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664
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691
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694
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829
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832
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833
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837
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840
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841
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848
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850
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851
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852
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855
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859
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866
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870
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871
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880
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881
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882
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885
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886
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893
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895
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901
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904
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905
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907
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908
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910
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912
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919
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920
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923
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925
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926
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927
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930
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931
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934
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937
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938
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940
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942
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949
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987
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991
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998
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1000
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1001
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1002
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1006
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1009
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1010
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1012
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1013
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1014
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1015
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1016
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1017
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1021
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1024
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1025
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1026
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1027
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1028
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1030
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1031
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1032
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1039
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1042
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1043
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1045
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1047
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1054
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1058
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1060
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1062
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1073
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1075
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1084
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1099
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1103
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1105
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1107
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1111
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1120
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1121
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1122
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1126
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1128
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1129
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1133
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1135
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1148
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1190
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1192
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1195
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1201
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1250
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+ args: fra-pan
1253
+ dataset:
1254
+ name: ntrex128
1255
+ type: ntrex128
1256
+ args: fra-pan
1257
+ metrics:
1258
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1259
+ type: bleu
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+ value: 10.2
1261
+ - name: chr-F
1262
+ type: chrf
1263
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1264
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+ name: Translation fra-urd
1266
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1267
+ args: fra-urd
1268
+ dataset:
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+ name: ntrex128
1270
+ type: ntrex128
1271
+ args: fra-urd
1272
+ metrics:
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1274
+ type: bleu
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+ value: 14.8
1276
+ - name: chr-F
1277
+ type: chrf
1278
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1279
+ - task:
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+ name: Translation por-fas
1281
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1282
+ args: por-fas
1283
+ dataset:
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+ name: ntrex128
1285
+ type: ntrex128
1286
+ args: por-fas
1287
+ metrics:
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1289
+ type: bleu
1290
+ value: 14.4
1291
+ - name: chr-F
1292
+ type: chrf
1293
+ value: 0.42010
1294
+ - task:
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+ name: Translation por-hin
1296
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1297
+ args: por-hin
1298
+ dataset:
1299
+ name: ntrex128
1300
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1301
+ args: por-hin
1302
+ metrics:
1303
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1304
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1305
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1306
+ - name: chr-F
1307
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1308
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1309
+ - task:
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+ name: Translation por-pan
1311
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1312
+ args: por-pan
1313
+ dataset:
1314
+ name: ntrex128
1315
+ type: ntrex128
1316
+ args: por-pan
1317
+ metrics:
1318
+ - name: BLEU
1319
+ type: bleu
1320
+ value: 10.6
1321
+ - name: chr-F
1322
+ type: chrf
1323
+ value: 0.36360
1324
+ - task:
1325
+ name: Translation por-urd
1326
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1327
+ args: por-urd
1328
+ dataset:
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+ name: ntrex128
1330
+ type: ntrex128
1331
+ args: por-urd
1332
+ metrics:
1333
+ - name: BLEU
1334
+ type: bleu
1335
+ value: 15.2
1336
+ - name: chr-F
1337
+ type: chrf
1338
+ value: 0.42484
1339
+ - task:
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+ name: Translation spa-ben
1341
+ type: translation
1342
+ args: spa-ben
1343
+ dataset:
1344
+ name: ntrex128
1345
+ type: ntrex128
1346
+ args: spa-ben
1347
+ metrics:
1348
+ - name: BLEU
1349
+ type: bleu
1350
+ value: 10.3
1351
+ - name: chr-F
1352
+ type: chrf
1353
+ value: 0.44905
1354
+ - task:
1355
+ name: Translation spa-fas
1356
+ type: translation
1357
+ args: spa-fas
1358
+ dataset:
1359
+ name: ntrex128
1360
+ type: ntrex128
1361
+ args: spa-fas
1362
+ metrics:
1363
+ - name: BLEU
1364
+ type: bleu
1365
+ value: 14.1
1366
+ - name: chr-F
1367
+ type: chrf
1368
+ value: 0.42207
1369
+ - task:
1370
+ name: Translation spa-hin
1371
+ type: translation
1372
+ args: spa-hin
1373
+ dataset:
1374
+ name: ntrex128
1375
+ type: ntrex128
1376
+ args: spa-hin
1377
+ metrics:
1378
+ - name: BLEU
1379
+ type: bleu
1380
+ value: 17.6
1381
+ - name: chr-F
1382
+ type: chrf
1383
+ value: 0.43380
1384
+ - task:
1385
+ name: Translation spa-pan
1386
+ type: translation
1387
+ args: spa-pan
1388
+ dataset:
1389
+ name: ntrex128
1390
+ type: ntrex128
1391
+ args: spa-pan
1392
+ metrics:
1393
+ - name: BLEU
1394
+ type: bleu
1395
+ value: 11.1
1396
+ - name: chr-F
1397
+ type: chrf
1398
+ value: 0.37361
1399
+ - task:
1400
+ name: Translation spa-prs
1401
+ type: translation
1402
+ args: spa-prs
1403
+ dataset:
1404
+ name: ntrex128
1405
+ type: ntrex128
1406
+ args: spa-prs
1407
+ metrics:
1408
+ - name: BLEU
1409
+ type: bleu
1410
+ value: 10.3
1411
+ - name: chr-F
1412
+ type: chrf
1413
+ value: 0.37448
1414
+ - task:
1415
+ name: Translation spa-urd
1416
+ type: translation
1417
+ args: spa-urd
1418
+ dataset:
1419
+ name: ntrex128
1420
+ type: ntrex128
1421
+ args: spa-urd
1422
+ metrics:
1423
+ - name: BLEU
1424
+ type: bleu
1425
+ value: 15.0
1426
+ - name: chr-F
1427
+ type: chrf
1428
+ value: 0.42434
1429
+ - task:
1430
+ name: Translation deu-fas
1431
+ type: translation
1432
+ args: deu-fas
1433
+ dataset:
1434
+ name: tatoeba-test-v2021-08-07
1435
+ type: tatoeba_mt
1436
+ args: deu-fas
1437
+ metrics:
1438
+ - name: BLEU
1439
+ type: bleu
1440
+ value: 20.3
1441
+ - name: chr-F
1442
+ type: chrf
1443
+ value: 0.45763
1444
