Commit
•
0d58f6f
1
Parent(s):
1aea373
Add MTEB benchmarking
Browse files
README.md
CHANGED
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@@ -4,9 +4,2498 @@ tags:
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| 4 |
- sentence-transformers
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| 5 |
- feature-extraction
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| 6 |
- sentence-similarity
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|
| 7 |
---
|
| 8 |
|
| 9 |
-
# SGPT-5.8B-weightedmean-
|
| 10 |
|
| 11 |
## Usage
|
| 12 |
|
|
@@ -14,16 +2503,16 @@ For usage instructions, refer to our codebase: https://github.com/Muennighoff/sg
|
|
| 14 |
|
| 15 |
## Evaluation Results
|
| 16 |
|
| 17 |
-
For eval results, refer to
|
| 18 |
|
| 19 |
## Training
|
| 20 |
The model was trained with the parameters:
|
| 21 |
|
| 22 |
**DataLoader**:
|
| 23 |
|
| 24 |
-
`
|
| 25 |
```
|
| 26 |
-
{'batch_size':
|
| 27 |
```
|
| 28 |
|
| 29 |
**Loss**:
|
|
@@ -36,17 +2525,17 @@ The model was trained with the parameters:
|
|
| 36 |
Parameters of the fit()-Method:
|
| 37 |
```
|
| 38 |
{
|
| 39 |
-
"epochs":
|
| 40 |
-
"evaluation_steps":
|
| 41 |
-
"evaluator": "
|
| 42 |
"max_grad_norm": 1,
|
| 43 |
"optimizer_class": "<class 'transformers.optimization.AdamW'>",
|
| 44 |
"optimizer_params": {
|
| 45 |
-
"lr":
|
| 46 |
},
|
| 47 |
"scheduler": "WarmupLinear",
|
| 48 |
"steps_per_epoch": null,
|
| 49 |
-
"warmup_steps":
|
| 50 |
"weight_decay": 0.01
|
| 51 |
}
|
| 52 |
```
|
|
@@ -55,7 +2544,7 @@ Parameters of the fit()-Method:
|
|
| 55 |
## Full Model Architecture
|
| 56 |
```
|
| 57 |
SentenceTransformer(
|
| 58 |
-
(0): Transformer({'max_seq_length':
|
| 59 |
(1): Pooling({'word_embedding_dimension': 4096, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': True, 'pooling_mode_lasttoken': False})
|
| 60 |
)
|
| 61 |
```
|
|
|
|
| 4 |
- sentence-transformers
|
| 5 |
- feature-extraction
|
| 6 |
- sentence-similarity
|
| 7 |
+
model-index:
|
| 8 |
+
- name: SGPT-5.8B-weightedmean-nli-bitfit
|
| 9 |
+
results:
|
| 10 |
+
- task:
|
| 11 |
+
type: Classification
|
| 12 |
+
dataset:
|
| 13 |
+
type: mteb/amazon_counterfactual
|
| 14 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
| 15 |
+
config: en
|
| 16 |
+
split: test
|
| 17 |
+
metrics:
|
| 18 |
+
- type: accuracy
|
| 19 |
+
value: 74.07462686567165
|
| 20 |
+
- type: ap
|
| 21 |
+
value: 37.44692407529112
|
| 22 |
+
- type: f1
|
| 23 |
+
value: 68.28971003916419
|
| 24 |
+
- task:
|
| 25 |
+
type: Classification
|
| 26 |
+
dataset:
|
| 27 |
+
type: mteb/amazon_counterfactual
|
| 28 |
+
name: MTEB AmazonCounterfactualClassification (de)
|
| 29 |
+
config: de
|
| 30 |
+
split: test
|
| 31 |
+
metrics:
|
| 32 |
+
- type: accuracy
|
| 33 |
+
value: 66.63811563169165
|
| 34 |
+
- type: ap
|
| 35 |
+
value: 78.57252079915924
|
| 36 |
+
- type: f1
|
| 37 |
+
value: 64.5543087846584
|
| 38 |
+
- task:
|
| 39 |
+
type: Classification
|
| 40 |
+
dataset:
|
| 41 |
+
type: mteb/amazon_counterfactual
|
| 42 |
+
name: MTEB AmazonCounterfactualClassification (en-ext)
|
| 43 |
+
config: en-ext
|
| 44 |
+
split: test
|
| 45 |
+
metrics:
|
| 46 |
+
- type: accuracy
|
| 47 |
+
value: 77.21889055472263
|
| 48 |
+
- type: ap
|
| 49 |
+
value: 25.663426367826712
|
| 50 |
+
- type: f1
|
| 51 |
+
value: 64.26265688503176
|
| 52 |
+
- task:
|
| 53 |
+
type: Classification
|
| 54 |
+
dataset:
|
| 55 |
+
type: mteb/amazon_counterfactual
|
| 56 |
+
name: MTEB AmazonCounterfactualClassification (ja)
|
| 57 |
+
config: ja
|
| 58 |
+
split: test
|
| 59 |
+
metrics:
|
| 60 |
+
- type: accuracy
|
| 61 |
+
value: 58.06209850107067
|
| 62 |
+
- type: ap
|
| 63 |
+
value: 14.028219107023915
|
| 64 |
+
- type: f1
|
| 65 |
+
value: 48.10387189660778
|
| 66 |
+
- task:
|
| 67 |
+
type: Classification
|
| 68 |
+
dataset:
|
| 69 |
+
type: mteb/amazon_polarity
|
| 70 |
+
name: MTEB AmazonPolarityClassification
|
| 71 |
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config: default
|
| 72 |
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split: test
|
| 73 |
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metrics:
|
| 74 |
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- type: accuracy
|
| 75 |
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value: 82.30920000000002
|
| 76 |
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- type: ap
|
| 77 |
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value: 76.88786578621213
|
| 78 |
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- type: f1
|
| 79 |
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value: 82.15455656065011
|
| 80 |
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- task:
|
| 81 |
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type: Classification
|
| 82 |
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dataset:
|
| 83 |
+
type: mteb/amazon_reviews_multi
|
| 84 |
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name: MTEB AmazonReviewsClassification (en)
|
| 85 |
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config: en
|
| 86 |
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split: test
|
| 87 |
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metrics:
|
| 88 |
+
- type: accuracy
|
| 89 |
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value: 41.584
|
| 90 |
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- type: f1
|
| 91 |
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value: 41.203137944390114
|
| 92 |
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- task:
|
| 93 |
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type: Classification
|
| 94 |
+
dataset:
|
| 95 |
+
type: mteb/amazon_reviews_multi
|
| 96 |
+
name: MTEB AmazonReviewsClassification (de)
|
| 97 |
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config: de
|
| 98 |
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split: test
|
| 99 |
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metrics:
|
| 100 |
+
- type: accuracy
|
| 101 |
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value: 35.288000000000004
|
| 102 |
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- type: f1
|
| 103 |
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value: 34.672995558518096
|
| 104 |
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- task:
|
| 105 |
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type: Classification
|
| 106 |
+
dataset:
|
| 107 |
+
type: mteb/amazon_reviews_multi
|
| 108 |
+
name: MTEB AmazonReviewsClassification (es)
|
| 109 |
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config: es
|
| 110 |
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split: test
|
| 111 |
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metrics:
|
| 112 |
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- type: accuracy
|
| 113 |
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value: 38.34
|
| 114 |
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- type: f1
|
| 115 |
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value: 37.608755629529455
|
| 116 |
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- task:
|
| 117 |
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type: Classification
|
| 118 |
+
dataset:
|
| 119 |
+
type: mteb/amazon_reviews_multi
|
| 120 |
+
name: MTEB AmazonReviewsClassification (fr)
|
| 121 |
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config: fr
|
| 122 |
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split: test
|
| 123 |
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metrics:
|
| 124 |
+
- type: accuracy
|
| 125 |
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value: 37.839999999999996
|
| 126 |
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- type: f1
|
| 127 |
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value: 36.86898201563507
|
| 128 |
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- task:
|
| 129 |
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type: Classification
|
| 130 |
+
dataset:
|
| 131 |
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type: mteb/amazon_reviews_multi
|
| 132 |
+
name: MTEB AmazonReviewsClassification (ja)
|
| 133 |
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config: ja
|
| 134 |
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split: test
|
| 135 |
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metrics:
|
| 136 |
+
- type: accuracy
|
| 137 |
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value: 30.936000000000003
|
| 138 |
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- type: f1
|
| 139 |
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value: 30.49401738527071
|
| 140 |
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- task:
|
| 141 |
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type: Classification
|
| 142 |
+
dataset:
|
| 143 |
+
type: mteb/amazon_reviews_multi
|
| 144 |
+
name: MTEB AmazonReviewsClassification (zh)
|
| 145 |
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config: zh
|
| 146 |
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split: test
|
| 147 |
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metrics:
|
| 148 |
+
- type: accuracy
|
| 149 |
+
value: 33.75
|
| 150 |
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- type: f1
|
| 151 |
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value: 33.38338946025617
|
| 152 |
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- task:
|
| 153 |
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type: Retrieval
|
| 154 |
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dataset:
|
| 155 |
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type: arguana
|
| 156 |
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name: MTEB ArguAna
|
| 157 |
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config: default
|
| 158 |
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split: test
|
| 159 |
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metrics:
|
| 160 |
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- type: map_at_1
|
| 161 |
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value: 13.727
|
| 162 |
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|
| 163 |
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value: 26.740000000000002
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| 164 |
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| 165 |
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value: 28.218
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| 166 |
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| 167 |
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value: 28.246
|
| 168 |
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|
| 169 |
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value: 21.728
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| 170 |
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|
| 171 |
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value: 24.371000000000002
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| 172 |
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|
| 173 |
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value: 13.727
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| 174 |
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|
| 175 |
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value: 35.07
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| 176 |
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|
| 177 |
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value: 41.947
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| 178 |
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|
| 179 |
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value: 42.649
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| 180 |
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value: 24.484
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| 182 |
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| 183 |
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value: 29.282999999999998
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| 185 |
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value: 13.727
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| 186 |
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|
| 187 |
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value: 6.223
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| 188 |
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|
| 189 |
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value: 0.9369999999999999
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| 190 |
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|
| 191 |
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value: 0.099
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| 192 |
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|
| 193 |
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value: 10.835
|
| 194 |
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|
| 195 |
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value: 8.848
|
| 196 |
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|
| 197 |
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value: 13.727
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| 198 |
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|
| 199 |
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value: 62.233000000000004
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| 200 |
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- type: recall_at_100
|
| 201 |
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value: 93.67
|
| 202 |
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- type: recall_at_1000
|
| 203 |
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value: 99.14699999999999
|
| 204 |
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- type: recall_at_3
|
| 205 |
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value: 32.504
|
| 206 |
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- type: recall_at_5
|
| 207 |
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value: 44.239
|
| 208 |
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- task:
|
| 209 |
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type: Clustering
|
| 210 |
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dataset:
|
| 211 |
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type: mteb/arxiv-clustering-p2p
|
| 212 |
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name: MTEB ArxivClusteringP2P
|
| 213 |
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config: default
|
| 214 |
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split: test
|
| 215 |
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metrics:
|
| 216 |
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- type: v_measure
|
| 217 |
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value: 40.553923271901695
|
| 218 |
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- task:
|
| 219 |
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type: Clustering
|
| 220 |
+
dataset:
|
| 221 |
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type: mteb/arxiv-clustering-s2s
