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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-coraa-exp-17
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xlsr-coraa-exp-17
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: 0.5486
- Wer: 0.3511
- Cer: 0.1797
- Per: 0.3387
## 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: 4e-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
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 150
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Per |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 38.4208 | 1.0 | 14 | 41.8095 | 1.0057 | 1.2146 | 1.0057 |
| 38.4208 | 2.0 | 28 | 12.2873 | 1.0 | 0.9619 | 1.0 |
| 38.4208 | 3.0 | 42 | 4.8093 | 1.0 | 0.9619 | 1.0 |
| 38.4208 | 4.0 | 56 | 3.9738 | 1.0 | 0.9619 | 1.0 |
| 38.4208 | 5.0 | 70 | 3.6684 | 1.0 | 0.9619 | 1.0 |
| 38.4208 | 6.0 | 84 | 3.5007 | 1.0 | 0.9619 | 1.0 |
| 38.4208 | 7.0 | 98 | 3.3854 | 1.0 | 0.9619 | 1.0 |
| 11.8009 | 8.0 | 112 | 3.4506 | 1.0 | 0.9619 | 1.0 |
| 11.8009 | 9.0 | 126 | 3.1789 | 1.0 | 0.9619 | 1.0 |
| 11.8009 | 10.0 | 140 | 3.1274 | 1.0 | 0.9619 | 1.0 |
| 11.8009 | 11.0 | 154 | 3.1624 | 1.0 | 0.9619 | 1.0 |
| 11.8009 | 12.0 | 168 | 3.1066 | 1.0 | 0.9619 | 1.0 |
| 11.8009 | 13.0 | 182 | 3.0580 | 1.0 | 0.9619 | 1.0 |
| 11.8009 | 14.0 | 196 | 3.0477 | 1.0 | 0.9619 | 1.0 |
| 3.0395 | 15.0 | 210 | 3.0519 | 1.0 | 0.9619 | 1.0 |
| 3.0395 | 16.0 | 224 | 3.0364 | 1.0 | 0.9619 | 1.0 |
| 3.0395 | 17.0 | 238 | 3.0152 | 1.0 | 0.9619 | 1.0 |
| 3.0395 | 18.0 | 252 | 3.0167 | 1.0 | 0.9619 | 1.0 |
| 3.0395 | 19.0 | 266 | 3.0130 | 1.0 | 0.9619 | 1.0 |
| 3.0395 | 20.0 | 280 | 3.0103 | 1.0 | 0.9619 | 1.0 |
| 3.0395 | 21.0 | 294 | 2.9994 | 1.0 | 0.9619 | 1.0 |
| 2.9424 | 22.0 | 308 | 2.9999 | 1.0 | 0.9619 | 1.0 |
| 2.9424 | 23.0 | 322 | 3.0009 | 1.0 | 0.9619 | 1.0 |
| 2.9424 | 24.0 | 336 | 3.0024 | 1.0 | 0.9619 | 1.0 |
| 2.9424 | 25.0 | 350 | 3.0001 | 1.0 | 0.9619 | 1.0 |
| 2.9424 | 26.0 | 364 | 2.9891 | 1.0 | 0.9619 | 1.0 |
| 2.9424 | 27.0 | 378 | 2.9881 | 1.0 | 0.9619 | 1.0 |
| 2.9424 | 28.0 | 392 | 2.9703 | 1.0 | 0.9619 | 1.0 |
| 2.9154 | 29.0 | 406 | 2.9531 | 1.0 | 0.9619 | 1.0 |
| 2.9154 | 30.0 | 420 | 2.9208 | 1.0 | 0.9619 | 1.0 |
| 2.9154 | 31.0 | 434 | 2.8981 | 1.0 | 0.9619 | 1.0 |
| 2.9154 | 32.0 | 448 | 2.8321 | 1.0 | 0.9619 | 1.0 |
| 2.9154 | 33.0 | 462 | 2.7583 | 1.0 | 0.9619 | 1.0 |
| 2.9154 | 34.0 | 476 | 2.6405 | 1.0 | 0.9616 | 1.0 |
| 2.9154 | 35.0 | 490 | 2.5072 | 1.0 | 0.8832 | 1.0 |
| 2.7552 | 36.0 | 504 | 2.1547 | 1.0 | 0.6144 | 1.0 |
