Add MTEB metadata
#2
by
Muennighoff
- opened
README.md
CHANGED
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@@ -4,6 +4,7 @@ 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 |
language: en
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| 8 |
license: apache-2.0
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| 9 |
datasets:
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@@ -28,7 +29,2277 @@ datasets:
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| 28 |
- embedding-data/SPECTER
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- embedding-data/PAQ_pairs
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- embedding-data/WikiAnswers
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|
| 32 |
---
|
| 33 |
|
| 34 |
|
|
@@ -93,7 +2364,7 @@ print(sentence_embeddings)
|
|
| 93 |
|
| 94 |
## Evaluation Results
|
| 95 |
|
| 96 |
-
For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=sentence-transformers/all-
|
| 97 |
|
| 98 |
------
|
| 99 |
|
|
|
|
| 4 |
- sentence-transformers
|
| 5 |
- feature-extraction
|
| 6 |
- sentence-similarity
|
| 7 |
+
- mteb
|
| 8 |
language: en
|
| 9 |
license: apache-2.0
|
| 10 |
datasets:
|
|
|
|
| 29 |
- embedding-data/SPECTER
|
| 30 |
- embedding-data/PAQ_pairs
|
| 31 |
- embedding-data/WikiAnswers
|
| 32 |
+
model-index:
|
| 33 |
+
- name: all-mpnet-base-v2
|
| 34 |
+
results:
|
| 35 |
+
- task:
|
| 36 |
+
type: Classification
|
| 37 |
+
dataset:
|
| 38 |
+
type: mteb/amazon_counterfactual
|
| 39 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
| 40 |
+
config: en
|
| 41 |
+
split: test
|
| 42 |
+
revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996
|
| 43 |
+
metrics:
|
| 44 |
+
- type: accuracy
|
| 45 |
+
value: 65.26865671641791
|
| 46 |
+
- type: ap
|
| 47 |
+
value: 28.47453420428918
|
| 48 |
+
- type: f1
|
| 49 |
+
value: 59.3470101009448
|
| 50 |
+
- task:
|
| 51 |
+
type: Classification
|
| 52 |
+
dataset:
|
| 53 |
+
type: mteb/amazon_polarity
|
| 54 |
+
name: MTEB AmazonPolarityClassification
|
| 55 |
+
config: default
|
| 56 |
+
split: test
|
| 57 |
+
revision: 80714f8dcf8cefc218ef4f8c5a966dd83f75a0e1
|
| 58 |
+
metrics:
|
| 59 |
+
- type: accuracy
|
| 60 |
+
value: 67.13145
|
| 61 |
+
- type: ap
|
| 62 |
+
value: 61.842060778903786
|
| 63 |
+
- type: f1
|
| 64 |
+
value: 66.79987305640383
|
| 65 |
+
- task:
|
| 66 |
+
type: Classification
|
| 67 |
+
dataset:
|
| 68 |
+
type: mteb/amazon_reviews_multi
|
| 69 |
+
name: MTEB AmazonReviewsClassification (en)
|
| 70 |
+
config: en
|
| 71 |
+
split: test
|
| 72 |
+
revision: c379a6705fec24a2493fa68e011692605f44e119
|
| 73 |
+
metrics:
|
| 74 |
+
- type: accuracy
|
| 75 |
+
value: 31.920000000000005
|
| 76 |
+
- type: f1
|
| 77 |
+
value: 31.2465193896153
|
| 78 |
+
- task:
|
| 79 |
+
type: Retrieval
|
| 80 |
+
dataset:
|
| 81 |
+
type: arguana
|
| 82 |
+
name: MTEB ArguAna
|
| 83 |
+
config: default
|
| 84 |
+
split: test
|
| 85 |
+
revision: 5b3e3697907184a9b77a3c99ee9ea1a9cbb1e4e3
|
| 86 |
+
metrics:
|
| 87 |
+
- type: map_at_1
|
| 88 |
+
value: 23.186
|
| 89 |
+
- type: map_at_10
|
| 90 |
+
value: 37.692
|
| 91 |
+
- type: map_at_100
|
| 92 |
+
value: 38.986
|
| 93 |
+
- type: map_at_1000
|
| 94 |
+
value: 38.991
|
| 95 |
+
- type: map_at_3
|
| 96 |
+
value: 32.622
|
| 97 |
+
- type: map_at_5
|
| 98 |
+
value: 35.004999999999995
|
| 99 |
+
- type: ndcg_at_1
|
| 100 |
+
value: 23.186
|
| 101 |
+
- type: ndcg_at_10
|
| 102 |
+
value: 46.521
|
| 103 |
+
- type: ndcg_at_100
|
| 104 |
+
value: 51.954
|
| 105 |
+
- type: ndcg_at_1000
|
| 106 |
+
value: 52.087
|
| 107 |
+
- type: ndcg_at_3
|
| 108 |
+
value: 35.849
|
| 109 |
+
- type: ndcg_at_5
|
| 110 |
+
value: 40.12
|
| 111 |
+
- type: precision_at_1
|
| 112 |
+
value: 23.186
|
| 113 |
+
- type: precision_at_10
|
| 114 |
+
value: 7.510999999999999
|
| 115 |
+
- type: precision_at_100
|
| 116 |
+
value: 0.9860000000000001
|
| 117 |
+
- type: precision_at_1000
|
| 118 |
+
value: 0.1
|
| 119 |
+
- type: precision_at_3
|
| 120 |
+
value: 15.078
|
| 121 |
+
- type: precision_at_5
|
| 122 |
+
value: 11.110000000000001
|
| 123 |
+
- type: recall_at_1
|
| 124 |
+
value: 23.186
|
| 125 |
+
- type: recall_at_10
|
| 126 |
+
value: 75.107
|
| 127 |
+
- type: recall_at_100
|
| 128 |
+
value: 98.649
|
| 129 |
+
- type: recall_at_1000
|
| 130 |
+
value: 99.644
|
| 131 |
+
- type: recall_at_3
|
| 132 |
+
value: 45.235
|
| 133 |
+
- type: recall_at_5
|
| 134 |
+
value: 55.547999999999995
|
| 135 |
+
- task:
|
| 136 |
+
type: Clustering
|
| 137 |
+
dataset:
|
| 138 |
+
type: mteb/arxiv-clustering-p2p
|
| 139 |
+
name: MTEB ArxivClusteringP2P
|
| 140 |
+
config: default
|
| 141 |
+
split: test
|
| 142 |
+
revision: 0bbdb47bcbe3a90093699aefeed338a0f28a7ee8
|
| 143 |
+
metrics:
|
| 144 |
+
- type: v_measure
|
| 145 |
+
value: 48.37886340922374
|
| 146 |
+
- task:
|
| 147 |
+
type: Clustering
|
| 148 |
+
dataset:
|
| 149 |
+
type: mteb/arxiv-clustering-s2s
|
| 150 |
+
name: MTEB ArxivClusteringS2S
|
| 151 |
+
config: default
|
| 152 |
+
split: test
|
| 153 |
+
revision: b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3
|
| 154 |
+
metrics:
|
| 155 |
+
- type: v_measure
|
| 156 |
+
value: 39.72488615315985
|
| 157 |
+
- task:
|
| 158 |
+
type: Reranking
|
| 159 |
+
dataset:
|
| 160 |
+
type: mteb/askubuntudupquestions-reranking
|
| 161 |
+
name: MTEB AskUbuntuDupQuestions
|
| 162 |
+
config: default
|
| 163 |
+
split: test
|
| 164 |
+
revision: 4d853f94cd57d85ec13805aeeac3ae3e5eb4c49c
|
| 165 |
+
metrics:
|
| 166 |
+
- type: map
|
| 167 |
+
value: 65.85199009344481
|
| 168 |
+
- type: mrr
|
| 169 |
+
value: 78.47700391329201
|
| 170 |
+
- task:
|
| 171 |
+
type: STS
|
| 172 |
+
dataset:
|
| 173 |
+
type: mteb/biosses-sts
|
| 174 |
+
name: MTEB BIOSSES
|
| 175 |
+
config: default
|
| 176 |
+
split: test
|
| 177 |
+
revision: 9ee918f184421b6bd48b78f6c714d86546106103
|
| 178 |
+
metrics:
|
| 179 |
+
- type: cos_sim_pearson
|
| 180 |
+
value: 84.47737119217858
|
| 181 |
+
- type: cos_sim_spearman
|
| 182 |
+
value: 80.43195317854409
|
| 183 |
+
- type: euclidean_pearson
|
| 184 |
+
value: 82.20496332547978
|
| 185 |
+
- type: euclidean_spearman
|
| 186 |
+
value: 80.43195317854409
|
| 187 |
+
- type: manhattan_pearson
|
| 188 |
+
value: 81.4836610720397
|
| 189 |
+
- type: manhattan_spearman
|
| 190 |
+
value: 79.65904400101908
|
| 191 |
+
- task:
|
| 192 |
+
type: Classification
|
| 193 |
+
dataset:
|
| 194 |
+
type: mteb/banking77
|
| 195 |
+
name: MTEB Banking77Classification
|
| 196 |
+
config: default
|
| 197 |
+
split: test
|
| 198 |
+
revision: 44fa15921b4c889113cc5df03dd4901b49161ab7
|
| 199 |
+
metrics:
|
| 200 |
+
- type: accuracy
|
| 201 |
+
value: 81.8603896103896
|
| 202 |
+
- type: f1
|
| 203 |
+
value: 81.28027245637479
|
| 204 |
+
- task:
|
| 205 |
+
type: Clustering
|
| 206 |
+
dataset:
|
| 207 |
+
type: mteb/biorxiv-clustering-p2p
|
| 208 |
+
name: MTEB BiorxivClusteringP2P
|
| 209 |
+
config: default
|
| 210 |
+
split: test
|
| 211 |
+
revision: 11d0121201d1f1f280e8cc8f3d98fb9c4d9f9c55
|
| 212 |
+
metrics:
|
| 213 |
+
- type: v_measure
|
| 214 |
+
value: 39.616605133625185
|
| 215 |
+
- task:
|
| 216 |
+
type: Clustering
|
| 217 |
+
dataset:
|
| 218 |
+
type: mteb/biorxiv-clustering-s2s
|
| 219 |
+
name: MTEB BiorxivClusteringS2S
|
| 220 |
+
config: default
|
| 221 |
+
split: test
|
| 222 |
+
revision: c0fab014e1bcb8d3a5e31b2088972a1e01547dc1
|
| 223 |
+
metrics:
|
| 224 |
+
- type: v_measure
|
| 225 |
+
value: 35.02442407186902
|
| 226 |
+
- task:
|
| 227 |
+
type: Retrieval
|
| 228 |
+
dataset:
|
| 229 |
+
type: BeIR/cqadupstack
|
| 230 |
+
name: MTEB CQADupstackAndroidRetrieval
|
| 231 |
+
config: default
|
| 232 |
+
split: test
|
| 233 |
+
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
|
| 234 |
+
metrics:
|
| 235 |
+
- type: map_at_1
|
| 236 |
+
value: 36.036
|
| 237 |
+
- type: map_at_10
|
| 238 |
+
value: 49.302
|
| 239 |
+
- type: map_at_100
|
| 240 |
+
value: 50.956
|
| 241 |
+
- type: map_at_1000
|
| 242 |
+
value: 51.080000000000005
|
| 243 |
+
- type: map_at_3
|
| 244 |
+
value: 45.237
|
| 245 |
+
- type: map_at_5
|
| 246 |
+
value: 47.353
|
| 247 |
+
- type: ndcg_at_1
|
| 248 |
+
value: 45.207
|
| 249 |
+
- type: ndcg_at_10
|
| 250 |
+
value: 56.485
|
| 251 |
+
- type: ndcg_at_100
|
| 252 |
+
value: 61.413
|
| 253 |
+
- type: ndcg_at_1000
|
| 254 |
+
value: 62.870000000000005
|
| 255 |
+
- type: ndcg_at_3
|
| 256 |
+
value: 51.346000000000004
|
| 257 |
+
- type: ndcg_at_5
|
| 258 |
+
value: 53.486
|
| 259 |
+
- type: precision_at_1
|
| 260 |
+
value: 45.207
|
| 261 |
+
- type: precision_at_10
|
| 262 |
+
value: 11.144
|
| 263 |
+
- type: precision_at_100
|
| 264 |
+
value: 1.735
|
| 265 |
+
- type: precision_at_1000
|
| 266 |
+
value: 0.22100000000000003
|
| 267 |
+
- type: precision_at_3
|
| 268 |
+
value: 24.94
|
| 269 |
+
- type: precision_at_5
|
| 270 |
+
value: 17.997
|
| 271 |
+
- type: recall_at_1
|
| 272 |
+
value: 36.036
|
| 273 |
+
- type: recall_at_10
|
| 274 |
+
value: 69.191
|
| 275 |
+
- type: recall_at_100
|
| 276 |
+
value: 89.423
|
| 277 |
+
- type: recall_at_1000
|
| 278 |
+
value: 98.425
|
| 279 |
+
- type: recall_at_3
|
| 280 |
+
value: 53.849999999999994
|
| 281 |
+
- type: recall_at_5
|
| 282 |
+
value: 60.107
|
| 283 |
+
- task:
|
| 284 |
+
type: Retrieval
|
| 285 |
+
dataset:
|
| 286 |
+
type: BeIR/cqadupstack
|
| 287 |
+
name: MTEB CQADupstackEnglishRetrieval
|
| 288 |
+
config: default
|
| 289 |
+
split: test
|
| 290 |
+
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
|
| 291 |
+
metrics:
|
| 292 |
+
- type: map_at_1
|
| 293 |
+
value: 32.92
|
| 294 |
+
- type: map_at_10
|
| 295 |
+
value: 45.739999999999995
|
| 296 |
+
- type: map_at_100
|
| 297 |
+
value: 47.309
|
| 298 |
+
- type: map_at_1000
|
| 299 |
+
value: 47.443000000000005
|
| 300 |
+
- type: map_at_3
|
| 301 |
+
value: 42.154
|
| 302 |
+
- type: map_at_5
|
| 303 |
+
value: 44.207
|
| 304 |
+
- type: ndcg_at_1
|
| 305 |
+
value: 42.229
|
| 306 |
+
- type: ndcg_at_10
|
| 307 |
+
value: 52.288999999999994
|
| 308 |
+
- type: ndcg_at_100
|
| 309 |
+
value: 57.04900000000001
|
| 310 |
+
- type: ndcg_at_1000
|
| 311 |
+
value: 58.788
|
| 312 |
+
- type: ndcg_at_3
|
| 313 |
+
value: 47.531
|
| 314 |
+
- type: ndcg_at_5
|
| 315 |
+
value: 49.861
|
| 316 |
+
- type: precision_at_1
|
| 317 |
+
value: 42.229
|
| 318 |
+
- type: precision_at_10
|
| 319 |
+
value: 10.299
|
| 320 |
+
- type: precision_at_100
|
| 321 |
+
value: 1.68
|
| 322 |
+
- type: precision_at_1000
|
| 323 |
+
value: 0.213
|
| 324 |
+
- type: precision_at_3
|
| 325 |
+
value: 23.673
|
| 326 |
+
- type: precision_at_5
|
| 327 |
+
value: 17.006
|
| 328 |
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- type: recall_at_1
|
| 329 |
+
value: 32.92
|
| 330 |
+
- type: recall_at_10
|
| 331 |
+
value: 63.865
|
| 332 |
+
- type: recall_at_100
|
| 333 |
+
value: 84.06700000000001
|
| 334 |
+
- type: recall_at_1000
|
| 335 |
+
value: 94.536
|
| 336 |
+
- type: recall_at_3
|
| 337 |
+
value: 49.643
|
| 338 |
+
- type: recall_at_5
|
| 339 |
+
value: 56.119
|
| 340 |
+
- task:
|
| 341 |
+
type: Retrieval
|
| 342 |
+
dataset:
|
| 343 |
+
type: BeIR/cqadupstack
|
| 344 |
+
name: MTEB CQADupstackGamingRetrieval
|
| 345 |
+
config: default
|
| 346 |
+
split: test
|
| 347 |
+
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
|
| 348 |
+
metrics:
|
| 349 |
+
- type: map_at_1
|
| 350 |
+
value: 40.695
|
| 351 |
+
- type: map_at_10
|
| 352 |
+
value: 53.787
|
| 353 |
+
- type: map_at_100
|
| 354 |
+
value: 54.778000000000006
|
| 355 |
+
- type: map_at_1000
|
| 356 |
+
value: 54.827000000000005
|
| 357 |
+
- type: map_at_3
|
| 358 |
+
value: 50.151999999999994
|
| 359 |
+
- type: map_at_5
|
| 360 |
+
value: 52.207
|
| 361 |
+
- type: ndcg_at_1
|
| 362 |
+
value: 46.52
|
| 363 |
+
- type: ndcg_at_10
|
| 364 |
+
value: 60.026
|
| 365 |
+
- type: ndcg_at_100
|
| 366 |
+
value: 63.81099999999999
|
| 367 |
+
- type: ndcg_at_1000
|
| 368 |
+
value: 64.741
|
| 369 |
+
- type: ndcg_at_3
|
| 370 |
+
value: 53.83
|
| 371 |
+
- type: ndcg_at_5
|
| 372 |
+
value: 56.928999999999995
|
| 373 |
+
- type: precision_at_1
|
| 374 |
+
value: 46.52
|
| 375 |
+
- type: precision_at_10
|
| 376 |
+
value: 9.754999999999999
|
| 377 |
+
- type: precision_at_100
|
| 378 |
+
value: 1.2670000000000001
|
| 379 |
+
- type: precision_at_1000
|
| 380 |
+
value: 0.13799999999999998
|
| 381 |
+
- type: precision_at_3
|
| 382 |
+
value: 24.096
|
| 383 |
+
- type: precision_at_5
|
| 384 |
+
value: 16.689999999999998
|
| 385 |
+
- type: recall_at_1
|
| 386 |
+
value: 40.695
|
| 387 |
+
- type: recall_at_10
|
| 388 |
+
value: 75.181
|
| 389 |
+
- type: recall_at_100
|
| 390 |
+
value: 91.479
|
| 391 |
+
- type: recall_at_1000
|
| 392 |
+
value: 98.06899999999999
|
| 393 |
+
- type: recall_at_3
|
| 394 |
+
value: 58.707
|
| 395 |
+
- type: recall_at_5
|
| 396 |
+
value: 66.295
|
| 397 |
+
- task:
|
| 398 |
+
type: Retrieval
|
| 399 |
+
dataset:
|
| 400 |
+
type: BeIR/cqadupstack
|
| 401 |
+
name: MTEB CQADupstackGisRetrieval
|
| 402 |
+
config: default
|
| 403 |
+
split: test
|
| 404 |
+
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
|
| 405 |
+
metrics:
|
| 406 |
+
- type: map_at_1
|
| 407 |
+
value: 29.024
|
| 408 |
+
- type: map_at_10
|
| 409 |
+
value: 38.438
|
| 410 |
+
- type: map_at_100
|
| 411 |
+
value: 39.576
|
| 412 |
+
- type: map_at_1000
|
| 413 |
+
value: 39.645
|
| 414 |
+
- type: map_at_3
|
| 415 |
+
value: 34.827999999999996
|
| 416 |
+
- type: map_at_5
|
| 417 |
+
value: 36.947
|
| 418 |
+
- type: ndcg_at_1
|
| 419 |
+
value: 31.299
|
| 420 |
+
- type: ndcg_at_10
|
| 421 |
+
value: 44.268
|
| 422 |
+
- type: ndcg_at_100
|
| 423 |
+
value: 49.507
|
| 424 |
+
- type: ndcg_at_1000
|
| 425 |
+
value: 51.205999999999996
|
| 426 |
+
- type: ndcg_at_3
|
| 427 |
+
value: 37.248999999999995
|
| 428 |
+
- type: ndcg_at_5
|
| 429 |
+
value: 40.861999999999995
|
| 430 |
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- type: precision_at_1
|
| 431 |
+
value: 31.299
|
| 432 |
+
- type: precision_at_10
|
| 433 |
+
value: 6.949
|
| 434 |
+
- type: precision_at_100
|
| 435 |
+
value: 1.012
|
| 436 |
+
- type: precision_at_1000
|
| 437 |
+
value: 0.11900000000000001
|
| 438 |
+
- type: precision_at_3
|
| 439 |
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value: 15.518
|
| 440 |
+
- type: precision_at_5
|
| 441 |
+
value: 11.366999999999999
|
| 442 |
+
- type: recall_at_1
|
| 443 |
+
value: 29.024
|
| 444 |
+
- type: recall_at_10
|
| 445 |
+
value: 60.404
|
| 446 |
+
- type: recall_at_100
|
| 447 |
+
value: 83.729
|
| 448 |
+
- type: recall_at_1000
|
| 449 |
+
value: 96.439
|
| 450 |
+
- type: recall_at_3
|
| 451 |
+
value: 41.65
|
| 452 |
+
- type: recall_at_5
|
| 453 |
+
value: 50.263999999999996
|
| 454 |
+
- task:
|
| 455 |
+
type: Retrieval
|
| 456 |
+
dataset:
|
| 457 |
+
type: BeIR/cqadupstack
|
| 458 |
+
name: MTEB CQADupstackMathematicaRetrieval
|
| 459 |
+
config: default
|
| 460 |
+
split: test
|
| 461 |
+
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
|
| 462 |
+
metrics:
|
| 463 |
+
- type: map_at_1
|
| 464 |
+
value: 17.774
|
| 465 |
+
- type: map_at_10
|
| 466 |
+
value: 28.099
|
| 467 |
+
- type: map_at_100
|
| 468 |
+
value: 29.603
|
| 469 |
+
- type: map_at_1000
|
| 470 |
+
value: 29.709999999999997
|
| 471 |
+
- type: map_at_3
|
| 472 |
+
value: 25.036
|
| 473 |
+
- type: map_at_5
|
| 474 |
+
value: 26.657999999999998
|
| 475 |
+
- type: ndcg_at_1
|
| 476 |
+
value: 22.139
|
| 477 |
+
- type: ndcg_at_10
|
| 478 |
+
value: 34.205999999999996
|
| 479 |
+
- type: ndcg_at_100
|
| 480 |
+
value: 40.844
|
| 481 |
+
- type: ndcg_at_1000
|
| 482 |
+
value: 43.144
|
| 483 |
+
- type: ndcg_at_3
|
| 484 |
+
value: 28.732999999999997
|
| 485 |
+
- type: ndcg_at_5
|
| 486 |
+
value: 31.252000000000002
|
| 487 |
+
- type: precision_at_1
|
| 488 |
+
value: 22.139
|
| 489 |
+
- type: precision_at_10
|
| 490 |
+
value: 6.567
|
| 491 |
+
- type: precision_at_100
|
| 492 |
+
value: 1.147
|
| 493 |
+
- type: precision_at_1000
|
| 494 |
+
value: 0.146
|
| 495 |
+
- type: precision_at_3
|
| 496 |
+
value: 14.386
|
| 497 |
+
- type: precision_at_5
|
| 498 |
+
value: 10.423
|
| 499 |
+
- type: recall_at_1
|
| 500 |
+
value: 17.774
|
| 501 |
+
- type: recall_at_10
|
| 502 |
+
value: 48.32
|
| 503 |
+
- type: recall_at_100
|
| 504 |
+
value: 76.373
|
| 505 |
+
- type: recall_at_1000
|
| 506 |
+
value: 92.559
|
| 507 |
+
- type: recall_at_3
|
| 508 |
+
value: 33.478
|
| 509 |
+
- type: recall_at_5
|
| 510 |
+
value: 39.872
|
| 511 |
+
- task:
|
| 512 |
+
type: Retrieval
|
| 513 |
+
dataset:
|
| 514 |
+
type: BeIR/cqadupstack
|
| 515 |
+
name: MTEB CQADupstackPhysicsRetrieval
|
| 516 |
+
config: default
|
| 517 |
+
split: test
|
| 518 |
+
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
|
| 519 |
+
metrics:
|
| 520 |
+
- type: map_at_1
|
| 521 |
+
value: 31.885
|
| 522 |
+
- type: map_at_10
|
| 523 |
+
value: 44.289
|
| 524 |
+
- type: map_at_100
|
| 525 |
+
value: 45.757999999999996
|
| 526 |
+
- type: map_at_1000
|
| 527 |
+
value: 45.86
|
| 528 |
+
