Upload README.md
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README.md
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@@ -174,6 +174,27 @@ model-index:
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value: 57.489775602270086
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- type: mrr
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value: 71.4973838104032
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- task:
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type: Classification
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dataset:
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value: 17.197000000000003
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- type: recall_at_5
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value: 21.701
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- task:
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type: Classification
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dataset:
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value: 44.79
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- type: f1
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value: 39.606429663804356
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- task:
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type: Classification
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dataset:
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value: 65.49215755861609
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- type: f1
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value: 71.4156268611186
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- task:
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type: Classification
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dataset:
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- type: v_measures
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value: [0.2778513235855922, 0.28421867096674863, 0.26686384263192103, 0.2891902768882141, 0.27793747293511695, 0.30323125759570635, 0.2807541398062003, 0.3122697317735093, 0.2933394111230221, 0.29326102893371997, 0.2778513235855922, 0.28421867096674863, 0.26686384263192103, 0.2891902768882141, 0.27793747293511695, 0.30323125759570635, 0.2807541398062003, 0.3122697317735093, 0.2933394111230221, 0.29326102893371997, 0.2778513235855922, 0.28421867096674863, 0.26686384263192103, 0.2891902768882141, 0.27793747293511695, 0.30323125759570635, 0.2807541398062003, 0.3122697317735093, 0.2933394111230221, 0.29326102893371997, 0.2778513235855922, 0.28421867096674863, 0.26686384263192103, 0.2891902768882141, 0.27793747293511695, 0.30323125759570635, 0.2807541398062003, 0.3122697317735093, 0.2933394111230221, 0.29326102893371997, 0.2778513235855922, 0.28421867096674863, 0.26686384263192103, 0.2891902768882141, 0.27793747293511695, 0.30323125759570635, 0.2807541398062003, 0.3122697317735093, 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1270 |
- task:
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1271 |
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type:
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1272 |
dataset:
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1273 |
-
type: mteb/
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1274 |
-
name: MTEB
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1275 |
config: default
|
1276 |
split: test
|
1277 |
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
@@ -1293,6 +2025,274 @@ model-index:
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|
1293 |
value: 51.444598402601414
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1294 |
- type: v_measures
|
1295 |
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0.5651003661101165, 0.5711537036766935, 0.5987455713312818, 0.31409385867326506, 0.5578455339174134, 0.4983473414145347, 0.2540544357081523, 0.6081787161021057, 0.5498858360771133, 0.6270544772494664, 0.5651003661101165, 0.5711537036766935, 0.5987455713312818, 0.31409385867326506, 0.5578455339174134, 0.4983473414145347, 0.2540544357081523, 0.6081787161021057, 0.5498858360771133, 0.6270544772494664]
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|
1296 |
- task:
|
1297 |
type: Reranking
|
1298 |
dataset:
|
@@ -1306,6 +2306,85 @@ model-index:
|
|
1306 |
value: 77.89395841192561
|
1307 |
- type: mrr
|
1308 |
value: 93.39039319431475
|
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|
1309 |
- task:
|
1310 |
type: PairClassification
|
1311 |
dataset:
|
@@ -1400,6 +2479,181 @@ model-index:
|
|
1400 |
value: 46.78149995864765
|
1401 |
- type: mrr
|
1402 |
value: 47.45282393260334
|
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|
|
|
1403 |
- task:
|
1404 |
type: Classification
|
1405 |
dataset:
|
|
|
174 |
value: 57.489775602270086
|
175 |
- type: mrr
|
176 |
value: 71.4973838104032
|
177 |
+
- task:
|
178 |
+
type: STS
|
179 |
+
dataset:
|
180 |
+
type: mteb/biosses-sts
|
181 |
+
name: MTEB BIOSSES
|
182 |
+
config: default
|
183 |
+
split: test
|
184 |
+
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
185 |
+
metrics:
|
186 |
+
- type: cos_sim_pearson
|
187 |
+
value: 85.81314286759594
|
188 |
+
- type: cos_sim_spearman
|
189 |
+
value: 85.04832342591277
|
190 |
+
- type: euclidean_pearson
|
191 |
+
value: 84.20540608390993
|
192 |
+
- type: euclidean_spearman
|
193 |
+
value: 84.54831203281398
|
194 |
+
- type: manhattan_pearson
|
195 |
+
value: 84.11283044138868
|
196 |
+
- type: manhattan_spearman
|
197 |
+
value: 84.13384475757064
|
198 |
- task:
|
199 |
type: Classification
|
200 |
dataset:
|
|
|
1182 |
value: 17.197000000000003
|
1183 |
- type: recall_at_5
|
1184 |
value: 21.701
|
1185 |
+
- task:
|
1186 |
+
type: Retrieval
|
1187 |
+
dataset:
|
1188 |
+
type: mteb/climate-fever
|
1189 |
+
name: MTEB ClimateFEVER
|
1190 |
+
config: default
|
1191 |
+
split: test
|
1192 |
+
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
|
1193 |
+
metrics:
|
1194 |
+
- type: map_at_1
|
1195 |
+
value: 7.172000000000001
|
1196 |
+
- type: map_at_10
|
1197 |
+
value: 11.935
|
1198 |
+
- type: map_at_100
|
1199 |
+
value: 13.305
|
1200 |
+
- type: map_at_1000
|
1201 |
+
value: 13.517000000000001
|
1202 |
+
- type: map_at_20
|
1203 |
+
value: 12.589
|
1204 |
+
- type: map_at_3
|
1205 |
+
value: 9.9
|
1206 |
+
- type: map_at_5
|
1207 |
+
value: 10.839
|
1208 |
+
- type: mrr_at_1
|
1209 |
+
value: 15.895999999999999
|
1210 |
+
- type: mrr_at_10
|
1211 |
+
value: 24.215999999999998
|
1212 |
+
- type: mrr_at_100
|
1213 |
+
value: 25.418000000000003
|
1214 |
+
- type: mrr_at_1000
|
1215 |
+
value: 25.480000000000004
|
1216 |
+
- type: mrr_at_20
|
1217 |
+
value: 24.934
|
1218 |
+
- type: mrr_at_3
|
1219 |
+
value: 21.064
|
1220 |
+
- type: mrr_at_5
|
1221 |
+
value: 22.676
|
1222 |
+
- type: ndcg_at_1
|
1223 |
+
value: 15.895999999999999
|
1224 |
+
- type: ndcg_at_10
|
1225 |
+
value: 17.69
|
1226 |
+
- type: ndcg_at_100
|
1227 |
+
value: 24.232
|
1228 |
+
- type: ndcg_at_1000
|
1229 |
+
value: 28.405
|
1230 |
+
- type: ndcg_at_20
|
1231 |
+
value: 19.933999999999997
|
1232 |
+
- type: ndcg_at_3
|
1233 |
+
value: 13.761000000000001
|
1234 |
+
- type: ndcg_at_5
|
1235 |
+
value: 14.963000000000001
|
1236 |
+
- type: precision_at_1
|
1237 |
+
value: 15.895999999999999
|
1238 |
+
- type: precision_at_10
|
1239 |
+
value: 5.733
|
1240 |
+
- type: precision_at_100
|
1241 |
+
value: 1.266
|
1242 |
+
- type: precision_at_1000
|
1243 |
+
value: 0.203
|
1244 |
+
- type: precision_at_20
|
1245 |
+
value: 3.798
|
1246 |
+
- type: precision_at_3
|
1247 |
+
value: 10.076
|
1248 |
+
- type: precision_at_5
|
1249 |
+
value: 7.9479999999999995
|
1250 |
+
- type: recall_at_1
|
1251 |
+
value: 7.172000000000001
|
1252 |
+
- type: recall_at_10
|
1253 |
+
value: 22.149
|
1254 |
+
- type: recall_at_100
|
1255 |
+
value: 45.491
|
1256 |
+
- type: recall_at_1000
|
1257 |
+
value: 69.34
|
1258 |
+
- type: recall_at_20
|
1259 |
+
value: 28.634999999999998
|
1260 |
+
- type: recall_at_3
|
1261 |
+
value: 12.701
|
1262 |
+
- type: recall_at_5
|
1263 |
+
value: 15.952
|
1264 |
+
- task:
|
1265 |
+