+ - task:
1445
+ name: Translation eng-hin
1446
+ type: translation
1447
+ args: eng-hin
1448
+ dataset:
1449
+ name: tatoeba-test-v2021-08-07
1450
+ type: tatoeba_mt
1451
+ args: eng-hin
1452
+ metrics:
1453
+ - name: BLEU
1454
+ type: bleu
1455
+ value: 28.4
1456
+ - name: chr-F
1457
+ type: chrf
1458
+ value: 0.52525
1459
+ - task:
1460
+ name: Translation eng-mar
1461
+ type: translation
1462
+ args: eng-mar
1463
+ dataset:
1464
+ name: tatoeba-test-v2021-08-07
1465
+ type: tatoeba_mt
1466
+ args: eng-mar
1467
+ metrics:
1468
+ - name: BLEU
1469
+ type: bleu
1470
+ value: 24.4
1471
+ - name: chr-F
1472
+ type: chrf
1473
+ value: 0.52549
1474
+ - task:
1475
+ name: Translation eng-ben
1476
+ type: translation
1477
+ args: eng-ben
1478
+ dataset:
1479
+ name: tico19-test
1480
+ type: tico19-test
1481
+ args: eng-ben
1482
+ metrics:
1483
+ - name: BLEU
1484
+ type: bleu
1485
+ value: 17.9
1486
+ - name: chr-F
1487
+ type: chrf
1488
+ value: 0.51563
1489
+ - task:
1490
+ name: Translation eng-fas
1491
+ type: translation
1492
+ args: eng-fas
1493
+ dataset:
1494
+ name: tico19-test
1495
+ type: tico19-test
1496
+ args: eng-fas
1497
+ metrics:
1498
+ - name: BLEU
1499
+ type: bleu
1500
+ value: 25.8
1501
+ - name: chr-F
1502
+ type: chrf
1503
+ value: 0.53182
1504
+ - task:
1505
+ name: Translation eng-hin
1506
+ type: translation
1507
+ args: eng-hin
1508
+ dataset:
1509
+ name: tico19-test
1510
+ type: tico19-test
1511
+ args: eng-hin
1512
+ metrics:
1513
+ - name: BLEU
1514
+ type: bleu
1515
+ value: 41.6
1516
+ - name: chr-F
1517
+ type: chrf
1518
+ value: 0.63128
1519
+ - task:
1520
+ name: Translation eng-mar
1521
+ type: translation
1522
+ args: eng-mar
1523
+ dataset:
1524
+ name: tico19-test
1525
+ type: tico19-test
1526
+ args: eng-mar
1527
+ metrics:
1528
+ - name: BLEU
1529
+ type: bleu
1530
+ value: 12.9
1531
+ - name: chr-F
1532
+ type: chrf
1533
+ value: 0.45619
1534
+ - task:
1535
+ name: Translation eng-nep
1536
+ type: translation
1537
+ args: eng-nep
1538
+ dataset:
1539
+ name: tico19-test
1540
+ type: tico19-test
1541
+ args: eng-nep
1542
+ metrics:
1543
+ - name: BLEU
1544
+ type: bleu
1545
+ value: 17.6
1546
+ - name: chr-F
1547
+ type: chrf
1548
+ value: 0.53413
1549
+ - task:
1550
+ name: Translation eng-prs
1551
+ type: translation
1552
+ args: eng-prs
1553
+ dataset:
1554
+ name: tico19-test
1555
+ type: tico19-test
1556
+ args: eng-prs
1557
+ metrics:
1558
+ - name: BLEU
1559
+ type: bleu
1560
+ value: 17.3
1561
+ - name: chr-F
1562
+ type: chrf
1563
+ value: 0.44101
1564
+ - task:
1565
+ name: Translation eng-pus
1566
+ type: translation
1567
+ args: eng-pus
1568
+ dataset:
1569
+ name: tico19-test
1570
+ type: tico19-test
1571
+ args: eng-pus
1572
+ metrics:
1573
+ - name: BLEU
1574
+ type: bleu
1575
+ value: 20.5
1576
+ - name: chr-F
1577
+ type: chrf
1578
+ value: 0.47063
1579
+ - task:
1580
+ name: Translation eng-urd
1581
+ type: translation
1582
+ args: eng-urd
1583
+ dataset:
1584
+ name: tico19-test
1585
+ type: tico19-test
1586
+ args: eng-urd
1587
+ metrics:
1588
+ - name: BLEU
1589
+ type: bleu
1590
+ value: 22.0
1591
+ - name: chr-F
1592
+ type: chrf
1593
+ value: 0.51054
1594
+ - task:
1595
+ name: Translation fra-fas
1596
+ type: translation
1597
+ args: fra-fas
1598
+ dataset:
1599
+ name: tico19-test
1600
+ type: tico19-test
1601
+ args: fra-fas
1602
+ metrics:
1603
+ - name: BLEU
1604
+ type: bleu
1605
+ value: 17.9
1606
+ - name: chr-F
1607
+ type: chrf
1608
+ value: 0.43476
1609
+ - task:
1610
+ name: Translation fra-hin
1611
+ type: translation
1612
+ args: fra-hin
1613
+ dataset:
1614
+ name: tico19-test
1615
+ type: tico19-test
1616
+ args: fra-hin
1617
+ metrics:
1618
+ - name: BLEU
1619
+ type: bleu
1620
+ value: 25.6
1621
+ - name: chr-F
1622
+ type: chrf
1623
+ value: 0.48625
1624
+ - task:
1625
+ name: Translation fra-prs
1626
+ type: translation
1627
+ args: fra-prs
1628
+ dataset:
1629
+ name: tico19-test
1630
+ type: tico19-test
1631
+ args: fra-prs
1632
+ metrics:
1633
+ - name: BLEU
1634
+ type: bleu
1635
+ value: 11.6
1636
+ - name: chr-F
1637
+ type: chrf
1638
+ value: 0.36130
1639
+ - task:
1640
+ name: Translation fra-pus
1641
+ type: translation
1642
+ args: fra-pus
1643
+ dataset:
1644
+ name: tico19-test
1645
+ type: tico19-test
1646
+ args: fra-pus
1647
+ metrics:
1648
+ - name: BLEU
1649
+ type: bleu
1650
+ value: 12.7
1651
+ - name: chr-F
1652
+ type: chrf
1653
+ value: 0.37217
1654
+ - task:
1655
+ name: Translation fra-urd
1656
+ type: translation
1657
+ args: fra-urd
1658
+ dataset:
1659
+ name: tico19-test
1660
+ type: tico19-test
1661
+ args: fra-urd
1662
+ metrics:
1663
+ - name: BLEU
1664
+ type: bleu
1665
+ value: 14.4
1666
+ - name: chr-F
1667
+ type: chrf
1668
+ value: 0.40482
1669
+ - task:
1670
+ name: Translation por-ben
1671
+ type: translation
1672
+ args: por-ben
1673
+ dataset:
1674
+ name: tico19-test
1675
+ type: tico19-test
1676
+ args: por-ben
1677
+ metrics:
1678
+ - name: BLEU
1679
+ type: bleu
1680
+ value: 12.5
1681
+ - name: chr-F
1682
+ type: chrf
1683
+ value: 0.45814
1684
+ - task:
1685
+ name: Translation por-fas
1686
+ type: translation
1687
+ args: por-fas
1688
+ dataset:
1689
+ name: tico19-test
1690
+ type: tico19-test
1691
+ args: por-fas
1692
+ metrics:
1693
+ - name: BLEU
1694
+ type: bleu
1695
+ value: 21.3
1696
+ - name: chr-F
1697
+ type: chrf
1698
+ value: 0.49181
1699
+ - task:
1700
+ name: Translation por-hin
1701
+ type: translation