|
| 222 |
+
name: MTEB ArxivClusteringS2S
|
| 223 |
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config: default
|
| 224 |
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split: test
|
| 225 |
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metrics:
|
| 226 |
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- type: v_measure
|
| 227 |
+
value: 32.49323183712211
|
| 228 |
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- task:
|
| 229 |
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type: Reranking
|
| 230 |
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dataset:
|
| 231 |
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type: mteb/askubuntudupquestions-reranking
|
| 232 |
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name: MTEB AskUbuntuDupQuestions
|
| 233 |
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config: default
|
| 234 |
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split: test
|
| 235 |
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metrics:
|
| 236 |
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- type: map
|
| 237 |
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value: 55.89811361443445
|
| 238 |
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- type: mrr
|
| 239 |
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value: 70.16235764850724
|
| 240 |
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- task:
|
| 241 |
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type: STS
|
| 242 |
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dataset:
|
| 243 |
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type: mteb/biosses-sts
|
| 244 |
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name: MTEB BIOSSES
|
| 245 |
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config: default
|
| 246 |
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split: test
|
| 247 |
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metrics:
|
| 248 |
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|
| 249 |
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value: 82.50506557805856
|
| 250 |
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- type: cos_sim_spearman
|
| 251 |
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value: 79.50000423261176
|
| 252 |
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- type: euclidean_pearson
|
| 253 |
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value: 75.76190885392926
|
| 254 |
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- type: euclidean_spearman
|
| 255 |
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value: 76.7330737163434
|
| 256 |
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- type: manhattan_pearson
|
| 257 |
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value: 75.825318036112
|
| 258 |
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- type: manhattan_spearman
|
| 259 |
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value: 76.7415076434559
|
| 260 |
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- task:
|
| 261 |
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type: BitextMining
|
| 262 |
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dataset:
|
| 263 |
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type: mteb/bucc-bitext-mining
|
| 264 |
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name: MTEB BUCC (de-en)
|
| 265 |
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config: de-en
|
| 266 |
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split: test
|
| 267 |
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metrics:
|
| 268 |
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- type: accuracy
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| 269 |
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value: 75.49060542797494
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| 270 |
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| 271 |
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value: 75.15379262352123
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| 273 |
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value: 74.99391092553932
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| 274 |
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- type: recall
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| 275 |
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value: 75.49060542797494
|
| 276 |
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- task:
|
| 277 |
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type: BitextMining
|
| 278 |
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dataset:
|
| 279 |
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type: mteb/bucc-bitext-mining
|
| 280 |
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name: MTEB BUCC (fr-en)
|
| 281 |
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config: fr-en
|
| 282 |
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split: test
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| 283 |
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metrics:
|
| 284 |
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- type: accuracy
|
| 285 |
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value: 0.4182258419546555
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| 286 |
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| 287 |
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value: 0.4182258419546555
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| 289 |
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value: 0.4182258419546555
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| 290 |
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- type: recall
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| 291 |
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value: 0.4182258419546555
|
| 292 |
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|
| 293 |
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type: BitextMining
|
| 294 |
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dataset:
|
| 295 |
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type: mteb/bucc-bitext-mining
|
| 296 |
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name: MTEB BUCC (ru-en)
|
| 297 |
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config: ru-en
|
| 298 |
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split: test
|
| 299 |
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metrics:
|
| 300 |
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| 301 |
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value: 0.013855213023900243
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| 302 |
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| 303 |
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value: 0.0115460108532502
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| 304 |
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| 305 |
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value: 0.010391409767925183
|
| 306 |
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- type: recall
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| 307 |
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value: 0.013855213023900243
|
| 308 |
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|
| 309 |
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type: BitextMining
|
| 310 |
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dataset:
|
| 311 |
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type: mteb/bucc-bitext-mining
|
| 312 |
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name: MTEB BUCC (zh-en)
|
| 313 |
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config: zh-en
|
| 314 |
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split: test
|
| 315 |
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metrics:
|
| 316 |
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| 317 |
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value: 0.315955766192733
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| 318 |
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|
| 319 |
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value: 0.315955766192733
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| 321 |
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value: 0.315955766192733
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| 322 |
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| 323 |
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value: 0.315955766192733
|
| 324 |
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| 325 |
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type: Classification
|
| 326 |
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dataset:
|
| 327 |
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type: mteb/banking77
|
| 328 |
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name: MTEB Banking77Classification
|
| 329 |
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config: default
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| 330 |
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split: test
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| 331 |
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metrics:
|
| 332 |
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| 333 |
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value: 81.74025974025973
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| 334 |
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|
| 335 |
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value: 81.66568824876
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| 336 |
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- task:
|
| 337 |
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type: Clustering
|
| 338 |
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dataset:
|
| 339 |
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type: mteb/biorxiv-clustering-p2p
|
| 340 |
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name: MTEB BiorxivClusteringP2P
|
| 341 |
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config: default
|
| 342 |
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split: test
|
| 343 |
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metrics:
|
| 344 |
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- type: v_measure
|
| 345 |
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value: 33.59451202614059
|
| 346 |
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- task:
|
| 347 |
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type: Clustering
|
| 348 |
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dataset:
|
| 349 |
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type: mteb/biorxiv-clustering-s2s
|
| 350 |
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name: MTEB BiorxivClusteringS2S
|
| 351 |
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config: default
|
| 352 |
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split: test
|
| 353 |
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metrics:
|
| 354 |
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- type: v_measure
|
| 355 |
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value: 29.128241446157165
|
| 356 |
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- task:
|
| 357 |
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type: Retrieval
|
| 358 |
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dataset:
|
| 359 |
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type: BeIR/cqadupstack
|
| 360 |
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name: MTEB CQADupstackAndroidRetrieval
|
| 361 |
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config: default
|
| 362 |
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split: test
|
| 363 |
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metrics:
|
| 364 |
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- type: map_at_1
|
| 365 |
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value: 26.715
|
| 366 |
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- type: map_at_10
|
| 367 |
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value: 35.007
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| 368 |
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| 369 |
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value: 36.352000000000004
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| 370 |
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| 371 |
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value: 36.51
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| 372 |
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|
| 373 |
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value: 32.257999999999996
|
| 374 |
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- type: map_at_5
|
| 375 |
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value: 33.595000000000006
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| 376 |
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|
| 377 |
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value: 33.906
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| 378 |
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|
| 379 |
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value: 40.353
|
| 380 |
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- type: ndcg_at_100
|
| 381 |
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value: 45.562999999999995
|
| 382 |
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- type: ndcg_at_1000
|
| 383 |
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value: 48.454
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| 384 |
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|
| 385 |
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value: 36.349
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| 386 |
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|
| 387 |
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value: 37.856
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| 388 |
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|
| 389 |
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value: 33.906
|
| 390 |
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|
| 391 |
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value: 7.854
|
| 392 |
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|
| 393 |
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value: 1.29
|
| 394 |
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|
| 395 |
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value: 0.188
|
| 396 |
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- type: precision_at_3
|
| 397 |
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value: 17.549
|
| 398 |
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- type: precision_at_5
|
| 399 |
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value: 12.561
|
| 400 |
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- type: recall_at_1
|
| 401 |
