80.97565977782956 |
|
- type: cos_sim_spearman |
|
value: 81.43311223145955 |
|
- type: euclidean_pearson |
|
value: 80.99231321031297 |
|
- type: euclidean_spearman |
|
value: 81.43311223145955 |
|
- type: manhattan_pearson |
|
value: 80.85980250491755 |
|
- type: manhattan_spearman |
|
value: 81.28760623160176 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 75.52199164461821 |
|
- type: cos_sim_spearman |
|
value: 76.00370946904079 |
|
- type: euclidean_pearson |
|
value: 75.52316904078243 |
|
- type: euclidean_spearman |
|
value: 76.00370946904079 |
|
- type: manhattan_pearson |
|
value: 75.3120467704852 |
|
- type: manhattan_spearman |
|
value: 75.73102913980114 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS17 (en-en) |
|
config: en-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.71078769268394 |
|
- type: cos_sim_spearman |
|
value: 84.92569102013795 |
|
- type: euclidean_pearson |
|
value: 84.42768434149738 |
|
- type: euclidean_spearman |
|
value: 84.92569102013795 |
|
- type: manhattan_pearson |
|
value: 84.36599569720875 |
|
- type: manhattan_spearman |
|
value: 84.97627760625926 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS22 (en) |
|
config: en |
|
split: test |
|
revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 60.75551853889779 |
|
- type: cos_sim_spearman |
|
value: 59.56097878013177 |
|
- type: euclidean_pearson |
|
value: 62.25756001900302 |
|
- type: euclidean_spearman |
|
value: 59.56097878013177 |
|
- type: manhattan_pearson |
|
value: 61.56622096305194 |
|
- type: manhattan_spearman |
|
value: 58.794887940253346 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 78.57502299404004 |
|
- type: cos_sim_spearman |
|
value: 76.84123747775618 |
|
- type: euclidean_pearson |
|
value: 78.18263544350317 |
|
- type: euclidean_spearman |
|
value: 76.84123747775618 |
|
- type: manhattan_pearson |
|
value: 78.06611402413624 |
|
- type: manhattan_spearman |
|
value: 76.79100666899737 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 82.80038681665185 |
|
- type: mrr |
|
value: 94.90057418978986 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 39.056000000000004 |
|
- type: map_at_10 |
|
value: 48.714 |
|
- type: map_at_100 |
|
value: 49.653999999999996 |
|
- type: map_at_1000 |
|
value: 49.706 |
|
- type: map_at_3 |
|
value: 45.806000000000004 |
|
- type: map_at_5 |
|
value: 47.5 |
|
- type: mrr_at_1 |
|
value: 41.0 |
|
- type: mrr_at_10 |
|
value: 50.104000000000006 |
|
- type: mrr_at_100 |
|
value: 50.859 |
|
- type: mrr_at_1000 |
|
value: 50.903 |
|
- type: mrr_at_3 |
|
value: 47.556 |
|
- type: mrr_at_5 |
|
value: 48.972 |
|
- type: ndcg_at_1 |
|
value: 41.0 |
|
- type: ndcg_at_10 |
|
value: 54.144999999999996 |
|
- type: ndcg_at_100 |
|
value: 58.269999999999996 |
|
- type: ndcg_at_1000 |
|
value: 59.648 |
|
- type: ndcg_at_3 |
|
value: 48.451 |
|
- type: ndcg_at_5 |
|
value: 51.319 |
|
- type: precision_at_1 |
|
value: 41.0 |
|
- type: precision_at_10 |
|
value: 7.7 |
|
- type: precision_at_100 |
|
value: 0.997 |
|
- type: precision_at_1000 |
|
value: 0.11199999999999999 |
|
- type: precision_at_3 |
|
value: 19.444 |
|
- type: precision_at_5 |
|
value: 13.333 |
|
- type: recall_at_1 |
|
value: 39.056000000000004 |
|
- type: recall_at_10 |
|
value: 69.61699999999999 |
|
- type: recall_at_100 |
|
value: 87.922 |
|
- type: recall_at_1000 |
|
value: 98.667 |
|
- type: recall_at_3 |
|
value: 54.193999999999996 |
|
- type: recall_at_5 |
|
value: 61.138999999999996 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.73762376237623 |
|
- type: cos_sim_ap |
|
value: 91.61413659372461 |
|
