generated_from_trainer

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wav2vec2-large-xls-r-300m-j-roman-colab

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Training results

Training Loss Epoch Step Validation Loss Wer
4.3479 1.22 400 1.6349 0.3868
0.8621 2.45 800 1.0185 0.2346
0.5421 3.67 1200 0.7549 0.1868
0.3932 4.89 1600 0.7893 0.1811
0.332 6.12 2000 0.9318 0.1919
0.2902 7.34 2400 0.8263 0.1839
0.2542 8.56 2800 0.8491 0.1829
0.2355 9.79 3200 0.8820 0.1805
0.2206 11.01 3600 0.9183 0.1748
0.2041 12.23 4000 0.9131 0.1725
0.1878 13.46 4400 0.9075 0.1699
0.1733 14.68 4800 0.8456 0.1665
0.1746 15.9 5200 0.9353 0.1745
0.1671 17.13 5600 0.9318 0.1713
0.1641 18.35 6000 0.8804 0.1661
0.1578 19.57 6400 0.9849 0.1795
0.1534 20.8 6800 1.0036 0.1637
0.1484 22.02 7200 0.9618 0.1722
0.1431 23.24 7600 0.9947 0.1680
0.139 24.46 8000 0.9923 0.1729
0.134 25.69 8400 1.0015 0.1641
0.1298 26.91 8800 0.9930 0.1704
0.1253 28.13 9200 0.9977 0.1605
0.1178 29.36 9600 0.9756 0.1653
0.1178 30.58 10000 1.1122 0.1784
0.1165 31.8 10400 0.9883 0.1655
0.1073 33.03 10800 1.1286 0.1677
0.1121 34.25 11200 1.0406 0.1660
0.1081 35.47 11600 1.0976 0.1678
0.109 36.7 12000 1.0915 0.1722
0.1027 37.92 12400 1.1167 0.1712
0.0925 39.14 12800 1.1598 0.1693
0.0913 40.37 13200 1.0712 0.1640
0.0895 41.59 13600 1.1692 0.1745
0.0908 42.81 14000 1.1248 0.1641
0.0905 44.04 14400 1.0523 0.1678
0.0864 45.26 14800 1.0261 0.1626
0.0843 46.48 15200 1.0746 0.1676
0.0759 47.71 15600 1.1035 0.1596
0.0758 48.93 16000 1.0977 0.1622
0.0743 50.15 16400 1.1203 0.1677
0.0826 51.38 16800 1.0983 0.1651
0.0743 52.6 17200 1.1452 0.1622
0.0713 53.82 17600 1.0882 0.1623
0.0651 55.05 18000 1.0588 0.1608
0.0669 56.27 18400 1.1332 0.1600
0.0626 57.49 18800 1.0747 0.1562
0.0646 58.72 19200 1.0585 0.1599
0.0639 59.94 19600 1.0106 0.1543
0.0603 61.16 20000 1.0875 0.1585
0.0551 62.39 20400 1.1273 0.1537
0.0553 63.61 20800 1.1376 0.1577
0.052 64.83 21200 1.1429 0.1553
0.0506 66.06 21600 1.0872 0.1577
0.0495 67.28 22000 1.0954 0.1488
0.0483 68.5 22400 1.1397 0.1524
0.0421 69.72 22800 1.2144 0.1581
0.0457 70.95 23200 1.1581 0.1532
0.0405 72.17 23600 1.2150 0.1566
0.0409 73.39 24000 1.1176 0.1508
0.0386 74.62 24400 1.2018 0.1526
0.0374 75.84 24800 1.2548 0.1494
0.0376 77.06 25200 1.2161 0.1486
0.033 78.29 25600 1.1607 0.1558
0.0339 79.51 26000 1.1557 0.1498
0.0355 80.73 26400 1.1234 0.1490
0.031 81.96 26800 1.1778 0.1473
0.0301 83.18 27200 1.1594 0.1441
0.0292 84.4 27600 1.2036 0.1482
0.0256 85.63 28000 1.2334 0.1463
0.0259 86.85 28400 1.2072 0.1469
0.0271 88.07 28800 1.1843 0.1456
0.0241 89.3 29200 1.1712 0.1445
0.0223 90.52 29600 1.2059 0.1433
0.0213 91.74 30000 1.2231 0.1452
0.0212 92.97 30400 1.1980 0.1438
0.0223 94.19 30800 1.2148 0.1459
0.0185 95.41 31200 1.2190 0.1437
0.0202 96.64 31600 1.2051 0.1437
0.0188 97.86 32000 1.2154 0.1438
0.0183 99.08 32400 1.2233 0.1437

Framework versions