openai/whisper-base
This model is a fine-tuned version of openai/whisper-base on the Hanhpt23/GermanMed dataset. It achieves the following results on the evaluation set:
- Loss: 5.5096
- Wer: 105.0517
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 |
|---|---|---|---|---|
| 3.094 | 1.0 | 765 | 3.6319 | 147.1871 |
| 2.2494 | 2.0 | 1530 | 3.7314 | 101.2055 |
| 1.5508 | 3.0 | 2295 | 3.9256 | 109.4719 |
| 0.9752 | 4.0 | 3060 | 4.2097 | 106.3720 |
| 0.4449 | 5.0 | 3825 | 4.5738 | 103.4443 |
| 0.2699 | 6.0 | 4590 | 4.7393 | 113.6625 |
| 0.2048 | 7.0 | 5355 | 4.9283 | 105.8553 |
| 0.1749 | 8.0 | 6120 | 4.9945 | 110.6200 |
| 0.1707 | 9.0 | 6885 | 5.1057 | 121.0677 |
| 0.1193 | 10.0 | 7650 | 5.1520 | 116.5327 |
| 0.1266 | 11.0 | 8415 | 5.3014 | 107.0608 |
| 0.1156 | 12.0 | 9180 | 5.3254 | 104.9369 |
| 0.1282 | 13.0 | 9945 | 5.3345 | 123.4214 |
| 0.0944 | 14.0 | 10710 | 5.3766 | 129.9656 |
| 0.113 | 15.0 | 11475 | 5.3981 | 109.5293 |
| 0.0986 | 16.0 | 12240 | 5.4435 | 104.5350 |
| 0.0919 | 17.0 | 13005 | 5.4113 | 105.9701 |
| 0.0824 | 18.0 | 13770 | 5.4515 | 102.2962 |
| 0.0974 | 19.0 | 14535 | 5.4659 | 108.0367 |
| 0.0995 | 20.0 | 15300 | 5.5096 | 105.0517 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1