type: Retrieval
|
1266 |
+
dataset:
|
1267 |
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type: mteb/dbpedia
|
1268 |
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name: MTEB DBPedia
|
1269 |
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config: default
|
1270 |
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split: test
|
1271 |
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revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
|
1272 |
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metrics:
|
1273 |
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- type: map_at_1
|
1274 |
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value: 7.101
|
1275 |
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- type: map_at_10
|
1276 |
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value: 15.125
|
1277 |
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- type: map_at_100
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1278 |
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value: 20.026
|
1279 |
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- type: map_at_1000
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1280 |
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value: 21.194
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1281 |
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|
1282 |
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value: 17.008000000000003
|
1283 |
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- type: map_at_3
|
1284 |
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value: 10.915999999999999
|
1285 |
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- type: map_at_5
|
1286 |
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value: 12.705
|
1287 |
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- type: mrr_at_1
|
1288 |
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value: 53.5
|
1289 |
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- type: mrr_at_10
|
1290 |
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value: 63.475
|
1291 |
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- type: mrr_at_100
|
1292 |
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value: 63.998
|
1293 |
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- type: mrr_at_1000
|
1294 |
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value: 64.019
|
1295 |
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- type: mrr_at_20
|
1296 |
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value: 63.800999999999995
|
1297 |
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- type: mrr_at_3
|
1298 |
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value: 62.041999999999994
|
1299 |
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- type: mrr_at_5
|
1300 |
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value: 62.678999999999995
|
1301 |
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- type: ndcg_at_1
|
1302 |
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value: 41.875
|
1303 |
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|
1304 |
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value: 32.967
|
1305 |
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|
1306 |
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value: 35.557
|
1307 |
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- type: ndcg_at_1000
|
1308 |
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value: 42.537000000000006
|
1309 |
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- type: ndcg_at_20
|
1310 |
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value: 31.930999999999997
|
1311 |
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- type: ndcg_at_3
|
1312 |
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value: 36.67
|
1313 |
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- type: ndcg_at_5
|
1314 |
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value: 34.474
|
1315 |
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- type: precision_at_1
|
1316 |
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value: 53.5
|
1317 |
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- type: precision_at_10
|
1318 |
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value: 27.0
|
1319 |
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- type: precision_at_100
|
1320 |
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value: 7.872999999999999
|
1321 |
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- type: precision_at_1000
|
1322 |
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value: 1.637
|
1323 |
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- type: precision_at_20
|
1324 |
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value: 19.487
|
1325 |
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- type: precision_at_3
|
1326 |
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value: 41.583
|
1327 |
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|
1328 |
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value: 34.699999999999996
|
1329 |
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- type: recall_at_1
|
1330 |
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value: 7.101
|
1331 |
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- type: recall_at_10
|
1332 |
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value: 20.408
|
1333 |
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- type: recall_at_100
|
1334 |
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value: 40.286
|
1335 |
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- type: recall_at_1000
|
1336 |
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value: 63.49399999999999
|
1337 |
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- type: recall_at_20
|
1338 |
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value: 25.478
|
1339 |
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- type: recall_at_3
|
1340 |
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value: 12.278
|
1341 |
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- type: recall_at_5
|
1342 |
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value: 15.392
|
1343 |
- task:
|
1344 |
type: Classification
|
1345 |
dataset:
|
|
|
1353 |
value: 44.79
|
1354 |
- type: f1
|
1355 |
value: 39.606429663804356
|
1356 |
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- task:
|
1357 |
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type: Retrieval
|
1358 |
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dataset:
|
1359 |
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type: mteb/fever
|
1360 |
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name: MTEB FEVER
|
1361 |
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config: default
|
1362 |
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split: test
|
1363 |
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revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
|
1364 |
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metrics:
|
1365 |
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- type: map_at_1
|
1366 |
+
value: 27.898
|
1367 |
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- type: map_at_10
|
1368 |
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value: 39.315
|
1369 |
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- type: map_at_100
|
1370 |
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value: 40.219
|
1371 |
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- type: map_at_1000
|
1372 |
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value: 40.268
|
1373 |
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- type: map_at_20
|
1374 |
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value: 39.893
|
1375 |
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- type: map_at_3
|
1376 |
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value: 35.993
|
1377 |
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- type: map_at_5
|
1378 |
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value: 38.016
