Whisper Small nl
This model is a fine-tuned version of openai/whisper-small on the procit009/nl_stt dataset. It achieves the following results on the evaluation set:
- Loss: 0.2637
- Wer: 14.1492
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: 5
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2302 | 1.0 | 125 | 0.2444 | 14.2023 |
| 0.1247 | 2.0 | 250 | 0.2396 | 14.4464 |
| 0.036 | 3.0 | 375 | 0.2448 | 13.9582 |
| 0.0117 | 4.0 | 500 | 0.2549 | 14.0113 |
| 0.0049 | 5.0 | 625 | 0.2604 | 15.5928 |
| 0.0031 | 6.0 | 750 | 0.2637 | 14.1492 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
- Downloads last month
- -
Model tree for procit009/whisper_finetune
Base model
openai/whisper-small