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value: 26.715
|
| 402 |
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- type: recall_at_10
|
| 403 |
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value: 49.508
|
| 404 |
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|
| 405 |
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value: 71.76599999999999
|
| 406 |
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- type: recall_at_1000
|
| 407 |
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value: 91.118
|
| 408 |
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- type: recall_at_3
|
| 409 |
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value: 37.356
|
| 410 |
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- type: recall_at_5
|
| 411 |
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value: 41.836
|
| 412 |
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- task:
|
| 413 |
+
type: Retrieval
|
| 414 |
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dataset:
|
| 415 |
+
type: BeIR/cqadupstack
|
| 416 |
+
name: MTEB CQADupstackEnglishRetrieval
|
| 417 |
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config: default
|
| 418 |
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split: test
|
| 419 |
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metrics:
|
| 420 |
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- type: map_at_1
|
| 421 |
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value: 19.663
|
| 422 |
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- type: map_at_10
|
| 423 |
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value: 27.086
|
| 424 |
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|
| 425 |
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value: 28.066999999999997
|
| 426 |
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|
| 427 |
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value: 28.18
|
| 428 |
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|
| 429 |
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value: 24.819
|
| 430 |
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|
| 431 |
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value: 26.332
|
| 432 |
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|
| 433 |
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value: 25.732
|
| 434 |
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|
| 435 |
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value: 31.613999999999997
|
| 436 |
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- type: ndcg_at_100
|
| 437 |
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value: 35.757
|
| 438 |
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- type: ndcg_at_1000
|
| 439 |
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value: 38.21
|
| 440 |
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|
| 441 |
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value: 28.332
|
| 442 |
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|
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value: 30.264000000000003
|
| 444 |
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|
| 445 |
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value: 25.732
|
| 446 |
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|
| 447 |
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value: 6.038
|
| 448 |
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|
| 449 |
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value: 1.034
|
| 450 |
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|
| 451 |
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value: 0.149
|
| 452 |
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|
| 453 |
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value: 13.864
|
| 454 |
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- type: precision_at_5
|
| 455 |
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value: 10.241999999999999
|
| 456 |
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- type: recall_at_1
|
| 457 |
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value: 19.663
|
| 458 |
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|
| 459 |
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value: 39.585
|
| 460 |
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|
| 461 |
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value: 57.718
|
| 462 |
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- type: recall_at_1000
|
| 463 |
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value: 74.26700000000001
|
| 464 |
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- type: recall_at_3
|
| 465 |
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value: 29.845
|
| 466 |
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- type: recall_at_5
|
| 467 |
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value: 35.105
|
| 468 |
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- task:
|
| 469 |
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type: Retrieval
|
| 470 |
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dataset:
|
| 471 |
+
type: BeIR/cqadupstack
|
| 472 |
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name: MTEB CQADupstackGamingRetrieval
|
| 473 |
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config: default
|
| 474 |
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split: test
|
| 475 |
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metrics:
|
| 476 |
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- type: map_at_1
|
| 477 |
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value: 30.125
|
| 478 |
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- type: map_at_10
|
| 479 |
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value: 39.824
|
| 480 |
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|
| 481 |
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value: 40.935
|
| 482 |
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- type: map_at_1000
|
| 483 |
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value: 41.019
|
| 484 |
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|
| 485 |
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value: 37.144
|
| 486 |
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- type: map_at_5
|
| 487 |
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value: 38.647999999999996
|
| 488 |
+
- type: ndcg_at_1
|
| 489 |
+
value: 34.922
|
| 490 |
+
- type: ndcg_at_10
|
| 491 |
+
value: 45.072
|
| 492 |
+
- type: ndcg_at_100
|
| 493 |
+
value: 50.046
|
| 494 |
+
- type: ndcg_at_1000
|
| 495 |
+
value: 51.895
|
| 496 |
+
- type: ndcg_at_3
|
| 497 |
+
value: 40.251
|
| 498 |
+
- type: ndcg_at_5
|
| 499 |
+
value: 42.581
|
| 500 |
+
- type: precision_at_1
|
| 501 |
+
value: 34.922
|
| 502 |
+
- type: precision_at_10
|
| 503 |
+
value: 7.303999999999999
|
| 504 |
+
- type: precision_at_100
|
| 505 |
+
value: 1.0739999999999998
|
| 506 |
+
- type: precision_at_1000
|
| 507 |
+
value: 0.13
|
| 508 |
+
- type: precision_at_3
|
| 509 |
+
value: 17.994
|
| 510 |
+
- type: precision_at_5
|
| 511 |
+
value: 12.475999999999999
|
| 512 |
+
- type: recall_at_1
|
| 513 |
+
value: 30.125
|
| 514 |
+
- type: recall_at_10
|
| 515 |
+
value: 57.253
|
| 516 |
+
- type: recall_at_100
|
| 517 |
+
value: 79.35799999999999
|
| 518 |
+
- type: recall_at_1000
|
| 519 |
+
value: 92.523
|
| 520 |
+
- type: recall_at_3
|
| 521 |
+
value: 44.088
|
| 522 |
+
- type: recall_at_5
|
| 523 |
+
value: 49.893
|
| 524 |
+
- task:
|
| 525 |
+
type: Retrieval
|
| 526 |
+
dataset:
|
| 527 |
+
type: BeIR/cqadupstack
|
| 528 |
+
name: MTEB CQADupstackGisRetrieval
|
| 529 |
+
config: default
|
| 530 |
+
split: test
|
| 531 |
+
metrics:
|
| 532 |
+
- type: map_at_1
|
| 533 |
+
value: 16.298000000000002
|
| 534 |
+
- type: map_at_10
|
| 535 |
+
value: 21.479
|
| 536 |
+
- type: map_at_100
|
| 537 |
+
value: 22.387
|
| 538 |
+
- type: map_at_1000
|
| 539 |
+
value: 22.483
|
| 540 |
+
- type: map_at_3
|
| 541 |
+
value: 19.743
|
| 542 |
+
- type: map_at_5
|
| 543 |
+
value: 20.444000000000003
|
| 544 |
+
- type: ndcg_at_1
|
| 545 |
+
value: 17.740000000000002
|
| 546 |
+
- type: ndcg_at_10
|
| 547 |
+
value: 24.887
|
| 548 |
+
- type: ndcg_at_100
|
| 549 |
+
value: 29.544999999999998
|
| 550 |
+
- type: ndcg_at_1000
|
| 551 |
+
value: 32.417
|
| 552 |
+
- type: ndcg_at_3
|
| 553 |
+
value: 21.274
|
| 554 |
+
- type: ndcg_at_5
|
| 555 |
+
value: 22.399
|
| 556 |
+
- type: precision_at_1
|
| 557 |
+
value: 17.740000000000002
|
| 558 |
+
- type: precision_at_10
|
| 559 |
+
value: 3.932
|
| 560 |
+
- type: precision_at_100
|
| 561 |
+
value: 0.666
|
| 562 |
+
- type: precision_at_1000
|
| 563 |
+
value: 0.094
|
| 564 |
+
- type: precision_at_3
|
| 565 |
+
value: 8.927
|
| 566 |
+
- type: precision_at_5
|
| 567 |
+
value: 6.056
|
| 568 |
+
- type: recall_at_1
|
| 569 |
+
value: 16.298000000000002
|
| 570 |
+
- type: recall_at_10
|
| 571 |
+
value: 34.031
|
| 572 |
+
- type: recall_at_100
|
| 573 |
+
value: 55.769000000000005
|
| 574 |
+
- type: recall_at_1000
|
| 575 |
+
value: 78.19500000000001
|
| 576 |
+
- type: recall_at_3
|
| 577 |
+
value: 23.799999999999997
|
| 578 |
+
- type: recall_at_5
|
| 579 |
+
value: 26.562
|
| 580 |
+
- task:
|
| 581 |
+
type: Retrieval
|
| 582 |
+
dataset:
|
| 583 |
+
type: BeIR/cqadupstack
|
| 584 |
+
name: MTEB CQADupstackMathematicaRetrieval
|
| 585 |
+
config: default
|
| 586 |
+
split: test
|
| 587 |
+
metrics:
|
| 588 |
+
- type: map_at_1
|
| 589 |
+
value: 10.958
|
| 590 |
+
- type: map_at_10
|
| 591 |
+
value: 16.999
|
| 592 |
+
- type: map_at_100
|
| 593 |
+
value: 17.979
|
| 594 |
+
- type: map_at_1000
|
| 595 |
+
value: 18.112000000000002
|
| 596 |
+
- type: map_at_3
|
| 597 |
+
value: 15.010000000000002
|
| 598 |
+
- type: map_at_5
|
| 599 |
+
value: 16.256999999999998
|
| 600 |
+
- type: ndcg_at_1
|
| 601 |
+
value: 14.179
|
| 602 |
+
- type: ndcg_at_10
|
| 603 |
+
value: 20.985
|
| 604 |
+
- type: ndcg_at_100
|
| 605 |
+
value: 26.216
|
| 606 |
+
- type: ndcg_at_1000
|
| 607 |
+
value: 29.675
|
| 608 |
+
- type: ndcg_at_3
|
| 609 |
+
value: 17.28
|
| 610 |
+
- type: ndcg_at_5
|
| 611 |
+
value: 19.301
|
| 612 |
+
- type: precision_at_1
|
| 613 |
+
value: 14.179
|
| 614 |
+
- type: precision_at_10
|
| 615 |
+
value: 3.968
|
| 616 |
+
- type: precision_at_100
|
| 617 |
+
value: 0.784
|
| 618 |
+
- type: precision_at_1000
|
| 619 |
+
value: 0.121
|
| 620 |
+
- type: precision_at_3
|
| 621 |
+
value: 8.541
|
| 622 |
+
- type: precision_at_5
|
| 623 |
+
value: 6.468
|
| 624 |
+
- type: recall_at_1
|
| 625 |
+
value: 10.958
|
| 626 |
+
- type: recall_at_10
|
| 627 |
+
value: 29.903000000000002
|
| 628 |
+
- type: recall_at_100
|
| 629 |
+
value: 53.413
|
| 630 |
+
- type: recall_at_1000
|
| 631 |
+
value: 78.74799999999999
|
| 632 |
+
- type: recall_at_3
|
| 633 |
+
value: 19.717000000000002
|
| 634 |
+
- type: recall_at_5
|
| 635 |
+
value: 24.817
|
| 636 |
+
- task:
|
| 637 |
+
type: Retrieval
|
| 638 |
+
dataset:
|
| 639 |
+
type: BeIR/cqadupstack
|
| 640 |
+
name: MTEB CQADupstackPhysicsRetrieval
|
| 641 |
+
config: default
|
| 642 |
+
split: test
|
| 643 |
+
metrics:
|
| 644 |
+
- type: map_at_1
|
| 645 |
+
value: 21.217
|
| 646 |
+
- type: map_at_10
|
| 647 |
+
value: 29.677
|
| 648 |
+
- type: map_at_100
|
| 649 |
+
value: 30.928
|
| 650 |
+
- type: map_at_1000
|
| 651 |
+
value: 31.063000000000002
|
| 652 |
+
- type: map_at_3
|
| 653 |
+
value: 26.611
|
| 654 |
+
- type: map_at_5
|
| 655 |
+
value: 28.463
|
| 656 |
+
- type: ndcg_at_1
|
| 657 |
+
value: 26.083000000000002
|
| 658 |
+
- type: ndcg_at_10
|
| 659 |
+
value: 35.217
|
| 660 |
+
- type: ndcg_at_100
|
| 661 |
+
value: 40.715
|
| 662 |
+
- type: ndcg_at_1000
|
| 663 |
+
value: 43.559
|
| 664 |
+
- type: ndcg_at_3
|
| 665 |
+
value: 30.080000000000002
|
| 666 |
+
- type: ndcg_at_5
|
| 667 |
+
value: 32.701
|
| 668 |
+
- type: precision_at_1
|
| 669 |
+
value: 26.083000000000002
|
| 670 |
+
- type: precision_at_10
|
| 671 |
+
value: 6.622
|
| 672 |
+
- type: precision_at_100
|
| 673 |
+
value: 1.115
|
| 674 |
+
- type: precision_at_1000
|
| 675 |
+
value: 0.156
|
| 676 |
+
- type: precision_at_3
|
| 677 |
+
value: 14.629
|
| 678 |
+
- type: precision_at_5
|
| 679 |
+
value: 10.837
|
| 680 |
+
- type: recall_at_1
|
| 681 |
+
value: 21.217
|
| 682 |
+
- type: recall_at_10
|
| 683 |
+
value: 47.031
|
| 684 |
+
- type: recall_at_100
|
| 685 |
+
value: 70.378
|
| 686 |
+
- type: recall_at_1000
|
| 687 |
+
value: 89.704
|
| 688 |
+
- type: recall_at_3
|
| 689 |
+
value: 32.427
|
| 690 |
+
- type: recall_at_5
|
| 691 |
+
value: 39.31
|
| 692 |
+
- task:
|
| 693 |
+
type: Retrieval
|
| 694 |
+
dataset:
|
| 695 |
+
type: BeIR/cqadupstack
|
| 696 |
+
name: MTEB CQADupstackProgrammersRetrieval
|
| 697 |
+
config: default
|
| 698 |
+
split: test
|
| 699 |
+
metrics:
|
| 700 |
+
- type: map_at_1
|
| 701 |
+
value: 19.274
|
| 702 |
+
- type: map_at_10
|
| 703 |
+
value: 26.398
|
| 704 |
+
- type: map_at_100
|
| 705 |
+
value: 27.711000000000002
|
| 706 |
+
- type: map_at_1000
|
| 707 |
+
value: 27.833000000000002
|
| 708 |
+
- type: map_at_3
|
| 709 |
+
value: 24.294
|
| 710 |
+
- type: map_at_5
|
| 711 |
+
value: 25.385
|
| 712 |
+
- type: ndcg_at_1
|
| 713 |
+
value: 24.886
|
| 714 |
+
- type: ndcg_at_10
|
| 715 |
+
value: 30.909
|
| 716 |
+
- type: ndcg_at_100
|
| 717 |
+
value: 36.941
|
| 718 |
+
- type: ndcg_at_1000
|
| 719 |
+
value: 39.838
|
| 720 |
+
- type: ndcg_at_3
|
| 721 |
+
value: 27.455000000000002
|
| 722 |
+
- type: ndcg_at_5
|
| 723 |
+
value: 28.828
|
| 724 |
+
- type: precision_at_1
|
| 725 |
+
value: 24.886
|
| 726 |
+
- type: precision_at_10
|
| 727 |
+
value: 5.6739999999999995
|
| 728 |
+
- type: precision_at_100
|
| 729 |
+
value: 1.0290000000000001
|
| 730 |
+
- type: precision_at_1000
|
| 731 |
+
value: 0.146
|
| 732 |
+
- type: precision_at_3
|
| 733 |
+
value: 13.242
|
| 734 |
+
- type: precision_at_5
|
| 735 |
+
value: 9.292
|
| 736 |
+
- type: recall_at_1
|
| 737 |
+
value: 19.274
|
| 738 |
+
- type: recall_at_10
|
| 739 |
+
value: 39.643
|
| 740 |
+
- type: recall_at_100
|
| 741 |
+
value: 66.091
|
| 742 |
+
- type: recall_at_1000
|
| 743 |
+
value: 86.547
|
| 744 |
+
- type: recall_at_3
|
| 745 |
+
value: 29.602
|
| 746 |
+
- type: recall_at_5
|
| 747 |
+
value: 33.561
|
| 748 |
+
- task:
|
| 749 |
+
type: Retrieval
|
| 750 |
+
dataset:
|
| 751 |
+
type: BeIR/cqadupstack
|
| 752 |
+
name: MTEB CQADupstackRetrieval
|
| 753 |
+
config: default
|
| 754 |
+
split: test
|
| 755 |
+
metrics:
|
| 756 |
+
- type: map_at_1
|
| 757 |
+
value: 18.653666666666666
|
| 758 |
+
- type: map_at_10
|
| 759 |
+
value: 25.606666666666666
|
| 760 |
+
- type: map_at_100
|
| 761 |
+
value: 26.669333333333334
|
| 762 |
+
- type: map_at_1000
|
| 763 |
+
value: 26.795833333333334
|
| 764 |
+
- type: map_at_3
|
| 765 |
+
value: 23.43433333333333
|
| 766 |
+
- type: map_at_5
|
| 767 |
+
value: 24.609666666666666
|
| 768 |
+
- type: ndcg_at_1
|
| 769 |
+
value: 22.742083333333333
|
| 770 |
+
- type: ndcg_at_10
|
| 771 |
+
value: 29.978333333333335
|
| 772 |
+
- type: ndcg_at_100
|
| 773 |
+
value: 34.89808333333333
|
| 774 |
+
- type: ndcg_at_1000
|
| 775 |
+
