Whisper Small Frisian 1h
This model is a fine-tuned version of openai/whisper-small on the Common Voice 6.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.9900
- Wer: 47.7918
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-06
- train_batch_size: 8
- 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: 50
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.4073 | 1.1236 | 100 | 2.2555 | 82.9549 |
| 1.5143 | 2.2472 | 200 | 1.6651 | 73.4557 |
| 1.1865 | 3.3708 | 300 | 1.4237 | 65.1256 |
| 0.9368 | 4.4944 | 400 | 1.2874 | 59.4832 |
| 0.8009 | 5.6180 | 500 | 1.1957 | 56.5461 |
| 0.6722 | 6.7416 | 600 | 1.1345 | 54.6890 |
| 0.5726 | 7.8652 | 700 | 1.0894 | 53.1919 |
| 0.5068 | 8.9888 | 800 | 1.0575 | 51.7769 |
| 0.4239 | 10.1124 | 900 | 1.0351 | 50.8002 |
| 0.3799 | 11.2360 | 1000 | 1.0197 | 49.9198 |
| 0.295 | 12.3596 | 1100 | 1.0110 | 49.3673 |
| 0.2852 | 13.4831 | 1200 | 1.0022 | 48.7507 |
| 0.2478 | 14.6067 | 1300 | 0.9965 | 48.3800 |
| 0.2267 | 15.7303 | 1400 | 0.9931 | 48.1911 |
| 0.1986 | 16.8539 | 1500 | 0.9916 | 48.1412 |
| 0.1922 | 17.9775 | 1600 | 0.9907 | 47.9558 |
| 0.1724 | 19.1011 | 1700 | 0.9905 | 47.8703 |
| 0.1709 | 20.2247 | 1800 | 0.9900 | 47.9059 |
| 0.1749 | 21.3483 | 1900 | 0.9900 | 47.7598 |
| 0.145 | 22.4719 | 2000 | 0.9900 | 47.7918 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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