Sentence Similarity
sentence-transformers
PyTorch
TensorBoard
Transformers
English
German
t5
text-embedding
embeddings
information-retrieval
beir
text-classification
language-model
text-clustering
text-semantic-similarity
text-evaluation
prompt-retrieval
text-reranking
feature-extraction
English
Sentence Similarity
natural_questions
ms_marco
fever
hotpot_qa
mteb
Commit
•
4dfd5a6
1
Parent(s):
d71e600
Remove evaluation results
Browse files
README.md
CHANGED
@@ -24,2505 +24,13 @@ tags:
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- fever
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- hotpot_qa
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- mteb
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language:
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inference: false
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license: apache-2.0
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model-index:
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- name: final_base_results
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results:
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-
- task:
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type: Classification
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-
dataset:
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type: mteb/amazon_counterfactual
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name: MTEB AmazonCounterfactualClassification (en)
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config: en
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split: test
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205
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metrics:
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- type: accuracy
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value: 86.2089552238806
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- type: ap
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value: 55.76273850794966
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- type: f1
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value: 81.26104211414781
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- task:
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type: Classification
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dataset:
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type: mteb/amazon_polarity
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name: MTEB AmazonPolarityClassification
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config: default
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split: test
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revision: e2d317d38cd51312af73b3d32a06d1a08b442046
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metrics:
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- type: accuracy
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value: 88.35995000000001
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- type: ap
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value: 84.18839957309655
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- type: f1
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value: 88.317619250081
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- task:
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type: Classification
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dataset:
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type: mteb/amazon_reviews_multi
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name: MTEB AmazonReviewsClassification (en)
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config: en
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split: test
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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metrics:
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- type: accuracy
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value: 44.64
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- type: f1
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value: 42.48663956478136
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- task:
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type: Retrieval
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dataset:
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type: arguana
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name: MTEB ArguAna
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config: default
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split: test
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revision: None
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metrics:
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- type: map_at_1
|
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value: 27.383000000000003
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- type: map_at_10
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value: 43.024
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value: 44.023
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value: 37.684
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value: 40.884
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value: 28.094
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value: 43.315
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value: 80.868
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value: 98.86200000000001
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value: 99.431
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value: 51.28
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- type: recall_at_5
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value: 65.22
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- task:
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type: Clustering
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dataset:
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type: mteb/arxiv-clustering-p2p
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name: MTEB ArxivClusteringP2P
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config: default
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split: test
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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metrics:
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- type: v_measure
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value: 39.68441054431849
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- task:
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type: Clustering
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dataset:
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type: mteb/arxiv-clustering-s2s
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name: MTEB ArxivClusteringS2S
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config: default
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split: test
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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metrics:
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- type: v_measure
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value: 29.188539728343844
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- task:
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type: Reranking
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dataset:
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type: mteb/askubuntudupquestions-reranking
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name: MTEB AskUbuntuDupQuestions
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config: default
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split: test
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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metrics:
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- type: map
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value: 63.173362687519784
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- type: mrr
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value: 76.18860748362133
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- task:
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type: STS
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dataset:
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type: mteb/biosses-sts
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name: MTEB BIOSSES
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config: default
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split: test
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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metrics:
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- type: cos_sim_spearman
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value: 82.30789953771232
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- task:
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type: Classification
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dataset:
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type: mteb/banking77
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name: MTEB Banking77Classification
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config: default
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split: test
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
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metrics:
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- type: accuracy
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value: 77.03571428571428
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- type: f1
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value: 75.87384305045917
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- task:
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type: Clustering
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dataset:
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type: mteb/biorxiv-clustering-p2p
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name: MTEB BiorxivClusteringP2P