- type: map_at_3
|
| 529 |
+
value: 40.459
|
| 530 |
+
- type: map_at_5
|
| 531 |
+
value: 42.662
|
| 532 |
+
- type: ndcg_at_1
|
| 533 |
+
value: 39.75
|
| 534 |
+
- type: ndcg_at_10
|
| 535 |
+
value: 50.975
|
| 536 |
+
- type: ndcg_at_100
|
| 537 |
+
value: 56.528999999999996
|
| 538 |
+
- type: ndcg_at_1000
|
| 539 |
+
value: 58.06099999999999
|
| 540 |
+
- type: ndcg_at_3
|
| 541 |
+
value: 45.327
|
| 542 |
+
- type: ndcg_at_5
|
| 543 |
+
value: 48.041
|
| 544 |
+
- type: precision_at_1
|
| 545 |
+
value: 39.75
|
| 546 |
+
- type: precision_at_10
|
| 547 |
+
value: 9.557
|
| 548 |
+
- type: precision_at_100
|
| 549 |
+
value: 1.469
|
| 550 |
+
- type: precision_at_1000
|
| 551 |
+
value: 0.17700000000000002
|
| 552 |
+
- type: precision_at_3
|
| 553 |
+
value: 22.073
|
| 554 |
+
- type: precision_at_5
|
| 555 |
+
value: 15.765
|
| 556 |
+
- type: recall_at_1
|
| 557 |
+
value: 31.885
|
| 558 |
+
- type: recall_at_10
|
| 559 |
+
value: 64.649
|
| 560 |
+
- type: recall_at_100
|
| 561 |
+
value: 87.702
|
| 562 |
+
- type: recall_at_1000
|
| 563 |
+
value: 97.327
|
| 564 |
+
- type: recall_at_3
|
| 565 |
+
value: 48.61
|
| 566 |
+
- type: recall_at_5
|
| 567 |
+
value: 55.882
|
| 568 |
+
- task:
|
| 569 |
+
type: Retrieval
|
| 570 |
+
dataset:
|
| 571 |
+
type: BeIR/cqadupstack
|
| 572 |
+
name: MTEB CQADupstackProgrammersRetrieval
|
| 573 |
+
config: default
|
| 574 |
+
split: test
|
| 575 |
+
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
|
| 576 |
+
metrics:
|
| 577 |
+
- type: map_at_1
|
| 578 |
+
value: 26.454
|
| 579 |
+
- type: map_at_10
|
| 580 |
+
value: 37.756
|
| 581 |
+
- type: map_at_100
|
| 582 |
+
value: 39.225
|
| 583 |
+
- type: map_at_1000
|
| 584 |
+
value: 39.332
|
| 585 |
+
- type: map_at_3
|
| 586 |
+
value: 34.115
|
| 587 |
+
- type: map_at_5
|
| 588 |
+
value: 35.942
|
| 589 |
+
- type: ndcg_at_1
|
| 590 |
+
value: 32.42
|
| 591 |
+
- type: ndcg_at_10
|
| 592 |
+
value: 44.165
|
| 593 |
+
- type: ndcg_at_100
|
| 594 |
+
value: 50.202000000000005
|
| 595 |
+
- type: ndcg_at_1000
|
| 596 |
+
value: 52.188
|
| 597 |
+
- type: ndcg_at_3
|
| 598 |
+
value: 38.381
|
| 599 |
+
- type: ndcg_at_5
|
| 600 |
+
value: 40.849000000000004
|
| 601 |
+
- type: precision_at_1
|
| 602 |
+
value: 32.42
|
| 603 |
+
- type: precision_at_10
|
| 604 |
+
value: 8.482000000000001
|
| 605 |
+
- type: precision_at_100
|
| 606 |
+
value: 1.332
|
| 607 |
+
- type: precision_at_1000
|
| 608 |
+
value: 0.169
|
| 609 |
+
- type: precision_at_3
|
| 610 |
+
value: 18.683
|
| 611 |
+
- type: precision_at_5
|
| 612 |
+
value: 13.539000000000001
|
| 613 |
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- type: recall_at_1
|
| 614 |
+
value: 26.454
|
| 615 |
+
- type: recall_at_10
|
| 616 |
+
value: 57.937000000000005
|
| 617 |
+
- type: recall_at_100
|
| 618 |
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value: 83.76
|
| 619 |
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- type: recall_at_1000
|
| 620 |
+
value: 96.82600000000001
|
| 621 |
+
- type: recall_at_3
|
| 622 |
+
value: 41.842
|
| 623 |
+
- type: recall_at_5
|
| 624 |
+
value: 48.285
|
| 625 |
+
- task:
|
| 626 |
+
type: Retrieval
|
| 627 |
+
dataset:
|
| 628 |
+
type: BeIR/cqadupstack
|
| 629 |
+
name: MTEB CQADupstackRetrieval
|
| 630 |
+
config: default
|
| 631 |
+
split: test
|
| 632 |
+
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
|
| 633 |
+
metrics:
|
| 634 |
+
- type: map_at_1
|
| 635 |
+
value: 27.743666666666666
|
| 636 |
+
- type: map_at_10
|
| 637 |
+
value: 38.75416666666667
|
| 638 |
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- type: map_at_100
|
| 639 |
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value: 40.133250000000004
|
| 640 |
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- type: map_at_1000
|
| 641 |
+
value: 40.24616666666667
|
| 642 |
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- type: map_at_3
|
| 643 |
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value: 35.267250000000004
|
| 644 |
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- type: map_at_5
|
| 645 |
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value: 37.132749999999994
|
| 646 |
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- type: ndcg_at_1
|
| 647 |
+
value: 33.14358333333333
|
| 648 |
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- type: ndcg_at_10
|
| 649 |
+
value: 44.95916666666667
|
| 650 |
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- type: ndcg_at_100
|
| 651 |
+
value: 50.46375
|
| 652 |
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- type: ndcg_at_1000
|
| 653 |
+
value: 52.35508333333334
|
| 654 |
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- type: ndcg_at_3
|
| 655 |
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value: 39.17883333333334
|
| 656 |
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- type: ndcg_at_5
|
| 657 |
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value: 41.79724999999999
|
| 658 |
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- type: precision_at_1
|
| 659 |
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value: 33.14358333333333
|
| 660 |
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- type: precision_at_10
|
| 661 |
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value: 8.201083333333333
|
| 662 |
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- type: precision_at_100
|
| 663 |
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value: 1.3085
|
| 664 |
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- type: precision_at_1000
|
| 665 |
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value: 0.1665833333333333
|
| 666 |
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- type: precision_at_3
|
| 667 |
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value: 18.405583333333333
|
| 668 |
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- type: precision_at_5
|
| 669 |
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value: 13.233166666666666
|
| 670 |
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- type: recall_at_1
|
| 671 |
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value: 27.743666666666666
|
| 672 |
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- type: recall_at_10
|
| 673 |
+
value: 58.91866666666667
|
| 674 |
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- type: recall_at_100
|
| 675 |
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value: 82.76216666666666
|
| 676 |
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- type: recall_at_1000
|
| 677 |
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value: 95.56883333333333
|
| 678 |
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- type: recall_at_3
|
| 679 |
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value: 42.86925
|
| 680 |
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- type: recall_at_5
|
| 681 |
+
value: 49.553333333333335
|
| 682 |
+
- task:
|
| 683 |
+
type: Retrieval
|
| 684 |
+
dataset:
|
| 685 |
+
type: BeIR/cqadupstack
|
| 686 |
+
name: MTEB CQADupstackStatsRetrieval
|
| 687 |
+
config: default
|
| 688 |
+
split: test
|
| 689 |
+
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
|
| 690 |
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metrics:
|
| 691 |
+
- type: map_at_1
|
| 692 |
+
value: 25.244
|
| 693 |
+
- type: map_at_10
|
| 694 |
+
value: 33.464
|
| 695 |
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- type: map_at_100
|
| 696 |
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value: 34.633
|
| 697 |
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- type: map_at_1000
|
| 698 |
+
value: 34.721999999999994
|
| 699 |
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- type: map_at_3
|
| 700 |
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value: 30.784
|
| 701 |
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- type: map_at_5
|
| 702 |
+
value: 32.183
|
| 703 |
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- type: ndcg_at_1
|
| 704 |
+
value: 28.681
|
| 705 |
+
- type: ndcg_at_10
|
| 706 |
+
value: 38.149
|
| 707 |
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- type: ndcg_at_100
|
| 708 |
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value: 43.856
|
| 709 |
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- type: ndcg_at_1000
|
| 710 |
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value: 46.026
|
| 711 |
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- type: ndcg_at_3
|
| 712 |
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value: 33.318
|
| 713 |
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- type: ndcg_at_5
|
| 714 |
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value: 35.454
|
| 715 |
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- type: precision_at_1
|
| 716 |
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value: 28.681
|
| 717 |
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- type: precision_at_10
|
| 718 |
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value: 6.304
|
| 719 |
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- type: precision_at_100
|
| 720 |
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value: 0.992
|
| 721 |
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- type: precision_at_1000
|
| 722 |
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value: 0.125
|
| 723 |
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- type: precision_at_3
|
| 724 |
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value: 14.673
|
| 725 |
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- type: precision_at_5
|
| 726 |
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value: 10.245
|
| 727 |
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- type: recall_at_1
|
| 728 |
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value: 25.244
|
| 729 |
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- type: recall_at_10
|
| 730 |
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value: 49.711
|
| 731 |
+
- type: recall_at_100
|
| 732 |
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value: 75.928
|
| 733 |
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- type: recall_at_1000
|
| 734 |
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value: 91.79899999999999
|
| 735 |
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- type: recall_at_3
|
| 736 |
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value: 36.325
|
| 737 |
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- type: recall_at_5
|
| 738 |
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value: 41.752
|
| 739 |
+
- task:
|
| 740 |
+
type: Retrieval
|
| 741 |
+
dataset:
|
| 742 |
+
type: BeIR/cqadupstack
|
| 743 |
+
name: MTEB CQADupstackTexRetrieval
|
| 744 |
+
config: default
|
| 745 |
+
split: test
|
| 746 |
+
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
|
| 747 |
+
metrics:
|
| 748 |
+
- type: map_at_1
|
| 749 |
+
value: 18.857
|
| 750 |
+
- type: map_at_10
|
| 751 |
+
value: 27.794
|
| 752 |
+
- type: map_at_100
|
| 753 |
+
value: 29.186
|
| 754 |
+
- type: map_at_1000
|
| 755 |
+
value: 29.323
|
| 756 |
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- type: map_at_3
|
| 757 |
+
value: 24.779
|
| 758 |
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- type: map_at_5
|
| 759 |
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value: 26.459
|
| 760 |
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- type: ndcg_at_1
|
| 761 |
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value: 23.227999999999998
|
| 762 |
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- type: ndcg_at_10
|
| 763 |
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value: 33.353
|
| 764 |
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- type: ndcg_at_100
|
| 765 |
+
value: 39.598
|
| 766 |
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- type: ndcg_at_1000
|
| 767 |
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value: 42.268
|
| 768 |
+
- type: ndcg_at_3
|
| 769 |
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value: 28.054000000000002
|
| 770 |
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- type: ndcg_at_5
|
| 771 |
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value: 30.566
|
| 772 |
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- type: precision_at_1
|
| 773 |
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value: 23.227999999999998
|
| 774 |
+
- type: precision_at_10
|
| 775 |
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value: 6.397
|
| 776 |
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- type: precision_at_100
|
| 777 |
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value: 1.129
|
| 778 |
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- type: precision_at_1000
|
| 779 |
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value: 0.155
|
| 780 |
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- type: precision_at_3
|
| 781 |
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value: 13.616
|
| 782 |
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- type: precision_at_5
|
| 783 |
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value: 10.116999999999999
|
| 784 |
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- type: recall_at_1
|
| 785 |
+
value: 18.857
|
| 786 |
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- type: recall_at_10
|
| 787 |
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value: 45.797
|
| 788 |
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- type: recall_at_100
|
| 789 |
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value: 73.615
|
| 790 |
+
- type: recall_at_1000
|
| 791 |
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value: 91.959
|
| 792 |
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- type: recall_at_3
|
| 793 |
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value: 31.129
|
| 794 |
+
- type: recall_at_5
|
| 795 |
+
value: 37.565
|
| 796 |
+
- task:
|
| 797 |
+
type: Retrieval
|
| 798 |
+
dataset:
|
| 799 |
+
type: BeIR/cqadupstack
|
| 800 |
+
name: MTEB CQADupstackUnixRetrieval
|
| 801 |
+
config: default
|
| 802 |
+
split: test
|
| 803 |
+
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
|
| 804 |
+
metrics:
|
| 805 |
+
- type: map_at_1
|
| 806 |
+
value: 27.486
|
| 807 |
+
- type: map_at_10
|
| 808 |
+
value: 39.164
|
| 809 |
+
- type: map_at_100
|
| 810 |
+
value: 40.543
|
| 811 |
+
- type: map_at_1000
|
| 812 |
+
value: 40.636
|
| 813 |
+
- type: map_at_3
|
| 814 |
+
value: 35.52
|
| 815 |
+
- type: map_at_5
|
| 816 |
+
value: 37.355
|
| 817 |
+
- type: ndcg_at_1
|
| 818 |
+
value: 32.275999999999996
|
| 819 |
+
- type: ndcg_at_10
|
| 820 |
+
value: 45.414
|
| 821 |
+
- type: ndcg_at_100
|
| 822 |
+
value: 51.254
|
| 823 |
+
- type: ndcg_at_1000
|
| 824 |
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value: 53.044000000000004
|
| 825 |
+
- type: ndcg_at_3
|
| 826 |
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value: 39.324999999999996
|
| 827 |
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- type: ndcg_at_5
|
| 828 |
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value: 41.835
|
| 829 |
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- type: precision_at_1
|
| 830 |
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value: 32.275999999999996
|
| 831 |
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- type: precision_at_10
|
| 832 |
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value: 8.144
|
| 833 |
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- type: precision_at_100
|
| 834 |
+
value: 1.237
|
| 835 |
+
- type: precision_at_1000
|
| 836 |
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value: 0.15
|
| 837 |
+
- type: precision_at_3
|
| 838 |
+
value: 18.501
|
| 839 |
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- type: precision_at_5
|
| 840 |
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value: 13.134
|
| 841 |
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- type: recall_at_1
|
| 842 |
+
value: 27.486
|
| 843 |
+
- type: recall_at_10
|
| 844 |
+
value: 60.449
|
| 845 |
+
- type: recall_at_100
|
| 846 |
+
value: 85.176
|
| 847 |
+
- type: recall_at_1000
|
| 848 |
+
value: 97.087
|
| 849 |
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- type: recall_at_3
|
| 850 |
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value: 43.59
|
| 851 |
+
- type: recall_at_5
|
| 852 |
+
value: 50.08899999999999
|
| 853 |
+
- task:
|
| 854 |
+
type: Retrieval
|
| 855 |
+
dataset:
|
| 856 |
+
type: BeIR/cqadupstack
|
| 857 |
+
name: MTEB CQADupstackWebmastersRetrieval
|
| 858 |
+
config: default
|
| 859 |
+
split: test
|
| 860 |
+
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
|
| 861 |
+
metrics:
|
| 862 |
+
- type: map_at_1
|
| 863 |
+
value: 26.207
|
| 864 |
+
- type: map_at_10
|
| 865 |
+
value: 37.255
|
| 866 |
+
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|
| 867 |
+