value: 37.806583333333336
|
| 776 |
+
- type: ndcg_at_3
|
| 777 |
+
value: 26.223666666666674
|
| 778 |
+
- type: ndcg_at_5
|
| 779 |
+
value: 27.91033333333333
|
| 780 |
+
- type: precision_at_1
|
| 781 |
+
value: 22.742083333333333
|
| 782 |
+
- type: precision_at_10
|
| 783 |
+
value: 5.397083333333334
|
| 784 |
+
- type: precision_at_100
|
| 785 |
+
value: 0.9340000000000002
|
| 786 |
+
- type: precision_at_1000
|
| 787 |
+
value: 0.13691666666666663
|
| 788 |
+
- type: precision_at_3
|
| 789 |
+
value: 12.331083333333332
|
| 790 |
+
- type: precision_at_5
|
| 791 |
+
value: 8.805499999999999
|
| 792 |
+
- type: recall_at_1
|
| 793 |
+
value: 18.653666666666666
|
| 794 |
+
- type: recall_at_10
|
| 795 |
+
value: 39.22625000000001
|
| 796 |
+
- type: recall_at_100
|
| 797 |
+
value: 61.31049999999999
|
| 798 |
+
- type: recall_at_1000
|
| 799 |
+
value: 82.19058333333334
|
| 800 |
+
- type: recall_at_3
|
| 801 |
+
value: 28.517333333333333
|
| 802 |
+
- type: recall_at_5
|
| 803 |
+
value: 32.9565
|
| 804 |
+
- task:
|
| 805 |
+
type: Retrieval
|
| 806 |
+
dataset:
|
| 807 |
+
type: BeIR/cqadupstack
|
| 808 |
+
name: MTEB CQADupstackStatsRetrieval
|
| 809 |
+
config: default
|
| 810 |
+
split: test
|
| 811 |
+
metrics:
|
| 812 |
+
- type: map_at_1
|
| 813 |
+
value: 16.07
|
| 814 |
+
- type: map_at_10
|
| 815 |
+
value: 21.509
|
| 816 |
+
- type: map_at_100
|
| 817 |
+
value: 22.335
|
| 818 |
+
- type: map_at_1000
|
| 819 |
+
value: 22.437
|
| 820 |
+
- type: map_at_3
|
| 821 |
+
value: 19.717000000000002
|
| 822 |
+
- type: map_at_5
|
| 823 |
+
value: 20.574
|
| 824 |
+
- type: ndcg_at_1
|
| 825 |
+
value: 18.865000000000002
|
| 826 |
+
- type: ndcg_at_10
|
| 827 |
+
value: 25.135999999999996
|
| 828 |
+
- type: ndcg_at_100
|
| 829 |
+
value: 29.483999999999998
|
| 830 |
+
- type: ndcg_at_1000
|
| 831 |
+
value: 32.303
|
| 832 |
+
- type: ndcg_at_3
|
| 833 |
+
value: 21.719
|
| 834 |
+
- type: ndcg_at_5
|
| 835 |
+
value: 23.039
|
| 836 |
+
- type: precision_at_1
|
| 837 |
+
value: 18.865000000000002
|
| 838 |
+
- type: precision_at_10
|
| 839 |
+
value: 4.263999999999999
|
| 840 |
+
- type: precision_at_100
|
| 841 |
+
value: 0.696
|
| 842 |
+
- type: precision_at_1000
|
| 843 |
+
value: 0.1
|
| 844 |
+
- type: precision_at_3
|
| 845 |
+
value: 9.866999999999999
|
| 846 |
+
- type: precision_at_5
|
| 847 |
+
value: 6.902
|
| 848 |
+
- type: recall_at_1
|
| 849 |
+
value: 16.07
|
| 850 |
+
- type: recall_at_10
|
| 851 |
+
value: 33.661
|
| 852 |
+
- type: recall_at_100
|
| 853 |
+
value: 54.001999999999995
|
| 854 |
+
- type: recall_at_1000
|
| 855 |
+
value: 75.564
|
| 856 |
+
- type: recall_at_3
|
| 857 |
+
value: 23.956
|
| 858 |
+
- type: recall_at_5
|
| 859 |
+
value: 27.264
|
| 860 |
+
- task:
|
| 861 |
+
type: Retrieval
|
| 862 |
+
dataset:
|
| 863 |
+
type: BeIR/cqadupstack
|
| 864 |
+
name: MTEB CQADupstackTexRetrieval
|
| 865 |
+
config: default
|
| 866 |
+
split: test
|
| 867 |
+
metrics:
|
| 868 |
+
- type: map_at_1
|
| 869 |
+
value: 10.847
|
| 870 |
+
- type: map_at_10
|
| 871 |
+
value: 15.518
|
| 872 |
+
- type: map_at_100
|
| 873 |
+
value: 16.384
|
| 874 |
+
- type: map_at_1000
|
| 875 |
+
value: 16.506
|
| 876 |
+
- type: map_at_3
|
| 877 |
+
value: 14.093
|
| 878 |
+
- type: map_at_5
|
| 879 |
+
value: 14.868
|
| 880 |
+
- type: ndcg_at_1
|
| 881 |
+
value: 13.764999999999999
|
| 882 |
+
- type: ndcg_at_10
|
| 883 |
+
value: 18.766
|
| 884 |
+
- type: ndcg_at_100
|
| 885 |
+
value: 23.076
|
| 886 |
+
- type: ndcg_at_1000
|
| 887 |
+
value: 26.344
|
| 888 |
+
- type: ndcg_at_3
|
| 889 |
+
value: 16.150000000000002
|
| 890 |
+
- type: ndcg_at_5
|
| 891 |
+
value: 17.373
|
| 892 |
+
- type: precision_at_1
|
| 893 |
+
value: 13.764999999999999
|
| 894 |
+
- type: precision_at_10
|
| 895 |
+
value: 3.572
|
| 896 |
+
- type: precision_at_100
|
| 897 |
+
value: 0.6779999999999999
|
| 898 |
+
- type: precision_at_1000
|
| 899 |
+
value: 0.11199999999999999
|
| 900 |
+
- type: precision_at_3
|
| 901 |
+
value: 7.88
|
| 902 |
+
- type: precision_at_5
|
| 903 |
+
value: 5.712
|
| 904 |
+
- type: recall_at_1
|
| 905 |
+
value: 10.847
|
| 906 |
+
- type: recall_at_10
|
| 907 |
+
value: 25.141999999999996
|
| 908 |
+
- type: recall_at_100
|
| 909 |
+
value: 44.847
|
| 910 |
+
- type: recall_at_1000
|
| 911 |
+
value: 68.92099999999999
|
| 912 |
+
- type: recall_at_3
|
| 913 |
+
value: 17.721999999999998
|
| 914 |
+
- type: recall_at_5
|
| 915 |
+
value: 20.968999999999998
|
| 916 |
+
- task:
|
| 917 |
+
type: Retrieval
|
| 918 |
+
dataset:
|
| 919 |
+
type: BeIR/cqadupstack
|
| 920 |
+
name: MTEB CQADupstackUnixRetrieval
|
| 921 |
+
config: default
|
| 922 |
+
split: test
|
| 923 |
+
metrics:
|
| 924 |
+
- type: map_at_1
|
| 925 |
+
value: 18.377
|
| 926 |
+
- type: map_at_10
|
| 927 |
+
value: 26.005
|
| 928 |
+
- type: map_at_100
|
| 929 |
+
value: 26.996
|
| 930 |
+
- type: map_at_1000
|
| 931 |
+
value: 27.116
|
| 932 |
+
- type: map_at_3
|
| 933 |
+
value: 23.712
|
| 934 |
+
- type: map_at_5
|
| 935 |
+
value: 24.859
|
| 936 |
+
- type: ndcg_at_1
|
| 937 |
+
value: 22.201
|
| 938 |
+
- type: ndcg_at_10
|
| 939 |
+
value: 30.635
|
| 940 |
+
- type: ndcg_at_100
|
| 941 |
+
value: 35.623
|
| 942 |
+
- type: ndcg_at_1000
|
| 943 |
+
value: 38.551
|
| 944 |
+
- type: ndcg_at_3
|
| 945 |
+
value: 26.565
|
| 946 |
+
- type: ndcg_at_5
|
| 947 |
+
value: 28.28
|
| 948 |
+
- type: precision_at_1
|
| 949 |
+
value: 22.201
|
| 950 |
+
- type: precision_at_10
|
| 951 |
+
value: 5.41
|
| 952 |
+
- type: precision_at_100
|
| 953 |
+
value: 0.88
|
| 954 |
+
- type: precision_at_1000
|
| 955 |
+
value: 0.125
|
| 956 |
+
- type: precision_at_3
|
| 957 |
+
value: 12.531
|
| 958 |
+
- type: precision_at_5
|
| 959 |
+
value: 8.806
|
| 960 |
+
- type: recall_at_1
|
| 961 |
+
value: 18.377
|
| 962 |
+
- type: recall_at_10
|
| 963 |
+
value: 40.908
|
| 964 |
+
- type: recall_at_100
|
| 965 |
+
value: 63.563
|
| 966 |
+
- type: recall_at_1000
|
| 967 |
+
value: 84.503
|
| 968 |
+
- type: recall_at_3
|
| 969 |
+
value: 29.793999999999997
|
| 970 |
+
- type: recall_at_5
|
| 971 |
+
value: 34.144999999999996
|
| 972 |
+
- task:
|
| 973 |
+
type: Retrieval
|
| 974 |
+
dataset:
|
| 975 |
+
type: BeIR/cqadupstack
|
| 976 |
+
name: MTEB CQADupstackWebmastersRetrieval
|
| 977 |
+
config: default
|
| 978 |
+
split: test
|
| 979 |
+
metrics:
|
| 980 |
+
- type: map_at_1
|
| 981 |
+
value: 20.246
|
| 982 |
+
- type: map_at_10
|
| 983 |
+
value: 27.528000000000002
|
| 984 |
+
- type: map_at_100
|
| 985 |
+
value: 28.78
|
| 986 |
+
- type: map_at_1000
|
| 987 |
+
value: 29.002
|
| 988 |
+
- type: map_at_3
|
| 989 |
+
value: 25.226
|
| 990 |
+
- type: map_at_5
|
| 991 |
+
value: 26.355
|
| 992 |
+
- type: ndcg_at_1
|
| 993 |
+
value: 25.099
|
| 994 |
+
- type: ndcg_at_10
|
| 995 |
+
value: 32.421
|
| 996 |
+
- type: ndcg_at_100
|
| 997 |
+
value: 37.2
|
| 998 |
+
- type: ndcg_at_1000
|
| 999 |
+
value: 40.693
|
| 1000 |
+
- type: ndcg_at_3
|
| 1001 |
+
value: 28.768
|
| 1002 |
+
- type: ndcg_at_5
|
| 1003 |
+
value: 30.23
|
| 1004 |
+
- type: precision_at_1
|
| 1005 |
+
value: 25.099
|
| 1006 |
+
- type: precision_at_10
|
| 1007 |
+
value: 6.245
|
| 1008 |
+
- type: precision_at_100
|
| 1009 |
+
value: 1.269
|
| 1010 |
+
- type: precision_at_1000
|
| 1011 |
+
value: 0.218
|
| 1012 |
+
- type: precision_at_3
|
| 1013 |
+
value: 13.767999999999999
|
| 1014 |
+
- type: precision_at_5
|
| 1015 |
+
value: 9.881
|
| 1016 |
+
- type: recall_at_1
|
| 1017 |
+
value: 20.246
|
| 1018 |
+
- type: recall_at_10
|
| 1019 |
+
value: 41.336
|
| 1020 |
+
- type: recall_at_100
|
| 1021 |
+
value: 63.098
|
| 1022 |
+
- type: recall_at_1000
|
| 1023 |
+
value: 86.473
|
| 1024 |
+
- type: recall_at_3
|
| 1025 |
+
value: 30.069000000000003
|
| 1026 |
+
- type: recall_at_5
|
| 1027 |
+
value: 34.262
|
| 1028 |
+
- task:
|
| 1029 |
+
type: Retrieval
|
| 1030 |
+
dataset:
|
| 1031 |
+
type: BeIR/cqadupstack
|
| 1032 |
+
name: MTEB CQADupstackWordpressRetrieval
|
| 1033 |
+
config: default
|
| 1034 |
+
split: test
|
| 1035 |
+
metrics:
|
| 1036 |
+
- type: map_at_1
|
| 1037 |
+
value: 14.054
|
| 1038 |
+
- type: map_at_10
|
| 1039 |
+
value: 20.25
|
| 1040 |
+
- type: map_at_100
|
| 1041 |
+
value: 21.178
|
| 1042 |
+
- type: map_at_1000
|
| 1043 |
+
value: 21.288999999999998
|
| 1044 |
+
- type: map_at_3
|
| 1045 |
+
value: 18.584999999999997
|
| 1046 |
+
- type: map_at_5
|
| 1047 |
+
value: 19.536
|
| 1048 |
+
- type: ndcg_at_1
|
| 1049 |
+
value: 15.527
|
| 1050 |
+
- type: ndcg_at_10
|
| 1051 |
+
value: 23.745
|
| 1052 |
+
- type: ndcg_at_100
|
| 1053 |
+
value: 28.610999999999997
|
| 1054 |
+
- type: ndcg_at_1000
|
| 1055 |
+
value: 31.740000000000002
|
| 1056 |
+
- type: ndcg_at_3
|
| 1057 |
+
value: 20.461
|
| 1058 |
+
- type: ndcg_at_5
|
| 1059 |
+
value: 22.072
|
| 1060 |
+
- type: precision_at_1
|
| 1061 |
+
value: 15.527
|
| 1062 |
+
- type: precision_at_10
|
| 1063 |
+
value: 3.882
|
| 1064 |
+
- type: precision_at_100
|
| 1065 |
+
value: 0.6930000000000001
|
| 1066 |
+
- type: precision_at_1000
|
| 1067 |
+
value: 0.104
|
| 1068 |
+
- type: precision_at_3
|
| 1069 |
+
value: 9.181000000000001
|
| 1070 |
+
- type: precision_at_5
|
| 1071 |
+
value: 6.433
|
| 1072 |
+
- type: recall_at_1
|
| 1073 |
+
value: 14.054
|
| 1074 |
+
- type: recall_at_10
|
| 1075 |
+
value: 32.714
|
| 1076 |
+
- type: recall_at_100
|
| 1077 |
+
value: 55.723
|
| 1078 |
+
- type: recall_at_1000
|
| 1079 |
+
value: 79.72399999999999
|
| 1080 |
+
- type: recall_at_3
|
| 1081 |
+
value: 23.832
|
| 1082 |
+
- type: recall_at_5
|
| 1083 |
+
value: 27.754
|
| 1084 |
+
- task:
|
| 1085 |
+
type: Retrieval
|
| 1086 |
+
dataset:
|
| 1087 |
+
type: climate-fever
|
| 1088 |
+
name: MTEB ClimateFEVER
|
| 1089 |
+
config: default
|
| 1090 |
+
split: test
|
| 1091 |
+
metrics:
|
| 1092 |
+
- type: map_at_1
|
| 1093 |
+
value: 6.122
|
| 1094 |
+
- type: map_at_10
|
| 1095 |
+
value: 11.556
|
| 1096 |
+
- type: map_at_100
|
| 1097 |
+
value: 12.998000000000001
|
| 1098 |
+
- type: map_at_1000
|
| 1099 |
+
value: 13.202
|
| 1100 |
+
- type: map_at_3
|
| 1101 |
+
value: 9.657
|
| 1102 |
+
- type: map_at_5
|
| 1103 |
+
value: 10.585
|
| 1104 |
+
- type: ndcg_at_1
|
| 1105 |
+
value: 15.049000000000001
|
| 1106 |
+
- type: ndcg_at_10
|
| 1107 |
+
value: 17.574
|
| 1108 |
+
- type: ndcg_at_100
|
| 1109 |
+
value: 24.465999999999998
|
| 1110 |
+
- type: ndcg_at_1000
|
| 1111 |
+
value: 28.511999999999997
|
| 1112 |
+
- type: ndcg_at_3
|
| 1113 |
+
value: 13.931
|
| 1114 |
+
- type: ndcg_at_5
|
| 1115 |
+
value: 15.112
|
| 1116 |
+
- type: precision_at_1
|
| 1117 |
+
value: 15.049000000000001
|
| 1118 |
+
- type: precision_at_10
|
| 1119 |
+
value: 5.831
|
| 1120 |
+
- type: precision_at_100
|
| 1121 |
+
value: 1.322
|
| 1122 |
+
- type: precision_at_1000
|
| 1123 |
+
value: 0.20500000000000002
|
| 1124 |
+
- type: precision_at_3
|
| 1125 |
+
value: 10.749
|
| 1126 |
+
- type: precision_at_5
|
| 1127 |
+
value: 8.365
|
| 1128 |
+
- type: recall_at_1
|
| 1129 |
+
value: 6.122
|
| 1130 |
+
- type: recall_at_10
|
| 1131 |
+
value: 22.207
|
| 1132 |
+
- type: recall_at_100
|
| 1133 |
+
value: 47.08
|
| 1134 |
+
- type: recall_at_1000
|
| 1135 |
+
value: 70.182
|
| 1136 |
+
- type: recall_at_3
|
| 1137 |
+
value: 13.416
|
| 1138 |
+
- type: recall_at_5
|
| 1139 |
+
value: 16.672
|
| 1140 |
+
- task:
|
| 1141 |
+
type: Retrieval
|
| 1142 |
+
dataset:
|
| 1143 |
+
type: dbpedia-entity
|
| 1144 |
+
name: MTEB DBPedia
|
| 1145 |
+
config: default
|
| 1146 |
+
split: test
|
| 1147 |
+
metrics:
|
| 1148 |
+
- type: map_at_1
|
| 1149 |
+
value: 4.672
|
| 1150 |
+
- type: map_at_10
|
| 1151 |
+
value: 10.534
|
| 1152 |
+
- type: map_at_100
|
| 1153 |
+
value: 14.798
|
| 1154 |
+
- type: map_at_1000
|
| 1155 |
+
value: 15.927
|
| 1156 |
+
- type: map_at_3
|
| 1157 |
+
value: 7.317
|
| 1158 |
+
- type: map_at_5
|
| 1159 |
+
value: 8.726
|
| 1160 |
+
- type: ndcg_at_1
|
| 1161 |
+
value: 36.5
|
| 1162 |
+
- type: ndcg_at_10
|
| 1163 |
+
value: 26.098
|
| 1164 |
+
- type: ndcg_at_100
|
| 1165 |
+
value: 29.215999999999998
|
| 1166 |
+
- type: ndcg_at_1000
|
| 1167 |
+
value: 36.254999999999995
|
| 1168 |
+
- type: ndcg_at_3
|
| 1169 |
+
value: 29.247
|
| 1170 |
+
- type: ndcg_at_5
|
| 1171 |
+
value: 27.692
|
| 1172 |
+
- type: precision_at_1
|
| 1173 |
+
value: 47.25
|
| 1174 |
+
- type: precision_at_10
|
| 1175 |
+
value: 22.625
|
| 1176 |
+
- type: precision_at_100
|
| 1177 |
+
value: 7.042
|
| 1178 |
+
- type: precision_at_1000
|
| 1179 |
+
value: 1.6129999999999998
|
| 1180 |
+
- type: precision_at_3
|
| 1181 |
+
value: 34.083000000000006
|
| 1182 |
+
- type: precision_at_5
|
| 1183 |
+
value: 29.5
|
| 1184 |
+
- type: recall_at_1
|
| 1185 |
+
value: 4.672
|
| 1186 |
+
- type: recall_at_10
|
| 1187 |
+
value: 15.638
|
| 1188 |
+
- type: recall_at_100
|
| 1189 |
+
value: 36.228
|
| 1190 |
+
- type: recall_at_1000
|
| 1191 |
+
value: 58.831
|
| 1192 |
+
- type: recall_at_3
|
| 1193 |
+
value: 8.578
|
| 1194 |
+
- type: recall_at_5
|
| 1195 |
+
value: 11.18
|
| 1196 |
+
- task:
|
| 1197 |
+
type: Classification
|
| 1198 |
+
dataset:
|
| 1199 |
+
type: mteb/emotion
|
| 1200 |
+
name: MTEB EmotionClassification
|
| 1201 |
+
config: default
|
| 1202 |
+
split: test
|
| 1203 |
+
metrics:
|
| 1204 |
+
- type: accuracy
|
| 1205 |
+
value: 49.919999999999995
|
| 1206 |
+
- type: f1
|
| 1207 |
+
value: 45.37973678791632
|
| 1208 |
+
- task:
|
| 1209 |
+
type: Retrieval
|
| 1210 |
+
dataset:
|
| 1211 |
+
type: fever
|
| 1212 |
+
name: MTEB FEVER
|
| 1213 |
+
config: default
|
| 1214 |
+
split: test
|
| 1215 |
+
metrics:
|
| 1216 |
+
- type: map_at_1
|
| 1217 |
+
value: 25.801000000000002
|
| 1218 |
+
- type: map_at_10
|
| 1219 |
+
value: 33.941
|
| 1220 |
+
- type: map_at_100
|
| 1221 |
+
value: 34.73
|
| 1222 |
+
- type: map_at_1000
|
| 1223 |
+
value: 34.793
|
| 1224 |
+
- type: map_at_3
|
| 1225 |
+
value: 31.705
|
| 1226 |
+
- type: map_at_5
|
| 1227 |
+
value: 33.047
|
| 1228 |
+
- type: ndcg_at_1
|
| 1229 |
+
value: 27.933000000000003
|
| 1230 |
+
- type: ndcg_at_10
|
| 1231 |
+
value: 38.644
|
| 1232 |
+
- type: ndcg_at_100
|
| 1233 |
+
value: 42.594
|
| 1234 |
+
- type: ndcg_at_1000
|
| 1235 |
+
value: 44.352000000000004
|
| 1236 |
+
- type: ndcg_at_3
|
| 1237 |
+
value: 34.199
|
| 1238 |
+
- type: ndcg_at_5
|
| 1239 |
+
value: 36.573
|
| 1240 |
+
- type: precision_at_1
|
| 1241 |
+
value: 27.933000000000003
|
| 1242 |
+
- type: precision_at_10
|
| 1243 |
+
value: 5.603000000000001
|
| 1244 |
+
- type: precision_at_100
|
| 1245 |
+
value: 0.773
|
| 1246 |
+
- type: precision_at_1000
|
| 1247 |
+
value: 0.094
|
| 1248 |
+
- type: precision_at_3
|
| 1249 |
+
value: 14.171
|
| 1250 |
+
- type: precision_at_5
|
| 1251 |
+
value: 9.786999999999999
|
| 1252 |
+
- type: recall_at_1
|
| 1253 |
+
value: 25.801000000000002
|
| 1254 |
+
- type: recall_at_10
|
| 1255 |
+
value: 50.876
|
| 1256 |
+
- type: recall_at_100
|
| 1257 |
+
value: 69.253
|
| 1258 |
+
- type: recall_at_1000
|
| 1259 |
+
value: 82.907
|
| 1260 |
+
- type: recall_at_3
|
| 1261 |
+
value: 38.879000000000005
|
| 1262 |
+
- type: recall_at_5
|
| 1263 |
+
value: 44.651999999999994
|
| 1264 |
+
- task:
|
| 1265 |
+
type: Retrieval
|
| 1266 |
+
dataset:
|
| 1267 |
+
type: fiqa
|
| 1268 |
+
