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---
language:
- de
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-small
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# openai/whisper-small
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Hanhpt23/GermanMed-full dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6821
- Wer: 26.4630
- Cer: 15.4774
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.5026 | 1.0 | 194 | 0.5290 | 29.2811 | 19.4792 |
| 0.2354 | 2.0 | 388 | 0.5282 | 34.3515 | 22.4451 |
| 0.1144 | 3.0 | 582 | 0.5396 | 32.5825 | 21.4992 |
| 0.073 | 4.0 | 776 | 0.5676 | 32.2226 | 22.5456 |
| 0.0465 | 5.0 | 970 | 0.6049 | 26.3499 | 16.4094 |
| 0.0375 | 6.0 | 1164 | 0.6197 | 33.1791 | 21.1216 |
| 0.0213 | 7.0 | 1358 | 0.6250 | 30.1759 | 20.1462 |
| 0.0229 | 8.0 | 1552 | 0.6453 | 31.4718 | 19.4914 |
| 0.0118 | 9.0 | 1746 | 0.6510 | 23.1924 | 14.5627 |
| 0.0138 | 10.0 | 1940 | 0.6604 | 27.9235 | 17.4974 |
| 0.0081 | 11.0 | 2134 | 0.6546 | 26.3705 | 16.3176 |
| 0.0029 | 12.0 | 2328 | 0.6527 | 25.3625 | 15.1725 |
| 0.0028 | 13.0 | 2522 | 0.6712 | 22.6473 | 14.5384 |
| 0.0003 | 14.0 | 2716 | 0.6743 | 30.7004 | 18.0015 |
| 0.0002 | 15.0 | 2910 | 0.6752 | 27.2035 | 16.0248 |
| 0.0001 | 16.0 | 3104 | 0.6787 | 24.8277 | 15.1292 |
| 0.0001 | 17.0 | 3298 | 0.6803 | 26.6893 | 15.6541 |
| 0.0001 | 18.0 | 3492 | 0.6813 | 26.5864 | 15.6021 |
| 0.0001 | 19.0 | 3686 | 0.6819 | 26.4836 | 15.4964 |
| 0.0001 | 20.0 | 3880 | 0.6821 | 26.4630 | 15.4774 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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