1702
+ args: por-hin
1703
+ dataset:
1704
+ name: tico19-test
1705
+ type: tico19-test
1706
+ args: por-hin
1707
+ metrics:
1708
+ - name: BLEU
1709
+ type: bleu
1710
+ value: 31.1
1711
+ - name: chr-F
1712
+ type: chrf
1713
+ value: 0.55759
1714
+ - task:
1715
+ name: Translation por-nep
1716
+ type: translation
1717
+ args: por-nep
1718
+ dataset:
1719
+ name: tico19-test
1720
+ type: tico19-test
1721
+ args: por-nep
1722
+ metrics:
1723
+ - name: BLEU
1724
+ type: bleu
1725
+ value: 12.1
1726
+ - name: chr-F
1727
+ type: chrf
1728
+ value: 0.47378
1729
+ - task:
1730
+ name: Translation por-prs
1731
+ type: translation
1732
+ args: por-prs
1733
+ dataset:
1734
+ name: tico19-test
1735
+ type: tico19-test
1736
+ args: por-prs
1737
+ metrics:
1738
+ - name: BLEU
1739
+ type: bleu
1740
+ value: 12.1
1741
+ - name: chr-F
1742
+ type: chrf
1743
+ value: 0.38725
1744
+ - task:
1745
+ name: Translation por-pus
1746
+ type: translation
1747
+ args: por-pus
1748
+ dataset:
1749
+ name: tico19-test
1750
+ type: tico19-test
1751
+ args: por-pus
1752
+ metrics:
1753
+ - name: BLEU
1754
+ type: bleu
1755
+ value: 15.9
1756
+ - name: chr-F
1757
+ type: chrf
1758
+ value: 0.42496
1759
+ - task:
1760
+ name: Translation por-urd
1761
+ type: translation
1762
+ args: por-urd
1763
+ dataset:
1764
+ name: tico19-test
1765
+ type: tico19-test
1766
+ args: por-urd
1767
+ metrics:
1768
+ - name: BLEU
1769
+ type: bleu
1770
+ value: 16.6
1771
+ - name: chr-F
1772
+ type: chrf
1773
+ value: 0.45560
1774
+ - task:
1775
+ name: Translation spa-ben
1776
+ type: translation
1777
+ args: spa-ben
1778
+ dataset:
1779
+ name: tico19-test
1780
+ type: tico19-test
1781
+ args: spa-ben
1782
+ metrics:
1783
+ - name: BLEU
1784
+ type: bleu
1785
+ value: 12.7
1786
+ - name: chr-F
1787
+ type: chrf
1788
+ value: 0.45751
1789
+ - task:
1790
+ name: Translation spa-fas
1791
+ type: translation
1792
+ args: spa-fas
1793
+ dataset:
1794
+ name: tico19-test
1795
+ type: tico19-test
1796
+ args: spa-fas
1797
+ metrics:
1798
+ - name: BLEU
1799
+ type: bleu
1800
+ value: 21.0
1801
+ - name: chr-F
1802
+ type: chrf
1803
+ value: 0.48974
1804
+ - task:
1805
+ name: Translation spa-hin
1806
+ type: translation
1807
+ args: spa-hin
1808
+ dataset:
1809
+ name: tico19-test
1810
+ type: tico19-test
1811
+ args: spa-hin
1812
+ metrics:
1813
+ - name: BLEU
1814
+ type: bleu
1815
+ value: 30.9
1816
+ - name: chr-F
1817
+ type: chrf
1818
+ value: 0.55641
1819
+ - task:
1820
+ name: Translation spa-nep
1821
+ type: translation
1822
+ args: spa-nep
1823
+ dataset:
1824
+ name: tico19-test
1825
+ type: tico19-test
1826
+ args: spa-nep
1827
+ metrics:
1828
+ - name: BLEU
1829
+ type: bleu
1830
+ value: 12.1
1831
+ - name: chr-F
1832
+ type: chrf
1833
+ value: 0.47164
1834
+ - task:
1835
+ name: Translation spa-prs
1836
+ type: translation
1837
+ args: spa-prs
1838
+ dataset:
1839
+ name: tico19-test
1840
+ type: tico19-test
1841
+ args: spa-prs
1842
+ metrics:
1843
+ - name: BLEU
1844
+ type: bleu
1845
+ value: 14.3
1846
+ - name: chr-F
1847
+ type: chrf
1848
+ value: 0.41879
1849
+ - task:
1850
+ name: Translation spa-pus
1851
+ type: translation
1852
+ args: spa-pus
1853
+ dataset:
1854
+ name: tico19-test
1855
+ type: tico19-test
1856
+ args: spa-pus
1857
+ metrics:
1858
+ - name: BLEU
1859
+ type: bleu
1860
+ value: 15.1
1861
+ - name: chr-F
1862
+ type: chrf
1863
+ value: 0.41714
1864
+ - task:
1865
+ name: Translation spa-urd
1866
+ type: translation
1867
+ args: spa-urd
1868
+ dataset:
1869
+ name: tico19-test
1870
+ type: tico19-test
1871
+ args: spa-urd
1872
+ metrics:
1873
+ - name: BLEU
1874
+ type: bleu
1875
+ value: 15.3
1876
+ - name: chr-F
1877
+ type: chrf
1878
+ value: 0.44931
1879
+ - task:
1880
+ name: Translation eng-hin
1881
+ type: translation
1882
+ args: eng-hin
1883
+ dataset:
1884
+ name: newstest2014
1885
+ type: wmt-2014-news
1886
+ args: eng-hin
1887
+ metrics:
1888
+ - name: BLEU
1889
+ type: bleu
1890
+ value: 23.6
1891
+ - name: chr-F
1892
+ type: chrf
1893
+ value: 0.51249
1894
+ - task:
1895
+ name: Translation eng-guj
1896
+ type: translation
1897
+ args: eng-guj
1898
+ dataset:
1899
+ name: newstest2019
1900
+ type: wmt-2019-news
1901
+ args: eng-guj
1902
+ metrics:
1903
+ - name: BLEU
1904
+ type: bleu
1905
+ value: 25.5
1906
+ - name: chr-F
1907
+ type: chrf
1908
+ value: 0.57282
1909
+ ---
1910
+ # opus-mt-tc-bible-big-deu_eng_fra_por_spa-iir
1911
+
1912
+ ## Table of Contents
1913
+ - [Model Details](#model-details)
1914
+ - [Uses](#uses)
1915
+ - [Risks, Limitations and Biases](#risks-limitations-and-biases)
1916
+ - [How to Get Started With the Model](#how-to-get-started-with-the-model)
1917
+ - [Training](#training)
1918
+ - [Evaluation](#evaluation)
1919
+ - [Citation Information](#citation-information)
1920
+ - [Acknowledgements](#acknowledgements)
1921
+
1922
+ ## Model Details
1923
+
1924
+ Neural machine translation model for translating from unknown (deu+eng+fra+por+spa) to Indo-Iranian languages (iir).
1925
+
1926
+ This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train).
1927
+ **Model Description:**
1928
+ - **Developed by:** Language Technology Research Group at the University of Helsinki
1929
+ - **Model Type:** Translation (transformer-big)
1930
+ - **Release**: 2024-05-30
1931
+ - **License:** Apache-2.0
1932
+ - **Language(s):**
1933
+ - Source Language(s): deu eng fra por spa
1934