name: MTEB FiQA2018
|
| 1269 |
+
config: default
|
| 1270 |
+
split: test
|
| 1271 |
+
metrics:
|
| 1272 |
+
- type: map_at_1
|
| 1273 |
+
value: 9.142
|
| 1274 |
+
- type: map_at_10
|
| 1275 |
+
value: 13.841999999999999
|
| 1276 |
+
- type: map_at_100
|
| 1277 |
+
value: 14.960999999999999
|
| 1278 |
+
- type: map_at_1000
|
| 1279 |
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value: 15.187000000000001
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value: 11.966000000000001
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| 1283 |
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value: 12.921
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| 1284 |
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| 1285 |
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value: 18.364
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| 1286 |
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| 1287 |
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value: 18.590999999999998
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| 1288 |
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| 1289 |
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value: 24.153
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| 1290 |
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| 1291 |
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value: 29.104000000000003
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| 1292 |
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value: 16.323
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| 1294 |
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| 1295 |
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value: 17.000999999999998
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| 1296 |
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| 1297 |
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value: 18.364
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| 1298 |
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|
| 1299 |
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value: 5.216
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| 1300 |
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| 1301 |
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value: 1.09
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| 1302 |
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| 1303 |
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value: 0.193
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| 1304 |
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| 1305 |
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value: 10.751
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| 1306 |
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|
| 1307 |
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value: 7.932
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| 1308 |
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- type: recall_at_1
|
| 1309 |
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value: 9.142
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| 1310 |
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|
| 1311 |
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value: 22.747
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| 1312 |
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| 1313 |
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value: 44.585
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| 1314 |
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| 1315 |
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value: 75.481
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| 1316 |
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| 1317 |
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value: 14.602
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| 1318 |
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|
| 1319 |
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value: 17.957
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| 1320 |
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|
| 1321 |
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type: Retrieval
|
| 1322 |
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dataset:
|
| 1323 |
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type: hotpotqa
|
| 1324 |
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name: MTEB HotpotQA
|
| 1325 |
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config: default
|
| 1326 |
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split: test
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| 1327 |
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metrics:
|
| 1328 |
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- type: map_at_1
|
| 1329 |
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value: 18.677
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| 1330 |
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| 1331 |
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value: 26.616
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| 1332 |
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| 1333 |
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value: 27.605
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| 1334 |
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| 1335 |
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value: 27.711999999999996
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| 1336 |
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| 1337 |
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value: 24.396
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| 1338 |
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| 1339 |
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value: 25.627
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| 1340 |
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| 1341 |
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value: 37.352999999999994
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| 1342 |
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| 1343 |
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value: 33.995
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| 1344 |
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| 1345 |
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value: 38.423
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| 1346 |
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| 1347 |
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value: 40.947
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| 1348 |
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| 1349 |
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value: 29.885
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| 1350 |
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| 1351 |
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value: 31.874999999999996
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| 1352 |
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value: 37.352999999999994
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| 1355 |
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value: 7.539999999999999
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| 1356 |
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value: 1.107
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| 1358 |
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|
| 1359 |
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value: 0.145
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| 1360 |
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|
| 1361 |
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value: 18.938
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| 1362 |
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|
| 1363 |
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value: 12.943
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| 1364 |
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- type: recall_at_1
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| 1365 |
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value: 18.677
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| 1366 |
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- type: recall_at_10
|
| 1367 |
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value: 37.698
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| 1368 |
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- type: recall_at_100
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| 1369 |
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value: 55.354000000000006
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| 1370 |
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- type: recall_at_1000
|
| 1371 |
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value: 72.255
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| 1372 |
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- type: recall_at_3
|
| 1373 |
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value: 28.406
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| 1374 |
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- type: recall_at_5
|
| 1375 |
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value: 32.357
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| 1376 |
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|
| 1377 |
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type: Classification
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| 1378 |
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dataset:
|
| 1379 |
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type: mteb/imdb
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| 1380 |
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name: MTEB ImdbClassification
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| 1381 |
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config: default
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| 1382 |
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split: test
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| 1383 |
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metrics:
|
| 1384 |
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- type: accuracy
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| 1385 |
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value: 74.3292
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| 1386 |
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- type: ap
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| 1387 |
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value: 68.30186110189658
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| 1389 |
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value: 74.20709636944783
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| 1390 |
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|
| 1391 |
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type: Retrieval
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| 1392 |
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dataset:
|
| 1393 |
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type: msmarco
|
| 1394 |
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name: MTEB MSMARCO
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| 1395 |
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config: default
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| 1396 |
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split: validation
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| 1397 |
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metrics:
|
| 1398 |
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|
| 1399 |
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value: 6.889000000000001
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| 1400 |
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| 1401 |
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value: 12.321
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| 1402 |
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| 1403 |
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value: 13.416
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| 1404 |
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| 1405 |
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value: 13.525
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| 1406 |
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| 1407 |
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value: 10.205
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| 1409 |
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value: 11.342
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| 1410 |
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| 1411 |
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| 1412 |
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| 1413 |
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value: 15.827
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| 1414 |
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| 1415 |
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value: 21.72
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| 1416 |
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| 1417 |
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value: 24.836
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| 1418 |
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| 1419 |
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value: 11.393
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| 1420 |
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| 1421 |
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value: 13.462
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| 1422 |
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| 1423 |
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value: 7.092
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| 1424 |
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| 1425 |
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value: 2.7969999999999997
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| 1426 |
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| 1427 |
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value: 0.583
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| 1428 |
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| 1429 |
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value: 0.08499999999999999
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| 1431 |
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value: 5.019
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| 1432 |
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| 1433 |
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value: 4.06
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| 1434 |
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| 1435 |