| 2.7552 | 37.0 | 518 | 1.7565 | 1.0 | 0.4996 | 1.0 |
| 2.7552 | 38.0 | 532 | 1.4602 | 1.0 | 0.4065 | 1.0 |
| 2.7552 | 39.0 | 546 | 1.2269 | 0.9896 | 0.3658 | 0.9892 |
| 2.7552 | 40.0 | 560 | 1.0906 | 0.8881 | 0.3205 | 0.8834 |
| 2.7552 | 41.0 | 574 | 0.9941 | 0.6772 | 0.2631 | 0.6603 |
| 2.7552 | 42.0 | 588 | 0.9133 | 0.5423 | 0.2322 | 0.5154 |
| 1.4599 | 43.0 | 602 | 0.8487 | 0.5142 | 0.2241 | 0.4882 |
| 1.4599 | 44.0 | 616 | 0.8211 | 0.4898 | 0.2207 | 0.4626 |
| 1.4599 | 45.0 | 630 | 0.7672 | 0.4803 | 0.2140 | 0.4518 |
| 1.4599 | 46.0 | 644 | 0.7432 | 0.4707 | 0.2092 | 0.4445 |
| 1.4599 | 47.0 | 658 | 0.7390 | 0.4492 | 0.2059 | 0.4262 |
| 1.4599 | 48.0 | 672 | 0.6994 | 0.4348 | 0.2011 | 0.4106 |
| 1.4599 | 49.0 | 686 | 0.6999 | 0.4230 | 0.1991 | 0.3998 |
| 0.7585 | 50.0 | 700 | 0.6738 | 0.4122 | 0.1959 | 0.3883 |
| 0.7585 | 51.0 | 714 | 0.6697 | 0.4094 | 0.1963 | 0.3858 |
| 0.7585 | 52.0 | 728 | 0.6707 | 0.4163 | 0.1996 | 0.3954 |
| 0.7585 | 53.0 | 742 | 0.6397 | 0.4031 | 0.1942 | 0.3832 |
| 0.7585 | 54.0 | 756 | 0.6293 | 0.4039 | 0.1939 | 0.3836 |
| 0.7585 | 55.0 | 770 | 0.6479 | 0.4027 | 0.1946 | 0.3852 |
| 0.7585 | 56.0 | 784 | 0.6307 | 0.3982 | 0.1934 | 0.3822 |
| 0.7585 | 57.0 | 798 | 0.6166 | 0.3844 | 0.1908 | 0.3673 |
| 0.5473 | 58.0 | 812 | 0.6099 | 0.3860 | 0.1906 | 0.3708 |
| 0.5473 | 59.0 | 826 | 0.6007 | 0.3868 | 0.1904 | 0.3730 |
| 0.5473 | 60.0 | 840 | 0.6191 | 0.3885 | 0.1928 | 0.3744 |
| 0.5473 | 61.0 | 854 | 0.6015 | 0.3885 | 0.1892 | 0.3732 |
| 0.5473 | 62.0 | 868 | 0.5965 | 0.3838 | 0.1902 | 0.3688 |
| 0.5473 | 63.0 | 882 | 0.5926 | 0.3826 | 0.1904 | 0.3667 |
| 0.5473 | 64.0 | 896 | 0.6188 | 0.3921 | 0.1921 | 0.3765 |
| 0.443 | 65.0 | 910 | 0.5835 | 0.3830 | 0.1892 | 0.3690 |
| 0.443 | 66.0 | 924 | 0.5914 | 0.3870 | 0.1903 | 0.3722 |
| 0.443 | 67.0 | 938 | 0.5828 | 0.3779 | 0.1876 | 0.3627 |
| 0.443 | 68.0 | 952 | 0.5745 | 0.3722 | 0.1857 | 0.3576 |
| 0.443 | 69.0 | 966 | 0.5786 | 0.3795 | 0.1882 | 0.3633 |
| 0.443 | 70.0 | 980 | 0.5869 | 0.3751 | 0.1884 | 0.3604 |
| 0.443 | 71.0 | 994 | 0.5923 | 0.3753 | 0.1888 | 0.3596 |
| 0.3564 | 72.0 | 1008 | 0.5707 | 0.3714 | 0.1859 | 0.3578 |
| 0.3564 | 73.0 | 1022 | 0.5733 | 0.3700 | 0.1857 | 0.3551 |
| 0.3564 | 74.0 | 1036 | 0.5731 | 0.3706 | 0.1854 | 0.3566 |
| 0.3564 | 75.0 | 1050 | 0.5644 | 0.3669 | 0.1847 | 0.3531 |
| 0.3564 | 76.0 | 1064 | 0.5661 | 0.3702 | 0.1852 | 0.3555 |
| 0.3564 | 77.0 | 1078 | 0.5705 | 0.3675 | 0.1847 | 0.3513 |
| 0.3564 | 78.0 | 1092 | 0.5631 | 0.3671 | 0.1835 | 0.3527 |