|
1379 |
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- type: mrr_at_1
|
1380 |
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value: 30.003
|
1381 |
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- type: mrr_at_10
|
1382 |
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value: 41.85
|
1383 |
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- type: mrr_at_100
|
1384 |
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value: 42.722
|
1385 |
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- type: mrr_at_1000
|
1386 |
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value: 42.760999999999996
|
1387 |
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- type: mrr_at_20
|
1388 |
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value: 42.419000000000004
|
1389 |
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- type: mrr_at_3
|
1390 |
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value: 38.451
|
1391 |
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- type: mrr_at_5
|
1392 |
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value: 40.547
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1393 |
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- type: ndcg_at_1
|
1394 |
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value: 30.003
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1395 |
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- type: ndcg_at_10
|
1396 |
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value: 45.907
|
1397 |
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- type: ndcg_at_100
|
1398 |
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value: 50.198
|
1399 |
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- type: ndcg_at_1000
|
1400 |
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value: 51.405
|
1401 |
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- type: ndcg_at_20
|
1402 |
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value: 47.97
|
1403 |
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- type: ndcg_at_3
|
1404 |
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value: 39.234
|
1405 |
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- type: ndcg_at_5
|
1406 |
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value: 42.844
|
1407 |
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- type: precision_at_1
|
1408 |
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value: 30.003
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1409 |
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- type: precision_at_10
|
1410 |
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value: 7.0040000000000004
|
1411 |
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- type: precision_at_100
|
1412 |
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value: 0.9259999999999999
|
1413 |
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- type: precision_at_1000
|
1414 |
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value: 0.104
|
1415 |
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- type: precision_at_20
|
1416 |
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value: 3.9510000000000005
|
1417 |
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- type: precision_at_3
|
1418 |
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value: 16.647000000000002
|
1419 |
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- type: precision_at_5
|
1420 |
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value: 11.914
|
1421 |
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- type: recall_at_1
|
1422 |
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value: 27.898
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1423 |
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- type: recall_at_10
|
1424 |
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value: 64.003
|
1425 |
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- type: recall_at_100
|
1426 |
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value: 83.42500000000001
|
1427 |
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- type: recall_at_1000
|
1428 |
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value: 92.448
|
1429 |
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- type: recall_at_20
|
1430 |
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value: 71.93
|
1431 |
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- type: recall_at_3
|
1432 |
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value: 46.12
|
1433 |
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- type: recall_at_5
|
1434 |
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value: 54.812000000000005
|
1435 |
+
- task:
|
1436 |
+
type: Retrieval
|
1437 |
+
dataset:
|
1438 |
+
type: mteb/fiqa
|
1439 |
+
name: MTEB FiQA2018
|
1440 |
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config: default
|
1441 |
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split: test
|
1442 |
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revision: 27a168819829fe9bcd655c2df245fb19452e8e06
|
1443 |
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metrics:
|
1444 |
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- type: map_at_1
|
1445 |
+
value: 10.282
|
1446 |
+
- type: map_at_10
|
1447 |
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value: 16.141
|
1448 |
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- type: map_at_100
|
1449 |
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value: 17.634
|
1450 |
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- type: map_at_1000
|
1451 |
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value: 17.836
|
1452 |
+
- type: map_at_20
|
1453 |
+
value: 16.99
|
1454 |
+
- type: map_at_3
|
1455 |
+
value: 13.947000000000001
|
1456 |
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- type: map_at_5
|
1457 |
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value: 15.149000000000001
|
1458 |
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- type: mrr_at_1
|
1459 |
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value: 20.679
|
1460 |
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- type: mrr_at_10
|
1461 |
+
value: 26.966
|
1462 |
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- type: mrr_at_100
|
1463 |
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value: 28.108
|
1464 |
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- type: mrr_at_1000
|
1465 |
+
value: 28.183999999999997
|
1466 |
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- type: mrr_at_20
|
1467 |
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value: 27.672
|
1468 |
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- type: mrr_at_3
|
1469 |
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value: 24.743000000000002
|
1470 |
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- type: mrr_at_5
|
1471 |
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value: 25.916
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1472 |
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- type: ndcg_at_1
|
1473 |
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value: 20.679
|
1474 |
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- type: ndcg_at_10
|
1475 |
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value: 21.291
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1476 |
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- type: ndcg_at_100
|
1477 |
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value: 27.884999999999998
|
1478 |
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- type: ndcg_at_1000
|
1479 |
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value: 32.122
|
1480 |
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- type: ndcg_at_20
|
1481 |
+
value: 23.898
|
1482 |
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- type: ndcg_at_3
|
1483 |
+
value: 18.553
|
1484 |
+
- type: ndcg_at_5
|
1485 |
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value: 19.468
|
1486 |
