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granite-embedding-125m-english-GGUF

Text Generation
GGUF
English
language
granite
embeddings
Eval Results
Inference Endpoints
feature-extraction
Model card Files Community
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  ---
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  quantized_by: bartowski
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  pipeline_tag: text-generation
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- language:
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- - en
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- tags:
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- - language
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- - granite
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- - embeddings
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- license: apache-2.0
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- base_model: ibm-granite/granite-embedding-125m-english
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- model-index:
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- - name: ibm-granite/granite-embedding-125m-english
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- results:
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- - task:
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- type: Retrieval
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- dataset:
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- name: MTEB ArguaAna
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- type: mteb/arguana
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- config: default
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- split: test
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- metrics:
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- - type: map_at_1
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- value: 0.33642
25
- - type: map_at_10
26
- value: 0.49716
27
- - type: map_at_100
28
- value: 0.50519
29
- - type: map_at_1000
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- value: 0.50521
31
- - type: map_at_3
32
- value: 0.45057
33
- - type: map_at_5
34
- value: 0.47774
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- - type: mrr_at_1
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- value: 0.34922
37
- - type: mrr_at_10
38
- value: 0.50197
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- - type: mrr_at_100
40
- value: 0.50992
41
- - type: mrr_at_1000
42
- value: 0.50994
43
- - type: mrr_at_3
44
- value: 0.45484
45
- - type: mrr_at_5
46
- value: 0.48272
47
- - type: ndcg_at_1
48
- value: 0.33642
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- - type: ndcg_at_10
50
- value: 0.58401
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- - type: ndcg_at_100
52
- value: 0.6157
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- - type: ndcg_at_1000
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- value: 0.61608
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- - type: ndcg_at_3
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- value: 0.48825
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- - type: ndcg_at_5
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- value: 0.53689
59
- - type: precision_at_1
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- value: 0.33642
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- - type: precision_at_10
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- value: 0.08606
63
- - type: precision_at_100
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- value: 0.00994
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- - type: precision_at_1000
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- value: 0.001
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- - type: precision_at_3
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- value: 0.19915
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- - type: precision_at_5
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- value: 0.14296
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- - type: recall_at_1
72
- value: 0.33642
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- - type: recall_at_10
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- value: 0.8606
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- - type: recall_at_100
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- value: 0.9936
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- - type: recall_at_1000
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- value: 0.99644
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- - type: recall_at_3
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- value: 0.59744
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- - type: recall_at_5
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- value: 0.71479
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- - task:
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- type: Retrieval
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- dataset:
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- name: MTEB ClimateFEVER
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- type: mteb/climate-fever
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- config: default
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- split: test
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- metrics:
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- - type: map_at_1
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- value: 0.1457
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- - type: map_at_10
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- value: 0.24102
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- - type: map_at_100
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- value: 0.25826
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- - type: map_at_1000
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- value: 0.26021
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- - type: map_at_3
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- value: 0.20346
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- - type: map_at_5
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- value: 0.22228
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- - type: mrr_at_1
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- value: 0.32573
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- - type: mrr_at_10
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- value: 0.44411
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- - type: mrr_at_100
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- value: 0.45176
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- - type: mrr_at_1000
