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: 0.3365
- Wer: 20.4123
It achieves the following results on the Test set:
- Eval_Wer: 20.430701270016566
- Eval_NormalizedWer: 17.3945021605222
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: 0.0001
- 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 |
|---|---|---|---|---|
| 1.4113 | 0.84 | 50 | 0.3499 | 29.6797 |
| 0.2435 | 1.68 | 100 | 0.3457 | 29.3392 |
| 0.1657 | 2.53 | 150 | 0.3645 | 28.0692 |
| 0.0981 | 3.37 | 200 | 0.3741 | 28.5478 |
| 0.0651 | 4.21 | 250 | 0.4005 | 29.8454 |
| 0.0471 | 5.05 | 300 | 0.3751 | 28.0968 |
| 0.0291 | 5.89 | 350 | 0.3521 | 25.7869 |
| 0.0178 | 6.74 | 400 | 0.3535 | 24.1303 |
| 0.0099 | 7.58 | 450 | 0.3393 | 23.2468 |
| 0.0053 | 8.42 | 500 | 0.3336 | 23.6702 |
| 0.0031 | 9.26 | 550 | 0.3284 | 21.9676 |
| 0.0018 | 10.11 | 600 | 0.3328 | 22.9615 |
| 0.0008 | 10.95 | 650 | 0.3324 | 20.6976 |
| 0.0003 | 11.79 | 700 | 0.3348 | 20.5227 |
| 0.0003 | 12.63 | 750 | 0.3360 | 20.4215 |
| 0.0002 | 13.47 | 800 | 0.3365 | 20.4123 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0
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