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: 0.2383
- Wer: 24.6733
It achieves the following results on the test set:
- Wer: 17.043990428860667
- normalized_wer: 14.149122000551623
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: 4
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|
| 0.5438 | 0.42 | 50 | 0.2371 | 23.3204 |
| 0.2701 | 0.84 | 100 | 0.2817 | 26.4035 |
| 0.1849 | 1.26 | 150 | 0.2757 | 26.3851 |
| 0.1282 | 1.68 | 200 | 0.2701 | 23.1640 |
| 0.1066 | 2.11 | 250 | 0.2573 | 22.6210 |
| 0.0611 | 2.53 | 300 | 0.2782 | 23.8082 |
| 0.062 | 2.95 | 350 | 0.2611 | 23.0167 |
| 0.033 | 3.37 | 400 | 0.2760 | 23.5321 |
| 0.0315 | 3.79 | 450 | 0.2745 | 25.0874 |
| 0.0194 | 4.21 | 500 | 0.2567 | 20.3111 |
| 0.0119 | 4.63 | 550 | 0.2399 | 24.1119 |
| 0.0085 | 5.05 | 600 | 0.2379 | 22.3541 |
| 0.0026 | 5.47 | 650 | 0.2417 | 21.5995 |
| 0.0025 | 5.89 | 700 | 0.2366 | 22.1701 |
| 0.0009 | 6.32 | 750 | 0.2370 | 24.8297 |
| 0.0006 | 6.74 | 800 | 0.2383 | 24.6733 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0
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