whisper-base-common-voice-16-pt
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: 0.3608
- Wer: 25.7805
- Wer Normalized: 19.8889
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: linear
- lr_scheduler_warmup_steps: 300
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Normalized |
|---|---|---|---|---|---|
| 0.4466 | 0.37 | 500 | 0.4422 | 30.9405 | 25.0028 |
| 0.3661 | 0.74 | 1000 | 0.4012 | 29.2259 | 22.9756 |
| 0.1767 | 1.11 | 1500 | 0.3841 | 27.5178 | 21.3383 |
| 0.1896 | 1.48 | 2000 | 0.3698 | 26.7728 | 20.5807 |
| 0.1637 | 1.85 | 2500 | 0.3616 | 25.5398 | 20.0286 |
| 0.1033 | 2.22 | 3000 | 0.3608 | 25.7805 | 19.8889 |
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