Common Voice 16
This model is a fine-tuned version of glob-asr/wav2vec2-large-xls-r-300m-guarani-small on the Common Voice 16 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4335
- Wer: 49.7002
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 3000
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.258 | 0.4955 | 500 | 0.3710 | 53.1646 |
| 0.921 | 0.9911 | 1000 | 0.3282 | 49.2338 |
| 0.7458 | 1.4866 | 1500 | 0.2940 | 46.7022 |
| 0.6763 | 1.9822 | 2000 | 0.2628 | 44.9700 |
| 0.568 | 2.4777 | 2500 | 0.2616 | 43.3711 |
| 0.5414 | 2.9732 | 3000 | 0.2504 | 39.8401 |
| 0.484 | 3.4688 | 3500 | 0.2462 | 41.0393 |
| 0.5281 | 3.9643 | 4000 | 0.3584 | 43.5043 |
| 0.5756 | 4.4599 | 4500 | 0.4220 | 44.3038 |
| 0.721 | 4.9554 | 5000 | 0.4335 | 49.7002 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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