- type: cos_sim_f1 |
|
value: 86.34046890927624 |
|
- type: cos_sim_precision |
|
value: 88.04573804573805 |
|
- type: cos_sim_recall |
|
value: 84.7 |
|
- type: dot_accuracy |
|
value: 99.73762376237623 |
|
- type: dot_ap |
|
value: 91.61413659372461 |
|
- type: dot_f1 |
|
value: 86.34046890927624 |
|
- type: dot_precision |
|
value: 88.04573804573805 |
|
- type: dot_recall |
|
value: 84.7 |
|
- type: euclidean_accuracy |
|
value: 99.73762376237623 |
|
- type: euclidean_ap |
|
value: 91.61413659372461 |
|
- type: euclidean_f1 |
|
value: 86.34046890927624 |
|
- type: euclidean_precision |
|
value: 88.04573804573805 |
|
- type: euclidean_recall |
|
value: 84.7 |
|
- type: manhattan_accuracy |
|
value: 99.74059405940594 |
|
- type: manhattan_ap |
|
value: 91.56213824792806 |
|
- type: manhattan_f1 |
|
value: 86.22502628811776 |
|
- type: manhattan_precision |
|
value: 90.9090909090909 |
|
- type: manhattan_recall |
|
value: 82.0 |
|
- type: max_accuracy |
|
value: 99.74059405940594 |
|
- type: max_ap |
|
value: 91.61413659372461 |
|
- type: max_f1 |
|
value: 86.34046890927624 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 53.09338784502622 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 32.57087655180163 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 41.59188785875835 |
|
- type: mrr |
|
value: 41.92390024191495 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: None |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 29.69015090602311 |
|
- type: cos_sim_spearman |
|
value: 30.124791626004075 |
|
- type: dot_pearson |
|
value: 29.69015070868056 |
|
- type: dot_spearman |
|
value: 30.09621990241238 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.186 |
|
- type: map_at_10 |
|
value: 1.2149999999999999 |
|
- type: map_at_100 |
|
value: 6.516 |
|
- type: map_at_1000 |
|
value: 14.704999999999998 |
|
- type: map_at_3 |
|
value: 0.469 |
|
- type: map_at_5 |
|
value: 0.701 |
|
- type: mrr_at_1 |
|
value: 72.0 |
|
- type: mrr_at_10 |
|
value: 80.238 |
|
- type: mrr_at_100 |
|
value: 80.622 |
|
- type: mrr_at_1000 |
|
value: 80.622 |
|
- type: mrr_at_3 |
|
value: 79.667 |
|
- type: mrr_at_5 |
|
value: 79.667 |
|
- type: ndcg_at_1 |
|
value: 64.0 |
|
- type: ndcg_at_10 |
|
value: 57.147000000000006 |
|
- type: ndcg_at_100 |
|
value: 40.5 |
|
- type: ndcg_at_1000 |
|
value: 33.954 |
|
- type: ndcg_at_3 |
|
value: 62.754 |
|
- type: ndcg_at_5 |
|
value: 59.933 |
|
- type: precision_at_1 |
|
value: 72.0 |
|
- type: precision_at_10 |
|
value: 60.6 |
|
- type: precision_at_100 |
|
value: 42.1 |
|
- type: precision_at_1000 |
|
value: 15.512 |
|
- type: precision_at_3 |
|
value: 67.333 |
|
- type: precision_at_5 |
|
value: 64.0 |
|
- type: recall_at_1 |
|
value: 0.186 |
|
- type: recall_at_10 |
|
value: 1.385 |
|
- type: recall_at_100 |
|
value: 9.332 |
|
- type: recall_at_1000 |
|
value: 31.922 |
|
- type: recall_at_3 |
|
value: 0.503 |
|
- type: recall_at_5 |
|
value: 0.759 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.0660000000000003 |
|
- type: map_at_10 |
|
value: 9.783999999999999 |
|
- type: map_at_100 |
|
value: 16.005 |
|
- type: map_at_1000 |
|
value: 17.694 |
|
- type: map_at_3 |
|
value: 4.524 |
|
- type: map_at_5 |
|
value: 6.651 |
|
- type: mrr_at_1 |
|
value: 32.653 |
|
- type: mrr_at_10 |
|
value: 49.26 |
|
- type: mrr_at_100 |
|
value: 49.791000000000004 |
|
- type: mrr_at_1000 |
|
value: 49.791000000000004 |
|
- type: mrr_at_3 |
|
value: 45.238 |
|
- type: mrr_at_5 |
|
value: 47.177 |
|
- type: ndcg_at_1 |
|
value: 29.592000000000002 |
|
- type: ndcg_at_10 |
|
value: 26.35 |
|
- type: ndcg_at_100 |
|