+ - Target Language(s): anp asm awa bal ben bho bpy ckb diq div dty fas gbm glk guj hif hin hne hns jdt kas kmr kok kur lah lrc mag mai mar mzn nep npi ori oss pal pan pes pli prs pus rhg rmy rom san sdh sin skr snd syl tgk tly urd zza
1935
+ - Valid Target Language Labels: >>aee<< >>aeq<< >>aiq<< >>anp<< >>anr<< >>ask<< >>asm<< >>atn<< >>avd<< >>ave<< >>awa<< >>bal<< >>bal_Latn<< >>bdv<< >>ben<< >>bfb<< >>bfy<< >>bfz<< >>bgc<< >>bgd<< >>bge<< >>bgw<< >>bha<< >>bhb<< >>bhd<< >>bhe<< >>bhh<< >>bhi<< >>bho<< >>bht<< >>bhu<< >>bjj<< >>bjm<< >>bkk<< >>bmj<< >>bns<< >>bpx<< >>bpy<< >>bqi<< >>bra<< >>bsg<< >>bsh<< >>btv<< >>ccp<< >>cdh<< >>cdi<< >>cdj<< >>cih<< >>ckb<< >>clh<< >>ctg<< >>dcc<< >>def<< >>deh<< >>dhn<< >>dho<< >>diq<< >>div<< >>dmk<< >>dml<< >>doi<< >>dry<< >>dty<< >>dub<< >>duh<< >>dwz<< >>emx<< >>esh<< >>fas<< >>fay<< >>gas<< >>gbk<< >>gbl<< >>gbm<< >>gbz<< >>gdx<< >>ggg<< >>ghr<< >>gig<< >>gjk<< >>glh<< >>glk<< >>goz<< >>gra<< >>guj<< >>gwc<< >>gwf<< >>gwt<< >>gzi<< >>hac<< >>haj<< >>haz<< >>hca<< >>hif<< >>hif_Latn<< >>hii<< >>hin<< >>hin_Latn<< >>hlb<< >>hne<< >>hns<< >>hrz<< >>isk<< >>jdg<< >>jdt<< >>jdt_Cyrl<< >>jml<< >>jnd<< >>jns<< >>jpr<< >>kas<< >>kas_Arab<< >>kas_Deva<< >>kbu<< >>keq<< >>key<< >>kfm<< >>kfr<< >>kfs<< >>kft<< >>kfu<< >>kfv<< >>kfx<< >>kfy<< >>kgn<< >>khn<< >>kho<< >>khw<< >>kjo<< >>kls<< >>kmr<< >>kok<< >>kra<< >>ksy<< >>ktl<< >>kur<< >>kur_Arab<< >>kur_Cyrl<< >>kur_Latn<< >>kvx<< >>kxp<< >>kyw<< >>lah<< >>lbm<< >>lhl<< >>lki<< >>lmn<< >>lrc<< >>lrl<< >>lsa<< >>lss<< >>luv<< >>luz<< >>mag<< >>mai<< >>mar<< >>mby<< >>mjl<< >>mjz<< >>mkb<< >>mke<< >>mki<< >>mnj<< >>mvy<< >>mwr<< >>mzn<< >>nag<< >>nep<< >>nhh<< >>nli<< >>nlx<< >>noe<< >>noi<< >>npi<< >>ntz<< >>nyq<< >>odk<< >>okh<< >>omr<< >>oos<< >>ori<< >>ort<< >>oru<< >>oss<< >>pal<< >>pan<< >>pan_Guru<< >>paq<< >>pcl<< >>peo<< >>pes<< >>pgg<< >>phd<< >>phl<< >>phv<< >>pli<< >>plk<< >>plp<< >>pmh<< >>prc<< >>prn<< >>prs<< >>psh<< >>psi<< >>psu<< >>pus<< >>pwr<< >>raj<< >>rat<< >>rdb<< >>rei<< >>rhg<< >>rhg_Latn<< >>rjs<< >>rkt<< >>rmi<< >>rmq<< >>rmt<< >>rmy<< >>rom<< >>rtw<< >>san<< >>san_Deva<< >>saz<< >>sbn<< >>sck<< >>scl<< >>sdb<< >>sdf<< >>sdg<< >>sdh<< >>sdr<< >>sgh<< >>sgl<< >>sgr<< >>sgy<< >>shd<< >>shm<< >>sin<< >>siy<< >>sjp<< >>skr<< >>smm<< >>smv<< >>smy<< >>snd<< >>snd_Arab<< >>sog<< >>soi<< >>soj<< >>sqo<< >>srh<< >>srx<< >>srz<< >>ssi<< >>sts<< >>syl<< >>syl_Sylo<< >>tdb<< >>tgk<< >>tgk_Cyrl<< >>tgk_Latn<< >>the<< >>thl<< >>thq<< >>thr<< >>tkb<< >>tks<< >>tkt<< >>tly<< >>tly_Latn<< >>tnv<< >>tov<< >>tra<< >>trm<< >>trw<< >>ttt<< >>urd<< >>ush<< >>vaa<< >>vaf<< >>vah<< >>vas<< >>vav<< >>ved<< >>vgr<< >>vmh<< >>wbk<< >>wbl<< >>wne<< >>wsv<< >>wtm<< >>xbc<< >>xco<< >>xka<< >>xkc<< >>xkj<< >>xkp<< >>xpr<< >>xsc<< >>xtq<< >>xvi<< >>xxx<< >>yah<< >>yai<< >>ydg<< >>zum<< >>zza<<
1936
+ - **Original Model**: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/deu+eng+fra+por+spa-iir/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip)
1937
+ - **Resources for more information:**
1938
+ - [OPUS-MT dashboard](https://opus.nlpl.eu/dashboard/index.php?pkg=opusmt&test=all&scoreslang=all&chart=standard&model=Tatoeba-MT-models/deu%2Beng%2Bfra%2Bpor%2Bspa-iir/opusTCv20230926max50%2Bbt%2Bjhubc_transformer-big_2024-05-30)
1939
+ - [OPUS-MT-train GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
1940
+ - [More information about MarianNMT models in the transformers library](https://huggingface.co/docs/transformers/model_doc/marian)
1941
+ - [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/)
1942
+ - [HPLT bilingual data v1 (as part of the Tatoeba Translation Challenge dataset)](https://hplt-project.org/datasets/v1)
1943
+ - [A massively parallel Bible corpus](https://aclanthology.org/L14-1215/)
1944
+
1945
+ This is a multilingual translation model with multiple target languages. A sentence initial language token is required in the form of `>>id<<` (id = valid target language ID), e.g. `>>anp<<`
1946
+
1947
+ ## Uses
1948
+
1949
+ This model can be used for translation and text-to-text generation.
1950
+
1951
+ ## Risks, Limitations and Biases
1952
+
1953
+ **CONTENT WARNING: Readers should be aware that the model is trained on various public data sets that may contain content that is disturbing, offensive, and can propagate historical and current stereotypes.**
1954
+
1955
+ Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)).
1956
+
1957
+ ## How to Get Started With the Model
1958
+
1959
+ A short example code:
1960
+
1961
+ ```python
1962
+ from transformers import MarianMTModel, MarianTokenizer
1963
+
1964
+ src_text = [
1965
+ ">>anp<< Replace this with text in an accepted source language.",
1966
+ ">>zza<< This is the second sentence."
1967
+ ]
1968
+
1969
+ model_name = "pytorch-models/opus-mt-tc-bible-big-deu_eng_fra_por_spa-iir"
1970
+ tokenizer = MarianTokenizer.from_pretrained(model_name)
1971
+ model = MarianMTModel.from_pretrained(model_name)
1972
+ translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True))
1973
+
1974
+ for t in translated:
1975
+ print( tokenizer.decode(t, skip_special_tokens=True) )
1976
+ ```
1977
+
1978
+ You can also use OPUS-MT models with the transformers pipelines, for example:
1979
+
1980
+ ```python
1981
+ from transformers import pipeline
1982
+ pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-bible-big-deu_eng_fra_por_spa-iir")
1983
+ print(pipe(">>anp<< Replace this with text in an accepted source language."))
