Update README.md
Browse files
README.md
CHANGED
|
@@ -50,6 +50,62 @@ model-index:
|
|
| 50 |
value: 48.214
|
| 51 |
- type: f1
|
| 52 |
value: 47.57084372829096
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 53 |
- task:
|
| 54 |
type: Classification
|
| 55 |
dataset:
|
|
@@ -63,6 +119,28 @@ model-index:
|
|
| 63 |
value: 86.35064935064935
|
| 64 |
- type: f1
|
| 65 |
value: 86.32782396028989
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 66 |
- task:
|
| 67 |
type: Classification
|
| 68 |
dataset:
|
|
@@ -143,6 +221,342 @@ model-index:
|
|
| 143 |
value: 78.9340954942838
|
| 144 |
- type: f1
|
| 145 |
value: 79.04036413238218
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 146 |
- task:
|
| 147 |
type: Classification
|
| 148 |
dataset:
|
|
@@ -171,6 +585,127 @@ model-index:
|
|
| 171 |
value: 59.67176004527447
|
| 172 |
- type: f1
|
| 173 |
value: 59.97320225890037
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 174 |
---
|
| 175 |
This is the quantized (INT8) ONNX variant of the [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) embeddings model created with [DeepSparse Optimum](https://github.com/neuralmagic/optimum-deepsparse) for ONNX export/inference pipeline and Neural Magic's [Sparsify](https://github.com/neuralmagic/sparsify) for one-shot quantization.
|
| 176 |
|
|
|
|
| 50 |
value: 48.214
|
| 51 |
- type: f1
|
| 52 |
value: 47.57084372829096
|
| 53 |
+
- task:
|
| 54 |
+
type: Clustering
|
| 55 |
+
dataset:
|
| 56 |
+
type: mteb/arxiv-clustering-p2p
|
| 57 |
+
name: MTEB ArxivClusteringP2P
|
| 58 |
+
config: default
|
| 59 |
+
split: test
|
| 60 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
| 61 |
+
metrics:
|
| 62 |
+
- type: v_measure
|
| 63 |
+
value: 48.499816497755646
|
| 64 |
+
- task:
|
| 65 |
+
type: Clustering
|
| 66 |
+
dataset:
|
| 67 |
+
type: mteb/arxiv-clustering-s2s
|
| 68 |
+
name: MTEB ArxivClusteringS2S
|
| 69 |
+
config: default
|
| 70 |
+
split: test
|
| 71 |
+
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
| 72 |
+
metrics:
|
| 73 |
+
- type: v_measure
|
| 74 |
+
value: 42.006939120636034
|
| 75 |
+
- task:
|
| 76 |
+
type: Reranking
|
| 77 |
+
dataset:
|
| 78 |
+
type: mteb/askubuntudupquestions-reranking
|
| 79 |
+
name: MTEB AskUbuntuDupQuestions
|
| 80 |
+
config: default
|
| 81 |
+
split: test
|
| 82 |
+
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
| 83 |
+
metrics:
|
| 84 |
+
- type: map
|
| 85 |
+
value: 62.390343953329875
|
| 86 |
+
- type: mrr
|
| 87 |
+
value: 75.69922613551422
|
| 88 |
+
- task:
|
| 89 |
+
type: STS
|
| 90 |
+
dataset:
|
| 91 |
+
type: mteb/biosses-sts
|
| 92 |
+
name: MTEB BIOSSES
|
| 93 |
+
config: default
|
| 94 |
+
split: test
|
| 95 |
+
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
| 96 |
+
metrics:
|
| 97 |
+
- type: cos_sim_pearson
|
| 98 |
+
value: 89.03408553833623
|
| 99 |
+
- type: cos_sim_spearman
|
| 100 |
+
value: 86.71221676053791
|