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config: default
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split: test
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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metrics:
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- type: v_measure
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value: 32.98041170516364
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- task:
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type: Clustering
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dataset:
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type: mteb/biorxiv-clustering-s2s
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name: MTEB BiorxivClusteringS2S
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config: default
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split: test
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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metrics:
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- type: v_measure
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value: 25.71652988451154
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- task:
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type: Retrieval
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dataset:
|
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type: BeIR/cqadupstack
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name: MTEB CQADupstackAndroidRetrieval
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config: default
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split: test
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revision: None
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metrics:
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value: 33.739999999999995
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value: 9.943
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value: 0.20500000000000002
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value: 23.413999999999998
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value: 16.481
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value: 97.475
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value: 51.953
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- task:
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type: Retrieval
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dataset:
|
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type: BeIR/cqadupstack
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-
name: MTEB CQADupstackEnglishRetrieval
|
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config: default
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split: test
|
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revision: None
|
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metrics:
|
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- type: map_at_1
|
305 |
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value: 31.169999999999998
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- type: map_at_10
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value: 39.427
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value: 47.818
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value: 47.181
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value: 51.737
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value: 53.74
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value: 43.261
|
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- type: ndcg_at_5
|
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value: 44.891
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- type: precision_at_1
|
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value: 39.427
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- type: precision_at_10
|
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-
value: 8.847
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- type: precision_at_100
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345 |
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value: 1.425
|
346 |
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- type: precision_at_1000
|
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value: 0.189
|
348 |
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- type: precision_at_3
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value: 20.785999999999998
|
350 |
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- type: precision_at_5
|
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value: 14.560999999999998
|
352 |
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- type: recall_at_1
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value: 31.169999999999998
|
354 |
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- type: recall_at_10
|
355 |
-
value: 56.971000000000004
|
356 |
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- type: recall_at_100
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value: 76.31400000000001
|
358 |
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- type: recall_at_1000
|
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-
value: 88.93900000000001
|
360 |
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- type: recall_at_3
|
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value: 45.208
|
362 |
-
- type: recall_at_5
|
363 |
-
value: 49.923
|
364 |
-
- task:
|
365 |
-
type: Retrieval
|
366 |
-
dataset:
|
367 |
-
type: BeIR/cqadupstack
|
368 |
-
name: MTEB CQADupstackGamingRetrieval
|
369 |
-
config: default
|
370 |
-
split: test
|
371 |
-
revision: None
|
372 |
-
metrics:
|
373 |
-
- type: map_at_1
|
374 |
-
value: 39.682
|
375 |
-
- type: map_at_10
|
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-
value: 52.766000000000005
|
377 |
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- type: map_at_100
|
378 |
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value: 53.84100000000001
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value: 49.291000000000004
|
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- type: map_at_5
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value: 51.365
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386 |
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value: 45.266
|
387 |
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388 |
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value: 56.093
|
389 |
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- type: mrr_at_100
|
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value: 56.763
|
391 |
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- type: mrr_at_1000
|
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value: 56.793000000000006
|
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value: 53.668000000000006
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- type: mrr_at_5
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value: 55.1
|
397 |
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value: 45.266
|
399 |
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- type: ndcg_at_10
|
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value: 58.836
|
401 |
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- type: ndcg_at_100
|
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value: 62.863
|
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-
- type: ndcg_at_1000
|
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value: 63.912
|
405 |
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|
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value: 53.19199999999999
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407 |
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value: 56.125
|
409 |
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|
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value: 45.266
|
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- type: precision_at_10
|
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value: 9.492
|
413 |
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- type: precision_at_100
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value: 1.236
|
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- type: precision_at_1000
|
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value: 0.13699999999999998
|
417 |
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- type: precision_at_3
|
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value: 23.762
|
419 |
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- type: precision_at_5
|
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value: 16.414
|
421 |
-
- type: recall_at_1
|
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-
value: 39.682
|
423 |
-
- type: recall_at_10
|
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-
value: 73.233
|
425 |
-
- type: recall_at_100
|
426 |
-
value: 90.335
|
427 |
-
- type: recall_at_1000
|
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-
value: 97.452
|
429 |
-
- type: recall_at_3
|
430 |
-
value: 58.562000000000005
|
431 |
-
- type: recall_at_5
|
432 |
-
value: 65.569
|
433 |
-
- task:
|
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-
type: Retrieval
|
435 |
-
dataset:
|
436 |
-
type: BeIR/cqadupstack
|
437 |
-
name: MTEB CQADupstackGisRetrieval
|
438 |
-
config: default
|
439 |
-
split: test
|
440 |
-
revision: None
|
441 |
-
metrics:
|
442 |
-
- type: map_at_1
|
443 |
-
value: 26.743
|
444 |
-
- type: map_at_10
|
445 |
-
value: 34.016000000000005
|
446 |
-
- type: map_at_100
|
447 |
-
value: 35.028999999999996
|
448 |
-
- type: map_at_1000
|
449 |
-
value: 35.113
|
450 |
-
- type: map_at_3
|
451 |
-
value: 31.763
|
452 |
-
- type: map_at_5
|
453 |
-
value: 33.013999999999996
|
454 |
-
- type: mrr_at_1
|
455 |
-
value: 28.927000000000003
|
456 |
-
- type: mrr_at_10
|
457 |
-
value: 36.32
|
458 |
-
- type: mrr_at_100
|
459 |
-
value: 37.221
|
460 |
-
- type: mrr_at_1000
|
461 |
-
value: 37.281
|
462 |
-
- type: mrr_at_3
|
463 |
-
value: 34.105000000000004
|
464 |
-
- type: mrr_at_5
|
465 |
-
value: 35.371
|
466 |
-
- type: ndcg_at_1
|
467 |
-
