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---
language:
- de
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-medium
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-medium
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Hanhpt23/GermanMed-full dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8743
- Wer: 26.2573
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.7043 | 1.0 | 194 | 0.7433 | 43.3508 |
| 0.4383 | 2.0 | 388 | 0.7578 | 37.6118 |
| 0.28 | 3.0 | 582 | 0.8223 | 39.6380 |
| 0.188 | 4.0 | 776 | 0.8428 | 35.1538 |
| 0.1479 | 5.0 | 970 | 0.8755 | 32.6751 |
| 0.1263 | 6.0 | 1164 | 0.8562 | 31.2249 |
| 0.0808 | 7.0 | 1358 | 0.8797 | 31.5129 |
| 0.063 | 8.0 | 1552 | 0.9294 | 33.3333 |
| 0.0469 | 9.0 | 1746 | 0.9285 | 35.4315 |
| 0.0464 | 10.0 | 1940 | 0.9110 | 29.5176 |
| 0.0302 | 11.0 | 2134 | 0.9158 | 33.4568 |
| 0.0355 | 12.0 | 2328 | 0.9420 | 31.9243 |
| 0.0167 | 13.0 | 2522 | 0.9098 | 30.6284 |
| 0.0119 | 14.0 | 2716 | 0.8894 | 29.7645 |
| 0.0092 | 15.0 | 2910 | 0.8861 | 26.9567 |
| 0.0034 | 16.0 | 3104 | 0.8764 | 26.9670 |
| 0.0007 | 17.0 | 3298 | 0.8692 | 26.2573 |
| 0.0007 | 18.0 | 3492 | 0.8724 | 26.6584 |
| 0.0002 | 19.0 | 3686 | 0.8739 | 26.2265 |
| 0.0002 | 20.0 | 3880 | 0.8743 | 26.2573 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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