| 101 |
+
- type: euclidean_pearson
|
| 102 |
+
value: 87.81477796215844
|
| 103 |
+
- type: euclidean_spearman
|
| 104 |
+
value: 87.28994076774481
|
| 105 |
+
- type: manhattan_pearson
|
| 106 |
+
value: 87.76204756059836
|
| 107 |
+
- type: manhattan_spearman
|
| 108 |
+
value: 87.1971675695072
|
| 109 |
- task:
|
| 110 |
type: Classification
|
| 111 |
dataset:
|
|
|
|
| 119 |
value: 86.35064935064935
|
| 120 |
- type: f1
|
| 121 |
value: 86.32782396028989
|
| 122 |
+
- task:
|
| 123 |
+
type: Clustering
|
| 124 |
+
dataset:
|
| 125 |
+
type: mteb/biorxiv-clustering-p2p
|
| 126 |
+
name: MTEB BiorxivClusteringP2P
|
| 127 |
+
config: default
|
| 128 |
+
split: test
|
| 129 |
+
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
| 130 |
+
metrics:
|
| 131 |
+
- type: v_measure
|
| 132 |
+
value: 39.299558776859485
|
| 133 |
+
- task:
|
| 134 |
+
type: Clustering
|
| 135 |
+
dataset:
|
| 136 |
+
type: mteb/biorxiv-clustering-s2s
|
| 137 |
+
name: MTEB BiorxivClusteringS2S
|
| 138 |
+
config: default
|
| 139 |
+
split: test
|
| 140 |
+
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
| 141 |
+
metrics:
|
| 142 |
+
- type: v_measure
|
| 143 |
+
value: 35.64603198816062
|
| 144 |
- task:
|
| 145 |
type: Classification
|
| 146 |
dataset:
|
|
|
|
| 221 |
value: 78.9340954942838
|
| 222 |
- type: f1
|
| 223 |
value: 79.04036413238218
|
| 224 |
+
- task:
|
| 225 |
+
type: Clustering
|
| 226 |
+
dataset:
|
| 227 |
+
type: mteb/medrxiv-clustering-p2p
|
| 228 |
+
name: MTEB MedrxivClusteringP2P
|
| 229 |
+
config: default
|
| 230 |
+
split: test
|
| 231 |
+
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
| 232 |
+
metrics:
|
| 233 |
+
- type: v_measure
|
| 234 |
+
value: 32.80025982143821
|
| 235 |
+
- task:
|
| 236 |
+
type: Clustering
|
| 237 |
+
dataset:
|
| 238 |
+
type: mteb/medrxiv-clustering-s2s
|
| 239 |
+
name: MTEB MedrxivClusteringS2S
|
| 240 |
+
config: default
|
| 241 |
+
split: test
|
| 242 |
+
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
| 243 |
+
metrics:
|
| 244 |
+
- type: v_measure
|
| 245 |
+
value: 30.956464446009623
|
| 246 |
+
- task:
|
| 247 |
+
type: Clustering
|
| 248 |
+
dataset:
|
| 249 |
+
type: mteb/reddit-clustering
|
| 250 |
+
name: MTEB RedditClustering
|
| 251 |
+
config: default
|
| 252 |
+
split: test
|
| 253 |
+
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
| 254 |
+
metrics:
|
| 255 |
+
- type: v_measure
|
| 256 |
+
value: 55.693914682185365
|
| 257 |
+
- task:
|
| 258 |
+
type: Clustering
|
| 259 |
+
dataset:
|
| 260 |
+
type: mteb/reddit-clustering-p2p
|
| 261 |
+
name: MTEB RedditClusteringP2P
|
| 262 |
+
config: default
|
| 263 |
+
split: test
|
| 264 |
+
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
| 265 |
+
metrics:
|
| 266 |
+
- type: v_measure
|
| 267 |
+
value: 62.32723620518647
|
| 268 |
+
- task:
|
| 269 |
+
type: STS
|
| 270 |
+
dataset:
|
| 271 |
+
type: mteb/sickr-sts
|
| 272 |
+
name: MTEB SICK-R