value: 39.043
|
| 868 |
+
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|
| 869 |
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value: 39.273
|
| 870 |
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|
| 871 |
+
value: 33.487
|
| 872 |
+
- type: map_at_5
|
| 873 |
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value: 35.441
|
| 874 |
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- type: ndcg_at_1
|
| 875 |
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value: 31.423000000000002
|
| 876 |
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- type: ndcg_at_10
|
| 877 |
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value: 44.235
|
| 878 |
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- type: ndcg_at_100
|
| 879 |
+
value: 50.49
|
| 880 |
+
- type: ndcg_at_1000
|
| 881 |
+
value: 52.283
|
| 882 |
+
- type: ndcg_at_3
|
| 883 |
+
value: 37.602000000000004
|
| 884 |
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- type: ndcg_at_5
|
| 885 |
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value: 40.518
|
| 886 |
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- type: precision_at_1
|
| 887 |
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value: 31.423000000000002
|
| 888 |
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- type: precision_at_10
|
| 889 |
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value: 8.715
|
| 890 |
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- type: precision_at_100
|
| 891 |
+
value: 1.7590000000000001
|
| 892 |
+
- type: precision_at_1000
|
| 893 |
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value: 0.257
|
| 894 |
+
- type: precision_at_3
|
| 895 |
+
value: 17.523
|
| 896 |
+
- type: precision_at_5
|
| 897 |
+
value: 13.161999999999999
|
| 898 |
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- type: recall_at_1
|
| 899 |
+
value: 26.207
|
| 900 |
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- type: recall_at_10
|
| 901 |
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value: 59.17099999999999
|
| 902 |
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- type: recall_at_100
|
| 903 |
+
value: 86.166
|
| 904 |
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- type: recall_at_1000
|
| 905 |
+
value: 96.54700000000001
|
| 906 |
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- type: recall_at_3
|
| 907 |
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value: 41.18
|
| 908 |
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- type: recall_at_5
|
| 909 |
+
value: 48.083999999999996
|
| 910 |
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- task:
|
| 911 |
+
type: Retrieval
|
| 912 |
+
dataset:
|
| 913 |
+
type: BeIR/cqadupstack
|
| 914 |
+
name: MTEB CQADupstackWordpressRetrieval
|
| 915 |
+
config: default
|
| 916 |
+
split: test
|
| 917 |
+
revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
|
| 918 |
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metrics:
|
| 919 |
+
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|
| 920 |
+
value: 20.342
|
| 921 |
+
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|
| 922 |
+
value: 29.962
|
| 923 |
+
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|
| 924 |
+
value: 30.989
|
| 925 |
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|
| 926 |
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value: 31.102999999999998
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| 927 |
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|
| 928 |
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value: 26.656000000000002
|
| 929 |
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- type: map_at_5
|
| 930 |
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value: 28.179
|
| 931 |
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- type: ndcg_at_1
|
| 932 |
+
value: 22.551
|
| 933 |
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- type: ndcg_at_10
|
| 934 |
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value: 35.945
|
| 935 |
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- type: ndcg_at_100
|
| 936 |
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value: 41.012
|
| 937 |
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- type: ndcg_at_1000
|
| 938 |
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value: 43.641999999999996
|
| 939 |
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- type: ndcg_at_3
|
| 940 |
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value: 29.45
|
| 941 |
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- type: ndcg_at_5
|
| 942 |
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value: 31.913999999999998
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| 943 |
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- type: precision_at_1
|
| 944 |
+
value: 22.551
|
| 945 |
+
- type: precision_at_10
|
| 946 |
+
value: 6.1
|
| 947 |
+
- type: precision_at_100
|
| 948 |
+
value: 0.943
|
| 949 |
+
- type: precision_at_1000
|
| 950 |
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value: 0.129
|
| 951 |
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- type: precision_at_3
|
| 952 |
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value: 13.184999999999999
|
| 953 |
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- type: precision_at_5
|
| 954 |
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value: 9.353
|
| 955 |
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- type: recall_at_1
|
| 956 |
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value: 20.342
|
| 957 |
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- type: recall_at_10
|
| 958 |
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value: 52.349000000000004
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| 959 |
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- type: recall_at_100
|
| 960 |
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value: 75.728
|
| 961 |
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- type: recall_at_1000
|
| 962 |
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value: 95.253
|
| 963 |
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- type: recall_at_3
|
| 964 |
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value: 34.427
|
| 965 |
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- type: recall_at_5
|
| 966 |
+
value: 40.326
|
| 967 |
+
- task:
|
| 968 |
+
type: Retrieval
|
| 969 |
+
dataset:
|
| 970 |
+
type: climate-fever
|
| 971 |
+
name: MTEB ClimateFEVER
|
| 972 |
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config: default
|
| 973 |
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split: test
|
| 974 |
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revision: 392b78eb68c07badcd7c2cd8f39af108375dfcce
|
| 975 |
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metrics:
|
| 976 |
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|
| 977 |
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value: 7.71
|
| 978 |
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- type: map_at_10
|
| 979 |
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value: 14.81
|
| 980 |
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|
| 981 |
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value: 16.536
|
| 982 |
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|
| 983 |
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value: 16.744999999999997
|
| 984 |
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- type: map_at_3
|
| 985 |
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value: 12.109
|
| 986 |
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- type: map_at_5
|
| 987 |
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value: 13.613
|
| 988 |
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- type: ndcg_at_1
|
| 989 |
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value: 18.046
|
| 990 |
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- type: ndcg_at_10
|
| 991 |
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value: 21.971
|
| 992 |
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- type: ndcg_at_100
|
| 993 |
+
value: 29.468
|
| 994 |
+
- type: ndcg_at_1000
|
| 995 |
+
value: 33.428999999999995
|
| 996 |
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- type: ndcg_at_3
|
| 997 |
+
value: 17.227999999999998
|
| 998 |
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- type: ndcg_at_5
|
| 999 |
+
value: 19.189999999999998
|
| 1000 |
+
- type: precision_at_1
|
| 1001 |
+
value: 18.046
|
| 1002 |
+
- type: precision_at_10
|
| 1003 |
+
value: 7.192
|
| 1004 |
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- type: precision_at_100
|
| 1005 |
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value: 1.51
|
| 1006 |
+
- type: precision_at_1000
|
| 1007 |
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value: 0.22499999999999998
|
| 1008 |
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- type: precision_at_3
|
| 1009 |
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value: 13.312
|
| 1010 |
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- type: precision_at_5
|
| 1011 |
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value: 10.775
|
| 1012 |
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- type: recall_at_1
|
| 1013 |
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value: 7.71
|
| 1014 |
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- type: recall_at_10
|
| 1015 |
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value: 27.908
|
| 1016 |
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- type: recall_at_100
|
| 1017 |
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value: 54.452
|
| 1018 |
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- type: recall_at_1000
|
| 1019 |
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value: 76.764
|
| 1020 |
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- type: recall_at_3
|
| 1021 |
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value: 16.64
|
| 1022 |
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- type: recall_at_5
|
| 1023 |
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value: 21.631
|
| 1024 |
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- task:
|
| 1025 |
+
type: Retrieval
|
| 1026 |
+
dataset:
|
| 1027 |
+
type: dbpedia-entity
|
| 1028 |
+
name: MTEB DBPedia
|
| 1029 |
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config: default
|
| 1030 |
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split: test
|
| 1031 |
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revision: f097057d03ed98220bc7309ddb10b71a54d667d6
|
| 1032 |
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metrics:
|
| 1033 |
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- type: map_at_1
|
| 1034 |
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value: 6.8180000000000005
|
| 1035 |
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- type: map_at_10
|
| 1036 |
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value: 14.591000000000001
|
| 1037 |
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- type: map_at_100
|
| 1038 |
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value: 19.855999999999998
|
| 1039 |
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- type: map_at_1000
|
| 1040 |
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value: 21.178
|
| 1041 |
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- type: map_at_3
|
| 1042 |
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value: 10.345
|
| 1043 |
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- type: map_at_5
|
| 1044 |
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value: 12.367
|
| 1045 |
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- type: ndcg_at_1
|
| 1046 |
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value: 39.25
|
| 1047 |
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- type: ndcg_at_10
|
| 1048 |
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value: 32.088
|
| 1049 |
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- type: ndcg_at_100
|
| 1050 |
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value: 36.019
|
| 1051 |
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- type: ndcg_at_1000
|
| 1052 |
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value: 43.649
|
| 1053 |
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- type: ndcg_at_3
|
| 1054 |
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value: 35.132999999999996
|
| 1055 |
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- type: ndcg_at_5
|
| 1056 |
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value: 33.777
|
| 1057 |
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- type: precision_at_1
|
| 1058 |
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value: 49.5
|
| 1059 |
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- type: precision_at_10
|
| 1060 |
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value: 25.624999999999996
|
| 1061 |
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- type: precision_at_100
|
| 1062 |
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value: 8.043
|
| 1063 |
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- type: precision_at_1000
|
| 1064 |
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value: 1.7409999999999999
|
| 1065 |
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- type: precision_at_3
|
| 1066 |
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value: 38.417
|
| 1067 |
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- type: precision_at_5
|
| 1068 |
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value: 33.2
|
| 1069 |
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- type: recall_at_1
|
| 1070 |
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value: 6.8180000000000005
|
| 1071 |
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- type: recall_at_10
|
| 1072 |
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value: 20.399
|
| 1073 |
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- type: recall_at_100
|
| 1074 |
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value: 42.8
|
| 1075 |
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- type: recall_at_1000
|
| 1076 |
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value: 68.081
|
| 1077 |
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- type: recall_at_3
|
| 1078 |
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value: 11.928999999999998
|
| 1079 |
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- type: recall_at_5
|
| 1080 |
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value: 15.348999999999998
|
| 1081 |
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- task:
|
| 1082 |
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type: Classification
|
| 1083 |
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dataset:
|
| 1084 |
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type: mteb/emotion
|
| 1085 |
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name: MTEB EmotionClassification
|
| 1086 |
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config: default
|
| 1087 |
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split: test
|
| 1088 |
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revision: 829147f8f75a25f005913200eb5ed41fae320aa1
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| 1089 |
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metrics:
|
| 1090 |
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- type: accuracy
|
| 1091 |
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value: 39.725
|
| 1092 |
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- type: f1
|
| 1093 |
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value: 35.19385687310605
|
| 1094 |
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- task:
|
| 1095 |
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type: Retrieval
|
| 1096 |
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dataset:
|
| 1097 |
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type: fever
|
| 1098 |
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name: MTEB FEVER
|
| 1099 |
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config: default
|
| 1100 |
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split: test
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| 1101 |
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revision: 1429cf27e393599b8b359b9b72c666f96b2525f9
|
| 1102 |
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metrics:
|
| 1103 |
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- type: map_at_1
|
| 1104 |
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value: 31.901000000000003
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| 1105 |
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- type: map_at_10
|
| 1106 |
