Commit
•
d0e2bf1
1
Parent(s):
4e81c80
Add new SentenceTransformer model.
Browse files- 1_Pooling/config.json +10 -0
- README.md +3381 -0
- config.json +27 -0
- config_sentence_transformers.json +9 -0
- model-00001-of-00006.safetensors +3 -0
- model-00002-of-00006.safetensors +3 -0
- model-00003-of-00006.safetensors +3 -0
- model-00004-of-00006.safetensors +3 -0
- model-00005-of-00006.safetensors +3 -0
- model-00006-of-00006.safetensors +3 -0
- model.safetensors.index.json +297 -0
- modules.json +14 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +35 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +53 -0
1_Pooling/config.json
ADDED
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@@ -0,0 +1,10 @@
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{
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"word_embedding_dimension": 4096,
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"pooling_mode_cls_token": false,
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"pooling_mode_mean_tokens": false,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false,
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"pooling_mode_weightedmean_tokens": false,
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"pooling_mode_lasttoken": true,
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"include_prompt": true
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}
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README.md
ADDED
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@@ -0,0 +1,3381 @@
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|
| 1 |
+
---
|
| 2 |
+
tags:
|
| 3 |
+
- mteb
|
| 4 |
+
- sentence-transformers
|
| 5 |
+
- transformers
|
| 6 |
+
model-index:
|
| 7 |
+
- name: SFR-Embedding-Mistral
|
| 8 |
+
results:
|
| 9 |
+
- task:
|
| 10 |
+
type: Classification
|
| 11 |
+
dataset:
|
| 12 |
+
type: mteb/amazon_counterfactual
|
| 13 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
| 14 |
+
config: en
|
| 15 |
+
split: test
|
| 16 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
| 17 |
+
metrics:
|
| 18 |
+
- type: accuracy
|
| 19 |
+
value: 77.92537313432834
|
| 20 |
+
- type: ap
|
| 21 |
+
value: 40.86767661556651
|
| 22 |
+
- type: f1
|
| 23 |
+
value: 71.65758897929837
|
| 24 |
+
- task:
|
| 25 |
+
type: Classification
|
| 26 |
+
dataset:
|
| 27 |
+
type: mteb/amazon_polarity
|
| 28 |
+
name: MTEB AmazonPolarityClassification
|
| 29 |
+
config: default
|
| 30 |
+
split: test
|
| 31 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
| 32 |
+
metrics:
|
| 33 |
+
- type: accuracy
|
| 34 |
+
value: 95.967
|
| 35 |
+
- type: ap
|
| 36 |
+
value: 94.46300829592593
|
| 37 |
+
- type: f1
|
| 38 |
+
value: 95.96507173189292
|
| 39 |
+
- task:
|
| 40 |
+
type: Classification
|
| 41 |
+
dataset:
|
| 42 |
+
type: mteb/amazon_reviews_multi
|
| 43 |
+
name: MTEB AmazonReviewsClassification (en)
|
| 44 |
+
config: en
|
| 45 |
+
split: test
|
| 46 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
| 47 |
+
metrics:
|
| 48 |
+
- type: accuracy
|
| 49 |
+
value: 54.352000000000004
|
| 50 |
+
- type: f1
|
| 51 |
+
value: 53.636682615380174
|
| 52 |
+
- task:
|
| 53 |
+
type: Retrieval
|
| 54 |
+
dataset:
|
| 55 |
+
type: arguana
|
| 56 |
+
name: MTEB ArguAna
|
| 57 |
+
config: default
|
| 58 |
+
split: test
|
| 59 |
+
revision: None
|
| 60 |
+
metrics:
|
| 61 |
+
- type: ndcg_at_1
|
| 62 |
+
value: 43.314
|
| 63 |
+
- type: ndcg_at_2
|
| 64 |
+
value: 54.757
|
| 65 |
+
- type: ndcg_at_3
|
| 66 |
+
value: 58.84700000000001
|
| 67 |
+
- type: ndcg_at_5
|
| 68 |
+
value: 63.634
|
| 69 |
+
- type: ndcg_at_7
|
| 70 |
+
value: 65.741
|
| 71 |
+
- type: ndcg_at_10
|
| 72 |
+
value: 67.171
|
| 73 |
+
- type: ndcg_at_20
|
| 74 |
+
value: 68.585
|
| 75 |
+
- type: ndcg_at_30
|
| 76 |
+
value: 68.81
|
| 77 |
+
- type: ndcg_at_50
|
| 78 |
+
value: 68.932
|
| 79 |
+
- type: ndcg_at_70
|
| 80 |
+
value: 68.992
|
| 81 |
+
- type: ndcg_at_100
|
| 82 |
+
value: 69.014
|
| 83 |
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- type: ndcg_at_200
|
| 84 |
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value: 69.014
|
| 85 |
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- type: ndcg_at_300
|
| 86 |
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value: 69.014
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| 87 |
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|
| 88 |
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value: 69.014
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| 89 |
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- type: ndcg_at_700
|
| 90 |
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value: 69.014
|
| 91 |
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- type: ndcg_at_1000
|
| 92 |
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value: 69.014
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| 93 |
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|
| 94 |
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value: 43.314
|
| 95 |
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- type: map_at_2
|
| 96 |
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value: 52.383
|
| 97 |
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- type: map_at_3
|
| 98 |
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value: 55.108999999999995
|
| 99 |
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- type: map_at_5
|
| 100 |
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value: 57.772999999999996
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| 101 |
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- type: map_at_7
|
| 102 |
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value: 58.718
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| 103 |
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|
| 104 |
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value: 59.256
|
| 105 |
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- type: map_at_20
|
| 106 |
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value: 59.668
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| 107 |
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- type: map_at_30
|
| 108 |
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value: 59.709999999999994
|
| 109 |
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- type: map_at_50
|
| 110 |
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value: 59.727
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| 111 |
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- type: map_at_70
|
| 112 |
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value: 59.733999999999995
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| 113 |
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| 114 |
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value: 59.73500000000001
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| 115 |
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| 116 |
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value: 59.73500000000001
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| 117 |
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| 118 |
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value: 59.73500000000001
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| 119 |
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| 120 |
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value: 59.73500000000001
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| 121 |
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| 122 |
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value: 59.73500000000001
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| 123 |
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| 124 |
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value: 59.73500000000001
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| 125 |
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- type: recall_at_1
|
| 126 |
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value: 43.314
|
| 127 |
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- type: recall_at_2
|
| 128 |
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value: 61.451
|
| 129 |
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- type: recall_at_3
|
| 130 |
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value: 69.63000000000001
|
| 131 |
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- type: recall_at_5
|
| 132 |
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value: 81.223
|
| 133 |
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- type: recall_at_7
|
| 134 |
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value: 87.33999999999999
|
| 135 |
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- type: recall_at_10
|
| 136 |
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value: 92.034
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| 137 |
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- type: recall_at_20
|
| 138 |
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value: 97.44
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| 139 |
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- type: recall_at_30
|
| 140 |
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value: 98.506
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| 141 |
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- type: recall_at_50
|
| 142 |
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value: 99.14699999999999
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| 143 |
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- type: recall_at_70
|
| 144 |
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value: 99.502
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| 145 |
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- type: recall_at_100
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| 146 |
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value: 99.644
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| 147 |
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- type: recall_at_200
|
| 148 |
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value: 99.644
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| 149 |
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- type: recall_at_300
|
| 150 |
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value: 99.644
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| 151 |
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- type: recall_at_500
|
| 152 |
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value: 99.644
|
| 153 |
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- type: recall_at_700
|
| 154 |
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value: 99.644
|
| 155 |
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- type: recall_at_1000
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| 156 |
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value: 99.644
|
| 157 |
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- type: precision_at_1
|
| 158 |
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value: 43.314
|
| 159 |
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- type: precision_at_2
|
| 160 |
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value: 30.725
|
| 161 |
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- type: precision_at_3
|
| 162 |
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value: 23.21
|
| 163 |
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- type: precision_at_5
|
| 164 |
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value: 16.245
|
| 165 |
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- type: precision_at_7
|
| 166 |
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value: 12.477
|
| 167 |
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- type: precision_at_10
|
| 168 |
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value: 9.203
|
| 169 |
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- type: precision_at_20
|
| 170 |
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value: 4.872
|
| 171 |
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- type: precision_at_30
|
| 172 |
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value: 3.2840000000000003
|
| 173 |
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- type: precision_at_50
|
| 174 |
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value: 1.983
|
| 175 |
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- type: precision_at_70
|
| 176 |
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value: 1.421
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| 177 |
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- type: precision_at_100
|
| 178 |
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value: 0.996
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| 179 |
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- type: precision_at_200
|
| 180 |
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value: 0.498
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| 181 |
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- type: precision_at_300
|
| 182 |
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value: 0.332
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| 183 |
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- type: precision_at_500
|
| 184 |
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value: 0.199
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| 185 |
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- type: precision_at_700
|
| 186 |
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value: 0.14200000000000002
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| 187 |
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- type: precision_at_1000
|
| 188 |
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value: 0.1
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| 189 |
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|
| 190 |
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value: 44.666
|
| 191 |
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|
| 192 |
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value: 52.418
|
| 193 |
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- type: mrr_at_3
|
| 194 |
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value: 55.595000000000006
|
| 195 |
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| 196 |
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value: 58.205
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| 197 |
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| 198 |
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value: 59.202999999999996
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| 199 |
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| 200 |
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value: 59.727
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| 201 |
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| 202 |
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value: 60.133
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| 203 |
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| 204 |
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value: 60.178
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| 205 |
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| 206 |
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value: 60.192
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| 208 |
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value: 60.19799999999999
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| 209 |
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| 210 |
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value: 60.199999999999996
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| 211 |
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| 212 |
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value: 60.199999999999996
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| 213 |
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- type: mrr_at_300
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| 214 |
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value: 60.199999999999996
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| 215 |
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| 216 |
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value: 60.199999999999996
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| 217 |
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| 218 |
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value: 60.199999999999996
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| 219 |
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- type: mrr_at_1000
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| 220 |
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value: 60.199999999999996
|
| 221 |
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- task:
|
| 222 |
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type: Clustering
|
| 223 |
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dataset:
|
| 224 |
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type: mteb/arxiv-clustering-p2p
|
| 225 |
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name: MTEB ArxivClusteringP2P
|
| 226 |
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config: default
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| 227 |
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split: test
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| 228 |
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
| 229 |
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metrics:
|
| 230 |
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- type: v_measure
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| 231 |
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value: 52.07508593014336
|
| 232 |
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- task:
|
| 233 |
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type: Clustering
|
| 234 |
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dataset:
|
| 235 |
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type: mteb/arxiv-clustering-s2s
|
| 236 |
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name: MTEB ArxivClusteringS2S