|
| 273 |
+
config: default
|
| 274 |
+
split: test
|
| 275 |
+
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
| 276 |
+
metrics:
|
| 277 |
+
- type: cos_sim_pearson
|
| 278 |
+
value: 84.70275347034692
|
| 279 |
+
- type: cos_sim_spearman
|
| 280 |
+
value: 80.06126639668393
|
| 281 |
+
- type: euclidean_pearson
|
| 282 |
+
value: 82.18370726102707
|
| 283 |
+
- type: euclidean_spearman
|
| 284 |
+
value: 80.05483013524909
|
| 285 |
+
- type: manhattan_pearson
|
| 286 |
+
value: 82.11962032129463
|
| 287 |
+
- type: manhattan_spearman
|
| 288 |
+
value: 79.97174232961949
|
| 289 |
+
- task:
|
| 290 |
+
type: STS
|
| 291 |
+
dataset:
|
| 292 |
+
type: mteb/sts12-sts
|
| 293 |
+
name: MTEB STS12
|
| 294 |
+
config: default
|
| 295 |
+
split: test
|
| 296 |
+
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
| 297 |
+
metrics:
|
| 298 |
+
- type: cos_sim_pearson
|
| 299 |
+
value: 86.08210281025868
|
| 300 |
+
- type: cos_sim_spearman
|
| 301 |
+
value: 77.75002826042643
|
| 302 |
+
- type: euclidean_pearson
|
| 303 |
+
value: 83.06487161944293
|
| 304 |
+
- type: euclidean_spearman
|
| 305 |
+
value: 78.0677956304104
|
| 306 |
+
- type: manhattan_pearson
|
| 307 |
+
value: 83.04321232787379
|
| 308 |
+
- type: manhattan_spearman
|
| 309 |
+
value: 78.09582483148635
|
| 310 |
+
- task:
|
| 311 |
+
type: STS
|
| 312 |
+
dataset:
|
| 313 |
+
type: mteb/sts13-sts
|
| 314 |
+
name: MTEB STS13
|
| 315 |
+
config: default
|
| 316 |
+
split: test
|
| 317 |
+
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
| 318 |
+
metrics:
|
| 319 |
+
- type: cos_sim_pearson
|
| 320 |
+
value: 84.64353592106988
|
| 321 |
+
- type: cos_sim_spearman
|
| 322 |
+
value: 86.07934653140616
|
| 323 |
+
- type: euclidean_pearson
|
| 324 |
+
value: 85.21820182954883
|
| 325 |
+
- type: euclidean_spearman
|
| 326 |
+
value: 86.18828773665395
|
| 327 |
+
- type: manhattan_pearson
|
| 328 |
+
value: 85.12075207905364
|
| 329 |
+
- type: manhattan_spearman
|
| 330 |
+
value: 86.12061116344299
|
| 331 |
+
- task:
|
| 332 |
+
type: STS
|
| 333 |
+
dataset:
|
| 334 |
+
type: mteb/sts14-sts
|
| 335 |
+
name: MTEB STS14
|
| 336 |
+
config: default
|
| 337 |
+
split: test
|
| 338 |
+
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
| 339 |
+
metrics:
|
| 340 |
+
- type: cos_sim_pearson
|
| 341 |
+
value: 84.33571296969136
|
| 342 |
+
- type: cos_sim_spearman
|
| 343 |
+
value: 82.8868213429789
|
| 344 |
+
- type: euclidean_pearson
|
| 345 |
+
value: 83.65476643152161
|
| 346 |
+
- type: euclidean_spearman
|
| 347 |
+
value: 82.76439753890263
|
| 348 |
+
- type: manhattan_pearson
|
| 349 |
+
value: 83.63348951033883
|
| 350 |
+
- type: manhattan_spearman
|
| 351 |
+
value: 82.76176495070241
|
| 352 |
+
- task:
|
| 353 |
+
type: STS
|
| 354 |
+
dataset:
|
| 355 |
+
type: mteb/sts15-sts
|
| 356 |
+
name: MTEB STS15
|
| 357 |
+
config: default
|
| 358 |
+
split: test
|
| 359 |
+