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value: 44.156
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| 1107 |
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- type: map_at_100
|
| 1108 |
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value: 44.901
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| 1109 |
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- type: map_at_1000
|
| 1110 |
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value: 44.939
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| 1111 |
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| 1112 |
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value: 41.008
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| 1113 |
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|
| 1114 |
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value: 42.969
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| 1115 |
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- type: ndcg_at_1
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| 1116 |
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value: 34.263
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| 1117 |
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- type: ndcg_at_10
|
| 1118 |
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value: 50.863
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| 1119 |
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- type: ndcg_at_100
|
| 1120 |
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value: 54.336
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| 1121 |
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- type: ndcg_at_1000
|
| 1122 |
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value: 55.297
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| 1123 |
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- type: ndcg_at_3
|
| 1124 |
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value: 44.644
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| 1125 |
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- type: ndcg_at_5
|
| 1126 |
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value: 48.075
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| 1127 |
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- type: precision_at_1
|
| 1128 |
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value: 34.263
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| 1129 |
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- type: precision_at_10
|
| 1130 |
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value: 7.542999999999999
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| 1131 |
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- type: precision_at_100
|
| 1132 |
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value: 0.9400000000000001
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| 1133 |
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- type: precision_at_1000
|
| 1134 |
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value: 0.104
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| 1135 |
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- type: precision_at_3
|
| 1136 |
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value: 18.912000000000003
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| 1137 |
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- type: precision_at_5
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| 1138 |
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value: 13.177
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| 1139 |
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- type: recall_at_1
|
| 1140 |
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value: 31.901000000000003
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| 1141 |
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- type: recall_at_10
|
| 1142 |
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value: 68.872
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| 1143 |
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- type: recall_at_100
|
| 1144 |
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value: 84.468
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| 1145 |
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- type: recall_at_1000
|
| 1146 |
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value: 91.694
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| 1147 |
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- type: recall_at_3
|
| 1148 |
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value: 52.272
|
| 1149 |
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- type: recall_at_5
|
| 1150 |
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value: 60.504999999999995
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| 1151 |
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- task:
|
| 1152 |
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type: Retrieval
|
| 1153 |
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dataset:
|
| 1154 |
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type: fiqa
|
| 1155 |
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name: MTEB FiQA2018
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| 1156 |
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config: default
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| 1157 |
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split: test
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| 1158 |
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revision: 41b686a7f28c59bcaaa5791efd47c67c8ebe28be
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| 1159 |
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metrics:
|
| 1160 |
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- type: map_at_1
|
| 1161 |
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value: 24.4
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| 1162 |
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| 1163 |
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value: 41.117
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| 1164 |
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- type: map_at_100
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| 1165 |
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value: 43.167
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| 1166 |
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- type: map_at_1000
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| 1167 |
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value: 43.323
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| 1168 |
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| 1169 |
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value: 35.744
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| 1170 |
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| 1171 |
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value: 38.708
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| 1172 |
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- type: ndcg_at_1
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| 1173 |
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value: 49.074
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| 1174 |
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- type: ndcg_at_10
|
| 1175 |
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value: 49.963
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| 1176 |
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| 1177 |
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value: 56.564
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| 1178 |
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- type: ndcg_at_1000
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| 1179 |
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value: 58.931999999999995
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| 1180 |
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- type: ndcg_at_3
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| 1181 |
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value: 45.489000000000004
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| 1182 |
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- type: ndcg_at_5
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| 1183 |
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value: 47.133
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| 1184 |
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- type: precision_at_1
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| 1185 |
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value: 49.074
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| 1186 |
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- type: precision_at_10
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| 1187 |
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value: 13.889000000000001
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| 1188 |
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- type: precision_at_100
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| 1189 |
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value: 2.091
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| 1190 |
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- type: precision_at_1000
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| 1191 |
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value: 0.251
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| 1192 |
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- type: precision_at_3
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| 1193 |
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value: 30.658
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| 1194 |
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- type: precision_at_5
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| 1195 |
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value: 22.593
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| 1196 |
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- type: recall_at_1
|
| 1197 |
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value: 24.4
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| 1198 |
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- type: recall_at_10
|
| 1199 |
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value: 58.111999999999995
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| 1200 |
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- type: recall_at_100
|
| 1201 |
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value: 81.96900000000001
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| 1202 |
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- type: recall_at_1000
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| 1203 |
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value: 96.187
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| 1204 |
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- type: recall_at_3
|
| 1205 |
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value: 41.661
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| 1206 |
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- type: recall_at_5
|
| 1207 |
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value: 49.24
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| 1208 |
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- task:
|
| 1209 |
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type: Retrieval
|
| 1210 |
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dataset:
|
| 1211 |
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type: hotpotqa
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| 1212 |
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name: MTEB HotpotQA
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| 1213 |
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config: default
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| 1214 |
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split: test
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| 1215 |
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revision: 766870b35a1b9ca65e67a0d1913899973551fc6c
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| 1216 |
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metrics:
|
| 1217 |
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- type: map_at_1
|
| 1218 |
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value: 22.262
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| 1219 |
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- type: map_at_10
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| 1220 |
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value: 31.266
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| 1221 |
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| 1222 |
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value: 32.202
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| 1223 |
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| 1224 |
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value: 32.300000000000004
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| 1226 |
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value: 28.874
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| 1227 |
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| 1228 |
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value: 30.246000000000002
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| 1229 |
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| 1230 |
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value: 44.524
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| 1232 |
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value: 39.294000000000004
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| 1233 |
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| 1234 |
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value: 43.296
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| 1236 |
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value: 45.561
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| 1238 |
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value: 35.013
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| 1239 |
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| 1240 |
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value: 37.177
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| 1242 |
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value: 44.524
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| 1244 |
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value: 8.52
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| 1245 |
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| 1246 |
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value: 1.169
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| 1247 |
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| 1248 |
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value: 0.147
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| 1249 |
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- type: precision_at_3
|
| 1250 |
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value: 22.003
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| 1251 |
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| 1252 |
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value: 14.914
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| 1253 |
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- type: recall_at_1
|
| 1254 |
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value: 22.262
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| 1255 |
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|
| 1256 |
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value: 42.6
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| 1257 |
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- type: recall_at_100
|
| 1258 |
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value: 58.46
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| 1259 |
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- type: recall_at_1000
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| 1260 |
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value: 73.565
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| 1261 |
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- type: recall_at_3
|
| 1262 |
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value: 33.005
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| 1263 |
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- type: recall_at_5
|
| 1264 |
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value: 37.286