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- type: precision_at_1
|
1487 |
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value: 20.679
|
1488 |
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- type: precision_at_10
|
1489 |
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value: 6.019
|
1490 |
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- type: precision_at_100
|
1491 |
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value: 1.252
|
1492 |
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- type: precision_at_1000
|
1493 |
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value: 0.201
|
1494 |
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- type: precision_at_20
|
1495 |
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value: 4.0120000000000005
|
1496 |
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- type: precision_at_3
|
1497 |
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value: 12.243
|
1498 |
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- type: precision_at_5
|
1499 |
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value: 9.321
|
1500 |
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- type: recall_at_1
|
1501 |
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value: 10.282
|
1502 |
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- type: recall_at_10
|
1503 |
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value: 25.901999999999997
|
1504 |
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- type: recall_at_100
|
1505 |
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value: 50.956999999999994
|
1506 |
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- type: recall_at_1000
|
1507 |
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value: 76.935
|
1508 |
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- type: recall_at_20
|
1509 |
+
value: 34.104
|
1510 |
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- type: recall_at_3
|
1511 |
+
value: 16.973
|
1512 |
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- type: recall_at_5
|
1513 |
+
value: 20.549999999999997
|
1514 |
+
- task:
|
1515 |
+
type: Retrieval
|
1516 |
+
dataset:
|
1517 |
+
type: mteb/hotpotqa
|
1518 |
+
name: MTEB HotpotQA
|
1519 |
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config: default
|
1520 |
+
split: test
|
1521 |
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revision: ab518f4d6fcca38d87c25209f94beba119d02014
|
1522 |
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metrics:
|
1523 |
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- type: map_at_1
|
1524 |
+
value: 30.567
|
1525 |
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- type: map_at_10
|
1526 |
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value: 42.314
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1527 |
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- type: map_at_100
|
1528 |
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value: 43.205
|
1529 |
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- type: map_at_1000
|
1530 |
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value: 43.288
|
1531 |
+
- type: map_at_20
|
1532 |
+
value: 42.812
|
1533 |
+
- type: map_at_3
|
1534 |
+
value: 39.695
|
1535 |
+
- type: map_at_5
|
1536 |
+
value: 41.214
|
1537 |
+
- type: mrr_at_1
|
1538 |
+
value: 61.134
|
1539 |
+
- type: mrr_at_10
|
1540 |
+
value: 68.57600000000001
|
1541 |
+
- type: mrr_at_100
|
1542 |
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value: 68.95599999999999
|
1543 |
+
- type: mrr_at_1000
|
1544 |
+
value: 68.97999999999999
|
1545 |
+
- type: mrr_at_20
|
1546 |
+
value: 68.818
|
1547 |
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- type: mrr_at_3
|
1548 |
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value: 66.99300000000001
|
1549 |
+
- type: mrr_at_5
|
1550 |
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value: 67.919
|
1551 |
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- type: ndcg_at_1
|
1552 |
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value: 61.134
|
1553 |
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- type: ndcg_at_10
|
1554 |
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value: 51.518
|
1555 |
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- type: ndcg_at_100
|
1556 |
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value: 55.022000000000006
|
1557 |
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- type: ndcg_at_1000
|
1558 |
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value: 56.81699999999999
|
1559 |
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- type: ndcg_at_20
|
1560 |
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value: 52.893
|
1561 |
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- type: ndcg_at_3
|
1562 |
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value: 47.216
|
1563 |
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- type: ndcg_at_5
|
1564 |
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value: 49.413000000000004
|
1565 |
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- type: precision_at_1
|
1566 |
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value: 61.134
|
1567 |
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- type: precision_at_10
|
1568 |
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value: 10.729
|
1569 |
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- type: precision_at_100
|
1570 |
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value: 1.351
|
1571 |
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- type: precision_at_1000
|
1572 |
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value: 0.159
|
1573 |
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- type: precision_at_20
|
1574 |
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value: 5.8069999999999995
|
1575 |
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- type: precision_at_3
|
1576 |
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value: 29.336000000000002
|
1577 |
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- type: precision_at_5
|
1578 |
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value: 19.346
|
1579 |
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- type: recall_at_1
|
1580 |
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value: 30.567
|
1581 |
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- type: recall_at_10
|
1582 |
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value: 53.64600000000001
|
1583 |
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- type: recall_at_100
|
1584 |
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value: 67.562
|
1585 |
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- type: recall_at_1000
|
1586 |
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value: 79.521
|
1587 |
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- type: recall_at_20
|
1588 |
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value: 58.069
|
1589 |
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- type: recall_at_3
|
1590 |
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value: 44.004
|
1591 |
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- type: recall_at_5
|
1592 |
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value: 48.366
|
1593 |
- task:
|
1594 |
type: Classification
|
1595 |
dataset:
|
|
|
1605 |
value: 65.49215755861609
|
1606 |
- type: f1
|
1607 |
value: 71.4156268611186
|
1608 |
+
- task:
|
1609 |
+
type: Retrieval
|
1610 |
+
dataset:
|
1611 |
+
type: mteb/msmarco
|
1612 |
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name: MTEB MSMARCO
|
1613 |
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config: default
|
1614 |
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split: dev
|
1615 |
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revision: c5a29a104738b98a9e76336939199e264163d4a0
|
1616 |
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metrics:
|
1617 |
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|
1618 |
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value: 14.574000000000002
