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pythia-14m-embedding

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  1. mean_pooling/AmazonPolarityClassification.json +15 -0
  2. mean_pooling/ArxivClusteringP2P.json +10 -0
  3. mean_pooling/ClimateFEVER.json +38 -0
  4. mean_pooling/DBPedia.json +38 -0
  5. mean_pooling/FEVER.json +38 -0
  6. mean_pooling/HotpotQA.json +38 -0
  7. mean_pooling/MSMARCO.json +38 -0
  8. mean_pooling/MassiveIntentClassification.json +365 -0
  9. mean_pooling/MassiveScenarioClassification.json +365 -0
  10. mean_pooling/MindSmallReranking.json +10 -0
  11. mean_pooling/NQ.json +38 -0
  12. mean_pooling/README.md +2772 -0
  13. mean_pooling/Touche2020.json +38 -0
  14. mean_pooling/mteb_metadata.md +1999 -152
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mean_pooling/ArxivClusteringP2P.json ADDED
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  dataset:
1248
- type: mteb/mtop_domain
1249
- name: MTEB MTOPDomainClassification (es)
1250
- config: es
1251
  split: test
1252
- revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
1253
  metrics:
1254
  - type: accuracy
1255
- value: 57.018012008005336
1256
  - type: f1
1257
- value: 54.23413458037234
1258
  - task:
1259
  type: Classification
1260
  dataset:
1261
- type: mteb/mtop_domain
1262
- name: MTEB MTOPDomainClassification (fr)
1263
- config: fr
1264
  split: test
1265
- revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
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  metrics:
1267
  - type: accuracy
1268
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1269
  - type: f1
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- value: 46.48494180527987
1271
  - task:
1272
  type: Classification
1273
  dataset:
1274
- type: mteb/mtop_domain
1275
- name: MTEB MTOPDomainClassification (hi)
1276
- config: hi
1277
  split: test
1278
- revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
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  metrics:
1280
  - type: accuracy
1281
- value: 39.7669415561133
1282
  - type: f1
1283
- value: 35.50974325529877
1284
  - task:
1285
  type: Classification
1286
  dataset:
1287
- type: mteb/mtop_domain
1288
- name: MTEB MTOPDomainClassification (th)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1289
  config: th
1290
  split: test
1291
- revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
1292
  metrics:
1293
  - type: accuracy
1294
- value: 42.589511754068724
1295
  - type: f1
1296
- value: 40.47244422785889
1297
  - task:
1298
  type: Classification
1299
  dataset:
1300
- type: mteb/mtop_intent
1301
- name: MTEB MTOPIntentClassification (en)
1302
- config: en
1303
  split: test
1304
- revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
1305
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1306
  - type: accuracy
1307
- value: 34.01276789785682
1308
  - type: f1
1309
- value: 21.256775922291286
1310
  - task:
1311
  type: Classification
1312
  dataset:
1313
- type: mteb/mtop_intent
1314
- name: MTEB MTOPIntentClassification (de)
1315
- config: de
1316
  split: test
1317
- revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
1318
  metrics:
1319
  - type: accuracy
1320
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1321
  - type: f1
1322
- value: 19.841703666811565
1323
  - task:
1324
  type: Classification
1325
  dataset:
1326
- type: mteb/mtop_intent
1327
- name: MTEB MTOPIntentClassification (es)
1328
- config: es
1329
  split: test
1330
- revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
1331
  metrics:
1332
  - type: accuracy
1333
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1334
  - type: f1
1335
- value: 19.34706868150749
1336
  - task:
1337
  type: Classification
1338
  dataset:
1339
- type: mteb/mtop_intent
1340
- name: MTEB MTOPIntentClassification (fr)
1341
- config: fr
1342
  split: test
1343
- revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
1344
  metrics:
1345
  - type: accuracy
1346
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1347
  - type: f1
1348
- value: 17.22608011891254
1349
  - task:
1350
  type: Classification
1351
  dataset:
1352
- type: mteb/mtop_intent
1353
- name: MTEB MTOPIntentClassification (hi)
1354
- config: hi
1355
  split: test
1356
- revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
1357
  metrics:
1358
  - type: accuracy
1359
- value: 15.320903549659375
1360
  - type: f1
1361
- value: 9.62002916015258
1362
  - task:
1363
  type: Classification
1364
  dataset:
1365
- type: mteb/mtop_intent
1366
- name: MTEB MTOPIntentClassification (th)
1367
- config: th
1368
  split: test
1369
- revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
1370
  metrics:
1371
  - type: accuracy
1372
- value: 16.426763110307412
1373
  - type: f1
1374
- value: 11.023799171137183
1375
  - task:
1376
  type: Clustering
1377
  dataset:
@@ -1394,6 +3091,19 @@ model-index:
1394
  metrics:
1395
  - type: v_measure
1396
  value: 16.58582885790446
 
