Whisper Base NL
This model is a fine-tuned version of openai/whisper-base on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.343928
- Wer: 19.003155
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: 1e-05
- train_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 7500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Step | Validation Loss | Wer |
|---|---|---|---|
| 0.3639 | 500 | 0.396971 | 24.3028 |
| 0.2625 | 1000 | 0.358340 | 22.5210 |
| 0.2212 | 1500 | 0.341232 | 21.0322 |
| 0.1455 | 2000 | 0.330033 | 20.2046 |
| 0.1406 | 2500 | 0.324484 | 20.0508 |
| 0.1244 | 3000 | 0.321562 | 19.5279 |
| 0.0848 | 3500 | 0.321506 | 19.5114 |
| 0.0844 | 4000 | 0.316492 | 19.1462 |
| 0.0731 | 4500 | 0.321992 | 19.0167 |
| 0.0515 | 5000 | 0.324720 | 19.1492 |
| 0.0532 | 5500 | 0.324773 | 19.0148 |
| 0.0426 | 6000 | 0.332404 | 19.0576 |
| 0.0328 | 6500 | 0.334900 | 18.8249 |
| 0.0327 | 7000 | 0.335876 | 19.0080 |
| 0.0252 | 7500 | 0.343928 | 19.0031 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
openai/whisper-base