|
| 237 |
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config: default
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| 238 |
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split: test
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| 239 |
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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| 240 |
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metrics:
|
| 241 |
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| 242 |
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value: 47.381339333240675
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| 243 |
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|
| 244 |
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type: Reranking
|
| 245 |
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dataset:
|
| 246 |
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type: mteb/askubuntudupquestions-reranking
|
| 247 |
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name: MTEB AskUbuntuDupQuestions
|
| 248 |
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config: default
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| 249 |
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split: test
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| 250 |
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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| 251 |
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|
| 252 |
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| 253 |
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value: 67.58376647859171
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| 254 |
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| 255 |
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value: 80.56885635140483
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| 256 |
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| 257 |
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type: STS
|
| 258 |
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dataset:
|
| 259 |
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type: mteb/biosses-sts
|
| 260 |
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name: MTEB BIOSSES
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| 262 |
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| 263 |
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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| 264 |
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|
| 265 |
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| 266 |
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value: 88.40107280274783
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| 267 |
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value: 86.07003345325681
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value: 87.1726034325395
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value: 86.07003345325681
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value: 87.25660625029772
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| 275 |
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value: 86.3808839096893
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| 277 |
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| 278 |
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type: Classification
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| 279 |
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dataset:
|
| 280 |
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type: mteb/banking77
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| 281 |
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name: MTEB Banking77Classification
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| 282 |
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config: default
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| 283 |
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split: test
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| 284 |
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
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metrics:
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| 286 |
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- type: accuracy
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| 287 |
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value: 88.81168831168831
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| 288 |
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- type: f1
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value: 88.76514496560141
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| 290 |
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| 291 |
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type: Clustering
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| 292 |
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dataset:
|
| 293 |
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type: mteb/biorxiv-clustering-p2p
|
| 294 |
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name: MTEB BiorxivClusteringP2P
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| 295 |
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config: default
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split: test
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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|
| 299 |
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| 300 |
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value: 43.9382520874344
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| 301 |
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- task:
|
| 302 |
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type: Clustering
|
| 303 |
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dataset:
|
| 304 |
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type: mteb/biorxiv-clustering-s2s
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| 305 |
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name: MTEB BiorxivClusteringS2S
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| 306 |
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config: default
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split: test
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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| 310 |
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| 311 |
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value: 41.14351847240913
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| 312 |
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|
| 313 |
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type: Retrieval
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| 314 |
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dataset:
|
| 315 |
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type: BeIR/cqadupstack
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| 316 |
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name: MTEB CQADupstackRetrieval
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| 317 |
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config: default
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| 318 |
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split: test
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| 319 |
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revision: None
|
| 320 |
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metrics:
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| 321 |
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| 322 |
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value: 34.51166666666667
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value: 29.10075
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| 405 |
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| 413 |
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| 414 |
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| 415 |
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value: 45.5365
|
| 477 |
+
- type: mrr_at_700
|
| 478 |
+
value: 45.538583333333335
|
| 479 |
+
- type: mrr_at_1000
|
| 480 |
+
value: 45.539583333333326
|
| 481 |
+
- task:
|
| 482 |
+
type: Retrieval
|
| 483 |
+
dataset:
|
| 484 |
+
type: climate-fever
|
| 485 |
+
name: MTEB ClimateFEVER
|
| 486 |
+
config: default
|
| 487 |
+
split: test
|
| 488 |
+
revision: None
|
| 489 |
+
metrics:
|
| 490 |
+
- type: ndcg_at_1
|
| 491 |
+
value: 35.179
|
| 492 |
+
- type: ndcg_at_2
|
| 493 |
+
value: 31.243
|
| 494 |
+
- type: ndcg_at_3
|
| 495 |
+
value: 30.562
|
| 496 |
+
- type: ndcg_at_5
|
| 497 |
+
value: 32.409
|
| 498 |
+
- type: ndcg_at_7
|
| 499 |
+
value: 34.525
|
| 500 |
+
- type: ndcg_at_10
|
| 501 |
+
value: 36.415
|
| 502 |
+
- type: ndcg_at_20
|
| 503 |
+
value: 39.443
|
| 504 |
+
- type: ndcg_at_30
|
| 505 |
+
value: 40.796
|
| 506 |
+
- type: ndcg_at_50
|
| 507 |
+
value: 42.16
|
| 508 |
+
- type: ndcg_at_70
|
| 509 |
+
value: 42.971
|
| 510 |
+
- type: ndcg_at_100
|
| 511 |
+
value: 43.691
|
| 512 |
+
- type: ndcg_at_200
|
| 513 |
+
value: 45.004
|
| 514 |
+
- type: ndcg_at_300
|
| 515 |
+
value: 45.527
|
| 516 |
+
- type: ndcg_at_500
|
| 517 |
+
value: 46.072
|
| 518 |
+
- type: ndcg_at_700
|
| 519 |
+
value: 46.387
|
| 520 |
+
- type: ndcg_at_1000
|
| 521 |
+
value: 46.663
|
| 522 |
+
- type: map_at_1
|
| 523 |
+
value: 15.692
|
| 524 |
+
- type: map_at_2
|
| 525 |
+
value: 20.116
|
| 526 |
+
- type: map_at_3
|
| 527 |
+
value: 22.6
|
| 528 |
+
- type: map_at_5
|
| 529 |
+
value: 24.701
|
| 530 |
+
- type: map_at_7
|
| 531 |
+
value: 25.934
|
| 532 |
+
- type: map_at_10
|
| 533 |
+
value: 26.843
|
| 534 |
+
- type: map_at_20
|
| 535 |
+
value: 27.975
|
| 536 |
+
- type: map_at_30
|
| 537 |
+
value: 28.372000000000003
|
| 538 |
+
- type: map_at_50
|
| 539 |
+
value: 28.671000000000003
|
| 540 |
+
- type: map_at_70
|
| 541 |
+
value: 28.803
|
| 542 |
+
- type: map_at_100
|
| 543 |
+
value: 28.895
|
| 544 |
+
- type: map_at_200
|
| 545 |
+
value: 29.011
|
| 546 |
+
- type: map_at_300
|
| 547 |
+
value: 29.042
|
| 548 |
+
- type: map_at_500
|
| 549 |
+
value: 29.065
|
| 550 |
+
- type: map_at_700
|
| 551 |
+
value: 29.075
|
| 552 |
+
- type: map_at_1000
|
| 553 |
+
value: 29.081000000000003
|
| 554 |
+
- type: recall_at_1
|
| 555 |
+
value: 15.692
|
| 556 |
+
- type: recall_at_2
|
| 557 |
+
value: 22.602
|
| 558 |
+
- type: recall_at_3
|
| 559 |
+
value: 27.814
|
| 560 |
+
- type: recall_at_5
|
| 561 |
+
value: 33.756
|
| 562 |
+
- type: recall_at_7
|
| 563 |
+
value: 38.073
|
| 564 |
+
- type: recall_at_10
|
| 565 |
+
value: 42.553000000000004
|
| 566 |
+
- type: recall_at_20
|
| 567 |
+
value: 51.121
|
| 568 |
+
- type: recall_at_30
|
| 569 |
+
value: 55.523999999999994
|
| 570 |
+
- type: recall_at_50
|
| 571 |
+
value: 60.586
|
| 572 |
+
- type: recall_at_70
|
| 573 |
+
value: 63.94
|
| 574 |
+
- type: recall_at_100
|
| 575 |
+
value: 67.134
|
| 576 |
+
- type: recall_at_200
|
| 577 |
+
value: 73.543
|
| 578 |
+
- type: recall_at_300
|
| 579 |
+
value: 76.372
|
| 580 |
+
- type: recall_at_500
|
| 581 |
+
value: 79.60199999999999
|
| 582 |
+
- type: recall_at_700
|
| 583 |
+
value: 81.536
|
| 584 |
+
- type: recall_at_1000
|
| 585 |
+
value: 83.37400000000001
|
| 586 |
+
- type: precision_at_1
|
| 587 |
+
value: 35.179
|
| 588 |
+
- type: precision_at_2
|
| 589 |
+
value: 27.199
|
| 590 |
+
- type: precision_at_3
|
| 591 |
+
value: 22.953000000000003
|
| 592 |
+
- type: precision_at_5
|
| 593 |
+
value: 17.224999999999998
|
| 594 |
+
- type: precision_at_7
|
| 595 |
+
value: 14.238999999999999
|
| 596 |
+
- type: precision_at_10
|
| 597 |
+
value: 11.303
|
| 598 |
+
- type: precision_at_20
|
| 599 |
+
value: 6.954000000000001
|
| 600 |
+
- type: precision_at_30
|
| 601 |
+
value: 5.116
|
| 602 |
+
- type: precision_at_50
|
| 603 |
+
value: 3.395
|
| 604 |
+
- type: precision_at_70
|
| 605 |
+
value: 2.579
|
| 606 |
+
- type: precision_at_100
|
| 607 |
+
value: 1.9109999999999998
|
| 608 |
+
- type: precision_at_200
|
| 609 |
+
value: 1.065
|
| 610 |
+
- type: precision_at_300
|
| 611 |
+
value: 0.743
|
| 612 |
+
- type: precision_at_500
|
| 613 |
+
value: 0.46699999999999997
|
| 614 |
+
- type: precision_at_700
|
| 615 |
+
value: 0.344
|
| 616 |
+
- type: precision_at_1000
|
| 617 |
+
value: 0.247
|
| 618 |
+
- type: mrr_at_1
|
| 619 |
+
value: 35.179
|
| 620 |
+
- type: mrr_at_2
|
| 621 |
+
value: 41.792
|
| 622 |
+
- type: mrr_at_3
|
| 623 |
+
value: 44.484
|
| 624 |
+
- type: mrr_at_5
|
| 625 |
+
value: 46.39
|
| 626 |
+
- type: mrr_at_7
|
| 627 |
+
value: 47.125
|
| 628 |
+
- type: mrr_at_10
|
| 629 |
+
value: 47.711999999999996
|
| 630 |
+
- type: mrr_at_20
|
| 631 |
+
value: 48.214
|
| 632 |
+
- type: mrr_at_30
|
| 633 |
+
value: 48.325
|
| 634 |
+
- type: mrr_at_50
|
| 635 |
+
value: 48.392
|
| 636 |
+
- type: mrr_at_70
|
| 637 |
+
value: 48.418
|
| 638 |
+
- type: mrr_at_100
|
| 639 |
+
value: 48.44
|
| 640 |
+
- type: mrr_at_200
|
| 641 |
+
value: 48.46
|
| 642 |
+
- type: mrr_at_300
|
| 643 |
+
value: 48.461999999999996
|
| 644 |
+
- type: mrr_at_500
|
| 645 |
+
value: 48.466
|
| 646 |
+
- type: mrr_at_700
|
| 647 |
+
value: 48.466
|
| 648 |
+
- type: mrr_at_1000
|
| 649 |
+
value: 48.467
|
| 650 |
+
- task:
|
| 651 |
+
type: Retrieval
|
| 652 |
+
dataset:
|
| 653 |
+
type: dbpedia-entity
|
| 654 |
+
name: MTEB DBPedia
|
| 655 |
+
config: default
|
| 656 |
+
split: test
|
| 657 |
+
revision: None
|
| 658 |
+
metrics:
|
| 659 |
+
- type: ndcg_at_1
|
| 660 |
+
value: 62.375
|
| 661 |
+
- type: ndcg_at_2
|
| 662 |
+
value: 56.286
|
| 663 |
+
- type: ndcg_at_3
|
| 664 |
+
value: 53.665
|
| 665 |
+
- type: ndcg_at_5
|
| 666 |
+
value: 51.139
|
| 667 |
+
- type: ndcg_at_7
|
| 668 |
+
value: 49.873
|
| 669 |
+
- type: ndcg_at_10
|
| 670 |
+
value: 49.056
|
| 671 |
+
- type: ndcg_at_20
|
| 672 |
+
value: 48.783
|
| 673 |
+
- type: ndcg_at_30
|
| 674 |
+
value: 49.166
|
| 675 |
+
- type: ndcg_at_50
|
| 676 |
+
value: 51.141999999999996
|
| 677 |
+
- type: ndcg_at_70
|
| 678 |
+
value: 52.774
|
| 679 |
+
- type: ndcg_at_100
|
| 680 |
+
value: 54.403
|
| 681 |
+
- type: ndcg_at_200
|
| 682 |
+
value: 57.419
|
| 683 |
+
- type: ndcg_at_300
|
| 684 |
+
value: 58.778
|
| 685 |
+
- type: ndcg_at_500
|
| 686 |
+
value: 60.228
|
| 687 |
+
- type: ndcg_at_700
|
| 688 |
+
value: 61.07599999999999
|
| 689 |
+
- type: ndcg_at_1000
|
| 690 |
+
value: 61.846000000000004
|
| 691 |
+
- type: map_at_1
|
| 692 |
+
value: 10.359
|
| 693 |
+
- type: map_at_2
|
| 694 |
+
value: 14.446
|
| 695 |
+
- type: map_at_3
|
| 696 |
+
value: 16.689
|
| 697 |
+
- type: map_at_5
|
| 698 |
+
value: 20.096
|
| 699 |
+
- type: map_at_7
|
| 700 |
+
value: 22.247
|
| 701 |
+
- type: map_at_10
|
| 702 |
+
value: 24.468999999999998
|
| 703 |
+
- type: map_at_20
|
| 704 |
+
value: 28.938000000000002
|
| 705 |
+
- type: map_at_30
|
| 706 |
+
value: 31.134
|
| 707 |
+
- type: map_at_50
|
| 708 |
+
value: 33.403
|
| 709 |
+
- type: map_at_70
|
| 710 |
+
value: 34.486
|
| 711 |
+
- type: map_at_100
|
| 712 |
+
value: 35.337
|
| 713 |
+
- type: map_at_200
|
| 714 |
+
value: 36.364999999999995
|
| 715 |
+
- type: map_at_300
|
| 716 |
+
value: 36.735
|
| 717 |
+
- type: map_at_500
|
| 718 |
+
value: 37.057
|
| 719 |
+
- type: map_at_700
|
| 720 |
+
value: 37.225
|
| 721 |
+
- type: map_at_1000
|
| 722 |
+
value: 37.379
|
| 723 |
+
- type: recall_at_1
|
| 724 |
+
value: 10.359
|
| 725 |
+
- type: recall_at_2
|
| 726 |
+
value: 14.945
|
| 727 |
+
- type: recall_at_3
|
| 728 |
+
value: 17.694
|
| 729 |
+
- type: recall_at_5
|
| 730 |
+
value: 22.677
|
| 731 |
+
- type: recall_at_7
|
| 732 |
+
value: 26.131
|
| 733 |
+
- type: recall_at_10
|
| 734 |
+
value: 30.053
|
| 735 |
+
- type: recall_at_20
|
| 736 |
+
value: 39.518
|
| 737 |
+
- type: recall_at_30
|
| 738 |
+
value: 44.925
|
| 739 |
+
- type: recall_at_50
|
| 740 |
+
value: 52.154
|
| 741 |
+
- type: recall_at_70
|
| 742 |
+
value: 56.729
|
| 743 |
+
- type: recall_at_100
|
| 744 |
+
value: 61.18900000000001
|
| 745 |
+
- type: recall_at_200
|
| 746 |
+
value: 70.407
|
| 747 |
+
- type: recall_at_300
|
| 748 |
+
value: 74.412
|
| 749 |
+
- type: recall_at_500
|
| 750 |
+
value: 78.891
|
| 751 |
+
- type: recall_at_700
|
| 752 |
+
value: 81.74
|
| 753 |
+
- type: recall_at_1000
|
| 754 |
+
value: 84.253
|
| 755 |
+
- type: precision_at_1
|
| 756 |
+
value: 75
|
| 757 |
+
- type: precision_at_2
|
| 758 |
+
value: 64.125
|
| 759 |
+
- type: precision_at_3
|
| 760 |
+
value: 57.833
|
| 761 |
+
- type: precision_at_5
|
| 762 |
+
value: 50.24999999999999
|
| 763 |
+
- type: precision_at_7
|
| 764 |
+
value: 44.75
|
| 765 |
+
- type: precision_at_10
|
| 766 |
+
value: 39.75
|
| 767 |
+
- type: precision_at_20
|
| 768 |
+
value: 30.412
|
| 769 |
+
- type: precision_at_30
|
| 770 |
+
value: 25.141999999999996
|
| 771 |
+
- type: precision_at_50
|
| 772 |
+
value: 19.2
|
| 773 |
+
- type: precision_at_70
|
| 774 |
+
value: 15.729000000000001
|
| 775 |
+
- type: precision_at_100
|
| 776 |
+
value: 12.552
|
| 777 |
+
- type: precision_at_200
|
| 778 |
+
value: 7.866
|
| 779 |
+
- type: precision_at_300
|
| 780 |
+
value: 5.9270000000000005
|
| 781 |
+
- type: precision_at_500
|
| 782 |
+
value: 4.1129999999999995
|
| 783 |
+
- type: precision_at_700
|
| 784 |
+
value: 3.2460000000000004
|
| 785 |
+
- type: precision_at_1000
|
| 786 |
+
value: 2.5260000000000002
|
| 787 |
+
- type: mrr_at_1
|
| 788 |
+
value: 75
|
| 789 |
+
- type: mrr_at_2
|
| 790 |
+
value: 78.625
|
| 791 |
+
- type: mrr_at_3
|
| 792 |
+
value: 79.708
|
| 793 |
+
- type: mrr_at_5
|
| 794 |
+
value: 80.446
|
| 795 |
+
- type: mrr_at_7
|
| 796 |
+
value: 80.862
|
| 797 |
+
- type: mrr_at_10
|
| 798 |
+
value: 81.161
|
| 799 |
+
- type: mrr_at_20
|
| 800 |
+
value: 81.3
|
| 801 |
+
- type: mrr_at_30
|
| 802 |
+
value: 81.348
|
| 803 |
+
- type: mrr_at_50
|
| 804 |
+
value: 81.361
|
| 805 |
+
- type: mrr_at_70
|
| 806 |
+
value: 81.361
|
| 807 |
+
- type: mrr_at_100
|
| 808 |
+
value: 81.361
|
| 809 |
+
- type: mrr_at_200
|
| 810 |
+
value: 81.367
|
| 811 |
+
- type: mrr_at_300
|
| 812 |
+
value: 81.367
|
| 813 |
+
- type: mrr_at_500
|
| 814 |
+
value: 81.368
|
| 815 |
+
- type: mrr_at_700
|
| 816 |
+
value: 81.368
|
| 817 |
+
- type: mrr_at_1000
|
| 818 |
+
value: 81.368
|
| 819 |
+
- task:
|
| 820 |
+
type: Classification
|
| 821 |
+
dataset:
|
| 822 |
