--- license: apache-2.0 tags: - generated_from_trainer metrics: - wer model-index: - name: wav2vec2-large-xlsr-coraa-exp-10 results: [] --- # wav2vec2-large-xlsr-coraa-exp-10 This model is a fine-tuned version of [Edresson/wav2vec2-large-xlsr-coraa-portuguese](https://huggingface.co/Edresson/wav2vec2-large-xlsr-coraa-portuguese) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5470 - Wer: 0.3417 - Cer: 0.1785 ## 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: - learning_rate: 3e-05 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 150 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| | 37.9224 | 1.0 | 14 | 24.6578 | 1.0 | 0.9618 | | 37.9224 | 2.0 | 28 | 7.1453 | 1.0 | 0.9619 | | 37.9224 | 3.0 | 42 | 4.4391 | 1.0 | 0.9619 | | 37.9224 | 4.0 | 56 | 3.9092 | 1.0 | 0.9619 | | 37.9224 | 5.0 | 70 | 3.6835 | 1.0 | 0.9619 | | 37.9224 | 6.0 | 84 | 3.5223 | 1.0 | 0.9619 | | 37.9224 | 7.0 | 98 | 3.3716 | 1.0 | 0.9619 | | 9.0651 | 8.0 | 112 | 3.2723 | 1.0 | 0.9619 | | 9.0651 | 9.0 | 126 | 3.1860 | 1.0 | 0.9619 | | 9.0651 | 10.0 | 140 | 3.1461 | 1.0 | 0.9619 | | 9.0651 | 11.0 | 154 | 3.1368 | 1.0 | 0.9619 | | 9.0651 | 12.0 | 168 | 3.0961 | 1.0 | 0.9619 | | 9.0651 | 13.0 | 182 | 3.0767 | 1.0 | 0.9619 | | 9.0651 | 14.0 | 196 | 3.0509 | 1.0 | 0.9619 | | 3.0601 | 15.0 | 210 | 3.0871 | 1.0 | 0.9619 | | 3.0601 | 16.0 | 224 | 3.0415 | 1.0 | 0.9619 | | 3.0601 | 17.0 | 238 | 3.0330 | 1.0 | 0.9619 | | 3.0601 | 18.0 | 252 | 3.0192 | 1.0 | 0.9619 | | 3.0601 | 19.0 | 266 | 3.0266 | 1.0 | 0.9619 | | 3.0601 | 20.0 | 280 | 3.0243 | 1.0 | 0.9619 | | 3.0601 | 21.0 | 294 | 3.0106 | 1.0 | 0.9619 | | 2.9552 | 22.0 | 308 | 3.0053 | 1.0 | 0.9619 | | 2.9552 | 23.0 | 322 | 2.9986 | 1.0 | 0.9619 | | 2.9552 | 24.0 | 336 | 3.0030 | 1.0 | 0.9619 | | 2.9552 | 25.0 | 350 | 2.9950 | 1.0 | 0.9619 | | 2.9552 | 26.0 | 364 | 3.0058 | 1.0 | 0.9619 | | 2.9552 | 27.0 | 378 | 2.9943 | 1.0 | 0.9619 | | 2.9552 | 28.0 | 392 | 2.9845 | 1.0 | 0.9619 | | 2.9213 | 29.0 | 406 | 2.9713 | 1.0 | 0.9619 | | 2.9213 | 30.0 | 420 | 2.9485 | 1.0 | 0.9619 | | 2.9213 | 31.0 | 434 | 2.9415 | 1.0 | 0.9619 | | 2.9213 | 32.0 | 448 | 2.8913 | 1.0 | 0.9619 | | 2.9213 | 33.0 | 462 | 2.8057 | 1.0 | 0.9612 | | 2.9213 | 34.0 | 476 | 2.6984 | 1.0 | 0.9599 | | 2.9213 | 35.0 | 490 | 2.5785 | 1.0 | 0.9067 | | 2.7804 | 36.0 | 504 | 2.3545 | 1.0 | 0.7929 | | 2.7804 | 37.0 | 518 | 2.0433 | 1.0 | 0.5933 | | 2.7804 | 38.0 | 532 | 1.7438 | 1.0 | 0.4701 | | 2.7804 | 39.0 | 546 | 1.4659 | 1.0 | 0.4139 | | 2.7804 | 40.0 | 560 | 1.2873 | 0.9929 | 0.3840 | | 2.7804 | 41.0 | 574 | 1.1588 | 0.9315 | 0.3387 | | 2.7804 | 42.0 | 588 | 1.0163 | 0.7395 | 0.2706 | | 1.6517 | 43.0 | 602 | 0.9399 | 0.5331 | 0.2258 | | 1.6517 | 44.0 | 616 | 0.9131 | 