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| 1265 |
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- task:
|
| 1266 |
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type: Classification
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| 1267 |
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dataset:
|
| 1268 |
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type: mteb/imdb
|
| 1269 |
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name: MTEB ImdbClassification
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| 1270 |
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config: default
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| 1271 |
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split: test
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| 1272 |
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revision: 8d743909f834c38949e8323a8a6ce8721ea6c7f4
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| 1273 |
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metrics:
|
| 1274 |
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- type: accuracy
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| 1275 |
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value: 70.7156
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| 1276 |
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- type: ap
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| 1277 |
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value: 64.89470531959896
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| 1278 |
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- type: f1
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| 1279 |
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value: 70.53051887683772
|
| 1280 |
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- task:
|
| 1281 |
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type: Retrieval
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| 1282 |
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dataset:
|
| 1283 |
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type: msmarco
|
| 1284 |
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name: MTEB MSMARCO
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| 1285 |
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config: default
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| 1286 |
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split: dev
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| 1287 |
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revision: e6838a846e2408f22cf5cc337ebc83e0bcf77849
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| 1288 |
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metrics:
|
| 1289 |
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- type: map_at_1
|
| 1290 |
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value: 21.174
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| 1291 |
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| 1292 |
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value: 33.0
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| 1293 |
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| 1294 |
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value: 34.178
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| 1295 |
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| 1296 |
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value: 34.227000000000004
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| 1298 |
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value: 29.275000000000002
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| 1300 |
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value: 31.341
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| 1302 |
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value: 21.776999999999997
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| 1304 |
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value: 39.745999999999995
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| 1305 |
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| 1306 |
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value: 45.488
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| 1308 |
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value: 46.733999999999995
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| 1309 |
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- type: ndcg_at_3
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| 1310 |
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value: 32.086
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| 1311 |
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| 1312 |
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value: 35.792
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| 1313 |
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| 1314 |
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value: 21.776999999999997
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| 1315 |
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| 1316 |
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value: 6.324000000000001
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| 1317 |
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| 1318 |
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value: 0.922
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| 1319 |
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| 1320 |
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value: 0.10300000000000001
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| 1321 |
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| 1322 |
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value: 13.696
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| 1323 |
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| 1324 |
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value: 10.100000000000001
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| 1325 |
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- type: recall_at_1
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| 1326 |
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value: 21.174
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| 1327 |
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- type: recall_at_10
|
| 1328 |
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value: 60.488
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| 1329 |
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- type: recall_at_100
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| 1330 |
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value: 87.234
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| 1331 |
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- type: recall_at_1000
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| 1332 |
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value: 96.806
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| 1333 |
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- type: recall_at_3
|
| 1334 |
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value: 39.582
|
| 1335 |
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- type: recall_at_5
|
| 1336 |
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value: 48.474000000000004
|
| 1337 |
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- task:
|
| 1338 |
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type: Classification
|
| 1339 |
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dataset:
|
| 1340 |
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type: mteb/mtop_domain
|
| 1341 |
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name: MTEB MTOPDomainClassification (en)
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| 1342 |
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config: en
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| 1343 |
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split: test
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| 1344 |
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revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
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| 1345 |
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metrics:
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| 1346 |
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- type: accuracy
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| 1347 |
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value: 92.07934336525308
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| 1348 |
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- type: f1
|
| 1349 |
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value: 91.93440027035814
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| 1350 |
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- task:
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| 1351 |
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type: Classification
|
| 1352 |
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dataset:
|
| 1353 |
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type: mteb/mtop_intent
|
| 1354 |
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name: MTEB MTOPIntentClassification (en)
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| 1355 |
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config: en
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| 1356 |
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split: test
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| 1357 |
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revision: 6299947a7777084cc2d4b64235bf7190381ce755
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| 1358 |
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metrics:
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| 1359 |
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- type: accuracy
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| 1360 |
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value: 70.20975832193344
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| 1361 |
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- type: f1
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| 1362 |
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value: 48.571776628850074
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| 1363 |
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- task:
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| 1364 |
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type: Classification
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| 1365 |
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dataset:
|
| 1366 |
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type: mteb/amazon_massive_intent
|
| 1367 |
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name: MTEB MassiveIntentClassification (en)
|
| 1368 |
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config: en
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| 1369 |
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split: test
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| 1370 |
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revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
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| 1371 |
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metrics:
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| 1372 |
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- type: accuracy
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| 1373 |
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value: 69.56624075319435
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| 1374 |
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- type: f1
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| 1375 |
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value: 67.64419185784621
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| 1376 |
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- task:
|
| 1377 |
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type: Classification
|
| 1378 |
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dataset:
|
| 1379 |
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type: mteb/amazon_massive_scenario
|
| 1380 |
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name: MTEB MassiveScenarioClassification (en)
|
| 1381 |
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config: en
|
| 1382 |
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split: test
|
| 1383 |
+
revision: 7d571f92784cd94a019292a1f45445077d0ef634
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| 1384 |
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metrics:
|
| 1385 |
+
- type: accuracy
|
| 1386 |
+
value: 76.01210490921318
|
| 1387 |
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- type: f1
|
| 1388 |
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value: 75.1934366365826
|
| 1389 |
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- task:
|
| 1390 |
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type: Clustering
|
| 1391 |
+
dataset:
|
| 1392 |
+
type: mteb/medrxiv-clustering-p2p
|
| 1393 |
+
name: MTEB MedrxivClusteringP2P
|
| 1394 |
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config: default
|
| 1395 |
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split: test
|
| 1396 |
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revision: dcefc037ef84348e49b0d29109e891c01067226b
|
| 1397 |
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metrics:
|
| 1398 |
+
- type: v_measure
|
| 1399 |
+
value: 35.58002813186373
|
| 1400 |
+
- task:
|
| 1401 |
+
type: Clustering
|
| 1402 |
+
dataset:
|
| 1403 |
+
type: mteb/medrxiv-clustering-s2s
|
| 1404 |
+
name: MTEB MedrxivClusteringS2S
|
| 1405 |
+
config: default
|
| 1406 |
+
split: test
|
| 1407 |
+
revision: 3cd0e71dfbe09d4de0f9e5ecba43e7ce280959dc
|
| 1408 |
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metrics:
|
| 1409 |
+
- type: v_measure
|
| 1410 |
+
value: 32.872725562410444
|
| 1411 |
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- task:
|
| 1412 |
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type: Reranking
|
| 1413 |
+
dataset:
|
| 1414 |
+
type: mteb/mind_small
|
| 1415 |
+
name: MTEB MindSmallReranking
|
| 1416 |
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config: default
|
| 1417 |
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split: test
|
| 1418 |
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revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
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| 1419 |
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metrics:
|
| 1420 |
+
- type: map
|
| 1421 |
+
value: 30.965343604861328
|
| 1422 |
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- type: mrr
|
| 1423 |
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value: 31.933710165863594
|
| 1424 |
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- task:
|
| 1425 |
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type: Retrieval
|
| 1426 |
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dataset:
|
| 1427 |
+
type: nfcorpus
|
| 1428 |
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name: MTEB NFCorpus
|
| 1429 |
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config: default
|
| 1430 |
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split: test
|
| 1431 |
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revision: 7eb63cc0c1eb59324d709ebed25fcab851fa7610
|
| 1432 |
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metrics:
|
| 1433 |
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- type: map_at_1
|
| 1434 |
+
value: 4.938
|
| 1435 |
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- type: map_at_10
|
| 1436 |
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value: 12.034
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| 1437 |
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- type: map_at_100
|
| 1438 |
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value: 15.675
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| 1439 |
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- type: map_at_1000
|
| 1440 |
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value: 17.18
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| 1441 |
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- type: map_at_3
|
| 1442 |
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value: 8.471
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| 1443 |
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|
| 1444 |
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value: 10.128