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- value: 0.45209
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- - type: mrr_at_3
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- value: 0.4126
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- - type: mrr_at_5
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- value: 0.43312
115
- - type: ndcg_at_1
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- value: 0.32573
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- - type: ndcg_at_10
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- value: 0.3315
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- - type: ndcg_at_100
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- value: 0.39898
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- - type: ndcg_at_1000
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- value: 0.43151
123
- - type: ndcg_at_3
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- value: 0.27683
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- - type: ndcg_at_5
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- value: 0.29538
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- - type: precision_at_1
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- value: 0.32573
129
- - type: precision_at_10
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- value: 0.10176
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- - type: precision_at_100
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- value: 0.01754
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- - type: precision_at_1000
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- value: 0.00236
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- - type: precision_at_3
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- value: 0.20347
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- - type: precision_at_5
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- value: 0.15505
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- - type: recall_at_1
140
- value: 0.1457
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- - type: recall_at_10
142
- value: 0.38825
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- - type: recall_at_100
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- value: 0.62237
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- - type: recall_at_1000
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- value: 0.8022
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- - type: recall_at_3
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- value: 0.25245
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- - type: recall_at_5
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- value: 0.30821
151
- - task:
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- type: Retrieval
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- dataset:
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- name: MTEB CQADupstackAndroidRetrieval
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- type: mteb/cqadupstack-android
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- config: default
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- split: test
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- metrics:
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- - type: map_at_1
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- value: 0.36964
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- - type: map_at_10
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- value: 0.5043
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- - type: map_at_100
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- value: 0.52066
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- - type: map_at_1000
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- value: 0.52175
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- - type: map_at_3
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- value: 0.46001
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- - type: map_at_5
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- value: 0.48312
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- - type: mrr_at_1
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- value: 0.45923
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- - type: mrr_at_10
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- value: 0.56733
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- - type: mrr_at_100
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- value: 0.57292
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- - type: mrr_at_1000
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- value: 0.57321
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- - type: mrr_at_3
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- value: 0.54053
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- - type: mrr_at_5
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- value: 0.55556
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- - type: ndcg_at_1
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- value: 0.45923
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- - type: ndcg_at_10
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- value: 0.57667
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- - type: ndcg_at_100
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- value: 0.62373
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- - type: ndcg_at_1000
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- - type: ndcg_at_3
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- - type: ndcg_at_5
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- value: 0.54257
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- - type: precision_at_1
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- value: 0.45923
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- - type: precision_at_10
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- value: 0.11316
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- - type: precision_at_100
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- value: 0.01705
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- - type: precision_at_1000
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- - type: precision_at_3
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- value: 0.2537
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- - type: precision_at_5
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- value: 0.1814
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- - type: recall_at_1
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- value: 0.36964
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- - type: recall_at_10
