Whisper Large v3 Fine-Tuned Finnish - CommonVoice13
This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3858
- Wer: 21.6363
It achieves the following results on the Test set:
- Eval_Wer: 21.636296705319342
- Eval_NormalizedWer: 18.727590328215502
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 800
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0049 | 0.84 | 50 | 0.4045 | 27.8851 |
| 0.0264 | 1.68 | 100 | 0.4482 | 29.3852 |
| 0.0189 | 2.53 | 150 | 0.4076 | 26.6980 |
| 0.0129 | 3.37 | 200 | 0.3772 | 24.5905 |
| 0.0087 | 4.21 | 250 | 0.3875 | 25.5108 |
| 0.0054 | 5.05 | 300 | 0.3754 | 24.9034 |
| 0.0035 | 5.89 | 350 | 0.3742 | 23.5505 |
| 0.0014 | 6.74 | 400 | 0.3823 | 23.4677 |
| 0.0014 | 7.58 | 450 | 0.3914 | 23.5781 |
| 0.0012 | 8.42 | 500 | 0.3771 | 22.3173 |
| 0.0007 | 9.26 | 550 | 0.3812 | 21.8756 |
| 0.0002 | 10.11 | 600 | 0.3812 | 21.7191 |
| 0.0002 | 10.95 | 650 | 0.3825 | 21.6547 |
| 0.0001 | 11.79 | 700 | 0.3844 | 21.6363 |
| 0.0001 | 12.63 | 750 | 0.3854 | 21.5995 |
| 0.0001 | 13.47 | 800 | 0.3858 | 21.6363 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0
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