value: 28.927000000000003
|
468 |
-
- type: ndcg_at_10
|
469 |
-
value: 38.474000000000004
|
470 |
-
- type: ndcg_at_100
|
471 |
-
value: 43.580000000000005
|
472 |
-
- type: ndcg_at_1000
|
473 |
-
value: 45.64
|
474 |
-
- type: ndcg_at_3
|
475 |
-
value: 34.035
|
476 |
-
- type: ndcg_at_5
|
477 |
-
value: 36.186
|
478 |
-
- type: precision_at_1
|
479 |
-
value: 28.927000000000003
|
480 |
-
- type: precision_at_10
|
481 |
-
value: 5.74
|
482 |
-
- type: precision_at_100
|
483 |
-
value: 0.8710000000000001
|
484 |
-
- type: precision_at_1000
|
485 |
-
value: 0.108
|
486 |
-
- type: precision_at_3
|
487 |
-
value: 14.124
|
488 |
-
- type: precision_at_5
|
489 |
-
value: 9.74
|
490 |
-
- type: recall_at_1
|
491 |
-
value: 26.743
|
492 |
-
- type: recall_at_10
|
493 |
-
value: 49.955
|
494 |
-
- type: recall_at_100
|
495 |
-
value: 73.904
|
496 |
-
- type: recall_at_1000
|
497 |
-
value: 89.133
|
498 |
-
- type: recall_at_3
|
499 |
-
value: 38.072
|
500 |
-
- type: recall_at_5
|
501 |
-
value: 43.266
|
502 |
-
- task:
|
503 |
-
type: Retrieval
|
504 |
-
dataset:
|
505 |
-
type: BeIR/cqadupstack
|
506 |
-
name: MTEB CQADupstackMathematicaRetrieval
|
507 |
-
config: default
|
508 |
-
split: test
|
509 |
-
revision: None
|
510 |
-
metrics:
|
511 |
-
- type: map_at_1
|
512 |
-
value: 16.928
|
513 |
-
- type: map_at_10
|
514 |
-
value: 23.549
|
515 |
-
- type: map_at_100
|
516 |
-
value: 24.887
|
517 |
-
- type: map_at_1000
|
518 |
-
value: 25.018
|
519 |
-
- type: map_at_3
|
520 |
-
value: 21.002000000000002
|
521 |
-
- type: map_at_5
|
522 |
-
value: 22.256
|
523 |
-
- type: mrr_at_1
|
524 |
-
value: 21.02
|
525 |
-
- type: mrr_at_10
|
526 |
-
value: 27.898
|
527 |
-
- type: mrr_at_100
|
528 |
-
value: 29.018
|
529 |
-
- type: mrr_at_1000
|
530 |
-
value: 29.099999999999998
|
531 |
-
- type: mrr_at_3
|
532 |
-
value: 25.456
|
533 |
-
- type: mrr_at_5
|
534 |
-
value: 26.625
|
535 |
-
- type: ndcg_at_1
|
536 |
-
value: 21.02
|
537 |
-
- type: ndcg_at_10
|
538 |
-
value: 28.277
|
539 |
-
- type: ndcg_at_100
|
540 |
-
value: 34.54
|
541 |
-
- type: ndcg_at_1000
|
542 |
-
value: 37.719
|
543 |
-
- type: ndcg_at_3
|
544 |
-
value: 23.707
|
545 |
-
- type: ndcg_at_5
|
546 |
-
value: 25.482
|
547 |
-
- type: precision_at_1
|
548 |
-
value: 21.02
|
549 |
-
- type: precision_at_10
|
550 |
-
value: 5.361
|
551 |
-
- type: precision_at_100
|
552 |
-
value: 0.9809999999999999
|
553 |
-
- type: precision_at_1000
|
554 |
-
value: 0.13899999999999998
|
555 |
-
- type: precision_at_3
|
556 |
-
value: 11.401
|
557 |
-
- type: precision_at_5
|
558 |
-
value: 8.209
|
559 |
-
- type: recall_at_1
|
560 |
-
value: 16.928
|
561 |
-
- type: recall_at_10
|
562 |
-
value: 38.601
|
563 |
-
- type: recall_at_100
|
564 |
-
value: 65.759
|
565 |
-
- type: recall_at_1000
|
566 |
-
value: 88.543
|
567 |
-
- type: recall_at_3
|
568 |
-
value: 25.556
|
569 |
-
- type: recall_at_5
|
570 |
-
value: 30.447000000000003
|
571 |
-
- task:
|
572 |
-
type: Retrieval
|
573 |
-
dataset:
|
574 |
-
type: BeIR/cqadupstack
|
575 |
-
name: MTEB CQADupstackPhysicsRetrieval
|
576 |
-
config: default
|
577 |
-
split: test
|
578 |
-
revision: None
|
579 |
-
metrics:
|
580 |
-
- type: map_at_1
|
581 |
-
value: 28.549000000000003
|
582 |
-
- type: map_at_10
|
583 |
-
value: 38.426
|
584 |
-
- type: map_at_100
|
585 |
-
value: 39.845000000000006
|
586 |
-
- type: map_at_1000
|
587 |
-
value: 39.956
|
588 |
-
- type: map_at_3
|
589 |
-
value: 35.372
|
590 |
-
- type: map_at_5
|
591 |
-
value: 37.204
|
592 |
-
- type: mrr_at_1
|
593 |
-
value: 35.034
|
594 |
-
- type: mrr_at_10
|
595 |
-
value: 44.041000000000004
|
596 |
-
- type: mrr_at_100
|
597 |
-
value: 44.95
|
598 |
-
- type: mrr_at_1000
|
599 |
-
value: 44.997
|
600 |
-
- type: mrr_at_3
|
601 |
-
value: 41.498000000000005
|
602 |
-
- type: mrr_at_5
|
603 |
-
value: 43.077
|
604 |
-
- type: ndcg_at_1
|
605 |
-
value: 35.034
|
606 |
-
- type: ndcg_at_10
|
607 |
-
value: 44.218
|
608 |
-
- type: ndcg_at_100
|
609 |
-
value: 49.958000000000006
|
610 |
-
- type: ndcg_at_1000
|
611 |
-
value: 52.019000000000005
|
612 |
-
- type: ndcg_at_3
|
613 |
-
value: 39.34
|
614 |
-
- type: ndcg_at_5
|
615 |
-
value: 41.892
|
616 |
-
- type: precision_at_1
|
617 |
-
value: 35.034
|
618 |
-
- type: precision_at_10
|
619 |
-
value: 7.911
|
620 |
-
- type: precision_at_100
|
621 |
-
value: 1.26
|
622 |
-
- type: precision_at_1000
|
623 |
-
value: 0.16
|
624 |
-
- type: precision_at_3
|
625 |
-
value: 18.511
|
626 |
-
- type: precision_at_5
|
627 |
-
value: 13.205
|
628 |
-
- type: recall_at_1
|
629 |
-
value: 28.549000000000003
|
630 |
-
- type: recall_at_10
|
631 |
-
value: 56.035999999999994
|
632 |
-
- type: recall_at_100
|
633 |
-
value: 79.701
|
634 |
-
- type: recall_at_1000
|
635 |
-
value: 93.149
|
636 |
-
- type: recall_at_3
|
637 |
-
value: 42.275
|
638 |
-
- type: recall_at_5
|
639 |
-
value: 49.097
|
640 |
-
- task:
|
641 |
-
type: Retrieval
|
642 |
-
dataset:
|
643 |
-
type: BeIR/cqadupstack
|
644 |
-
name: MTEB CQADupstackProgrammersRetrieval
|
645 |
-
config: default
|
646 |
-
split: test
|
647 |
-
revision: None
|
648 |
-
metrics:
|
649 |
-
- type: map_at_1
|
650 |
-
value: 29.391000000000002
|
651 |
-
- type: map_at_10
|
652 |
-
value: 39.48
|
653 |
-
- type: map_at_100
|
654 |
-
value: 40.727000000000004
|
655 |
-
- type: map_at_1000
|
656 |
-
value: 40.835
|
657 |
-
- type: map_at_3
|
658 |
-
value: 36.234
|
659 |
-
- type: map_at_5
|
660 |
-
value: 37.877
|
661 |
-
- type: mrr_at_1
|
662 |
-
value: 35.959
|
663 |
-
- type: mrr_at_10
|
664 |
-
value: 44.726
|
665 |
-
- type: mrr_at_100
|
666 |
-
value: 45.531
|
667 |
-
- type: mrr_at_1000
|
668 |
-
value: 45.582
|
669 |
-
- type: mrr_at_3
|
670 |
-
value: 42.047000000000004
|
671 |
-
- type: mrr_at_5
|
672 |
-
value: 43.611
|
673 |
-
- type: ndcg_at_1
|
674 |
-
value: 35.959
|
675 |
-
- type: ndcg_at_10
|
676 |
-
value: 45.303
|
677 |
-
- type: ndcg_at_100
|
678 |
-
value: 50.683
|
679 |
-
- type: ndcg_at_1000
|
680 |
-
value: 52.818
|
681 |
-
- type: ndcg_at_3
|
682 |
-
value: 39.987
|
683 |
-
- type: ndcg_at_5
|
684 |
-
value: 42.243
|
685 |
-
- type: precision_at_1
|
686 |
-
value: 35.959
|
687 |
-
- type: precision_at_10
|
688 |
-
value: 8.241999999999999
|
689 |
-
- type: precision_at_100
|
690 |
-
value: 1.274
|
691 |
-
- type: precision_at_1000
|
692 |
-
value: 0.163
|
693 |
-
- type: precision_at_3
|
694 |
-
value: 18.836
|
695 |
-
- type: precision_at_5
|
696 |
-
value: 13.196
|
697 |
-
- type: recall_at_1
|
698 |
-
value: 29.391000000000002
|
699 |
-
- type: recall_at_10
|
700 |
-
value: 57.364000000000004
|
701 |
-
- type: recall_at_100
|
702 |
-
value: 80.683
|
703 |
-
- type: recall_at_1000
|
704 |
-
value: 94.918
|
705 |
-
- type: recall_at_3
|
706 |
-
value: 42.263
|
707 |
-
- type: recall_at_5
|
708 |
-
value: 48.634
|
709 |
-
- task:
|
710 |
-
type: Retrieval
|
711 |
-
dataset:
|
712 |
-
type: BeIR/cqadupstack
|
713 |
-
name: MTEB CQADupstackRetrieval
|
714 |
-
config: default
|
715 |
-
split: test
|
716 |
-
revision: None
|
717 |
-
metrics:
|
718 |
-
- type: map_at_1
|
719 |
-
value: 26.791749999999997
|
720 |
-
- type: map_at_10
|
721 |
-
value: 35.75541666666667
|
722 |
-
- type: map_at_100
|
723 |
-
value: 37.00791666666667
|
724 |
-
- type: map_at_1000
|
725 |
-
value: 37.12408333333333
|
726 |
-
- type: map_at_3
|
727 |
-
value: 33.02966666666667
|
728 |
-
- type: map_at_5
|
729 |
-
value: 34.56866666666667
|
730 |
-
- type: mrr_at_1
|
731 |
-
value: 31.744333333333337
|
732 |
-
- type: mrr_at_10
|
733 |
-
value: 39.9925
|
734 |
-
- type: mrr_at_100
|
735 |
-
value: 40.86458333333333
|
736 |
-
- type: mrr_at_1000
|
737 |
-
value: 40.92175000000001
|
738 |
-
- type: mrr_at_3
|
739 |
-
value: 37.68183333333334
|
740 |
-
- type: mrr_at_5
|
741 |
-
value: 39.028499999999994
|
742 |
-
- type: ndcg_at_1
|
743 |
-
value: 31.744333333333337
|
744 |
-
- type: ndcg_at_10
|
745 |
-
value: 40.95008333333334
|
746 |
-
- type: ndcg_at_100
|
747 |
-
value: 46.25966666666667
|
748 |
-
- type: ndcg_at_1000
|
749 |
-
value: 48.535333333333334
|
750 |
-
- type: ndcg_at_3
|
751 |
-
value: 36.43333333333333
|
752 |
-
- type: ndcg_at_5
|
753 |
-
value: 38.602333333333334
|
754 |
-
- type: precision_at_1
|
755 |
-
value: 31.744333333333337
|
756 |
-
- type: precision_at_10
|
757 |
-
value: 7.135166666666666
|
758 |
-
- type: precision_at_100
|
759 |
-
value: 1.1535833333333334
|
760 |
-
- type: precision_at_1000
|
761 |
-
value: 0.15391666666666665
|
762 |
-
- type: precision_at_3
|
763 |
-
value: 16.713
|
764 |
-
- type: precision_at_5
|
765 |
-
value: 11.828416666666666
|
766 |
-
- type: recall_at_1
|
767 |
-
value: 26.791749999999997
|
768 |
-
- type: recall_at_10
|
769 |
-
value: 51.98625
|
770 |
-
- type: recall_at_100
|
771 |
-
value: 75.30358333333334
|
772 |
-
- type: recall_at_1000
|
773 |
-
value: 91.05433333333333
|
774 |
-
- type: recall_at_3
|
775 |
-
value: 39.39583333333333
|
776 |
-
- type: recall_at_5
|
777 |
-
value: 45.05925
|
778 |
-
- task:
|
779 |
-
type: Retrieval
|
780 |
-
dataset:
|
781 |
-
type: BeIR/cqadupstack
|
782 |
-
name: MTEB CQADupstackStatsRetrieval
|
783 |
-
config: default
|
784 |
-
split: test
|
785 |
-
revision: None
|
786 |
-
metrics:
|
787 |
-
- type: map_at_1
|
788 |
-
value: 22.219
|
789 |
-
- type: map_at_10
|
790 |
-
value: 29.162
|
791 |
-
- type: map_at_100
|
792 |
-
value: 30.049999999999997
|
793 |
-
- type: map_at_1000
|
794 |
-
value: 30.144
|
795 |
-
- type: map_at_3
|
796 |
-
value: 27.204
|
797 |
-
- type: map_at_5
|
798 |
-
value: 28.351
|
799 |
-
- type: mrr_at_1
|
800 |
-
value: 25.153
|
801 |
-
- type: mrr_at_10
|
802 |
-
value: 31.814999999999998
|
803 |
-
- type: mrr_at_100
|
804 |
-
value: 32.573
|
805 |
-
- type: mrr_at_1000
|
806 |
-
value: 32.645
|
807 |
-
- type: mrr_at_3
|
808 |
-
value: 29.934
|
809 |
-
- type: mrr_at_5
|
810 |
-
value: 30.946
|
811 |
-
- type: ndcg_at_1
|
812 |
-
value: 25.153
|
813 |
-
- type: ndcg_at_10
|
814 |
-
value: 33.099000000000004
|
815 |
-
- type: ndcg_at_100
|
816 |
-
value: 37.768
|
817 |
-
- type: ndcg_at_1000
|
818 |
-
value: 40.331
|
819 |
-
- type: ndcg_at_3
|
820 |
-
value: 29.473
|
821 |
-
- type: ndcg_at_5
|
822 |
-
value: 31.206
|
823 |
-
- type: precision_at_1
|
824 |
-
value: 25.153
|
825 |
-