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- value: 0.71234
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- - type: recall_at_100
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- value: 0.90421
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- - type: recall_at_1000
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- value: 0.98296
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- - type: recall_at_3
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- value: 0.53655
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- - type: recall_at_5
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- value: 0.60996
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- - task:
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- type: Retrieval
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- dataset:
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- name: MTEB CQADupstackEnglishRetrieval
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- type: mteb/cqadupstack-english
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- config: default
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- split: test
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- metrics:
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- - type: map_at_1
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- value: 0.36198
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- - type: map_at_10
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- value: 0.49199
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- - type: map_at_100
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- value: 0.50602
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- - type: map_at_1000
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- value: 0.50736
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- - type: map_at_3
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- value: 0.45678
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- - type: map_at_5
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- value: 0.47605
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- - type: mrr_at_1
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- value: 0.45478
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- - type: mrr_at_10
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- value: 0.55075
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- - type: mrr_at_100
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- value: 0.55656
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- - type: mrr_at_1000
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- value: 0.55688
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- - type: mrr_at_3
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- value: 0.52887
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- - type: mrr_at_5
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- value: 0.54282
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- - type: ndcg_at_1
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- value: 0.45478
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- - type: ndcg_at_10
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- value: 0.55505
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- - type: ndcg_at_100
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- value: 0.59606
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- - type: ndcg_at_1000
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- value: 0.61255
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- - type: ndcg_at_3
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- value: 0.51124
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- - type: ndcg_at_5
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- value: 0.53166
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- - type: precision_at_1
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- value: 0.45478
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- - type: precision_at_10
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- value: 0.10752
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- - type: precision_at_100
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- value: 0.01666
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- - type: precision_at_1000
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- value: 0.00211
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- - type: precision_at_3
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- value: 0.25053
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- - type: precision_at_5
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- value: 0.17694
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- - type: recall_at_1
276
- value: 0.36198
277
- - type: recall_at_10
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- value: 0.66465
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- - type: recall_at_100
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- value: 0.83632
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- - type: recall_at_1000
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- value: 0.93276
283
- - type: recall_at_3
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- value: 0.53207
285
- - type: recall_at_5
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- value: 0.59169
287
- - task:
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- type: Retrieval
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- dataset:
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- name: MTEB CQADupstackGamingRetrieval
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- type: mteb/cqadupstack-gaming
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- config: default
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- split: test
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- metrics:
295
- - type: map_at_1
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- value: 0.44157
297
- - type: map_at_10
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- value: 0.57753
299
- - type: map_at_100
300
- value: 0.58698
301
- - type: map_at_1000
302
- value: 0.5874
303
- - type: map_at_3
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- value: 0.54223
305
- - type: map_at_5
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- value: 0.56307
307
- - type: mrr_at_1
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- value: 0.50094
309
- - type: mrr_at_10
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- value: 0.607
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- - type: mrr_at_100
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- value: 0.6126
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- - type: mrr_at_1000
