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wav2vec2-l-xlsr-es-col-pro-noise
This model is a fine-tuned version of jonatasgrosman/wav2vec2-large-xlsr-53-spanish on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0677
- Wer: 0.0380
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: 0.0003
- 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_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.94 | 1.21 | 400 | 0.0800 | 0.0814 |
| 0.4711 | 2.42 | 800 | 0.0730 | 0.0692 |
| 0.3451 | 3.62 | 1200 | 0.0729 | 0.0669 |
| 0.2958 | 4.83 | 1600 | 0.0796 | 0.0667 |
| 0.2544 | 6.04 | 2000 | 0.0808 | 0.0584 |
| 0.227 | 7.25 | 2400 | 0.0791 | 0.0643 |
| 0.2061 | 8.46 | 2800 | 0.0718 | 0.0582 |
| 0.1901 | 9.67 | 3200 | 0.0709 | 0.0587 |
| 0.179 | 10.87 | 3600 | 0.0698 | 0.0558 |
| 0.1693 | 12.08 | 4000 | 0.0709 | 0.0530 |
| 0.1621 | 13.29 | 4400 | 0.0640 | 0.0487 |
| 0.1443 | 14.5 | 4800 | 0.0793 | 0.0587 |
| 0.1408 | 15.71 | 5200 | 0.0741 | 0.0528 |
| 0.1377 | 16.92 | 5600 | 0.0702 | 0.0462 |
| 0.1292 | 18.13 | 6000 | 0.0822 | 0.0539 |
| 0.1197 | 19.33 | 6400 | 0.0625 | 0.0436 |
| 0.1137 | 20.54 | 6800 | 0.0650 | 0.0419 |
| 0.1017 | 21.75 | 7200 | 0.0630 | 0.0392 |
| 0.0976 | 22.96 | 7600 | 0.0630 | 0.0387 |
| 0.0942 | 24.17 | 8000 | 0.0631 | 0.0380 |
| 0.0924 | 25.38 | 8400 | 0.0645 | 0.0374 |
| 0.0862 | 26.59 | 8800 | 0.0677 | 0.0402 |
| 0.0831 | 27.79 | 9200 | 0.0680 | 0.0393 |
| 0.077 | 29.0 | 9600 | 0.0677 | 0.0380 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.1+cu102
- Datasets 1.13.3
- Tokenizers 0.10.3