- type: precision_at_10
|
826 |
-
value: 5.183999999999999
|
827 |
-
- type: precision_at_100
|
828 |
-
value: 0.8170000000000001
|
829 |
-
- type: precision_at_1000
|
830 |
-
value: 0.11100000000000002
|
831 |
-
- type: precision_at_3
|
832 |
-
value: 12.831999999999999
|
833 |
-
- type: precision_at_5
|
834 |
-
value: 8.895999999999999
|
835 |
-
- type: recall_at_1
|
836 |
-
value: 22.219
|
837 |
-
- type: recall_at_10
|
838 |
-
value: 42.637
|
839 |
-
- type: recall_at_100
|
840 |
-
value: 64.704
|
841 |
-
- type: recall_at_1000
|
842 |
-
value: 83.963
|
843 |
-
- type: recall_at_3
|
844 |
-
value: 32.444
|
845 |
-
- type: recall_at_5
|
846 |
-
value: 36.802
|
847 |
-
- task:
|
848 |
-
type: Retrieval
|
849 |
-
dataset:
|
850 |
-
type: BeIR/cqadupstack
|
851 |
-
name: MTEB CQADupstackTexRetrieval
|
852 |
-
config: default
|
853 |
-
split: test
|
854 |
-
revision: None
|
855 |
-
metrics:
|
856 |
-
- type: map_at_1
|
857 |
-
value: 17.427999999999997
|
858 |
-
- type: map_at_10
|
859 |
-
value: 24.029
|
860 |
-
- type: map_at_100
|
861 |
-
value: 25.119999999999997
|
862 |
-
- type: map_at_1000
|
863 |
-
value: 25.257
|
864 |
-
- type: map_at_3
|
865 |
-
value: 22.016
|
866 |
-
- type: map_at_5
|
867 |
-
value: 23.143
|
868 |
-
- type: mrr_at_1
|
869 |
-
value: 21.129
|
870 |
-
- type: mrr_at_10
|
871 |
-
value: 27.750000000000004
|
872 |
-
- type: mrr_at_100
|
873 |
-
value: 28.666999999999998
|
874 |
-
- type: mrr_at_1000
|
875 |
-
value: 28.754999999999995
|
876 |
-
- type: mrr_at_3
|
877 |
-
value: 25.849
|
878 |
-
- type: mrr_at_5
|
879 |
-
value: 26.939999999999998
|
880 |
-
- type: ndcg_at_1
|
881 |
-
value: 21.129
|
882 |
-
- type: ndcg_at_10
|
883 |
-
value: 28.203
|
884 |
-
- type: ndcg_at_100
|
885 |
-
value: 33.44
|
886 |
-
- type: ndcg_at_1000
|
887 |
-
value: 36.61
|
888 |
-
- type: ndcg_at_3
|
889 |
-
value: 24.648999999999997
|
890 |
-
- type: ndcg_at_5
|
891 |
-
value: 26.316
|
892 |
-
- type: precision_at_1
|
893 |
-
value: 21.129
|
894 |
-
- type: precision_at_10
|
895 |
-
value: 5.055
|
896 |
-
- type: precision_at_100
|
897 |
-
value: 0.909
|
898 |
-
- type: precision_at_1000
|
899 |
-
value: 0.13699999999999998
|
900 |
-
- type: precision_at_3
|
901 |
-
value: 11.666
|
902 |
-
- type: precision_at_5
|
903 |
-
value: 8.3
|
904 |
-
- type: recall_at_1
|
905 |
-
value: 17.427999999999997
|
906 |
-
- type: recall_at_10
|
907 |
-
value: 36.923
|
908 |
-
- type: recall_at_100
|
909 |
-
value: 60.606
|
910 |
-
- type: recall_at_1000
|
911 |
-
value: 83.19
|
912 |
-
- type: recall_at_3
|
913 |
-
value: 26.845000000000002
|
914 |
-
- type: recall_at_5
|
915 |
-
value: 31.247000000000003
|
916 |
-
- task:
|
917 |
-
type: Retrieval
|
918 |
-
dataset:
|
919 |
-
type: BeIR/cqadupstack
|
920 |
-
name: MTEB CQADupstackUnixRetrieval
|
921 |
-
config: default
|
922 |
-
split: test
|
923 |
-
revision: None
|
924 |
-
metrics:
|
925 |
-
- type: map_at_1
|
926 |
-
value: 26.457000000000004
|
927 |
-
- type: map_at_10
|
928 |
-
value: 35.228
|
929 |
-
- type: map_at_100
|
930 |
-
value: 36.475
|
931 |
-
- type: map_at_1000
|
932 |
-
value: 36.585
|
933 |
-
- type: map_at_3
|
934 |
-
value: 32.444
|
935 |
-
- type: map_at_5
|
936 |
-
value: 34.046
|
937 |
-
- type: mrr_at_1
|
938 |
-
value: 30.784
|
939 |
-
- type: mrr_at_10
|
940 |
-
value: 39.133
|
941 |
-
- type: mrr_at_100
|
942 |
-
value: 40.11
|
943 |
-
- type: mrr_at_1000
|
944 |
-
value: 40.169
|
945 |
-
- type: mrr_at_3
|
946 |
-
value: 36.692
|
947 |
-
- type: mrr_at_5
|
948 |
-
value: 38.17
|
949 |
-
- type: ndcg_at_1
|
950 |
-
value: 30.784
|
951 |
-
- type: ndcg_at_10
|
952 |
-
value: 40.358
|
953 |
-
- type: ndcg_at_100
|
954 |
-
value: 46.119
|
955 |
-
- type: ndcg_at_1000
|
956 |
-
value: 48.428
|
957 |
-
- type: ndcg_at_3
|
958 |
-
value: 35.504000000000005
|
959 |
-
- type: ndcg_at_5
|
960 |
-
value: 37.864
|
961 |
-
- type: precision_at_1
|
962 |
-
value: 30.784
|
963 |
-
- type: precision_at_10
|
964 |
-
value: 6.800000000000001
|
965 |
-
- type: precision_at_100
|
966 |
-
value: 1.083
|
967 |
-
- type: precision_at_1000
|
968 |
-
value: 0.13899999999999998
|
969 |
-
- type: precision_at_3
|
970 |
-
value: 15.920000000000002
|
971 |
-
- type: precision_at_5
|
972 |
-
value: 11.437
|
973 |
-
- type: recall_at_1
|
974 |
-
value: 26.457000000000004
|
975 |
-
- type: recall_at_10
|
976 |
-
value: 51.845
|
977 |
-
- type: recall_at_100
|
978 |
-
value: 77.046
|
979 |
-
- type: recall_at_1000
|
980 |
-
value: 92.892
|
981 |
-
- type: recall_at_3
|
982 |
-
value: 38.89
|
983 |
-
- type: recall_at_5
|
984 |
-
value: 44.688
|
985 |
-
- task:
|
986 |
-
type: Retrieval
|
987 |
-
dataset:
|
988 |
-
type: BeIR/cqadupstack
|
989 |
-
name: MTEB CQADupstackWebmastersRetrieval
|
990 |
-
config: default
|
991 |
-
split: test
|
992 |
-
revision: None
|
993 |
-
metrics:
|
994 |
-
- type: map_at_1
|
995 |
-
value: 29.378999999999998
|
996 |
-
- type: map_at_10
|
997 |
-
value: 37.373
|
998 |
-
- type: map_at_100
|
999 |
-
value: 39.107
|
1000 |
-
- type: map_at_1000
|
1001 |
-
value: 39.317
|
1002 |
-
- type: map_at_3
|
1003 |
-
value: 34.563
|
1004 |
-
- type: map_at_5
|
1005 |
-
value: 36.173
|
1006 |
-
- type: mrr_at_1
|
1007 |
-
value: 35.178
|
1008 |
-
- type: mrr_at_10
|
1009 |
-
value: 42.44
|
1010 |
-
- type: mrr_at_100
|
1011 |
-
value: 43.434
|
1012 |
-
- type: mrr_at_1000
|
1013 |
-
value: 43.482
|
1014 |
-
- type: mrr_at_3
|
1015 |
-
value: 39.987
|
1016 |
-
- type: mrr_at_5
|
1017 |
-
value: 41.370000000000005
|
1018 |
-
- type: ndcg_at_1
|
1019 |
-
value: 35.178
|
1020 |
-
- type: ndcg_at_10
|
1021 |
-
value: 42.82
|
1022 |
-
- type: ndcg_at_100
|
1023 |
-
value: 48.935
|
1024 |
-
- type: ndcg_at_1000
|
1025 |
-
value: 51.28
|
1026 |
-
- type: ndcg_at_3
|
1027 |
-
value: 38.562999999999995
|
1028 |
-
- type: ndcg_at_5
|
1029 |
-
value: 40.687
|
1030 |
-
- type: precision_at_1
|
1031 |
-
value: 35.178
|
1032 |
-
- type: precision_at_10
|
1033 |
-
value: 7.945
|
1034 |
-
- type: precision_at_100
|
1035 |
-
value: 1.524
|
1036 |
-
- type: precision_at_1000
|
1037 |
-
value: 0.242
|
1038 |
-
- type: precision_at_3
|
1039 |
-
value: 17.721
|
1040 |
-
- type: precision_at_5
|
1041 |
-
value: 12.925
|
1042 |
-
- type: recall_at_1
|
1043 |
-
value: 29.378999999999998
|
1044 |
-
- type: recall_at_10
|
1045 |
-
value: 52.141999999999996
|
1046 |
-
- type: recall_at_100
|
1047 |
-
value: 79.49000000000001
|
1048 |
-
- type: recall_at_1000
|
1049 |
-
value: 93.782
|
1050 |
-
- type: recall_at_3
|
1051 |
-
value: 39.579
|
1052 |
-
- type: recall_at_5
|
1053 |
-
value: 45.462
|
1054 |
-
- task:
|
1055 |
-
type: Retrieval
|
1056 |
-
dataset:
|
1057 |
-
type: BeIR/cqadupstack
|
1058 |
-
name: MTEB CQADupstackWordpressRetrieval
|
1059 |
-
config: default
|
1060 |
-
split: test
|
1061 |
-
revision: None
|
1062 |
-
metrics:
|
1063 |
-
- type: map_at_1
|
1064 |
-
value: 19.814999999999998
|
1065 |
-
- type: map_at_10
|
1066 |
-
value: 27.383999999999997
|
1067 |
-
- type: map_at_100
|
1068 |
-
value: 28.483999999999998
|
1069 |
-
- type: map_at_1000
|
1070 |
-
value: 28.585
|
1071 |
-
- type: map_at_3
|
1072 |
-
value: 24.807000000000002
|
1073 |
-
- type: map_at_5
|
1074 |
-
value: 26.485999999999997
|
1075 |
-
- type: mrr_at_1
|
1076 |
-
value: 21.996
|
1077 |
-
- type: mrr_at_10
|
1078 |
-
value: 29.584
|
1079 |
-
- type: mrr_at_100
|
1080 |
-
value: 30.611
|
1081 |
-
- type: mrr_at_1000
|
1082 |
-
value: 30.684
|
1083 |
-
- type: mrr_at_3
|
1084 |
-
value: 27.11
|
1085 |
-
- type: mrr_at_5
|
1086 |
-
value: 28.746
|
1087 |
-
- type: ndcg_at_1
|
1088 |
-
value: 21.996
|
1089 |
-
- type: ndcg_at_10
|
1090 |
-
value: 32.024
|
1091 |
-
- type: ndcg_at_100
|
1092 |
-
value: 37.528
|
1093 |
-
- type: ndcg_at_1000
|
1094 |
-
value: 40.150999999999996
|
1095 |
-
- type: ndcg_at_3
|
1096 |
-
value: 27.016000000000002
|
1097 |
-
- type: ndcg_at_5
|
1098 |
-
value: 29.927999999999997
|
1099 |
-
- type: precision_at_1
|
1100 |
-
value: 21.996
|
1101 |
-
- type: precision_at_10
|
1102 |
-
value: 5.102
|
1103 |
-
- type: precision_at_100
|
1104 |
-
value: 0.856
|
1105 |
-
- type: precision_at_1000
|
1106 |
-
value: 0.117
|
1107 |
-
- type: precision_at_3
|
1108 |
-
value: 11.583
|
1109 |
-
- type: precision_at_5
|
1110 |
-
value: 8.577
|
1111 |
-
- type: recall_at_1
|
1112 |
-
value: 19.814999999999998
|
1113 |
-
- type: recall_at_10
|
1114 |
-
value: 44.239
|
1115 |
-
- type: recall_at_100
|
1116 |
-
value: 69.269
|
1117 |
-
- type: recall_at_1000
|
1118 |
-
value: 89.216
|
1119 |
-
- type: recall_at_3
|
1120 |
-
value: 31.102999999999998
|
1121 |
-
- type: recall_at_5
|
1122 |
-
value: 38.078
|
1123 |
-
- task:
|
1124 |
-
type: Retrieval
|
1125 |
-
dataset:
|
1126 |
-
type: climate-fever
|
1127 |
-
name: MTEB ClimateFEVER
|
1128 |
-
config: default
|
1129 |
-
split: test
|
1130 |
-
revision: None
|
1131 |
-
metrics:
|
1132 |
-
- type: map_at_1
|
1133 |
-
value: 11.349
|
1134 |
-
- type: map_at_10
|
1135 |
-
value: 19.436
|
1136 |
-
- type: map_at_100
|
1137 |
-
value: 21.282999999999998
|
1138 |
-
- type: map_at_1000
|
1139 |
-
value: 21.479
|
1140 |
-
- type: map_at_3
|
1141 |
-
value: 15.841
|
1142 |
-
- type: map_at_5
|
1143 |
-
value: 17.558
|
1144 |
-
- type: mrr_at_1
|
1145 |
-
value: 25.863000000000003
|
1146 |
-
- type: mrr_at_10
|
1147 |
-
value: 37.218
|
1148 |
-
- type: mrr_at_100
|
1149 |
-
value: 38.198
|
1150 |
-
- type: mrr_at_1000
|
1151 |
-
value: 38.236
|
1152 |
-
- type: mrr_at_3
|
1153 |
-
value: 33.409
|
1154 |
-
- type: mrr_at_5
|
1155 |
-
value: 35.602000000000004
|
1156 |
-
- type: ndcg_at_1
|
1157 |
-
value: 25.863000000000003
|
1158 |
-
- type: ndcg_at_10
|
1159 |
-
value: 27.953
|
1160 |
-
- type: ndcg_at_100
|
1161 |
-
value: 35.327
|
1162 |
-
- type: ndcg_at_1000
|
1163 |
-
value: 38.708999999999996
|
1164 |
-
- type: ndcg_at_3
|
1165 |
-
value: 21.985
|
1166 |
-
- type: ndcg_at_5
|
1167 |
-
value: 23.957
|
1168 |
-
- type: precision_at_1
|
1169 |
-
value: 25.863000000000003
|
1170 |
-
- type: precision_at_10
|
1171 |
-
value: 8.99
|
1172 |
-
- type: precision_at_100
|
1173 |
-
value: 1.6889999999999998
|
1174 |
-
- type: precision_at_1000
|
1175 |
-
value: 0.232
|
1176 |
-
- type: precision_at_3
|
1177 |
-
value: 16.308
|
1178 |
-
- type: precision_at_5
|
1179 |
-
value: 12.912