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- value: 0.6128
315
- - type: mrr_at_3
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- value: 0.58265
317
- - type: mrr_at_5
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- value: 0.59817
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- - type: ndcg_at_1
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- value: 0.50094
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- - type: ndcg_at_10
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- value: 0.63641
323
- - type: ndcg_at_100
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- value: 0.67055
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- - type: ndcg_at_1000
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- value: 0.67855
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- - type: ndcg_at_3
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- value: 0.58022
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- - type: ndcg_at_5
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- - type: precision_at_1
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- value: 0.50094
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- - type: precision_at_10
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- value: 0.10182
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- - type: precision_at_100
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- value: 0.01278
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- - type: precision_at_1000
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- value: 0.00138
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- - type: precision_at_3
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- value: 0.2581
341
- - type: precision_at_5
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- value: 0.17755
343
- - type: recall_at_1
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- value: 0.44157
345
- - type: recall_at_10
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- value: 0.7778
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- - type: recall_at_100
348
- value: 0.92244
349
- - type: recall_at_1000
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- value: 0.9781
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- - type: recall_at_3
352
- value: 0.63087
353
- - type: recall_at_5
354
- value: 0.70172
355
- - task:
356
- type: Retrieval
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- dataset:
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- name: MTEB CQADupstackGisRetrieval
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- type: mteb/cqadupstack-gis
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- config: default
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- split: test
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- metrics:
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- - type: map_at_1
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- value: 0.29532
365
- - type: map_at_10
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- value: 0.40214
367
- - type: map_at_100
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- - type: map_at_1000
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371
- - type: map_at_3
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- - type: map_at_5
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- - type: mrr_at_1
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- - type: mrr_at_10
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- - type: mrr_at_100
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- value: 0.43342
381
- - type: mrr_at_1000
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- value: 0.43395
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- - type: mrr_at_3
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- - type: mrr_at_5
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- - type: ndcg_at_10
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- - type: ndcg_at_100
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- value: 0.5103
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- - type: ndcg_at_1000
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- value: 0.52668
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- - type: ndcg_at_3
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- - type: ndcg_at_5
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- value: 0.43111
399
- - type: precision_at_1
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- value: 0.3209
401
- - type: precision_at_10
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- value: 0.07141
403
- - type: precision_at_100
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- value: 0.01018
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- - type: precision_at_1000
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- value: 0.00118
407
- - type: precision_at_3
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- value: 0.17175
409
- - type: precision_at_5
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- value: 0.12068
411
- - type: recall_at_1
412
- value: 0.29532
413
- - type: recall_at_10
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- value: 0.62025
415
- - type: recall_at_100
416
- value: 0.83829
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- - type: recall_at_1000
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- value: 0.95995
419
- - type: recall_at_3
420
- value: 0.4603
421
- - type: recall_at_5
422
- value: 0.53089
423
- - task:
424
- type: Retrieval
425
- dataset:
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- name: MTEB CQADupstackMathematicaRetrieval
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- type: mteb/cqadupstack-mathematica
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- config: default
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- split: test
430
- metrics:
431
- - type: map_at_1
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- value: 0.18944
433
- - type: map_at_10
434
- value: 0.29611
435
- - type: map_at_100
436
- value: 0.31063
437
- - type: map_at_1000
438
- value: 0.31174
439
- - type: map_at_3
440
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441
- - type: map_at_5
442
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443
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445
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446
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447
- - type: mrr_at_100
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449
- - type: mrr_at_1000
450
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451
- - type: mrr_at_3
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453
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457
- - type: ndcg_at_10