+
type: mteb/emotion
|
| 823 |
+
name: MTEB EmotionClassification
|
| 824 |
+
config: default
|
| 825 |
+
split: test
|
| 826 |
+
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
| 827 |
+
metrics:
|
| 828 |
+
- type: accuracy
|
| 829 |
+
value: 50.239999999999995
|
| 830 |
+
- type: f1
|
| 831 |
+
value: 46.42361822342044
|
| 832 |
+
- task:
|
| 833 |
+
type: Retrieval
|
| 834 |
+
dataset:
|
| 835 |
+
type: fever
|
| 836 |
+
name: MTEB FEVER
|
| 837 |
+
config: default
|
| 838 |
+
split: test
|
| 839 |
+
revision: None
|
| 840 |
+
metrics:
|
| 841 |
+
- type: ndcg_at_1
|
| 842 |
+
value: 83.723
|
| 843 |
+
- type: ndcg_at_2
|
| 844 |
+
value: 86.777
|
| 845 |
+
- type: ndcg_at_3
|
| 846 |
+
value: 87.997
|
| 847 |
+
- type: ndcg_at_5
|
| 848 |
+
value: 88.864
|
| 849 |
+
- type: ndcg_at_7
|
| 850 |
+
value: 89.143
|
| 851 |
+
- type: ndcg_at_10
|
| 852 |
+
value: 89.349
|
| 853 |
+
- type: ndcg_at_20
|
| 854 |
+
value: 89.709
|
| 855 |
+
- type: ndcg_at_30
|
| 856 |
+
value: 89.82900000000001
|
| 857 |
+
- type: ndcg_at_50
|
| 858 |
+
value: 89.923
|
| 859 |
+
- type: ndcg_at_70
|
| 860 |
+
value: 89.982
|
| 861 |
+
- type: ndcg_at_100
|
| 862 |
+
value: 90.026
|
| 863 |
+
- type: ndcg_at_200
|
| 864 |
+
value: 90.10000000000001
|
| 865 |
+
- type: ndcg_at_300
|
| 866 |
+
value: 90.12599999999999
|
| 867 |
+
- type: ndcg_at_500
|
| 868 |
+
value: 90.17399999999999
|
| 869 |
+
- type: ndcg_at_700
|
| 870 |
+
value: 90.19
|
| 871 |
+
- type: ndcg_at_1000
|
| 872 |
+
value: 90.208
|
| 873 |
+
- type: map_at_1
|
| 874 |
+
value: 77.64999999999999
|
| 875 |
+
- type: map_at_2
|
| 876 |
+
value: 83.769
|
| 877 |
+
- type: map_at_3
|
| 878 |
+
value: 85.041
|
| 879 |
+
- type: map_at_5
|
| 880 |
+
value: 85.736
|
| 881 |
+
- type: map_at_7
|
| 882 |
+
value: 85.924
|
| 883 |
+
- type: map_at_10
|
| 884 |
+
value: 86.032
|
| 885 |
+
- type: map_at_20
|
| 886 |
+
value: 86.177
|
| 887 |
+
- type: map_at_30
|
| 888 |
+
value: 86.213
|
| 889 |
+
- type: map_at_50
|
| 890 |
+
value: 86.233
|
| 891 |
+
- type: map_at_70
|
| 892 |
+
value: 86.24300000000001
|
| 893 |
+
- type: map_at_100
|
| 894 |
+
value: 86.249
|
| 895 |
+
- type: map_at_200
|
| 896 |
+
value: 86.256
|
| 897 |
+
- type: map_at_300
|
| 898 |
+
value: 86.258
|
| 899 |
+
- type: map_at_500
|
| 900 |
+
value: 86.26
|
| 901 |
+
- type: map_at_700
|
| 902 |
+
value: 86.26
|
| 903 |
+
- type: map_at_1000
|
| 904 |
+
value: 86.261
|
| 905 |
+
- type: recall_at_1
|
| 906 |
+
value: 77.64999999999999
|
| 907 |
+
- type: recall_at_2
|
| 908 |
+
value: 88.53999999999999
|
| 909 |
+
- type: recall_at_3
|
| 910 |
+
value: 91.696
|
| 911 |
+
- type: recall_at_5
|
| 912 |
+
value: 93.916
|
| 913 |
+
- type: recall_at_7
|
| 914 |
+
value: 94.731
|
| 915 |
+
- type: recall_at_10
|
| 916 |
+
value: 95.318
|
| 917 |
+
- type: recall_at_20
|
| 918 |
+
value: 96.507
|
| 919 |
+
- type: recall_at_30
|
| 920 |
+
value: 96.956
|
| 921 |
+
- type: recall_at_50
|
| 922 |
+
value: 97.34899999999999
|
| 923 |
+
- type: recall_at_70
|
| 924 |
+
value: 97.61
|
| 925 |
+
- type: recall_at_100
|
| 926 |
+
value: 97.83
|
| 927 |
+
- type: recall_at_200
|
| 928 |
+
value: 98.223
|
| 929 |
+
- type: recall_at_300
|
| 930 |
+
value: 98.374
|
| 931 |
+
- type: recall_at_500
|
| 932 |
+
value: 98.67899999999999
|
| 933 |
+
- type: recall_at_700
|
| 934 |
+
value: 98.787
|
| 935 |
+
- type: recall_at_1000
|
| 936 |
+
value: 98.919
|
| 937 |
+
- type: precision_at_1
|
| 938 |
+
value: 83.723
|
| 939 |
+
- type: precision_at_2
|
| 940 |
+
value: 48.425000000000004
|
| 941 |
+
- type: precision_at_3
|
| 942 |
+
value: 33.638
|
| 943 |
+
- type: precision_at_5
|
| 944 |
+
value: 20.843
|
| 945 |
+
- type: precision_at_7
|
| 946 |
+
value: 15.079
|
| 947 |
+
- type: precision_at_10
|
| 948 |
+
value: 10.674999999999999
|
| 949 |
+
- type: precision_at_20
|
| 950 |
+
value: 5.457999999999999
|
| 951 |
+
- type: precision_at_30
|
| 952 |
+
value: 3.6740000000000004
|
| 953 |
+
- type: precision_at_50
|
| 954 |
+
value: 2.2239999999999998
|
| 955 |
+
- type: precision_at_70
|
| 956 |
+
value: 1.599
|
| 957 |
+
- type: precision_at_100
|
| 958 |
+
value: 1.125
|
| 959 |
+
- type: precision_at_200
|
| 960 |
+
value: 0.5680000000000001
|
| 961 |
+
- type: precision_at_300
|
| 962 |
+
value: 0.38
|
| 963 |
+
- type: precision_at_500
|
| 964 |
+
value: 0.22999999999999998
|
| 965 |
+
- type: precision_at_700
|
| 966 |
+
value: 0.165
|
| 967 |
+
- type: precision_at_1000
|
| 968 |
+
value: 0.116
|
| 969 |
+
- type: mrr_at_1
|
| 970 |
+
value: 83.723
|
| 971 |
+
- type: mrr_at_2
|
| 972 |
+
value: 88.794
|
| 973 |
+
- type: mrr_at_3
|
| 974 |
+
value: 89.679
|
| 975 |
+
- type: mrr_at_5
|
| 976 |
+
value: 90.049
|
| 977 |
+
- type: mrr_at_7
|
| 978 |
+
value: 90.129
|
| 979 |
+
- type: mrr_at_10
|
| 980 |
+
value: 90.167
|
| 981 |
+
- type: mrr_at_20
|
| 982 |
+
value: 90.208
|
| 983 |
+
- type: mrr_at_30
|
| 984 |
+
value: 90.214
|
| 985 |
+
- type: mrr_at_50
|
| 986 |
+
value: 90.217
|
| 987 |
+
- type: mrr_at_70
|
| 988 |
+
value: 90.218
|
| 989 |
+
- type: mrr_at_100
|
| 990 |
+
value: 90.21900000000001
|
| 991 |
+
- type: mrr_at_200
|
| 992 |
+
value: 90.21900000000001
|
| 993 |
+
- type: mrr_at_300
|
| 994 |
+
value: 90.21900000000001
|
| 995 |
+
- type: mrr_at_500
|
| 996 |
+
value: 90.21900000000001
|
| 997 |
+
- type: mrr_at_700
|
| 998 |
+
value: 90.21900000000001
|
| 999 |
+
- type: mrr_at_1000
|
| 1000 |
+
value: 90.21900000000001
|
| 1001 |
+
- task:
|
| 1002 |
+
type: Retrieval
|
| 1003 |
+
dataset:
|
| 1004 |
+
type: fiqa
|
| 1005 |
+
name: MTEB FiQA2018
|
| 1006 |
+
config: default
|
| 1007 |
+
split: test
|
| 1008 |
+
revision: None
|
| 1009 |
+
metrics:
|
| 1010 |
+
- type: ndcg_at_1
|
| 1011 |
+
value: 59.721999999999994
|
| 1012 |
+
- type: ndcg_at_2
|
| 1013 |
+
value: 56.85
|
| 1014 |
+
- type: ndcg_at_3
|
| 1015 |
+
value: 56.462999999999994
|
| 1016 |
+
- type: ndcg_at_5
|
| 1017 |
+
value: 57.75599999999999
|
| 1018 |
+
- type: ndcg_at_7
|
| 1019 |
+
value: 59.109
|
| 1020 |
+
- type: ndcg_at_10
|
| 1021 |
+
value: 60.402
|
| 1022 |
+
- type: ndcg_at_20
|
| 1023 |
+
value: 63.071999999999996
|
| 1024 |
+
- type: ndcg_at_30
|
| 1025 |
+
value: 64.302
|
| 1026 |
+
- type: ndcg_at_50
|
| 1027 |
+
value: 65.619
|
| 1028 |
+
- type: ndcg_at_70
|
| 1029 |
+
value: 66.161
|
| 1030 |
+
- type: ndcg_at_100
|
| 1031 |
+
value: 66.645
|
| 1032 |
+
- type: ndcg_at_200
|
| 1033 |
+
value: 67.353
|
| 1034 |
+
- type: ndcg_at_300
|
| 1035 |
+
value: 67.646
|
| 1036 |
+
- type: ndcg_at_500
|
| 1037 |
+
value: 67.852
|
| 1038 |
+
- type: ndcg_at_700
|
| 1039 |
+
value: 67.974
|
| 1040 |
+
- type: ndcg_at_1000
|
| 1041 |
+
value: 68.084
|
| 1042 |
+
- type: map_at_1
|
| 1043 |
+
value: 31.56
|
| 1044 |
+
- type: map_at_2
|
| 1045 |
+
value: 42.093
|
| 1046 |
+
- type: map_at_3
|
| 1047 |
+
value: 46.177
|
| 1048 |
+
- type: map_at_5
|
| 1049 |
+
value: 49.78
|
| 1050 |
+
- type: map_at_7
|
| 1051 |
+
value: 51.410999999999994
|
| 1052 |
+
- type: map_at_10
|
| 1053 |
+
value: 52.524
|
| 1054 |
+
- type: map_at_20
|
| 1055 |
+
value: 53.815000000000005
|
| 1056 |
+
- type: map_at_30
|
| 1057 |
+
value: 54.201
|
| 1058 |
+
- type: map_at_50
|
| 1059 |
+
value: 54.531
|
| 1060 |
+
- type: map_at_70
|
| 1061 |
+
value: 54.625
|
| 1062 |
+
- type: map_at_100
|
| 1063 |
+
value: 54.686
|
| 1064 |
+
- type: map_at_200
|
| 1065 |
+
value: 54.757999999999996
|
| 1066 |
+
- type: map_at_300
|
| 1067 |
+
value: 54.776
|
| 1068 |
+
- type: map_at_500
|
| 1069 |
+
value: 54.786
|
| 1070 |
+
- type: map_at_700
|
| 1071 |
+
value: 54.790000000000006
|
| 1072 |
+
- type: map_at_1000
|
| 1073 |
+
value: 54.793000000000006
|
| 1074 |
+
- type: recall_at_1
|
| 1075 |
+
value: 31.56
|
| 1076 |
+
- type: recall_at_2
|
| 1077 |
+
value: 44.858
|
| 1078 |
+
- type: recall_at_3
|
| 1079 |
+
value: 51.11
|
| 1080 |
+
- type: recall_at_5
|
| 1081 |
+
value: 58.394
|
| 1082 |
+
- type: recall_at_7
|
| 1083 |
+
value: 63.001
|
| 1084 |
+
- type: recall_at_10
|
| 1085 |
+
value: 66.81200000000001
|
| 1086 |
+
- type: recall_at_20
|
| 1087 |
+
value: 74.901
|
| 1088 |
+
- type: recall_at_30
|
| 1089 |
+
value: 79.218
|
| 1090 |
+
- type: recall_at_50
|
| 1091 |
+
value: 84.49
|
| 1092 |
+
- type: recall_at_70
|
| 1093 |
+
value: 87.003
|
| 1094 |
+
- type: recall_at_100
|
| 1095 |
+
value: 89.345
|
| 1096 |
+
- type: recall_at_200
|
| 1097 |
+
value: 93.173
|
| 1098 |
+
- type: recall_at_300
|
| 1099 |
+
value: 94.906
|
| 1100 |
+
- type: recall_at_500
|
| 1101 |
+
value: 96.223
|
| 1102 |
+
- type: recall_at_700
|
| 1103 |
+
value: 97.043
|
| 1104 |
+
- type: recall_at_1000
|
| 1105 |
+
value: 97.785
|
| 1106 |
+
- type: precision_at_1
|
| 1107 |
+
value: 59.721999999999994
|
| 1108 |
+
- type: precision_at_2
|
| 1109 |
+
value: 46.682
|
| 1110 |
+
- type: precision_at_3
|
| 1111 |
+
value: 37.602999999999994
|
| 1112 |
+
- type: precision_at_5
|
| 1113 |
+
value: 27.500000000000004
|
| 1114 |
+
- type: precision_at_7
|
| 1115 |
+
value: 21.847
|
| 1116 |
+
- type: precision_at_10
|
| 1117 |
+
value: 16.667
|
| 1118 |
+
- type: precision_at_20
|
| 1119 |
+
value: 9.545
|
| 1120 |
+
- type: precision_at_30
|
| 1121 |
+
value: 6.795
|
| 1122 |
+
- type: precision_at_50
|
| 1123 |
+
value: 4.38
|
| 1124 |
+
- type: precision_at_70
|
| 1125 |
+
value: 3.221
|
| 1126 |
+
- type: precision_at_100
|
| 1127 |
+
value: 2.319
|
| 1128 |
+
- type: precision_at_200
|
| 1129 |
+
value: 1.2149999999999999
|
| 1130 |
+
- type: precision_at_300
|
| 1131 |
+
value: 0.827
|
| 1132 |
+
- type: precision_at_500
|
| 1133 |
+
value: 0.504
|
| 1134 |
+
- type: precision_at_700
|
| 1135 |
+
value: 0.364
|
| 1136 |
+
- type: precision_at_1000
|
| 1137 |
+
value: 0.257
|
| 1138 |
+
- type: mrr_at_1
|
| 1139 |
+
value: 59.721999999999994
|
| 1140 |
+
- type: mrr_at_2
|
| 1141 |
+
value: 64.506
|
| 1142 |
+
- type: mrr_at_3
|
| 1143 |
+
value: 65.792
|
| 1144 |
+
- type: mrr_at_5
|
| 1145 |
+
value: 66.965
|
| 1146 |
+
- type: mrr_at_7
|
| 1147 |
+
value: 67.34700000000001
|
| 1148 |
+
- type: mrr_at_10
|
| 1149 |
+
value: 67.57
|
| 1150 |
+
- type: mrr_at_20
|
| 1151 |
+
value: 67.896
|
| 1152 |
+
- type: mrr_at_30
|
| 1153 |
+
value: 68.008
|
| 1154 |
+
- type: mrr_at_50
|
| 1155 |
+
value: 68.083
|
| 1156 |
+
- type: mrr_at_70
|
| 1157 |
+
value: 68.105
|
| 1158 |
+
- type: mrr_at_100
|
| 1159 |
+
value: 68.116
|
| 1160 |
+
- type: mrr_at_200
|
| 1161 |
+
value: 68.12700000000001
|
| 1162 |
+
- type: mrr_at_300
|
| 1163 |
+
value: 68.13
|
| 1164 |
+
- type: mrr_at_500
|
| 1165 |
+
value: 68.132
|
| 1166 |
+
- type: mrr_at_700
|
| 1167 |
+
value: 68.133
|
| 1168 |
+
- type: mrr_at_1000
|
| 1169 |
+
value: 68.133
|
| 1170 |
+
- task:
|
| 1171 |
+
type: Retrieval
|
| 1172 |
+
dataset:
|
| 1173 |
+
type: hotpotqa
|
| 1174 |
+
name: MTEB HotpotQA
|
| 1175 |
+
config: default
|
| 1176 |
+
split: test
|
| 1177 |
+
revision: None
|
| 1178 |
+
metrics:
|
| 1179 |
+
- type: ndcg_at_1
|
| 1180 |
+
value: 81.796
|
| 1181 |
+
- type: ndcg_at_2
|
| 1182 |
+
value: 67.999
|
| 1183 |
+
- type: ndcg_at_3
|
| 1184 |
+
value: 72.15599999999999
|
| 1185 |
+
- type: ndcg_at_5
|
| 1186 |
+
value: 74.99900000000001
|
| 1187 |
+
- type: ndcg_at_7
|
| 1188 |
+
value: 76.179
|
| 1189 |
+
- type: ndcg_at_10
|
| 1190 |
+
value: 77.022
|
| 1191 |
+
- type: ndcg_at_20
|
| 1192 |
+
value: 78.173
|
| 1193 |
+
- type: ndcg_at_30
|
| 1194 |
+
value: 78.648
|
| 1195 |
+
- type: ndcg_at_50
|
| 1196 |
+
value: 79.104
|
| 1197 |
+
- type: ndcg_at_70
|
| 1198 |
+
value: 79.335
|
| 1199 |
+
- type: ndcg_at_100
|
| 1200 |
+
value: 79.56
|
| 1201 |
+
- type: ndcg_at_200
|
| 1202 |
+
value: 79.911
|
| 1203 |
+
- type: ndcg_at_300
|
| 1204 |
+
value: 80.045
|
| 1205 |
+
- type: ndcg_at_500
|
| 1206 |
+
value: 80.19500000000001
|
| 1207 |
+
- type: ndcg_at_700
|
| 1208 |
+
value: 80.281
|
| 1209 |
+
- type: ndcg_at_1000
|
| 1210 |
+
value: 80.35
|
| 1211 |
+
- type: map_at_1
|
| 1212 |
+
value: 40.898
|
| 1213 |
+
- type: map_at_2
|
| 1214 |
+
value: 62.016000000000005
|
| 1215 |
+
- type: map_at_3
|
| 1216 |
+
value: 66.121
|
| 1217 |
+
- type: map_at_5
|
| 1218 |
+
value: 68.471
|
| 1219 |
+
- type: map_at_7
|
| 1220 |
+
value: 69.261
|
| 1221 |
+
- type: map_at_10
|
| 1222 |
+
value: 69.738
|
| 1223 |
+
- type: map_at_20
|
| 1224 |
+
value: 70.208
|
| 1225 |
+
- type: map_at_30
|
| 1226 |
+
value: 70.343
|
| 1227 |
+
- type: map_at_50
|
| 1228 |
+
value: 70.43700000000001
|
| 1229 |
+
- type: map_at_70
|
| 1230 |
+
value: 70.47099999999999
|
| 1231 |
+
- type: map_at_100
|
| 1232 |
+
value: 70.498
|
| 1233 |
+
- type: map_at_200
|
| 1234 |
+
value: 70.526
|
| 1235 |
+
- type: map_at_300
|
| 1236 |
+
value: 70.533
|
| 1237 |
+
- type: map_at_500
|
| 1238 |
+
value: 70.538
|
| 1239 |
+
- type: map_at_700
|
| 1240 |
+
value: 70.541
|
| 1241 |
+
- type: map_at_1000
|
| 1242 |
+
value: 70.542
|
| 1243 |
+
- type: recall_at_1
|
| 1244 |
+
value: 40.898
|
| 1245 |
+
- type: recall_at_2
|
| 1246 |
+
value: 63.964
|
| 1247 |
+
- type: recall_at_3
|
| 1248 |
+
value: 70.743
|
| 1249 |
+
- type: recall_at_5
|
| 1250 |
+
value: 76.36699999999999
|
| 1251 |
+
- type: recall_at_7
|
| 1252 |
+
value: 79.142
|
| 1253 |
+
- type: recall_at_10
|
| 1254 |
+
value: 81.404
|
| 1255 |
+
- type: recall_at_20
|
| 1256 |
+
value: 85.111
|
| 1257 |
+
- type: recall_at_30
|
| 1258 |
+
value: 86.92800000000001
|
| 1259 |
+
- type: recall_at_50
|
| 1260 |
+
value: 88.899
|
| 1261 |
+
- type: recall_at_70
|
| 1262 |
+
value: 90.01400000000001
|
| 1263 |
+
- type: recall_at_100
|
| 1264 |
+
value: 91.19500000000001
|
| 1265 |
+
- type: recall_at_200
|
| 1266 |
+
value: 93.234
|
| 1267 |
+
- type: recall_at_300
|
| 1268 |
+
value: 94.105
|
| 1269 |
+
- type: recall_at_500
|
| 1270 |
+
value: 95.159
|
| 1271 |
+
- type: recall_at_700
|
| 1272 |
+
value: 95.8
|
| 1273 |
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- type: recall_at_1000
|
| 1274 |
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value: 96.34700000000001
|
| 1275 |
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- type: precision_at_1
|
| 1276 |
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value: 81.796
|
| 1277 |
+
- type: precision_at_2
|
| 1278 |
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value: 63.964
|
| 1279 |
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- type: precision_at_3
|
| 1280 |
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value: 47.162
|
| 1281 |
+
- type: precision_at_5
|
| 1282 |
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value: 30.547
|
| 1283 |
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- type: precision_at_7
|
| 1284 |
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value: 22.612
|
| 1285 |
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- type: precision_at_10
|
| 1286 |
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value: 16.281000000000002
|
| 1287 |
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- type: precision_at_20
|
| 1288 |
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value: 8.511000000000001
|
| 1289 |
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- type: precision_at_30
|
| 1290 |
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value: 5.795
|
| 1291 |
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- type: precision_at_50
|
| 1292 |
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value: 3.556
|
| 1293 |
+
- type: precision_at_70
|
| 1294 |
+
value: 2.572
|
| 1295 |
+
- type: precision_at_100
|
| 1296 |
+
value: 1.8239999999999998
|
| 1297 |
+
- type: precision_at_200
|
| 1298 |
+
value: 0.932
|
| 1299 |
+
- type: precision_at_300
|
| 1300 |
+
value: 0.627
|
| 1301 |
+
- type: precision_at_500
|
| 1302 |
+
value: 0.381
|
| 1303 |
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- type: precision_at_700
|
| 1304 |
+
value: 0.27399999999999997
|
| 1305 |
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- type: precision_at_1000
|
| 1306 |
+
value: 0.193
|
| 1307 |
+
- type: mrr_at_1
|
| 1308 |
+
value: 81.796
|
| 1309 |
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- type: mrr_at_2
|
| 1310 |
+
value: 85.69200000000001
|
| 1311 |
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- type: mrr_at_3
|
| 1312 |
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value: 86.52
|
| 1313 |
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- type: mrr_at_5
|
| 1314 |
+
value: 86.973
|
| 1315 |
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- type: mrr_at_7
|
| 1316 |
+
value: 87.13300000000001
|
| 1317 |
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- type: mrr_at_10
|
| 1318 |
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value: 87.208
|
| 1319 |
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- type: mrr_at_20
|
| 1320 |
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value: 87.303
|
| 1321 |
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- type: mrr_at_30
|
| 1322 |
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value: 87.32799999999999
|
| 1323 |
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- type: mrr_at_50
|
| 1324 |
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value: 87.347
|
| 1325 |
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- type: mrr_at_70
|
| 1326 |
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value: 87.35199999999999
|
| 1327 |
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- type: mrr_at_100
|
| 1328 |
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value: 87.355
|
| 1329 |
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- type: mrr_at_200
|
| 1330 |
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value: 87.357
|
| 1331 |
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- type: mrr_at_300
|
| 1332 |
+
value: 87.357
|
| 1333 |
+
- type: mrr_at_500
|
| 1334 |
+
value: 87.358
|
| 1335 |
+
- type: mrr_at_700
|
| 1336 |
+
value: 87.358
|
| 1337 |
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- type: mrr_at_1000
|
| 1338 |
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value: 87.358
|
| 1339 |
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- task:
|
| 1340 |
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type: Classification
|
| 1341 |
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dataset:
|
| 1342 |
+
type: mteb/imdb
|
| 1343 |
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name: MTEB ImdbClassification
|
| 1344 |
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config: default
