Whisper Base NL
This model is a fine-tuned version of openai/whisper-base on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3354
- Wer: 20.4818
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.294 | 0.3734 | 1000 | 0.4016 | 24.5123 |
| 0.216 | 0.7468 | 2000 | 0.3617 | 22.3141 |
| 0.1437 | 1.1202 | 3000 | 0.3424 | 21.1733 |
| 0.1299 | 1.4937 | 4000 | 0.3354 | 20.4818 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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