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
| 360 |
+
metrics:
|
| 361 |
+
- type: cos_sim_pearson
|
| 362 |
+
value: 87.6337321089215
|
| 363 |
+
- type: cos_sim_spearman
|
| 364 |
+
value: 88.54453531860615
|
| 365 |
+
- type: euclidean_pearson
|
| 366 |
+
value: 87.68754116644199
|
| 367 |
+
- type: euclidean_spearman
|
| 368 |
+
value: 88.22610830299979
|
| 369 |
+
- type: manhattan_pearson
|
| 370 |
+
value: 87.62214887890859
|
| 371 |
+
- type: manhattan_spearman
|
| 372 |
+
value: 88.14766677391091
|
| 373 |
+
- task:
|
| 374 |
+
type: STS
|
| 375 |
+
dataset:
|
| 376 |
+
type: mteb/sts16-sts
|
| 377 |
+
name: MTEB STS16
|
| 378 |
+
config: default
|
| 379 |
+
split: test
|
| 380 |
+
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
| 381 |
+
metrics:
|
| 382 |
+
- type: cos_sim_pearson
|
| 383 |
+
value: 83.89742747806514
|
| 384 |
+
- type: cos_sim_spearman
|
| 385 |
+
value: 85.76282302560992
|
| 386 |
+
- type: euclidean_pearson
|
| 387 |
+
value: 84.83917251074928
|
| 388 |
+
- type: euclidean_spearman
|
| 389 |
+
value: 85.74354740775905
|
| 390 |
+
- type: manhattan_pearson
|
| 391 |
+
value: 84.91190952448616
|
| 392 |
+
- type: manhattan_spearman
|
| 393 |
+
value: 85.82001542154245
|
| 394 |
+
- task:
|
| 395 |
+
type: STS
|
| 396 |
+
dataset:
|
| 397 |
+
type: mteb/sts17-crosslingual-sts
|
| 398 |
+
name: MTEB STS17 (en-en)
|
| 399 |
+
config: en-en
|
| 400 |
+
split: test
|
| 401 |
+
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
| 402 |
+
metrics:
|
| 403 |
+
- type: cos_sim_pearson
|
| 404 |
+
value: 87.70974342036347
|
| 405 |
+
- type: cos_sim_spearman
|
| 406 |
+
value: 87.82200371351459
|
| 407 |
+
- type: euclidean_pearson
|
| 408 |
+
value: 88.04095125600278
|
| 409 |
+
- type: euclidean_spearman
|
| 410 |
+
value: 87.5069523002544
|
| 411 |
+
- type: manhattan_pearson
|
| 412 |
+
value: 88.03247709799281
|
| 413 |
+
- type: manhattan_spearman
|
| 414 |
+
value: 87.43433979175654
|
| 415 |
+
- task:
|
| 416 |
+
type: STS
|
| 417 |
+
dataset:
|
| 418 |
+
type: mteb/sts22-crosslingual-sts
|
| 419 |
+
name: MTEB STS22 (en)
|
| 420 |
+
config: en
|
| 421 |
+
split: test
|
| 422 |
+
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
| 423 |
+
metrics:
|
| 424 |
+
- type: cos_sim_pearson
|
| 425 |
+
value: 65.0349727703108
|
| 426 |
+
- type: cos_sim_spearman
|
| 427 |
+
value: 65.46090125254047
|
| 428 |
+
- type: euclidean_pearson
|
| 429 |
+
value: 66.75349075443432
|
| 430 |
+
- type: euclidean_spearman
|
| 431 |
+
value: 65.57576680702924
|
| 432 |
+
- type: manhattan_pearson
|
| 433 |
+
value: 66.72598998285412
|
| 434 |
+
- type: manhattan_spearman
|
| 435 |
+
value: 65.63446184311414
|
| 436 |
+
- task:
|
| 437 |
+
type: STS
|
| 438 |
+
dataset:
|
| 439 |
+
type: mteb/stsbenchmark-sts
|
| 440 |
+
name: MTEB STSBenchmark
|
| 441 |
+
config: default
|
| 442 |
+
split: test
|
| 443 |
+
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