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value: 6.889000000000001
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| 1436 |
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| 1437 |
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value: 26.791999999999998
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| 1438 |
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- type: recall_at_100
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| 1439 |
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value: 55.371
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| 1440 |
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- type: recall_at_1000
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| 1441 |
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value: 80.12899999999999
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| 1442 |
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- type: recall_at_3
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| 1443 |
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value: 14.573
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| 1444 |
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- type: recall_at_5
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| 1445 |
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value: 19.557
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| 1446 |
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|
| 1447 |
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type: Classification
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| 1448 |
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dataset:
|
| 1449 |
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type: mteb/mtop_domain
|
| 1450 |
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name: MTEB MTOPDomainClassification (en)
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| 1451 |
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config: en
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| 1452 |
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split: test
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| 1453 |
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metrics:
|
| 1454 |
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- type: accuracy
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| 1455 |
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value: 89.6374829001368
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| 1456 |
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| 1457 |
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value: 89.20878379358307
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| 1458 |
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| 1459 |
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type: Classification
|
| 1460 |
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dataset:
|
| 1461 |
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type: mteb/mtop_domain
|
| 1462 |
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name: MTEB MTOPDomainClassification (de)
|
| 1463 |
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config: de
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| 1464 |
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split: test
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| 1465 |
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metrics:
|
| 1466 |
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- type: accuracy
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| 1467 |
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value: 84.54212454212454
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| 1468 |
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| 1469 |
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value: 82.81080100037023
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| 1470 |
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| 1471 |
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type: Classification
|
| 1472 |
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dataset:
|
| 1473 |
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type: mteb/mtop_domain
|
| 1474 |
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name: MTEB MTOPDomainClassification (es)
|
| 1475 |
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config: es
|
| 1476 |
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split: test
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| 1477 |
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metrics:
|
| 1478 |
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| 1479 |
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value: 86.46430953969313
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| 1480 |
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| 1481 |
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value: 86.00019824223267
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| 1482 |
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| 1483 |
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type: Classification
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| 1484 |
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dataset:
|
| 1485 |
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type: mteb/mtop_domain
|
| 1486 |
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name: MTEB MTOPDomainClassification (fr)
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| 1487 |
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config: fr
|
| 1488 |
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split: test
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| 1489 |
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|
| 1490 |
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| 1491 |
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value: 81.31850923896022
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| 1492 |
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| 1494 |
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| 1495 |
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type: Classification
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| 1496 |
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dataset:
|
| 1497 |
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type: mteb/mtop_domain
|
| 1498 |
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name: MTEB MTOPDomainClassification (hi)
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| 1499 |
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config: hi
|
| 1500 |
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split: test
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| 1501 |
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|
| 1502 |
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| 1503 |
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value: 58.23234134098243
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| 1504 |
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| 1506 |
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| 1507 |
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type: Classification
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| 1508 |
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dataset:
|
| 1509 |
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type: mteb/mtop_domain
|
| 1510 |
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name: MTEB MTOPDomainClassification (th)
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| 1511 |
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config: th
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| 1512 |
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split: test
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| 1513 |
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| 1514 |
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| 1515 |
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value: 72.28571428571429
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| 1516 |
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| 1518 |
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| 1519 |
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| 1520 |
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dataset:
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| 1521 |
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type: mteb/mtop_intent
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| 1522 |
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name: MTEB MTOPIntentClassification (en)
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| 1523 |
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config: en
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| 1524 |
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split: test
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| 1525 |
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| 1526 |
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| 1527 |
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| 1528 |
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| 1531 |
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| 1532 |
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dataset:
|
| 1533 |
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type: mteb/mtop_intent
|
| 1534 |
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name: MTEB MTOPIntentClassification (de)
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| 1535 |
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config: de
|
| 1536 |
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split: test
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| 1537 |
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metrics:
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| 1538 |
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| 1539 |
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value: 60.521273598196665
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value: 42.70492970339204
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dataset:
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| 1545 |
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type: mteb/mtop_intent
|
| 1546 |
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name: MTEB MTOPIntentClassification (es)
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| 1547 |
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config: es
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| 1548 |
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split: test
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| 1549 |
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| 1550 |
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| 1551 |
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| 1555 |
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| 1556 |
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dataset:
|
| 1557 |
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type: mteb/mtop_intent
|
| 1558 |
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name: MTEB MTOPIntentClassification (fr)
|
| 1559 |
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config: fr
|
| 1560 |
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split: test
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| 1561 |
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| 1562 |
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| 1563 |
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| 1567 |
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dataset:
|
| 1569 |
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type: mteb/mtop_intent
|
| 1570 |
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name: MTEB MTOPIntentClassification (hi)
|
| 1571 |
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config: hi
|
| 1572 |
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split: test
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| 1573 |
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| 1574 |
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| 1575 |
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| 1579 |
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dataset:
|
| 1581 |
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type: mteb/mtop_intent
|
| 1582 |
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name: MTEB MTOPIntentClassification (th)
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| 1583 |
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config: th
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| 1584 |
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split: test
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| 1585 |
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| 1591 |
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type: Classification
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| 1592 |
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dataset:
|
| 1593 |
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type: mteb/amazon_massive_intent
|
| 1594 |
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name: MTEB MassiveIntentClassification (en)
|
| 1595 |
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config: en
|
| 1596 |
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split: test
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| 1597 |
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| 1598 |
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| 1600 |
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| 1603 |
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| 1604 |
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dataset:
|
| 1605 |
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type: mteb/amazon_massive_scenario
|
| 1606 |
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name: MTEB MassiveScenarioClassification (en)
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| 1607 |
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config: en
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| 1608 |
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split: test
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| 1609 |
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| 1610 |
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| 1611 |
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| 1615 |
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| 1616 |
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dataset:
|
| 1617 |
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type: mteb/medrxiv-clustering-p2p
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| 1618 |
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name: MTEB MedrxivClusteringP2P
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| 1619 |
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config: default
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| 1620 |
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split: test