|
1619 |
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- type: map_at_10
|
1620 |
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value: 23.966
|
1621 |
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- type: map_at_100
|
1622 |
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value: 25.19
|
1623 |
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- type: map_at_1000
|
1624 |
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value: 25.266
|
1625 |
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- type: map_at_20
|
1626 |
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value: 24.668
|
1627 |
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- type: map_at_3
|
1628 |
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value: 20.815
|
1629 |
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- type: map_at_5
|
1630 |
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value: 22.576
|
1631 |
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- type: mrr_at_1
|
1632 |
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value: 14.957
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1633 |
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- type: mrr_at_10
|
1634 |
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value: 24.413999999999998
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1635 |
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- type: mrr_at_100
|
1636 |
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value: 25.616
|
1637 |
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- type: mrr_at_1000
|
1638 |
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value: 25.685999999999996
|
1639 |
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- type: mrr_at_20
|
1640 |
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value: 25.11
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1641 |
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- type: mrr_at_3
|
1642 |
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value: 21.304000000000002
|
1643 |
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- type: mrr_at_5
|
1644 |
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value: 23.047
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1645 |
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- type: ndcg_at_1
|
1646 |
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value: 14.957
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1647 |
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- type: ndcg_at_10
|
1648 |
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value: 29.49
|
1649 |
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- type: ndcg_at_100
|
1650 |
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value: 35.734
|
1651 |
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- type: ndcg_at_1000
|
1652 |
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value: 37.785000000000004
|
1653 |
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- type: ndcg_at_20
|
1654 |
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value: 32.004
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1655 |
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- type: ndcg_at_3
|
1656 |
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value: 23.006999999999998
|
1657 |
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- type: ndcg_at_5
|
1658 |
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value: 26.154
|
1659 |
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- type: precision_at_1
|
1660 |
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value: 14.957
|
1661 |
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- type: precision_at_10
|
1662 |
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value: 4.8500000000000005
|
1663 |
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- type: precision_at_100
|
1664 |
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value: 0.8009999999999999
|
1665 |
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- type: precision_at_1000
|
1666 |
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value: 0.098
|
1667 |
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- type: precision_at_20
|
1668 |
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value: 2.943
|
1669 |
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- type: precision_at_3
|
1670 |
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value: 9.962
|
1671 |
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- type: precision_at_5
|
1672 |
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value: 7.556
|
1673 |
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- type: recall_at_1
|
1674 |
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value: 14.574000000000002
|
1675 |
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- type: recall_at_10
|
1676 |
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value: 46.655
|
1677 |
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- type: recall_at_100
|
1678 |
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value: 76.26899999999999
|
1679 |
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- type: recall_at_1000
|
1680 |
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value: 92.303
|
1681 |
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- type: recall_at_20
|
1682 |
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value: 56.424
|
1683 |
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- type: recall_at_3
|
1684 |
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value: 28.874
|
1685 |
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- type: recall_at_5
|
1686 |
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value: 36.441
|
1687 |
- task:
|
1688 |
type: Classification
|
1689 |
dataset:
|
|
|
1763 |
- type: v_measures
|
1764 |
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|
1765 |
- task:
|
1766 |
+
type: Retrieval
|
1767 |
dataset:
|
1768 |
+
type: mteb/nfcorpus
|
1769 |
+
name: MTEB NFCorpus
|
1770 |
+
config: default
|
1771 |
+
split: test
|
1772 |
+
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
|
1773 |
+
metrics:
|
1774 |
+
- type: map_at_1
|
1775 |
+
value: 3.726
|
1776 |
+
- type: map_at_10
|
1777 |
+
value: 8.604000000000001
|
1778 |
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- type: map_at_100
|
1779 |
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value: 10.95
|
1780 |
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- type: map_at_1000
|
1781 |
+
value: 12.256
|
1782 |
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- type: map_at_20
|
1783 |
+
value: 9.573
|
1784 |
+
- type: map_at_3
|
1785 |
+
value: 6.264
|
1786 |
+
- type: map_at_5
|
1787 |
+
value: 7.343
|
1788 |
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- type: mrr_at_1
|
1789 |
+
value: 37.771
|
1790 |
+
- type: mrr_at_10
|
1791 |
+
value: 46.476
|
1792 |
+
- type: mrr_at_100
|
1793 |
+
value: 47.164
|
1794 |
+
- type: mrr_at_1000
|
1795 |
+
value: 47.213
|
1796 |
+
- type: mrr_at_20
|
1797 |
+
value: 46.792
|
1798 |
+
- type: mrr_at_3
|
1799 |
+
value: 44.272
|
1800 |
+
- type: mrr_at_5
|
1801 |
+
value: 45.728
|
1802 |
+
- type: ndcg_at_1
|
1803 |
+
value: 35.604
|
1804 |
+
- type: ndcg_at_10
|
1805 |
+
value: 26.778000000000002
|
1806 |
+
- type: ndcg_at_100
|
1807 |
+
value: 24.313000000000002
|
1808 |
+
- type: ndcg_at_1000
|
1809 |
+
value: 33.601
|
1810 |
+
- type: ndcg_at_20
|
1811 |
+
value: 24.788
|
1812 |
+
- type: ndcg_at_3
|
1813 |
+
value: 30.991999999999997
|
1814 |
+
- type: ndcg_at_5
|
1815 |
+
value: 28.9
|
1816 |
+
- type: precision_at_1
|
1817 |
+
value: 37.152
|
1818 |
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- type: precision_at_10
|
1819 |
+
value: 19.875999999999998
|
1820 |
+
- type: precision_at_100
|
1821 |
+
value: 6.449000000000001
|
1822 |
+
- type: precision_at_1000
|
1823 |
+
value: 1.934
|
1824 |
+
- type: precision_at_20
|
1825 |
+
value: 14.721
|
1826 |
+
- type: precision_at_3
|
1827 |
+
value: 28.999000000000002
|
1828 |
+