458
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459
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460
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461
- - type: ndcg_at_1000
462
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463
- - type: ndcg_at_3
464
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465
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466
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467
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468
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469
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470
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471
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472
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473
- - type: precision_at_1000
474
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475
- - type: precision_at_3
476
- value: 0.14635
477
- - type: precision_at_5
478
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479
- - type: recall_at_1
480
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481
- - type: recall_at_10
482
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483
- - type: recall_at_100
484
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485
- - type: recall_at_1000
486
- value: 0.93624
487
- - type: recall_at_3
488
- value: 0.33611
489
- - type: recall_at_5
490
- value: 0.41427
491
- - task:
492
- type: Retrieval
493
- dataset:
494
- name: MTEB CQADupstackPhysicsRetrieval
495
- type: mteb/cqadupstack-physics
496
- config: default
497
- split: test
498
- metrics:
499
- - type: map_at_1
500
- value: 0.33824
501
- - type: map_at_10
502
- value: 0.46868
503
- - type: map_at_100
504
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505
- - type: map_at_1000
506
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507
- - type: map_at_3
508
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509
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510
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515
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517
- - type: mrr_at_1000
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519
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521
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527
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528
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529
- - type: ndcg_at_1000
530
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531
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532
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533
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534
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535
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537
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541
- - type: precision_at_1000
542
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543
- - type: precision_at_3
544
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545
- - type: precision_at_5
546
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547
- - type: recall_at_1
548
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549
- - type: recall_at_10
550
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551
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552
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553
- - type: recall_at_1000
554
- value: 0.97816
555
- - type: recall_at_3
556
- value: 0.52305
557
- - type: recall_at_5
558
- value: 0.58804
559
- - task:
560
- type: Retrieval
561
- dataset:
562
- name: MTEB CQADupstackProgrammersRetrieval
563
- type: mteb/cqadupstack-programmers
564
- config: default
565
- split: test
566
- metrics:
567
- - type: map_at_1
568
- value: 0.30125
569
- - type: map_at_10
570
- value: 0.42119
571
- - type: map_at_100
572
- value: 0.43599
573
- - type: map_at_1000
574
- value: 0.4369
575
- - type: map_at_3
576
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577
- - type: map_at_5
578
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579
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580
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581
- - type: mrr_at_10
582
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583
- - type: mrr_at_100
584
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585
- - type: mrr_at_1000
586
- value: 0.48499
587
- - type: mrr_at_3
588
- value: 0.44654
589
- - type: mrr_at_5
590
- value: 0.4644
591
- - type: ndcg_at_1
592
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593
- - type: ndcg_at_10
594
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595
- - type: ndcg_at_100
596
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597
- - type: ndcg_at_1000
598
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599
- - type: ndcg_at_3
600
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601
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602
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603
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605
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606
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607
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608
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609
- - type: precision_at_1000
610
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611
- - type: precision_at_3
612
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613
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627
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628
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629
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630
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631
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632
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633
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634
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635
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679
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687
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695
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696
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697
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698
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699
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700
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701
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702
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703
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733
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735
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745