|
| 1345 |
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split: test
|
| 1346 |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
| 1347 |
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metrics:
|
| 1348 |
+
- type: accuracy
|
| 1349 |
+
value: 94.79200000000002
|
| 1350 |
+
- type: ap
|
| 1351 |
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value: 92.54484356773553
|
| 1352 |
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- type: f1
|
| 1353 |
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value: 94.78965313682525
|
| 1354 |
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- task:
|
| 1355 |
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type: Retrieval
|
| 1356 |
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dataset:
|
| 1357 |
+
type: msmarco
|
| 1358 |
+
name: MTEB MSMARCO
|
| 1359 |
+
config: default
|
| 1360 |
+
split: dev
|
| 1361 |
+
revision: None
|
| 1362 |
+
metrics:
|
| 1363 |
+
- type: ndcg_at_1
|
| 1364 |
+
value: 24.398
|
| 1365 |
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- type: ndcg_at_2
|
| 1366 |
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value: 31.336000000000002
|
| 1367 |
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- type: ndcg_at_3
|
| 1368 |
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value: 35.266999999999996
|
| 1369 |
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- type: ndcg_at_5
|
| 1370 |
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value: 39.356
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| 1371 |
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- type: ndcg_at_7
|
| 1372 |
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value: 41.562
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| 1373 |
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- type: ndcg_at_10
|
| 1374 |
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value: 43.408
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| 1375 |
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- type: ndcg_at_20
|
| 1376 |
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value: 46.107
|
| 1377 |
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- type: ndcg_at_30
|
| 1378 |
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value: 47.164
|
| 1379 |
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- type: ndcg_at_50
|
| 1380 |
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value: 48.126000000000005
|
| 1381 |
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- type: ndcg_at_70
|
| 1382 |
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value: 48.626999999999995
|
| 1383 |
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- type: ndcg_at_100
|
| 1384 |
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value: 49.043
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| 1385 |
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- type: ndcg_at_200
|
| 1386 |
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value: 49.575
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| 1387 |
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- type: ndcg_at_300
|
| 1388 |
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value: 49.794
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| 1389 |
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- type: ndcg_at_500
|
| 1390 |
+
value: 49.942
|
| 1391 |
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- type: ndcg_at_700
|
| 1392 |
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value: 50.014
|
| 1393 |
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- type: ndcg_at_1000
|
| 1394 |
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value: 50.077000000000005
|
| 1395 |
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- type: map_at_1
|
| 1396 |
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value: 23.723
|
| 1397 |
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- type: map_at_2
|
| 1398 |
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value: 29.593000000000004
|
| 1399 |
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- type: map_at_3
|
| 1400 |
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value: 32.273
|
| 1401 |
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- type: map_at_5
|
| 1402 |
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value: 34.587
|
| 1403 |
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- type: map_at_7
|
| 1404 |
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value: 35.589999999999996
|
| 1405 |
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- type: map_at_10
|
| 1406 |
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value: 36.296
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| 1407 |
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- type: map_at_20
|
| 1408 |
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value: 37.059999999999995
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| 1409 |
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- type: map_at_30
|
| 1410 |
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value: 37.265
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| 1411 |
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- type: map_at_50
|
| 1412 |
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value: 37.402
|
| 1413 |
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- type: map_at_70
|
| 1414 |
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value: 37.454
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| 1415 |
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- type: map_at_100
|
| 1416 |
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value: 37.486999999999995
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| 1417 |
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- type: map_at_200
|
| 1418 |
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value: 37.516
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| 1419 |
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- type: map_at_300
|
| 1420 |
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value: 37.524
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| 1421 |
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- type: map_at_500
|
| 1422 |
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value: 37.528
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| 1423 |
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- type: map_at_700
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| 1424 |
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value: 37.529
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| 1425 |
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- type: map_at_1000
|
| 1426 |
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value: 37.53
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| 1427 |
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- type: recall_at_1
|
| 1428 |
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value: 23.723
|
| 1429 |
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- type: recall_at_2
|
| 1430 |
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value: 35.355
|
| 1431 |
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- type: recall_at_3
|
| 1432 |
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value: 43.22
|
| 1433 |
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- type: recall_at_5
|
| 1434 |
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value: 53.025
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| 1435 |
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- type: recall_at_7
|
| 1436 |
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value: 59.327
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| 1437 |
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- type: recall_at_10
|
| 1438 |
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value: 65.302
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| 1439 |
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- type: recall_at_20
|
| 1440 |
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value: 75.765
|
| 1441 |
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- type: recall_at_30
|
| 1442 |
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value: 80.632
|
| 1443 |
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- type: recall_at_50
|
| 1444 |
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value: 85.63499999999999
|
| 1445 |
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- type: recall_at_70
|
| 1446 |
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value: 88.554
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| 1447 |
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- type: recall_at_100
|
| 1448 |
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value: 91.16300000000001
|
| 1449 |
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- type: recall_at_200
|
| 1450 |
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value: 94.85
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| 1451 |
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- type: recall_at_300
|
| 1452 |
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value: 96.532
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| 1453 |
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- type: recall_at_500
|
| 1454 |
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value: 97.751
|
| 1455 |
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- type: recall_at_700
|
| 1456 |
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value: 98.383
|
| 1457 |
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- type: recall_at_1000
|
| 1458 |
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value: 98.97
|
| 1459 |
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- type: precision_at_1
|
| 1460 |
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value: 24.398
|
| 1461 |
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- type: precision_at_2
|
| 1462 |
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value: 18.274
|
| 1463 |
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- type: precision_at_3
|
| 1464 |
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value: 14.951999999999998
|
| 1465 |
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- type: precision_at_5
|
| 1466 |
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value: 11.052
|
| 1467 |
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- type: precision_at_7
|
| 1468 |
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value: 8.84
|
| 1469 |
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- type: precision_at_10
|
| 1470 |
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value: 6.8309999999999995
|
| 1471 |
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- type: precision_at_20
|
| 1472 |
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value: 3.978
|
| 1473 |
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- type: precision_at_30
|
| 1474 |
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value: 2.827
|
| 1475 |
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- type: precision_at_50
|
| 1476 |
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value: 1.807
|
| 1477 |
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- type: precision_at_70
|
| 1478 |
+
value: 1.336
|
| 1479 |
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- type: precision_at_100
|
| 1480 |
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value: 0.964
|
| 1481 |
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- type: precision_at_200
|
| 1482 |
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value: 0.502
|
| 1483 |
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- type: precision_at_300
|
| 1484 |
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value: 0.34099999999999997
|
| 1485 |
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- type: precision_at_500
|
| 1486 |
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value: 0.208
|
| 1487 |
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- type: precision_at_700
|
| 1488 |
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value: 0.15
|
| 1489 |
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- type: precision_at_1000
|
| 1490 |
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value: 0.105
|
| 1491 |
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- type: mrr_at_1
|
| 1492 |
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value: 24.398
|
| 1493 |
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- type: mrr_at_2
|
| 1494 |
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value: 30.351
|
| 1495 |
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- type: mrr_at_3
|
| 1496 |
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value: 33.001000000000005
|
| 1497 |
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- type: mrr_at_5
|
| 1498 |
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value: 35.228
|
| 1499 |
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- type: mrr_at_7
|
| 1500 |
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value: 36.223
|
| 1501 |
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- type: mrr_at_10
|
| 1502 |
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value: 36.903999999999996
|
| 1503 |
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- type: mrr_at_20
|
| 1504 |
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value: 37.631
|
| 1505 |
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- type: mrr_at_30
|
| 1506 |
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value: 37.830000000000005
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| 1507 |
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- type: mrr_at_50
|
| 1508 |
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value: 37.955
|
| 1509 |
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- type: mrr_at_70
|
| 1510 |
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value: 38.003
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| 1511 |
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- type: mrr_at_100
|
| 1512 |
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value: 38.033
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| 1513 |
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- type: mrr_at_200
|
| 1514 |
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value: 38.059
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| 1515 |
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- type: mrr_at_300
|
| 1516 |
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value: 38.066
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| 1517 |
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- type: mrr_at_500
|
| 1518 |
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value: 38.068999999999996
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| 1519 |
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- type: mrr_at_700
|
| 1520 |
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value: 38.07
|
| 1521 |
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- type: mrr_at_1000
|
| 1522 |
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value: 38.07
|
| 1523 |
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- task:
|
| 1524 |
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type: Classification
|
| 1525 |
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dataset:
|
| 1526 |
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type: mteb/mtop_domain
|
| 1527 |
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name: MTEB MTOPDomainClassification (en)
|
| 1528 |
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config: en
|
| 1529 |
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split: test
|
| 1530 |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
| 1531 |
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metrics:
|
| 1532 |
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- type: accuracy
|
| 1533 |
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value: 96.35658914728683
|
| 1534 |
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- type: f1
|
| 1535 |
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value: 96.15039630903114
|
| 1536 |
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- task:
|
| 1537 |
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type: Classification
|
| 1538 |
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dataset:
|
| 1539 |
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type: mteb/mtop_intent
|
| 1540 |
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name: MTEB MTOPIntentClassification (en)
|
| 1541 |
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config: en
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| 1542 |
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split: test
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| 1543 |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
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| 1544 |
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metrics:
|
| 1545 |
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- type: accuracy
|
| 1546 |
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value: 86.29730962152303
|
| 1547 |
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- type: f1
|
| 1548 |
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value: 71.12166316567485
|
| 1549 |
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- task:
|
| 1550 |
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type: Classification
|
| 1551 |
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dataset:
|
| 1552 |
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type: mteb/amazon_massive_intent
|
| 1553 |
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name: MTEB MassiveIntentClassification (en)
|
| 1554 |
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config: en
|
| 1555 |
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split: test
|
| 1556 |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
| 1557 |
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metrics:
|
| 1558 |
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- type: accuracy
|
| 1559 |
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value: 79.98991257565568