- type: precision_at_5
|
1829 |
+
value: 24.582
|
1830 |
+
- type: recall_at_1
|
1831 |
+
value: 3.726
|
1832 |
+
- type: recall_at_10
|
1833 |
+
value: 12.529000000000002
|
1834 |
+
- type: recall_at_100
|
1835 |
+
value: 25.726
|
1836 |
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- type: recall_at_1000
|
1837 |
+
value: 58.336
|
1838 |
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- type: recall_at_20
|
1839 |
+
value: 16.028000000000002
|
1840 |
+
- type: recall_at_3
|
1841 |
+
value: 7.176
|
1842 |
+
- type: recall_at_5
|
1843 |
+
value: 9.511
|
1844 |
+
- task:
|
1845 |
+
type: Retrieval
|
1846 |
+
dataset:
|
1847 |
+
type: mteb/nq
|
1848 |
+
name: MTEB NQ
|
1849 |
+
config: default
|
1850 |
+
split: test
|
1851 |
+
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
|
1852 |
+
metrics:
|
1853 |
+
- type: map_at_1
|
1854 |
+
value: 15.110000000000001
|
1855 |
+
- type: map_at_10
|
1856 |
+
value: 25.983
|
1857 |
+
- type: map_at_100
|
1858 |
+
value: 27.332
|
1859 |
+
- type: map_at_1000
|
1860 |
+
value: 27.406999999999996
|
1861 |
+
- type: map_at_20
|
1862 |
+
value: 26.804
|
1863 |
+
- type: map_at_3
|
1864 |
+
value: 22.182
|
1865 |
+
- type: map_at_5
|
1866 |
+
value: 24.247
|
1867 |
+
- type: mrr_at_1
|
1868 |
+
value: 17.236
|
1869 |
+
- type: mrr_at_10
|
1870 |
+
value: 28.177999999999997
|
1871 |
+
- type: mrr_at_100
|
1872 |
+
value: 29.346
|
1873 |
+
- type: mrr_at_1000
|
1874 |
+
value: 29.401
|
1875 |
+
- type: mrr_at_20
|
1876 |
+
value: 28.906
|
1877 |
+
- type: mrr_at_3
|
1878 |
+
value: 24.593999999999998
|
1879 |
+
- type: mrr_at_5
|
1880 |
+
value: 26.540999999999997
|
1881 |
+
- type: ndcg_at_1
|
1882 |
+
value: 17.207
|
1883 |
+
- type: ndcg_at_10
|
1884 |
+
value: 32.603
|
1885 |
+
- type: ndcg_at_100
|
1886 |
+
value: 38.883
|
1887 |
+
- type: ndcg_at_1000
|
1888 |
+
value: 40.708
|
1889 |
+
- type: ndcg_at_20
|
1890 |
+
value: 35.397
|
1891 |
+
- type: ndcg_at_3
|
1892 |
+
value: 25.002999999999997
|
1893 |
+
- type: ndcg_at_5
|
1894 |
+
value: 28.572999999999997
|
1895 |
+
- type: precision_at_1
|
1896 |
+
value: 17.207
|
1897 |
+
- type: precision_at_10
|
1898 |
+
value: 5.985
|
1899 |
+
- type: precision_at_100
|
1900 |
+
value: 0.951
|
1901 |
+
- type: precision_at_1000
|
1902 |
+
value: 0.11299999999999999
|
1903 |
+
- type: precision_at_20
|
1904 |
+
value: 3.656
|
1905 |
+
- type: precision_at_3
|
1906 |
+
value: 11.848
|
1907 |
+
- type: precision_at_5
|
1908 |
+
value: 9.125
|
1909 |
+
- type: recall_at_1
|
1910 |
+
value: 15.110000000000001
|
1911 |
+
- type: recall_at_10
|
1912 |
+
value: 51.00900000000001
|
1913 |
+
- type: recall_at_100
|
1914 |
+
value: 79.193
|
1915 |
+
- type: recall_at_1000
|
1916 |
+
value: 92.828
|
1917 |
+
- type: recall_at_20
|
1918 |
+
value: 61.402
|
1919 |
+
- type: recall_at_3
|
1920 |
+
value: 30.791
|
1921 |
+
- type: recall_at_5
|
1922 |
+
value: 39.091
|
1923 |
+
- task:
|
1924 |
+
type: Retrieval
|
1925 |
+
dataset:
|
1926 |
+
type: mteb/quora
|
1927 |
+
name: MTEB QuoraRetrieval
|
1928 |
+
config: default
|
1929 |
+
split: test
|
1930 |
+
revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
|
1931 |
+
metrics:
|
1932 |
+
- type: map_at_1
|
1933 |
+
value: 67.465
|
1934 |
+
- type: map_at_10
|
1935 |
+
value: 81.035
|
1936 |
+
- type: map_at_100
|
1937 |
+
value: 81.718
|
1938 |
+
- type: map_at_1000
|
1939 |
+
value: 81.742
|
1940 |
+
- type: map_at_20
|
1941 |
+
value: 81.486
|
1942 |
+
- type: map_at_3
|
1943 |
+
value: 77.972
|
1944 |
+
- type: map_at_5
|
1945 |
+
value: 79.903
|
1946 |
+
- type: mrr_at_1
|
1947 |
+
value: 77.64
|
1948 |
+
- type: mrr_at_10
|
1949 |
+
value: 84.584
|
1950 |
+
- type: mrr_at_100
|
1951 |
+
value: 84.722
|
1952 |
+
- type: mrr_at_1000
|
1953 |
+
value: 84.724
|
1954 |
+
- type: mrr_at_20
|
1955 |
+
value: 84.684
|
1956 |
+
- type: mrr_at_3
|
1957 |
+
value: 83.325
|
1958 |
+
- type: mrr_at_5
|
1959 |
+
value: 84.15899999999999
|
1960 |
+
- type: ndcg_at_1
|
1961 |
+
value: 77.66999999999999
|
1962 |
+
- type: ndcg_at_10
|
1963 |
+
value: 85.30499999999999
|
1964 |
+
- type: ndcg_at_100
|
1965 |
+
value: 86.834
|
1966 |
+
- type: ndcg_at_1000
|
1967 |
+
value: 87.033
|
1968 |
+
- type: ndcg_at_20
|
1969 |
+
value: 86.12100000000001
|
1970 |
+
- type: ndcg_at_3
|
1971 |
+
value: 81.974
|
1972 |
+
- type: ndcg_at_5
|
1973 |
+
value: 83.813
|
1974 |
+
- type: precision_at_1
|
1975 |
+
value: 77.66999999999999
|
1976 |
+
- type: precision_at_10
|
1977 |
+
value: 12.931000000000001
|
1978 |
+
- type: precision_at_100
|
1979 |
+
value: 1.5
|
1980 |
+
- type: precision_at_1000
|
1981 |
+
value: 0.156
|
1982 |
+
- type: precision_at_20
|
1983 |
+
value: 6.903
|
1984 |
+
- type: precision_at_3
|
1985 |
+
value: 35.730000000000004
|
1986 |
+
- type: precision_at_5
|
1987 |
+
value: 23.642
|
1988 |
+
- type: recall_at_1
|
1989 |
+
value: 67.465
|
1990 |
+
- type: recall_at_10
|
1991 |
+
value: 93.581
|
1992 |
+
- type: recall_at_100
|
1993 |
+
value: 98.91499999999999
|
1994 |
+
- type: recall_at_1000
|
1995 |
+
value: 99.90599999999999
|
1996 |
+
- type: recall_at_20
|
1997 |
+
value: 96.221
|
1998 |
+
- type: recall_at_3
|
1999 |
+
value: 84.071
|
2000 |
+
- type: recall_at_5
|
2001 |
+
value: 89.14999999999999
|
2002 |
+
- task:
|
2003 |
+
type: Clustering
|
2004 |
+
dataset:
|
2005 |
+
type: mteb/reddit-clustering
|
2006 |
+
name: MTEB RedditClustering
|
2007 |
config: default
|
2008 |
split: test
|
2009 |
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
|
|
2025 |
value: 51.444598402601414
|
2026 |
- type: v_measures
|
2027 |
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|
2028 |
+
- task:
|
2029 |
+
type: Retrieval
|
2030 |
+
dataset:
|
2031 |
+
type: mteb/scidocs
|
2032 |
+
name: MTEB SCIDOCS
|
2033 |
+
config: default
|
2034 |
+
split: test
|
2035 |
+
revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
|
2036 |
+
metrics:
|
2037 |
+
- type: map_at_1
|
2038 |
+
value: 3.5929999999999995
|
2039 |
+
- type: map_at_10
|
2040 |
+
value: 8.753
|
2041 |
+
- type: map_at_100
|
2042 |
+
value: 10.349
|
2043 |
+
- type: map_at_1000
|
2044 |
+
value: 10.624
|
2045 |
+
- type: map_at_20
|
2046 |
+
value: 9.553
|
2047 |
+
- type: map_at_3
|
2048 |
+
value: 6.2700000000000005
|
2049 |
+
- type: map_at_5
|
2050 |
+
value: 7.5329999999999995
|
2051 |
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- type: mrr_at_1
|
2052 |
+
value: 17.7
|
2053 |
+
- type: mrr_at_10
|
2054 |
+
value: 27.167
|
2055 |
+
- type: mrr_at_100
|
2056 |
+
value: 28.351
|
2057 |
+
- type: mrr_at_1000
|
2058 |
+
value: 28.418
|
2059 |
+
- type: mrr_at_20
|
2060 |
+
value: 27.819
|
2061 |
+
- type: mrr_at_3
|
2062 |
+
value: 24.282999999999998
|
2063 |
+
- type: mrr_at_5
|
2064 |
+
value: 26.073
|
2065 |
+
- type: ndcg_at_1
|
2066 |
+
value: 17.7
|
2067 |
+
- type: ndcg_at_10
|
2068 |
+
value: 15.312000000000001
|
2069 |
+
- type: ndcg_at_100
|
2070 |
+
value: 22.178
|
2071 |
+
- type: ndcg_at_1000
|
2072 |
+
value: 27.575
|
2073 |
+
- type: ndcg_at_20
|
2074 |
+
value: 17.648
|
2075 |
+
- type: ndcg_at_3
|
2076 |
+
value: 14.41
|
2077 |
+
- type: ndcg_at_5
|
2078 |
+
value: 12.774
|
2079 |
+
- type: precision_at_1
|
2080 |
+
value: 17.7
|
2081 |
+
- type: precision_at_10
|
2082 |
+
value: 7.93
|
2083 |
+
- type: precision_at_100
|
2084 |
+
value: 1.7930000000000001
|
2085 |
+
- type: precision_at_1000
|
2086 |
+
value: 0.31
|
2087 |
+
- type: precision_at_20
|
2088 |
+
value: 5.315
|
2089 |
+
- type: precision_at_3
|
2090 |
+
value: 13.367
|
2091 |
+
- type: precision_at_5
|
2092 |
+
value: 11.26
|
2093 |
+
- type: recall_at_1
|
2094 |
+
value: 3.5929999999999995
|
2095 |
+
- type: recall_at_10
|
2096 |
+
value: 16.088
|
2097 |
+
- type: recall_at_100
|
2098 |
+
value: 36.39
|
2099 |
+
- type: recall_at_1000
|
2100 |
+
value: 62.932
|
2101 |
+
- type: recall_at_20
|
2102 |
+
value: 21.562
|
2103 |
+
- type: recall_at_3
|
2104 |
+
value: 8.123
|
2105 |
+
- type: recall_at_5
|
2106 |
+
value: 11.393
|
2107 |
+
- task:
|
2108 |
+
type: STS
|
2109 |
+
dataset:
|
2110 |
+
type: mteb/sickr-sts
|
2111 |
+
name: MTEB SICK-R
|
2112 |
+
config: default
|
2113 |
+
split: test
|
2114 |