 
 
 
 
 
 
 
 
 
 
 
 
1397
  - task:
1398
  type: Retrieval
1399
  dataset:
@@ -1463,6 +3173,75 @@ model-index:
1463
  value: 1.702
1464
  - type: recall_at_5
1465
  value: 1.9879999999999998
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1466
  - task:
1467
  type: Retrieval
1468
  dataset:
@@ -2620,6 +4399,75 @@ model-index:
2620
  value: 0.231
2621
  - type: recall_at_5
2622
  value: 0.367
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2623
  - task:
2624
  type: Classification
2625
  dataset:
@@ -2768,5 +4616,4 @@ model-index:
2768
  - type: max_ap
2769
  value: 64.59241956109807
2770
  - type: max_f1
2771
- value: 57.83203629255339
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- ---
 
64
  value: 14.367489440317666
65
  - type: f1
66
  value: 50.48473578289779
67
+ - task:
68
+ type: Classification
69
+ dataset:
70
+ type: mteb/amazon_polarity
71
+ name: MTEB AmazonPolarityClassification
72
+ config: default
73
+ split: test
74
+ revision: e2d317d38cd51312af73b3d32a06d1a08b442046
75
+ metrics:
76
+ - type: accuracy
77
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78
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79
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80
+ - type: f1
81
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82
  - task:
83
  type: Classification
84
  dataset:
 
226
  value: 12.447
227
  - type: recall_at_5
228
  value: 16.145
229
+ - task:
230
+ type: Clustering
231
+ dataset:
232
+ type: mteb/arxiv-clustering-p2p
233
+ name: MTEB ArxivClusteringP2P
234
+ config: default
235
+ split: test
236
+ revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
237
+ metrics:
238
+ - type: v_measure
239
+ value: 25.92658946113241
240
  - task:
241
  type: Clustering
242
  dataset:
 
1145
  value: 6.784
1146
  - type: recall_at_5
1147
  value: 8.17
1148
+ - task:
1149
+ type: Retrieval
1150
+ dataset:
1151
+ type: climate-fever
1152
+ name: MTEB ClimateFEVER
1153
+ config: default
1154
+ split: test
1155
+ revision: None
1156
+ metrics:
1157
+ - type: map_at_1
1158
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1159
+ - type: map_at_10
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1183
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1189
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1191
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1198
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1199
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1200
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1201
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1202
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1203
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1204
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1205
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1206
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1207
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1208
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1209
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1211
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1213
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1214
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1215
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1216
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1217
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1218
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1219
+ dataset:
1220
+ type: dbpedia-entity
1221
+ name: MTEB DBPedia
1222
+ config: default
1223
+ split: test
1224
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1225
+ metrics:
1226
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1227
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1228
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1229
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1230
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1231
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1232
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1236
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1238
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1240
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1241
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1242
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1243
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1244
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1245
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1246
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1247
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1248
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1249
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1250
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1251
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1252
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1253
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1254
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1255
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1256
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1258
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1260
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1262
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1264
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1266
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1268
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1272
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1276
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1280
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1282
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1284
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1285
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1286
+ - task:
1287
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1288
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+ type: mteb/emotion
1290
+ name: MTEB EmotionClassification
1291
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1292
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1293
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1294
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1295
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1296
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1297
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1299
+ - task:
1300
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1301
+ dataset:
1302
+ type: fever
1303
+ name: MTEB FEVER
1304
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1305
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1306
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1307
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1308
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1309
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1310
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1311
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1312
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1326
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1348
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1351
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1360
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1369
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1370
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1372
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1373
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1374
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1375
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1376
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1377
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1379
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1381
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1383
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1438
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1439
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1441
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1442
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1443
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1444
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1445
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1446
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1447
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1448
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1452
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1462
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1502
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1505
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1507
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1508
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1510
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1511
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1513
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1523
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1525
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1526
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1527
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1528
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1529
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1530
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1531
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+ - type: recall_at_5
4470
+ value: 2.604
4471
  - task:
4472
  type: Classification
4473
  dataset:
 
4616
  - type: max_ap
4617
  value: 64.59241956109807
4618
  - type: max_f1
4619
+ value: 57.83203629255339