openai/whisper-small
This model is a fine-tuned version of openai/whisper-small on the Hanhpt23/GermanMed-full dataset. It achieves the following results on the evaluation set:
- Loss: 0.5327
- Wer: 22.8736
- Cer: 15.0096
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 | Cer |
|---|---|---|---|---|---|
| 0.4351 | 1.0 | 194 | 0.4422 | 66.5535 | 48.8609 |
| 0.2391 | 2.0 | 388 | 0.4250 | 54.4071 | 37.4409 |
| 0.1426 | 3.0 | 582 | 0.4290 | 56.2172 | 35.4555 |
| 0.0877 | 4.0 | 776 | 0.4469 | 55.1682 | 35.9389 |
| 0.0456 | 5.0 | 970 | 0.4723 | 29.5691 | 19.8569 |
| 0.0374 | 6.0 | 1164 | 0.4664 | 34.9275 | 22.5023 |
| 0.015 | 7.0 | 1358 | 0.4901 | 24.7249 | 16.3800 |
| 0.0179 | 8.0 | 1552 | 0.4805 | 29.3325 | 19.8240 |
| 0.0112 | 9.0 | 1746 | 0.4858 | 25.3317 | 16.7420 |
| 0.0064 | 10.0 | 1940 | 0.4905 | 25.7534 | 16.3488 |
| 0.0037 | 11.0 | 2134 | 0.5068 | 26.1648 | 16.7871 |
| 0.0027 | 12.0 | 2328 | 0.5067 | 23.2747 | 15.2504 |
| 0.0013 | 13.0 | 2522 | 0.5167 | 25.7842 | 16.4181 |
| 0.0009 | 14.0 | 2716 | 0.5195 | 23.0690 | 15.1586 |
| 0.0008 | 15.0 | 2910 | 0.5206 | 23.1719 | 15.2106 |
| 0.0007 | 16.0 | 3104 | 0.5260 | 23.0382 | 14.9230 |
| 0.0007 | 17.0 | 3298 | 0.5288 | 23.1719 | 15.1118 |
| 0.0006 | 18.0 | 3492 | 0.5310 | 23.1821 | 15.1465 |
| 0.0006 | 19.0 | 3686 | 0.5323 | 22.8633 | 15.0079 |
| 0.0006 | 20.0 | 3880 | 0.5327 | 22.8736 | 15.0096 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1