| 0.3456 | 79.0 | 1106 | 0.5675 | 0.3651 | 0.1831 | 0.3503 |
| 0.3456 | 80.0 | 1120 | 0.5697 | 0.3645 | 0.1846 | 0.3507 |
| 0.3456 | 81.0 | 1134 | 0.5644 | 0.3631 | 0.1841 | 0.3492 |
| 0.3456 | 82.0 | 1148 | 0.5657 | 0.3627 | 0.1843 | 0.3480 |
| 0.3456 | 83.0 | 1162 | 0.5831 | 0.3679 | 0.1876 | 0.3523 |
| 0.3456 | 84.0 | 1176 | 0.5824 | 0.3659 | 0.1862 | 0.3523 |
| 0.3456 | 85.0 | 1190 | 0.5567 | 0.3653 | 0.1833 | 0.3509 |
| 0.3073 | 86.0 | 1204 | 0.5755 | 0.3649 | 0.1852 | 0.3507 |
| 0.3073 | 87.0 | 1218 | 0.5590 | 0.3586 | 0.1829 | 0.3450 |
| 0.3073 | 88.0 | 1232 | 0.5663 | 0.3610 | 0.1835 | 0.3480 |
| 0.3073 | 89.0 | 1246 | 0.5734 | 0.3618 | 0.1851 | 0.3468 |
| 0.3073 | 90.0 | 1260 | 0.5657 | 0.3602 | 0.1830 | 0.3458 |
| 0.3073 | 91.0 | 1274 | 0.5651 | 0.3578 | 0.1828 | 0.3442 |
| 0.3073 | 92.0 | 1288 | 0.5608 | 0.3557 | 0.1820 | 0.3415 |
| 0.2836 | 93.0 | 1302 | 0.5505 | 0.3525 | 0.1807 | 0.3389 |
| 0.2836 | 94.0 | 1316 | 0.5495 | 0.3501 | 0.1798 | 0.3375 |
| 0.2836 | 95.0 | 1330 | 0.5693 | 0.3557 | 0.1816 | 0.3432 |
| 0.2836 | 96.0 | 1344 | 0.5638 | 0.3564 | 0.1822 | 0.3417 |
| 0.2836 | 97.0 | 1358 | 0.5486 | 0.3511 | 0.1797 | 0.3387 |
| 0.2836 | 98.0 | 1372 | 0.5618 | 0.3545 | 0.1810 | 0.3415 |
| 0.2836 | 99.0 | 1386 | 0.5637 | 0.3515 | 0.1800 | 0.3399 |
| 0.2502 | 100.0 | 1400 | 0.5658 | 0.3555 | 0.1810 | 0.3438 |
| 0.2502 | 101.0 | 1414 | 0.5527 | 0.3525 | 0.1795 | 0.3411 |
| 0.2502 | 102.0 | 1428 | 0.5701 | 0.3562 | 0.1807 | 0.3440 |
| 0.2502 | 103.0 | 1442 | 0.5543 | 0.3497 | 0.1794 | 0.3389 |
| 0.2502 | 104.0 | 1456 | 0.5660 | 0.3509 | 0.1803 | 0.3399 |
| 0.2502 | 105.0 | 1470 | 0.5543 | 0.3501 | 0.1795 | 0.3399 |
| 0.2502 | 106.0 | 1484 | 0.5742 | 0.3547 | 0.1817 | 0.3432 |
| 0.2502 | 107.0 | 1498 | 0.5527 | 0.3454 | 0.1789 | 0.3350 |
| 0.2368 | 108.0 | 1512 | 0.5577 | 0.3497 | 0.1789 | 0.3379 |
| 0.2368 | 109.0 | 1526 | 0.5539 | 0.3452 | 0.1789 | 0.3356 |
| 0.2368 | 110.0 | 1540 | 0.5700 | 0.3517 | 0.1802 | 0.3417 |
| 0.2368 | 111.0 | 1554 | 0.5627 | 0.3501 | 0.1794 | 0.3397 |
| 0.2368 | 112.0 | 1568 | 0.5622 | 0.3497 | 0.1797 | 0.3405 |
| 0.2368 | 113.0 | 1582 | 0.5708 | 0.3495 | 0.1801 | 0.3403 |
| 0.2368 | 114.0 | 1596 | 0.5733 | 0.3511 | 0.1805 | 0.3401 |
| 0.2288 | 115.0 | 1610 | 0.5615 | 0.3486 | 0.1795 | 0.3387 |
| 0.2288 | 116.0 | 1624 | 0.5741 | 0.3497 | 0.1809 | 0.3397 |
| 0.2288 | 117.0 | 1638 | 0.5610 | 0.3460 | 0.1796 | 0.3373 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.13.3
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