Whisper Base Hu v2
This model is a fine-tuned version of openai/whisper-base on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1599
- Wer Ortho: 12.6641
- Wer: 11.4171
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: 2.75e-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: 500
- training_steps: 15000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.199 | 0.33 | 1000 | 0.3838 | 36.7548 | 33.5517 |
| 0.3037 | 0.67 | 2000 | 0.3131 | 31.2748 | 28.3664 |
| 0.221 | 1.0 | 3000 | 0.2546 | 27.1739 | 24.1773 |
| 0.1562 | 1.34 | 4000 | 0.2319 | 23.9341 | 21.3341 |
| 0.1623 | 1.67 | 5000 | 0.2101 | 21.4079 | 18.9623 |
| 0.077 | 2.01 | 6000 | 0.1818 | 18.5415 | 16.2852 |
| 0.078 | 2.34 | 7000 | 0.1846 | 17.8339 | 15.7456 |
| 0.0818 | 2.68 | 8000 | 0.1712 | 16.4669 | 14.5983 |
| 0.0352 | 3.01 | 9000 | 0.1669 | 15.6178 | 14.0676 |
| 0.0413 | 3.35 | 10000 | 0.1673 | 14.9464 | 13.4539 |
| 0.0454 | 3.68 | 11000 | 0.1649 | 14.5459 | 12.7542 |
| 0.0225 | 4.02 | 12000 | 0.1589 | 13.5885 | 12.2087 |
| 0.0269 | 4.35 | 13000 | 0.1638 | 14.3864 | 12.8343 |
| 0.0299 | 4.69 | 14000 | 0.1621 | 13.0555 | 11.7610 |
| 0.0171 | 5.02 | 15000 | 0.1599 | 12.6641 | 11.4171 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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