Whisper Small for Common Accent
This model is a fine-tuned version of openai/whisper-small on the Common Accent dataset. It achieves the following results on the evaluation set:
- Loss: 0.4234
- Wer Ortho: 17.9229
- Wer: 13.0605
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: 2500
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.1012 | 1.14 | 500 | 0.3215 | 16.3784 | 11.5941 |
| 0.0345 | 2.28 | 1000 | 0.3483 | 16.6496 | 11.8450 |
| 0.018 | 3.42 | 1500 | 0.3829 | 17.1622 | 12.4707 |
| 0.0075 | 4.57 | 2000 | 0.4069 | 17.8667 | 13.0116 |
| 0.0059 | 5.71 | 2500 | 0.4234 | 17.9229 | 13.0605 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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Model tree for Wishwa98/ASRForCommonVoice
Base model
openai/whisper-small