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| 1621 |
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| 1623 |
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value: 30.327566856300813
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| 1626 |
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dataset:
|
| 1627 |
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type: mteb/medrxiv-clustering-s2s
|
| 1628 |
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name: MTEB MedrxivClusteringS2S
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| 1629 |
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config: default
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| 1630 |
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split: test
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| 1631 |
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| 1632 |
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| 1633 |
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| 1635 |
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dataset:
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| 1637 |
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type: mteb/mind_small
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| 1638 |
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name: MTEB MindSmallReranking
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| 1639 |
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config: default
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| 1640 |
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split: test
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| 1641 |
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value: 31.11041256752524
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dataset:
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type: nfcorpus
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| 1650 |
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name: MTEB NFCorpus
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| 1651 |
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| 1652 |
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split: test
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| 1653 |
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metrics:
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value: 3.527
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| 1684 |
+
- type: precision_at_1000
|
| 1685 |
+
value: 1.989
|
| 1686 |
+
- type: precision_at_3
|
| 1687 |
+
value: 30.857
|
| 1688 |
+
- type: precision_at_5
|
| 1689 |
+
value: 27.307
|
| 1690 |
+
- type: recall_at_1
|
| 1691 |
+
value: 3.527
|
| 1692 |
+
- type: recall_at_10
|
| 1693 |
+
value: 14.015
|
| 1694 |
+
- type: recall_at_100
|
| 1695 |
+
value: 28.402
|
| 1696 |
+
- type: recall_at_1000
|
| 1697 |
+
value: 59.795
|
| 1698 |
+
- type: recall_at_3
|
| 1699 |
+
value: 7.5969999999999995
|
| 1700 |
+
- type: recall_at_5
|
| 1701 |
+
value: 10.641
|
| 1702 |
+
- task:
|
| 1703 |
+
type: Retrieval
|
| 1704 |
+
dataset:
|
| 1705 |
+
type: nq
|
| 1706 |
+
name: MTEB NQ
|
| 1707 |
+
config: default
|
| 1708 |
+
split: test
|
| 1709 |
+
metrics:
|
| 1710 |
+
- type: map_at_1
|
| 1711 |
+
value: 11.631
|
| 1712 |
+
- type: map_at_10
|
| 1713 |
+
value: 19.532
|
| 1714 |
+
- type: map_at_100
|
| 1715 |
+
value: 20.821
|
| 1716 |
+
- type: map_at_1000
|
| 1717 |
+
value: 20.910999999999998
|
| 1718 |
+
- type: map_at_3
|
| 1719 |
+
value: 16.597
|
| 1720 |
+
- type: map_at_5
|
| 1721 |
+
value: 18.197
|
| 1722 |
+
- type: ndcg_at_1
|
| 1723 |
+
value: 13.413
|
| 1724 |
+
- type: ndcg_at_10
|
| 1725 |
+
value: 24.628
|
| 1726 |
+
- type: ndcg_at_100
|
| 1727 |
+
value: 30.883
|
| 1728 |
+
- type: ndcg_at_1000
|
| 1729 |
+
value: 33.216
|
| 1730 |
+
- type: ndcg_at_3
|
| 1731 |
+
value: 18.697
|
| 1732 |
+
- type: ndcg_at_5
|
| 1733 |
+
value: 21.501
|
| 1734 |
+
- type: precision_at_1
|
| 1735 |
+
value: 13.413
|
| 1736 |
+
- type: precision_at_10
|
| 1737 |
+
value: 4.571
|
| 1738 |
+
- type: precision_at_100
|
| 1739 |
+
value: 0.812
|
| 1740 |
+
- type: precision_at_1000
|
| 1741 |
+
value: 0.10300000000000001
|
| 1742 |
+
- type: precision_at_3
|
| 1743 |
+
value: 8.845
|
| 1744 |
+
- type: precision_at_5
|
| 1745 |
+
value: 6.889000000000001
|
| 1746 |
+
- type: recall_at_1
|
| 1747 |
+
value: 11.631
|
| 1748 |
+
- type: recall_at_10
|
| 1749 |
+
value: 38.429
|
| 1750 |
+
- type: recall_at_100
|
| 1751 |
+
value: 67.009
|
| 1752 |
+
- type: recall_at_1000
|
| 1753 |
+
value: 84.796
|
| 1754 |
+
- type: recall_at_3
|
| 1755 |
+
value: 22.74
|
| 1756 |
+
- type: recall_at_5
|
| 1757 |
+
value: 29.266
|
| 1758 |
+
- task:
|
| 1759 |
+
type: Retrieval
|
| 1760 |
+
dataset:
|
| 1761 |
+
type: quora
|
| 1762 |
+
name: MTEB QuoraRetrieval
|
| 1763 |
+
config: default
|
| 1764 |
+
split: test
|
| 1765 |
+
metrics:
|
| 1766 |
+
- type: map_at_1
|
| 1767 |
+
value: 66.64
|
| 1768 |
+
- type: map_at_10
|
| 1769 |
+
value: 80.394
|
| 1770 |
+
- type: map_at_100
|
| 1771 |
+
value: 81.099
|
| 1772 |
+
- type: map_at_1000
|
| 1773 |
+
value: 81.122
|
| 1774 |
+
- type: map_at_3
|
| 1775 |
+
value: 77.289
|
| 1776 |
+
- type: map_at_5
|
| 1777 |
+
value: 79.25999999999999
|
| 1778 |
+
- type: ndcg_at_1
|
| 1779 |
+
value: 76.85
|
| 1780 |
+
- type: ndcg_at_10
|
| 1781 |
+
value: 84.68
|
| 1782 |
+
- type: ndcg_at_100
|
| 1783 |
+
value: 86.311
|
| 1784 |
+
- type: ndcg_at_1000
|
| 1785 |
+
value: 86.49900000000001
|
| 1786 |
+
- type: ndcg_at_3
|
| 1787 |
+
value: 81.295
|
| 1788 |
+
- type: ndcg_at_5
|
| 1789 |
+
value: 83.199
|
| 1790 |
+
- type: precision_at_1
|
| 1791 |
+
value: 76.85
|
| 1792 |
+
- type: precision_at_10
|
| 1793 |
+
value: 12.928999999999998
|
| 1794 |
+
- type: precision_at_100
|
| 1795 |
+
value: 1.51
|
| 1796 |
+
- type: precision_at_1000
|
| 1797 |
+
value: 0.156
|
| 1798 |
+
- type: precision_at_3
|
| 1799 |
+
value: 35.557
|
| 1800 |
+
- type: precision_at_5
|
| 1801 |
+
value: 23.576
|
| 1802 |
+
- type: recall_at_1
|
| 1803 |
+
value: 66.64
|
| 1804 |
+
- type: recall_at_10
|
| 1805 |
+
value: 93.059
|
| 1806 |
+
- type: recall_at_100
|
| 1807 |
+
value: 98.922
|
| 1808 |
+
- type: recall_at_1000
|
| 1809 |
+
value: 99.883
|
| 1810 |
+
- type: recall_at_3
|
| 1811 |
+
value: 83.49499999999999
|
| 1812 |
+
- type: recall_at_5
|
| 1813 |
+
value: 88.729
|
| 1814 |
+
- task:
|
| 1815 |
+
type: Clustering
|
| 1816 |
+
dataset:
|
| 1817 |
+
type: mteb/reddit-clustering
|
| 1818 |
+
name: MTEB RedditClustering
|
| 1819 |
+
config: default
|
| 1820 |
+
split: test
|
| 1821 |
+
metrics:
|
| 1822 |
+
- type: v_measure
|
| 1823 |
+
value: 42.17131361041068
|
| 1824 |
+
- task:
|
| 1825 |
+
type: Clustering
|
| 1826 |
+
dataset:
|
| 1827 |
+
type: mteb/reddit-clustering-p2p
|
| 1828 |
+
name: MTEB RedditClusteringP2P
|
| 1829 |
+
config: default
|
| 1830 |
+
split: test
|
| 1831 |
+
metrics:
|
| 1832 |
+
- type: v_measure
|
| 1833 |
+
value: 48.01815621479994
|
| 1834 |
+
- task:
|
| 1835 |
+
type: Retrieval
|
| 1836 |
+
dataset:
|
| 1837 |
+
type: scidocs
|
| 1838 |
+
name: MTEB SCIDOCS
|
| 1839 |
+
config: default
|
| 1840 |
+
split: test
|
| 1841 |
+
metrics:
|
| 1842 |
+
- type: map_at_1
|
| 1843 |
+
value: 3.198
|
| 1844 |
+
- type: map_at_10
|
| 1845 |
+
value: 7.550999999999999
|
| 1846 |
+
- type: map_at_100
|
| 1847 |
+
value: 9.232
|
| 1848 |
+
- type: map_at_1000
|
| 1849 |
+
value: 9.51
|
| 1850 |
+
- type: map_at_3
|
| 1851 |
+
value: 5.2940000000000005
|
| 1852 |
+
- type: map_at_5
|
| 1853 |
+
value: 6.343999999999999
|
| 1854 |
+
- type: ndcg_at_1
|
| 1855 |
+
value: 15.8
|
| 1856 |
+
- type: ndcg_at_10
|
| 1857 |
+
value: 13.553999999999998
|
| 1858 |
+
- type: ndcg_at_100
|
| 1859 |
+
value: 20.776
|
| 1860 |
+
- type: ndcg_at_1000
|
| 1861 |
+
value: 26.204
|
| 1862 |
+
- type: ndcg_at_3
|
| 1863 |
+
value: 12.306000000000001
|
| 1864 |
+
- type: ndcg_at_5
|
| 1865 |
+
value: 10.952
|
| 1866 |
+
- type: precision_at_1
|
| 1867 |
+
value: 15.8
|
| 1868 |
+
- type: precision_at_10
|
| 1869 |
+
value: 7.180000000000001
|
| 1870 |
+
- type: precision_at_100
|
| 1871 |
+
value: 1.762
|
| 1872 |
+
- type: precision_at_1000
|
| 1873 |
+
value: 0.307
|
| 1874 |
+
- type: precision_at_3
|
| 1875 |
+
value: 11.333
|
| 1876 |
+
- type: precision_at_5
|
| 1877 |
+
value: 9.62
|
| 1878 |
+
- type: recall_at_1
|
| 1879 |
+
value: 3.198
|
| 1880 |
+
- type: recall_at_10
|
| 1881 |
+
value: 14.575
|
| 1882 |
+
- type: recall_at_100
|
| 1883 |
+
value: 35.758
|
| 1884 |
+
- type: recall_at_1000
|
| 1885 |
+
value: 62.317
|
| 1886 |
+
- type: recall_at_3
|
| 1887 |
+
value: 6.922000000000001
|
| 1888 |
+
- type: recall_at_5
|
| 1889 |
+
value: 9.767000000000001
|
| 1890 |
+
- task:
|
| 1891 |
+
type: STS
|
| 1892 |
+
dataset:
|
| 1893 |
+
type: mteb/sickr-sts
|
| 1894 |
+
name: MTEB SICK-R
|
| 1895 |
+
config: default
|
| 1896 |
+
split: test
|
| 1897 |
+
metrics:
|
| 1898 |
+
- type: cos_sim_pearson
|
| 1899 |
+
value: 84.5217161312271
|
| 1900 |
+
- type: cos_sim_spearman
|
| 1901 |
+
value: 79.58562467776268
|
| 1902 |
+
- type: euclidean_pearson
|
| 1903 |
+
value: 76.69364353942403
|
| 1904 |
+
- type: euclidean_spearman
|
| 1905 |
+
value: 74.68959282070473
|
| 1906 |
+
- type: manhattan_pearson
|
| 1907 |
+
value: 76.81159265133732
|
| 1908 |
+
- type: manhattan_spearman
|
| 1909 |
+
value: 74.7519444048176
|
| 1910 |
+
- task:
|
| 1911 |
+
type: STS
|
| 1912 |
+
dataset:
|
| 1913 |
+
type: mteb/sts12-sts
|
| 1914 |
+
name: MTEB STS12
|
| 1915 |
+
config: default
|
| 1916 |
+
split: test
|
| 1917 |
+
metrics:
|
| 1918 |
+
- type: cos_sim_pearson
|
| 1919 |
+
value: 83.70403706922605
|
| 1920 |
+
- type: cos_sim_spearman
|
| 1921 |
+
value: 74.28502198729447
|
| 1922 |
+
- type: euclidean_pearson
|
| 1923 |
+
value: 83.32719404608066
|
| 1924 |
+
- type: euclidean_spearman
|
| 1925 |
+
value: 75.92189433460788
|
| 1926 |
+
- type: manhattan_pearson
|
| 1927 |
+
value: 83.35841543005293
|
| 1928 |
+
- type: manhattan_spearman
|
| 1929 |
+
value: 75.94458615451978
|
| 1930 |
+
- task:
|
| 1931 |
+
type: STS
|
| 1932 |
+
dataset:
|
| 1933 |
+
type: mteb/sts13-sts
|
| 1934 |
+
name: MTEB STS13
|
| 1935 |
+
config: default
|
| 1936 |
+
split: test
|
| 1937 |
+
metrics:
|
| 1938 |
+
- type: cos_sim_pearson
|
| 1939 |
+
value: 84.94127878986795
|
| 1940 |
+
- type: cos_sim_spearman
|
| 1941 |
+
value: 85.35148434923192
|
| 1942 |
+
- type: euclidean_pearson
|
| 1943 |
+
value: 81.71127467071571
|
| 1944 |
+
- type: euclidean_spearman
|
| 1945 |
+
value: 82.88240481546771
|
| 1946 |
+
- type: manhattan_pearson
|
| 1947 |
+
value: 81.72826221967252
|
| 1948 |
+
- type: manhattan_spearman
|
| 1949 |
+
value: 82.90725064625128
|
| 1950 |
+
- task:
|
| 1951 |
+
type: STS
|
| 1952 |
+
dataset:
|
| 1953 |
+
type: mteb/sts14-sts
|
| 1954 |
+
name: MTEB STS14
|
| 1955 |
+
config: default
|
| 1956 |
+
split: test
|
| 1957 |
+
metrics:
|
| 1958 |
+
- type: cos_sim_pearson
|
| 1959 |
+
value: 83.1474704168523
|
| 1960 |
+
- type: cos_sim_spearman
|
| 1961 |
+
value: 79.20612995350827
|
| 1962 |
+
- type: euclidean_pearson
|
| 1963 |
+
value: 78.85993329596555
|
| 1964 |
+
- type: euclidean_spearman
|
| 1965 |
+
value: 78.91956572744715
|
| 1966 |
+
- type: manhattan_pearson
|
| 1967 |
+
value: 78.89999720522347
|
| 1968 |
+
- type: manhattan_spearman
|
| 1969 |
+
value: 78.93956842550107
|
| 1970 |
+
- task:
|
| 1971 |
+
type: STS
|
| 1972 |
+
dataset:
|
| 1973 |
+
type: mteb/sts15-sts
|
| 1974 |
+
name: MTEB STS15
|
| 1975 |
+
config: default
|
| 1976 |
+
split: test
|
| 1977 |
+
metrics:
|
| 1978 |
+
- type: cos_sim_pearson
|
| 1979 |
+
value: 84.81255514055894
|
| 1980 |
+
- type: cos_sim_spearman
|
| 1981 |
+
value: 85.5217140762934
|
| 1982 |
+
- type: euclidean_pearson
|
| 1983 |
+
value: 82.15024353784499
|
| 1984 |
+
- type: euclidean_spearman
|
| 1985 |
+
value: 83.04155334389833
|
| 1986 |
+
- type: manhattan_pearson
|
| 1987 |
+
value: 82.18598945053624
|
| 1988 |
+
- type: manhattan_spearman
|
| 1989 |
+
value: 83.07248357693301
|
| 1990 |
+
- task:
|
| 1991 |
+
type: STS
|
| 1992 |
+
dataset:
|
| 1993 |
+
type: mteb/sts16-sts
|
| 1994 |
+
name: MTEB STS16
|
| 1995 |
+
config: default
|
| 1996 |
+
split: test
|
| 1997 |
+
metrics:
|
| 1998 |
+
- type: cos_sim_pearson
|
| 1999 |
+
value: 80.63248465157822
|
| 2000 |
+
- type: cos_sim_spearman
|
| 2001 |
+
value: 82.53853238521991
|
| 2002 |
+
- type: euclidean_pearson
|
| 2003 |
+
value: 78.33936863828221
|
| 2004 |
+
- type: euclidean_spearman
|
| 2005 |
+
value: 79.16305579487414
|
| 2006 |
+
- type: manhattan_pearson
|
| 2007 |
+
value: 78.3888359870894
|
| 2008 |
+
- type: manhattan_spearman
|
| 2009 |
+
value: 79.18504473136467
|
| 2010 |
+
- task:
|
| 2011 |
+
type: STS
|
| 2012 |
+
dataset:
|
| 2013 |
+
type: mteb/sts17-crosslingual-sts
|
| 2014 |
+
name: MTEB STS17 (en-en)
|
| 2015 |
+
config: en-en
|
| 2016 |
+
split: test
|
| 2017 |
+
metrics:
|
| 2018 |
+
- type: cos_sim_pearson
|
| 2019 |
+
value: 90.09066290639687
|
| 2020 |
+
- type: cos_sim_spearman
|
| 2021 |
+
value: 90.43893699357069
|
| 2022 |
+
- type: euclidean_pearson
|
| 2023 |
+
value: 82.39520777222396
|
| 2024 |
+
- type: euclidean_spearman
|
| 2025 |
+
value: 81.23948185395952
|
| 2026 |
+
- type: manhattan_pearson
|
| 2027 |
+
value: 82.35529784653383
|
| 2028 |
+
- type: manhattan_spearman
|
| 2029 |
+
value: 81.12681522483975
|
| 2030 |
+
- task:
|
| 2031 |
+
type: STS
|
| 2032 |
+
dataset:
|
| 2033 |
+
type: mteb/sts22-crosslingual-sts
|
| 2034 |
+
name: MTEB STS22 (en)
|
| 2035 |
+
config: en
|
| 2036 |
+
split: test
|
| 2037 |
+
metrics:
|
| 2038 |
+
- type: cos_sim_pearson
|
| 2039 |
+
value: 63.52752323046846
|
| 2040 |
+
- type: cos_sim_spearman
|
| 2041 |
+
value: 63.19719780439462
|
| 2042 |
+
- type: euclidean_pearson
|
| 2043 |
+
value: 58.29085490641428
|
| 2044 |
+
- type: euclidean_spearman
|
| 2045 |
+
value: 58.975178656335046
|
| 2046 |
+
- type: manhattan_pearson
|
| 2047 |
+
value: 58.183542772416985
|
| 2048 |
+
- type: manhattan_spearman
|
| 2049 |
+
value: 59.190630462178994
|
| 2050 |
+
- task:
|
| 2051 |
+
type: STS
|
| 2052 |
+
dataset:
|
| 2053 |
+
type: mteb/stsbenchmark-sts
|
| 2054 |
+
name: MTEB STSBenchmark
|
| 2055 |
+
config: default
|
| 2056 |
+
split: test
|
| 2057 |
+
metrics:
|
| 2058 |
+
- type: cos_sim_pearson
|
| 2059 |
+
value: 85.45100366635687
|
| 2060 |
+
- type: cos_sim_spearman
|
| 2061 |
+
value: 85.66816193002651
|
| 2062 |
+
- type: euclidean_pearson
|
| 2063 |
+
value: 81.87976731329091
|
| 2064 |
+
- type: euclidean_spearman
|
| 2065 |
+
value: 82.01382867690964
|
| 2066 |
+
- type: manhattan_pearson
|
| 2067 |
+
value: 81.88260155706726
|
| 2068 |
+
- type: manhattan_spearman
|
| 2069 |
+
value: 82.05258597906492
|
| 2070 |
+
- task:
|
| 2071 |
+
type: Reranking
|
| 2072 |
+
dataset:
|
| 2073 |
+
type: mteb/scidocs-reranking
|
| 2074 |
+
name: MTEB SciDocsRR
|
| 2075 |
+
config: default
|
| 2076 |
+
split: test
|
| 2077 |
+
metrics:
|
| 2078 |
+
- type: map
|
| 2079 |
+
value: 77.53549990038017
|
| 2080 |
+
- type: mrr
|
| 2081 |
+
value: 93.37474163454556
|
| 2082 |
+
- task:
|
| 2083 |
+
type: Retrieval
|
| 2084 |
+
dataset:
|
| 2085 |
+