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| 1445 |
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- type: ndcg_at_1
|
| 1446 |
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value: 40.402
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| 1447 |
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- type: ndcg_at_10
|
| 1448 |
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value: 33.289
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| 1449 |
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- type: ndcg_at_100
|
| 1450 |
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value: 31.496000000000002
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| 1451 |
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- type: ndcg_at_1000
|
| 1452 |
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value: 40.453
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| 1453 |
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- type: ndcg_at_3
|
| 1454 |
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value: 37.841
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| 1455 |
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- type: ndcg_at_5
|
| 1456 |
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value: 36.215
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| 1457 |
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- type: precision_at_1
|
| 1458 |
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value: 41.796
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| 1459 |
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- type: precision_at_10
|
| 1460 |
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value: 25.294
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| 1461 |
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- type: precision_at_100
|
| 1462 |
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value: 8.381
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| 1463 |
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- type: precision_at_1000
|
| 1464 |
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value: 2.1260000000000003
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| 1465 |
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- type: precision_at_3
|
| 1466 |
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value: 36.429
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| 1467 |
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- type: precision_at_5
|
| 1468 |
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value: 32.446000000000005
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| 1469 |
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- type: recall_at_1
|
| 1470 |
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value: 4.938
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| 1471 |
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- type: recall_at_10
|
| 1472 |
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value: 16.637
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| 1473 |
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- type: recall_at_100
|
| 1474 |
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value: 33.853
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| 1475 |
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- type: recall_at_1000
|
| 1476 |
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value: 66.07
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| 1477 |
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- type: recall_at_3
|
| 1478 |
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value: 9.818
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| 1479 |
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- type: recall_at_5
|
| 1480 |
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value: 12.544
|
| 1481 |
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- task:
|
| 1482 |
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type: Retrieval
|
| 1483 |
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dataset:
|
| 1484 |
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type: nq
|
| 1485 |
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name: MTEB NQ
|
| 1486 |
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config: default
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| 1487 |
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split: test
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| 1488 |
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revision: 6062aefc120bfe8ece5897809fb2e53bfe0d128c
|
| 1489 |
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metrics:
|
| 1490 |
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- type: map_at_1
|
| 1491 |
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value: 27.124
|
| 1492 |
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- type: map_at_10
|
| 1493 |
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value: 42.418
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| 1494 |
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- type: map_at_100
|
| 1495 |
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value: 43.633
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| 1496 |
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- type: map_at_1000
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| 1497 |
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value: 43.66
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| 1498 |
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- type: map_at_3
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| 1499 |
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value: 37.766
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| 1500 |
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- type: map_at_5
|
| 1501 |
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value: 40.482
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| 1502 |
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- type: ndcg_at_1
|
| 1503 |
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value: 30.794
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| 1504 |
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- type: ndcg_at_10
|
| 1505 |
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value: 50.449999999999996
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| 1506 |
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- type: ndcg_at_100
|
| 1507 |
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value: 55.437999999999995
|
| 1508 |
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- type: ndcg_at_1000
|
| 1509 |
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value: 56.084
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| 1510 |
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- type: ndcg_at_3
|
| 1511 |
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value: 41.678
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| 1512 |
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- type: ndcg_at_5
|
| 1513 |
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value: 46.257
|
| 1514 |
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- type: precision_at_1
|
| 1515 |
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value: 30.794
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| 1516 |
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- type: precision_at_10
|
| 1517 |
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value: 8.656
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| 1518 |
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- type: precision_at_100
|
| 1519 |
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value: 1.141
|
| 1520 |
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- type: precision_at_1000
|
| 1521 |
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value: 0.12
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| 1522 |
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- type: precision_at_3
|
| 1523 |
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value: 19.37
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| 1524 |
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- type: precision_at_5
|
| 1525 |
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value: 14.218
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| 1526 |
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- type: recall_at_1
|
| 1527 |
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value: 27.124
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| 1528 |
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- type: recall_at_10
|
| 1529 |
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value: 72.545
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| 1530 |
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- type: recall_at_100
|
| 1531 |
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value: 93.938
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| 1532 |
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- type: recall_at_1000
|
| 1533 |
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value: 98.788
|
| 1534 |
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- type: recall_at_3
|
| 1535 |
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value: 49.802
|
| 1536 |
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- type: recall_at_5
|
| 1537 |
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value: 60.426
|
| 1538 |
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- task:
|
| 1539 |
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type: Retrieval
|
| 1540 |
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dataset:
|
| 1541 |
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type: quora
|
| 1542 |
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name: MTEB QuoraRetrieval
|
| 1543 |
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config: default
|
| 1544 |
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split: test
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| 1545 |
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revision: 6205996560df11e3a3da9ab4f926788fc30a7db4
|
| 1546 |
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metrics:
|
| 1547 |
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- type: map_at_1
|
| 1548 |
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value: 69.33500000000001
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| 1549 |
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- type: map_at_10
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| 1550 |
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value: 83.554
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| 1551 |
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- type: map_at_100
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| 1552 |
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value: 84.237
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| 1553 |
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- type: map_at_1000
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| 1554 |
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value: 84.251
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| 1555 |
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- type: map_at_3
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| 1556 |
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value: 80.456
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| 1557 |
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- type: map_at_5
|
| 1558 |
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value: 82.395
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| 1559 |
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- type: ndcg_at_1
|
| 1560 |
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value: 80.06
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| 1561 |
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- type: ndcg_at_10
|
| 1562 |
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value: 87.46199999999999
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| 1563 |
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- type: ndcg_at_100
|
| 1564 |
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value: 88.774
|
| 1565 |
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- type: ndcg_at_1000
|
| 1566 |
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value: 88.864
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| 1567 |
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- type: ndcg_at_3
|
| 1568 |
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value: 84.437
|
| 1569 |
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- type: ndcg_at_5
|
| 1570 |
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value: 86.129
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| 1571 |
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- type: precision_at_1
|
| 1572 |
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value: 80.06
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| 1573 |
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- type: precision_at_10
|
| 1574 |
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value: 13.418
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| 1575 |
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- type: precision_at_100
|
| 1576 |
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value: 1.536
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| 1577 |
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- type: precision_at_1000
|
| 1578 |
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value: 0.157
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| 1579 |
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- type: precision_at_3
|
| 1580 |
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value: 37.103
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| 1581 |
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- type: precision_at_5
|
| 1582 |
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value: 24.522
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| 1583 |
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- type: recall_at_1
|
| 1584 |
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value: 69.33500000000001
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| 1585 |
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- type: recall_at_10
|
| 1586 |
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value: 95.03200000000001
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| 1587 |
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- type: recall_at_100
|
| 1588 |
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value: 99.559
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| 1589 |
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- type: recall_at_1000
|
| 1590 |
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value: 99.98700000000001
|
| 1591 |
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- type: recall_at_3
|
| 1592 |
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value: 86.404
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| 1593 |
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- type: recall_at_5
|
| 1594 |
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value: 91.12400000000001
|
| 1595 |
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- task:
|
| 1596 |
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type: Clustering
|
| 1597 |
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dataset:
|
| 1598 |
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type: mteb/reddit-clustering
|
| 1599 |
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name: MTEB RedditClustering
|
| 1600 |
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config: default
|
| 1601 |
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split: test
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| 1602 |
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revision: b2805658ae38990172679479369a78b86de8c390
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| 1603 |
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metrics:
|
| 1604 |
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- type: v_measure
|
| 1605 |
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value: 54.824256698437324
|
| 1606 |
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- task:
|
| 1607 |
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type: Clustering
|
| 1608 |
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dataset:
|
| 1609 |
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type: mteb/reddit-clustering-p2p
|
| 1610 |
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name: MTEB RedditClusteringP2P
|
| 1611 |