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747
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760
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761
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762
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763
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764
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765
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766
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767
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768
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769
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770
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771
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772
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830
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831
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832
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833
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834
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835
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836
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837
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838
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839
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840
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881
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896
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897
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898
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900
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901
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902
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903
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904
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905
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906
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907
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908
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910
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959
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961
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963
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967
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968
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969
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970
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971
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972
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973
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974
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1036
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1037
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1038
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1039
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1040
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1041
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1042
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1043
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1104
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1105
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1106
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1107
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1108
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1109
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1110
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1172
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1173
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1174
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1175
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1176
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1177
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1178
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1179
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1180
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1217
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1218
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1219
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1220
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1221
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1222
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1223
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1224
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1225
- - type: precision_at_5
1226
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1227
- - type: recall_at_1
1228
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1229
- - type: recall_at_10
1230
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1231
- - type: recall_at_100
1232
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1233
- - type: recall_at_1000
1234
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1235
- - type: recall_at_3
1236
- value: 0.60169
1237
- - type: recall_at_5
1238
- value: 0.65638
1239
- - task:
1240
- type: Retrieval
1241
- dataset:
1242
- name: MTEB MSMARCO
1243
- type: mteb/msmarco
1244
- config: default
1245
- split: dev
1246
- metrics:
1247
- - type: map_at_1
1248
- value: 0.15062
1249
- - type: map_at_10
1250
- value: 0.26008
1251
- - type: map_at_100
1252
- value: 0.27305
1253
- - type: map_at_1000
1254
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1255
- - type: map_at_3
1256
- value: 0.22236
1257
- - type: map_at_5
1258
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1259
- - type: mrr_at_1
1260
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1261
- - type: mrr_at_10
1262
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1263
- - type: mrr_at_100
1264
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1265
- - type: mrr_at_1000
1266
- value: 0.2778
1267
- - type: mrr_at_3
1268
- value: 0.22701
1269
- - type: mrr_at_5
1270
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1271
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1272
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1273
- - type: ndcg_at_10
1274
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1275
- - type: ndcg_at_100
1276
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1277
- - type: ndcg_at_1000
1278
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1279
- - type: ndcg_at_3
1280
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1281
- - type: ndcg_at_5
1282
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1283