type: scifact
|
| 2086 |
+
name: MTEB SciFact
|
| 2087 |
+
config: default
|
| 2088 |
+
split: test
|
| 2089 |
+
metrics:
|
| 2090 |
+
- type: map_at_1
|
| 2091 |
+
value: 31.167
|
| 2092 |
+
- type: map_at_10
|
| 2093 |
+
value: 40.778
|
| 2094 |
+
- type: map_at_100
|
| 2095 |
+
value: 42.063
|
| 2096 |
+
- type: map_at_1000
|
| 2097 |
+
value: 42.103
|
| 2098 |
+
- type: map_at_3
|
| 2099 |
+
value: 37.12
|
| 2100 |
+
- type: map_at_5
|
| 2101 |
+
value: 39.205
|
| 2102 |
+
- type: ndcg_at_1
|
| 2103 |
+
value: 33.667
|
| 2104 |
+
- type: ndcg_at_10
|
| 2105 |
+
value: 46.662
|
| 2106 |
+
- type: ndcg_at_100
|
| 2107 |
+
value: 51.995999999999995
|
| 2108 |
+
- type: ndcg_at_1000
|
| 2109 |
+
value: 53.254999999999995
|
| 2110 |
+
- type: ndcg_at_3
|
| 2111 |
+
value: 39.397999999999996
|
| 2112 |
+
- type: ndcg_at_5
|
| 2113 |
+
value: 42.934
|
| 2114 |
+
- type: precision_at_1
|
| 2115 |
+
value: 33.667
|
| 2116 |
+
- type: precision_at_10
|
| 2117 |
+
value: 7.1
|
| 2118 |
+
- type: precision_at_100
|
| 2119 |
+
value: 0.993
|
| 2120 |
+
- type: precision_at_1000
|
| 2121 |
+
value: 0.11
|
| 2122 |
+
- type: precision_at_3
|
| 2123 |
+
value: 16.111
|
| 2124 |
+
- type: precision_at_5
|
| 2125 |
+
value: 11.600000000000001
|
| 2126 |
+
- type: recall_at_1
|
| 2127 |
+
value: 31.167
|
| 2128 |
+
- type: recall_at_10
|
| 2129 |
+
value: 63.744
|
| 2130 |
+
- type: recall_at_100
|
| 2131 |
+
value: 87.156
|
| 2132 |
+
- type: recall_at_1000
|
| 2133 |
+
value: 97.556
|
| 2134 |
+
- type: recall_at_3
|
| 2135 |
+
value: 44.0
|
| 2136 |
+
- type: recall_at_5
|
| 2137 |
+
value: 52.556000000000004
|
| 2138 |
+
- task:
|
| 2139 |
+
type: PairClassification
|
| 2140 |
+
dataset:
|
| 2141 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
| 2142 |
+
name: MTEB SprintDuplicateQuestions
|
| 2143 |
+
config: default
|
| 2144 |
+
split: test
|
| 2145 |
+
metrics:
|
| 2146 |
+
- type: cos_sim_accuracy
|
| 2147 |
+
value: 99.55148514851486
|
| 2148 |
+
- type: cos_sim_ap
|
| 2149 |
+
value: 80.535236573428
|
| 2150 |
+
- type: cos_sim_f1
|
| 2151 |
+
value: 75.01331912626532
|
| 2152 |
+
- type: cos_sim_precision
|
| 2153 |
+
value: 80.27366020524515
|
| 2154 |
+
- type: cos_sim_recall
|
| 2155 |
+
value: 70.39999999999999
|
| 2156 |
+
- type: dot_accuracy
|
| 2157 |
+
value: 99.04851485148515
|
| 2158 |
+
- type: dot_ap
|
| 2159 |
+
value: 28.505358821499726
|
| 2160 |
+
- type: dot_f1
|
| 2161 |
+
value: 36.36363636363637
|
| 2162 |
+
- type: dot_precision
|
| 2163 |
+
value: 37.160751565762006
|
| 2164 |
+
- type: dot_recall
|
| 2165 |
+
value: 35.6
|
| 2166 |
+
- type: euclidean_accuracy
|
| 2167 |
+
value: 99.4990099009901
|
| 2168 |
+
- type: euclidean_ap
|
| 2169 |
+
value: 74.95819047075476
|
| 2170 |
+
- type: euclidean_f1
|
| 2171 |
+
value: 71.15489874110564
|
| 2172 |
+
- type: euclidean_precision
|
| 2173 |
+
value: 78.59733978234583
|
| 2174 |
+
- type: euclidean_recall
|
| 2175 |
+
value: 65.0
|
| 2176 |
+
- type: manhattan_accuracy
|
| 2177 |
+
value: 99.50198019801981
|
| 2178 |
+
- type: manhattan_ap
|
| 2179 |
+
value: 75.02070096015086
|
| 2180 |
+
- type: manhattan_f1
|
| 2181 |
+
value: 71.20535714285712
|
| 2182 |
+
- type: manhattan_precision
|
| 2183 |
+
value: 80.55555555555556
|
| 2184 |
+
- type: manhattan_recall
|
| 2185 |
+
value: 63.800000000000004
|
| 2186 |
+
- type: max_accuracy
|
| 2187 |
+
value: 99.55148514851486
|
| 2188 |
+
- type: max_ap
|
| 2189 |
+
value: 80.535236573428
|
| 2190 |
+
- type: max_f1
|
| 2191 |
+
value: 75.01331912626532
|
| 2192 |
+
- task:
|
| 2193 |
+
type: Clustering
|
| 2194 |
+
dataset:
|
| 2195 |
+
type: mteb/stackexchange-clustering
|
| 2196 |
+
name: MTEB StackExchangeClustering
|
| 2197 |
+
config: default
|
| 2198 |
+
split: test
|
| 2199 |
+
metrics:
|
| 2200 |
+
- type: v_measure
|
| 2201 |
+
value: 54.13314692311623
|
| 2202 |
+
- task:
|
| 2203 |
+
type: Clustering
|
| 2204 |
+
dataset:
|
| 2205 |
+
type: mteb/stackexchange-clustering-p2p
|
| 2206 |
+
name: MTEB StackExchangeClusteringP2P
|
| 2207 |
+
config: default
|
| 2208 |
+
split: test
|
| 2209 |
+
metrics:
|
| 2210 |
+
- type: v_measure
|
| 2211 |
+
value: 31.115181648287145
|
| 2212 |
+
- task:
|
| 2213 |
+
type: Reranking
|
| 2214 |
+
dataset:
|
| 2215 |
+
type: mteb/stackoverflowdupquestions-reranking
|
| 2216 |
+
name: MTEB StackOverflowDupQuestions
|
| 2217 |
+
config: default
|
| 2218 |
+
split: test
|
| 2219 |
+
metrics:
|
| 2220 |
+
- type: map
|
| 2221 |
+
value: 44.771112666694336
|
| 2222 |
+
- type: mrr
|
| 2223 |
+
value: 45.30415764790765
|
| 2224 |
+
- task:
|
| 2225 |
+
type: Summarization
|
| 2226 |
+
dataset:
|
| 2227 |
+
type: mteb/summeval
|
| 2228 |
+
name: MTEB SummEval
|
| 2229 |
+
config: default
|
| 2230 |
+
split: test
|
| 2231 |
+
metrics:
|
| 2232 |
+
- type: cos_sim_pearson
|
| 2233 |
+
value: 30.849429597669374
|
| 2234 |
+
- type: cos_sim_spearman
|
| 2235 |
+
value: 30.384175038360194
|
| 2236 |
+
- type: dot_pearson
|
| 2237 |
+
value: 29.030383429536823
|
| 2238 |
+
- type: dot_spearman
|
| 2239 |
+
value: 28.03273624951732
|
| 2240 |
+
- task:
|
| 2241 |
+
type: Retrieval
|
| 2242 |
+
dataset:
|
| 2243 |
+
type: trec-covid
|
| 2244 |
+
name: MTEB TRECCOVID
|
| 2245 |
+
config: default
|
| 2246 |
+
split: test
|
| 2247 |
+
metrics:
|
| 2248 |
+
- type: map_at_1
|
| 2249 |
+
value: 0.19499999999999998
|
| 2250 |
+
- type: map_at_10
|
| 2251 |
+
value: 1.0959999999999999
|
| 2252 |
+
- type: map_at_100
|
| 2253 |
+
value: 5.726
|
| 2254 |
+
- type: map_at_1000
|
| 2255 |
+
value: 13.611999999999998
|
| 2256 |
+
- type: map_at_3
|
| 2257 |
+
value: 0.45399999999999996
|
| 2258 |
+
- type: map_at_5
|
| 2259 |
+
value: 0.67
|
| 2260 |
+
- type: ndcg_at_1
|
| 2261 |
+
value: 71.0
|
| 2262 |
+
- type: ndcg_at_10
|
| 2263 |
+
value: 55.352999999999994
|
| 2264 |
+
- type: ndcg_at_100
|
| 2265 |
+
value: 40.797
|
| 2266 |
+
- type: ndcg_at_1000
|
| 2267 |
+
value: 35.955999999999996
|
| 2268 |
+
- type: ndcg_at_3
|
| 2269 |
+
value: 63.263000000000005
|
| 2270 |
+
- type: ndcg_at_5
|
| 2271 |
+
value: 60.14000000000001
|
| 2272 |
+
- type: precision_at_1
|
| 2273 |
+
value: 78.0
|
| 2274 |
+
- type: precision_at_10
|
| 2275 |
+
value: 56.99999999999999
|
| 2276 |
+
- type: precision_at_100
|
| 2277 |
+
value: 41.199999999999996
|
| 2278 |
+
- type: precision_at_1000
|
| 2279 |
+
value: 16.154
|
| 2280 |
+
- type: precision_at_3
|
| 2281 |
+
value: 66.667
|
| 2282 |
+
- type: precision_at_5
|
| 2283 |
+
value: 62.8
|
| 2284 |
+
- type: recall_at_1
|
| 2285 |
+
value: 0.19499999999999998
|
| 2286 |
+
- type: recall_at_10
|
| 2287 |
+
value: 1.3639999999999999
|
| 2288 |
+
- type: recall_at_100
|
| 2289 |
+
value: 9.317
|
| 2290 |
+
- type: recall_at_1000
|
| 2291 |
+
value: 33.629999999999995
|
| 2292 |
+
- type: recall_at_3
|
| 2293 |
+
value: 0.49300000000000005
|
| 2294 |
+
- type: recall_at_5
|
| 2295 |
+
value: 0.756
|
| 2296 |
+
- task:
|
| 2297 |
+
type: Retrieval
|
| 2298 |
+
dataset:
|
| 2299 |
+
type: webis-touche2020
|
| 2300 |
+
name: MTEB Touche2020
|
| 2301 |
+
config: default
|
| 2302 |
+
split: test
|
| 2303 |
+
metrics:
|
| 2304 |
+
- type: map_at_1
|
| 2305 |
+
value: 1.335
|
| 2306 |
+
- type: map_at_10
|
| 2307 |
+
value: 6.293
|
| 2308 |
+
- type: map_at_100
|
| 2309 |
+
value: 10.928
|
| 2310 |
+
- type: map_at_1000
|
| 2311 |
+
value: 12.359
|
| 2312 |
+
- type: map_at_3
|
| 2313 |
+
value: 3.472
|
| 2314 |
+
- type: map_at_5
|
| 2315 |
+
value: 4.935
|
| 2316 |
+
- type: ndcg_at_1
|
| 2317 |
+
value: 19.387999999999998
|
| 2318 |
+
- type: ndcg_at_10
|
| 2319 |
+
value: 16.178
|
| 2320 |
+
- type: ndcg_at_100
|
| 2321 |
+
value: 28.149
|
| 2322 |
+
- type: ndcg_at_1000
|
| 2323 |
+
value: 39.845000000000006
|
| 2324 |
+
- type: ndcg_at_3
|
| 2325 |
+
value: 19.171
|
| 2326 |
+
- type: ndcg_at_5
|
| 2327 |
+
value: 17.864
|
| 2328 |
+
- type: precision_at_1
|
| 2329 |
+
value: 20.408
|
| 2330 |
+
- type: precision_at_10
|
| 2331 |
+
value: 14.49
|
| 2332 |
+
- type: precision_at_100
|
| 2333 |
+
value: 6.306000000000001
|
| 2334 |
+
- type: precision_at_1000
|
| 2335 |
+
value: 1.3860000000000001
|
| 2336 |
+
- type: precision_at_3
|
| 2337 |
+
value: 21.088
|
| 2338 |
+
- type: precision_at_5
|
| 2339 |
+
value: 18.367
|
| 2340 |
+
- type: recall_at_1
|
| 2341 |
+
value: 1.335
|
| 2342 |
+
- type: recall_at_10
|
| 2343 |
+
value: 10.825999999999999
|
| 2344 |
+
- type: recall_at_100
|
| 2345 |
+
value: 39.251000000000005
|
| 2346 |
+
- type: recall_at_1000
|
| 2347 |
+
value: 74.952
|
| 2348 |
+
- type: recall_at_3
|
| 2349 |
+
value: 4.9110000000000005
|
| 2350 |
+
- type: recall_at_5
|
| 2351 |
+
value: 7.312
|
| 2352 |
+
- task:
|
| 2353 |
+
type: Classification
|
| 2354 |
+
dataset:
|
| 2355 |
+
type: mteb/toxic_conversations_50k
|
| 2356 |
+
name: MTEB ToxicConversationsClassification
|
| 2357 |
+
config: default
|
| 2358 |
+
split: test
|
| 2359 |
+
metrics:
|
| 2360 |
+
- type: accuracy
|
| 2361 |
+
value: 69.93339999999999
|
| 2362 |
+
- type: ap
|
| 2363 |
+
value: 13.87476602492533
|
| 2364 |
+
- type: f1
|
| 2365 |
+
value: 53.867357615848555
|
| 2366 |
+
- task:
|
| 2367 |
+
type: Classification
|
| 2368 |
+
dataset:
|
| 2369 |
+
type: mteb/tweet_sentiment_extraction
|
| 2370 |
+
name: MTEB TweetSentimentExtractionClassification
|
| 2371 |
+
config: default
|
| 2372 |
+
split: test
|
| 2373 |
+
metrics:
|
| 2374 |
+
- type: accuracy
|
| 2375 |
+
value: 62.43916242218449
|
| 2376 |
+
- type: f1
|
| 2377 |
+
value: 62.870386304954685
|
| 2378 |
+
- task:
|
| 2379 |
+
type: Clustering
|
| 2380 |
+
dataset:
|
| 2381 |
+
type: mteb/twentynewsgroups-clustering
|
| 2382 |
+
name: MTEB TwentyNewsgroupsClustering
|
| 2383 |
+
config: default
|
| 2384 |
+
split: test
|
| 2385 |
+
metrics:
|
| 2386 |
+
- type: v_measure
|
| 2387 |
+
value: 37.202082549859796
|
| 2388 |
+
- task:
|
| 2389 |
+
type: PairClassification
|
| 2390 |
+
dataset:
|
| 2391 |
+
type: mteb/twittersemeval2015-pairclassification
|
| 2392 |
+
name: MTEB TwitterSemEval2015
|
| 2393 |
+
config: default
|
| 2394 |
+
split: test
|
| 2395 |
+
metrics:
|
| 2396 |
+
- type: cos_sim_accuracy
|
| 2397 |
+
value: 83.65023544137807
|
| 2398 |
+
- type: cos_sim_ap
|
| 2399 |
+
value: 65.99787692764193
|
| 2400 |
+
- type: cos_sim_f1
|
| 2401 |
+
value: 62.10650887573965
|
| 2402 |
+
- type: cos_sim_precision
|
| 2403 |
+
value: 56.30901287553648
|
| 2404 |
+
- type: cos_sim_recall
|
| 2405 |
+
value: 69.23482849604221
|
| 2406 |
+
- type: dot_accuracy
|
| 2407 |
+
value: 79.10830303391549
|
| 2408 |
+
- type: dot_ap
|
| 2409 |
+
value: 48.80109642320246
|
| 2410 |
+
- type: dot_f1
|
| 2411 |
+
value: 51.418744625967314
|
| 2412 |
+
- type: dot_precision
|
| 2413 |
+
value: 40.30253107683091
|
| 2414 |
+
- type: dot_recall
|
| 2415 |
+
value: 71.00263852242745
|
| 2416 |
+
- type: euclidean_accuracy
|
| 2417 |
+
value: 82.45812719794957
|
| 2418 |
+
- type: euclidean_ap
|
| 2419 |
+
value: 60.09969493259607
|
| 2420 |
+
- type: euclidean_f1
|
| 2421 |
+
value: 57.658573789246226
|
| 2422 |
+
- type: euclidean_precision
|
| 2423 |
+
value: 55.62913907284768
|
| 2424 |
+
- type: euclidean_recall
|
| 2425 |
+
value: 59.84168865435356
|
| 2426 |
+
- type: manhattan_accuracy
|
| 2427 |
+
value: 82.46408773916671
|
| 2428 |
+
- type: manhattan_ap
|
| 2429 |
+
value: 60.116199786815116
|
| 2430 |
+
- type: manhattan_f1
|
| 2431 |
+
value: 57.683903860160235
|
| 2432 |
+
- type: manhattan_precision
|
| 2433 |
+
value: 53.41726618705036
|
| 2434 |
+
- type: manhattan_recall
|
| 2435 |
+
value: 62.69129287598945
|
| 2436 |
+
- type: max_accuracy
|
| 2437 |
+
value: 83.65023544137807
|
| 2438 |
+
- type: max_ap
|
| 2439 |
+
value: 65.99787692764193
|
| 2440 |
+
- type: max_f1
|
| 2441 |
+
value: 62.10650887573965
|
| 2442 |
+
- task:
|
| 2443 |
+
type: PairClassification
|
| 2444 |
+
dataset:
|
| 2445 |
+
type: mteb/twitterurlcorpus-pairclassification
|
| 2446 |
+
name: MTEB TwitterURLCorpus
|
| 2447 |
+
config: default
|
| 2448 |
+
split: test
|
| 2449 |
+
metrics:
|
| 2450 |
+
- type: cos_sim_accuracy
|
| 2451 |
+
value: 88.34943920518494
|
| 2452 |
+
- type: cos_sim_ap
|
| 2453 |
+
value: 84.5428891020442
|
| 2454 |
+
- type: cos_sim_f1
|
| 2455 |
+
value: 77.09709933923172
|
| 2456 |
+
- type: cos_sim_precision
|
| 2457 |
+
value: 74.83150952967607
|
| 2458 |
+
- type: cos_sim_recall
|
| 2459 |
+
value: 79.50415768401602
|
| 2460 |
+
- type: dot_accuracy
|
| 2461 |
+
value: 84.53448208949432
|
| 2462 |
+
- type: dot_ap
|
| 2463 |
+
value: 73.96328242371995
|
| 2464 |
+
- type: dot_f1
|
| 2465 |
+
value: 70.00553786515299
|
| 2466 |
+
- type: dot_precision
|
| 2467 |
+
value: 63.58777665995976
|
| 2468 |
+
- type: dot_recall
|
| 2469 |
+
value: 77.86418232214352
|
| 2470 |
+
- type: euclidean_accuracy
|
| 2471 |
+
value: 86.87662514068381
|
| 2472 |
+
- type: euclidean_ap
|
| 2473 |
+
value: 81.45499631520235
|
| 2474 |
+
- type: euclidean_f1
|
| 2475 |
+
value: 73.46567109816063
|
| 2476 |
+
- type: euclidean_precision
|
| 2477 |
+
value: 69.71037533697381
|
| 2478 |
+
- type: euclidean_recall
|
| 2479 |
+
value: 77.6485987064983
|
| 2480 |
+
- type: manhattan_accuracy
|
| 2481 |
+
value: 86.88244654014825
|
| 2482 |
+
- type: manhattan_ap
|
| 2483 |
+
value: 81.47180273946366
|
| 2484 |
+
- type: manhattan_f1
|
| 2485 |
+
value: 73.44624393136418
|
| 2486 |
+
- type: manhattan_precision
|
| 2487 |
+
value: 70.80385852090032
|
| 2488 |
+
- type: manhattan_recall
|
| 2489 |
+
value: 76.29350169387126
|
| 2490 |
+
- type: max_accuracy
|
| 2491 |
+
value: 88.34943920518494
|
| 2492 |
+
- type: max_ap
|
| 2493 |
+
value: 84.5428891020442
|
| 2494 |
+
- type: max_f1
|
| 2495 |
+
value: 77.09709933923172
|
| 2496 |
---
|
| 2497 |
|
| 2498 |
+
# SGPT-5.8B-weightedmean-msmarco-specb-bitfit
|
| 2499 |
|
| 2500 |
## Usage
|
| 2501 |
|
|
|
|
| 2503 |
|
| 2504 |
## Evaluation Results
|
| 2505 |
|
| 2506 |
+
For eval results, refer to our paper: https://arxiv.org/abs/2202.08904
|
| 2507 |
|
| 2508 |
## Training
|
| 2509 |
The model was trained with the parameters:
|
| 2510 |
|
| 2511 |
**DataLoader**:
|
| 2512 |
|
| 2513 |
+
`torch.utils.data.dataloader.DataLoader` of length 249592 with parameters:
|
| 2514 |
```
|
| 2515 |
+
{'batch_size': 2, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
|
| 2516 |
```
|
| 2517 |
|
| 2518 |
**Loss**:
|
|
|
|
| 2525 |
Parameters of the fit()-Method:
|
| 2526 |
```
|
| 2527 |
{
|
| 2528 |
+
"epochs": 10,
|
| 2529 |
+
"evaluation_steps": 0,
|
| 2530 |
+
"evaluator": "NoneType",
|
| 2531 |
"max_grad_norm": 1,
|
| 2532 |
"optimizer_class": "<class 'transformers.optimization.AdamW'>",
|
| 2533 |
"optimizer_params": {
|
| 2534 |
+
"lr": 5e-05
|
| 2535 |
},
|
| 2536 |
"scheduler": "WarmupLinear",
|
| 2537 |
"steps_per_epoch": null,
|
| 2538 |
+
"warmup_steps": 1000,
|
| 2539 |
"weight_decay": 0.01
|
| 2540 |
}
|
| 2541 |
```
|
|
|
|
| 2544 |
## Full Model Architecture
|
| 2545 |
```
|
| 2546 |
SentenceTransformer(
|
| 2547 |
+
(0): Transformer({'max_seq_length': 300, 'do_lower_case': False}) with Transformer model: GPTJModel
|
| 2548 |
(1): Pooling({'word_embedding_dimension': 4096, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': True, 'pooling_mode_lasttoken': False})
|
| 2549 |
)
|
| 2550 |
```
|