|
| 1560 |
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- type: f1
|
| 1561 |
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value: 77.41680115095276
|
| 1562 |
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- task:
|
| 1563 |
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type: Classification
|
| 1564 |
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dataset:
|
| 1565 |
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type: mteb/amazon_massive_scenario
|
| 1566 |
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name: MTEB MassiveScenarioClassification (en)
|
| 1567 |
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config: en
|
| 1568 |
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split: test
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| 1569 |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
| 1570 |
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metrics:
|
| 1571 |
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- type: accuracy
|
| 1572 |
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value: 82.1990585070612
|
| 1573 |
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- type: f1
|
| 1574 |
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value: 82.23719179179362
|
| 1575 |
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- task:
|
| 1576 |
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type: Clustering
|
| 1577 |
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dataset:
|
| 1578 |
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type: mteb/medrxiv-clustering-p2p
|
| 1579 |
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name: MTEB MedrxivClusteringP2P
|
| 1580 |
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config: default
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| 1581 |
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split: test
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| 1582 |
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revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
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| 1583 |
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metrics:
|
| 1584 |
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- type: v_measure
|
| 1585 |
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value: 40.03019554933584
|
| 1586 |
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- task:
|
| 1587 |
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type: Clustering
|
| 1588 |
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dataset:
|
| 1589 |
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type: mteb/medrxiv-clustering-s2s
|
| 1590 |
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name: MTEB MedrxivClusteringS2S
|
| 1591 |
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config: default
|
| 1592 |
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split: test
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| 1593 |
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revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
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| 1594 |
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metrics:
|
| 1595 |
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- type: v_measure
|
| 1596 |
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value: 38.999760551497815
|
| 1597 |
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- task:
|
| 1598 |
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type: Reranking
|
| 1599 |
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dataset:
|
| 1600 |
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type: mteb/mind_small
|
| 1601 |
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name: MTEB MindSmallReranking
|
| 1602 |
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config: default
|
| 1603 |
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split: test
|
| 1604 |
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revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
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| 1605 |
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metrics:
|
| 1606 |
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- type: map
|
| 1607 |
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value: 32.72383151953079
|
| 1608 |
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- type: mrr
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| 1609 |
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value: 33.93989699030721
|
| 1610 |
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- task:
|
| 1611 |
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type: Retrieval
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| 1612 |
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dataset:
|
| 1613 |
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type: nfcorpus
|
| 1614 |
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name: MTEB NFCorpus
|
| 1615 |
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config: default
|
| 1616 |
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split: test
|
| 1617 |
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revision: None
|
| 1618 |
+
metrics:
|
| 1619 |
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- type: ndcg_at_1
|
| 1620 |
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value: 51.858000000000004
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| 1621 |
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- type: ndcg_at_2
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| 1622 |
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value: 49.675999999999995
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| 1623 |
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- type: ndcg_at_3
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| 1624 |
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value: 47.519
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| 1626 |
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value: 45.198
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| 1627 |
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| 1628 |
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value: 43.504
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| 1629 |
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- type: ndcg_at_10
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| 1630 |
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value: 41.88
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| 1631 |
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- type: ndcg_at_20
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| 1632 |
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value: 39.122
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| 1633 |
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- type: ndcg_at_30
|
| 1634 |
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value: 37.95
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| 1635 |
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- type: ndcg_at_50
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| 1636 |
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value: 37.602999999999994
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| 1637 |
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- type: ndcg_at_70
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| 1638 |
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value: 37.836
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| 1639 |
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- type: ndcg_at_100
|
| 1640 |
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value: 38.493
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| 1641 |
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- type: ndcg_at_200
|
| 1642 |
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value: 40.187
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| 1643 |
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|
| 1644 |
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value: 41.524
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| 1645 |
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- type: ndcg_at_500
|
| 1646 |
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value: 43.657000000000004
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| 1647 |
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- type: ndcg_at_700
|
| 1648 |
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value: 45.234
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| 1649 |
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- type: ndcg_at_1000
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| 1650 |
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value: 47.047
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| 1651 |
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- type: map_at_1
|
| 1652 |
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value: 6.392
|
| 1653 |
+
- type: map_at_2
|
| 1654 |
+
value: 10.113
|
| 1655 |
+
- type: map_at_3
|
| 1656 |
+
value: 11.543000000000001
|
| 1657 |
+
- type: map_at_5
|
| 1658 |
+
value: 13.729
|
| 1659 |
+
- type: map_at_7
|
| 1660 |
+
value: 14.985000000000001
|
| 1661 |
+
- type: map_at_10
|
| 1662 |
+
value: 16.217000000000002
|
| 1663 |
+
- type: map_at_20
|
| 1664 |
+
value: 18.106
|
| 1665 |
+
- type: map_at_30
|
| 1666 |
+
value: 18.878
|
| 1667 |
+
- type: map_at_50
|
| 1668 |
+
value: 19.822
|
| 1669 |
+
- type: map_at_70
|
| 1670 |
+
value: 20.352999999999998
|
| 1671 |
+
- type: map_at_100
|
| 1672 |
+
value: 20.827
|
| 1673 |
+
- type: map_at_200
|
| 1674 |
+
value: 21.512
|
| 1675 |
+
- type: map_at_300
|
| 1676 |
+
value: 21.826
|
| 1677 |
+
- type: map_at_500
|
| 1678 |
+
value: 22.155
|
| 1679 |
+
- type: map_at_700
|
| 1680 |
+
value: 22.349
|
| 1681 |
+
- type: map_at_1000
|
| 1682 |
+
value: 22.531000000000002
|
| 1683 |
+
- type: recall_at_1
|
| 1684 |
+
value: 6.392
|
| 1685 |
+
- type: recall_at_2
|
| 1686 |
+
value: 11.215
|
| 1687 |
+
- type: recall_at_3
|
| 1688 |
+
value: 13.231000000000002
|
| 1689 |
+
- type: recall_at_5
|
| 1690 |
+
value: 16.66
|
| 1691 |
+
- type: recall_at_7
|
| 1692 |
+
value: 18.802
|
| 1693 |
+
- type: recall_at_10
|
| 1694 |
+
value: 21.185000000000002
|
| 1695 |
+
- type: recall_at_20
|
| 1696 |
+
value: 25.35
|
| 1697 |
+
- type: recall_at_30
|
| 1698 |
+
value: 27.91
|
| 1699 |
+
- type: recall_at_50
|
| 1700 |
+
value: 32.845
|
| 1701 |
+
- type: recall_at_70
|
| 1702 |
+
value: 35.789
|
| 1703 |
+
- type: recall_at_100
|
| 1704 |
+
value: 39.247
|
| 1705 |
+
- type: recall_at_200
|
| 1706 |
+
value: 46.655
|
| 1707 |
+
- type: recall_at_300
|
| 1708 |
+
value: 51.43299999999999
|
| 1709 |
+
- type: recall_at_500
|
| 1710 |
+
value: 59.472
|
| 1711 |
+
- type: recall_at_700
|
| 1712 |
+
value: 64.742
|
| 1713 |
+
- type: recall_at_1000
|
| 1714 |
+
value: 70.97099999999999
|
| 1715 |
+
- type: precision_at_1
|
| 1716 |
+
value: 53.559999999999995
|
| 1717 |
+
- type: precision_at_2
|
| 1718 |
+
value: 48.762
|
| 1719 |
+
- type: precision_at_3
|
| 1720 |
+
value: 44.169000000000004
|
| 1721 |
+
- type: precision_at_5
|
| 1722 |
+
value: 39.071
|
| 1723 |
+
- type: precision_at_7
|
| 1724 |
+
value: 35.161
|
| 1725 |
+
- type: precision_at_10
|
| 1726 |
+
value: 31.238
|
| 1727 |
+
- type: precision_at_20
|
| 1728 |
+
value: 23.064999999999998
|
| 1729 |
+
- type: precision_at_30
|
| 1730 |
+
value: 18.844
|
| 1731 |
+
- type: precision_at_50
|
| 1732 |
+
value: 14.601
|
| 1733 |
+
- type: precision_at_70
|
| 1734 |
+
value: 12.088000000000001
|
| 1735 |
+
- type: precision_at_100
|
| 1736 |
+
value: 9.844999999999999
|
| 1737 |
+
- type: precision_at_200
|
| 1738 |
+
value: 6.358
|
| 1739 |
+
- type: precision_at_300
|
| 1740 |
+
value: 4.915
|
| 1741 |
+
- type: precision_at_500
|
| 1742 |
+
value: 3.531
|
| 1743 |
+
- type: precision_at_700
|
| 1744 |
+
value: 2.8649999999999998
|
| 1745 |
+
- type: precision_at_1000
|
| 1746 |
+
value: 2.289
|
| 1747 |
+
- type: mrr_at_1
|
| 1748 |
+
value: 54.17999999999999
|
| 1749 |
+
- type: mrr_at_2
|
| 1750 |
+
value: 59.288
|
| 1751 |
+
- type: mrr_at_3
|
| 1752 |
+
value: 60.836
|
| 1753 |
+
- type: mrr_at_5
|
| 1754 |
+
value: 62.275999999999996
|
| 1755 |
+
- type: mrr_at_7
|
| 1756 |
+
value: 62.688
|
| 1757 |
+
- type: mrr_at_10
|
| 1758 |
+
value: 62.865
|
| 1759 |
+
- type: mrr_at_20
|
| 1760 |
+
value: 63.11
|
| 1761 |
+
- type: mrr_at_30
|
| 1762 |
+
value: 63.193999999999996
|
| 1763 |
+
- type: mrr_at_50
|
| 1764 |
+
value: 63.258
|
| 1765 |
+
- type: mrr_at_70
|
| 1766 |
+
value: 63.278
|
| 1767 |
+
- type: mrr_at_100
|
| 1768 |
+
value: 63.297000000000004
|
| 1769 |
+
- type: mrr_at_200
|
| 1770 |
+
value: 63.315999999999995
|
| 1771 |
+
- type: mrr_at_300
|
| 1772 |
+
value: 63.318
|
| 1773 |
+
- type: mrr_at_500
|
| 1774 |
+
value: 63.32299999999999
|
| 1775 |
+
- type: mrr_at_700
|
| 1776 |
+
value: 63.324000000000005
|
| 1777 |
+
- type: mrr_at_1000
|
| 1778 |
+
value: 63.324999999999996
|
| 1779 |
+
- task:
|
| 1780 |
+
type: Retrieval
|
| 1781 |
+
dataset:
|
| 1782 |
+
type: nq
|
| 1783 |
+
name: MTEB NQ
|
| 1784 |
+
config: default
|
| 1785 |
+
split: test
|
| 1786 |
+
revision: None
|
| 1787 |
+
metrics:
|
| 1788 |
+
- type: ndcg_at_1
|
| 1789 |
+
value: 50.897999999999996
|
| 1790 |
+
- type: ndcg_at_2
|
| 1791 |
+
value: 59.126
|
| 1792 |
+
- type: ndcg_at_3
|
| 1793 |
+
value: 63.093999999999994
|
| 1794 |
+
- type: ndcg_at_5
|
| 1795 |
+
value: 67.197
|
| 1796 |
+
- type: ndcg_at_7
|
| 1797 |
+
value: 68.719
|
| 1798 |
+
- type: ndcg_at_10
|
| 1799 |
+
value: 69.915
|
| 1800 |
+
- type: ndcg_at_20
|
| 1801 |
+
value: 71.229
|
| 1802 |
+
- type: ndcg_at_30
|
| 1803 |
+
value: 71.667
|
| 1804 |
+
- type: ndcg_at_50
|
| 1805 |
+
value: 71.98
|
| 1806 |
+
- type: ndcg_at_70
|
| 1807 |
+
value: 72.127
|
| 1808 |
+
- type: ndcg_at_100
|
| 1809 |
+
value: 72.217
|
| 1810 |
+
- type: ndcg_at_200
|
| 1811 |
+
value: 72.319
|
| 1812 |
+
- type: ndcg_at_300
|
| 1813 |
+
value: 72.347
|
| 1814 |
+
- type: ndcg_at_500
|
| 1815 |
+
value: 72.37
|
| 1816 |
+
- type: ndcg_at_700
|
| 1817 |
+
value: 72.379
|
| 1818 |
+
- type: ndcg_at_1000
|
| 1819 |
+
value: 72.381
|
| 1820 |
+
- type: map_at_1
|
| 1821 |
+
value: 45.297
|
| 1822 |
+
- type: map_at_2
|
| 1823 |
+
value: 55.596000000000004
|
| 1824 |
+
- type: map_at_3
|
| 1825 |
+
value: 58.724
|
| 1826 |
+
- type: map_at_5
|
| 1827 |
+
value: 61.387
|
| 1828 |
+
- type: map_at_7
|
| 1829 |
+
value: 62.173
|
| 1830 |
+
- type: map_at_10
|
| 1831 |
+
value: 62.69
|
| 1832 |
+
- type: map_at_20
|
| 1833 |
+
value: 63.125
|
| 1834 |
+
- type: map_at_30
|
| 1835 |
+
value: 63.223
|
| 1836 |
+
- type: map_at_50
|
| 1837 |
+
value: 63.27700000000001
|
| 1838 |
+
- type: map_at_70
|
| 1839 |
+
value: 63.295
|
| 1840 |
+
- type: map_at_100
|
| 1841 |
+
value: 63.303
|
| 1842 |
+
- type: map_at_200
|
| 1843 |
+
value: 63.31
|
| 1844 |
+
- type: map_at_300
|
| 1845 |
+
value: 63.31099999999999
|
| 1846 |
+
- type: map_at_500
|
| 1847 |
+
value: 63.312000000000005
|
| 1848 |
+
- type: map_at_700
|
| 1849 |
+
value: 63.312000000000005
|
| 1850 |
+
- type: map_at_1000
|
| 1851 |
+
value: 63.312000000000005
|
| 1852 |
+
- type: recall_at_1
|
| 1853 |
+
value: 45.297
|
| 1854 |
+
- type: recall_at_2
|
| 1855 |
+
value: 63.866
|
| 1856 |
+
- type: recall_at_3
|
| 1857 |
+
value: 71.898
|
| 1858 |
+
- type: recall_at_5
|
| 1859 |
+
value: 81.16600000000001
|
| 1860 |
+
- type: recall_at_7
|
| 1861 |
+
value: 85.301
|
| 1862 |
+
- type: recall_at_10
|
| 1863 |
+
value: 88.94800000000001
|
| 1864 |
+
- type: recall_at_20
|
| 1865 |
+
value: 93.719
|
| 1866 |
+
- type: recall_at_30
|
| 1867 |
+
value: 95.628
|
| 1868 |
+
- type: recall_at_50
|
| 1869 |
+
value: 97.14699999999999
|
| 1870 |
+
- type: recall_at_70
|
| 1871 |
+
value: 97.955
|
| 1872 |
+
- type: recall_at_100
|
| 1873 |
+
value: 98.48599999999999
|
| 1874 |
+
- type: recall_at_200
|
| 1875 |
+
value: 99.157
|
| 1876 |
+
- type: recall_at_300
|
| 1877 |
+
value: 99.355
|
| 1878 |
+
- type: recall_at_500
|
| 1879 |
+
value: 99.53699999999999
|
| 1880 |
+
- type: recall_at_700
|
| 1881 |
+
value: 99.62299999999999
|
| 1882 |
+
- type: recall_at_1000
|
| 1883 |
+
value: 99.638
|
| 1884 |
+
- type: precision_at_1
|
| 1885 |
+
value: 50.897999999999996
|
| 1886 |
+
- type: precision_at_2
|
| 1887 |
+
value: 36.703
|
| 1888 |
+
- type: precision_at_3
|
| 1889 |
+
value: 27.926000000000002
|
| 1890 |
+
- type: precision_at_5
|
| 1891 |
+
value: 19.276
|
| 1892 |
+
- type: precision_at_7
|
| 1893 |
+
value: 14.533999999999999
|
| 1894 |
+
- type: precision_at_10
|
| 1895 |
+
value: 10.678
|
| 1896 |
+
- type: precision_at_20
|
| 1897 |
+
value: 5.663
|
| 1898 |
+
- type: precision_at_30
|
| 1899 |
+
value: 3.8600000000000003
|
| 1900 |
+
- type: precision_at_50
|
| 1901 |
+
value: 2.358
|
| 1902 |
+
- type: precision_at_70
|
| 1903 |
+
value: 1.7000000000000002
|
| 1904 |
+
- type: precision_at_100
|
| 1905 |
+
value: 1.198
|
| 1906 |
+
- type: precision_at_200
|
| 1907 |
+
value: 0.603
|
| 1908 |
+
- type: precision_at_300
|
| 1909 |
+
value: 0.40299999999999997
|
| 1910 |
+
- type: precision_at_500
|
| 1911 |
+
value: 0.242
|
| 1912 |
+
- type: precision_at_700
|
| 1913 |
+
value: 0.173
|
| 1914 |
+
- type: precision_at_1000
|
| 1915 |
+
value: 0.121
|
| 1916 |
+
- type: mrr_at_1
|
| 1917 |
+
value: 50.897999999999996
|
| 1918 |
+
- type: mrr_at_2
|
| 1919 |
+
value: 59.994
|
| 1920 |
+
- type: mrr_at_3
|
| 1921 |
+
value: 62.553000000000004
|
| 1922 |
+
- type: mrr_at_5
|
| 1923 |
+
value: 64.307
|
| 1924 |
+
- type: mrr_at_7
|
| 1925 |
+
value: 64.864
|
| 1926 |
+
- type: mrr_at_10
|
| 1927 |
+
value: 65.22200000000001
|
| 1928 |
+
- type: mrr_at_20
|
| 1929 |
+
value: 65.499
|
| 1930 |
+
- type: mrr_at_30
|
| 1931 |
+
value: 65.561
|
| 1932 |
+
- type: mrr_at_50
|
| 1933 |
+
value: 65.592
|
| 1934 |
+
- type: mrr_at_70
|
| 1935 |
+
value: 65.602
|
| 1936 |
+
- type: mrr_at_100
|
| 1937 |
+
value: 65.607
|
| 1938 |
+
- type: mrr_at_200
|
| 1939 |
+
value: 65.61099999999999
|
| 1940 |
+
- type: mrr_at_300
|
| 1941 |
+
value: 65.61200000000001
|
| 1942 |
+
- type: mrr_at_500
|
| 1943 |
+
value: 65.61200000000001
|
| 1944 |
+
- type: mrr_at_700
|
| 1945 |
+
value: 65.61200000000001
|