+
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
|
2115 |
+
metrics:
|
2116 |
+
- type: cos_sim_pearson
|
2117 |
+
value: 82.6885494958054
|
2118 |
+
- type: cos_sim_spearman
|
2119 |
+
value: 76.0433546110243
|
2120 |
+
- type: euclidean_pearson
|
2121 |
+
value: 79.85820435751087
|
2122 |
+
- type: euclidean_spearman
|
2123 |
+
value: 75.9326257444857
|
2124 |
+
- type: manhattan_pearson
|
2125 |
+
value: 79.6973024858654
|
2126 |
+
- type: manhattan_spearman
|
2127 |
+
value: 75.71084698490509
|
2128 |
+
- task:
|
2129 |
+
type: STS
|
2130 |
+
dataset:
|
2131 |
+
type: mteb/sts12-sts
|
2132 |
+
name: MTEB STS12
|
2133 |
+
config: default
|
2134 |
+
split: test
|
2135 |
+
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
2136 |
+
metrics:
|
2137 |
+
- type: cos_sim_pearson
|
2138 |
+
value: 77.34659218404506
|
2139 |
+
- type: cos_sim_spearman
|
2140 |
+
value: 69.49541146727839
|
2141 |
+
- type: euclidean_pearson
|
2142 |
+
value: 74.80982564474151
|
2143 |
+
- type: euclidean_spearman
|
2144 |
+
value: 70.04102091813081
|
2145 |
+
- type: manhattan_pearson
|
2146 |
+
value: 75.00200126757426
|
2147 |
+
- type: manhattan_spearman
|
2148 |
+
value: 70.22802660355588
|
2149 |
+
- task:
|
2150 |
+
type: STS
|
2151 |
+
dataset:
|
2152 |
+
type: mteb/sts13-sts
|
2153 |
+
name: MTEB STS13
|
2154 |
+
config: default
|
2155 |
+
split: test
|
2156 |
+
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
2157 |
+
metrics:
|
2158 |
+
- type: cos_sim_pearson
|
2159 |
+
value: 79.91444494464905
|
2160 |
+
- type: cos_sim_spearman
|
2161 |
+
value: 80.96085686108583
|
2162 |
+
- type: euclidean_pearson
|
2163 |
+
value: 80.5915387592164
|
2164 |
+
- type: euclidean_spearman
|
2165 |
+
value: 80.8861855866439
|
2166 |
+
- type: manhattan_pearson
|
2167 |
+
value: 80.46881359994653
|
2168 |
+
- type: manhattan_spearman
|
2169 |
+
value: 80.80230339264102
|
2170 |
+
- task:
|
2171 |
+
type: STS
|
2172 |
+
dataset:
|
2173 |
+
type: mteb/sts14-sts
|
2174 |
+
name: MTEB STS14
|
2175 |
+
config: default
|
2176 |
+
split: test
|
2177 |
+
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
2178 |
+
metrics:
|
2179 |
+
- type: cos_sim_pearson
|
2180 |
+
value: 80.81974904249208
|
2181 |
+
- type: cos_sim_spearman
|
2182 |
+
value: 77.08348207580887
|
2183 |
+
- type: euclidean_pearson
|
2184 |
+
value: 80.13431221409199
|
2185 |
+
- type: euclidean_spearman
|
2186 |
+
value: 77.31778188790902
|
2187 |
+
- type: manhattan_pearson
|
2188 |
+
value: 80.05343415464556
|
2189 |
+
- type: manhattan_spearman
|
2190 |
+
value: 77.26095229151665
|
2191 |
+
- task:
|
2192 |
+
type: STS
|
2193 |
+
dataset:
|
2194 |
+
type: mteb/sts15-sts
|
2195 |
+
name: MTEB STS15
|
2196 |
+
config: default
|
2197 |
+
split: test
|
2198 |
+
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
2199 |
+
metrics:
|
2200 |
+
- type: cos_sim_pearson
|
2201 |
+
value: 84.37398871508579
|
2202 |
+
- type: cos_sim_spearman
|
2203 |
+
value: 85.41548418250477
|
2204 |
+
- type: euclidean_pearson
|
2205 |
+
value: 85.18569982361353
|
2206 |
+
- type: euclidean_spearman
|
2207 |
+
value: 85.73446512176643
|
2208 |
+
- type: manhattan_pearson
|
2209 |
+
value: 85.1016252976206
|
2210 |
+
- type: manhattan_spearman
|
2211 |
+
value: 85.66092136939069
|
2212 |
+
- task:
|
2213 |
+
type: STS
|
2214 |
+
dataset:
|
2215 |
+
type: mteb/sts16-sts
|
2216 |
+
name: MTEB STS16
|
2217 |
+
config: default
|
2218 |
+
split: test
|
2219 |
+
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
2220 |
+
metrics:
|
2221 |
+
- type: cos_sim_pearson
|
2222 |
+
value: 80.59702638640928
|
2223 |
+
- type: cos_sim_spearman
|
2224 |
+
value: 82.29583005583622
|
2225 |
+
- type: euclidean_pearson
|
2226 |
+
value: 81.83307796549182
|
2227 |
+
- type: euclidean_spearman
|
2228 |
+
value: 82.39554204652183
|
2229 |
+
- type: manhattan_pearson
|
2230 |
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value: 81.78282737393326
|
2231 |
+
- type: manhattan_spearman
|
2232 |
+
value: 82.34235304571907
|
2233 |
+
- task:
|
2234 |
+
type: STS
|
2235 |
+
dataset:
|
2236 |
+
type: mteb/sts17-crosslingual-sts
|
2237 |
+
name: MTEB STS17 (en-en)
|
2238 |
+
config: en-en
|
2239 |
+
split: test
|
2240 |
+
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
2241 |
+
metrics:
|
2242 |
+
- type: cos_sim_pearson
|
2243 |
+
value: 86.89190122908971
|
2244 |
+
- type: cos_sim_spearman
|
2245 |
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value: 88.03461344591356
|
2246 |
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- type: euclidean_pearson
|
2247 |
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value: 87.81999485969313
|
2248 |
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- type: euclidean_spearman
|
2249 |
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value: 88.07040076481854
|
2250 |
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- type: manhattan_pearson
|
2251 |
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value: 87.53382294293554
|
2252 |
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- type: manhattan_spearman
|
2253 |
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value: 87.76615089464353
|
2254 |
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- task:
|
2255 |
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type: STS
|
2256 |
+
dataset:
|
2257 |
+
type: mteb/sts22-crosslingual-sts
|
2258 |
+
name: MTEB STS22 (en)
|
2259 |
+
config: en
|
2260 |
+
split: test
|
2261 |
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revision: eea2b4fe26a775864c896887d910b76a8098ad3f
|
2262 |
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metrics:
|
2263 |
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- type: cos_sim_pearson
|
2264 |
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value: 57.97869820676485
|
2265 |
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- type: cos_sim_spearman
|
2266 |
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value: 64.12171377270657
|
2267 |
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- type: euclidean_pearson
|
2268 |
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value: 60.9601725696545
|
2269 |
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- type: euclidean_spearman
|
2270 |
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value: 63.48982922146721
|
2271 |
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- type: manhattan_pearson
|
2272 |
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value: 61.37553142926566
|
2273 |
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- type: manhattan_spearman
|
2274 |
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value: 63.759462595791796
|
2275 |
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- task:
|
2276 |
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type: STS
|
2277 |
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dataset:
|
2278 |
+
type: mteb/stsbenchmark-sts
|
2279 |
+
name: MTEB STSBenchmark
|
2280 |
+
config: default
|
2281 |
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split: test
|
2282 |
+
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
2283 |
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metrics:
|
2284 |
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- type: cos_sim_pearson
|
2285 |
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value: 83.14812517797631
|
2286 |
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- type: cos_sim_spearman
|
2287 |
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value: 83.33681512924129
|
2288 |
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- type: euclidean_pearson
|
2289 |
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value: 84.0552689078266
|
2290 |
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- type: euclidean_spearman
|
2291 |
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value: 83.45075258664495
|
2292 |
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- type: manhattan_pearson
|
2293 |
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value: 83.94309504683835
|
2294 |