1984
+ ```
1985
+
1986
+ ## Training
1987
+
1988
+ - **Data**: opusTCv20230926max50+bt+jhubc ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
1989
+ - **Pre-processing**: SentencePiece (spm32k,spm32k)
1990
+ - **Model Type:** transformer-big
1991
+ - **Original MarianNMT Model**: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/deu+eng+fra+por+spa-iir/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-30.zip)
1992
+ - **Training Scripts**: [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
1993
+
1994
+ ## Evaluation
1995
+
1996
+ * [Model scores at the OPUS-MT dashboard](https://opus.nlpl.eu/dashboard/index.php?pkg=opusmt&test=all&scoreslang=all&chart=standard&model=Tatoeba-MT-models/deu%2Beng%2Bfra%2Bpor%2Bspa-iir/opusTCv20230926max50%2Bbt%2Bjhubc_transformer-big_2024-05-30)
1997
+ * test set translations: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/deu+eng+fra+por+spa-iir/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.test.txt)
1998
+ * test set scores: [opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/deu+eng+fra+por+spa-iir/opusTCv20230926max50+bt+jhubc_transformer-big_2024-05-29.eval.txt)
1999
+ * benchmark results: [benchmark_results.txt](benchmark_results.txt)
2000
+ * benchmark output: [benchmark_translations.zip](benchmark_translations.zip)
2001
+
2002
+ | langpair | testset | chr-F | BLEU | #sent | #words |
2003
+ |----------|---------|-------|-------|-------|--------|
2004
+ | deu-fas | tatoeba-test-v2021-08-07 | 0.45763 | 20.3 | 3185 | 24941 |
2005
+ | deu-kur_Latn | tatoeba-test-v2021-08-07 | 1.027 | 0.6 | 223 | 1249 |
2006
+ | eng-ben | tatoeba-test-v2021-08-07 | 0.47927 | 17.6 | 2500 | 11654 |
2007
+ | eng-fas | tatoeba-test-v2021-08-07 | 0.40192 | 17.1 | 3762 | 31110 |
2008
+ | eng-hin | tatoeba-test-v2021-08-07 | 0.52525 | 28.4 | 5000 | 32904 |
2009
+ | eng-kur_Latn | tatoeba-test-v2021-08-07 | 0.493 | 0.0 | 290 | 1682 |
2010
+ | eng-mar | tatoeba-test-v2021-08-07 | 0.52549 | 24.4 | 10396 | 61140 |
2011
+ | eng-pes | tatoeba-test-v2021-08-07 | 0.40401 | 17.3 | 3757 | 31044 |
2012
+ | eng-urd | tatoeba-test-v2021-08-07 | 0.45764 | 18.1 | 1663 | 12155 |
2013
+ | fra-fas | tatoeba-test-v2021-08-07 | 0.42414 | 18.9 | 376 | 3217 |
2014
+ | deu-npi | flores101-devtest | 3.082 | 0.2 | 1012 | 19762 |
2015
+ | eng-ben | flores101-devtest | 0.51055 | 17.0 | 1012 | 21155 |
2016
+ | eng-ckb | flores101-devtest | 0.45337 | 7.1 | 1012 | 21159 |
2017
+ | eng-guj | flores101-devtest | 0.53972 | 22.3 | 1012 | 23840 |
2018
+ | eng-hin | flores101-devtest | 0.57980 | 33.4 | 1012 | 27743 |
2019
+ | eng-mar | flores101-devtest | 0.48206 | 14.3 | 1012 | 21810 |
2020
+ | eng-urd | flores101-devtest | 0.48050 | 20.5 | 1012 | 28098 |
2021
+ | fra-ben | flores101-devtest | 0.43806 | 10.9 | 1012 | 21155 |
2022
+ | fra-ckb | flores101-devtest | 0.41016 | 4.9 | 1012 | 21159 |
2023
+ | por-ben | flores101-devtest | 0.42730 | 10.0 | 1012 | 21155 |
2024
+ | por-npi | flores101-devtest | 2.084 | 0.2 | 1012 | 19762 |
2025
+ | spa-hin | flores101-devtest | 0.43371 | 16.0 | 1012 | 27743 |
2026
+ | deu-ben | flores200-devtest | 0.44005 | 10.6 | 1012 | 21155 |
2027
+ | deu-hin | flores200-devtest | 0.48448 | 22.3 | 1012 | 27743 |
2028
+ | deu-hne | flores200-devtest | 0.42659 | 13.8 | 1012 | 26582 |
2029
+ | deu-mag | flores200-devtest | 0.42477 | 14.0 | 1012 | 26516 |
2030
+ | deu-npi | flores200-devtest | 5.870 | 0.1 | 1012 | 19762 |
2031
+ | deu-pes | flores200-devtest | 0.42726 | 14.9 | 1012 | 24986 |
2032
+ | deu-tgk | flores200-devtest | 0.40932 | 12.9 | 1012 | 25530 |
2033
+ | deu-urd | flores200-devtest | 0.41250 | 14.4 | 1012 | 28098 |
2034
+ | eng-ben | flores200-devtest | 0.51361 | 17.1 | 1012 | 21155 |
2035
+ | eng-ckb | flores200-devtest | 0.45750 | 7.7 | 1012 | 21152 |
2036
+ | eng-guj | flores200-devtest | 0.54231 | 22.4 | 1012 | 23840 |
2037
+ | eng-hin | flores200-devtest | 0.58371 | 33.7 | 1012 | 27743 |
2038
+ | eng-hne | flores200-devtest | 0.47591 | 19.9 | 1012 | 26582 |
2039
+ | eng-mag | flores200-devtest | 0.51070 | 22.2 | 1012 | 26516 |
2040
+ | eng-mar | flores200-devtest | 0.48733 | 14.8 | 1012 | 21810 |
2041
+ | eng-pan | flores200-devtest | 0.45015 | 18.1 | 1012 | 27451 |
2042
+ | eng-pes | flores200-devtest | 0.48588 | 21.1 | 1012 | 24986 |
2043
+ | eng-prs | flores200-devtest | 0.51879 | 24.5 | 1012 | 25885 |
