openai/whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the Hanhpt23/GermanMed-full dataset. It achieves the following results on the evaluation set:
- Loss: 0.6710
- Wer: 19.0888
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: 0.0001
- 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: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5095 | 1.0 | 194 | 0.5514 | 29.2194 |
| 0.2795 | 2.0 | 388 | 0.5479 | 27.2138 |
| 0.177 | 3.0 | 582 | 0.5744 | 24.6323 |
| 0.1321 | 4.0 | 776 | 0.6230 | 26.0311 |
| 0.0829 | 5.0 | 970 | 0.6206 | 22.8222 |
| 0.0865 | 6.0 | 1164 | 0.6116 | 22.9456 |
| 0.0681 | 7.0 | 1358 | 0.6316 | 23.9638 |
| 0.0536 | 8.0 | 1552 | 0.6182 | 22.3696 |
| 0.0289 | 9.0 | 1746 | 0.6302 | 21.3309 |
| 0.0228 | 10.0 | 1940 | 0.6738 | 19.5002 |
| 0.0178 | 11.0 | 2134 | 0.6600 | 19.7367 |
| 0.011 | 12.0 | 2328 | 0.6765 | 20.1172 |
| 0.0073 | 13.0 | 2522 | 0.6586 | 21.3823 |
| 0.0042 | 14.0 | 2716 | 0.6455 | 18.9036 |
| 0.004 | 15.0 | 2910 | 0.6595 | 19.0785 |
| 0.0003 | 16.0 | 3104 | 0.6635 | 18.9036 |
| 0.0019 | 17.0 | 3298 | 0.6694 | 19.1093 |
| 0.0001 | 18.0 | 3492 | 0.6747 | 19.0270 |
| 0.0001 | 19.0 | 3686 | 0.6708 | 19.0990 |
| 0.0001 | 20.0 | 3880 | 0.6710 | 19.0888 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1