|
1180 |
-
- type: recall_at_1
|
1181 |
-
value: 11.349
|
1182 |
-
- type: recall_at_10
|
1183 |
-
value: 34.581
|
1184 |
-
- type: recall_at_100
|
1185 |
-
value: 60.178
|
1186 |
-
- type: recall_at_1000
|
1187 |
-
value: 78.88199999999999
|
1188 |
-
- type: recall_at_3
|
1189 |
-
value: 20.041999999999998
|
1190 |
-
- type: recall_at_5
|
1191 |
-
value: 25.458
|
1192 |
-
- task:
|
1193 |
-
type: Retrieval
|
1194 |
-
dataset:
|
1195 |
-
type: dbpedia-entity
|
1196 |
-
name: MTEB DBPedia
|
1197 |
-
config: default
|
1198 |
-
split: test
|
1199 |
-
revision: None
|
1200 |
-
metrics:
|
1201 |
-
- type: map_at_1
|
1202 |
-
value: 7.893
|
1203 |
-
- type: map_at_10
|
1204 |
-
value: 15.457
|
1205 |
-
- type: map_at_100
|
1206 |
-
value: 20.905
|
1207 |
-
- type: map_at_1000
|
1208 |
-
value: 22.116
|
1209 |
-
- type: map_at_3
|
1210 |
-
value: 11.593
|
1211 |
-
- type: map_at_5
|
1212 |
-
value: 13.134
|
1213 |
-
- type: mrr_at_1
|
1214 |
-
value: 57.49999999999999
|
1215 |
-
- type: mrr_at_10
|
1216 |
-
value: 65.467
|
1217 |
-
- type: mrr_at_100
|
1218 |
-
value: 66.022
|
1219 |
-
- type: mrr_at_1000
|
1220 |
-
value: 66.039
|
1221 |
-
- type: mrr_at_3
|
1222 |
-
value: 63.458000000000006
|
1223 |
-
- type: mrr_at_5
|
1224 |
-
value: 64.546
|
1225 |
-
- type: ndcg_at_1
|
1226 |
-
value: 45.875
|
1227 |
-
- type: ndcg_at_10
|
1228 |
-
value: 33.344
|
1229 |
-
- type: ndcg_at_100
|
1230 |
-
value: 36.849
|
1231 |
-
- type: ndcg_at_1000
|
1232 |
-
value: 44.03
|
1233 |
-
- type: ndcg_at_3
|
1234 |
-
value: 37.504
|
1235 |
-
- type: ndcg_at_5
|
1236 |
-
value: 34.892
|
1237 |
-
- type: precision_at_1
|
1238 |
-
value: 57.49999999999999
|
1239 |
-
- type: precision_at_10
|
1240 |
-
value: 25.95
|
1241 |
-
- type: precision_at_100
|
1242 |
-
value: 7.89
|
1243 |
-
- type: precision_at_1000
|
1244 |
-
value: 1.669
|
1245 |
-
- type: precision_at_3
|
1246 |
-
value: 40.333000000000006
|
1247 |
-
- type: precision_at_5
|
1248 |
-
value: 33.050000000000004
|
1249 |
-
- type: recall_at_1
|
1250 |
-
value: 7.893
|
1251 |
-
- type: recall_at_10
|
1252 |
-
value: 20.724999999999998
|
1253 |
-
- type: recall_at_100
|
1254 |
-
value: 42.516
|
1255 |
-
- type: recall_at_1000
|
1256 |
-
value: 65.822
|
1257 |
-
- type: recall_at_3
|
1258 |
-
value: 12.615000000000002
|
1259 |
-
- type: recall_at_5
|
1260 |
-
value: 15.482000000000001
|
1261 |
-
- task:
|
1262 |
-
type: Classification
|
1263 |
-
dataset:
|
1264 |
-
type: mteb/emotion
|
1265 |
-
name: MTEB EmotionClassification
|
1266 |
-
config: default
|
1267 |
-
split: test
|
1268 |
-
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
1269 |
-
metrics:
|
1270 |
-
- type: accuracy
|
1271 |
-
value: 51.760000000000005
|
1272 |
-
- type: f1
|
1273 |
-
value: 45.51690565701713
|
1274 |
-
- task:
|
1275 |
-
type: Retrieval
|
1276 |
-
dataset:
|
1277 |
-
type: fever
|
1278 |
-
name: MTEB FEVER
|
1279 |
-
config: default
|
1280 |
-
split: test
|
1281 |
-
revision: None
|
1282 |
-
metrics:
|
1283 |
-
- type: map_at_1
|
1284 |
-
value: 53.882
|
1285 |
-
- type: map_at_10
|
1286 |
-
value: 65.902
|
1287 |
-
- type: map_at_100
|
1288 |
-
value: 66.33
|
1289 |
-
- type: map_at_1000
|
1290 |
-
value: 66.348
|
1291 |
-
- type: map_at_3
|
1292 |
-
value: 63.75999999999999
|
1293 |
-
- type: map_at_5
|
1294 |
-
value: 65.181
|
1295 |
-
- type: mrr_at_1
|
1296 |
-
value: 58.041
|
1297 |
-
- type: mrr_at_10
|
1298 |
-
value: 70.133
|
1299 |
-
- type: mrr_at_100
|
1300 |
-
value: 70.463
|
1301 |
-
- type: mrr_at_1000
|
1302 |
-
value: 70.47
|
1303 |
-
- type: mrr_at_3
|
1304 |
-
value: 68.164
|
1305 |
-
- type: mrr_at_5
|
1306 |
-
value: 69.465
|
1307 |
-
- type: ndcg_at_1
|
1308 |
-
value: 58.041
|
1309 |
-
- type: ndcg_at_10
|
1310 |
-
value: 71.84700000000001
|
1311 |
-
- type: ndcg_at_100
|
1312 |
-
value: 73.699
|
1313 |
-
- type: ndcg_at_1000
|
1314 |
-
value: 74.06700000000001
|
1315 |
-
- type: ndcg_at_3
|
1316 |
-
value: 67.855
|
1317 |
-
- type: ndcg_at_5
|
1318 |
-
value: 70.203
|
1319 |
-
- type: precision_at_1
|
1320 |
-
value: 58.041
|
1321 |
-
- type: precision_at_10
|
1322 |
-
value: 9.427000000000001
|
1323 |
-
- type: precision_at_100
|
1324 |
-
value: 1.049
|
1325 |
-
- type: precision_at_1000
|
1326 |
-
value: 0.11
|
1327 |
-
- type: precision_at_3
|
1328 |
-
value: 27.278000000000002
|
1329 |
-
- type: precision_at_5
|
1330 |
-
value: 17.693
|
1331 |
-
- type: recall_at_1
|
1332 |
-
value: 53.882
|
1333 |
-
- type: recall_at_10
|
1334 |
-
value: 85.99
|
1335 |
-
- type: recall_at_100
|
1336 |
-
value: 94.09100000000001
|
1337 |
-
- type: recall_at_1000
|
1338 |
-
value: 96.612
|
1339 |
-
- type: recall_at_3
|
1340 |
-
value: 75.25
|
1341 |
-
- type: recall_at_5
|
1342 |
-
value: 80.997
|
1343 |
-
- task:
|
1344 |
-
type: Retrieval
|
1345 |
-
dataset:
|
1346 |
-
type: fiqa
|
1347 |
-
name: MTEB FiQA2018
|
1348 |
-
config: default
|
1349 |
-
split: test
|
1350 |
-
revision: None
|
1351 |
-
metrics:
|
1352 |
-
- type: map_at_1
|
1353 |
-
value: 19.165
|
1354 |
-
- type: map_at_10
|
1355 |
-
value: 31.845000000000002
|
1356 |
-
- type: map_at_100
|
1357 |
-
value: 33.678999999999995
|
1358 |
-
- type: map_at_1000
|
1359 |
-
value: 33.878
|
1360 |
-
- type: map_at_3
|
1361 |
-
value: 27.881
|
1362 |
-
- type: map_at_5
|
1363 |
-
value: 30.049999999999997
|
1364 |
-
- type: mrr_at_1
|
1365 |
-
value: 38.272
|
1366 |
-
- type: mrr_at_10
|
1367 |
-
value: 47.04
|
1368 |
-
- type: mrr_at_100
|
1369 |
-
value: 47.923
|
1370 |
-
- type: mrr_at_1000
|
1371 |
-
value: 47.973
|
1372 |
-
- type: mrr_at_3
|
1373 |
-
value: 44.985
|
1374 |
-
- type: mrr_at_5
|
1375 |
-
value: 46.150000000000006
|
1376 |
-
- type: ndcg_at_1
|
1377 |
-
value: 38.272
|
1378 |
-
- type: ndcg_at_10
|
1379 |
-
value: 39.177
|
1380 |
-
- type: ndcg_at_100
|
1381 |
-
value: 45.995000000000005
|
1382 |
-
- type: ndcg_at_1000
|
1383 |
-
value: 49.312
|
1384 |
-
- type: ndcg_at_3
|
1385 |
-
value: 36.135
|
1386 |
-
- type: ndcg_at_5
|
1387 |
-
value: 36.936
|
1388 |
-
- type: precision_at_1
|
1389 |
-
value: 38.272
|
1390 |
-
- type: precision_at_10
|
1391 |
-
value: 10.926
|
1392 |
-
- type: precision_at_100
|
1393 |
-
value: 1.809
|
1394 |
-
- type: precision_at_1000
|
1395 |
-
value: 0.23700000000000002
|
1396 |
-
- type: precision_at_3
|
1397 |
-
value: 24.331
|
1398 |
-
- type: precision_at_5
|
1399 |
-
value: 17.747
|
1400 |
-
- type: recall_at_1
|
1401 |
-
value: 19.165
|
1402 |
-
- type: recall_at_10
|
1403 |
-
value: 45.103
|
1404 |
-
- type: recall_at_100
|
1405 |
-
value: 70.295
|
1406 |
-
- type: recall_at_1000
|
1407 |
-
value: 90.592
|
1408 |
-
- type: recall_at_3
|
1409 |
-
value: 32.832
|
1410 |
-
- type: recall_at_5
|
1411 |
-
value: 37.905
|
1412 |
-
- task:
|
1413 |
-
type: Retrieval
|
1414 |
-
dataset:
|
1415 |
-
type: hotpotqa
|
1416 |
-
name: MTEB HotpotQA
|
1417 |
-
config: default
|
1418 |
-
split: test
|
1419 |
-
revision: None
|
1420 |
-
metrics:
|
1421 |
-
- type: map_at_1
|
1422 |
-
value: 32.397
|
1423 |
-
- type: map_at_10
|
1424 |
-
value: 44.83
|
1425 |
-
- type: map_at_100
|
1426 |
-
value: 45.716
|
1427 |
-
- type: map_at_1000
|
1428 |
-
value: 45.797
|
1429 |
-
- type: map_at_3
|
1430 |
-
value: 41.955999999999996
|
1431 |
-
- type: map_at_5
|
1432 |
-
value: 43.736999999999995
|
1433 |
-
- type: mrr_at_1
|
1434 |
-
value: 64.794
|
1435 |
-
- type: mrr_at_10
|
1436 |
-
value: 71.866
|
1437 |
-
- type: mrr_at_100
|
1438 |
-
value: 72.22
|
1439 |
-
- type: mrr_at_1000
|
1440 |
-
value: 72.238
|
1441 |
-
- type: mrr_at_3
|
1442 |
-
value: 70.416
|
1443 |
-
- type: mrr_at_5
|
1444 |
-
value: 71.304
|
1445 |
-
- type: ndcg_at_1
|
1446 |
-
value: 64.794
|
1447 |
-
- type: ndcg_at_10
|
1448 |
-
value: 54.186
|
1449 |
-
- type: ndcg_at_100
|
1450 |
-
value: 57.623000000000005
|
1451 |
-
- type: ndcg_at_1000
|
1452 |
-
value: 59.302
|
1453 |
-
- type: ndcg_at_3
|
1454 |
-
value: 49.703
|
1455 |
-
- type: ndcg_at_5
|
1456 |
-
value: 52.154999999999994
|
1457 |
-
- type: precision_at_1
|
1458 |
-
value: 64.794
|
1459 |
-
- type: precision_at_10
|
1460 |
-
value: 11.219
|
1461 |
-
- type: precision_at_100
|
1462 |
-
value: 1.394
|
1463 |
-
- type: precision_at_1000
|
1464 |
-
value: 0.16199999999999998
|
1465 |
-
- type: precision_at_3
|
1466 |
-
value: 30.767
|
1467 |
-
- type: precision_at_5
|
1468 |
-
value: 20.397000000000002
|
1469 |
-
- type: recall_at_1
|
1470 |
-
value: 32.397
|
1471 |
-
- type: recall_at_10
|
1472 |
-
value: 56.096999999999994
|
1473 |
-
- type: recall_at_100
|
1474 |
-
value: 69.696
|
1475 |
-
- type: recall_at_1000
|
1476 |
-
value: 80.88499999999999
|
1477 |
-
- type: recall_at_3
|
1478 |
-
value: 46.150999999999996
|
1479 |
-
- type: recall_at_5
|
1480 |
-
value: 50.993
|
1481 |
-
- task:
|
1482 |
-
type: Classification
|
1483 |
-
dataset:
|
1484 |
-
type: mteb/imdb
|
1485 |
-
name: MTEB ImdbClassification
|
1486 |
-
config: default
|
1487 |
-
split: test
|
1488 |
-
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
1489 |
-
metrics:
|
1490 |
-
- type: accuracy
|
1491 |
-
value: 81.1744
|
1492 |
-
- type: ap
|
1493 |
-
value: 75.44973697032414
|
1494 |
-
- type: f1
|
1495 |
-
value: 81.09901117955782
|
1496 |
-
- task:
|
1497 |
-
type: Retrieval
|
1498 |
-
dataset:
|
1499 |
-
type: msmarco
|
1500 |
-
name: MTEB MSMARCO
|
1501 |
-
config: default
|
1502 |
-
split: dev
|
1503 |
-
revision: None
|
1504 |
-
metrics:
|
1505 |
-
- type: map_at_1
|
1506 |
-
value: 19.519000000000002
|
1507 |
-
- type: map_at_10
|
1508 |
-
value: 31.025000000000002
|
1509 |
-
- type: map_at_100
|
1510 |
-
value: 32.275999999999996
|
1511 |
-
- type: map_at_1000
|
1512 |
-
value: 32.329
|
1513 |
-
- type: map_at_3
|
1514 |
-
value: 27.132
|
1515 |
-
- type: map_at_5
|
1516 |
-
value: 29.415999999999997
|
1517 |
-
- type: mrr_at_1
|
1518 |
-
value: 20.115
|
1519 |
-
- type: mrr_at_10
|
1520 |
-
value: 31.569000000000003
|
1521 |
-
- type: mrr_at_100
|
1522 |
-
value: 32.768
|
1523 |
-
- type: mrr_at_1000
|
1524 |
-
value: 32.816
|
1525 |
-
- type: mrr_at_3
|
1526 |
-
value: 27.748
|
1527 |
-
- type: mrr_at_5
|
1528 |
-
value: 29.956
|
1529 |
-
- type: ndcg_at_1
|
1530 |
-
value: 20.115
|
1531 |
-
- type: ndcg_at_10
|
1532 |
-
value: 37.756
|
1533 |
-
- type: ndcg_at_100
|
1534 |
-
value: 43.858000000000004