| 1946 |
+
- type: mrr_at_1000
|
| 1947 |
+
value: 65.61200000000001
|
| 1948 |
+
- task:
|
| 1949 |
+
type: Retrieval
|
| 1950 |
+
dataset:
|
| 1951 |
+
type: quora
|
| 1952 |
+
name: MTEB QuoraRetrieval
|
| 1953 |
+
config: default
|
| 1954 |
+
split: test
|
| 1955 |
+
revision: None
|
| 1956 |
+
metrics:
|
| 1957 |
+
- type: ndcg_at_1
|
| 1958 |
+
value: 82.96
|
| 1959 |
+
- type: ndcg_at_2
|
| 1960 |
+
value: 85.614
|
| 1961 |
+
- type: ndcg_at_3
|
| 1962 |
+
value: 87.19
|
| 1963 |
+
- type: ndcg_at_5
|
| 1964 |
+
value: 88.654
|
| 1965 |
+
- type: ndcg_at_7
|
| 1966 |
+
value: 89.287
|
| 1967 |
+
- type: ndcg_at_10
|
| 1968 |
+
value: 89.785
|
| 1969 |
+
- type: ndcg_at_20
|
| 1970 |
+
value: 90.384
|
| 1971 |
+
- type: ndcg_at_30
|
| 1972 |
+
value: 90.589
|
| 1973 |
+
- type: ndcg_at_50
|
| 1974 |
+
value: 90.738
|
| 1975 |
+
- type: ndcg_at_70
|
| 1976 |
+
value: 90.789
|
| 1977 |
+
- type: ndcg_at_100
|
| 1978 |
+
value: 90.824
|
| 1979 |
+
- type: ndcg_at_200
|
| 1980 |
+
value: 90.869
|
| 1981 |
+
- type: ndcg_at_300
|
| 1982 |
+
value: 90.881
|
| 1983 |
+
- type: ndcg_at_500
|
| 1984 |
+
value: 90.886
|
| 1985 |
+
- type: ndcg_at_700
|
| 1986 |
+
value: 90.889
|
| 1987 |
+
- type: ndcg_at_1000
|
| 1988 |
+
value: 90.889
|
| 1989 |
+
- type: map_at_1
|
| 1990 |
+
value: 72.152
|
| 1991 |
+
- type: map_at_2
|
| 1992 |
+
value: 80.818
|
| 1993 |
+
- type: map_at_3
|
| 1994 |
+
value: 83.462
|
| 1995 |
+
- type: map_at_5
|
| 1996 |
+
value: 85.286
|
| 1997 |
+
- type: map_at_7
|
| 1998 |
+
value: 85.921
|
| 1999 |
+
- type: map_at_10
|
| 2000 |
+
value: 86.334
|
| 2001 |
+
- type: map_at_20
|
| 2002 |
+
value: 86.737
|
| 2003 |
+
- type: map_at_30
|
| 2004 |
+
value: 86.847
|
| 2005 |
+
- type: map_at_50
|
| 2006 |
+
value: 86.911
|
| 2007 |
+
- type: map_at_70
|
| 2008 |
+
value: 86.932
|
| 2009 |
+
- type: map_at_100
|
| 2010 |
+
value: 86.943
|
| 2011 |
+
- type: map_at_200
|
| 2012 |
+
value: 86.953
|
| 2013 |
+
- type: map_at_300
|
| 2014 |
+
value: 86.955
|
| 2015 |
+
- type: map_at_500
|
| 2016 |
+
value: 86.956
|
| 2017 |
+
- type: map_at_700
|
| 2018 |
+
value: 86.956
|
| 2019 |
+
- type: map_at_1000
|
| 2020 |
+
value: 86.956
|
| 2021 |
+
- type: recall_at_1
|
| 2022 |
+
value: 72.152
|
| 2023 |
+
- type: recall_at_2
|
| 2024 |
+
value: 84.129
|
| 2025 |
+
- type: recall_at_3
|
| 2026 |
+
value: 88.87
|
| 2027 |
+
- type: recall_at_5
|
| 2028 |
+
value: 93.067
|
| 2029 |
+
- type: recall_at_7
|
| 2030 |
+
value: 94.882
|
| 2031 |
+
- type: recall_at_10
|
| 2032 |
+
value: 96.353
|
| 2033 |
+
- type: recall_at_20
|
| 2034 |
+
value: 98.26700000000001
|
| 2035 |
+
- type: recall_at_30
|
| 2036 |
+
value: 98.92999999999999
|
| 2037 |
+
- type: recall_at_50
|
| 2038 |
+
value: 99.441
|
| 2039 |
+
- type: recall_at_70
|
| 2040 |
+
value: 99.619
|
| 2041 |
+
- type: recall_at_100
|
| 2042 |
+
value: 99.748
|
| 2043 |
+
- type: recall_at_200
|
| 2044 |
+
value: 99.911
|
| 2045 |
+
- type: recall_at_300
|
| 2046 |
+
value: 99.956
|
| 2047 |
+
- type: recall_at_500
|
| 2048 |
+
value: 99.98
|
| 2049 |
+
- type: recall_at_700
|
| 2050 |
+
value: 99.991
|
| 2051 |
+
- type: recall_at_1000
|
| 2052 |
+
value: 99.996
|
| 2053 |
+
- type: precision_at_1
|
| 2054 |
+
value: 82.96
|
| 2055 |
+
- type: precision_at_2
|
| 2056 |
+
value: 52.175000000000004
|
| 2057 |
+
- type: precision_at_3
|
| 2058 |
+
value: 38.223
|
| 2059 |
+
- type: precision_at_5
|
| 2060 |
+
value: 25.056
|
| 2061 |
+
- type: precision_at_7
|
| 2062 |
+
value: 18.717
|
| 2063 |
+
- type: precision_at_10
|
| 2064 |
+
value: 13.614999999999998
|
| 2065 |
+
- type: precision_at_20
|
| 2066 |
+
value: 7.208
|
| 2067 |
+
- type: precision_at_30
|
| 2068 |
+
value: 4.928
|
| 2069 |
+
- type: precision_at_50
|
| 2070 |
+
value: 3.024
|
| 2071 |
+
- type: precision_at_70
|
| 2072 |
+
value: 2.183
|
| 2073 |
+
- type: precision_at_100
|
| 2074 |
+
value: 1.54
|
| 2075 |
+
- type: precision_at_200
|
| 2076 |
+
value: 0.779
|
| 2077 |
+
- type: precision_at_300
|
| 2078 |
+
value: 0.521
|
| 2079 |
+
- type: precision_at_500
|
| 2080 |
+
value: 0.313
|
| 2081 |
+
- type: precision_at_700
|
| 2082 |
+
value: 0.22399999999999998
|
| 2083 |
+
- type: precision_at_1000
|
| 2084 |
+
value: 0.157
|
| 2085 |
+
- type: mrr_at_1
|
| 2086 |
+
value: 82.96
|
| 2087 |
+
- type: mrr_at_2
|
| 2088 |
+
value: 87.005
|
| 2089 |
+
- type: mrr_at_3
|
| 2090 |
+
value: 88.07199999999999
|
| 2091 |
+
- type: mrr_at_5
|
| 2092 |
+
value: 88.634
|
| 2093 |
+
- type: mrr_at_7
|
| 2094 |
+
value: 88.793
|
| 2095 |
+
- type: mrr_at_10
|
| 2096 |
+
value: 88.87899999999999
|
| 2097 |
+
- type: mrr_at_20
|
| 2098 |
+
value: 88.94999999999999
|
| 2099 |
+
- type: mrr_at_30
|
| 2100 |
+
value: 88.96
|
| 2101 |
+
- type: mrr_at_50
|
| 2102 |
+
value: 88.965
|
| 2103 |
+
- type: mrr_at_70
|
| 2104 |
+
value: 88.966
|
| 2105 |
+
- type: mrr_at_100
|
| 2106 |
+
value: 88.967
|
| 2107 |
+
- type: mrr_at_200
|
| 2108 |
+
value: 88.967
|
| 2109 |
+
- type: mrr_at_300
|
| 2110 |
+
value: 88.967
|
| 2111 |
+
- type: mrr_at_500
|
| 2112 |
+
value: 88.967
|
| 2113 |
+
- type: mrr_at_700
|
| 2114 |
+
value: 88.967
|
| 2115 |
+
- type: mrr_at_1000
|
| 2116 |
+
value: 88.967
|
| 2117 |
+
- task:
|
| 2118 |
+
type: Clustering
|
| 2119 |
+
dataset:
|
| 2120 |
+
type: mteb/reddit-clustering
|
| 2121 |
+
name: MTEB RedditClustering
|
| 2122 |
+
config: default
|
| 2123 |
+
split: test
|
| 2124 |
+
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
| 2125 |
+
metrics:
|
| 2126 |
+
- type: v_measure
|
| 2127 |
+
value: 59.90388554491155
|
| 2128 |
+
- task:
|
| 2129 |
+
type: Clustering
|
| 2130 |
+
dataset:
|
| 2131 |
+
type: mteb/reddit-clustering-p2p
|
| 2132 |
+
name: MTEB RedditClusteringP2P
|
| 2133 |
+
config: default
|
| 2134 |
+
split: test
|
| 2135 |
+
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
| 2136 |
+
metrics:
|
| 2137 |
+
- type: v_measure
|
| 2138 |
+
value: 67.64232539036783
|
| 2139 |
+
- task:
|
| 2140 |
+
type: Retrieval
|
| 2141 |
+
dataset:
|
| 2142 |
+
type: scidocs
|
| 2143 |
+
name: MTEB SCIDOCS
|
| 2144 |
+
config: default
|
| 2145 |
+
split: test
|
| 2146 |
+
revision: None
|
| 2147 |
+
metrics:
|
| 2148 |
+
- type: ndcg_at_1
|
| 2149 |
+
value: 22.6
|
| 2150 |
+
- type: ndcg_at_2
|
| 2151 |
+
value: 20.355999999999998
|
| 2152 |
+
- type: ndcg_at_3
|
| 2153 |
+
value: 18.536
|
| 2154 |
+
- type: ndcg_at_5
|
| 2155 |
+
value: 16.523
|
| 2156 |
+
- type: ndcg_at_7
|
| 2157 |
+
value: 17.979
|
| 2158 |
+
- type: ndcg_at_10
|
| 2159 |
+
value: 19.908
|
| 2160 |
+
- type: ndcg_at_20
|
| 2161 |
+
value: 22.887
|
| 2162 |
+
- type: ndcg_at_30
|
| 2163 |
+
value: 24.43
|
| 2164 |
+
- type: ndcg_at_50
|
| 2165 |
+
value: 25.959
|
| 2166 |
+
- type: ndcg_at_70
|
| 2167 |
+
value: 26.989
|
| 2168 |
+
- type: ndcg_at_100
|
| 2169 |
+
value: 27.977
|
| 2170 |
+
- type: ndcg_at_200
|
| 2171 |
+
value: 29.831000000000003
|
| 2172 |
+
- type: ndcg_at_300
|
| 2173 |
+
value: 30.787
|
| 2174 |
+
- type: ndcg_at_500
|
| 2175 |
+
value: 31.974999999999998
|
| 2176 |
+
- type: ndcg_at_700
|
| 2177 |
+
value: 32.554
|
| 2178 |
+
- type: ndcg_at_1000
|
| 2179 |
+
value: 33.277
|
| 2180 |
+
- type: map_at_1
|
| 2181 |
+
value: 4.593
|
| 2182 |
+
- type: map_at_2
|
| 2183 |
+
value: 6.923
|
| 2184 |
+
- type: map_at_3
|
| 2185 |
+
value: 8.3
|
| 2186 |
+
- type: map_at_5
|
| 2187 |
+
value: 10.072000000000001
|
| 2188 |
+
- type: map_at_7
|
| 2189 |
+
value: 10.782
|
| 2190 |
+
- type: map_at_10
|
| 2191 |
+
value: 11.72
|
| 2192 |
+
- type: map_at_20
|
| 2193 |
+
value: 12.838
|
| 2194 |
+
- type: map_at_30
|
| 2195 |
+
value: 13.257
|
| 2196 |
+
- type: map_at_50
|
| 2197 |
+
value: 13.569
|
| 2198 |
+
- type: map_at_70
|
| 2199 |
+
value: 13.733
|
| 2200 |
+
- type: map_at_100
|
| 2201 |
+
value: 13.858999999999998
|
| 2202 |
+
- type: map_at_200
|
| 2203 |
+
value: 14.018
|
| 2204 |
+
- type: map_at_300
|
| 2205 |
+
value: 14.072999999999999
|
| 2206 |
+
- type: map_at_500
|
| 2207 |
+
value: 14.126
|
| 2208 |
+
- type: map_at_700
|
| 2209 |
+
value: 14.145
|
| 2210 |
+
- type: map_at_1000
|
| 2211 |
+
value: 14.161999999999999
|
| 2212 |
+
- type: recall_at_1
|
| 2213 |
+
value: 4.593
|
| 2214 |
+
- type: recall_at_2
|
| 2215 |
+
value: 7.997999999999999
|
| 2216 |
+
- type: recall_at_3
|
| 2217 |
+
value: 10.563
|
| 2218 |
+
- type: recall_at_5
|
| 2219 |
+
value: 14.907
|
| 2220 |
+
- type: recall_at_7
|
| 2221 |
+
value: 17.4
|
| 2222 |
+
- type: recall_at_10
|
| 2223 |
+
value: 21.18
|
| 2224 |
+
- type: recall_at_20
|
| 2225 |
+
value: 28.144999999999996
|
| 2226 |
+
- type: recall_at_30
|
| 2227 |
+
value: 32.462
|
| 2228 |
+
- type: recall_at_50
|
| 2229 |
+
value: 37.267
|
| 2230 |
+
- type: recall_at_70
|
| 2231 |
+
value: 40.875
|
| 2232 |
+
- type: recall_at_100
|
| 2233 |
+
value: 44.641999999999996
|
| 2234 |
+
- type: recall_at_200
|
| 2235 |
+
value: 52.573
|
| 2236 |
+
- type: recall_at_300
|
| 2237 |
+
value: 57.089999999999996
|
| 2238 |
+
- type: recall_at_500
|
| 2239 |
+
value: 63.14300000000001
|
| 2240 |
+
- type: recall_at_700
|
| 2241 |
+
value: 66.313
|
| 2242 |
+
- type: recall_at_1000
|
| 2243 |
+
value: 70.458
|
| 2244 |
+
- type: precision_at_1
|
| 2245 |
+
value: 22.6
|
| 2246 |
+
- type: precision_at_2
|
| 2247 |
+
value: 19.7
|
| 2248 |
+
- type: precision_at_3
|
| 2249 |
+
value: 17.333000000000002
|
| 2250 |
+
- type: precision_at_5
|
| 2251 |
+
value: 14.680000000000001
|
| 2252 |
+
- type: precision_at_7
|
| 2253 |
+
value: 12.243
|
| 2254 |
+
- type: precision_at_10
|
| 2255 |
+
value: 10.440000000000001
|
| 2256 |
+
- type: precision_at_20
|
| 2257 |
+
value: 6.944999999999999
|
| 2258 |
+
- type: precision_at_30
|
| 2259 |
+
value: 5.333
|
| 2260 |
+
- type: precision_at_50
|
| 2261 |
+
value: 3.678
|
| 2262 |
+
- type: precision_at_70
|
| 2263 |
+
value: 2.881
|
| 2264 |
+
- type: precision_at_100
|
| 2265 |
+
value: 2.2030000000000003
|
| 2266 |
+
- type: precision_at_200
|
| 2267 |
+
value: 1.295
|
| 2268 |
+
- type: precision_at_300
|
| 2269 |
+
value: 0.9369999999999999
|
| 2270 |
+
- type: precision_at_500
|
| 2271 |
+
value: 0.622
|
| 2272 |
+
- type: precision_at_700
|
| 2273 |
+
value: 0.466
|
| 2274 |
+
- type: precision_at_1000
|
| 2275 |
+
value: 0.347
|
| 2276 |
+
- type: mrr_at_1
|
| 2277 |
+
value: 22.6
|
| 2278 |
+
- type: mrr_at_2
|
| 2279 |
+
value: 27.900000000000002
|
| 2280 |
+
- type: mrr_at_3
|
| 2281 |
+
value: 30.067
|
| 2282 |
+
- type: mrr_at_5
|
| 2283 |
+
value: 32.207
|
| 2284 |
+
- type: mrr_at_7
|
| 2285 |
+
value: 33.004
|
| 2286 |
+
- type: mrr_at_10
|
| 2287 |
+
value: 33.596
|
| 2288 |
+
- type: mrr_at_20
|
| 2289 |
+
value: 34.268
|
| 2290 |
+
- type: mrr_at_30
|
| 2291 |
+
value: 34.492
|
| 2292 |
+
- type: mrr_at_50
|
| 2293 |
+
value: 34.628
|
| 2294 |
+
- type: mrr_at_70
|
| 2295 |
+
value: 34.681
|
| 2296 |
+
- type: mrr_at_100
|
| 2297 |
+
value: 34.717
|
| 2298 |
+
- type: mrr_at_200
|
| 2299 |
+
value: 34.757
|
| 2300 |
+
- type: mrr_at_300
|
| 2301 |
+
value: 34.768
|
| 2302 |
+
- type: mrr_at_500
|
| 2303 |
+
value: 34.772
|
| 2304 |
+
- type: mrr_at_700
|
| 2305 |
+
value: 34.774
|
| 2306 |
+
- type: mrr_at_1000
|
| 2307 |
+
value: 34.775
|
| 2308 |
+
- task:
|
| 2309 |
+
type: STS
|
| 2310 |
+
dataset:
|
| 2311 |
+
type: mteb/sickr-sts
|
| 2312 |
+
name: MTEB SICK-R
|
| 2313 |
+
config: default
|
| 2314 |
+
split: test
|
| 2315 |
+
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
| 2316 |
+
metrics:
|
| 2317 |
+
- type: cos_sim_pearson
|
| 2318 |
+
value: 86.90122745229677
|
| 2319 |
+
- type: cos_sim_spearman
|
| 2320 |
+
value: 82.92294737327579
|
| 2321 |
+
- type: euclidean_pearson
|
| 2322 |
+
value: 84.08979655773187
|
| 2323 |
+
- type: euclidean_spearman
|
| 2324 |
+
value: 82.92294657285412
|
| 2325 |
+
- type: manhattan_pearson
|
| 2326 |
+
value: 84.09347480531832
|
| 2327 |
+
- type: manhattan_spearman
|
| 2328 |
+
value: 82.91564613948087
|
| 2329 |
+
- task:
|
| 2330 |
+
type: STS
|
| 2331 |
+
dataset:
|
| 2332 |
+
type: mteb/sts12-sts
|
| 2333 |
+
name: MTEB STS12
|
| 2334 |
+
config: default
|
| 2335 |
+
split: test
|
| 2336 |
+
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
| 2337 |
+
metrics:
|
| 2338 |
+
- type: cos_sim_pearson
|
| 2339 |
+
value: 87.01218713698583
|
| 2340 |
+
- type: cos_sim_spearman
|
| 2341 |
+
value: 79.46865215168464
|
| 2342 |
+
- type: euclidean_pearson
|
| 2343 |
+
value: 83.22621889891909
|
| 2344 |
+
- type: euclidean_spearman
|
| 2345 |
+
value: 79.46853821709514
|
| 2346 |
+
- type: manhattan_pearson
|
| 2347 |
+
value: 83.69962580788805
|
| 2348 |
+
- type: manhattan_spearman
|
| 2349 |
+
value: 79.9561593356932
|
| 2350 |
+
- task:
|
| 2351 |
+
type: STS
|
| 2352 |
+
dataset:
|
| 2353 |
+
type: mteb/sts13-sts
|
| 2354 |
+
name: MTEB STS13
|
| 2355 |
+
config: default
|
| 2356 |
+
split: test
|
| 2357 |
+
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
| 2358 |
+
metrics:
|
| 2359 |
+
- type: cos_sim_pearson
|
| 2360 |
+
value: 88.98438696342964
|
| 2361 |
+
- type: cos_sim_spearman
|
| 2362 |
+
value: 89.15419511870839
|
| 2363 |
+
- type: euclidean_pearson
|
| 2364 |
+
value: 88.49646141802894
|
| 2365 |
+
- type: euclidean_spearman
|
| 2366 |
+
value: 89.15419503946019
|
| 2367 |
+
- type: manhattan_pearson
|
| 2368 |
+
value: 88.6420585616327
|
| 2369 |
+
- type: manhattan_spearman
|
| 2370 |
+
value: 89.42648950757743
|
| 2371 |
+
- task:
|
| 2372 |
+
type: STS
|
| 2373 |
+
dataset:
|
| 2374 |
+
type: mteb/sts14-sts
|
| 2375 |
+
name: MTEB STS14
|
| 2376 |
+
config: default
|
| 2377 |
+
split: test
|
| 2378 |
+
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
| 2379 |
+
metrics:
|
| 2380 |
+
- type: cos_sim_pearson
|
| 2381 |
+
value: 87.30772547759544
|
| 2382 |
+
- type: cos_sim_spearman
|
| 2383 |
+
value: 84.93199878424691
|
| 2384 |
+
- type: euclidean_pearson
|
| 2385 |
+
value: 86.16266630395455
|
| 2386 |
+
- type: euclidean_spearman
|
| 2387 |
+
value: 84.93198798543634
|
| 2388 |
+
- type: manhattan_pearson
|
| 2389 |
+
value: 86.14285723189803
|
| 2390 |
+
- type: manhattan_spearman
|
| 2391 |
+
value: 85.0361672522687
|
| 2392 |
+
- task:
|
| 2393 |
+
type: STS
|
| 2394 |
+
dataset:
|
| 2395 |
+
type: mteb/sts15-sts
|
| 2396 |
+
name: MTEB STS15
|
| 2397 |
+
config: default
|
| 2398 |
+
split: test
|
| 2399 |
+
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
| 2400 |
+
metrics:
|
| 2401 |
+
- type: cos_sim_pearson
|
| 2402 |
+
value: 90.21342071197127
|
| 2403 |
+
- type: cos_sim_spearman
|
| 2404 |
+
value: 90.7407512744838
|
| 2405 |
+
- type: euclidean_pearson
|
| 2406 |
+
value: 90.1517933113061
|
| 2407 |
+
- type: euclidean_spearman
|
| 2408 |
+
value: 90.74075125431919
|
| 2409 |
+
- type: manhattan_pearson
|
| 2410 |
+
value: 90.17963034676193
|
| 2411 |
+
- type: manhattan_spearman
|
| 2412 |
+
value: 90.88999275865135
|
| 2413 |
+
- task:
|
| 2414 |
+
type: STS
|
| 2415 |
+
dataset:
|
| 2416 |
+
type: mteb/sts16-sts
|
| 2417 |
+
name: MTEB STS16
|
| 2418 |
+
config: default
|
| 2419 |
+
split: test
|
| 2420 |
+
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
| 2421 |
+
metrics:
|
| 2422 |
+
- type: cos_sim_pearson
|
| 2423 |
+
value: 86.82518054100498
|
| 2424 |
+
- type: cos_sim_spearman
|
| 2425 |
+
value: 87.81570533154735
|
| 2426 |
+
- type: euclidean_pearson
|
| 2427 |
+
value: 86.91684561573618
|
| 2428 |
+
- type: euclidean_spearman
|
| 2429 |
+
value: 87.81570533154735
|
| 2430 |
+
- type: manhattan_pearson
|
| 2431 |
+
value: 86.98311935744032
|
| 2432 |
+
- type: manhattan_spearman
|
| 2433 |
+
value: 87.9594667151966
|
| 2434 |
+
- task:
|
| 2435 |
+
type: STS
|
| 2436 |
+
dataset:
|
| 2437 |
+
type: mteb/sts17-crosslingual-sts
|
| 2438 |
+
name: MTEB STS17 (en-en)
|
| 2439 |
+
config: en-en
|
| 2440 |
+
split: test
|
| 2441 |
+
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
| 2442 |
+
metrics:
|
| 2443 |
+
- type: cos_sim_pearson
|
| 2444 |
+
value: 92.09578436612053
|
| 2445 |
+
- type: cos_sim_spearman
|
| 2446 |
+
value: 92.01519349090438
|
| 2447 |
+
- type: euclidean_pearson
|
| 2448 |
+
value: 92.07113635890894
|
| 2449 |
+
- type: euclidean_spearman
|
| 2450 |
+
value: 92.01519349090438
|
| 2451 |
+
- type: manhattan_pearson
|
| 2452 |
+
value: 91.89343820765625
|
| 2453 |
+
- type: manhattan_spearman
|
| 2454 |
+
value: 91.7443476810177
|
| 2455 |
+
- task:
|
| 2456 |
+
type: STS
|
| 2457 |
+
dataset:
|
| 2458 |
+
type: mteb/sts22-crosslingual-sts
|
| 2459 |
+
name: MTEB STS22 (en)
|
| 2460 |
+
config: en
|
| 2461 |
+
split: test
|
| 2462 |
+
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
| 2463 |
+
metrics:
|
| 2464 |
+
- type: cos_sim_pearson
|
| 2465 |
+
value: 69.29997751464549
|
| 2466 |
+
- type: cos_sim_spearman
|
| 2467 |
+
value: 68.36425436812782
|
| 2468 |
+
- type: euclidean_pearson
|
| 2469 |
+
value: 69.81381677661783
|
| 2470 |
+
- type: euclidean_spearman
|
| 2471 |
+
value: 68.36425436812782
|
| 2472 |
+
- type: manhattan_pearson
|
| 2473 |
+
value: 69.92823397008026
|
| 2474 |
+
- type: manhattan_spearman
|
| 2475 |
+
value: 68.35770640039254
|
| 2476 |
+
- task:
|
| 2477 |
+
type: STS
|
| 2478 |
+
dataset:
|
| 2479 |
+
type: mteb/stsbenchmark-sts
|
| 2480 |
+
name: MTEB STSBenchmark
|
| 2481 |
+
config: default
|
| 2482 |
+
split: test
|
| 2483 |
+
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
| 2484 |
+
metrics:
|
| 2485 |
+
- type: cos_sim_pearson
|
| 2486 |
+
value: 88.39126315452359
|
| 2487 |
+
- type: cos_sim_spearman
|
| 2488 |
+
value: 88.99708463265337
|
| 2489 |
+
- type: euclidean_pearson
|
| 2490 |
+
value: 88.60793820038607
|
| 2491 |
+
- type: euclidean_spearman
|
| 2492 |
+
value: 88.99708463265337
|
| 2493 |
+
- type: manhattan_pearson
|
| 2494 |
+
value: 88.69860633571047
|
| 2495 |
+
- type: manhattan_spearman
|
| 2496 |
+
value: 89.20094593888012
|
| 2497 |
+
- task:
|
| 2498 |
+
type: Reranking
|
| 2499 |
+
dataset:
|
| 2500 |
+
type: mteb/scidocs-reranking
|
| 2501 |
+
name: MTEB SciDocsRR
|
| 2502 |
+
config: default
|
| 2503 |
+
split: test
|
| 2504 |
+
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
| 2505 |
+
metrics:
|
| 2506 |
+
- type: map
|
| 2507 |
+
value: 86.58028062818582
|
| 2508 |
+
- type: mrr
|
| 2509 |
+
value: 96.53586790841693
|
| 2510 |
+
- task:
|
| 2511 |
+
type: Retrieval
|
| 2512 |
+
dataset:
|
| 2513 |
+
type: scifact
|
| 2514 |
+
name: MTEB SciFact
|
| 2515 |
+
config: default
|
| 2516 |
+
split: test
|
| 2517 |
+
revision: None
|
| 2518 |
+
metrics:
|
| 2519 |
+
- type: ndcg_at_1
|
| 2520 |
