whisper-base-google-fleurs-pt-br
This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4987
- Wer: 22.2974
- Wer Normalized: 18.5291
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: 2.05e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: reduce_lr_on_plateau
- lr_scheduler_warmup_steps: 120
- training_steps: 2400
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Normalized |
|---|---|---|---|---|---|
| 0.3716 | 1.01 | 400 | 0.3988 | 21.8039 | 17.8916 |
| 0.2003 | 2.02 | 800 | 0.4440 | 22.3350 | 18.6242 |
| 0.0571 | 3.02 | 1200 | 0.4960 | 22.5982 | 19.2284 |
| 0.03 | 4.03 | 1600 | 0.4987 | 22.2974 | 18.5291 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1
- Datasets 2.16.1
- Tokenizers 0.15.0
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Base model
openai/whisper-base