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- type: manhattan_spearman
|
2295 |
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value: 83.37311472277489
|
2296 |
- task:
|
2297 |
type: Reranking
|
2298 |
dataset:
|
|
|
2306 |
value: 77.89395841192561
|
2307 |
- type: mrr
|
2308 |
value: 93.39039319431475
|
2309 |
+
- task:
|
2310 |
+
type: Retrieval
|
2311 |
+
dataset:
|
2312 |
+
type: mteb/scifact
|
2313 |
+
name: MTEB SciFact
|
2314 |
+
config: default
|
2315 |
+
split: test
|
2316 |
+
revision: 0228b52cf27578f30900b9e5271d331663a030d7
|
2317 |
+
metrics:
|
2318 |
+
- type: map_at_1
|
2319 |
+
value: 47.65
|
2320 |
+
- type: map_at_10
|
2321 |
+
value: 58.287
|
2322 |
+
- type: map_at_100
|
2323 |
+
value: 58.965999999999994
|
2324 |
+
- type: map_at_1000
|
2325 |
+
value: 58.998
|
2326 |
+
- type: map_at_20
|
2327 |
+
value: 58.709
|
2328 |
+
- type: map_at_3
|
2329 |
+
value: 55.272
|
2330 |
+
- type: map_at_5
|
2331 |
+
value: 57.135999999999996
|
2332 |
+
- type: mrr_at_1
|
2333 |
+
value: 50.333000000000006
|
2334 |
+
- type: mrr_at_10
|
2335 |
+
value: 59.589999999999996
|
2336 |
+
- type: mrr_at_100
|
2337 |
+
value: 60.129999999999995
|
2338 |
+
- type: mrr_at_1000
|
2339 |
+
value: 60.162000000000006
|
2340 |
+
- type: mrr_at_20
|
2341 |
+
value: 59.95700000000001
|
2342 |
+
- type: mrr_at_3
|
2343 |
+
value: 57.389
|
2344 |
+
- type: mrr_at_5
|
2345 |
+
value: 58.656
|
2346 |
+
- type: ndcg_at_1
|
2347 |
+
value: 50.333000000000006
|
2348 |
+
- type: ndcg_at_10
|
2349 |
+
value: 63.232
|
2350 |
+
- type: ndcg_at_100
|
2351 |
+
value: 66.213
|
2352 |
+
- type: ndcg_at_1000
|
2353 |
+
value: 67.203
|
2354 |
+
- type: ndcg_at_20
|
2355 |
+
value: 64.63499999999999
|
2356 |
+
- type: ndcg_at_3
|
2357 |
+
value: 58.163
|
2358 |
+
- type: ndcg_at_5
|
2359 |
+
value: 60.785999999999994
|
2360 |
+
- type: precision_at_1
|
2361 |
+
value: 50.333000000000006
|
2362 |
+
- type: precision_at_10
|
2363 |
+
value: 8.633000000000001
|
2364 |
+
- type: precision_at_100
|
2365 |
+
value: 1.03
|
2366 |
+
- type: precision_at_1000
|
2367 |
+
value: 0.11100000000000002
|
2368 |
+
- type: precision_at_20
|
2369 |
+
value: 4.633
|
2370 |
+
- type: precision_at_3
|
2371 |
+
value: 22.889
|
2372 |
+
- type: precision_at_5
|
2373 |
+
value: 15.4
|
2374 |
+
- type: recall_at_1
|
2375 |
+
value: 47.65
|
2376 |
+
- type: recall_at_10
|
2377 |
+
value: 76.95
|
2378 |
+
- type: recall_at_100
|
2379 |
+
value: 90.333
|
2380 |
+
- type: recall_at_1000
|
2381 |
+
value: 98.333
|
2382 |
+
- type: recall_at_20
|
2383 |
+
value: 82.267
|
2384 |
+
- type: recall_at_3
|
2385 |
+
value: 63.632999999999996
|
2386 |
+
- type: recall_at_5
|
2387 |
+
value: 69.978
|
2388 |
- task:
|
2389 |
type: PairClassification
|
2390 |
dataset:
|
|
|
2479 |
value: 46.78149995864765
|
2480 |
- type: mrr
|
2481 |
value: 47.45282393260334
|
2482 |
+
- task:
|
2483 |
+
type: Summarization
|
2484 |
+
dataset:
|
2485 |
+
type: mteb/summeval
|
2486 |
+
name: MTEB SummEval
|
2487 |
+
config: default
|
2488 |
+
split: test
|
2489 |
+
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
2490 |
+
metrics:
|
2491 |
+
- type: cos_sim_pearson
|
2492 |
+
value: 31.202698233290022
|
2493 |
+
- type: cos_sim_spearman
|
2494 |
+
value: 30.971936219818662
|
2495 |
+
- type: dot_pearson
|
2496 |
+
value: 25.486069760264634
|
2497 |
+
- type: dot_spearman
|
2498 |
+
value: 25.811060638581246
|
2499 |
+
- task:
|
2500 |
+
type: Retrieval
|
2501 |
+
dataset:
|
2502 |
+
type: mteb/trec-covid
|
2503 |
+
name: MTEB TRECCOVID
|
2504 |
+
config: default
|
2505 |
+
split: test
|
2506 |
+
revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
|
2507 |
+
metrics:
|
2508 |
+
- type: map_at_1
|
2509 |
+
value: 0.16999999999999998
|
2510 |
+
- type: map_at_10
|
2511 |
+
value: 0.943
|
2512 |
+
- type: map_at_100
|
2513 |
+
value: 5.0200000000000005
|
2514 |
+
- type: map_at_1000
|
2515 |
+
value: 13.855
|
2516 |
+
- type: map_at_20
|
2517 |
+
value: 1.609
|
2518 |
+
- type: map_at_3
|
2519 |
+
value: 0.384
|
2520 |
+
- type: map_at_5
|
2521 |
+
value: 0.5660000000000001
|
2522 |
+
- type: mrr_at_1
|
2523 |
+
value: 68.0
|
2524 |
+
- type: mrr_at_10
|
2525 |
+
value: 77.983
|
2526 |
+
- type: mrr_at_100
|
2527 |
+
value: 78.16499999999999
|
2528 |
+
- type: mrr_at_1000
|
2529 |
+
value: 78.16499999999999
|
2530 |
+
- type: mrr_at_20
|
2531 |
+
value: 78.16499999999999
|
2532 |
+
- type: mrr_at_3
|
2533 |
+
value: 75.667
|
2534 |
+
- type: mrr_at_5
|
2535 |
+
value: 77.067
|
2536 |
+
- type: ndcg_at_1
|
2537 |
+
value: 62.0
|
2538 |
+
- type: ndcg_at_10
|
2539 |
+
value: 47.772999999999996
|
2540 |
+
- type: ndcg_at_100
|
2541 |
+
value: 36.15
|
2542 |
+
- type: ndcg_at_1000
|
2543 |
+
value: 36.071
|
2544 |
+
- type: ndcg_at_20
|
2545 |
+
value: 44.641
|
2546 |
+
- type: ndcg_at_3
|
2547 |
+
value: 52.608999999999995
|
2548 |
+
- type: ndcg_at_5
|
2549 |
+
value: 50.397999999999996
|
2550 |
+
- type: precision_at_1
|
2551 |
+
value: 68.0
|
2552 |
+
- type: precision_at_10
|
2553 |
+
value: 50.8
|
2554 |
+
- type: precision_at_100
|
2555 |
+
value: 37.62
|
2556 |
+
- type: precision_at_1000
|
2557 |
+
value: 16.97
|
2558 |
+
- type: precision_at_20
|
2559 |
+
value: 47.099999999999994
|
2560 |
+
- type: precision_at_3
|
2561 |
+
value: 56.667
|
2562 |
+
- type: precision_at_5
|
2563 |
+
value: 54.0
|
2564 |
+
- type: recall_at_1
|
2565 |
+
value: 0.16999999999999998
|
2566 |
+
- type: recall_at_10
|
2567 |
+
value: 1.2349999999999999
|
2568 |
+
- type: recall_at_100
|
2569 |
+
value: 8.666
|
2570 |
+
- type: recall_at_1000
|
2571 |
+
value: 35.326
|
2572 |
+
- type: recall_at_20
|
2573 |
+
value: 2.276
|
2574 |
+
- type: recall_at_3
|
2575 |
+
value: 0.428
|
2576 |
+
- type: recall_at_5
|
2577 |
+
value: 0.672
|
2578 |
+
- task:
|
2579 |
+
type: Retrieval
|
2580 |
+
dataset:
|
2581 |
+
type: mteb/touche2020
|
2582 |
+
name: MTEB Touche2020
|
2583 |
+
config: default
|
2584 |
+
split: test
|
2585 |
+
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
|
2586 |
+
metrics:
|
2587 |
+
- type: map_at_1
|
2588 |
+
value: 1.897
|
2589 |
+
- type: map_at_10
|
2590 |
+
value: 6.034
|
2591 |
+
- type: map_at_100
|
2592 |
+
value: 10.475
|
2593 |
+
- type: map_at_1000
|
2594 |
+
value: 11.95
|
2595 |
+
- type: map_at_20
|
2596 |
+
value: 8.149000000000001
|
2597 |
+
- type: map_at_3
|
2598 |
+
value: 2.8449999999999998
|
2599 |
+
- type: map_at_5
|
2600 |
+
value: 3.972
|
2601 |
+
- type: mrr_at_1
|
2602 |
+
value: 24.490000000000002
|
2603 |
+
- type: mrr_at_10
|
2604 |
+
value: 33.751
|
2605 |
+
- type: mrr_at_100
|
2606 |
+
value: 35.544
|
2607 |
+
- type: mrr_at_1000
|
2608 |
+
value: 35.544
|
2609 |
+
- type: mrr_at_20
|
2610 |
+
value: 34.926
|
2611 |
+
- type: mrr_at_3
|
2612 |
+
value: 29.252
|
2613 |
+
- type: mrr_at_5
|
2614 |
+
value: 31.905
|
2615 |
+
- type: ndcg_at_1
|
2616 |
+
value: 22.448999999999998
|
2617 |
+
- type: ndcg_at_10
|
2618 |
+
value: 16.303
|
2619 |
+
- type: ndcg_at_100
|
2620 |
+
value: 27.165
|
2621 |
+
- type: ndcg_at_1000
|
2622 |
+
value: 39.736
|
2623 |
+
- type: ndcg_at_20
|
2624 |
+
value: 18.340999999999998
|
2625 |
+
- type: ndcg_at_3
|
2626 |
+
value: 15.137999999999998
|
2627 |
+
- type: ndcg_at_5
|
2628 |
+
value: 16.332
|
2629 |
+
- type: precision_at_1
|
2630 |
+
value: 24.490000000000002
|
2631 |
+
- type: precision_at_10
|
2632 |
+
value: 15.714
|
2633 |
+
- type: precision_at_100
|
2634 |
+
value: 6.184
|
2635 |
+
- type: precision_at_1000
|
2636 |
+
value: 1.439
|
2637 |
+
- type: precision_at_20
|
2638 |
+
value: 13.163
|
2639 |
+
- type: precision_at_3
|
2640 |
+
value: 15.645999999999999
|
2641 |
+
- type: precision_at_5
|
2642 |
+
value: 17.551
|
2643 |
+
- type: recall_at_1
|
2644 |
+
value: 1.897
|
2645 |
+
- type: recall_at_10
|
2646 |
+
value: 11.938
|
2647 |
+
- type: recall_at_100
|
2648 |
+
value: 39.249
|
2649 |
+
- type: recall_at_1000
|
2650 |
+
value: 78.121
|
2651 |
+
- type: recall_at_20
|
2652 |
+
value: 19.244
|
2653 |
+
- type: recall_at_3
|
2654 |
+
value: 3.5409999999999995
|
2655 |
+
- type: recall_at_5
|
2656 |
+
value: 6.297999999999999
|
2657 |
- task:
|
2658 |
type: Classification
|
2659 |
dataset:
|