| 444 |
+
metrics:
|
| 445 |
+
- type: cos_sim_pearson
|
| 446 |
+
value: 85.18026134463653
|
| 447 |
+
- type: cos_sim_spearman
|
| 448 |
+
value: 86.79430055943524
|
| 449 |
+
- type: euclidean_pearson
|
| 450 |
+
value: 86.2668626122386
|
| 451 |
+
- type: euclidean_spearman
|
| 452 |
+
value: 86.72288498504841
|
| 453 |
+
- type: manhattan_pearson
|
| 454 |
+
value: 86.28615540445857
|
| 455 |
+
- type: manhattan_spearman
|
| 456 |
+
value: 86.7110630606802
|
| 457 |
+
- task:
|
| 458 |
+
type: Reranking
|
| 459 |
+
dataset:
|
| 460 |
+
type: mteb/scidocs-reranking
|
| 461 |
+
name: MTEB SciDocsRR
|
| 462 |
+
config: default
|
| 463 |
+
split: test
|
| 464 |
+
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
| 465 |
+
metrics:
|
| 466 |
+
- type: map
|
| 467 |
+
value: 87.05335415919195
|
| 468 |
+
- type: mrr
|
| 469 |
+
value: 96.27455968142243
|
| 470 |
+
- task:
|
| 471 |
+
type: PairClassification
|
| 472 |
+
dataset:
|
| 473 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
| 474 |
+
name: MTEB SprintDuplicateQuestions
|
| 475 |
+
config: default
|
| 476 |
+
split: test
|
| 477 |
+
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
| 478 |
+
metrics:
|
| 479 |
+
- type: cos_sim_accuracy
|
| 480 |
+
value: 99.84653465346534
|
| 481 |
+
- type: cos_sim_ap
|
| 482 |
+
value: 96.38115549823692
|
| 483 |
+
- type: cos_sim_f1
|
| 484 |
+
value: 92.15983813859383
|
| 485 |
+
- type: cos_sim_precision
|
| 486 |
+
value: 93.24462640736951
|
| 487 |
+
- type: cos_sim_recall
|
| 488 |
+
value: 91.10000000000001
|
| 489 |
+
- type: dot_accuracy
|
| 490 |
+
value: 99.81782178217821
|
| 491 |
+
- type: dot_ap
|
| 492 |
+
value: 95.65732630933346
|
| 493 |
+
- type: dot_f1
|
| 494 |
+
value: 90.68825910931176
|
| 495 |
+
- type: dot_precision
|
| 496 |
+
value: 91.80327868852459
|
| 497 |
+
- type: dot_recall
|
| 498 |
+
value: 89.60000000000001
|
| 499 |
+
- type: euclidean_accuracy
|
| 500 |
+
value: 99.84653465346534
|
| 501 |
+
- type: euclidean_ap
|
| 502 |
+
value: 96.34134720479366
|
| 503 |
+
- type: euclidean_f1
|
| 504 |
+
value: 92.1756688541141
|
| 505 |
+
- type: euclidean_precision
|
| 506 |
+
value: 93.06829765545362
|
| 507 |
+
- type: euclidean_recall
|
| 508 |
+
value: 91.3
|
| 509 |
+
- type: manhattan_accuracy
|
| 510 |
+
value: 99.84356435643565
|
| 511 |
+
- type: manhattan_ap
|
| 512 |
+
value: 96.38165573090185
|
| 513 |
+
- type: manhattan_f1
|
| 514 |
+
value: 92.07622868605819
|
| 515 |
+
- type: manhattan_precision
|
| 516 |
+
value: 92.35412474849095
|
| 517 |
+
- type: manhattan_recall
|
| 518 |
+
value: 91.8
|
| 519 |
+
- type: max_accuracy
|
| 520 |
+
value: 99.84653465346534
|
| 521 |
+
- type: max_ap
|
| 522 |
+
value: 96.38165573090185
|
| 523 |
+
- type: max_f1
|
| 524 |
+
value: 92.1756688541141
|
| 525 |
+
- task:
|
| 526 |
+
type: Clustering
|
| 527 |
+
dataset:
|
| 528 |
+
type: mteb/stackexchange-clustering
|
| 529 |
