Common Voice 16 - Guarani
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5109
- Cer: 9.2551
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 2.4482 | 1.01 | 100 | 0.8934 | 14.3691 |
| 0.3998 | 2.02 | 200 | 0.5143 | 10.8002 |
| 0.1611 | 3.03 | 300 | 0.4834 | 11.6409 |
| 0.0765 | 4.04 | 400 | 0.5059 | 9.7844 |
| 0.0482 | 5.05 | 500 | 0.5109 | 9.2551 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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