0.4929 | 0.2167 | | 1.6517 | 45.0 | 630 | 0.8352 | 0.4770 | 0.2114 | | 1.6517 | 46.0 | 644 | 0.8115 | 0.4555 | 0.2084 | | 1.6517 | 47.0 | 658 | 0.7850 | 0.4403 | 0.2038 | | 1.6517 | 48.0 | 672 | 0.7574 | 0.4356 | 0.2019 | | 1.6517 | 49.0 | 686 | 0.7238 | 0.4248 | 0.1989 | | 0.7966 | 50.0 | 700 | 0.7132 | 0.4130 | 0.1960 | | 0.7966 | 51.0 | 714 | 0.7054 | 0.4128 | 0.1963 | | 0.7966 | 52.0 | 728 | 0.7119 | 0.4134 | 0.1990 | | 0.7966 | 53.0 | 742 | 0.6793 | 0.3990 | 0.1945 | | 0.7966 | 54.0 | 756 | 0.6718 | 0.3944 | 0.1932 | | 0.7966 | 55.0 | 770 | 0.6718 | 0.4013 | 0.1949 | | 0.7966 | 56.0 | 784 | 0.6831 | 0.3976 | 0.1965 | | 0.7966 | 57.0 | 798 | 0.6400 | 0.3870 | 0.1916 | | 0.5799 | 58.0 | 812 | 0.6423 | 0.3844 | 0.1906 | | 0.5799 | 59.0 | 826 | 0.6394 | 0.3834 | 0.1908 | | 0.5799 | 60.0 | 840 | 0.6574 | 0.3785 | 0.1924 | | 0.5799 | 61.0 | 854 | 0.6321 | 0.3816 | 0.1918 | | 0.5799 | 62.0 | 868 | 0.6306 | 0.3801 | 0.1913 | | 0.5799 | 63.0 | 882 | 0.6433 | 0.3799 | 0.1916 | | 0.5799 | 64.0 | 896 | 0.6342 | 0.3811 | 0.1896 | | 0.445 | 65.0 | 910 | 0.6212 | 0.3811 | 0.1904 | | 0.445 | 66.0 | 924 | 0.6164 | 0.3789 | 0.1895 | | 0.445 | 67.0 | 938 | 0.6006 | 0.3732 | 0.1872 | | 0.445 | 68.0 | 952 | 0.6054 | 0.3746 | 0.1891 | | 0.445 | 69.0 | 966 | 0.6245 | 0.3722 | 0.1894 | | 0.445 | 70.0 | 980 | 0.6090 | 0.3688 | 0.1878 | | 0.445 | 71.0 | 994 | 0.6073 | 0.3669 | 0.1876 | | 0.3746 | 72.0 | 1008 | 0.5989 | 0.3708 | 0.1889 | | 0.3746 | 73.0 | 1022 | 0.5968 | 0.3681 | 0.1874 | | 0.3746 | 74.0 | 1036 | 0.5946 | 0.3659 | 0.1870 | | 0.3746 | 75.0 | 1050 | 0.5874 | 0.3623 | 0.1864 | | 0.3746 | 76.0 | 1064 | 0.5928 | 0.3639 | 0.1870 | | 0.3746 | 77.0 | 1078 | 0.5889 | 0.3681 | 0.1882 | | 0.3746 | 78.0 | 1092 | 0.5723 | 0.3683 | 0.1864 | | 0.3543 | 79.0 | 1106 | 0.5928 | 0.3657 | 0.1863 | | 0.3543 | 80.0 | 1120 | 0.5832 | 0.3649 | 0.1855 | | 0.3543 | 81.0 | 1134 | 0.5785 | 0.3645 | 0.1849 | | 0.3543 | 82.0 | 1148 | 0.5877 | 0.3580 | 0.1842 | | 0.3543 | 83.0 | 1162 | 0.5870 | 0.3627 | 0.1853 | | 0.3543 | 84.0 | 1176 | 0.5738 | 0.3618 | 0.1846 | | 0.3543 | 85.0 | 1190 | 0.5641 | 0.3576 | 0.1816 | | 0.3207 | 86.0 | 1204 | 0.5728 | 0.3566 | 0.1821 | | 0.3207 | 87.0 | 1218 | 0.5706 | 0.3560 | 0.1817 | | 0.3207 | 88.0 | 1232 | 0.5607 | 0.3570 | 0.1813 | | 0.3207 | 89.0 | 1246 | 0.5644 | 0.3557 | 0.1817 | | 0.3207 | 90.0 | 1260 | 0.5660 | 0.3582 | 0.1824 | | 0.3207 | 91.0 | 1274 | 0.5688 | 0.3566 | 0.1829 | | 0.3207 | 92.0 | 1288 | 0.5635 | 0.3541 | 0.1807 | | 0.2984 | 93.0 | 1302 | 0.5663 | 0.3503 | 0.1814 | | 0.2984 | 94.0 | 1316 | 0.5515 | 0.3543 | 0.1807 | | 0.2984 | 95.0 | 1330 | 0.5563 | 0.3517 | 0.1803 | | 0.2984 | 96.0 | 1344 | 0.5618 | 0.3509 | 0.1809 | | 0.2984 | 97.0 | 1358 | 0.5554 | 0.3517 | 0.1807 | | 0.2984 | 98.0 | 1372 | 0.5606 | 0.3529 | 0.1809 | | 0.2984 | 99.0 | 1386 | 0.5597 | 0.3511 | 0.1813 | | 0.2622 | 100.0 | 1400 | 0.5628 | 0.3505 | 0.1812 | | 0.2622 | 101.0 | 1414 | 0.5564 | 0.3495 | 0.1799 | | 0.2622 | 102.0 | 1428 | 0.5626 | 0.3484 | 0.1811 | | 0.2622 | 103.0 | 1442 | 0.5556 | 0.3470 | 0.1800 | | 0.2622 | 104.0 | 1456 | 0.5603 | 0.3464 | 0.1799 | | 0.2622 | 105.0 | 1470 | 0.5571 | 0.3454 | 0.1799 | | 0.2622 | 106.0 | 1484 | 0.5618 | 0.3466 | 0.1799 | | 0.2622 | 107.0 | 1498 | 0.5519 | 0.3440 | 0.1787 | | 0.2519 | 108.0 | 1512 | 0.5541 | 0.3440 | 0.1790 | | 0.2519 | 109.0 | 1526 | 0.5574 | 0.3464 | 0.1794 | | 0.2519 | 110.0 | 1540 | 0.5590 | 0.3454 | 0.1801 | | 0.2519 | 111.0 | 1554 | 0.5530 | 0.3448 | 0.1796 | | 0.2519 | 112.0 | 1568 | 0.5501 | 0.3438 | 0.1792 | | 0.2519 | 113.0 | 1582 | 0.5595 | 0.3448 | 0.1799 | | 0.2519 | 114.0 | 1596 | 0.5536 | 0.3446 | 0.1801 | | 0.245 | 115.0 | 1610 | 0.5480 | 0.3432 | 0.1789 | | 0.245 | 116.0 | 1624 | 0.5623 | 0.3486 | 0.1798 | | 0.245 | 117.0 | 1638 | 0.5496 | 0.3427 | 0.1790 | | 0.245 | 118.0 | 1652 | 0.5552 | 0.3421 | 0.1789 | | 0.245 | 119.0 | 1666 | 0.5558 | 0.3438 | 0.1787 | | 0.245 | 120.0 | 1680 | 0.5524 | 0.3425 | 0.1783 | | 0.245 | 121.0 | 1694 | 0.5582 | 0.3421 | 0.1786 | | 0.2322 | 122.0 | 1708 | 0.5534 | 0.3425 | 0.1786 | | 0.2322 | 123.0 | 1722 | 0.5596 | 0.3464 | 0.1801 | | 0.2322 | 124.0 | 1736 | 0.5486 | 0.3432 | 0.1790 | | 0.2322 | 125.0 | 1750 | 0.5581 | 0.3425 | 0.1792 | | 0.2322 | 126.0 | 1764 | 0.5470 | 0.3417 | 0.1785 | | 0.2322 | 127.0 | 1778 | 0.5544 | 0.3413 | 0.1781 | | 0.2322 | 128.0 | 1792 | 0.5501 | 0.3436 | 0.1781 | | 0.2324 | 129.0 | 1806 | 0.5518 | 0.3440 | 0.1782 | | 0.2324 | 130.0 | 1820 | 0.5511 | 0.3389 | 0.1775 | | 0.2324 | 131.0 | 1834 | 0.5584 | 0.3417 | 0.1782 | | 0.2324 | 132.0 | 1848 | 0.5493 | 0.3373 | 0.1775 | | 0.2324 | 133.0 | 1862 | 0.5506 | 0.3395 | 0.1777 | | 0.2324 | 134.0 | 1876 | 0.5543 | 0.3409 | 0.1782 | | 0.2324 | 135.0 | 1890 | 0.5589 | 0.3399 | 0.1781 | | 0.2077 | 136.0 | 1904 | 0.5556 | 0.3391 | 0.1778 | | 0.2077 | 137.0 | 1918 | 0.5555 | 0.3407 | 0.1778 | | 0.2077 | 138.0 | 1932 | 0.5501 | 0.3391 | 0.1774 | | 0.2077 | 139.0 | 1946 | 0.5544 | 0.3375 | 0.1772 | | 0.2077 | 140.0 | 1960 | 0.5554 | 0.3387 | 0.1773 | | 0.2077 | 141.0 | 1974 | 0.5504 | 0.3381 | 0.1772 | | 0.2077 | 142.0 | 1988 | 0.5484 | 0.3383 | 0.1770 | | 0.2089 | 143.0 | 2002 | 0.5519 | 0.3385 | 0.1772 | | 0.2089 | 144.0 | 2016 | 0.5532 | 0.3391 | 0.1772 | | 0.2089 | 145.0 | 2030 | 0.5530 | 0.3397 | 0.1775 | | 0.2089 | 146.0 | 2044 | 0.5551 | 0.3397 | 0.1775 | ### Framework versions - Transformers 4.28.0 - Pytorch 2.4.1+cu121 - Datasets 3.2.0 - Tokenizers 0.13.3