|
1535 |
-
- type: ndcg_at_1000
|
1536 |
-
value: 45.199
|
1537 |
-
- type: ndcg_at_3
|
1538 |
-
value: 29.818
|
1539 |
-
- type: ndcg_at_5
|
1540 |
-
value: 33.875
|
1541 |
-
- type: precision_at_1
|
1542 |
-
value: 20.115
|
1543 |
-
- type: precision_at_10
|
1544 |
-
value: 6.122
|
1545 |
-
- type: precision_at_100
|
1546 |
-
value: 0.919
|
1547 |
-
- type: precision_at_1000
|
1548 |
-
value: 0.10300000000000001
|
1549 |
-
- type: precision_at_3
|
1550 |
-
value: 12.794
|
1551 |
-
- type: precision_at_5
|
1552 |
-
value: 9.731
|
1553 |
-
- type: recall_at_1
|
1554 |
-
value: 19.519000000000002
|
1555 |
-
- type: recall_at_10
|
1556 |
-
value: 58.62500000000001
|
1557 |
-
- type: recall_at_100
|
1558 |
-
value: 86.99
|
1559 |
-
- type: recall_at_1000
|
1560 |
-
value: 97.268
|
1561 |
-
- type: recall_at_3
|
1562 |
-
value: 37.002
|
1563 |
-
- type: recall_at_5
|
1564 |
-
value: 46.778
|
1565 |
-
- task:
|
1566 |
-
type: Classification
|
1567 |
-
dataset:
|
1568 |
-
type: mteb/mtop_domain
|
1569 |
-
name: MTEB MTOPDomainClassification (en)
|
1570 |
-
config: en
|
1571 |
-
split: test
|
1572 |
-
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
1573 |
-
metrics:
|
1574 |
-
- type: accuracy
|
1575 |
-
value: 93.71865025079799
|
1576 |
-
- type: f1
|
1577 |
-
value: 93.38906173610519
|
1578 |
-
- task:
|
1579 |
-
type: Classification
|
1580 |
-
dataset:
|
1581 |
-
type: mteb/mtop_intent
|
1582 |
-
name: MTEB MTOPIntentClassification (en)
|
1583 |
-
config: en
|
1584 |
-
split: test
|
1585 |
-
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
1586 |
-
metrics:
|
1587 |
-
- type: accuracy
|
1588 |
-
value: 70.2576379388965
|
1589 |
-
- type: f1
|
1590 |
-
value: 49.20405830249464
|
1591 |
-
- task:
|
1592 |
-
type: Classification
|
1593 |
-
dataset:
|
1594 |
-
type: mteb/amazon_massive_intent
|
1595 |
-
name: MTEB MassiveIntentClassification (en)
|
1596 |
-
config: en
|
1597 |
-
split: test
|
1598 |
-
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
1599 |
-
metrics:
|
1600 |
-
- type: accuracy
|
1601 |
-
value: 67.48486886348351
|
1602 |
-
- type: f1
|
1603 |
-
value: 64.92199176095157
|
1604 |
-
- task:
|
1605 |
-
type: Classification
|
1606 |
-
dataset:
|
1607 |
-
type: mteb/amazon_massive_scenario
|
1608 |
-
name: MTEB MassiveScenarioClassification (en)
|
1609 |
-
config: en
|
1610 |
-
split: test
|
1611 |
-
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
1612 |
-
metrics:
|
1613 |
-
- type: accuracy
|
1614 |
-
value: 72.59246805648958
|
1615 |
-
- type: f1
|
1616 |
-
value: 72.1222026389164
|
1617 |
-
- task:
|
1618 |
-
type: Clustering
|
1619 |
-
dataset:
|
1620 |
-
type: mteb/medrxiv-clustering-p2p
|
1621 |
-
name: MTEB MedrxivClusteringP2P
|
1622 |
-
config: default
|
1623 |
-
split: test
|
1624 |
-
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
1625 |
-
metrics:
|
1626 |
-
- type: v_measure
|
1627 |
-
value: 30.887642595096825
|
1628 |
-
- task:
|
1629 |
-
type: Clustering
|
1630 |
-
dataset:
|
1631 |
-
type: mteb/medrxiv-clustering-s2s
|
1632 |
-
name: MTEB MedrxivClusteringS2S
|
1633 |
-
config: default
|
1634 |
-
split: test
|
1635 |
-
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
1636 |
-
metrics:
|
1637 |
-
- type: v_measure
|
1638 |
-
value: 28.3764418784054
|
1639 |
-
- task:
|
1640 |
-
type: Reranking
|
1641 |
-
dataset:
|
1642 |
-
type: mteb/mind_small
|
1643 |
-
name: MTEB MindSmallReranking
|
1644 |
-
config: default
|
1645 |
-
split: test
|
1646 |
-
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
1647 |
-
metrics:
|
1648 |
-
- type: map
|
1649 |
-
value: 31.81544126336991
|
1650 |
-
- type: mrr
|
1651 |
-
value: 32.82666576268031
|
1652 |
-
- task:
|
1653 |
-
type: Retrieval
|
1654 |
-
dataset:
|
1655 |
-
type: nfcorpus
|
1656 |
-
name: MTEB NFCorpus
|
1657 |
-
config: default
|
1658 |
-
split: test
|
1659 |
-
revision: None
|
1660 |
-
metrics:
|
1661 |
-
- type: map_at_1
|
1662 |
-
value: 5.185
|
1663 |
-
- type: map_at_10
|
1664 |
-
value: 11.158
|
1665 |
-
- type: map_at_100
|
1666 |
-
value: 14.041
|
1667 |
-
- type: map_at_1000
|
1668 |
-
value: 15.360999999999999
|
1669 |
-
- type: map_at_3
|
1670 |
-
value: 8.417
|
1671 |
-
- type: map_at_5
|
1672 |
-
value: 9.378
|
1673 |
-
- type: mrr_at_1
|
1674 |
-
value: 44.582
|
1675 |
-
- type: mrr_at_10
|
1676 |
-
value: 53.083999999999996
|
1677 |
-
- type: mrr_at_100
|
1678 |
-
value: 53.787
|
1679 |
-
- type: mrr_at_1000
|
1680 |
-
value: 53.824000000000005
|
1681 |
-
- type: mrr_at_3
|
1682 |
-
value: 51.187000000000005
|
1683 |
-
- type: mrr_at_5
|
1684 |
-
value: 52.379
|
1685 |
-
- type: ndcg_at_1
|
1686 |
-
value: 42.57
|
1687 |
-
- type: ndcg_at_10
|
1688 |
-
value: 31.593
|
1689 |
-
- type: ndcg_at_100
|
1690 |
-
value: 29.093999999999998
|
1691 |
-
- type: ndcg_at_1000
|
1692 |
-
value: 37.909
|
1693 |
-
- type: ndcg_at_3
|
1694 |
-
value: 37.083
|
1695 |
-
- type: ndcg_at_5
|
1696 |
-
value: 34.397
|
1697 |
-
- type: precision_at_1
|
1698 |
-
value: 43.963
|
1699 |
-
- type: precision_at_10
|
1700 |
-
value: 23.498
|
1701 |
-
- type: precision_at_100
|
1702 |
-
value: 7.6160000000000005
|
1703 |
-
- type: precision_at_1000
|
1704 |
-
value: 2.032
|
1705 |
-
- type: precision_at_3
|
1706 |
-
value: 34.572
|
1707 |
-
- type: precision_at_5
|
1708 |
-
value: 29.412
|
1709 |
-
- type: recall_at_1
|
1710 |
-
value: 5.185
|
1711 |
-
- type: recall_at_10
|
1712 |
-
value: 15.234
|
1713 |
-
- type: recall_at_100
|
1714 |
-
value: 29.49
|
1715 |
-
- type: recall_at_1000
|
1716 |
-
value: 62.273999999999994
|
1717 |
-
- type: recall_at_3
|
1718 |
-
value: 9.55
|
1719 |
-
- type: recall_at_5
|
1720 |
-
value: 11.103
|
1721 |
-
- task:
|
1722 |
-
type: Retrieval
|
1723 |
-
dataset:
|
1724 |
-
type: nq
|
1725 |
-
name: MTEB NQ
|
1726 |
-
config: default
|
1727 |
-
split: test
|
1728 |
-
revision: None
|
1729 |
-
metrics:
|
1730 |
-
- type: map_at_1
|
1731 |
-
value: 23.803
|
1732 |
-
- type: map_at_10
|
1733 |
-
value: 38.183
|
1734 |
-
- type: map_at_100
|
1735 |
-
value: 39.421
|
1736 |
-
- type: map_at_1000
|
1737 |
-
value: 39.464
|
1738 |
-
- type: map_at_3
|
1739 |
-
value: 33.835
|
1740 |
-
- type: map_at_5
|
1741 |
-
value: 36.327
|
1742 |
-
- type: mrr_at_1
|
1743 |
-
value: 26.68
|
1744 |
-
- type: mrr_at_10
|
1745 |
-
value: 40.439
|
1746 |
-
- type: mrr_at_100
|
1747 |
-
value: 41.415
|
1748 |
-
- type: mrr_at_1000
|
1749 |
-
value: 41.443999999999996
|
1750 |
-
- type: mrr_at_3
|
1751 |
-
value: 36.612
|
1752 |
-
- type: mrr_at_5
|
1753 |
-
value: 38.877
|
1754 |
-
- type: ndcg_at_1
|
1755 |
-
value: 26.68
|
1756 |
-
- type: ndcg_at_10
|
1757 |
-
value: 45.882
|
1758 |
-
- type: ndcg_at_100
|
1759 |
-
value: 51.227999999999994
|
1760 |
-
- type: ndcg_at_1000
|
1761 |
-
value: 52.207
|
1762 |
-
- type: ndcg_at_3
|
1763 |
-
value: 37.511
|
1764 |
-
- type: ndcg_at_5
|
1765 |
-
value: 41.749
|
1766 |
-
- type: precision_at_1
|
1767 |
-
value: 26.68
|
1768 |
-
- type: precision_at_10
|
1769 |
-
value: 7.9750000000000005
|
1770 |
-
- type: precision_at_100
|
1771 |
-
value: 1.0959999999999999
|
1772 |
-
- type: precision_at_1000
|
1773 |
-
value: 0.11900000000000001
|
1774 |
-
- type: precision_at_3
|
1775 |
-
value: 17.449
|
1776 |
-
- type: precision_at_5
|
1777 |
-
value: 12.897
|
1778 |
-
- type: recall_at_1
|
1779 |
-
value: 23.803
|
1780 |
-
- type: recall_at_10
|
1781 |
-
value: 67.152
|
1782 |
-
- type: recall_at_100
|
1783 |
-
value: 90.522
|
1784 |
-
- type: recall_at_1000
|
1785 |
-
value: 97.743
|
1786 |
-
- type: recall_at_3
|
1787 |
-
value: 45.338
|
1788 |
-
- type: recall_at_5
|
1789 |
-
value: 55.106
|
1790 |
-
- task:
|
1791 |
-
type: Retrieval
|
1792 |
-
dataset:
|
1793 |
-
type: quora
|
1794 |
-
name: MTEB QuoraRetrieval
|
1795 |
-
config: default
|
1796 |
-
split: test
|
1797 |
-
revision: None
|
1798 |
-
metrics:
|
1799 |
-
- type: map_at_1
|
1800 |
-
value: 70.473
|
1801 |
-
- type: map_at_10
|
1802 |
-
value: 84.452
|
1803 |
-
- type: map_at_100
|
1804 |
-
value: 85.101
|
1805 |
-
- type: map_at_1000
|
1806 |
-
value: 85.115
|
1807 |
-
- type: map_at_3
|
1808 |
-
value: 81.435
|
1809 |
-
- type: map_at_5
|
1810 |
-
value: 83.338
|
1811 |
-
- type: mrr_at_1
|
1812 |
-
value: 81.19
|
1813 |
-
- type: mrr_at_10
|
1814 |
-
value: 87.324
|
1815 |
-
- type: mrr_at_100
|
1816 |
-
value: 87.434
|
1817 |
-
- type: mrr_at_1000
|
1818 |
-
value: 87.435
|
1819 |
-
- type: mrr_at_3
|
1820 |
-
value: 86.31
|
1821 |
-
- type: mrr_at_5
|
1822 |
-
value: 87.002
|
1823 |
-
- type: ndcg_at_1
|
1824 |
-
value: 81.21000000000001
|
1825 |
-
- type: ndcg_at_10
|
1826 |
-
value: 88.19
|
1827 |
-
- type: ndcg_at_100
|
1828 |
-
value: 89.44
|
1829 |
-
- type: ndcg_at_1000
|
1830 |
-
value: 89.526
|
1831 |
-
- type: ndcg_at_3
|
1832 |
-
value: 85.237
|
1833 |
-
- type: ndcg_at_5
|
1834 |
-
value: 86.892
|
1835 |
-
- type: precision_at_1
|
1836 |
-
value: 81.21000000000001
|
1837 |
-
- type: precision_at_10
|
1838 |
-
value: 13.417000000000002
|
1839 |
-
- type: precision_at_100
|
1840 |
-
value: 1.537
|
1841 |
-
- type: precision_at_1000
|
1842 |
-
value: 0.157
|
1843 |
-
- type: precision_at_3
|
1844 |
-
value: 37.31
|
1845 |
-
- type: precision_at_5
|
1846 |
-
value: 24.59
|
1847 |
-
- type: recall_at_1
|
1848 |
-
value: 70.473
|
1849 |
-
- type: recall_at_10
|
1850 |
-
value: 95.367
|
1851 |
-
- type: recall_at_100
|
1852 |
-
value: 99.616
|
1853 |
-
- type: recall_at_1000
|
1854 |
-
value: 99.996
|
1855 |
-
- type: recall_at_3
|
1856 |
-
value: 86.936
|
1857 |
-
- type: recall_at_5
|
1858 |
-
value: 91.557
|
1859 |
-
- task:
|
1860 |
-
type: Clustering
|
1861 |
-
dataset:
|
1862 |
-
type: mteb/reddit-clustering
|
1863 |
-
name: MTEB RedditClustering
|
1864 |
-
config: default
|
1865 |
-
split: test
|
1866 |
-
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
1867 |
-
metrics:
|
1868 |
-
- type: v_measure
|
1869 |
-
value: 59.25776525253911
|
1870 |
-
- task:
|
1871 |
-
type: Clustering
|
1872 |
-
dataset:
|
1873 |
-
type: mteb/reddit-clustering-p2p
|
1874 |
-
name: MTEB RedditClusteringP2P
|
1875 |
-
config: default
|
1876 |
-
split: test
|
1877 |
-
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
1878 |
-
metrics:
|
1879 |
-
- type: v_measure
|
1880 |
-
value: 63.22135271663078
|
1881 |
-
- task:
|
1882 |
-