2044
+ | eng-sin | flores200-devtest | 0.43823 | 10.6 | 1012 | 23278 |
2045
+ | eng-tgk | flores200-devtest | 0.47323 | 17.8 | 1012 | 25530 |
2046
+ | eng-urd | flores200-devtest | 0.48212 | 20.4 | 1012 | 28098 |
2047
+ | fra-ben | flores200-devtest | 0.44029 | 11.0 | 1012 | 21155 |
2048
+ | fra-ckb | flores200-devtest | 0.41353 | 5.3 | 1012 | 21152 |
2049
+ | fra-hin | flores200-devtest | 0.48406 | 22.6 | 1012 | 27743 |
2050
+ | fra-hne | flores200-devtest | 0.42353 | 13.9 | 1012 | 26582 |
2051
+ | fra-mag | flores200-devtest | 0.42678 | 14.3 | 1012 | 26516 |
2052
+ | fra-npi | flores200-devtest | 6.525 | 0.1 | 1012 | 19762 |
2053
+ | fra-pes | flores200-devtest | 0.43526 | 15.5 | 1012 | 24986 |
2054
+ | fra-tgk | flores200-devtest | 0.42982 | 13.7 | 1012 | 25530 |
2055
+ | fra-urd | flores200-devtest | 0.41438 | 14.2 | 1012 | 28098 |
2056
+ | por-ben | flores200-devtest | 0.43390 | 10.4 | 1012 | 21155 |
2057
+ | por-ckb | flores200-devtest | 0.42303 | 5.6 | 1012 | 21152 |
2058
+ | por-hin | flores200-devtest | 0.49524 | 23.6 | 1012 | 27743 |
2059
+ | por-hne | flores200-devtest | 0.42269 | 13.9 | 1012 | 26582 |
2060
+ | por-mag | flores200-devtest | 0.42753 | 15.0 | 1012 | 26516 |
2061
+ | por-npi | flores200-devtest | 6.737 | 0.1 | 1012 | 19762 |
2062
+ | por-pes | flores200-devtest | 0.43194 | 15.4 | 1012 | 24986 |
2063
+ | por-tgk | flores200-devtest | 0.41860 | 13.2 | 1012 | 25530 |
2064
+ | por-urd | flores200-devtest | 0.41799 | 14.8 | 1012 | 28098 |
2065
+ | spa-ben | flores200-devtest | 0.41893 | 8.3 | 1012 | 21155 |
2066
+ | spa-hin | flores200-devtest | 0.43777 | 16.4 | 1012 | 27743 |
2067
+ | spa-kas_Arab | flores200-devtest | 9.380 | 0.1 | 1012 | 23514 |
2068
+ | spa-npi | flores200-devtest | 7.518 | 0.2 | 1012 | 19762 |
2069
+ | spa-pes | flores200-devtest | 0.40856 | 12.2 | 1012 | 24986 |
2070
+ | spa-prs | flores200-devtest | 0.40361 | 12.8 | 1012 | 25885 |
2071
+ | spa-tgk | flores200-devtest | 0.40100 | 10.8 | 1012 | 25530 |
2072
+ | eng-hin | newstest2014 | 0.51249 | 23.6 | 2507 | 60872 |
2073
+ | eng-guj | newstest2019 | 0.57282 | 25.5 | 998 | 21924 |
2074
+ | deu-ben | ntrex128 | 0.43971 | 9.6 | 1997 | 40095 |
2075
+ | deu-fas | ntrex128 | 0.41469 | 13.8 | 1997 | 50525 |
2076
+ | deu-hin | ntrex128 | 0.42940 | 16.8 | 1997 | 55219 |
2077
+ | deu-snd_Arab | ntrex128 | 6.129 | 0.1 | 1997 | 49866 |
2078
+ | deu-urd | ntrex128 | 0.41881 | 14.5 | 1997 | 54259 |
2079
+ | eng-ben | ntrex128 | 0.51555 | 16.6 | 1997 | 40095 |
2080
+ | eng-fas | ntrex128 | 0.46895 | 19.7 | 1997 | 50525 |
2081
+ | eng-guj | ntrex128 | 0.48990 | 17.1 | 1997 | 45335 |
2082
+ | eng-hin | ntrex128 | 0.52307 | 26.9 | 1997 | 55219 |
2083
+ | eng-mar | ntrex128 | 0.44580 | 10.4 | 1997 | 42375 |
2084
+ | eng-nep | ntrex128 | 0.42955 | 8.4 | 1997 | 40570 |
2085
+ | eng-pan | ntrex128 | 0.46141 | 19.6 | 1997 | 54355 |
2086
+ | eng-sin | ntrex128 | 0.42236 | 9.7 | 1997 | 44429 |
2087
+ | eng-snd_Arab | ntrex128 | 1.932 | 0.1 | 1997 | 49866 |
2088
+ | eng-urd | ntrex128 | 0.49646 | 22.1 | 1997 | 54259 |
2089
+ | fra-ben | ntrex128 | 0.41716 | 8.9 | 1997 | 40095 |
2090
+ | fra-fas | ntrex128 | 0.41282 | 13.8 | 1997 | 50525 |
2091
+ | fra-hin | ntrex128 | 0.42475 | 17.1 | 1997 | 55219 |
2092
+ | fra-snd_Arab | ntrex128 | 6.047 | 0.0 | 1997 | 49866 |
2093
+ | fra-urd | ntrex128 | 0.41536 | 14.8 | 1997 | 54259 |
2094
+ | por-ben | ntrex128 | 0.43855 | 9.9 | 1997 | 40095 |
2095
+ | por-fas | ntrex128 | 0.42010 | 14.4 | 1997 | 50525 |
2096
+ | por-hin | ntrex128 | 0.43275 | 17.6 | 1997 | 55219 |
2097
+ | por-snd_Arab | ntrex128 | 6.336 | 0.1 | 1997 | 49866 |
2098
+ | por-urd | ntrex128 | 0.42484 | 15.2 | 1997 | 54259 |
2099
+ | spa-ben | ntrex128 | 0.44905 | 10.3 | 1997 | 40095 |
2100
+ | spa-fas | ntrex128 | 0.42207 | 14.1 | 1997 | 50525 |
2101
+ | spa-hin | ntrex128 | 0.43380 | 17.6 | 1997 | 55219 |
2102
+ | spa-snd_Arab | ntrex128 | 5.551 | 0.0 | 1997 | 49866 |
2103
+ | spa-urd | ntrex128 | 0.42434 | 15.0 | 1997 | 54259 |
2104
+ | eng-ben | tico19-test | 0.51563 | 17.9 | 2100 | 51695 |
2105
+ | eng-ckb | tico19-test | 0.46188 | 8.9 | 2100 | 50500 |
2106
+ | eng-fas | tico19-test | 0.53182 | 25.8 | 2100 | 59779 |
2107
+ | eng-hin | tico19-test | 0.63128 | 41.6 | 2100 | 62680 |
2108
+ | eng-mar | tico19-test | 0.45619 | 12.9 | 2100 | 50872 |
