Wav2Vec2-XLS-TR
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the Common Voice 17 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5348
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 21.9538 | 0.3446 | 500 | 12.1320 |
| 7.2139 | 0.6892 | 1000 | 5.5372 |
| 4.9229 | 1.0338 | 1500 | 4.4389 |
| 4.0539 | 1.3784 | 2000 | 3.7210 |
| 3.5019 | 1.7229 | 2500 | 3.3480 |
| 3.2272 | 2.0675 | 3000 | 3.1302 |
| 2.9163 | 2.4121 | 3500 | 2.5875 |
| 1.902 | 2.7567 | 4000 | 1.5471 |
| 1.2034 | 3.1013 | 4500 | 1.1319 |
| 0.9389 | 3.4459 | 5000 | 1.0412 |
| 0.7599 | 3.7905 | 5500 | 0.8486 |
| 0.6418 | 4.1351 | 6000 | 0.7179 |
| 0.569 | 4.4797 | 6500 | 0.7109 |
| 0.5248 | 4.8243 | 7000 | 0.6470 |
| 0.4752 | 5.1688 | 7500 | 0.6298 |
| 0.4461 | 5.5134 | 8000 | 0.6198 |
| 0.4187 | 5.8580 | 8500 | 0.6224 |
| 0.3935 | 6.2026 | 9000 | 0.6116 |
| 0.3756 | 6.5472 | 9500 | 0.5536 |
| 0.3597 | 6.8918 | 10000 | 0.5263 |
| 0.3483 | 7.2364 | 10500 | 0.5179 |
| 0.3283 | 7.5810 | 11000 | 0.5054 |
| 0.3204 | 7.9256 | 11500 | 0.5200 |
| 0.3031 | 8.2702 | 12000 | 0.4984 |
| 0.2986 | 8.6147 | 12500 | 0.4846 |
| 0.2936 | 8.9593 | 13000 | 0.4984 |
| 0.2789 | 9.3039 | 13500 | 0.4888 |
| 0.2724 | 9.6485 | 14000 | 0.4654 |
| 0.2718 | 9.9931 | 14500 | 0.4553 |
| 0.2533 | 10.3377 | 15000 | 0.4506 |
| 0.2498 | 10.6823 | 15500 | 0.4983 |
| 0.2501 | 11.0269 | 16000 | 0.4835 |
| 0.2384 | 11.3715 | 16500 | 0.4749 |
| 0.2371 | 11.7161 | 17000 | 0.4877 |
| 0.2319 | 12.0606 | 17500 | 0.4806 |
| 0.2235 | 12.4052 | 18000 | 0.4874 |
| 0.2218 | 12.7498 | 18500 | 0.4565 |
| 0.2193 | 13.0944 | 19000 | 0.4733 |
| 0.2154 | 13.4390 | 19500 | 0.4747 |
| 0.2157 | 13.7836 | 20000 | 0.4694 |
| 0.2067 | 14.1282 | 20500 | 0.4848 |
| 0.2044 | 14.4728 | 21000 | 0.5092 |
| 0.2023 | 14.8174 | 21500 | 0.4752 |
| 0.1975 | 15.1620 | 22000 | 0.4852 |
| 0.1903 | 15.5065 | 22500 | 0.4891 |
| 0.1922 | 15.8511 | 23000 | 0.4825 |
| 0.1901 | 16.1957 | 23500 | 0.4836 |
| 0.1862 | 16.5403 | 24000 | 0.4838 |
| 0.1842 | 16.8849 | 24500 | 0.4897 |
| 0.1837 | 17.2295 | 25000 | 0.4920 |
| 0.1782 | 17.5741 | 25500 | 0.4937 |
| 0.1775 | 17.9187 | 26000 | 0.4868 |
| 0.1738 | 18.2633 | 26500 | 0.5107 |
| 0.1739 | 18.6079 | 27000 | 0.4943 |
| 0.1722 | 18.9524 | 27500 | 0.4740 |
| 0.1691 | 19.2970 | 28000 | 0.4965 |
| 0.1684 | 19.6416 | 28500 | 0.4834 |
| 0.1646 | 19.9862 | 29000 | 0.5187 |
| 0.1637 | 20.3308 | 29500 | 0.4979 |
| 0.1625 | 20.6754 | 30000 | 0.4945 |
| 0.1608 | 21.0200 | 30500 | 0.5149 |
| 0.1567 | 21.3646 | 31000 | 0.5030 |
| 0.1571 | 21.7092 | 31500 | 0.5013 |
| 0.1589 | 22.0538 | 32000 | 0.5269 |
| 0.1524 | 22.3983 | 32500 | 0.5191 |
| 0.1491 | 22.7429 | 33000 | 0.5200 |
| 0.1521 | 23.0875 | 33500 | 0.5206 |
| 0.149 | 23.4321 | 34000 | 0.5214 |
| 0.1505 | 23.7767 | 34500 | 0.5255 |
| 0.1516 | 24.1213 | 35000 | 0.5168 |
| 0.1479 | 24.4659 | 35500 | 0.5431 |
| 0.1476 | 24.8105 | 36000 | 0.5352 |
| 0.1433 | 25.1551 | 36500 | 0.5281 |
| 0.1464 | 25.4997 | 37000 | 0.5207 |
| 0.1444 | 25.8442 | 37500 | 0.5254 |
| 0.1466 | 26.1888 | 38000 | 0.5163 |
| 0.1424 | 26.5334 | 38500 | 0.5200 |
| 0.1375 | 26.8780 | 39000 | 0.5188 |
| 0.1428 | 27.2226 | 39500 | 0.5315 |
| 0.1376 | 27.5672 | 40000 | 0.5323 |
| 0.139 | 27.9118 | 40500 | 0.5370 |
| 0.1437 | 28.2564 | 41000 | 0.5426 |
| 0.138 | 28.6010 | 41500 | 0.5263 |
| 0.1382 | 28.9456 | 42000 | 0.5286 |
| 0.139 | 29.2901 | 42500 | 0.5302 |
| 0.139 | 29.6347 | 43000 | 0.5334 |
| 0.1356 | 29.9793 | 43500 | 0.5348 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1