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config: default
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| 1612 |
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split: test
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| 1613 |
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revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
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| 1614 |
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metrics:
|
| 1615 |
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- type: v_measure
|
| 1616 |
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value: 56.768972678049366
|
| 1617 |
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- task:
|
| 1618 |
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type: Retrieval
|
| 1619 |
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dataset:
|
| 1620 |
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type: scidocs
|
| 1621 |
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name: MTEB SCIDOCS
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| 1622 |
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config: default
|
| 1623 |
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split: test
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| 1624 |
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revision: 5c59ef3e437a0a9651c8fe6fde943e7dce59fba5
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| 1625 |
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metrics:
|
| 1626 |
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- type: map_at_1
|
| 1627 |
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value: 5.192
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| 1628 |
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| 1629 |
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value: 14.426
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| 1631 |
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value: 17.18
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| 1632 |
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| 1633 |
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value: 17.580000000000002
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| 1634 |
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| 1635 |
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value: 9.94
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| 1636 |
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| 1637 |
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value: 12.077
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| 1638 |
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- type: ndcg_at_1
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| 1639 |
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value: 25.5
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| 1640 |
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- type: ndcg_at_10
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| 1641 |
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value: 23.765
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| 1642 |
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- type: ndcg_at_100
|
| 1643 |
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value: 33.664
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| 1644 |
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- type: ndcg_at_1000
|
| 1645 |
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value: 39.481
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| 1646 |
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- type: ndcg_at_3
|
| 1647 |
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value: 21.813
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| 1648 |
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- type: ndcg_at_5
|
| 1649 |
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value: 19.285
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| 1650 |
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- type: precision_at_1
|
| 1651 |
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value: 25.5
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| 1652 |
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|
| 1653 |
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value: 12.690000000000001
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| 1654 |
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- type: precision_at_100
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| 1655 |
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value: 2.71
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| 1656 |
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| 1657 |
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value: 0.409
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| 1658 |
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- type: precision_at_3
|
| 1659 |
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value: 20.732999999999997
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| 1660 |
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- type: precision_at_5
|
| 1661 |
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value: 17.24
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| 1662 |
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- type: recall_at_1
|
| 1663 |
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value: 5.192
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| 1664 |
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- type: recall_at_10
|
| 1665 |
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value: 25.712000000000003
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| 1666 |
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- type: recall_at_100
|
| 1667 |
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value: 54.99699999999999
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| 1668 |
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- type: recall_at_1000
|
| 1669 |
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value: 82.97200000000001
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| 1670 |
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- type: recall_at_3
|
| 1671 |
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value: 12.631999999999998
|
| 1672 |
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- type: recall_at_5
|
| 1673 |
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value: 17.497
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| 1674 |
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- task:
|
| 1675 |
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type: STS
|
| 1676 |
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dataset:
|
| 1677 |
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type: mteb/sickr-sts
|
| 1678 |
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name: MTEB SICK-R
|
| 1679 |
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config: default
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| 1680 |
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split: test
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| 1681 |
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revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
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| 1682 |
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metrics:
|
| 1683 |
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- type: cos_sim_pearson
|
| 1684 |
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value: 84.00280838354293
|
| 1685 |
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- type: cos_sim_spearman
|
| 1686 |
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value: 80.5854192844009
|
| 1687 |
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- type: euclidean_pearson
|
| 1688 |
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value: 80.55974827073891
|
| 1689 |
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- type: euclidean_spearman
|
| 1690 |
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value: 80.58541460172292
|
| 1691 |
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- type: manhattan_pearson
|
| 1692 |
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value: 80.27294578437488
|
| 1693 |
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- type: manhattan_spearman
|
| 1694 |
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value: 80.33176193921884
|
| 1695 |
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- task:
|
| 1696 |
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type: STS
|
| 1697 |
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dataset:
|
| 1698 |
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type: mteb/sts12-sts
|
| 1699 |
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name: MTEB STS12
|
| 1700 |
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config: default
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| 1701 |
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split: test
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| 1702 |
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revision: fdf84275bb8ce4b49c971d02e84dd1abc677a50f
|
| 1703 |
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metrics:
|
| 1704 |
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- type: cos_sim_pearson
|
| 1705 |
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value: 83.2801353818369
|
| 1706 |
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- type: cos_sim_spearman
|
| 1707 |
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value: 72.63427853822449
|
| 1708 |
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- type: euclidean_pearson
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| 1709 |
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value: 79.01343235899544
|
| 1710 |
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- type: euclidean_spearman
|
| 1711 |
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value: 72.63178302036903
|
| 1712 |
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- type: manhattan_pearson
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| 1713 |
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value: 78.65899981586094
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| 1714 |
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- type: manhattan_spearman
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| 1715 |
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value: 72.26646573268035
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| 1716 |
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- task:
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| 1717 |
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|
| 1718 |
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dataset:
|
| 1719 |
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type: mteb/sts13-sts
|
| 1720 |
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name: MTEB STS13
|
| 1721 |
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config: default
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| 1722 |
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split: test
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| 1723 |
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| 1724 |
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metrics:
|
| 1725 |
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|
| 1726 |
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value: 83.20700572036095
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| 1727 |
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| 1728 |
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| 1729 |
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- type: euclidean_pearson
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value: 82.82555353364394
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| 1731 |
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- type: euclidean_spearman
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| 1733 |
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value: 82.46034885462956
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value: 83.09829447251937
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| 1737 |
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| 1738 |
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| 1739 |
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dataset:
|
| 1740 |
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type: mteb/sts14-sts
|
| 1741 |
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| 1742 |
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| 1743 |
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split: test
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| 1744 |
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| 1745 |
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metrics:
|
| 1746 |
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| 1747 |
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value: 82.27113025749529
|
| 1748 |
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- type: cos_sim_spearman
|
| 1749 |
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value: 78.0001371342168
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| 1750 |
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- type: euclidean_pearson
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| 1751 |
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value: 80.62651938409732
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| 1752 |
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- type: euclidean_spearman
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| 1753 |
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value: 78.0001341029446
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| 1754 |
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- type: manhattan_pearson
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value: 80.25786381999085
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| 1756 |
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value: 77.68750207429126
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| 1758 |
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| 1759 |
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type: STS
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| 1760 |
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dataset:
|
| 1761 |
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type: mteb/sts15-sts
|
| 1762 |
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name: MTEB STS15
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| 1763 |
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config: default
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| 1764 |
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split: test
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| 1765 |
+
revision: 1cd7298cac12a96a373b6a2f18738bb3e739a9b6
|
| 1766 |
+
metrics:
|
| 1767 |
+
- type: cos_sim_pearson
|
| 1768 |
+
value: 84.98824030948605
|
| 1769 |
+
- type: cos_sim_spearman
|
| 1770 |
+
value: 85.66275391649481
|
| 1771 |
+
- type: euclidean_pearson
|
| 1772 |
+
value: 84.88733530073506
|
| 1773 |
+
- type: euclidean_spearman
|
| 1774 |
+
value: 85.66275062257034
|
| 1775 |
+
- type: manhattan_pearson
|
| 1776 |
+
value: 84.70100813924223
|
| 1777 |
+
- type: manhattan_spearman
|
| 1778 |
+
value: 85.50318526944764
|
| 1779 |
+
- task:
|
| 1780 |
+
type: STS
|
| 1781 |
+
dataset:
|
| 1782 |
+
type: mteb/sts16-sts
|
| 1783 |
+
name: MTEB STS16
|
| 1784 |
+
config: default
|
| 1785 |
+
split: test
|
| 1786 |
+
revision: 360a0b2dff98700d09e634a01e1cc1624d3e42cd
|
| 1787 |
+
metrics:
|
| 1788 |
+
- type: cos_sim_pearson
|
| 1789 |
+
value: 78.82478639193744
|
| 1790 |
+
- type: cos_sim_spearman
|
| 1791 |
+
value: 80.03011315645662
|
| 1792 |
+
- type: euclidean_pearson
|
| 1793 |
+
value: 79.84794502236802
|
| 1794 |
+
- type: euclidean_spearman
|
| 1795 |
+
value: 80.03011258077692
|
| 1796 |
+
- type: manhattan_pearson
|
| 1797 |
+
value: 79.47012152325492
|
| 1798 |
+
- type: manhattan_spearman
|
| 1799 |
+
value: 79.60652985087651
|
| 1800 |
+
- task:
|
| 1801 |
+
type: STS
|
| 1802 |
+
dataset:
|
| 1803 |
+
type: mteb/sts17-crosslingual-sts
|
| 1804 |
+
name: MTEB STS17 (en-en)
|
| 1805 |
+
config: en-en
|
| 1806 |
+
split: test
|
| 1807 |
+
revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
|
| 1808 |
+
metrics:
|
| 1809 |
+
- type: cos_sim_pearson
|
| 1810 |
+
value: 90.90804154377126
|
| 1811 |
+
- type: cos_sim_spearman
|
| 1812 |
+
value: 90.59523263123734
|
| 1813 |
+
- type: euclidean_pearson
|
| 1814 |
+
value: 89.8466957775513
|
| 1815 |
+
- type: euclidean_spearman
|