type: Retrieval
|
1883 |
-
dataset:
|
1884 |
-
type: scidocs
|
1885 |
-
name: MTEB SCIDOCS
|
1886 |
-
config: default
|
1887 |
-
split: test
|
1888 |
-
revision: None
|
1889 |
-
metrics:
|
1890 |
-
- type: map_at_1
|
1891 |
-
value: 4.003
|
1892 |
-
- type: map_at_10
|
1893 |
-
value: 10.062999999999999
|
1894 |
-
- type: map_at_100
|
1895 |
-
value: 11.854000000000001
|
1896 |
-
- type: map_at_1000
|
1897 |
-
value: 12.145999999999999
|
1898 |
-
- type: map_at_3
|
1899 |
-
value: 7.242
|
1900 |
-
- type: map_at_5
|
1901 |
-
value: 8.652999999999999
|
1902 |
-
- type: mrr_at_1
|
1903 |
-
value: 19.7
|
1904 |
-
- type: mrr_at_10
|
1905 |
-
value: 29.721999999999998
|
1906 |
-
- type: mrr_at_100
|
1907 |
-
value: 30.867
|
1908 |
-
- type: mrr_at_1000
|
1909 |
-
value: 30.944
|
1910 |
-
- type: mrr_at_3
|
1911 |
-
value: 26.683
|
1912 |
-
- type: mrr_at_5
|
1913 |
-
value: 28.498
|
1914 |
-
- type: ndcg_at_1
|
1915 |
-
value: 19.7
|
1916 |
-
- type: ndcg_at_10
|
1917 |
-
value: 17.095
|
1918 |
-
- type: ndcg_at_100
|
1919 |
-
value: 24.375
|
1920 |
-
- type: ndcg_at_1000
|
1921 |
-
value: 29.831000000000003
|
1922 |
-
- type: ndcg_at_3
|
1923 |
-
value: 16.305
|
1924 |
-
- type: ndcg_at_5
|
1925 |
-
value: 14.291
|
1926 |
-
- type: precision_at_1
|
1927 |
-
value: 19.7
|
1928 |
-
- type: precision_at_10
|
1929 |
-
value: 8.799999999999999
|
1930 |
-
- type: precision_at_100
|
1931 |
-
value: 1.9349999999999998
|
1932 |
-
- type: precision_at_1000
|
1933 |
-
value: 0.32399999999999995
|
1934 |
-
- type: precision_at_3
|
1935 |
-
value: 15.2
|
1936 |
-
- type: precision_at_5
|
1937 |
-
value: 12.540000000000001
|
1938 |
-
- type: recall_at_1
|
1939 |
-
value: 4.003
|
1940 |
-
- type: recall_at_10
|
1941 |
-
value: 17.877000000000002
|
1942 |
-
- type: recall_at_100
|
1943 |
-
value: 39.217
|
1944 |
-
- type: recall_at_1000
|
1945 |
-
value: 65.862
|
1946 |
-
- type: recall_at_3
|
1947 |
-
value: 9.242
|
1948 |
-
- type: recall_at_5
|
1949 |
-
value: 12.715000000000002
|
1950 |
-
- task:
|
1951 |
-
type: STS
|
1952 |
-
dataset:
|
1953 |
-
type: mteb/sickr-sts
|
1954 |
-
name: MTEB SICK-R
|
1955 |
-
config: default
|
1956 |
-
split: test
|
1957 |
-
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1958 |
-
metrics:
|
1959 |
-
- type: cos_sim_spearman
|
1960 |
-
value: 80.25888668589654
|
1961 |
-
- task:
|
1962 |
-
type: STS
|
1963 |
-
dataset:
|
1964 |
-
type: mteb/sts12-sts
|
1965 |
-
name: MTEB STS12
|
1966 |
-
config: default
|
1967 |
-
split: test
|
1968 |
-
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1969 |
-
metrics:
|
1970 |
-
- type: cos_sim_spearman
|
1971 |
-
value: 77.02037527837669
|
1972 |
-
- task:
|
1973 |
-
type: STS
|
1974 |
-
dataset:
|
1975 |
-
type: mteb/sts13-sts
|
1976 |
-
name: MTEB STS13
|
1977 |
-
config: default
|
1978 |
-
split: test
|
1979 |
-
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
1980 |
-
metrics:
|
1981 |
-
- type: cos_sim_spearman
|
1982 |
-
value: 86.58432681008449
|
1983 |
-
- task:
|
1984 |
-
type: STS
|
1985 |
-
dataset:
|
1986 |
-
type: mteb/sts14-sts
|
1987 |
-
name: MTEB STS14
|
1988 |
-
config: default
|
1989 |
-
split: test
|
1990 |
-
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
1991 |
-
metrics:
|
1992 |
-
- type: cos_sim_spearman
|
1993 |
-
value: 81.31697756099051
|
1994 |
-
- task:
|
1995 |
-
type: STS
|
1996 |
-
dataset:
|
1997 |
-
type: mteb/sts15-sts
|
1998 |
-
name: MTEB STS15
|
1999 |
-
config: default
|
2000 |
-
split: test
|
2001 |
-
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
2002 |
-
metrics:
|
2003 |
-
- type: cos_sim_spearman
|
2004 |
-
value: 88.18867599667057
|
2005 |
-
- task:
|
2006 |
-
type: STS
|
2007 |
-
dataset:
|
2008 |
-
type: mteb/sts16-sts
|
2009 |
-
name: MTEB STS16
|
2010 |
-
config: default
|
2011 |
-
split: test
|
2012 |
-
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
2013 |
-
metrics:
|
2014 |
-
- type: cos_sim_spearman
|
2015 |
-
value: 84.87853941747623
|
2016 |
-
- task:
|
2017 |
-
type: STS
|
2018 |
-
dataset:
|
2019 |
-
type: mteb/sts17-crosslingual-sts
|
2020 |
-
name: MTEB STS17 (en-en)
|
2021 |
-
config: en-en
|
2022 |
-
split: test
|
2023 |
-
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
2024 |
-
metrics:
|
2025 |
-
- type: cos_sim_spearman
|
2026 |
-
value: 89.46479925383916
|
2027 |
-
- task:
|
2028 |
-
type: STS
|
2029 |
-
dataset:
|
2030 |
-
type: mteb/sts22-crosslingual-sts
|
2031 |
-
name: MTEB STS22 (en)
|
2032 |
-
config: en
|
2033 |
-
split: test
|
2034 |
-
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
2035 |
-
metrics:
|
2036 |
-
- type: cos_sim_spearman
|
2037 |
-
value: 66.45272113649146
|
2038 |
-
- task:
|
2039 |
-
type: STS
|
2040 |
-
dataset:
|
2041 |
-
type: mteb/stsbenchmark-sts
|
2042 |
-
name: MTEB STSBenchmark
|
2043 |
-
config: default
|
2044 |
-
split: test
|
2045 |
-
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
2046 |
-
metrics:
|
2047 |
-
- type: cos_sim_spearman
|
2048 |
-
value: 86.43357313527851
|
2049 |
-
- task:
|
2050 |
-
type: Reranking
|
2051 |
-
dataset:
|
2052 |
-
type: mteb/scidocs-reranking
|
2053 |
-
name: MTEB SciDocsRR
|
2054 |
-
config: default
|
2055 |
-
split: test
|
2056 |
-
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
2057 |
-
metrics:
|
2058 |
-
- type: map
|
2059 |
-
value: 78.82761687254882
|
2060 |
-
- type: mrr
|
2061 |
-
value: 93.46223674655047
|
2062 |
-
- task:
|
2063 |
-
type: Retrieval
|
2064 |
-
dataset:
|
2065 |
-
type: scifact
|
2066 |
-
name: MTEB SciFact
|
2067 |
-
config: default
|
2068 |
-
split: test
|
2069 |
-
revision: None
|
2070 |
-
metrics:
|
2071 |
-
- type: map_at_1
|
2072 |
-
value: 44.583
|
2073 |
-
- type: map_at_10
|
2074 |
-
value: 52.978
|
2075 |
-
- type: map_at_100
|
2076 |
-
value: 53.803
|
2077 |
-
- type: map_at_1000
|
2078 |
-
value: 53.839999999999996
|
2079 |
-
- type: map_at_3
|
2080 |
-
value: 50.03300000000001
|
2081 |
-
- type: map_at_5
|
2082 |
-
value: 51.939
|
2083 |
-
- type: mrr_at_1
|
2084 |
-
value: 47.0
|
2085 |
-
- type: mrr_at_10
|
2086 |
-
value: 54.730000000000004
|
2087 |
-
- type: mrr_at_100
|
2088 |
-
value: 55.31399999999999
|
2089 |
-
- type: mrr_at_1000
|
2090 |
-
value: 55.346
|
2091 |
-
- type: mrr_at_3
|
2092 |
-
value: 52.0
|
2093 |
-
- type: mrr_at_5
|
2094 |
-
value: 53.783
|
2095 |
-
- type: ndcg_at_1
|
2096 |
-
value: 47.0
|
2097 |
-
- type: ndcg_at_10
|
2098 |
-
value: 57.82899999999999
|
2099 |
-
- type: ndcg_at_100
|
2100 |
-
value: 61.49400000000001
|
2101 |
-
- type: ndcg_at_1000
|
2102 |
-
value: 62.676
|
2103 |
-
- type: ndcg_at_3
|
2104 |
-
value: 52.373000000000005
|
2105 |
-
- type: ndcg_at_5
|
2106 |
-
value: 55.481
|
2107 |
-
- type: precision_at_1
|
2108 |
-
value: 47.0
|
2109 |
-
- type: precision_at_10
|
2110 |
-
value: 7.867
|
2111 |
-
- type: precision_at_100
|
2112 |
-
value: 0.997
|
2113 |
-
- type: precision_at_1000
|
2114 |
-
value: 0.11
|
2115 |
-
- type: precision_at_3
|
2116 |
-
value: 20.556
|
2117 |
-
- type: precision_at_5
|
2118 |
-
value: 14.066999999999998
|
2119 |
-
- type: recall_at_1
|
2120 |
-
value: 44.583
|
2121 |
-
- type: recall_at_10
|
2122 |
-
value: 71.172
|
2123 |
-
- type: recall_at_100
|
2124 |
-
value: 87.7
|
2125 |
-
- type: recall_at_1000
|
2126 |
-
value: 97.333
|
2127 |
-
- type: recall_at_3
|
2128 |
-
value: 56.511
|
2129 |
-
- type: recall_at_5
|
2130 |
-
value: 64.206
|
2131 |
-
- task:
|
2132 |
-
type: PairClassification
|
2133 |
-
dataset:
|
2134 |
-
type: mteb/sprintduplicatequestions-pairclassification
|
2135 |
-
name: MTEB SprintDuplicateQuestions
|
2136 |
-
config: default
|
2137 |
-
split: test
|
2138 |
-
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
2139 |
-
metrics:
|
2140 |
-
- type: cos_sim_accuracy
|
2141 |
-
value: 99.66237623762376
|
2142 |
-
- type: cos_sim_ap
|
2143 |
-
value: 90.35465126226322
|
2144 |
-
- type: cos_sim_f1
|
2145 |
-
value: 82.44575936883628
|
2146 |
-
- type: cos_sim_precision
|
2147 |
-
value: 81.32295719844358
|
2148 |
-
- type: cos_sim_recall
|
2149 |
-
value: 83.6
|
2150 |
-
- type: dot_accuracy
|
2151 |
-
value: 99.66237623762376
|
2152 |
-
- type: dot_ap
|
2153 |
-
value: 90.35464287920453
|
2154 |
-
- type: dot_f1
|
2155 |
-
value: 82.44575936883628
|
2156 |
-
- type: dot_precision
|
2157 |
-
value: 81.32295719844358
|
2158 |
-
- type: dot_recall
|
2159 |
-
value: 83.6
|
2160 |
-
- type: euclidean_accuracy
|
2161 |
-
value: 99.66237623762376
|
2162 |
-
- type: euclidean_ap
|
2163 |
-
value: 90.3546512622632
|
2164 |
-
- type: euclidean_f1
|
2165 |
-
value: 82.44575936883628
|
2166 |
-
- type: euclidean_precision
|
2167 |
-
value: 81.32295719844358
|
2168 |
-
- type: euclidean_recall
|
2169 |
-
value: 83.6
|
2170 |
-
- type: manhattan_accuracy
|
2171 |
-
value: 99.65940594059406
|
2172 |
-
- type: manhattan_ap
|
2173 |
-
value: 90.29220174849843
|
2174 |
-
- type: manhattan_f1
|
2175 |
-
value: 82.4987605354487
|
2176 |
-
- type: manhattan_precision
|
2177 |
-
value: 81.80924287118977
|
2178 |
-
- type: manhattan_recall
|
2179 |
-
value: 83.2
|
2180 |
-
- type: max_accuracy
|
2181 |
-
value: 99.66237623762376
|
2182 |
-
- type: max_ap
|
2183 |
-
value: 90.35465126226322
|
2184 |
-
- type: max_f1
|
2185 |
-
value: 82.4987605354487
|
2186 |
-
- task:
|
2187 |
-
type: Clustering
|
2188 |
-
dataset:
|
2189 |
-
type: mteb/stackexchange-clustering
|
2190 |
-
name: MTEB StackExchangeClustering
|
2191 |
-
config: default
|
2192 |
-
split: test
|
2193 |
-
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
2194 |
-
metrics:
|
2195 |
-
- type: v_measure
|
2196 |
-
value: 65.0394225901397
|
2197 |
-
- task:
|
2198 |
-
type: Clustering
|
2199 |
-
dataset:
|
2200 |
-
type: mteb/stackexchange-clustering-p2p
|
2201 |
-
name: MTEB StackExchangeClusteringP2P
|
2202 |
-
config: default
|
2203 |
-
split: test
|
2204 |
-
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
2205 |
-
metrics:
|
2206 |
-
- type: v_measure
|
2207 |
-
value: 35.27954189859326
|
2208 |
-
- task:
|
2209 |
-
type: Reranking
|
2210 |
-
dataset:
|
2211 |
-
type: mteb/stackoverflowdupquestions-reranking
|
2212 |
-
name: MTEB StackOverflowDupQuestions
|
2213 |
-
config: default
|
2214 |
-
split: test
|
2215 |
-
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
2216 |
-
metrics:
|
2217 |
-
- type: map
|
2218 |
