Whisper Small german
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3092
- Wer: 12.2134
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
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- 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: 500
- training_steps: 6000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1427 | 1.99 | 1000 | 0.2298 | 12.2134 |
| 0.032 | 3.98 | 2000 | 0.2521 | 12.4540 |
| 0.0066 | 5.96 | 3000 | 0.2766 | 12.3981 |
| 0.0036 | 7.95 | 4000 | 0.2932 | 12.5753 |
| 0.0023 | 9.94 | 5000 | 0.3041 | 12.5719 |
| 0.0019 | 11.93 | 6000 | 0.3092 | 12.6312 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2