+
name: MTEB StackExchangeClustering
|
| 530 |
+
config: default
|
| 531 |
+
split: test
|
| 532 |
+
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
| 533 |
+
metrics:
|
| 534 |
+
- type: v_measure
|
| 535 |
+
value: 64.81205738681385
|
| 536 |
+
- task:
|
| 537 |
+
type: Clustering
|
| 538 |
+
dataset:
|
| 539 |
+
type: mteb/stackexchange-clustering-p2p
|
| 540 |
+
name: MTEB StackExchangeClusteringP2P
|
| 541 |
+
config: default
|
| 542 |
+
split: test
|
| 543 |
+
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
| 544 |
+
metrics:
|
| 545 |
+
- type: v_measure
|
| 546 |
+
value: 34.083934029129445
|
| 547 |
+
- task:
|
| 548 |
+
type: Reranking
|
| 549 |
+
dataset:
|
| 550 |
+
type: mteb/stackoverflowdupquestions-reranking
|
| 551 |
+
name: MTEB StackOverflowDupQuestions
|
| 552 |
+
config: default
|
| 553 |
+
split: test
|
| 554 |
+
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
| 555 |
+
metrics:
|
| 556 |
+
- type: map
|
| 557 |
+
value: 54.447346270481376
|
| 558 |
+
- type: mrr
|
| 559 |
+
value: 55.382382119514475
|
| 560 |
- task:
|
| 561 |
type: Classification
|
| 562 |
dataset:
|
|
|
|
| 585 |
value: 59.67176004527447
|
| 586 |
- type: f1
|
| 587 |
value: 59.97320225890037
|
| 588 |
+
- task:
|
| 589 |
+
type: Clustering
|
| 590 |
+
dataset:
|
| 591 |
+
type: mteb/twentynewsgroups-clustering
|
| 592 |
+
name: MTEB TwentyNewsgroupsClustering
|
| 593 |
+
config: default
|
| 594 |
+
split: test
|
| 595 |
+
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
| 596 |
+
metrics:
|
| 597 |
+
- type: v_measure
|
| 598 |
+
value: 49.50190094208029
|
| 599 |
+
- task:
|
| 600 |
+
type: PairClassification
|
| 601 |
+
dataset:
|
| 602 |
+
type: mteb/twittersemeval2015-pairclassification
|
| 603 |
+
name: MTEB TwitterSemEval2015
|
| 604 |
+
config: default
|
| 605 |
+
split: test
|
| 606 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
| 607 |
+
metrics:
|
| 608 |
+
- type: cos_sim_accuracy
|
| 609 |
+
value: 86.70799308577219
|
| 610 |
+
- type: cos_sim_ap
|
| 611 |
+
value: 76.40980707197174
|
| 612 |
+
- type: cos_sim_f1
|
| 613 |
+
value: 70.64264849074976
|
| 614 |
+
- type: cos_sim_precision
|
| 615 |
+
value: 65.56710347943967
|
| 616 |
+
- type: cos_sim_recall
|
| 617 |
+
value: 76.56992084432717
|
| 618 |
+
- type: dot_accuracy
|
| 619 |
+
value: 85.75430649102938
|
| 620 |
+
- type: dot_ap
|
| 621 |
+
value: 72.68783978286282
|
| 622 |
+
- type: dot_f1
|
| 623 |
+
value: 67.56951102588687
|
| 624 |
+
- type: dot_precision
|
| 625 |
+
value: 61.90162494510321
|
| 626 |
+
- type: dot_recall
|
| 627 |
+
value: 74.37994722955145
|
| 628 |
+
- type: euclidean_accuracy
|
| 629 |
+
value: 86.70799308577219
|
| 630 |
+
- type: euclidean_ap
|
| 631 |
+
value: 76.43046769325314
|
| 632 |
+
- type: euclidean_f1
|
| 633 |
+
value: 70.84852905421832
|
| 634 |
+
- type: euclidean_precision
|
| 635 |
+
value: 65.68981064021641
|
| 636 |
+