| 1816 |
+
value: 90.59523263123734
|
| 1817 |
+
- type: manhattan_pearson
|
| 1818 |
+
value: 89.82268413033941
|
| 1819 |
+
- type: manhattan_spearman
|
| 1820 |
+
value: 90.68706496728889
|
| 1821 |
+
- task:
|
| 1822 |
+
type: STS
|
| 1823 |
+
dataset:
|
| 1824 |
+
type: mteb/sts22-crosslingual-sts
|
| 1825 |
+
name: MTEB STS22 (en)
|
| 1826 |
+
config: en
|
| 1827 |
+
split: test
|
| 1828 |
+
revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
|
| 1829 |
+
metrics:
|
| 1830 |
+
- type: cos_sim_pearson
|
| 1831 |
+
value: 66.78771571400975
|
| 1832 |
+
- type: cos_sim_spearman
|
| 1833 |
+
value: 67.94534221542501
|
| 1834 |
+
- type: euclidean_pearson
|
| 1835 |
+
value: 68.62534447097993
|
| 1836 |
+
- type: euclidean_spearman
|
| 1837 |
+
value: 67.94534221542501
|
| 1838 |
+
- type: manhattan_pearson
|
| 1839 |
+
value: 68.35916011329631
|
| 1840 |
+
- type: manhattan_spearman
|
| 1841 |
+
value: 67.58212723406085
|
| 1842 |
+
- task:
|
| 1843 |
+
type: STS
|
| 1844 |
+
dataset:
|
| 1845 |
+
type: mteb/stsbenchmark-sts
|
| 1846 |
+
name: MTEB STSBenchmark
|
| 1847 |
+
config: default
|
| 1848 |
+
split: test
|
| 1849 |
+
revision: 8913289635987208e6e7c72789e4be2fe94b6abd
|
| 1850 |
+
metrics:
|
| 1851 |
+
- type: cos_sim_pearson
|
| 1852 |
+
value: 84.03996099800993
|
| 1853 |
+
- type: cos_sim_spearman
|
| 1854 |
+
value: 83.421898505618
|
| 1855 |
+
- type: euclidean_pearson
|
| 1856 |
+
value: 83.78671249317563
|
| 1857 |
+
- type: euclidean_spearman
|
| 1858 |
+
value: 83.4219042133061
|
| 1859 |
+
- type: manhattan_pearson
|
| 1860 |
+
value: 83.44085827249334
|
| 1861 |
+
- type: manhattan_spearman
|
| 1862 |
+
value: 83.02901331535297
|
| 1863 |
+
- task:
|
| 1864 |
+
type: Reranking
|
| 1865 |
+
dataset:
|
| 1866 |
+
type: mteb/scidocs-reranking
|
| 1867 |
+
name: MTEB SciDocsRR
|
| 1868 |
+
config: default
|
| 1869 |
+
split: test
|
| 1870 |
+
revision: 56a6d0140cf6356659e2a7c1413286a774468d44
|
| 1871 |
+
metrics:
|
| 1872 |
+
- type: map
|
| 1873 |
+
value: 88.65396986895777
|
| 1874 |
+
- type: mrr
|
| 1875 |
+
value: 96.60209525405604
|
| 1876 |
+
- task:
|
| 1877 |
+
type: Retrieval
|
| 1878 |
+
dataset:
|
| 1879 |
+
type: scifact
|
| 1880 |
+
name: MTEB SciFact
|
| 1881 |
+
config: default
|
| 1882 |
+
split: test
|
| 1883 |
+
revision: a75ae049398addde9b70f6b268875f5cbce99089
|
| 1884 |
+
metrics:
|
| 1885 |
+
- type: map_at_1
|
| 1886 |
+
value: 51.456
|
| 1887 |
+
- type: map_at_10
|
| 1888 |
+
value: 60.827
|
| 1889 |
+
- type: map_at_100
|
| 1890 |
+
value: 61.595
|
| 1891 |
+
- type: map_at_1000
|
| 1892 |
+
value: 61.629999999999995
|
| 1893 |
+
- type: map_at_3
|
| 1894 |
+
value: 57.518
|
| 1895 |
+
- type: map_at_5
|
| 1896 |
+
value: 59.435
|
| 1897 |
+
- type: ndcg_at_1
|
| 1898 |
+
value: 53.333
|
| 1899 |
+
- type: ndcg_at_10
|
| 1900 |
+
value: 65.57
|
| 1901 |
+
- type: ndcg_at_100
|
| 1902 |
+
value: 68.911
|
| 1903 |
+
- type: ndcg_at_1000
|
| 1904 |
+
value: 69.65299999999999
|
| 1905 |
+
- type: ndcg_at_3
|
| 1906 |
+
value: 60.009
|
| 1907 |
+
- type: ndcg_at_5
|
| 1908 |
+
value: 62.803
|
| 1909 |
+
- type: precision_at_1
|
| 1910 |
+
value: 53.333
|
| 1911 |
+
- type: precision_at_10
|
| 1912 |
+
value: 8.933
|
| 1913 |
+
- type: precision_at_100
|
| 1914 |
+
value: 1.0699999999999998
|
| 1915 |
+
- type: precision_at_1000
|
| 1916 |
+
value: 0.11299999999999999
|
| 1917 |
+
- type: precision_at_3
|
| 1918 |
+
value: 23.333000000000002
|
| 1919 |
+
- type: precision_at_5
|
| 1920 |
+
value: 15.8
|
| 1921 |
+
- type: recall_at_1
|
| 1922 |
+
value: 51.456
|
| 1923 |
+
- type: recall_at_10
|
| 1924 |
+
value: 79.011
|
| 1925 |
+
- type: recall_at_100
|
| 1926 |
+
value: 94.167
|
| 1927 |
+
- type: recall_at_1000
|
| 1928 |
+
value: 99.667
|
| 1929 |
+
- type: recall_at_3
|
| 1930 |
+
value: 64.506
|
| 1931 |
+
- type: recall_at_5
|
| 1932 |
+
value: 71.211
|
| 1933 |
+
- task:
|
| 1934 |
+
type: PairClassification
|
| 1935 |
+
dataset:
|
| 1936 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
| 1937 |
+
name: MTEB SprintDuplicateQuestions
|
| 1938 |
+
config: default
|
| 1939 |
+
split: test
|
| 1940 |
+
revision: 5a8256d0dff9c4bd3be3ba3e67e4e70173f802ea
|
| 1941 |
+
metrics:
|
| 1942 |
+
- type: cos_sim_accuracy
|
| 1943 |
+
value: 99.65940594059406
|
| 1944 |
+
- type: cos_sim_ap
|
| 1945 |
+
value: 90.1455141683116
|
| 1946 |
+
- type: cos_sim_f1
|
| 1947 |
+
value: 82.26044226044226
|
| 1948 |
+
- type: cos_sim_precision
|
| 1949 |
+
value: 80.8695652173913
|
| 1950 |
+
- type: cos_sim_recall
|
| 1951 |
+
value: 83.7
|
| 1952 |
+
- type: dot_accuracy
|
| 1953 |
+
value: 99.65940594059406
|
| 1954 |
+
- type: dot_ap
|
| 1955 |
+
value: 90.1455141683116
|
| 1956 |
+
- type: dot_f1
|
| 1957 |
+
value: 82.26044226044226
|
| 1958 |
+
- type: dot_precision
|
| 1959 |
+
value: 80.8695652173913
|
| 1960 |
+
- type: dot_recall
|
| 1961 |
+
value: 83.7
|
| 1962 |
+
- type: euclidean_accuracy
|
| 1963 |
+
value: 99.65940594059406
|
| 1964 |
+
- type: euclidean_ap
|
| 1965 |
+
value: 90.14551416831162
|
| 1966 |
+
- type: euclidean_f1
|
| 1967 |
+
value: 82.26044226044226
|
| 1968 |
+
- type: euclidean_precision
|
| 1969 |
+
value: 80.8695652173913
|
| 1970 |
+
- type: euclidean_recall
|
| 1971 |
+
value: 83.7
|
| 1972 |
+
- type: manhattan_accuracy
|
| 1973 |
+
value: 99.64950495049504
|
| 1974 |
+
- type: manhattan_ap
|
| 1975 |
+
value: 89.5492617367771
|
| 1976 |
+
- type: manhattan_f1
|
| 1977 |
+
value: 81.58280410356619
|
| 1978 |
+
- type: manhattan_precision
|
| 1979 |
+
value: 79.75167144221585
|
| 1980 |
+
- type: manhattan_recall
|
| 1981 |
+
value: 83.5
|
| 1982 |
+
- type: max_accuracy
|
| 1983 |
+
value: 99.65940594059406
|
| 1984 |
+
- type: max_ap
|
| 1985 |
+
value: 90.14551416831162
|
| 1986 |
+
- type: max_f1
|
| 1987 |
+
value: 82.26044226044226
|
| 1988 |
+
- task:
|
| 1989 |
+
type: Clustering
|
| 1990 |
+
dataset:
|
| 1991 |
+
type: mteb/stackexchange-clustering
|
| 1992 |
+
name: MTEB StackExchangeClustering
|
| 1993 |
+
config: default
|
| 1994 |
+
split: test
|
| 1995 |
+
revision: 70a89468f6dccacc6aa2b12a6eac54e74328f235
|
| 1996 |
+
metrics:
|
| 1997 |
+
- type: v_measure
|
| 1998 |
+
value: 53.80048409076929
|
| 1999 |
+
- task:
|
| 2000 |
+
type: Clustering
|
| 2001 |
+
dataset:
|
| 2002 |
+
type: mteb/stackexchange-clustering-p2p
|
| 2003 |
+
name: MTEB StackExchangeClusteringP2P
|
| 2004 |
+
config: default
|
| 2005 |
+
split: test
|
| 2006 |
+
revision: d88009ab563dd0b16cfaf4436abaf97fa3550cf0
|
| 2007 |
+
metrics:
|
| 2008 |
+
- type: v_measure
|
| 2009 |
+
value: 34.280269334397545
|
| 2010 |
+
- task:
|
| 2011 |
+
type: Reranking
|
| 2012 |
+
dataset:
|
| 2013 |
+
type: mteb/stackoverflowdupquestions-reranking
|
| 2014 |
+
name: MTEB StackOverflowDupQuestions
|
| 2015 |
+
config: default
|
| 2016 |
+
split: test
|
| 2017 |
+
revision: ef807ea29a75ec4f91b50fd4191cb4ee4589a9f9
|
| 2018 |
+
metrics:
|
| 2019 |
+
- type: map
|
| 2020 |
+
value: 51.97907654945493
|
| 2021 |
+
- type: mrr
|
| 2022 |
+
value: 52.82873376623376
|
| 2023 |
+
- task:
|
| 2024 |
+
type: Summarization
|
| 2025 |
+
dataset:
|
| 2026 |
+
type: mteb/summeval
|
| 2027 |
+
name: MTEB SummEval
|
| 2028 |
+
config: default
|
| 2029 |
+
split: test
|
| 2030 |
+
revision: 8753c2788d36c01fc6f05d03fe3f7268d63f9122
|
| 2031 |
+
metrics:
|
| 2032 |
+
- type: cos_sim_pearson
|
| 2033 |
+
value: 28.364293841556304
|
| 2034 |
+
- type: cos_sim_spearman
|
| 2035 |
+
value: 27.485869639926136
|
| 2036 |
+
- type: dot_pearson
|
| 2037 |
+
value: 28.364295910221145
|
| 2038 |
+
- type: dot_spearman
|
| 2039 |
+
value: 27.485869639926136
|
| 2040 |
+
- task:
|
| 2041 |
+
type: Retrieval
|
| 2042 |
+
dataset:
|
| 2043 |
+
type: trec-covid
|
| 2044 |
+
name: MTEB TRECCOVID
|
| 2045 |
+
config: default
|
| 2046 |
+
split: test
|
| 2047 |
+
revision: 2c8041b2c07a79b6f7ba8fe6acc72e5d9f92d217
|
| 2048 |
+
metrics:
|
| 2049 |
+
- type: map_at_1
|
| 2050 |
+
value: 0.19499999999999998
|
| 2051 |
+
- type: map_at_10
|
| 2052 |
+
value: 1.218
|
| 2053 |
+
- type: map_at_100
|
| 2054 |
+
value: 7.061000000000001
|
| 2055 |
+
- type: map_at_1000
|
| 2056 |
+
value: 19.735
|
| 2057 |
+
- type: map_at_3
|
| 2058 |
+
value: 0.46499999999999997
|
| 2059 |
+
- type: map_at_5
|
| 2060 |
+
value: 0.672
|
| 2061 |
+
- type: ndcg_at_1
|
| 2062 |
+
value: 60.0
|
| 2063 |
+
- type: ndcg_at_10
|
| 2064 |
+
value: 51.32600000000001
|
| 2065 |
+
- type: ndcg_at_100
|
| 2066 |
+
value: 41.74
|
| 2067 |
+
- type: ndcg_at_1000
|
| 2068 |
+
value: 43.221
|
| 2069 |
+
- type: ndcg_at_3
|
| 2070 |
+
value: 54.989
|
| 2071 |
+
- type: ndcg_at_5
|
| 2072 |
+
value: 52.905
|
| 2073 |
+
- type: precision_at_1
|
| 2074 |
+
value: 66.0
|
| 2075 |
+
- type: precision_at_10
|
| 2076 |
+
value: 55.60000000000001
|
| 2077 |
+
- type: precision_at_100
|
| 2078 |
+
value: 43.34
|
| 2079 |
+
- type: precision_at_1000
|
| 2080 |
+
value: 19.994
|
| 2081 |
+
- type: precision_at_3
|
| 2082 |
+
value: 59.333000000000006
|
| 2083 |
+
- type: precision_at_5
|
| 2084 |
+
value: 57.199999999999996
|
| 2085 |
+
- type: recall_at_1
|
| 2086 |
+
value: 0.19499999999999998
|
| 2087 |
+
- type: recall_at_10
|
| 2088 |
+
value: 1.473
|
| 2089 |
+
- type: recall_at_100
|
| 2090 |
+
value: 10.596
|
| 2091 |
+
- type: recall_at_1000
|
| 2092 |
+
value: 42.466
|
| 2093 |
+
- type: recall_at_3
|
| 2094 |
+
value: 0.49899999999999994
|
| 2095 |
+
- type: recall_at_5
|
| 2096 |
+
value: 0.76
|
| 2097 |
+
- task:
|
| 2098 |
+
type: Retrieval
|
| 2099 |
+
dataset:
|
| 2100 |
+
type: webis-touche2020
|
| 2101 |
+
name: MTEB Touche2020
|
| 2102 |
+
config: default
|
| 2103 |
+
split: test
|
| 2104 |
+
revision: 527b7d77e16e343303e68cb6af11d6e18b9f7b3b
|
| 2105 |
+
metrics:
|
| 2106 |
+
- type: map_at_1
|
| 2107 |
+
value: 1.997
|
| 2108 |
+
- type: map_at_10
|
| 2109 |
+
value: 7.5569999999999995
|
| 2110 |
+
- type: map_at_100
|
| 2111 |
+
value: 12.238
|
| 2112 |
+
- type: map_at_1000
|
| 2113 |
+
value: 13.773
|
| 2114 |
+
- type: map_at_3
|
| 2115 |
+
value: 4.334
|
| 2116 |
+
- type: map_at_5
|
| 2117 |
+
value: 5.5
|
| 2118 |
+
- type: ndcg_at_1
|
| 2119 |
+
value: 22.448999999999998
|
| 2120 |
+
- type: ndcg_at_10
|
| 2121 |
+
value: 19.933999999999997
|
| 2122 |
+
- type: ndcg_at_100
|
| 2123 |
+
value: 30.525999999999996
|
| 2124 |
+
- type: ndcg_at_1000
|
| 2125 |
+
value: 43.147999999999996
|
| 2126 |
+
- type: ndcg_at_3
|
| 2127 |
+
value: 22.283
|
| 2128 |
+
- type: ndcg_at_5
|
| 2129 |
+
value: 21.224
|
| 2130 |
+
- type: precision_at_1
|
| 2131 |
+
value: 24.490000000000002
|
| 2132 |
+
- type: precision_at_10
|
| 2133 |
+
value: 17.551
|
| 2134 |
+
- type: precision_at_100
|
| 2135 |
+
value: 6.4079999999999995
|
| 2136 |
+
- type: precision_at_1000
|
| 2137 |
+
value: 1.463
|
| 2138 |
+
- type: precision_at_3
|
| 2139 |
+
value: 23.128999999999998
|
| 2140 |
+
- type: precision_at_5
|
| 2141 |
+
value: 20.816000000000003
|
| 2142 |
+
- type: recall_at_1
|
| 2143 |
+
value: 1.997
|
| 2144 |
+
- type: recall_at_10
|
| 2145 |
+
value: 13.001999999999999
|
| 2146 |
+
- type: recall_at_100
|
| 2147 |
+
value: 40.98
|
| 2148 |
+
- type: recall_at_1000
|
| 2149 |
+
value: 79.40899999999999
|
| 2150 |
+
- type: recall_at_3
|
| 2151 |
+
value: 5.380999999999999
|
| 2152 |
+
- type: recall_at_5
|
| 2153 |
+
value: 7.721
|
| 2154 |
+
- task:
|
| 2155 |
+
type: Classification
|
| 2156 |
+
dataset:
|
| 2157 |
+
type: mteb/toxic_conversations_50k
|
| 2158 |
+
name: MTEB ToxicConversationsClassification
|
| 2159 |
+
config: default
|
| 2160 |
+
split: test
|
| 2161 |
+
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
|
| 2162 |
+
metrics:
|
| 2163 |
+
- type: accuracy
|
| 2164 |
+
value: 60.861200000000004
|
| 2165 |
+
- type: ap
|
| 2166 |
+
value: 11.39641747026629
|
| 2167 |
+
- type: f1
|
| 2168 |
+
value: 47.80230380517065
|
| 2169 |
+
- task:
|
| 2170 |
+
type: Classification
|
| 2171 |
+
dataset:
|
| 2172 |
+
type: mteb/tweet_sentiment_extraction
|
| 2173 |
+
name: MTEB TweetSentimentExtractionClassification
|
| 2174 |
+
config: default
|
| 2175 |
+
split: test
|
| 2176 |
+
revision: 62146448f05be9e52a36b8ee9936447ea787eede
|
| 2177 |
+
metrics:
|
| 2178 |
+
- type: accuracy
|
| 2179 |
+
value: 55.464063384267114
|
| 2180 |
+
- type: f1
|
| 2181 |
+
value: 55.759039643764666
|
| 2182 |
+
- task:
|
| 2183 |
+
type: Clustering
|
| 2184 |
+
dataset:
|
| 2185 |
+
type: mteb/twentynewsgroups-clustering
|
| 2186 |
+
name: MTEB TwentyNewsgroupsClustering
|
| 2187 |
+
config: default
|
| 2188 |
+
split: test
|
| 2189 |
+
revision: 091a54f9a36281ce7d6590ec8c75dd485e7e01d4
|
| 2190 |
+
metrics:
|
| 2191 |
+
- type: v_measure
|
| 2192 |
+
value: 49.74455348083809
|
| 2193 |
+
- task:
|
| 2194 |
+
type: PairClassification
|
| 2195 |
+
dataset:
|
| 2196 |
+
type: mteb/twittersemeval2015-pairclassification
|
| 2197 |
+
name: MTEB TwitterSemEval2015
|
| 2198 |
+
config: default
|
| 2199 |
+
split: test
|
| 2200 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
| 2201 |
+
metrics:
|
| 2202 |
+
- type: cos_sim_accuracy
|
| 2203 |
+
value: 86.07617571675507
|
| 2204 |
+
- type: cos_sim_ap
|
| 2205 |
+
value: 73.85398650568216
|
| 2206 |
+
- type: cos_sim_f1
|
| 2207 |
+
value: 68.50702798531087
|
| 2208 |
+
- type: cos_sim_precision
|
| 2209 |
+
value: 65.86316045775506
|
| 2210 |
+
- type: cos_sim_recall
|
| 2211 |
+
value: 71.37203166226914
|
| 2212 |
+
- type: dot_accuracy
|
| 2213 |
+
value: 86.07617571675507
|
| 2214 |
+
- type: dot_ap
|
| 2215 |
+
value: 73.85398346238429
|
| 2216 |
+
- type: dot_f1
|
| 2217 |
+
value: 68.50702798531087
|
| 2218 |
+
- type: dot_precision
|
| 2219 |
+
value: 65.86316045775506
|
| 2220 |
+
- type: dot_recall
|
| 2221 |
+
value: 71.37203166226914
|
| 2222 |
+
- type: euclidean_accuracy
|
| 2223 |
+
value: 86.07617571675507
|
| 2224 |
+
- type: euclidean_ap
|
| 2225 |
+
value: 73.85398625060357
|
| 2226 |
+
- type: euclidean_f1
|
| 2227 |
+
value: 68.50702798531087
|
| 2228 |
+
- type: euclidean_precision
|
| 2229 |
+
value: 65.86316045775506
|
| 2230 |
+
- type: euclidean_recall
|
| 2231 |
+
value: 71.37203166226914
|
| 2232 |
+
- type: manhattan_accuracy
|
| 2233 |
+
value: 85.98676759849795
|
| 2234 |
+
- type: manhattan_ap
|
| 2235 |
+
value: 73.86874126878737
|
| 2236 |
+
- type: manhattan_f1
|
| 2237 |
+
value: 68.55096559662361
|
| 2238 |
+
- type: manhattan_precision
|
| 2239 |
+
value: 66.51774633904195
|
| 2240 |
+
- type: manhattan_recall
|
| 2241 |
+
value: 70.71240105540898
|
| 2242 |
+
- type: max_accuracy
|
| 2243 |
+
value: 86.07617571675507
|
| 2244 |
+
- type: max_ap
|
| 2245 |
+
value: 73.86874126878737
|
| 2246 |
+
- type: max_f1
|
| 2247 |
+
value: 68.55096559662361
|
| 2248 |
+
- task:
|
| 2249 |
+
type: PairClassification
|
| 2250 |
+
dataset:
|
| 2251 |
+
type: mteb/twitterurlcorpus-pairclassification
|
| 2252 |
+
name: MTEB TwitterURLCorpus
|
| 2253 |
+
config: default
|
| 2254 |
+
split: test
|
| 2255 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
| 2256 |
+
metrics:
|
| 2257 |
+
- type: cos_sim_accuracy
|
| 2258 |
+
value: 88.51631932316529
|
| 2259 |
+
- type: cos_sim_ap
|
| 2260 |
+
value: 85.10831084479727
|
| 2261 |
+
- type: cos_sim_f1
|
| 2262 |
+
value: 77.14563397129186
|
| 2263 |
+
- type: cos_sim_precision
|
| 2264 |
+
value: 74.9709386806161
|
| 2265 |
+
- type: cos_sim_recall
|
| 2266 |
+
value: 79.45026178010471
|
| 2267 |
+
- type: dot_accuracy
|
| 2268 |
+
value: 88.51631932316529
|
| 2269 |
+
- type: dot_ap
|
| 2270 |
+
value: 85.10831188797107
|
| 2271 |
+
- type: dot_f1
|
| 2272 |
+
value: 77.14563397129186
|
| 2273 |
+
- type: dot_precision
|
| 2274 |
+
value: 74.9709386806161
|
| 2275 |
+
- type: dot_recall
|
| 2276 |
+
value: 79.45026178010471
|
| 2277 |
+
- type: euclidean_accuracy
|
| 2278 |
+
value: 88.51631932316529
|
| 2279 |
+
- type: euclidean_ap
|
| 2280 |
+
value: 85.10829618408616
|
| 2281 |
+
- type: euclidean_f1
|
| 2282 |
+
value: 77.14563397129186
|
| 2283 |
+
- type: euclidean_precision
|
| 2284 |
+
value: 74.9709386806161
|
| 2285 |
+
- type: euclidean_recall
|
| 2286 |
+
value: 79.45026178010471
|
| 2287 |
+
- type: manhattan_accuracy
|
| 2288 |
+
value: 88.50467652423643
|
| 2289 |
+
- type: manhattan_ap
|
| 2290 |
+
value: 85.08329502055064
|
| 2291 |
+
- type: manhattan_f1
|
| 2292 |
+
value: 77.11157455683002
|
| 2293 |
+
- type: manhattan_precision
|
| 2294 |
+
value: 74.67541834968263
|
| 2295 |
+
- type: manhattan_recall
|
| 2296 |
+
value: 79.71204188481676
|
| 2297 |
+
- type: max_accuracy
|
| 2298 |
+
value: 88.51631932316529
|
| 2299 |
+
- type: max_ap
|
| 2300 |
+
value: 85.10831188797107
|
| 2301 |
+
- type: max_f1
|
| 2302 |
+
value: 77.14563397129186
|
| 2303 |
---
|
| 2304 |
|
| 2305 |
|
|
|
|
| 2364 |
|
| 2365 |
## Evaluation Results
|
| 2366 |
|
| 2367 |
+
For an automated evaluation of this model, see *MTEB*: https://huggingface.co/spaces/mteb/leaderboard or the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=sentence-transformers/all-MiniLM-L12-v2)
|
| 2368 |
|
| 2369 |
------
|
| 2370 |
|