Whisper Base Danish - WasuratS
This model is a fine-tuned version of openai/whisper-base on the Common Voice 13 dataset. It achieves the following results on the evaluation set:
- Loss: 0.9795
- Wer Ortho: 45.5986
- Wer: 39.7363
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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 6000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.5156 | 1.61 | 500 | 0.7387 | 47.8293 | 42.2586 |
| 0.2086 | 3.22 | 1000 | 0.7157 | 46.7087 | 41.0652 |
| 0.1439 | 4.82 | 1500 | 0.7300 | 46.5367 | 40.9610 |
| 0.0514 | 6.43 | 2000 | 0.7804 | 45.2963 | 39.5279 |
| 0.027 | 8.04 | 2500 | 0.8314 | 46.3126 | 40.3825 |
| 0.0133 | 9.65 | 3000 | 0.8739 | 44.8585 | 39.2777 |
| 0.0053 | 11.25 | 3500 | 0.9081 | 45.4839 | 39.7103 |
| 0.0041 | 12.86 | 4000 | 0.9347 | 45.4110 | 39.7050 |
| 0.0028 | 14.47 | 4500 | 0.9535 | 46.0624 | 40.3096 |
| 0.0024 | 16.08 | 5000 | 0.9673 | 45.6351 | 39.8979 |
| 0.0021 | 17.68 | 5500 | 0.9762 | 45.7862 | 39.9187 |
| 0.002 | 19.29 | 6000 | 0.9795 | 45.5986 | 39.7363 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
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