value: 38.078 |
|
- type: ndcg_at_1000 |
|
value: 49.222 |
|
- type: ndcg_at_3 |
|
value: 28.749000000000002 |
|
- type: ndcg_at_5 |
|
value: 28.156 |
|
- type: precision_at_1 |
|
value: 32.653 |
|
- type: precision_at_10 |
|
value: 25.306 |
|
- type: precision_at_100 |
|
value: 8.449 |
|
- type: precision_at_1000 |
|
value: 1.559 |
|
- type: precision_at_3 |
|
value: 31.293 |
|
- type: precision_at_5 |
|
value: 30.203999999999997 |
|
- type: recall_at_1 |
|
value: 2.0660000000000003 |
|
- type: recall_at_10 |
|
value: 17.009 |
|
- type: recall_at_100 |
|
value: 50.065000000000005 |
|
- type: recall_at_1000 |
|
value: 84.247 |
|
- type: recall_at_3 |
|
value: 6.223 |
|
- type: recall_at_5 |
|
value: 10.062 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 65.9572 |
|
- type: ap |
|
value: 11.472412091038306 |
|
- type: f1 |
|
value: 50.25348253932964 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 49.60384833050367 |
|
- type: f1 |
|
value: 49.6458985672963 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 32.85259172670649 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 79.30500089408118 |
|
- type: cos_sim_ap |
|
value: 48.463983264840934 |
|
- type: cos_sim_f1 |
|
value: 49.28199791883455 |
|
- type: cos_sim_precision |
|
value: 40.687285223367695 |
|
- type: cos_sim_recall |
|
value: 62.48021108179419 |
|
- type: dot_accuracy |
|
value: 79.30500089408118 |
|
- type: dot_ap |
|
value: 48.463988663433994 |
|
- type: dot_f1 |
|
value: 49.28199791883455 |
|
- type: dot_precision |
|
value: 40.687285223367695 |
|
- type: dot_recall |
|
value: 62.48021108179419 |
|
- type: euclidean_accuracy |
|
value: 79.30500089408118 |
|
- type: euclidean_ap |
|
value: 48.463983264840934 |
|
- type: euclidean_f1 |
|
value: 49.28199791883455 |
|
- type: euclidean_precision |
|
value: 40.687285223367695 |
|
- type: euclidean_recall |
|
value: 62.48021108179419 |
|
- type: manhattan_accuracy |
|
value: 79.2811587292126 |
|
- type: manhattan_ap |
|
value: 48.38522593516497 |
|
- type: manhattan_f1 |
|
value: 49.11896465903435 |
|
- type: manhattan_precision |
|
value: 39.440447641886486 |
|
- type: manhattan_recall |
|
value: 65.09234828496042 |
|
- type: max_accuracy |
|
value: 79.30500089408118 |
|
- type: max_ap |
|
value: 48.463988663433994 |
|
- type: max_f1 |
|
value: 49.28199791883455 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 86.58167423448597 |
|
- type: cos_sim_ap |
|
value: 80.70276946703169 |
|
- type: cos_sim_f1 |
|
value: 73.6376389338513 |
|
- type: cos_sim_precision |
|
value: 69.10146492945385 |
|
- type: cos_sim_recall |
|
value: 78.81121034801355 |
|
- type: dot_accuracy |
|
value: 86.58167423448597 |
|
- type: dot_ap |
|
value: 80.70276237270826 |
|
- type: dot_f1 |
|
value: 73.6376389338513 |
|
- type: dot_precision |
|
value: 69.10146492945385 |
|
- type: dot_recall |
|
value: 78.81121034801355 |
|
- type: euclidean_accuracy |
|
value: 86.58167423448597 |
|
- type: euclidean_ap |
|
value: 80.70277058558774 |
|
- type: euclidean_f1 |
|
value: 73.6376389338513 |
|
- type: euclidean_precision |
|
value: 69.10146492945385 |
|
- type: euclidean_recall |
|
value: 78.81121034801355 |
|
- type: manhattan_accuracy |
|
value: 86.47882951061435 |
|
- type: manhattan_ap |
|
value: 80.56146544234434 |
|
- type: manhattan_f1 |
|
value: 73.43608995415659 |
|
- type: manhattan_precision |
|
value: 69.1267414203194 |
|
- type: manhattan_recall |
|
value: 78.31844779796735 |
|
- type: max_accuracy |
|
value: 86.58167423448597 |
|
- type: max_ap |
|
value: 80.70277058558774 |
|
- type: max_f1 |
|
value: 73.6376389338513 |
|
--- |