-
value: 50.99055979974896
|
2219 |
-
- type: mrr
|
2220 |
-
value: 51.82745257193787
|
2221 |
-
- task:
|
2222 |
-
type: Summarization
|
2223 |
-
dataset:
|
2224 |
-
type: mteb/summeval
|
2225 |
-
name: MTEB SummEval
|
2226 |
-
config: default
|
2227 |
-
split: test
|
2228 |
-
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
2229 |
-
metrics:
|
2230 |
-
- type: cos_sim_pearson
|
2231 |
-
value: 30.21655465344237
|
2232 |
-
- type: cos_sim_spearman
|
2233 |
-
value: 29.853205339630172
|
2234 |
-
- type: dot_pearson
|
2235 |
-
value: 30.216540628083564
|
2236 |
-
- type: dot_spearman
|
2237 |
-
value: 29.868978894753027
|
2238 |
-
- task:
|
2239 |
-
type: Retrieval
|
2240 |
-
dataset:
|
2241 |
-
type: trec-covid
|
2242 |
-
name: MTEB TRECCOVID
|
2243 |
-
config: default
|
2244 |
-
split: test
|
2245 |
-
revision: None
|
2246 |
-
metrics:
|
2247 |
-
- type: map_at_1
|
2248 |
-
value: 0.2
|
2249 |
-
- type: map_at_10
|
2250 |
-
value: 1.398
|
2251 |
-
- type: map_at_100
|
2252 |
-
value: 7.406
|
2253 |
-
- type: map_at_1000
|
2254 |
-
value: 18.401
|
2255 |
-
- type: map_at_3
|
2256 |
-
value: 0.479
|
2257 |
-
- type: map_at_5
|
2258 |
-
value: 0.772
|
2259 |
-
- type: mrr_at_1
|
2260 |
-
value: 70.0
|
2261 |
-
- type: mrr_at_10
|
2262 |
-
value: 79.25999999999999
|
2263 |
-
- type: mrr_at_100
|
2264 |
-
value: 79.25999999999999
|
2265 |
-
- type: mrr_at_1000
|
2266 |
-
value: 79.25999999999999
|
2267 |
-
- type: mrr_at_3
|
2268 |
-
value: 77.333
|
2269 |
-
- type: mrr_at_5
|
2270 |
-
value: 78.133
|
2271 |
-
- type: ndcg_at_1
|
2272 |
-
value: 63.0
|
2273 |
-
- type: ndcg_at_10
|
2274 |
-
value: 58.548
|
2275 |
-
- type: ndcg_at_100
|
2276 |
-
value: 45.216
|
2277 |
-
- type: ndcg_at_1000
|
2278 |
-
value: 41.149
|
2279 |
-
- type: ndcg_at_3
|
2280 |
-
value: 60.641999999999996
|
2281 |
-
- type: ndcg_at_5
|
2282 |
-
value: 61.135
|
2283 |
-
- type: precision_at_1
|
2284 |
-
value: 70.0
|
2285 |
-
- type: precision_at_10
|
2286 |
-
value: 64.0
|
2287 |
-
- type: precision_at_100
|
2288 |
-
value: 46.92
|
2289 |
-
- type: precision_at_1000
|
2290 |
-
value: 18.642
|
2291 |
-
- type: precision_at_3
|
2292 |
-
value: 64.667
|
2293 |
-
- type: precision_at_5
|
2294 |
-
value: 66.4
|
2295 |
-
- type: recall_at_1
|
2296 |
-
value: 0.2
|
2297 |
-
- type: recall_at_10
|
2298 |
-
value: 1.6729999999999998
|
2299 |
-
- type: recall_at_100
|
2300 |
-
value: 10.856
|
2301 |
-
- type: recall_at_1000
|
2302 |
-
value: 38.964999999999996
|
2303 |
-
- type: recall_at_3
|
2304 |
-
value: 0.504
|
2305 |
-
- type: recall_at_5
|
2306 |
-
value: 0.852
|
2307 |
-
- task:
|
2308 |
-
type: Retrieval
|
2309 |
-
dataset:
|
2310 |
-
type: webis-touche2020
|
2311 |
-
name: MTEB Touche2020
|
2312 |
-
config: default
|
2313 |
-
split: test
|
2314 |
-
revision: None
|
2315 |
-
metrics:
|
2316 |
-
- type: map_at_1
|
2317 |
-
value: 1.6629999999999998
|
2318 |
-
- type: map_at_10
|
2319 |
-
value: 8.601
|
2320 |
-
- type: map_at_100
|
2321 |
-
value: 14.354
|
2322 |
-
- type: map_at_1000
|
2323 |
-
value: 15.927
|
2324 |
-
- type: map_at_3
|
2325 |
-
value: 4.1930000000000005
|
2326 |
-
- type: map_at_5
|
2327 |
-
value: 5.655
|
2328 |
-
- type: mrr_at_1
|
2329 |
-
value: 18.367
|
2330 |
-
- type: mrr_at_10
|
2331 |
-
value: 34.466
|
2332 |
-
- type: mrr_at_100
|
2333 |
-
value: 35.235
|
2334 |
-
- type: mrr_at_1000
|
2335 |
-
value: 35.27
|
2336 |
-
- type: mrr_at_3
|
2337 |
-
value: 28.571
|
2338 |
-
- type: mrr_at_5
|
2339 |
-
value: 31.531
|
2340 |
-
- type: ndcg_at_1
|
2341 |
-
value: 14.285999999999998
|
2342 |
-
- type: ndcg_at_10
|
2343 |
-
value: 20.374
|
2344 |
-
- type: ndcg_at_100
|
2345 |
-
value: 33.532000000000004
|
2346 |
-
- type: ndcg_at_1000
|
2347 |
-
value: 45.561
|
2348 |
-
- type: ndcg_at_3
|
2349 |
-
value: 18.442
|
2350 |
-
- type: ndcg_at_5
|
2351 |
-
value: 18.076
|
2352 |
-
- type: precision_at_1
|
2353 |
-
value: 18.367
|
2354 |
-
- type: precision_at_10
|
2355 |
-
value: 20.204
|
2356 |
-
- type: precision_at_100
|
2357 |
-
value: 7.489999999999999
|
2358 |
-
- type: precision_at_1000
|
2359 |
-
value: 1.5630000000000002
|
2360 |
-
- type: precision_at_3
|
2361 |
-
value: 21.769
|
2362 |
-
- type: precision_at_5
|
2363 |
-
value: 20.408
|
2364 |
-
- type: recall_at_1
|
2365 |
-
value: 1.6629999999999998
|
2366 |
-
- type: recall_at_10
|
2367 |
-
value: 15.549
|
2368 |
-
- type: recall_at_100
|
2369 |
-
value: 47.497
|
2370 |
-
- type: recall_at_1000
|
2371 |
-
value: 84.524
|
2372 |
-
- type: recall_at_3
|
2373 |
-
value: 5.289
|
2374 |
-
- type: recall_at_5
|
2375 |
-
value: 8.035
|
2376 |
-
- task:
|
2377 |
-
type: Classification
|
2378 |
-
dataset:
|
2379 |
-
type: mteb/toxic_conversations_50k
|
2380 |
-
name: MTEB ToxicConversationsClassification
|
2381 |
-
config: default
|
2382 |
-
split: test
|
2383 |
-
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
2384 |
-
metrics:
|
2385 |
-
- type: accuracy
|
2386 |
-
value: 71.8194
|
2387 |
-
- type: ap
|
2388 |
-
value: 14.447702451658554
|
2389 |
-
- type: f1
|
2390 |
-
value: 55.13659412856185
|
2391 |
-
- task:
|
2392 |
-
type: Classification
|
2393 |
-
dataset:
|
2394 |
-
type: mteb/tweet_sentiment_extraction
|
2395 |
-
name: MTEB TweetSentimentExtractionClassification
|
2396 |
-
config: default
|
2397 |
-
split: test
|
2398 |
-
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
2399 |
-
metrics:
|
2400 |
-
- type: accuracy
|
2401 |
-
value: 63.310696095076416
|
2402 |
-
- type: f1
|
2403 |
-
value: 63.360434851097814
|
2404 |
-
- task:
|
2405 |
-
type: Clustering
|
2406 |
-
dataset:
|
2407 |
-
type: mteb/twentynewsgroups-clustering
|
2408 |
-
name: MTEB TwentyNewsgroupsClustering
|
2409 |
-
config: default
|
2410 |
-
split: test
|
2411 |
-
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
2412 |
-
metrics:
|
2413 |
-
- type: v_measure
|
2414 |
-
value: 51.30677907335145
|
2415 |
-
- task:
|
2416 |
-
type: PairClassification
|
2417 |
-
dataset:
|
2418 |
-
type: mteb/twittersemeval2015-pairclassification
|
2419 |
-
name: MTEB TwitterSemEval2015
|
2420 |
-
config: default
|
2421 |
-
split: test
|
2422 |
-
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
2423 |
-
metrics:
|
2424 |
-
- type: cos_sim_accuracy
|
2425 |
-
value: 86.12386004649221
|
2426 |
-
- type: cos_sim_ap
|
2427 |
-
value: 73.99096426215495
|
2428 |
-
- type: cos_sim_f1
|
2429 |
-
value: 68.18416968442834
|
2430 |
-
- type: cos_sim_precision
|
2431 |
-
value: 66.86960933536275
|
2432 |
-
- type: cos_sim_recall
|
2433 |
-
value: 69.55145118733509
|
2434 |
-
- type: dot_accuracy
|
2435 |
-
value: 86.12386004649221
|
2436 |
-
- type: dot_ap
|
2437 |
-
value: 73.99096813038672
|
2438 |
-
- type: dot_f1
|
2439 |
-
value: 68.18416968442834
|
2440 |
-
- type: dot_precision
|
2441 |
-
value: 66.86960933536275
|
2442 |
-
- type: dot_recall
|
2443 |
-
value: 69.55145118733509
|
2444 |
-
- type: euclidean_accuracy
|
2445 |
-
value: 86.12386004649221
|
2446 |
-
- type: euclidean_ap
|
2447 |
-
value: 73.99095984980165
|
2448 |
-
- type: euclidean_f1
|
2449 |
-
value: 68.18416968442834
|
2450 |
-
- type: euclidean_precision
|
2451 |
-
value: 66.86960933536275
|
2452 |
-
- type: euclidean_recall
|
2453 |
-
value: 69.55145118733509
|
2454 |
-
- type: manhattan_accuracy
|
2455 |
-
value: 86.09405734040651
|
2456 |
-
- type: manhattan_ap
|
2457 |
-
value: 73.96825745608601
|
2458 |
-
- type: manhattan_f1
|
2459 |
-
value: 68.13888179729383
|
2460 |
-
- type: manhattan_precision
|
2461 |
-
value: 65.99901088031652
|
2462 |
-
- type: manhattan_recall
|
2463 |
-
value: 70.42216358839049
|
2464 |
-
- type: max_accuracy
|
2465 |
-
value: 86.12386004649221
|
2466 |
-
- type: max_ap
|
2467 |
-
value: 73.99096813038672
|
2468 |
-
- type: max_f1
|
2469 |
-
value: 68.18416968442834
|
2470 |
-
- task:
|
2471 |
-
type: PairClassification
|
2472 |
-
dataset:
|
2473 |
-
type: mteb/twitterurlcorpus-pairclassification
|
2474 |
-
name: MTEB TwitterURLCorpus
|
2475 |
-
config: default
|
2476 |
-
split: test
|
2477 |
-
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
2478 |
-
metrics:
|
2479 |
-
- type: cos_sim_accuracy
|
2480 |
-
value: 88.99367407924865
|
2481 |
-
- type: cos_sim_ap
|
2482 |
-
value: 86.19720829843081
|
2483 |
-
- type: cos_sim_f1
|
2484 |
-
value: 78.39889075384951
|
2485 |
-
- type: cos_sim_precision
|
2486 |
-
value: 74.5110278818144
|
2487 |
-
- type: cos_sim_recall
|
2488 |
-
value: 82.71481367416075
|
2489 |
-
- type: dot_accuracy
|
2490 |
-
value: 88.99367407924865
|
2491 |
-
- type: dot_ap
|
2492 |
-
value: 86.19718471454047
|
2493 |
-
- type: dot_f1
|
2494 |
-
value: 78.39889075384951
|
2495 |
-
- type: dot_precision
|
2496 |
-
value: 74.5110278818144
|
2497 |
-
- type: dot_recall
|
2498 |
-
value: 82.71481367416075
|
2499 |
-
- type: euclidean_accuracy
|
2500 |
-
value: 88.99367407924865
|
2501 |
-
- type: euclidean_ap
|
2502 |
-
value: 86.1972021422436
|
2503 |
-
- type: euclidean_f1
|
2504 |
-
value: 78.39889075384951
|
2505 |
-
- type: euclidean_precision
|
2506 |
-
value: 74.5110278818144
|
2507 |
-
- type: euclidean_recall
|
2508 |
-
value: 82.71481367416075
|
2509 |
-
- type: manhattan_accuracy
|
2510 |
-
value: 88.95680521597392
|
2511 |
-
- type: manhattan_ap
|
2512 |
-
value: 86.16659921351506
|
2513 |
-
- type: manhattan_f1
|
2514 |
-
value: 78.39125971550081
|
2515 |
-
- type: manhattan_precision
|
2516 |
-
value: 74.82502799552073
|
2517 |
-
- type: manhattan_recall
|
2518 |
-
value: 82.31444410224823
|
2519 |
-
- type: max_accuracy
|
2520 |
-
value: 88.99367407924865
|
2521 |
-
- type: max_ap
|
2522 |
-
value: 86.19720829843081
|
2523 |
-
- type: max_f1
|
2524 |
-
value: 78.39889075384951
|
2525 |
---
|
|
|
2526 |
# pascalhuerten/instructor-skillfit
|
2527 |
A finetuning of hkunlp/instructor-base specialized on performing retrival of relevant skills based on a given learning outcome.
|
2528 |
|
|
|
24 |
- fever
|
25 |
- hotpot_qa
|
26 |
- mteb
|
27 |
+
language:
|
28 |
+
- en
|
29 |
+
- de
|
30 |
inference: false
|
31 |
license: apache-2.0
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32 |
---
|
33 |
+
|
34 |
# pascalhuerten/instructor-skillfit
|
35 |
A finetuning of hkunlp/instructor-base specialized on performing retrival of relevant skills based on a given learning outcome.
|
36 |
|