+
value: 66.333
|
| 2521 |
+
- type: ndcg_at_2
|
| 2522 |
+
value: 70.655
|
| 2523 |
+
- type: ndcg_at_3
|
| 2524 |
+
value: 72.801
|
| 2525 |
+
- type: ndcg_at_5
|
| 2526 |
+
value: 75.793
|
| 2527 |
+
- type: ndcg_at_7
|
| 2528 |
+
value: 76.946
|
| 2529 |
+
- type: ndcg_at_10
|
| 2530 |
+
value: 77.66199999999999
|
| 2531 |
+
- type: ndcg_at_20
|
| 2532 |
+
value: 78.786
|
| 2533 |
+
- type: ndcg_at_30
|
| 2534 |
+
value: 79.066
|
| 2535 |
+
- type: ndcg_at_50
|
| 2536 |
+
value: 79.255
|
| 2537 |
+
- type: ndcg_at_70
|
| 2538 |
+
value: 79.423
|
| 2539 |
+
- type: ndcg_at_100
|
| 2540 |
+
value: 79.476
|
| 2541 |
+
- type: ndcg_at_200
|
| 2542 |
+
value: 79.65299999999999
|
| 2543 |
+
- type: ndcg_at_300
|
| 2544 |
+
value: 79.696
|
| 2545 |
+
- type: ndcg_at_500
|
| 2546 |
+
value: 79.73599999999999
|
| 2547 |
+
- type: ndcg_at_700
|
| 2548 |
+
value: 79.77199999999999
|
| 2549 |
+
- type: ndcg_at_1000
|
| 2550 |
+
value: 79.77199999999999
|
| 2551 |
+
- type: map_at_1
|
| 2552 |
+
value: 63.383
|
| 2553 |
+
- type: map_at_2
|
| 2554 |
+
value: 68.144
|
| 2555 |
+
- type: map_at_3
|
| 2556 |
+
value: 70.19800000000001
|
| 2557 |
+
- type: map_at_5
|
| 2558 |
+
value: 72.38
|
| 2559 |
+
- type: map_at_7
|
| 2560 |
+
value: 72.955
|
| 2561 |
+
- type: map_at_10
|
| 2562 |
+
value: 73.312
|
| 2563 |
+
- type: map_at_20
|
| 2564 |
+
value: 73.678
|
| 2565 |
+
- type: map_at_30
|
| 2566 |
+
value: 73.72800000000001
|
| 2567 |
+
- type: map_at_50
|
| 2568 |
+
value: 73.75500000000001
|
| 2569 |
+
- type: map_at_70
|
| 2570 |
+
value: 73.771
|
| 2571 |
+
- type: map_at_100
|
| 2572 |
+
value: 73.776
|
| 2573 |
+
- type: map_at_200
|
| 2574 |
+
value: 73.783
|
| 2575 |
+
- type: map_at_300
|
| 2576 |
+
value: 73.784
|
| 2577 |
+
- type: map_at_500
|
| 2578 |
+
value: 73.785
|
| 2579 |
+
- type: map_at_700
|
| 2580 |
+
value: 73.786
|
| 2581 |
+
- type: map_at_1000
|
| 2582 |
+
value: 73.786
|
| 2583 |
+
- type: recall_at_1
|
| 2584 |
+
value: 63.383
|
| 2585 |
+
- type: recall_at_2
|
| 2586 |
+
value: 72.283
|
| 2587 |
+
- type: recall_at_3
|
| 2588 |
+
value: 77.183
|
| 2589 |
+
- type: recall_at_5
|
| 2590 |
+
value: 84.56099999999999
|
| 2591 |
+
- type: recall_at_7
|
| 2592 |
+
value: 87.67200000000001
|
| 2593 |
+
- type: recall_at_10
|
| 2594 |
+
value: 89.822
|
| 2595 |
+
- type: recall_at_20
|
| 2596 |
+
value: 94
|
| 2597 |
+
- type: recall_at_30
|
| 2598 |
+
value: 95.333
|
| 2599 |
+
- type: recall_at_50
|
| 2600 |
+
value: 96.333
|
| 2601 |
+
- type: recall_at_70
|
| 2602 |
+
value: 97.333
|
| 2603 |
+
- type: recall_at_100
|
| 2604 |
+
value: 97.667
|
| 2605 |
+
- type: recall_at_200
|
| 2606 |
+
value: 99
|
| 2607 |
+
- type: recall_at_300
|
| 2608 |
+
value: 99.333
|
| 2609 |
+
- type: recall_at_500
|
| 2610 |
+
value: 99.667
|
| 2611 |
+
- type: recall_at_700
|
| 2612 |
+
value: 100
|
| 2613 |
+
- type: recall_at_1000
|
| 2614 |
+
value: 100
|
| 2615 |
+
- type: precision_at_1
|
| 2616 |
+
value: 66.333
|
| 2617 |
+
- type: precision_at_2
|
| 2618 |
+
value: 38.667
|
| 2619 |
+
- type: precision_at_3
|
| 2620 |
+
value: 28.111000000000004
|
| 2621 |
+
- type: precision_at_5
|
| 2622 |
+
value: 18.933
|
| 2623 |
+
- type: precision_at_7
|
| 2624 |
+
value: 14.094999999999999
|
| 2625 |
+
- type: precision_at_10
|
| 2626 |
+
value: 10.167
|
| 2627 |
+
- type: precision_at_20
|
| 2628 |
+
value: 5.35
|
| 2629 |
+
- type: precision_at_30
|
| 2630 |
+
value: 3.611
|
| 2631 |
+
- type: precision_at_50
|
| 2632 |
+
value: 2.1870000000000003
|
| 2633 |
+
- type: precision_at_70
|
| 2634 |
+
value: 1.576
|
| 2635 |
+
- type: precision_at_100
|
| 2636 |
+
value: 1.107
|
| 2637 |
+
- type: precision_at_200
|
| 2638 |
+
value: 0.5599999999999999
|
| 2639 |
+
- type: precision_at_300
|
| 2640 |
+
value: 0.374
|
| 2641 |
+
- type: precision_at_500
|
| 2642 |
+
value: 0.22499999999999998
|
| 2643 |
+
- type: precision_at_700
|
| 2644 |
+
value: 0.161
|
| 2645 |
+
- type: precision_at_1000
|
| 2646 |
+
value: 0.11299999999999999
|
| 2647 |
+
- type: mrr_at_1
|
| 2648 |
+
value: 66.333
|
| 2649 |
+
- type: mrr_at_2
|
| 2650 |
+
value: 70.833
|
| 2651 |
+
- type: mrr_at_3
|
| 2652 |
+
value: 72.167
|
| 2653 |
+
- type: mrr_at_5
|
| 2654 |
+
value: 73.6
|
| 2655 |
+
- type: mrr_at_7
|
| 2656 |
+
value: 74.084
|
| 2657 |
+
- type: mrr_at_10
|
| 2658 |
+
value: 74.283
|
| 2659 |
+
- type: mrr_at_20
|
| 2660 |
+
value: 74.54499999999999
|
| 2661 |
+
- type: mrr_at_30
|
| 2662 |
+
value: 74.59599999999999
|
| 2663 |
+
- type: mrr_at_50
|
| 2664 |
+
value: 74.622
|
| 2665 |
+
- type: mrr_at_70
|
| 2666 |
+
value: 74.639
|
| 2667 |
+
- type: mrr_at_100
|
| 2668 |
+
value: 74.643
|
| 2669 |
+
- type: mrr_at_200
|
| 2670 |
+
value: 74.65
|
| 2671 |
+
- type: mrr_at_300
|
| 2672 |
+
value: 74.652
|
| 2673 |
+
- type: mrr_at_500
|
| 2674 |
+
value: 74.653
|
| 2675 |
+
- type: mrr_at_700
|
| 2676 |
+
value: 74.653
|
| 2677 |
+
- type: mrr_at_1000
|
| 2678 |
+
value: 74.653
|
| 2679 |
+
- task:
|
| 2680 |
+
type: PairClassification
|
| 2681 |
+
dataset:
|
| 2682 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
| 2683 |
+
name: MTEB SprintDuplicateQuestions
|
| 2684 |
+
config: default
|
| 2685 |
+
split: test
|
| 2686 |
+
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
| 2687 |
+
metrics:
|
| 2688 |
+
- type: cos_sim_accuracy
|
| 2689 |
+
value: 99.84554455445544
|
| 2690 |
+
- type: cos_sim_ap
|
| 2691 |
+
value: 96.31178339136798
|
| 2692 |
+
- type: cos_sim_f1
|
| 2693 |
+
value: 92.1921921921922
|
| 2694 |
+
- type: cos_sim_precision
|
| 2695 |
+
value: 92.28456913827655
|
| 2696 |
+
- type: cos_sim_recall
|
| 2697 |
+
value: 92.10000000000001
|
| 2698 |
+
- type: dot_accuracy
|
| 2699 |
+
value: 99.84554455445544
|
| 2700 |
+
- type: dot_ap
|
| 2701 |
+
value: 96.31178339136797
|
| 2702 |
+
- type: dot_f1
|
| 2703 |
+
value: 92.1921921921922
|
| 2704 |
+
- type: dot_precision
|
| 2705 |
+
value: 92.28456913827655
|
| 2706 |
+
- type: dot_recall
|
| 2707 |
+
value: 92.10000000000001
|
| 2708 |
+
- type: euclidean_accuracy
|
| 2709 |
+
value: 99.84554455445544
|
| 2710 |
+
- type: euclidean_ap
|
| 2711 |
+
value: 96.31178339136798
|
| 2712 |
+
- type: euclidean_f1
|
| 2713 |
+
value: 92.1921921921922
|
| 2714 |
+
- type: euclidean_precision
|
| 2715 |
+
value: 92.28456913827655
|
| 2716 |
+
- type: euclidean_recall
|
| 2717 |
+
value: 92.10000000000001
|
| 2718 |
+
- type: manhattan_accuracy
|
| 2719 |
+
value: 99.84752475247525
|
| 2720 |
+
- type: manhattan_ap
|
| 2721 |
+
value: 96.4591954606088
|
| 2722 |
+
- type: manhattan_f1
|
| 2723 |
+
value: 92.25352112676056
|
| 2724 |
+
- type: manhattan_precision
|
| 2725 |
+
value: 92.81376518218623
|
| 2726 |
+
- type: manhattan_recall
|
| 2727 |
+
value: 91.7
|
| 2728 |
+
- type: max_accuracy
|
| 2729 |
+
value: 99.84752475247525
|
| 2730 |
+
- type: max_ap
|
| 2731 |
+
value: 96.4591954606088
|
| 2732 |
+
- type: max_f1
|
| 2733 |
+
value: 92.25352112676056
|
| 2734 |
+
- task:
|
| 2735 |
+
type: Clustering
|
| 2736 |
+
dataset:
|
| 2737 |
+
type: mteb/stackexchange-clustering
|
| 2738 |
+
name: MTEB StackExchangeClustering
|
| 2739 |
+
config: default
|
| 2740 |
+
split: test
|
| 2741 |
+
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
| 2742 |
+
metrics:
|
| 2743 |
+
- type: v_measure
|
| 2744 |
+
value: 74.24659759283294
|
| 2745 |
+
- task:
|
| 2746 |
+
type: Clustering
|
| 2747 |
+
dataset:
|
| 2748 |
+
type: mteb/stackexchange-clustering-p2p
|
| 2749 |
+
name: MTEB StackExchangeClusteringP2P
|
| 2750 |
+
config: default
|
| 2751 |
+
split: test
|
| 2752 |
+
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
| 2753 |
+
metrics:
|
| 2754 |
+
- type: v_measure
|
| 2755 |
+
value: 46.77690051260451
|
| 2756 |
+
- task:
|
| 2757 |
+
type: Reranking
|
| 2758 |
+
dataset:
|
| 2759 |
+
type: mteb/stackoverflowdupquestions-reranking
|
| 2760 |
+
name: MTEB StackOverflowDupQuestions
|
| 2761 |
+
config: default
|
| 2762 |
+
split: test
|
| 2763 |
+
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
| 2764 |
+
metrics:
|
| 2765 |
+
- type: map
|
| 2766 |
+
value: 55.68436757803185
|
| 2767 |
+
- type: mrr
|
| 2768 |
+
value: 56.82157711569475
|
| 2769 |
+
- task:
|
| 2770 |
+
type: Summarization
|
| 2771 |
+
dataset:
|
| 2772 |
+
type: mteb/summeval
|
| 2773 |
+
name: MTEB SummEval
|
| 2774 |
+
config: default
|
| 2775 |
+
split: test
|
| 2776 |
+
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
| 2777 |
+
metrics:
|
| 2778 |
+
- type: cos_sim_pearson
|
| 2779 |
+
value: 31.652482405629843
|
| 2780 |
+
- type: cos_sim_spearman
|
| 2781 |
+
value: 31.16341822347735
|
| 2782 |
+
- type: dot_pearson
|
| 2783 |
+
value: 31.652479892699837
|
| 2784 |
+
- type: dot_spearman
|
| 2785 |
+
value: 31.16341822347735
|
| 2786 |
+
- task:
|
| 2787 |
+
type: Retrieval
|
| 2788 |
+
dataset:
|
| 2789 |
+
type: trec-covid
|
| 2790 |
+
name: MTEB TRECCOVID
|
| 2791 |
+
config: default
|
| 2792 |
+
split: test
|
| 2793 |
+
revision: None
|
| 2794 |
+
metrics:
|
| 2795 |
+
- type: ndcg_at_1
|
| 2796 |
+
value: 92
|
| 2797 |
+
- type: ndcg_at_2
|
| 2798 |
+
value: 90.839
|
| 2799 |
+
- type: ndcg_at_3
|
| 2800 |
+
value: 90.642
|
| 2801 |
+
- type: ndcg_at_5
|
| 2802 |
+
value: 90.348
|
| 2803 |
+
- type: ndcg_at_7
|
| 2804 |
+
value: 89.015
|
| 2805 |
+
- type: ndcg_at_10
|
| 2806 |
+
value: 87.599
|
| 2807 |
+
- type: ndcg_at_20
|
| 2808 |
+
value: 84.434
|
| 2809 |
+
- type: ndcg_at_30
|
| 2810 |
+
value: 81.655
|
| 2811 |
+
- type: ndcg_at_50
|
| 2812 |
+
value: 77.278
|
| 2813 |
+
- type: ndcg_at_70
|
| 2814 |
+
value: 73.957
|
| 2815 |
+
- type: ndcg_at_100
|
| 2816 |
+
value: 69.56
|
| 2817 |
+
- type: ndcg_at_200
|
| 2818 |
+
value: 60.724000000000004
|
| 2819 |
+
- type: ndcg_at_300
|
| 2820 |
+
value: 57.245000000000005
|
| 2821 |
+
- type: ndcg_at_500
|
| 2822 |
+
value: 56.316
|
| 2823 |
+
- type: ndcg_at_700
|
| 2824 |
+
value: 58.399
|
| 2825 |
+
- type: ndcg_at_1000
|
| 2826 |
+
value: 62.21600000000001
|
| 2827 |
+
- type: map_at_1
|
| 2828 |
+
value: 0.247
|
| 2829 |
+
- type: map_at_2
|
| 2830 |
+
value: 0.488
|
| 2831 |
+
- type: map_at_3
|
| 2832 |
+
value: 0.7230000000000001
|
| 2833 |
+
- type: map_at_5
|
| 2834 |
+
value: 1.204
|
| 2835 |
+
- type: map_at_7
|
| 2836 |
+
value: 1.6500000000000001
|
| 2837 |
+
- type: map_at_10
|
| 2838 |
+
value: 2.292
|
| 2839 |
+
- type: map_at_20
|
| 2840 |
+
value: 4.274
|
| 2841 |
+
- type: map_at_30
|
| 2842 |
+
value: 6.027
|
| 2843 |
+
- type: map_at_50
|
| 2844 |
+
value: 9.083
|
| 2845 |
+
- type: map_at_70
|
| 2846 |
+
value: 11.751000000000001
|
| 2847 |
+
- type: map_at_100
|
| 2848 |
+
value: 14.912
|
| 2849 |
+
- type: map_at_200
|
| 2850 |
+
value: 22.213
|
| 2851 |
+
- type: map_at_300
|
| 2852 |
+
value: 26.667999999999996
|
| 2853 |
+
- type: map_at_500
|
| 2854 |
+
value: 31.556
|
| 2855 |
+
- type: map_at_700
|
| 2856 |
+
value: 34.221000000000004
|
| 2857 |
+
- type: map_at_1000
|
| 2858 |
+
value: 36.443999999999996
|
| 2859 |
+
- type: recall_at_1
|
| 2860 |
+
value: 0.247
|
| 2861 |
+
- type: recall_at_2
|
| 2862 |
+
value: 0.49899999999999994
|
| 2863 |
+
- type: recall_at_3
|
| 2864 |
+
value: 0.742
|
| 2865 |
+
- type: recall_at_5
|
| 2866 |
+
value: 1.247
|
| 2867 |
+
- type: recall_at_7
|
| 2868 |
+
value: 1.722
|
| 2869 |
+
- type: recall_at_10
|
| 2870 |
+
value: 2.405
|
| 2871 |
+
- type: recall_at_20
|
| 2872 |
+
value: 4.583
|
| 2873 |
+
- type: recall_at_30
|
| 2874 |
+
value: 6.587999999999999
|
| 2875 |
+
- type: recall_at_50
|
| 2876 |
+
value: 10.188
|
| 2877 |
+
- type: recall_at_70
|
| 2878 |
+
value: 13.496
|
| 2879 |
+
- type: recall_at_100
|
| 2880 |
+
value: 17.578
|
| 2881 |
+
- type: recall_at_200
|
| 2882 |
+
value: 28.158
|
| 2883 |
+
- type: recall_at_300
|
| 2884 |
+
value: 35.532000000000004
|
| 2885 |
+
- type: recall_at_500
|
| 2886 |
+
value: 45.31
|
| 2887 |
+
- type: recall_at_700
|
| 2888 |
+
value: 51.822
|
| 2889 |
+
- type: recall_at_1000
|
| 2890 |
+
value: 58.53
|
| 2891 |
+
- type: precision_at_1
|
| 2892 |
+
value: 96
|
| 2893 |
+
- type: precision_at_2
|
| 2894 |
+
value: 96
|
| 2895 |
+
- type: precision_at_3
|
| 2896 |
+
value: 95.333
|
| 2897 |
+
- type: precision_at_5
|
| 2898 |
+
value: 94.8
|
| 2899 |
+
- type: precision_at_7
|
| 2900 |
+
value: 93.429
|
| 2901 |
+
- type: precision_at_10
|
| 2902 |
+
value: 91.4
|
| 2903 |
+
- type: precision_at_20
|
| 2904 |
+
value: 87.7
|
| 2905 |
+
- type: precision_at_30
|
| 2906 |
+
value: 84.867
|
| 2907 |
+
- type: precision_at_50
|
| 2908 |
+
value: 80.24
|
| 2909 |
+
- type: precision_at_70
|
| 2910 |
+
value: 76.371
|
| 2911 |
+
- type: precision_at_100
|
| 2912 |
+
value: 71.08
|
| 2913 |
+
- type: precision_at_200
|
| 2914 |
+
value: 59.4
|
| 2915 |
+
- type: precision_at_300
|
| 2916 |
+
value: 51.459999999999994
|
| 2917 |
+
- type: precision_at_500
|
| 2918 |
+
value: 40.644000000000005
|
| 2919 |
+
- type: precision_at_700
|
| 2920 |
+
value: 33.889
|
| 2921 |
+
- type: precision_at_1000
|
| 2922 |
+
value: 27.250000000000004
|
| 2923 |
+
- type: mrr_at_1
|
| 2924 |
+
value: 96
|
| 2925 |
+
- type: mrr_at_2
|
| 2926 |
+
value: 98
|
| 2927 |
+
- type: mrr_at_3
|
| 2928 |
+
value: 98
|
| 2929 |
+
- type: mrr_at_5
|
| 2930 |
+
value: 98
|
| 2931 |
+
- type: mrr_at_7
|
| 2932 |
+
value: 98
|
| 2933 |
+
- type: mrr_at_10
|
| 2934 |
+
value: 98
|
| 2935 |
+
- type: mrr_at_20
|
| 2936 |
+
value: 98
|
| 2937 |
+
- type: mrr_at_30
|
| 2938 |
+
value: 98
|
| 2939 |
+
- type: mrr_at_50
|
| 2940 |
+
value: 98
|
| 2941 |
+
- type: mrr_at_70
|
| 2942 |
+
value: 98
|
| 2943 |
+
- type: mrr_at_100
|
| 2944 |
+
value: 98
|
| 2945 |
+
- type: mrr_at_200
|
| 2946 |
+
value: 98
|
| 2947 |
+
- type: mrr_at_300
|
| 2948 |
+
value: 98
|
| 2949 |
+
- type: mrr_at_500
|
| 2950 |
+
value: 98
|
| 2951 |
+
- type: mrr_at_700
|
| 2952 |
+
value: 98
|
| 2953 |
+
- type: mrr_at_1000
|
| 2954 |
+
value: 98
|
| 2955 |
+
- task:
|
| 2956 |
+
type: Retrieval
|
| 2957 |
+
dataset:
|
| 2958 |
+
type: webis-touche2020
|
| 2959 |
+
name: MTEB Touche2020
|
| 2960 |
+
config: default
|
| 2961 |
+
split: test
|
| 2962 |
+
revision: None
|
| 2963 |
+
metrics:
|
| 2964 |
+
- type: ndcg_at_1
|
| 2965 |
+
value: 43.878
|
| 2966 |
+
- type: ndcg_at_2
|
| 2967 |
+
value: 37.956
|
| 2968 |
+
- type: ndcg_at_3
|
| 2969 |
+
value: 35.053
|
| 2970 |
+
- type: ndcg_at_5
|
| 2971 |
+
value: 32.59
|
| 2972 |
+
- type: ndcg_at_7
|
| 2973 |
+
value: 30.226
|
| 2974 |
+
- type: ndcg_at_10
|
| 2975 |
+
value: 29.005
|
| 2976 |
+
- type: ndcg_at_20
|
| 2977 |
+
value: 30.11
|
| 2978 |
+
- type: ndcg_at_30
|
| 2979 |
+
value: 32.019999999999996
|
| 2980 |
+
- type: ndcg_at_50
|
| 2981 |
+
value: 34.354
|
| 2982 |
+
- type: ndcg_at_70
|
| 2983 |
+
value: 36.665
|
| 2984 |
+
- type: ndcg_at_100
|
| 2985 |
+
value: 38.888
|
| 2986 |
+
- type: ndcg_at_200
|
| 2987 |
+
value: 43.435
|
| 2988 |
+
- type: ndcg_at_300
|
| 2989 |
+
value: 45.795
|
| 2990 |
+
- type: ndcg_at_500
|
| 2991 |
+
value: 48.699999999999996
|
| 2992 |
+
- type: ndcg_at_700
|
| 2993 |
+
value: 50.242
|
| 2994 |
+
- type: ndcg_at_1000
|
| 2995 |
+
value: 51.529
|
| 2996 |
+
- type: map_at_1
|
| 2997 |
+
value: 3.521
|
| 2998 |
+
- type: map_at_2
|
| 2999 |
+
value: 5.309
|
| 3000 |
+
- type: map_at_3
|
| 3001 |
+
value: 6.576
|
| 3002 |
+
- type: map_at_5
|
| 3003 |
+
value: 8.97
|
| 3004 |
+
- type: map_at_7
|
| 3005 |
+
value: 10.194
|
| 3006 |
+
- type: map_at_10
|
| 3007 |
+
value: 11.949
|
| 3008 |
+
- type: map_at_20
|
| 3009 |
+
value: 14.686
|
| 3010 |
+
- type: map_at_30
|
| 3011 |
+
value: 15.8
|
| 3012 |
+
- type: map_at_50
|
| 3013 |
+
value: 16.59
|
| 3014 |
+
- type: map_at_70
|
| 3015 |
+
value: 17.2
|
| 3016 |
+
- type: map_at_100
|
| 3017 |
+
value: 17.765
|
| 3018 |
+
- type: map_at_200
|
| 3019 |
+
value: 18.636
|
| 3020 |
+
- type: map_at_300
|
| 3021 |
+
value: 18.972
|
| 3022 |
+
- type: map_at_500
|
| 3023 |
+
value: 19.301
|
| 3024 |
+
- type: map_at_700
|
| 3025 |
+
value: 19.445
|
| 3026 |
+
- type: map_at_1000
|
| 3027 |
+
value: 19.546
|
| 3028 |
+
- type: recall_at_1
|
| 3029 |
+
value: 3.521
|
| 3030 |
+
- type: recall_at_2
|
| 3031 |
+
value: 5.848
|
| 3032 |
+
- type: recall_at_3
|
| 3033 |
+
value: 7.657
|
| 3034 |
+
- type: recall_at_5
|
| 3035 |
+
value: 11.368
|
| 3036 |
+
- type: recall_at_7
|
| 3037 |
+
value: 13.748
|
| 3038 |
+
- type: recall_at_10
|
| 3039 |
+
value: 18.061
|
| 3040 |
+
- type: recall_at_20
|
| 3041 |
+
value: 26.844
|
| 3042 |
+
- type: recall_at_30
|
| 3043 |
+
value: 31.186000000000003
|
| 3044 |
+
- type: recall_at_50
|
| 3045 |
+
value: 35.951
|
| 3046 |
+
- type: recall_at_70
|
| 3047 |
+
value: 40.961999999999996
|
| 3048 |
+
- type: recall_at_100
|
| 3049 |
+
value: 46.743
|
| 3050 |
+
- type: recall_at_200
|
| 3051 |
+
value: 58.483
|
| 3052 |
+
- type: recall_at_300
|
| 3053 |
+
value: 65.973
|
| 3054 |
+
- type: recall_at_500
|
| 3055 |
+
value: 75.233
|
| 3056 |
+
- type: recall_at_700
|
| 3057 |
+
value: 80.472
|
| 3058 |
+
- type: recall_at_1000
|
| 3059 |
+
value: 85.02
|
| 3060 |
+
- type: precision_at_1
|
| 3061 |
+
value: 46.939
|
| 3062 |
+
- type: precision_at_2
|
| 3063 |
+
value: 38.775999999999996
|
| 3064 |
+
- type: precision_at_3
|
| 3065 |
+
value: 34.694
|
| 3066 |
+
- type: precision_at_5
|
| 3067 |
+
value: 31.429000000000002
|
| 3068 |
+
- type: precision_at_7
|
| 3069 |
+
value: 27.697
|
| 3070 |
+
- type: precision_at_10
|
| 3071 |
+
value: 24.490000000000002
|
| 3072 |
+
- type: precision_at_20
|
| 3073 |
+
value: 18.776
|
| 3074 |
+
- type: precision_at_30
|
| 3075 |
+
value: 15.034
|
| 3076 |
+
- type: precision_at_50
|
| 3077 |
+
value: 10.857
|
| 3078 |
+
- type: precision_at_70
|
| 3079 |
+
value: 9.096
|
| 3080 |
+
- type: precision_at_100
|
| 3081 |
+
value: 7.51
|
| 3082 |
+
- type: precision_at_200
|
| 3083 |
+
value: 4.929
|
| 3084 |
+
- type: precision_at_300
|
| 3085 |
+
value: 3.7760000000000002
|
| 3086 |
+
- type: precision_at_500
|
| 3087 |
+
value: 2.6780000000000004
|
| 3088 |
+
- type: precision_at_700
|
| 3089 |
+
value: 2.085
|
| 3090 |
+
- type: precision_at_1000
|
| 3091 |
+
value: 1.5709999999999997
|
| 3092 |
+
- type: mrr_at_1
|
| 3093 |
+
value: 46.939
|
| 3094 |
+
- type: mrr_at_2
|
| 3095 |
+
value: 55.102
|
| 3096 |
+
- type: mrr_at_3
|
| 3097 |
+
value: 57.823
|
| 3098 |
+
- type: mrr_at_5
|
| 3099 |
+
value: 60.68
|
| 3100 |
+
- type: mrr_at_7
|
| 3101 |
+
value: 60.972
|
| 3102 |
+
- type: mrr_at_10
|
| 3103 |
+
value: 61.199000000000005
|
| 3104 |
+
- type: mrr_at_20
|
| 3105 |
+
value: 61.831
|