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1284
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1285
- - type: precision_at_10
1286
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1287
- - type: precision_at_100
1288
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1289
- - type: precision_at_1000
1290
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1291
- - type: precision_at_3
1292
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1293
- - type: precision_at_5
1294
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1295
- - type: recall_at_1
1296
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1297
- - type: recall_at_10
1298
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1299
- - type: recall_at_100
1300
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1301
- - type: recall_at_1000
1302
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1303
- - type: recall_at_3
1304
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1305
- - type: recall_at_5
1306
- value: 0.40706
1307
- - task:
1308
- type: Retrieval
1309
- dataset:
1310
- name: MTEB NFCorpus
1311
- type: mteb/nfcorpus
1312
- config: default
1313
- split: test
1314
- metrics:
1315
- - type: map_at_1
1316
- value: 0.06126
1317
- - type: map_at_10
1318
- value: 0.14152
1319
- - type: map_at_100
1320
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1321
- - type: map_at_1000
1322
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1323
- - type: map_at_3
1324
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1325
- - type: map_at_5
1326
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1327
- - type: mrr_at_1
1328
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1329
- - type: mrr_at_10
1330
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1331
- - type: mrr_at_100
1332
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1333
- - type: mrr_at_1000
1334
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1335
- - type: mrr_at_3
1336
- value: 0.55315
1337
- - type: mrr_at_5
1338
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1339
- - type: ndcg_at_1
1340
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1341
- - type: ndcg_at_10
1342
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1343
- - type: ndcg_at_100
1344
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1345
- - type: ndcg_at_1000
1346
- value: 0.43374
1347
- - type: ndcg_at_3
1348
- value: 0.42643
1349
- - type: ndcg_at_5
1350
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1351
- - type: precision_at_1
1352
- value: 0.47368
1353
- - type: precision_at_10
1354
- value: 0.2774
1355
- - type: precision_at_100
1356
- value: 0.09071
1357
- - type: precision_at_1000
1358
- value: 0.02226
1359
- - type: precision_at_3
1360
- value: 0.40144
1361
- - type: precision_at_5
1362
- value: 0.35913
1363
- - type: recall_at_1
1364
- value: 0.06126
1365
- - type: recall_at_10
1366
- value: 0.18427
1367
- - type: recall_at_100
1368
- value: 0.35018
1369
- - type: recall_at_1000
1370
- value: 0.6766
1371
- - type: recall_at_3
1372
- value: 0.11706
1373
- - type: recall_at_5
1374
- value: 0.14419
1375
- - task:
1376
- type: Retrieval
1377
- dataset:
1378
- name: MTEB NQ
1379
- type: mteb/nq
1380
- config: default
1381
- split: test
1382
- metrics:
1383
- - type: map_at_1
1384
- value: 0.33053
1385
- - type: map_at_10
1386
- value: 0.49739
1387
- - type: map_at_100
1388
- value: 0.50626
1389
- - type: map_at_1000
1390
- value: 0.50647
1391
- - type: map_at_3
1392
- value: 0.4491
1393
- - type: map_at_5
1394
- value: 0.4783
1395
- - type: mrr_at_1
1396
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1397
- - type: mrr_at_10
1398
- value: 0.52222
1399
- - type: mrr_at_100
1400
- value: 0.52855
1401
- - type: mrr_at_1000
1402
- value: 0.52869
1403
- - type: mrr_at_3
1404
- value: 0.48445
1405
- - type: mrr_at_5
1406
- value: 0.50834
1407
- - type: ndcg_at_1
1408
- value: 0.37254
1409
- - type: ndcg_at_10
1410
- value: 0.58044
1411
- - type: ndcg_at_100
1412
- value: 0.61613
1413
- - type: ndcg_at_1000
1414
- value: 0.62046
1415
- - type: ndcg_at_3
1416
- value: 0.49219
1417
- - type: ndcg_at_5
1418
- value: 0.54037
1419
- - type: precision_at_1
1420
- value: 0.37254
1421
- - type: precision_at_10
1422
- value: 0.09655
1423
- - type: precision_at_100
1424
- value: 0.01167
1425
- - type: precision_at_1000
1426
- value: 0.00121
1427
- - type: precision_at_3
1428
- value: 0.22538
1429
- - type: precision_at_5
1430
- value: 0.16344
1431
- - type: recall_at_1
1432
- value: 0.33053
1433
- - type: recall_at_10
1434
- value: 0.8076
1435
- - type: recall_at_100
1436
- value: 0.95862
1437
- - type: recall_at_1000
1438
- value: 0.99044
1439
- - type: recall_at_3
1440
- value: 0.58157
1441
- - type: recall_at_5
1442
- value: 0.69235
1443
- - task:
1444
- type: Retrieval
1445
- dataset:
1446
- name: MTEB QuoraRetrieval
1447
- type: mteb/quora
1448
- config: default
1449
- split: test
1450
- metrics:
1451
- - type: map_at_1
1452
- value: 0.70056
1453
- - type: map_at_10
1454
- value: 0.84009
1455
- - type: map_at_100
1456
- value: 0.84661
1457
- - type: map_at_1000
1458
- value: 0.84678
1459
- - type: map_at_3
1460
- value: 0.81036
1461
- - type: map_at_5
1462
- value: 0.82923
1463
- - type: mrr_at_1
1464
- value: 0.8062
1465
- - type: mrr_at_10
1466
- value: 0.86971
1467
- - type: mrr_at_100
1468
- value: 0.87079
1469
- - type: mrr_at_1000
1470
- value: 0.8708
1471
- - type: mrr_at_3
1472
- value: 0.85943
1473
- - type: mrr_at_5
1474
- value: 0.86664
1475
- - type: ndcg_at_1
1476
- value: 0.8064
1477
- - type: ndcg_at_10
1478
- value: 0.87821
1479
- - type: ndcg_at_100
1480
- value: 0.89091
1481
- - type: ndcg_at_1000
1482
- value: 0.89202
1483
- - type: ndcg_at_3
1484
- value: 0.849
1485
- - type: ndcg_at_5
1486
- value: 0.86544
1487
- - type: precision_at_1
1488
- value: 0.8064
1489
- - type: precision_at_10
1490
- value: 0.13347
1491
- - type: precision_at_100
1492
- value: 0.01527
1493
- - type: precision_at_1000
1494
- value: 0.00157
1495
- - type: precision_at_3
1496
- value: 0.37153
1497
- - type: precision_at_5
1498
- value: 0.2448
1499
- - type: recall_at_1
1500
- value: 0.70056
1501
- - type: recall_at_10
1502
- value: 0.95148
1503
- - type: recall_at_100
1504
- value: 0.99474
1505
- - type: recall_at_1000
1506
- value: 0.99977
1507
- - type: recall_at_3
1508
- value: 0.86773
1509
- - type: recall_at_5
1510
- value: 0.91396
1511
- - task:
1512
- type: Retrieval
1513
- dataset:
1514
- name: MTEB SCIDOCS
1515
- type: mteb/scidocs
1516
- config: default
1517
- split: test
1518
- metrics:
1519
- - type: map_at_1
1520
- value: 0.05737
1521
- - type: map_at_10
1522
- value: 0.14896
1523
- - type: map_at_100
1524
- value: 0.17646
1525
- - type: map_at_1000
1526
- value: 0.1803
1527
- - type: map_at_3