- type: euclidean_recall
|
| 637 |
+
value: 76.88654353562005
|
| 638 |
+
- type: manhattan_accuracy
|
| 639 |
+
value: 86.70203254455504
|
| 640 |
+
- type: manhattan_ap
|
| 641 |
+
value: 76.39254562413156
|
| 642 |
+
- type: manhattan_f1
|
| 643 |
+
value: 70.86557059961316
|
| 644 |
+
- type: manhattan_precision
|
| 645 |
+
value: 65.39491298527443
|
| 646 |
+
- type: manhattan_recall
|
| 647 |
+
value: 77.33509234828496
|
| 648 |
+
- type: max_accuracy
|
| 649 |
+
value: 86.70799308577219
|
| 650 |
+
- type: max_ap
|
| 651 |
+
value: 76.43046769325314
|
| 652 |
+
- type: max_f1
|
| 653 |
+
value: 70.86557059961316
|
| 654 |
+
- task:
|
| 655 |
+
type: PairClassification
|
| 656 |
+
dataset:
|
| 657 |
+
type: mteb/twitterurlcorpus-pairclassification
|
| 658 |
+
name: MTEB TwitterURLCorpus
|
| 659 |
+
config: default
|
| 660 |
+
split: test
|
| 661 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
| 662 |
+
metrics:
|
| 663 |
+
- type: cos_sim_accuracy
|
| 664 |
+
value: 88.92381728567548
|
| 665 |
+
- type: cos_sim_ap
|
| 666 |
+
value: 85.92532857788025
|
| 667 |
+
- type: cos_sim_f1
|
| 668 |
+
value: 78.11970128792525
|
| 669 |
+
- type: cos_sim_precision
|
| 670 |
+
value: 73.49806530445998
|
| 671 |
+
- type: cos_sim_recall
|
| 672 |
+
value: 83.3615645210964
|
| 673 |
+
- type: dot_accuracy
|
| 674 |
+
value: 88.28540381107618
|
| 675 |
+
- type: dot_ap
|
| 676 |
+
value: 84.42890126108796
|
| 677 |
+
- type: dot_f1
|
| 678 |
+
value: 76.98401162790698
|
| 679 |
+
- type: dot_precision
|
| 680 |
+
value: 72.89430222956234
|
| 681 |
+
- type: dot_recall
|
| 682 |
+
value: 81.55990144748999
|
| 683 |
+
- type: euclidean_accuracy
|
| 684 |
+
value: 88.95874568246207
|
| 685 |
+
- type: euclidean_ap
|
| 686 |
+
value: 85.88338025133037
|
| 687 |
+
- type: euclidean_f1
|
| 688 |
+
value: 78.14740888593184
|
| 689 |
+
- type: euclidean_precision
|
| 690 |
+
value: 75.15285084601166
|
| 691 |
+
- type: euclidean_recall
|
| 692 |
+
value: 81.3905143209116
|
| 693 |
+
- type: manhattan_accuracy
|
| 694 |
+
value: 88.92769821865176
|
| 695 |
+
- type: manhattan_ap
|
| 696 |
+
value: 85.84824183217555
|
| 697 |
+
- type: manhattan_f1
|
| 698 |
+
value: 77.9830582736965
|
| 699 |
+
- type: manhattan_precision
|
| 700 |
+
value: 74.15972222222223
|
| 701 |
+
- type: manhattan_recall
|
| 702 |
+
value: 82.22205112411457
|
| 703 |
+
- type: max_accuracy
|
| 704 |
+
value: 88.95874568246207
|
| 705 |
+
- type: max_ap
|
| 706 |
+
value: 85.92532857788025
|
| 707 |
+
- type: max_f1
|
| 708 |
+
value: 78.14740888593184
|
| 709 |
---
|
| 710 |
This is the quantized (INT8) ONNX variant of the [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) embeddings model created with [DeepSparse Optimum](https://github.com/neuralmagic/optimum-deepsparse) for ONNX export/inference pipeline and Neural Magic's [Sparsify](https://github.com/neuralmagic/sparsify) for one-shot quantization.
|
| 711 |
|