| 3106 |
+
- type: mrr_at_30
|
| 3107 |
+
value: 61.831
|
| 3108 |
+
- type: mrr_at_50
|
| 3109 |
+
value: 61.873
|
| 3110 |
+
- type: mrr_at_70
|
| 3111 |
+
value: 61.873
|
| 3112 |
+
- type: mrr_at_100
|
| 3113 |
+
value: 61.873
|
| 3114 |
+
- type: mrr_at_200
|
| 3115 |
+
value: 61.873
|
| 3116 |
+
- type: mrr_at_300
|
| 3117 |
+
value: 61.873
|
| 3118 |
+
- type: mrr_at_500
|
| 3119 |
+
value: 61.873
|
| 3120 |
+
- type: mrr_at_700
|
| 3121 |
+
value: 61.873
|
| 3122 |
+
- type: mrr_at_1000
|
| 3123 |
+
value: 61.873
|
| 3124 |
+
- task:
|
| 3125 |
+
type: Classification
|
| 3126 |
+
dataset:
|
| 3127 |
+
type: mteb/toxic_conversations_50k
|
| 3128 |
+
name: MTEB ToxicConversationsClassification
|
| 3129 |
+
config: default
|
| 3130 |
+
split: test
|
| 3131 |
+
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
| 3132 |
+
metrics:
|
| 3133 |
+
- type: accuracy
|
| 3134 |
+
value: 69.3294
|
| 3135 |
+
- type: ap
|
| 3136 |
+
value: 14.561333393364736
|
| 3137 |
+
- type: f1
|
| 3138 |
+
value: 53.992309820496466
|
| 3139 |
+
- task:
|
| 3140 |
+
type: Classification
|
| 3141 |
+
dataset:
|
| 3142 |
+
type: mteb/tweet_sentiment_extraction
|
| 3143 |
+
name: MTEB TweetSentimentExtractionClassification
|
| 3144 |
+
config: default
|
| 3145 |
+
split: test
|
| 3146 |
+
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
| 3147 |
+
metrics:
|
| 3148 |
+
- type: accuracy
|
| 3149 |
+
value: 63.63893604980192
|
| 3150 |
+
- type: f1
|
| 3151 |
+
value: 63.92959380489434
|
| 3152 |
+
- task:
|
| 3153 |
+
type: Clustering
|
| 3154 |
+
dataset:
|
| 3155 |
+
type: mteb/twentynewsgroups-clustering
|
| 3156 |
+
name: MTEB TwentyNewsgroupsClustering
|
| 3157 |
+
config: default
|
| 3158 |
+
split: test
|
| 3159 |
+
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
| 3160 |
+
metrics:
|
| 3161 |
+
- type: v_measure
|
| 3162 |
+
value: 56.270879258659775
|
| 3163 |
+
- task:
|
| 3164 |
+
type: PairClassification
|
| 3165 |
+
dataset:
|
| 3166 |
+
type: mteb/twittersemeval2015-pairclassification
|
| 3167 |
+
name: MTEB TwitterSemEval2015
|
| 3168 |
+
config: default
|
| 3169 |
+
split: test
|
| 3170 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
| 3171 |
+
metrics:
|
| 3172 |
+
- type: cos_sim_accuracy
|
| 3173 |
+
value: 88.71073493473207
|
| 3174 |
+
- type: cos_sim_ap
|
| 3175 |
+
value: 81.52392540284202
|
| 3176 |
+
- type: cos_sim_f1
|
| 3177 |
+
value: 74.71162377994676
|
| 3178 |
+
- type: cos_sim_precision
|
| 3179 |
+
value: 71.89558428885094
|
| 3180 |
+
- type: cos_sim_recall
|
| 3181 |
+
value: 77.75725593667546
|
| 3182 |
+
- type: dot_accuracy
|
| 3183 |
+
value: 88.71073493473207
|
| 3184 |
+
- type: dot_ap
|
| 3185 |
+
value: 81.52394754041109
|
| 3186 |
+
- type: dot_f1
|
| 3187 |
+
value: 74.71162377994676
|
| 3188 |
+
- type: dot_precision
|
| 3189 |
+
value: 71.89558428885094
|
| 3190 |
+
- type: dot_recall
|
| 3191 |
+
value: 77.75725593667546
|
| 3192 |
+
- type: euclidean_accuracy
|
| 3193 |
+
value: 88.71073493473207
|
| 3194 |
+
- type: euclidean_ap
|
| 3195 |
+
value: 81.52392035435321
|
| 3196 |
+
- type: euclidean_f1
|
| 3197 |
+
value: 74.71162377994676
|
| 3198 |
+
- type: euclidean_precision
|
| 3199 |
+
value: 71.89558428885094
|
| 3200 |
+
- type: euclidean_recall
|
| 3201 |
+
value: 77.75725593667546
|
| 3202 |
+
- type: manhattan_accuracy
|
| 3203 |
+
value: 88.47231328604637
|
| 3204 |
+
- type: manhattan_ap
|
| 3205 |
+
value: 81.22907439267321
|
| 3206 |
+
- type: manhattan_f1
|
| 3207 |
+
value: 74.3351571446749
|
| 3208 |
+
- type: manhattan_precision
|
| 3209 |
+
value: 71.78667977390022
|
| 3210 |
+
- type: manhattan_recall
|
| 3211 |
+
value: 77.0712401055409
|
| 3212 |
+
- type: max_accuracy
|
| 3213 |
+
value: 88.71073493473207
|
| 3214 |
+
- type: max_ap
|
| 3215 |
+
value: 81.52394754041109
|
| 3216 |
+
- type: max_f1
|
| 3217 |
+
value: 74.71162377994676
|
| 3218 |
+
- task:
|
| 3219 |
+
type: PairClassification
|
| 3220 |
+
dataset:
|
| 3221 |
+
type: mteb/twitterurlcorpus-pairclassification
|
| 3222 |
+
name: MTEB TwitterURLCorpus
|
| 3223 |
+
config: default
|
| 3224 |
+
split: test
|
| 3225 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
| 3226 |
+
metrics:
|
| 3227 |
+
- type: cos_sim_accuracy
|
| 3228 |
+
value: 89.85136026700819
|
| 3229 |
+
- type: cos_sim_ap
|
| 3230 |
+
value: 87.7768002924216
|
| 3231 |
+
- type: cos_sim_f1
|
| 3232 |
+
value: 80.358908624794
|
| 3233 |
+
- type: cos_sim_precision
|
| 3234 |
+
value: 76.62918209122023
|
| 3235 |
+
- type: cos_sim_recall
|
| 3236 |
+
value: 84.47028025870034
|
| 3237 |
+
- type: dot_accuracy
|
| 3238 |
+
value: 89.85136026700819
|
| 3239 |
+
- type: dot_ap
|
| 3240 |
+
value: 87.77680027889778
|
| 3241 |
+
- type: dot_f1
|
| 3242 |
+
value: 80.358908624794
|
| 3243 |
+
- type: dot_precision
|
| 3244 |
+
value: 76.62918209122023
|
| 3245 |
+
- type: dot_recall
|
| 3246 |
+
value: 84.47028025870034
|
| 3247 |
+
- type: euclidean_accuracy
|
| 3248 |
+
value: 89.85136026700819
|
| 3249 |
+
- type: euclidean_ap
|
| 3250 |
+
value: 87.77680174697751
|
| 3251 |
+
- type: euclidean_f1
|
| 3252 |
+
value: 80.358908624794
|
| 3253 |
+
- type: euclidean_precision
|
| 3254 |
+
value: 76.62918209122023
|
| 3255 |
+
- type: euclidean_recall
|
| 3256 |
+
value: 84.47028025870034
|
| 3257 |
+
- type: manhattan_accuracy
|
| 3258 |
+
value: 89.86300306593705
|
| 3259 |
+
- type: manhattan_ap
|
| 3260 |
+
value: 87.78613271895861
|
| 3261 |
+
- type: manhattan_f1
|
| 3262 |
+
value: 80.31831016905645
|
| 3263 |
+
- type: manhattan_precision
|
| 3264 |
+
value: 76.68230516070304
|
| 3265 |
+
- type: manhattan_recall
|
| 3266 |
+
value: 84.3162919618109
|
| 3267 |
+
- type: max_accuracy
|
| 3268 |
+
value: 89.86300306593705
|
| 3269 |
+
- type: max_ap
|
| 3270 |
+
value: 87.78613271895861
|
| 3271 |
+
- type: max_f1
|
| 3272 |
+
value: 80.358908624794
|
| 3273 |
+
language:
|
| 3274 |
+
- en
|
| 3275 |
+
license: cc-by-nc-4.0
|
| 3276 |
+
---
|
| 3277 |
+
|
| 3278 |
+
<h1 align="center">Salesforce/SFR-Embedding-Mistral</h1>
|
| 3279 |
+
|
| 3280 |
+
**SFR-Embedding by Salesforce Research.**
|
| 3281 |
+
|
| 3282 |
+
The model is trained on top of [E5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct) and [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1).
|
| 3283 |
+
|
| 3284 |
+
This project is for research purposes only. Third-party datasets may be subject to additional terms and conditions under their associated licenses. Please refer to specific papers for more details:
|
| 3285 |
+
- [MTEB benchmark](https://arxiv.org/abs/2210.07316)
|
| 3286 |
+
- [Mistral](https://arxiv.org/abs/2310.06825)
|
| 3287 |
+
- [E5-mistral-7b-instruct](https://arxiv.org/pdf/2401.00368.pdf)
|
| 3288 |
+
|
| 3289 |
+
More technical details will be updated later.
|
| 3290 |
+
|
| 3291 |
+
## How to run
|
| 3292 |
+
|
| 3293 |
+
### Transformers
|
| 3294 |
+
The models can be used as follows:
|
| 3295 |
+
```python
|
| 3296 |
+
import torch
|
| 3297 |
+
import torch.nn.functional as F
|
| 3298 |
+
from torch import Tensor
|
| 3299 |
+
from transformers import AutoTokenizer, AutoModel
|
| 3300 |
+
|
| 3301 |
+
def last_token_pool(last_hidden_states: Tensor,
|
| 3302 |
+
attention_mask: Tensor) -> Tensor:
|
| 3303 |
+
left_padding = (attention_mask[:, -1].sum() == attention_mask.shape[0])
|
| 3304 |
+
if left_padding:
|
| 3305 |
+
return last_hidden_states[:, -1]
|
| 3306 |
+
else:
|
| 3307 |
+
sequence_lengths = attention_mask.sum(dim=1) - 1
|
| 3308 |
+
batch_size = last_hidden_states.shape[0]
|
| 3309 |
+
return last_hidden_states[torch.arange(batch_size, device=last_hidden_states.device), sequence_lengths]
|
| 3310 |
+
|
| 3311 |
+
def get_detailed_instruct(task_description: str, query: str) -> str:
|
| 3312 |
+
return f'Instruct: {task_description}\nQuery: {query}'
|
| 3313 |
+
|
| 3314 |
+
# Each query must come with a one-sentence instruction that describes the task
|
| 3315 |
+
task = 'Given a web search query, retrieve relevant passages that answer the query'
|
| 3316 |
+
queries = [
|
| 3317 |
+
get_detailed_instruct(task, 'How to bake a chocolate cake'),
|
| 3318 |
+
get_detailed_instruct(task, 'Symptoms of the flu')
|
| 3319 |
+
]
|
| 3320 |
+
# No need to add instruction for retrieval documents
|
| 3321 |
+
passages = [
|
| 3322 |
+
"To bake a delicious chocolate cake, you'll need the following ingredients: all-purpose flour, sugar, cocoa powder, baking powder, baking soda, salt, eggs, milk, vegetable oil, and vanilla extract. Start by preheating your oven to 350°F (175°C). In a mixing bowl, combine the dry ingredients (flour, sugar, cocoa powder, baking powder, baking soda, and salt). In a separate bowl, whisk together the wet ingredients (eggs, milk, vegetable oil, and vanilla extract). Gradually add the wet mixture to the dry ingredients, stirring until well combined. Pour the batter into a greased cake pan and bake for 30-35 minutes. Let it cool before frosting with your favorite chocolate frosting. Enjoy your homemade chocolate cake!",
|
| 3323 |
+
"The flu, or influenza, is an illness caused by influenza viruses. Common symptoms of the flu include a high fever, chills, cough, sore throat, runny or stuffy nose, body aches, headache, fatigue, and sometimes nausea and vomiting. These symptoms can come on suddenly and are usually more severe than the common cold. It's important to get plenty of rest, stay hydrated, and consult a healthcare professional if you suspect you have the flu. In some cases, antiviral medications can help alleviate symptoms and reduce the duration of the illness."
|
| 3324 |
+
]
|
| 3325 |
+
|
| 3326 |
+
# load model and tokenizer
|
| 3327 |
+
tokenizer = AutoTokenizer.from_pretrained('Salesforce/SFR-Embedding-Mistral')
|
| 3328 |
+
model = AutoModel.from_pretrained('Salesforce/SFR-Embedding-Mistral')
|
| 3329 |
+
|
| 3330 |
+
# get the embeddings
|
| 3331 |
+
max_length = 4096
|
| 3332 |
+
input_texts = queries + passages
|
| 3333 |
+
batch_dict = tokenizer(input_texts, max_length=max_length, padding=True, truncation=True, return_tensors="pt")
|
| 3334 |
+
outputs = model(**batch_dict)
|
| 3335 |
+
embeddings = last_token_pool(outputs.last_hidden_state, batch_dict['attention_mask'])
|
| 3336 |
+
|
| 3337 |
+
# normalize embeddings
|
| 3338 |
+
embeddings = F.normalize(embeddings, p=2, dim=1)
|
| 3339 |
+
scores = (embeddings[:2] @ embeddings[2:].T) * 100
|
| 3340 |
+
print(scores.tolist())
|
| 3341 |
+
# [[86.7153549194336, 36.64569091796875], [35.00493621826172, 82.0738525390625]]
|
| 3342 |
+
```
|
| 3343 |
+
|
| 3344 |
+
### Sentence Transformers
|
| 3345 |
+
```python
|
| 3346 |
+
|
| 3347 |
+
from sentence_transformers import SentenceTransformer, util
|
| 3348 |
+
|
| 3349 |
+
model = SentenceTransformer("Salesforce/SFR-Embedding-Mistral")
|
| 3350 |
+
|
| 3351 |
+
def get_detailed_instruct(task_description: str, query: str) -> str:
|
| 3352 |
+
return f'Instruct: {task_description}\nQuery: {query}'
|
| 3353 |
+
|
| 3354 |
+
# Each query must come with a one-sentence instruction that describes the task
|
| 3355 |
+
task = 'Given a web search query, retrieve relevant passages that answer the query'
|
| 3356 |
+
queries = [
|
| 3357 |
+
get_detailed_instruct(task, 'How to bake a chocolate cake'),
|
| 3358 |
+
get_detailed_instruct(task, 'Symptoms of the flu')
|
| 3359 |
+
]
|
| 3360 |
+
# No need to add instruction for retrieval documents
|
| 3361 |
+
passages = [
|
| 3362 |
+
"To bake a delicious chocolate cake, you'll need the following ingredients: all-purpose flour, sugar, cocoa powder, baking powder, baking soda, salt, eggs, milk, vegetable oil, and vanilla extract. Start by preheating your oven to 350°F (175°C). In a mixing bowl, combine the dry ingredients (flour, sugar, cocoa powder, baking powder, baking soda, and salt). In a separate bowl, whisk together the wet ingredients (eggs, milk, vegetable oil, and vanilla extract). Gradually add the wet mixture to the dry ingredients, stirring until well combined. Pour the batter into a greased cake pan and bake for 30-35 minutes. Let it cool before frosting with your favorite chocolate frosting. Enjoy your homemade chocolate cake!",
|
| 3363 |
+
"The flu, or influenza, is an illness caused by influenza viruses. Common symptoms of the flu include a high fever, chills, cough, sore throat, runny or stuffy nose, body aches, headache, fatigue, and sometimes nausea and vomiting. These symptoms can come on suddenly and are usually more severe than the common cold. It's important to get plenty of rest, stay hydrated, and consult a healthcare professional if you suspect you have the flu. In some cases, antiviral medications can help alleviate symptoms and reduce the duration of the illness."
|
| 3364 |
+
]
|
| 3365 |
+
|
| 3366 |
+
embeddings = model.encode(queries + passages)
|
| 3367 |
+
scores = util.cos_sim(embeddings[:2], embeddings[2:]) * 100
|
| 3368 |
+
print(scores.tolist())
|
| 3369 |
+
# [[86.71537780761719, 36.645721435546875], [35.00497055053711, 82.07388305664062]]
|
| 3370 |
+
```
|
| 3371 |
+
|
| 3372 |
+
### MTEB Benchmark Evaluation
|
| 3373 |
+
Check out [unilm/e5](https://github.com/microsoft/unilm/tree/master/e5) to reproduce evaluation results on the [BEIR](https://arxiv.org/abs/2104.08663) and [MTEB](https://arxiv.org/abs/2210.07316) benchmark.
|
| 3374 |
+
|
| 3375 |
+
|
| 3376 |
+
SFR-Embedding Team (∗indicates lead contributors).
|
| 3377 |
+
* Rui Meng*
|
| 3378 |
+
* Ye Liu*
|
| 3379 |
+
* Semih Yavuz
|
| 3380 |
+
* Yingbo Zhou
|
| 3381 |
+
* Caiming Xiong
|
config.json
ADDED
|
@@ -0,0 +1,27 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "Salesforce/SFR-Embedding-Mistral",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"MistralModel"
|
| 5 |
+
],
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"bos_token_id": 1,
|
| 8 |
+
"eos_token_id": 2,
|
| 9 |
+
"hidden_act": "silu",
|
| 10 |
+
"hidden_size": 4096,
|
| 11 |
+
"initializer_range": 0.02,
|
| 12 |
+
"intermediate_size": 14336,
|
| 13 |
+
"max_position_embeddings": 32768,
|
| 14 |
+
"model_type": "mistral",
|
| 15 |
+
"num_attention_heads": 32,
|
| 16 |
+
"num_hidden_layers": 32,
|
| 17 |
+
"num_key_value_heads": 8,
|
| 18 |
+
"pad_token_id": 2,
|
| 19 |
+
"rms_norm_eps": 1e-05,
|
| 20 |
+
"rope_theta": 10000.0,
|
| 21 |
+
"sliding_window": 4096,
|
| 22 |
+
"tie_word_embeddings": false,
|
| 23 |
+
"torch_dtype": "float32",
|
| 24 |
+
"transformers_version": "4.37.2",
|
| 25 |
+
"use_cache": false,
|
| 26 |
+
"vocab_size": 32000
|
| 27 |
+
}
|
config_sentence_transformers.json
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"__version__": {
|
| 3 |
+
"sentence_transformers": "2.2.2",
|
| 4 |
+
"transformers": "4.37.2",
|
| 5 |
+
"pytorch": "2.1.0+cu121"
|
| 6 |
+
},
|
| 7 |
+
"prompts": {},
|
| 8 |
+
"default_prompt_name": null
|
| 9 |
+
}
|
model-00001-of-00006.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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| 3 |
+
size 4987196648
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model-00002-of-00006.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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model-00003-of-00006.safetensors
ADDED
|
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version https://git-lfs.github.com/spec/v1
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model-00004-of-00006.safetensors
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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| 3 |
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size 4999812808
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model-00005-of-00006.safetensors
ADDED
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version https://git-lfs.github.com/spec/v1
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| 3 |
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size 4832007216
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model-00006-of-00006.safetensors
ADDED
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version https://git-lfs.github.com/spec/v1
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|
model.safetensors.index.json
ADDED
|
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|
|
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|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
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|
|
|
|
|
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|
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|
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|
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|
|
|
|
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|
|
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|
|
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|
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|
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|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
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| 1 |
+
{
|
| 2 |
+
"add_bos_token": true,
|
| 3 |
+
"add_eos_token": true,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
+
"0": {
|
| 6 |
+
"content": "<unk>",
|
| 7 |
+
"lstrip": false,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false,
|
| 11 |
+
"special": true
|
| 12 |
+
},
|
| 13 |
+
"1": {
|
| 14 |
+
"content": "<s>",
|
| 15 |
+
"lstrip": false,
|
| 16 |
+
"normalized": false,
|
| 17 |
+
"rstrip": false,
|
| 18 |
+
"single_word": false,
|
| 19 |
+
"special": true
|
| 20 |
+
},
|
| 21 |
+
"2": {
|
| 22 |
+
"content": "</s>",
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": false,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": true
|
| 28 |
+
}
|
| 29 |
+
},
|
| 30 |
+
"additional_special_tokens": [
|
| 31 |
+
"<unk>",
|
| 32 |
+
"<s>",
|
| 33 |
+
"</s>"
|
| 34 |
+
],
|
| 35 |
+
"bos_token": "<s>",
|
| 36 |
+
"clean_up_tokenization_spaces": false,
|
| 37 |
+
"eos_token": "</s>",
|
| 38 |
+
"legacy": true,
|
| 39 |
+
"max_length": 512,
|
| 40 |
+
"model_max_length": 1000000000000000019884624838656,
|
| 41 |
+
"pad_to_multiple_of": null,
|
| 42 |
+
"pad_token": "</s>",
|
| 43 |
+
"pad_token_type_id": 0,
|
| 44 |
+
"padding_side": "right",
|
| 45 |
+
"sp_model_kwargs": {},
|
| 46 |
+
"spaces_between_special_tokens": false,
|
| 47 |
+
"stride": 0,
|
| 48 |
+
"tokenizer_class": "LlamaTokenizer",
|
| 49 |
+
"truncation_side": "right",
|
| 50 |
+
"truncation_strategy": "longest_first",
|
| 51 |
+
"unk_token": "<unk>",
|
| 52 |
+
"use_default_system_prompt": false
|
| 53 |
+
}
|