2109
+ | eng-nep | tico19-test | 0.53413 | 17.6 | 2100 | 48363 |
2110
+ | eng-prs | tico19-test | 0.44101 | 17.3 | 2100 | 62972 |
2111
+ | eng-pus | tico19-test | 0.47063 | 20.5 | 2100 | 66213 |
2112
+ | eng-urd | tico19-test | 0.51054 | 22.0 | 2100 | 65312 |
2113
+ | fra-fas | tico19-test | 0.43476 | 17.9 | 2100 | 59779 |
2114
+ | fra-hin | tico19-test | 0.48625 | 25.6 | 2100 | 62680 |
2115
+ | fra-nep | tico19-test | 0.41153 | 9.7 | 2100 | 48363 |
2116
+ | fra-urd | tico19-test | 0.40482 | 14.4 | 2100 | 65312 |
2117
+ | por-ben | tico19-test | 0.45814 | 12.5 | 2100 | 51695 |
2118
+ | por-ckb | tico19-test | 0.41684 | 5.6 | 2100 | 50500 |
2119
+ | por-fas | tico19-test | 0.49181 | 21.3 | 2100 | 59779 |
2120
+ | por-hin | tico19-test | 0.55759 | 31.1 | 2100 | 62680 |
2121
+ | por-mar | tico19-test | 0.40067 | 9.1 | 2100 | 50872 |
2122
+ | por-nep | tico19-test | 0.47378 | 12.1 | 2100 | 48363 |
2123
+ | por-pus | tico19-test | 0.42496 | 15.9 | 2100 | 66213 |
2124
+ | por-urd | tico19-test | 0.45560 | 16.6 | 2100 | 65312 |
2125
+ | spa-ben | tico19-test | 0.45751 | 12.7 | 2100 | 51695 |
2126
+ | spa-ckb | tico19-test | 0.41568 | 5.4 | 2100 | 50500 |
2127
+ | spa-fas | tico19-test | 0.48974 | 21.0 | 2100 | 59779 |
2128
+ | spa-hin | tico19-test | 0.55641 | 30.9 | 2100 | 62680 |
2129
+ | spa-mar | tico19-test | 0.40329 | 9.4 | 2100 | 50872 |
2130
+ | spa-nep | tico19-test | 0.47164 | 12.1 | 2100 | 48363 |
2131
+ | spa-prs | tico19-test | 0.41879 | 14.3 | 2100 | 62972 |
2132
+ | spa-pus | tico19-test | 0.41714 | 15.1 | 2100 | 66213 |
2133
+ | spa-urd | tico19-test | 0.44931 | 15.3 | 2100 | 65312 |
2134
+
2135
+ ## Citation Information
2136
+
2137
+ * Publications: [Democratizing neural machine translation with OPUS-MT](https://doi.org/10.1007/s10579-023-09704-w) and [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.)
2138
+
2139
+ ```bibtex
2140
+ @article{tiedemann2023democratizing,
2141
+ title={Democratizing neural machine translation with {OPUS-MT}},
2142
+ author={Tiedemann, J{\"o}rg and Aulamo, Mikko and Bakshandaeva, Daria and Boggia, Michele and Gr{\"o}nroos, Stig-Arne and Nieminen, Tommi and Raganato, Alessandro and Scherrer, Yves and Vazquez, Raul and Virpioja, Sami},
2143
+ journal={Language Resources and Evaluation},
2144
+ number={58},
2145
+ pages={713--755},
2146
+ year={2023},
2147
+ publisher={Springer Nature},
2148
+ issn={1574-0218},
2149
+ doi={10.1007/s10579-023-09704-w}
2150
+ }
2151
+
2152
+ @inproceedings{tiedemann-thottingal-2020-opus,
2153
+ title = "{OPUS}-{MT} {--} Building open translation services for the World",
2154
+ author = {Tiedemann, J{\"o}rg and Thottingal, Santhosh},
2155
+ booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation",
2156
+ month = nov,
2157
+ year = "2020",
2158
+ address = "Lisboa, Portugal",
2159
+ publisher = "European Association for Machine Translation",
2160
+ url = "https://aclanthology.org/2020.eamt-1.61",
2161
+ pages = "479--480",
2162
+ }
2163
+
2164
+ @inproceedings{tiedemann-2020-tatoeba,
2165
+ title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}",
2166
+ author = {Tiedemann, J{\"o}rg},
2167
+ booktitle = "Proceedings of the Fifth Conference on Machine Translation",
2168
+ month = nov,
2169
+ year = "2020",
2170
+ address = "Online",
2171
+ publisher = "Association for Computational Linguistics",
2172
+ url = "https://aclanthology.org/2020.wmt-1.139",
2173
+ pages = "1174--1182",
2174
+ }
2175
+ ```
2176
+
2177
+ ## Acknowledgements
2178
+
2179
+ The work is supported by the [HPLT project](https://hplt-project.org/), funded by the European Union’s Horizon Europe research and innovation programme under grant agreement No 101070350. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland, and the [EuroHPC supercomputer LUMI](https://www.lumi-supercomputer.eu/).
2180
+
2181
+ ## Model conversion info
2182
+
2183
+ * transformers version: 4.45.1
2184
+ * OPUS-MT git hash: 0882077
2185
+ * port time: Tue Oct 8 10:05:20 EEST 2024
2186
+ * port machine: LM0-400-22516.local
benchmark_results.txt ADDED
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benchmark_translations.zip ADDED
File without changes
config.json ADDED
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1
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