1528
- value: 0.10474
1529
- - type: map_at_5
1530
- value: 0.12656
1531
- - type: mrr_at_1
1532
- value: 0.281
1533
- - type: mrr_at_10
1534
- value: 0.39579
1535
- - type: mrr_at_100
1536
- value: 0.40687
1537
- - type: mrr_at_1000
1538
- value: 0.40722
1539
- - type: mrr_at_3
1540
- value: 0.35917
1541
- - type: mrr_at_5
1542
- value: 0.38097
1543
- - type: ndcg_at_1
1544
- value: 0.281
1545
- - type: ndcg_at_10
1546
- value: 0.24146
1547
- - type: ndcg_at_100
1548
- value: 0.339
1549
- - type: ndcg_at_1000
1550
- value: 0.39728
1551
- - type: ndcg_at_3
1552
- value: 0.22721
1553
- - type: ndcg_at_5
1554
- value: 0.20015
1555
- - type: precision_at_1
1556
- value: 0.281
1557
- - type: precision_at_10
1558
- value: 0.1254
1559
- - type: precision_at_100
1560
- value: 0.02651
1561
- - type: precision_at_1000
1562
- value: 0.00404
1563
- - type: precision_at_3
1564
- value: 0.212
1565
- - type: precision_at_5
1566
- value: 0.176
1567
- - type: recall_at_1
1568
- value: 0.05737
1569
- - type: recall_at_10
1570
- value: 0.254
1571
- - type: recall_at_100
1572
- value: 0.53772
1573
- - type: recall_at_1000
1574
- value: 0.82013
1575
- - type: recall_at_3
1576
- value: 0.12897
1577
- - type: recall_at_5
1578
- value: 0.17855
1579
- - task:
1580
- type: Retrieval
1581
- dataset:
1582
- name: MTEB SciFact
1583
- type: mteb/scifact
1584
- config: default
1585
- split: test
1586
- metrics:
1587
- - type: map_at_1
1588
- value: 0.60011
1589
- - type: map_at_10
1590
- value: 0.70101
1591
- - type: map_at_100
1592
- value: 0.70687
1593
- - type: map_at_1000
1594
- value: 0.70699
1595
- - type: map_at_3
1596
- value: 0.67135
1597
- - type: map_at_5
1598
- value: 0.6878
1599
- - type: mrr_at_1
1600
- value: 0.62667
1601
- - type: mrr_at_10
1602
- value: 0.71022
1603
- - type: mrr_at_100
1604
- value: 0.71484
1605
- - type: mrr_at_1000
1606
- value: 0.71496
1607
- - type: mrr_at_3
1608
- value: 0.68944
1609
- - type: mrr_at_5
1610
- value: 0.69961
1611
- - type: ndcg_at_1
1612
- value: 0.62667
1613
- - type: ndcg_at_10
1614
- value: 0.7472
1615
- - type: ndcg_at_100
1616
- value: 0.76961
1617
- - type: ndcg_at_1000
1618
- value: 0.77294
1619
- - type: ndcg_at_3
1620
- value: 0.69776
1621
- - type: ndcg_at_5
1622
- value: 0.71964
1623
- - type: precision_at_1
1624
- value: 0.62667
1625
- - type: precision_at_10
1626
- value: 0.09933
1627
- - type: precision_at_100
1628
- value: 0.01103
1629
- - type: precision_at_1000
1630
- value: 0.00113
1631
- - type: precision_at_3
1632
- value: 0.27
1633
- - type: precision_at_5
1634
- value: 0.178
1635
- - type: recall_at_1
1636
- value: 0.60011
1637
- - type: recall_at_10
1638
- value: 0.878
1639
- - type: recall_at_100
1640
- value: 0.97333
1641
- - type: recall_at_1000
1642
- value: 1
1643
- - type: recall_at_3
1644
- value: 0.74839
1645
- - type: recall_at_5
1646
- value: 0.80028
1647
- - task:
1648
- type: Retrieval
1649
- dataset:
1650
- name: MTEB Touche2020
1651
- type: mteb/touche2020
1652
- config: default
1653
- split: test
1654
- metrics:
1655
- - type: map_at_1
1656
- value: 0.02152
1657
- - type: map_at_10
1658
- value: 0.07747
1659
- - type: map_at_100
1660
- value: 0.1364
1661
- - type: map_at_1000
1662
- value: 0.15235
1663
- - type: map_at_3
1664
- value: 0.04103
1665
- - type: map_at_5
1666
- value: 0.05482
1667
- - type: mrr_at_1
1668
- value: 0.26531
1669
- - type: mrr_at_10
1670
- value: 0.41399
1671
- - type: mrr_at_100
1672
- value: 0.43047
1673
- - type: mrr_at_1000
1674
- value: 0.43047
1675
- - type: mrr_at_3
1676
- value: 0.38776
1677
- - type: mrr_at_5
1678
- value: 0.40612
1679
- - type: ndcg_at_1
1680
- value: 0.23469
1681
- - type: ndcg_at_10
1682
- value: 0.20147
1683
- - type: ndcg_at_100
1684
- value: 0.3279
1685
- - type: ndcg_at_1000
1686
- value: 0.45324
1687
- - type: ndcg_at_3
1688
- value: 0.22555
1689
- - type: ndcg_at_5
1690
- value: 0.2097
1691
- - type: precision_at_1
1692
- value: 0.26531
1693
- - type: precision_at_10
1694
- value: 0.17755
1695
- - type: precision_at_100
1696
- value: 0.07082
1697
- - type: precision_at_1000
1698
- value: 0.01547
1699
- - type: precision_at_3
1700
- value: 0.2449
1701
- - type: precision_at_5
1702
- value: 0.21633
1703
- - type: recall_at_1
1704
- value: 0.02152
1705
- - type: recall_at_10
1706
- value: 0.13331
1707
- - type: recall_at_100
1708
- value: 0.4535
1709
- - type: recall_at_1000
1710
- value: 0.83447
1711
- - type: recall_at_3
1712
- value: 0.05531
1713
- - type: recall_at_5
1714
- value: 0.08029
1715
- - task:
1716
- type: Retrieval
1717
- dataset:
1718
- name: MTEB TRECCOVID
1719
- type: mteb/trec-covid
1720
- config: default
1721
- split: test
1722
- metrics:
1723
- - type: map_at_1
1724
- value: 0.00202
1725
- - type: map_at_10
1726
- value: 0.01727
1727
- - type: map_at_100
1728
- value: 0.10906
1729
- - type: map_at_1000
1730
- value: 0.2894
1731
- - type: map_at_3
1732
- value: 0.00553
1733
- - type: map_at_5
1734
- value: 0.00924
1735
- - type: mrr_at_1
1736
- value: 0.74
1737
- - type: mrr_at_10
1738
- value: 0.85667
1739
- - type: mrr_at_100
1740
- value: 0.85667
1741
- - type: mrr_at_1000
1742
- value: 0.85667
1743
- - type: mrr_at_3
1744
- value: 0.85667
1745
- - type: mrr_at_5
1746
- value: 0.85667
1747
- - type: ndcg_at_1
1748
- value: 0.66
1749
- - type: ndcg_at_10
1750
- value: 0.69259
1751
- - type: ndcg_at_100
1752
- value: 0.57274
1753
- - type: ndcg_at_1000
1754
- value: 0.55462
1755
- - type: ndcg_at_3
1756
- value: 0.70654
1757
- - type: ndcg_at_5
1758
- value: 0.71611
1759
- - type: precision_at_1
1760
- value: 0.74
1761
- - type: precision_at_10
1762
- value: 0.748
1763
- - type: precision_at_100
1764
- value: 0.5962
1765
- - type: precision_at_1000
1766
- value: 0.24842
1767
- - type: precision_at_3
1768
- value: 0.77333
1769
- - type: precision_at_5
1770
- value: 0.788
1771
- - type: recall_at_1
1772
- value: 0.00202
1773
- - type: recall_at_10
1774
- value: 0.02001
1775
- - type: recall_at_100
1776
- value: 0.14801
1777
- - type: recall_at_1000
1778
- value: 0.53939
1779
- - type: recall_at_3
1780
- value: 0.00609
1781
- - type: recall_at_5
1782
- value: 0.01048
1783
  ---
1784
  ## 💫 Community Model> granite embedding 125m english by Ibm-Granite
1785
 
@@ -1787,7 +8,7 @@ model-index:
1787
 
1788
  **Model creator:** [ibm-granite](https://huggingface.co/ibm-granite)<br>
1789
  **Original model**: [granite-embedding-125m-english](https://huggingface.co/ibm-granite/granite-embedding-125m-english)<br>
1790
- **GGUF quantization:** provided by [bartowski](https://huggingface.co/bartowski) based on `llama.cpp` release [b4341](https://github.com/ggerganov/llama.cpp/releases/tag/b4341)<br>
1791
 
1792
  ## Technical Details
1793
 
 
1
  ---
2
  quantized_by: bartowski
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